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The past few years have witnessed a surge of interest towards deep reinforcement learning (DRL) in computer networks. With extraordinary ability of feature extraction, DRL has the potential to re-engineer the fundamental resource allocation problems in networking without relying on pre-programmed models or assumptions about dynamic environments. However, such black-box systems suffer from poor robustness, showing high performance variance and poor tail performance. In this work, we propose a unified Teacher-Student learning framework that harnesses rich domain knowledge to improve robustness. The domain-specific algorithms, less performant but more trustable than DRL, play the role of teachers providing advice at critical states; the student neural network is steered to maximize the expected reward as usual and mimic the teacher’s advice meanwhile. The Teacher-Student method comprises of three modules where the confidence check module locates wrong decisions and risky decisions, the reward shaping module designs a new updating function to stimulate the learning of student network, and the prioritized experience replay module to effectively utilize the advised actions. We further implement our Teacher-Student framework in existing video streaming (Pensieve), load balancing (DeepLB), and TCP congestion control (Aurora). Experimental results manifest that the proposed approach reduces the performance standard deviation of DeepLB by 37%; it improves the 90th, 95th, and 99th tail performance of Pensieve by 7.6%, 8.8%, and 10.7% respectively; and it accelerates the growth rate of Aurora by 2x at the initial stage, and achieves a more stable performance in dynamic environments.

The blind modulation recognition (BMR) of high-order modulation types is a pressing task and needs to be raised in the calendar for the Beyond 5G (B5G) OSTBC-OFDM (Orthogonal Space-Time Block Coded-Orthogonal Frequency Division Multiplexing) system. In this letter, a BMR algorithm based on a project constellation vector which employs a temporal convolutional network (PCV-TCNet) is proposed to recognize 13 modulation formats, such as high-order 1024QAM and 2048QAM. Without any prior information, a zero-forcing blind equalization algorithm is leveraged to reconstruct the impaired signal. Furthermore, the learning content of PCV-TCNet is PCV features, which are transformed by the constellation diagram of the reconstructed signal. In addition, PCV-TCNet utilizes causal and dilated convolutions to accelerate the BMR process. The simulation results verify the proposed PCV-TCNet for recognizing the high-order modulation types in the B5G OSTBC-OFDM system and demonstrate its preferable recognition performance with the lowest complexity to existing methods.

Atmospheric plasma discharges are finding increased applications in addressing environmental challenges including water purification, chemical synthesis and biotechnology. An effective means of interfacing the reactivity of plasma gas discharges with liquids is needed to enhance liquid phase chemical reactions. Plasma discharges in bubbles has been considered as an innovative solution for achieving this goal potentially offering electrically driven, sustainable chemistry with low energy consumption and the unique benefit of maintaining a large volume discharge under the liquid surface. Here we provide a concise review on the state-of-art for research on plasma-bubble interactions and a perspective for future research.

In terms of the traditional dynamic vibration absorber (DVA), the vibration damping effect improves with the mass ratio of DVA increasing, and the vibration level of target system is effectively controlled in the case that the mass ratio of DVA is large. This characteristic restricts the application of DVA to the track because of the limited available space. This study proposes one type of DVA with negative stiffness (NSDVA) applied to floating slab track to reduce the track vibration under the condition of small mass ratio and presents a design methodology of NSDVA attached on flexible system. Firstly, the mechanical model of floating slab with NSDVA is simplified to a two-degree-of-freedom system, and theoretical expressions of NSDVA’s optimal parameters, i.e., ratio of frequency, damping and stiffness are deduced according to the fixed-point expansion theory and stability condition. Secondly, with the combination of the multi-modal control theory and the finite element method, optimal parameters of NSDVA applied to a multi-degree of freedom (MDOF) system are calculated. 3-D finite element model of floating slab-NSDVA is built in ABAQUS software, and the modal analysis of floating slab is conducted to determine the target modal and equivalent mass. Compared with the traditional Voigt type DVA, the NSDVA adopted in this paper is proved to be more effective to reduce the both floating slab and rail vibration level. The design methodology of NSDVA attached to a MDOF system presented in this paper is feasible.

The aim of this study was to compare the safety and efficacy of radiofrequency ablation (RFA) with microwave ablation (MWA) for hepatocellular carcinoma (HCC) within the Milan criteria in challenging locations. This study retrospectively investigated 201 consecutive patients with Milan criteria HCCs who underwent RFA (RFA group, n = 150) or MWA (MWA group, n = 51) between January 2012 and December 2016. Overall survival (OS), recurrence-free survival (RFS), local tumor control, and treatment-related complications were compared between the two groups. Prognostic factors were analyzed using the Cox proportional hazard regression model. Median follow-up duration was 36.7 months (range: 6.2–64.0 months). Cumulative 1-, 3-, and 5-year OS rates were 97.9%, 92.3%, and 80.6% in the MWA group and 96.4%, 87.4%, and 78.2% in the RFA group, respectively, (P = 0.450). Cumulative RFS rates at 1, 3, and 5 years were 93.2%, 74.4%, and 63.7% in the MWA group and 80.3%, 57.3%, and 49.6% in the RFA group, respectively, (P = 0.097). Multivariate analyses showed that variable categories “patient age above 65 years” (P = 0.004) and “more than one tumor” (P = 0.004) were associated with overall mortality, and “patient age above 65 years” (P = 0.048) and “tumor size greater than 3 cm” (P = 0.009) were associated with inferior RFS. The incidences of major complications were not significantly different between the two groups (3.3% vs 3.9%, P = 0.843). RFA and MWA were associated with comparable safety and efficacy for HCC within the Milan criteria in challenging locations. Further study in a large, multi-center patient cohort is necessary to validate the results.

