Reconsideration of the QCD corrections to the ηc\eta_c decays into light hadrons using the principle of maximum conformality

In the paper, we analyze the $\eta_c$ decays into light hadrons at the next-to-leading order QCD corrections by applying the principle of maximum conformality (PMC). The relativistic correction at the ${\cal{O}}(\alpha_s v^2)$-order level has been included in the discussion, which gives about $10\%$ contribution to the ratio $R$. The PMC, which satisfies the renormalization group invariance, is designed to obtain a scale-fixed and scheme-independent prediction at any fixed order. To avoid the confusion of treating $n_f$-terms, we transform the usual $\overline{\rm MS}$ pQCD series into the one under the minimal momentum space subtraction scheme. To compare with the prediction under conventional scale setting, $R_{\rm{Conv,mMOM}-r}= \left(4.12^{+0.30}_{-0.28}\right)\times10^3$, after applying the PMC, we obtain $R_{\rm PMC,mMOM-r}=\left(6.09^{+0.62}_{-0.55}\right) \times10^3$, where the errors are squared averages of the ones caused by $m_c$ and $\Lambda_{\rm mMOM}$. The PMC prediction agrees with the recent PDG value within errors, i.e. $R^{\rm exp}=\left(6.3\pm0.5\right)\times10^3$. Thus we think the mismatching of the prediction under conventional scale-setting with the data is due to improper choice of scale, which however can be solved by using the PMC.Comment: 5 pages, 2 figure

Robust Outdoor Vehicle Visual Tracking Based on k-Sparse Stacked Denoising Auto-Encoder

Robust visual tracking for outdoor vehicle is still a challenging problem due to large object appearance variations caused by illumination variation, occlusion, and fast motion. In this chapter, k-sparse constraint is added to the encoder part of stacked auto-encoder network to learn more invariant feature of object appearance, and a stacked k-sparse-auto-encoder–based robust outdoor vehicle tracking method under particle filter inference is further proposed to solve the problem of appearance variance during the tracking. Firstly, a stacked denoising auto-encoder is pre-trained to learn the generic feature representation. Then, a k-sparse constraint is added to the stacked denoising auto-encoder, and the encoder of k-sparse stacked denoising auto-encoder is connected with a classification layer to construct a classification neural network. Finally, confidence of each particle is computed by the classification neural network and is used for online tracking under particle filter framework. Comprehensive tracking experiments are conducted on a challenging single-object tracking benchmark. Experimental results show that our tracker outperforms most state-of-the-art trackers

2-Phenyl­imidazolium hemi(benzene-1,3-dicarboxyl­ate) monohydrate

The asymmetric unit of the title compound, C9H9N2 +·0.5C8H4O4 −·H2O, contains one 2-phenyl­imidazolium cation, half a benzene-1,3-dicarboxyl­ate anion and one water mol­ecule. In the crystal, components are connected by N—H⋯O and O—H⋯O hydrogen-bonding inter­actions into a three-dimensional network

Direct fiber vector eigenmode multiplexing transmission seeded by integrated optical vortex emitters

Spatial modes have received substantial attention over the last decades and are used in optical communication applications. In fiber-optic communications, the employed linearly polarized modes and phase vortex modes carrying orbital angular momentum can be synthesized by fiber vector eigenmodes. To improve the transmission capacity and miniaturize the communication system, straightforward fiber vector eigenmode multiplexing and generation of fiber-eigenmode-like polarization vortices (vector vortex modes) using photonic integrated devices are of substantial interest. Here, we propose and demonstrate direct fiber vector eigenmode multiplexing transmission seeded by integrated optical vortex emitters. By exploiting vector vortex modes (radially and azimuthally polarized beams) generated from silicon microring resonators etched with angular gratings, we report data-carrying fiber vector eigenmode multiplexing transmission through a 2-km large-core fiber, showing low-level mode crosstalk and favorable link performance. These demonstrations may open up added capacity scaling opportunities by directly accessing multiple vector eigenmodes in the fiber and provide compact solutions to replace bulky diffractive optical elements for generating various optical vector beams

Automated Stroke Rehabilitation Assessment using Wearable Accelerometers in Free-Living Environments