Objective Alveolar repair has become a routine part of treatment protocols for patients with non-syndromic cleft lip and/or palate, but there is no clear conclusion of whether the presurgical orthodontic treatment is necessary to alveolar bone grafting or not. The purpose was to determine the necessity of the presurgical orthodontics in cleft lip and palate patients. Materials and Methods Electronic databases including PubMed, Ovid, Embase, Cochrane Library, Web of Knowledge, and China Biology Medicine disc (SinoMed) were searched. Only studies published in English or Chinese were included. The last search was updated on 1 May 2020. 1225 articles remaining after the exclusion of duplicates. Finally, there were 11 publications (five in English and six in Chinese) eligible for systematic review according to the previously established inclusion and exclusion criteria. A descriptive statistical method was used to present data. The methodological index for non-randomized studies (MINORS) was used to determine the risk of bias. Result Eleven articles were included in this review, of which seven publications were retrospective study and four articles were comparative study. The average success rate of reconstruction with the presurgical orthodontic treatment was approximately 70% to 97%, while the success rate of the non-presurgical orthodontics was 25% to 80%. The fixed and removable presurgical orthodontic methods were frequently performed, rather than a single treatment model. The incidence of the postoperative complications resulting from whether adopting the presurgical orthodontics was different from none to 75%. Conclusion There are a higher postoperative bone formation rate and a lower complication rate after ABG with presurgical orthodontics. However, more studies with high methodological quality and with a longer follow-up are needed to offer more safety for practitioners and patients regarding the surgical method selected to repair the cleft alveolar.

This paper presents a new methodology for designing a broadband three-way Doherty power amplifier (DPA), which utilizes a reactance compensation generated by parallel peaking amplifiers to extend the bandwidth and improve the back-off efficiency. By analyzing the load impedance and efficiency of the reactance-compensated DPA, the optimal reactance at the output of the peaking amplifier required for bandwidth extension can be obtained. Then, a structure using two parallel peaking amplifiers is proposed to reduce the output reactance for the desired distribution. Using a $\lambda _{0}$ /4 transmission line, a sufficiently large output reactance of the peaking branch can be realized at the combining point over a wider frequency band, which can compensate the effective load impedance of the carrier amplifier and improve its efficiency and bandwidth. A wideband three-way DPA is designed and fabricated to verify the proposed method. Measurement results indicate that an efficiency of 50–53% at 10 dB output power back-off and a saturated efficiency of 54–68% can be achieved over the frequency range from 1.6 to 2.7 GHz.

Hydrogen peroxide (H2O2) is a green oxidant widely used in various fields, from water treatment to rocket propellant. Currently, H2O2 is predominantly manufactured via the anthraquinone process, which requires large infrastructure investments and high energy consumption. In this study, an argon plasma-catalytic bubble process was designed to generate underwater plasma bubbles for efficient delivery of reactive species for H2O2 synthesis, using only water as a reactant and solar radiation as the renewable energy source. The process demonstrates unprecedented energy efficiency by employing a plasma-bubble catalytic reactor capable of operation in two discharge modes, i.e., glow and spark discharges, and using dual reactors within a single AC-circuit to mitigate energy losses around the ground electrode. The results suggest that the principal route of H2O2 generation is from the combination of dissolved ˙OH radicals at the plasma–liquid interface (PLI) of the forming bubbles. The dissolution of H2O2 formed in the gas phase also contributes to aqueous H2O2 generation, especially when employing humid argon. By employing a secondary reactor to utilise the lost energy around the low-voltage electrode and integrating a strongly interfacial-coupled 2D-TiO2/2D-g-C3N4 photocatalyst in the glow discharge area, the achieved H2O2 production rate and energy efficiency of the system are 164.6 mg h−1 and 9.0 g kW h−1, respectively. This study provides new insights for sustainable and decentralised H2O2 production, and the proposed strategy can be further developed as a stand-alone or auxiliary technology in green and sustainable chemistry.

Background Career intention is closely related to the distribution of university graduates across sectors in pharmacy-related field. The aim of the study was to describe career intention and identify its influencing factors among final-year pharmacy undergraduate students in China. Methods A questionnaire study on demographic characteristics, educational situation, family background, occupational value and career intention was conducted among final-year pharmacy undergraduate students at three universities in northwest China. Exploratory factor analysis was used to identify the constructs of occupational value. Multinominal logistic regression was adopted to analyse the factors influencing career intention. Results Among the 275 student participants, 62.6% intended to work in public medical institutions (rural: 44.4%; urban: 18.2%), 26.5% aimed to work in the pharmaceutical industry, 6.5% wanted to work in other sectors in the pharmacy-related field, and 4.4% planned to work in other fields. Their gender, father’s education level, monthly household income per capita, whose opinions were considered most during job selection, the self-gratification factor of occupational value, and employment guidance had significant impacts on students’ career intentions. Conclusion In the Chinese background, the career intention of more than half of the undergraduate pharmacy students was to work in public medical institutions. The career intentions of the overall participants were mainly determined by their gender, family background as well as psychological self-gratification, and they could also be influenced by employment guidance.

It is known that surface waves have significant influence on the hydrodynamic performance of ocean current turbines which locate near the water surface. In order to quantitatively analyze the wave influence and reveal the interaction mechanism between the wave and the turbine flow, this paper proposes a three-dimensional transient computational fluid dynamics (CFD) model which can accurately predict the hydrodynamic performance of ocean current turbines under current-wave interaction flow conditions. The influences of two key wave parameters, the wave height and the submerged depth of the turbine, on the hydrodynamic forces and flow structures of a three-bladed horizontal axis ocean current turbine are discussed in depth. It is found that the both the average value and the oscillation amplitude of the torque on the turbine increase with the increased wave height, but decrease with the increase of the submerged depth. It is also found that in the cases of shallow submerged depth, the wake structures of the turbine are affected by the surface wave.

Objectives To develop a clinicopathological‐based nomogram to improve the prediction of the seeding risk of after percutaneous thermal ablation (PTA) in primary liver carcinoma (PLC). Methods A total of 2030 patients with PLC who underwent PTA were included between April 2009 and December 2018. The patients were grouped into a training dataset (n = 1024) and an external validation dataset (n = 1006). Baseline characteristics were collected to identify the risk factors of seeding after PTA. The multivariate Cox proportional hazards model based on the risk factors was used to develop the nomogram, which was used for assessment for its predictive accuracy using mainly the Harrell's C‐index and receiver operating characteristic curve (AUC). Results The median follow‐up time was 30.3 months (range, 3.2‐115.7 months). The seeding risk was 0.89% per tumor and 1.5% per patient in the training set. The nomogram was developed based on tumor size, subcapsular, α‐fetoprotein (AFP), and international normalized ratio (INR). The 1‐, 2‐, and 3‐year cumulative seeding rates were 0.1%, 0.7% and 1.2% in the low‐risk group, and 1.7%, 6.3% and 6.3% in the high‐risk group, respectively, showing significant statistical difference (P, Seeding on the thoracoabdominal wall from primary liver carcinoma is a potential complication after percutaneous thermal ablation. Seeding risk is a liver ablation complication that affects future oncology management. A calibrated and objective model to predict seeding risk after liver ablation may guide patient selection and ablation treatment.

Single shot multibox detector (SSD) takes several feature layers for object detection, but each layer is used independently. This structure may ignore some context information and is not conducive to improving the detection accuracy of small objects. Moreover, the imbalances of samples and multi-tasks during SSD training process can lead to inefficient training and model degradation. In order to improve the performance of SSD, this paper proposes a balanced feature fusion SSD (BFSSD) algorithm. Firstly, a feature fusion module is proposed to fuse and refine different layers of the feature pyramid. Then, a more balanced L1 loss function is proposed to further solve these imbalances. Finally, our model is trained with Pascal VOC2007 and VOC2012 trainval datasets and tested on Pascal VOC2007 test datasets. Simulation results show that, for the input size of 300 × 300, BFSSD exceeds the best results provided by the conventional SSD and other advanced object detection algorithms.

Zhimei Huang,1 Mengxuan Zuo,1 Jiayan Ni,1 Yangkui Gu,1 Tianqi Zhang,1 Yiquan Jiang,1 Shuiqing Zhuo,2 Chao An,1 Jinhua Huang1 1Department of Minimal Invasive Intervention, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China; 2Department of Radiology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of ChinaCorrespondence: Jinhua Huang; Chao AnDepartment of Minimal Invasive Intervention, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, 651, Dongfeng East Road, Guangzhou 510060, People’s Republic of ChinaTel/Fax +86-20-87343447Email huangjh@sysucc.org.cn; anchao@sysucc.org.cnObjective: Based on the albumin-bilirubin (ALBI) and platelet-albumin-bilirubin (PALBI) grade to assess the long-term outcomes of patients with large hepatocellular carcinoma (HCC) after transarterial chemoembolization combined with cryoablation (TACE-CRA).Materials and Methods: We studied 86 patients with HCC nodules (up to 3 HCCs with maximum diameters of 4.1– 12.0 cm) who subsequently underwent TACE-CRA from July 2007 to August 2018. The overall survival (OS) was compared between groups classified by ALBI and PALBI grade. Baseline characteristics were collected to identify the risk factors for determination of poor OS after TACE-CRA. The prognostic performances of CTP class, ALBI and PALBI grade were compared.Results: After a median follow-up time of 33.8 months, 41 patients had died. The cumulative1-, 3- and 5-year OS rates were 74.5%, 38.0% and 29.3%, respectively. Stratified according to ALBI grade, the cumulative 3- and 5-year OS rates were 41.2% and 41.2% in grade 1, respectively, and 20.9% and 9.8% in grades 2– 3, respectively (P < 0.001). Stratified according to PALBI grade, the cumulative 3- and 5-year OS rates were 41.2% and 37.5% in grade 1, respectively, and 36.3% and 21.2% in grades 2– 3, respectively (P = 0.002). Multivariate analysis results showed that older age, and ALBI grade 2– 3 were associated with overall mortality. ALBI grade demonstrated significantly greater area under the curve values than CTP class and PALBI in predicting 1-, 3- and 5-year OS.Conclusion: ALBI grade offers accurate prediction of long-term outcome for patients with HCC (diameter > 4 cm) after TACE-CRA.Keywords: hepatocellular carcinoma, transarterial chemoembolization, cryoablation, albumin-bilirubin, platelet-albumin-bilirubin