Stroke is known as a major global health problem, and for stroke survivors it is key to monitor the recovery levels. However, traditional stroke rehabilitation assessment methods (such as the popular clinical assessment) can be subjective and expensive, and it is also less convenient for patients to visit clinics in a high frequency. To address this issue, in this work based on wearable sensing and machine learning techniques, we developed an automated system that can predict the assessment score in an objective and continues manner. With wrist-worn sensors, accelerometer data was collected from 59 stroke survivors in free-living environments for a duration of 8 weeks, and we aim to map the week-wise accelerometer data (3 days per week) to the assessment score by developing signal processing and predictive model pipeline. To achieve this, we proposed two new features, which can encode the rehabilitation information from both paralysed/non-paralysed sides while suppressing the high-level noises such as irrelevant daily activities. We further developed the longitudinal mixed-effects model with Gaussian process prior (LMGP), which can model the random effects caused by different subjects and time slots (during the 8 weeks). Comprehensive experiments were conducted to evaluate our system on both acute and chronic patients, and the results suggested its effectiveness.Comment: submitted to ACM Trans. Computing for Healthcar

Double-charm and hidden-charm hexaquark states under the complex scaling method

We investigate the double-charm and hidden-charm hexaquarks as molecules in the framework of the one-boson-exchange potential model. The multichannel coupling and $S-D$ wave mixing are taken into account carefully. We adopt the complex scaling method to investigate the possible quasibound states, whose widths are from the three-body decay channel $\Lambda_c\Lambda_c\pi$ or $\Lambda_c\bar{\Lambda}_c\pi$. For the double-charm system of $I(J^P)=1(1^+)$, we obtain a quasibound state, whose width is 0.50 MeV if the binding energy is -14.27 MeV. And the $S$-wave $\Lambda_c\Sigma_c$ and $\Lambda_c\Sigma_c^*$ components give the dominant contributions. For the $1(0^+)$ double-charm hexaquark system, we do not find any pole. We find more poles in the hidden-charm hexaquark system. We obtain one pole as a quasibound state in the $I^G(J^{PC})=1^+(0^{--})$ system, which only has one channel $(\Lambda_c\bar{\Sigma}_c+\Sigma_c\bar{\Lambda}_c)/\sqrt{2}$. Its width is 1.72 MeV with a binding energy of -5.37 MeV. But, we do not find any pole for the scalar $1^-(0^{-+})$ system. For the vector $1^-(1^{-+})$ system, we find a quasibound state. Its energies, widths and constituents are very similar to those of the $1(1^+)$ double-charm case. In the vector $1^+(1^{--})$ system, we get two poles -- a quasibound state and a resonance. The quasibound state has a width of 0.6 MeV with a binding energy of -15.37 MeV. For the resonance, its width is 2.72 MeV with an energy of 63.55 MeV relative to the $\Lambda_c\bar{\Sigma}_c$ threshold. And its partial width from the two-body decay channel $(\Lambda_c\bar{\Sigma}_c-\Sigma_c\bar{\Lambda}_c)/\sqrt{2}$ is apparently larger than the partial width from the three-body decay channel $\Lambda_c\bar{\Lambda}_c\pi$

Re-evaluating serum angiotensin-converting enzyme in sarcoidosis

Sarcoidosis is a systemic inflammatory disease of unknown etiology, which mainly affects the lungs and lymph nodes, as well as extrapulmonary organs. Its incidence, and prevalence rate, and disease course largely vary with regions and populations globally. The clinical manifestations of sarcoidosis depend on the affected organs and the degree of severity, and the diagnosis is mainly based on serum biomarkers, radiographic, magnetic resonance, or positron emission tomography imaging, and pathological biopsy. Noncaseating granulomas composing T cells, macrophages, epithelioid cells, and giant cells, were observed in a pathological biopsy, which was the characteristic pathological manifestation of sarcoidosis. Angiotensin-converting enzyme (ACE) was first found in the renin–angiotensin–aldosterone system. Its main function is to convert angiotensin I (Ang I) into Ang II, which plays an important role in regulating blood pressure. Also, an ACE insertion/deletion polymorphism exists in the human genome, which is involved in the occurrence and development of many diseases, including hypertension, heart failure, and sarcoidosis. The serum ACE level, most commonly used as a biomarker in diagnosing sarcoidosis, in patients with sarcoidosis increases. because of epithelioid cells and giant cells of sarcoid granuloma expressing ACE. Thus, it serves as the most commonly used biomarker in the diagnosis of sarcoidosis and also aids in analyzing its therapeutic effect and prognosis in patients with sarcoidosis