Objective To assess the clinical efficacy and safety of computed tomography-guided radiofrequency ablation(CT-RFA) combined with transarterial embolization(TAE) assisted by a three-dimensional visualization ablation planning system(3DVAPS) for hepatocellular carcinoma(HCC) in challenging locations. Methods Data from 62 treatment-naive patients with hepatocellular carcinoma(HCC), with 83 lesions in challenging locations, and who met the Milan criteria and underwent CT-RFA between June 2013 and June 2016 were reviewed. Patients were divided into one of two groups according to different treatment modalities: study group (TAE combined with RFA assisted by 3DVAPS [n = 32]); and control (RFA only [n = 30]). Oncological outcomes included ablation-related complications, local tumor progression (LTP), and overall survival (OS). Univariate and multivariate Cox proportional hazards regression analyses were performed to assess risk factors associated with LTP and OS. Results HCC lesions (mean size, 1.9 ± 1.0 mm in diameter) abutting the gastrointestinal tract (n = 25), heart and diaphragm (n = 21), major vessels (n = 13), and gallbladder (n = 3) were treated. A significant difference was detected in LTP between the two groups (P = 0.034), with no significant difference in OS between the two groups (P = 0.193). There were no severe complications related to ablation. Univariate analysis revealed that sex (P = 0.046) and child-turcotte-pugh (CTP) grade (PPP = 0.005) was independently associated with poor OS, and RFA alone (P Conclusion CT-RFA combined with TAE assisted by a 3DVAPS provided ideal clinical efficiency for HCC in challenging locations and was a highly safe treatment modality.

Rapid growth in demand for spectrum resources and technology expansion in wireless communication systems such as satellite communication networks and upcoming 5G networks has led us to investigate the best cognitive radio network scheme towards achievements of energy efficiency in wireless communication networks for cooperative spectrum sensing. In this paper, we introduce a double-deck cluster cooperative relay assistance model in hybrid spectrum sharing for cognitive radio networks. This proposed model enables the attainment of energy efficiency by optimizing cooperative secondary users in their respective cluster groups. According to the design of this model, we apply the power allocation scheme under mathematical analysis based on its power constraints. Normalized energy consumptions and amplifying gains are achieved and assessed for both network scenarios when cognitive relays are used and not used in the network. Simulation results show that there is a good performance on the energy efficiency of our proposed scheme compared to a traditional scheme.

Objectives To develop and validate the nomograms to predict survival outcomes after microwave ablation (MWA) in elderly patients(>65 years old) with early-stage hepatocellular carcinoma (EHCC). Methods This retrospective study was approved by the institutional review board. A total of 265 EHCC patients (76 females, 189 males; average age 71.4 years ± 5.4 [standard deviation]) with 345 nodules subsequently underwent MWA from April 2006 to October 2019. Baseline characteristics were collected to identify the risk factors for the determination of survival outcomes after MWA. The nomograms were based on prognostic factors for overall survival (OS) and recurrence-free survival (RFS) from the multivariate Cox proportional hazards model and validated in external cohorts from another two institutions (n = 130). The nomograms were assessed for their predictive accuracy using Harrell’s concordance index (C-index). Results After a median follow-up time of 28.6 months, 29.8% (79/265) of the patients died, and 54.3% (144/265) of the patients experienced recurrence in the training set. The OS nomogram was developed based on the hepatitis B virus (HBV) presence, α-fetoprotein (AFP), and albumin, with a C-index of 0.757 (95% confidence interval [CI]: 0.645, 0.789).The scores of the nomogram ranged from 0 to 24. The RFS nomogram was developed based on tumor number, abutting major vessels and platelets, with a C-index of 0.733 (CI: 0.672, 0.774). The likelihood of 3- and 5-year OS and RFS were consistent between clinical observations and nomogram predictions in external cohorts. Conclusions The nomogram models can be useful in determining the risk of OS and RFS in elderly patients with EHCC after MWA, which can guide individual patient management.Key points MWA is an effective and feasible treatment for elderly patients with EHCC and can improve survival outcomes. A calibrated and objective nomogram model for the prediction of survival outcomes in elderly patients (>65 years old) may guide patient selection and MWA treatment. Older age was not deemed to be a risk factor for survival outcomes when the elderly patients with EHCC underwent MWA.

Broadband and ultrafast response of plasmonic nanoparticles offer a significant advantage in optical modulation and allow ultrashort pulse generation from visible to mid‐infrared (MIR) region. However, many of the materials exhibit limited saturable absorption bandwidth in MIR spectral region, which limits the MIR pulses generation and the relative applications. Herein, it is shown that solution‐processed silver nanowires (AgNWs) exhibit an ultrabroadband localized surface plasmon resonance (LSPR) from 0.3 to over 25 μm, which contributes to wideband nonlinear optical response in the whole MIR region. Using those AgNWs as saturable absorbers (SA), all‐optical modulation in near infrared and MIR region is demonstrated. Mode‐locked lasers are realized at 1, 1.5, and 2 μm bands with minimal pulse duration down to a few hundreds of femtoseconds, and a Q‐switched laser at 3 μm band is achieved. The results show that AgNWs SA has the potential for constructing pulsed lasers in the MIR or even longer wavelength region.

Despite the fact that chemotherapy has been widely used in the clinical treatment of breast cancer, the toxicity of chemotherapeutics to normal tissues cannot be ignored due to the low specificity. Therefore, due to the non-negligible toxicity of chemotherapeutic agents to normal tissues, tumor microenvironment (TME)-responsive cancer therapy has attracted a great deal of attention. Here, we report a TME-responsive theranostic nanoagent MnOx@PAA@HKUST-1-DSF@BSA fabricated via a layer-by-layer synthesis method. Once endocytosed by tumor cells, the nanoagent can be degraded into Mn2+ for magnetic resonance imaging and Cu2+ for Fenton-like reaction and chelating with released disulfiram in situ, achieving enhanced chemotherapy. Both in vitro and in vivo experiments demonstrate that the TME-targeted nanoagent can efficiently kill tumor cells. This work provides an alternative option for effective imaging and treatment of breast cancer without collateral damage to normal tissues.

Tenofovir alafenamide (TAF) is a novel prodrug of tenofovir (TFV) that has been approved for the treatment of chronic hepatitis B virus (HBV) infection. It has greater plasma stability and more favorable renal safety than tenofovir disoproxil fumarate (TDF), the first approved oral prodrug of TFV. However, the distribution of TFV in the breast milk of mothers treated with TAF is still unclear. In this study, sixteen participants with chronic HBV infection were enrolled and received antiretroviral therapy with 25 mg of TAF or 300 mg of TDF daily from 24 to 28 weeks of gestation until the 4th week postpartum. For the first time, the distribution of TFV in the breast milk of mothers with chronic HBV infection treated with TAF and its difference from TDF were evaluated by using a sensitive UPLC–MS/MS method. Chromatographic separation was achieved on a Waters ACQUITY UPLC BEH C18 column (1.7 µm 2.1 × 100 mm). Mass spectrometry analysis was performed in positive electrospray ionization mode and multiple reaction monitoring (MRM) conditions of transitions m/z 288.1→176.2 for TFV. This method was linear from 0.5 to 500 ng/ml. Surprisingly, on the third postpartum day, the median Cmax of TFV in the breast milk was much higher in the mothers treated with TAF (101.2 ng/ml) than TDF (21.6 ng/ml) at a similar Tmax of 4 h. Accordingly, the median AUC0-8 value was 755.6 ng h/mL in the mothers taking TAF, which was at a 5-fold higher level than TDF. The concentration of TFV in the breast milk of mothers in both groups decreased with increasing lactation time. These data indicated that there was a relatively higher exposure of TFV in the breast milk of mothers taking TAF, despite the lower dosage compared to TDF. This study provides support for further evaluating the safety of breastfeeding after the administration of TAF and TDF.

Speech is easily interfered by the external environment in reality, which will lose the important features. Deep learning method has become the mainstream method of speech enhancement because of its superior potential in complex nonlinear mapping problems. However, there are some problems are exist such as the deficiency for the learning the important information from previous time steps and long-term event dependencies. Due to the lack of the correlation in the same layer of Deep Neural Networks (DNNs), which is an existing typical intelligent deep model of speech signal, it is difficult to capture the long-term dependence between the time-series data. To overcome this problem, we propose a novel speech enhancement method from fused features based on deep neural network and gated recurrent unit network. The method takes advantage of both deep neural network and recurrent neural network to reduce the number of parameters and simultaneously improve speech quality and intelligibility. Firstly, DNN with multiple hidden layers is used to learn the mapping relationship between the logarithmic power spectrum (LPS) features of noisy speech and clean speech. Secondly, the LPS feature of the deep neural network is fused with the noisy speech as the input of gated recurrent unit (GRU) network to compensate the missing context information. Finally, GRU network is performed to learn the mapping relationship between LPS features and log power spectrum features of clean speech spectrum. Experimental results demonstrate that the PESQ, SSNR and STOI of the proposed algorithm are improved by 30.72%, 39.84% and 5.53% respectively compared with the noise signal under the condition of matched noise. Under the condition of unmatched noise, the PESQ and STOI of the algorithm are improved by 23.8% and 37.36% respectively. The advantage of the proposed method is that it uses of the key information of features to suppress noise in both matched and unmatched noise cases and the proposed method outperforms other common methods in speech enhancement.

Graph Edit Distance (GED) is a popular similarity measurement for pairwise graphs and it also refers to the recovery of the edit path from the source graph to the target graph. Traditional A* algorithm suffers scalability issues due to its exhaustive nature, whose search heuristics heavily rely on human prior knowledge. This paper presents a hybrid approach by combing the interpretability of traditional search-based techniques for producing the edit path, as well as the efficiency and adaptivity of deep embedding models to achieve a cost-effective GED solver. Inspired by dynamic programming, node-level embedding is designated in a dynamic reuse fashion and suboptimal branches are encouraged to be pruned. To this end, our method can be readily integrated into A* procedure in a dynamic fashion, as well as significantly reduce the computational burden with a learned heuristic. Experimental results on different graph datasets show that our approach can remarkably ease the search process of A* without sacrificing much accuracy. To our best knowledge, this work is also the first deep learning-based GED method for recovering the edit path.

This paper proposes an object detection model named Feature Enriching Object Detection Framework with Weak Segmentation Loss (FEOD) based on convolutional neural networks, which is an improvement of You Only Look Once (YOLO). To overcome the shortcoming of insensitivity to small objects, a novel feature enriching module is proposed to augment the semantic information of the feature in the shallow layer within a typical deep detector. Meanwhile, Focal Loss is also introduced to our model to further improve the algorithm performance. To obtain features more suitable for object detection, a more powerful feature extractor – DetNet is used as the backbone. An mAP of 83.8 in VOC2007 test and an mAP of 82.1 in VOC2012 test are achieved with a FPS of 11.3 with a NVIDIA GTX1080Ti GPU. For a lower resolution version, we achieve an mAP of 81.9 and 80.9 respectively in VOC2007 and VOC2012 tests with FPS of 17. Comparisons with other object detection algorithms have shown that our method works well and achieves a trade-off of accuracy and speed.

BACKGROUND To report on the use of percutaneous hydrochloric acid (HCl) enhanced radiofrequency ablation (HRFA) for the treatment of large (maximum diameter ≥ 5 cm) hepatocellular carcinoma (HCC) in the caudate lobe. CASE SUMMARY Between August 2013 and June 2016, three patients with a large HCC (maximum diameter: 5.0, 5.7, and 8.1 cm) in the caudate lobe were treated by transarterial chemoembolization followed by computer tomography (CT) guided RFA using a monopolar perfusion RF electrode, which was enhanced by local infusion of 10% HCl at 0.2 mL/min (total volume, 3 to 12 mL). The output power of HRFA reached 100 W, and the average ablation time was 39 min (range, 15 to 60 min). Two patients each underwent one session of HRFA and one patient two sessions. After treatment, CT/magnetic resonance imaging showed that all the three lesions were completely ablated. There was no major complication. Two patients had asymptomatic bile duct dilatation. One patient died of tongue cancer 24 mo after ablation. The remaining two patients were alive and no area of enhancement is detected in the caudate lobe at 28 and 60 mo after ablation, respectively. CONCLUSION Percutaneous CT-guided HRFA is safe and efficacious in treating large HCC in the caudate lobe.

The stringent reaction conditions for an effective Fenton reaction (pH range of 3-4) hinders its application in cancer therapy. Therefore, how to improve the efficiency of the Fenton reaction in a tumor site has been the main obstacle in chemodynamic therapy (CDT). Herein, we report biocompatible one-dimensional (1D) ferrous phosphide nanorods (FP NRs) with ultrasound (US)- and photothermal (PT)-enhanced Fenton properties and excellent photothermal conversion efficiency (56.6 %) in the NIR II window, showing synergistic therapeutic properties. Additionally, the high photothermal conversion efficiency and excellent traverse relaxivity (277.79 mm-1 s-1 ) of the FP NRs means they are excellent photoacoustic imaging (PAI) and magnetic resonance imaging (MRI) agents. This is the first report on exploiting the response of metallic phosphides to NIR II laser (1064 nm) and ultrasound to improve the CDT effect with a high therapeutic effect and PA/MR imaging.

To evaluate the incidence, risk factors and clinical significance of four types of tumor progression (TP) after microwave ablation (MWA) of single hepatocellular carcinoma (HCC) of p = 0.492, 0.971, 0.681 and 0.219). Univariate analysis showed that age (p < 0.001, hazard ratio [HR] = 2.783), comorbidities (p = 0.042, HR = 1.864), IDR, AIR and EDR (p = 0.027, HR = 1.719; p = 0.001, HR = 3.628; p = 0.009, HR = 2.638) were independently associated with OS. Multivariate analysis showed older age (p < 0.001, HR = 2.478), the occurrence of AIR (p < 0.001, HR = 2.648) and the occurrence of EDR (p = 0.002, HR = 2.222), were associated with poor OS. The occurrence rate of IDR is the highest of all TPs following MWA of a single HCC of

Quantum dot light-emitting diodes (QLEDs) possess huge potential in display due to their outstanding optoelectronic performance; however, serve degradation during operation blocks their practical applications. High temperature is regarded as one of major factors causing degradation. Therefore, a systematical study on the working temperature of QLEDs is very essential and urgent for the development of high stable QLEDs. In this work, different influence factors such as the electro-optic conversion efficiency (EOCE), voltage, current density, active area, substrate size, substrate type and sample contact are discussed in detail on the working temperature of QLEDs. The research results show that the working temperature of general QLEDs under normal operation conditions is usually smaller than 75 °C when the ambient temperature is 25 °C. However, temperature of QLEDs working under extreme conditions, such as high power or small substrate size, will exceed 100 °C, resulting in irreversible damage to the devices. Moreover, some effective measures to reduce the working temperature are also proposed. The analysis and discussion of various influencing factors in this work will provide guidance for the design of stable QLEDs and help them work at a safer temperature.

Graph Neural Networks(GNNs), like GCN and GAT, have achieved great success in a number of supervised or semi-supervised tasks including node classification and link prediction. These existing graph neural networks can effectively encode neighborhood information of graph nodes through their message aggregating mechanisms. However, there are some unsupervised and structure-related tasks like community detection, which is a fundamental problem in network analysis that finds densely-connected groups of nodes and separates them from others in graphs. It is still difficult for these general-purposed GNNs to learn the needed structural information in these particular problems. To overcome the shortcomings of general-purposed graph representation learning methods, we propose the Community Deep Graph Infomax (CommDGI), a graph neural network designed to handle community detection problems. Inspired by the success of deep graph infomax in self-supervised graph learning, we design a novel mutual information mechanism to capture neighborhood as well as community information in graphs. A trainable clustering layer is employed to learn the community partition in an end-to-end manner. Disentangled representation learning is applied in our graph neural network so that the model can improve interpretability and generalization. Throughout the whole learning process, joint optimization is applied to learn the community-related node representations. The experimental results show that our algorithm outperforms state-of-the-art community detection methods.

Background: In recent years, the incidence of Parkinson's disease (PD) has been on the rise. However, the existing therapy of PD cannot fundamentally treat the disease. Meanwhile, the complementary and alternative therapies of PD have played a positive role in the treatment of PD. Traditional meta-analysis was only able to compare 2 interventions, while the efficacy and safety of many complementary and alternative therapies were not comparable. Therefore, this study compared the efficacy and safety of different complementary and alternative therapies through network meta-analysis (NMA). Methods: A comprehensive search of randomized controlled trials of complementary and alternative therapies for PD, as well as trials currently in progress, will be conducted until August 2020. Literature and data extraction were independently completed by two researchers. Through the meta-analysis of pairwise comparison and Bayesian NMA, all evidences are comprehensively evaluated. Use STATA15.0 and WinBUGS1.4.3 software for data processing and analysis, and use grading of recommendations assessment development and evaluation to classify the quality of evidence in the NMA. Results: The aim of this study is to obtain a ranking of efficacy and safety of different complementary and alternative therapies for PD. Conclusion: Complementary and alternative therapies for PD have positive significance in improving the symptoms of PD, and can provide evidence support for clinicians and patients. INPLASY registration number: INPLASY202080079

The building-integrated wind turbine is a new technology for the utilization of wind energy in cities. Previous studies mainly focused on the wind turbines mounted on the roofs of buildings. This paper discusses the performance of Savonius wind turbines which are mounted on the edges of a high-rise building. A transient CFD method is used to investigate the performance of the turbine and the interaction flows between the turbine and the building. The influence of three main parameters, including the turbine gap, wind angle, and adjacent turbines, are considered. The variations of the turbine torque and power under different operating conditions are evaluated and explained in depth. It is found that the edge-mounted Savonius turbine has a higher coefficient of power than that operating in uniform flows; the average Cp of the turbine under 360-degree wind angles is 92.5% higher than the turbine operating in uniform flows. It is also found that the flow around the building has a great impact on turbine performance, especially when the turbine is located downwind of the building.

We demonstrated a multi-dark soliton train generated from self-mode-locking ultra-long ring cavity fiber laser. The fiber laser used 10m double-clad Yb-doped fiber as gain medium, and used a polarization independent isolator to ensure the light propagation in one direction. The ring cavity of the laser was designed without any intra-cavity polarization controlling component. The cavity length is 1300 meters by insetting single mode fiber. When the pump power was increased to 2.75W, the multi-dark soliton trains were obtained. The stable pulse train has a repetition rate of 153.9 kHz corresponding to the cavity length. The number of sub-pulse continues to decrease during the increase of the incident pumping power until 3.39W. Stable three peaks appear in the spectra of our fiber laser due to the absence of the polarization controller in the cavity. The maximum peak wavelength locates around 1083.9nm with the 3dB bandwidth of 1.4nm. There are two sidebands with the central wavelength of 1086.3nm and 1090.1nm with a lower intensity. The occurrence of multi-dark soliton pulses train is relevant to the self-mode-locked operation at the cavity with a large amount of normal dispersion and accumulated nonlinearity.

Fault diagnosis of industrial processes has recently received widespread attention. Some studies applied neural networks to fault classification algorithms, which directly take the raw data as input of the neural network for training, and then use classifier to classify faults. However, the raw data of industrial usually has high dimension and the variables has linear correlations between each other, which may not only lead to higher computational complexity and cause the neural network difficult to converge. In this paper, a fault diagnosis algorithm based on a modified bidirectional long-short term memory network (BiLSTM) is investigated. The proposed method introduces the linear discriminant analysis (LDA) before the architecture of networks to reduce the dimension of input data. Then the LDA-BiLSTM is tested in Tennessee Eastman Process (TEP) platform. Experiment results show that the dimension reduction procedure can speed up the convergence of neural network, and may improve the classification accuracy. Extensive experimental results indicate that developed algorithm provides better diagnosis performance.

This study is aimed at determining the optimal sinus augmentation approach considering the poor bone condition in the zone of atrophic posterior maxilla. A series of simplified maxillary segment models varying in residual bone height (RBH) and bone quality were established. A 10 mm standard implant combined with two types of maxillary sinus augmentation methods was applied with the RBH, which was less than 10 mm in the maxilla. The maximal equivalent von Mises (EQV) stress in residual bone was evaluated. Bone quality had an enormous impact on the stress magnitude of supporting bone. Applying sinus augmentation combined with grafts was suitable for stress distribution, and high-stiffness graft performed better than low-stiffness one. For 7 mm and 5 mm atrophic maxilla, nongrafted maxillary sinus augmentation was feasible in D3 bone. Poor bone quality was a negative factor for the implant in the region of atrophic posterior maxilla, which could be improved by grafts. Meanwhile, the choice of maxillary sinus augmentation approaches should be determined by the RBH and quality.

For the difficulty of separation of accompaniment from mono music, image filtering was applied into a novel approach to separate accompaniment music. Our approach presents how single channel music manifests in the 2D Fourier Transform spectrum. In image domain, the position of periodic peak energy was determined by image filtering, and then masking matrix was constructed by rectangular window to extract the constituent of the accompaniment music. We find that our system is more robust and very simple to describe. The simulation experiments show that the method in this work has an advantage over other separation algorithm.

Osteoporosis(OP) and osteoarthritis(OA) co-exist with increased inflammatory cytokines as a common feature. Modern diet containing high n-6/n-3 PUFA was suggested contributing to these chronic inflammatory diseases. Although fish oil (FO) rich in n-3 PUFAs has been confirmed beneficial for OA and bone loss in previous studies, whether small amounts of FO could alleviate osteoporotic OA under a high n-6/n-3 PUFA condition has not been reported. In this study, the osteoporotic OA mice were fed with 20:1 or 6:1 n-6/n-3 PUFA diets with or without FO for 12 weeks. The results showed that 20:1 diet with FO ameliorated systemic inflammation and cartilage degradation in model mice, compared to the non-FO 20:1 diet. Specifically, diets with FO altered the fatty acids composition with elevating n-3/n-6 PUFA in articular cartilage, thus restoring the cartilage homeostasis by inhibiting the catabolic process. Mechanistically, 20:1 non-FO diet promoted the expression of NLRP3 via PGE2/EP4/NFκB. However, 20:1 FO-H diet significantly inhibited the expression of NLRP3 and further exhibited a greater affinity for GPR120 than 20:1 non-FO diet to inactivate caspase-1-dependent NLRP3 inflammasome. As a consequence, 20:1 FO-H diet inhibited chondrocyte pyroptosis and followed by the reduction of the two catabolic cytokines: IL-1β and IL-18. Notably, the 20:1 FO-H diet performed as well as the 6:1 non-FO diet, and 6:1 diet with FO could further improve osteoporotic OA in a dose-dependent manner. This study demonstrated that FO could attenuate the adverse effect of 20:1 n-6/n-3 PUFA diet on osteoporotic OA, providing skeletal evidence for healthy diet.

The present study introduced ultrasound volume navigation (UVN) to reduce the radiation exposure and puncture time of percutaneous transpedicular puncture in percutaneous vertebroplasty (PVP) or percutaneous kyphoplasty (PKP).We retrospectively reviewed the medical records of patients with osteoporotic vertebral compression fracture who had undergone PVP or PKP guided by UVN or fluoroscopy from September 2017 to December 2017.We enrolled 10 patients (6 women, 4 men) with 24 pedicles involved in the present study. Significant reductions in fluoroscopy frequency (2.58 vs. 17.42; P0.01), exposure time (2.36 vs. 15.69 seconds; P0.01), and puncture time (4.13 vs. 19.21 minutes; P0.01) for each pedicle were observed in the UVN group compared with the fluoroscopy group. Obvious correlations among fluoroscopy frequency, exposure time, and puncture time for each pedicle were observed (P0.01). The visual analog scale scores and Oswestry Disability Index were both significantly improved after the procedures. All patients achieved excellent or good clinical outcomes. No complications were observed in any patient.UVN could obviously reduce the radiation exposure and puncture time of percutaneous transpedicular puncture in PVP and PKP.

Objective Ultrasound volume navigation (UVN) has been widely used for accurate guidance and decreased radiation exposure. However, few studies have focused on the clinical significance of UVN in guiding percutaneous puncture in percutaneous transforaminal endoscopic discectomy (PTED). We evaluated UVN to guide percutaneous puncture in PTED. Methods We retrospectively reviewed the medical records of 12 patients (8 men and 4 women), who had undergone PTED with the help of UVN or fluoroscopic guidance for lumbar disc herniation from November 2017 to December 2017. Results The age of these 12 patients range was 26–71 years, and the body mass index range was 18.19–26.91 kg/m2. Of the 12 patients, 6 were in UVN group and 6 were in fluoroscopy group. The mean number of punctures was 1.00 in UVN group and 3.83 in fluoroscopy group. The mean exposure time was 3.60 and 13.80 seconds in UVN and fluoroscopy groups, respectively. The mean operation time was 48.17 minutes and 61.33 minutes in UVN and fluoroscopy groups, respectively. A positive relationship was found between operation time and exposure time (P Conclusions UVN decreased the number of puncture attempts, radiation exposure, and operation time compared with fluoroscopic guidance in PTED. Therefore, UVN is a feasible and efficient method for guiding percutaneous puncture in PTED.

Activation-pyrolysis of textile wastes was considered a sustainable technique to fabricate activated carbon. Highly mesoporous activated carbon was prepared from waste polyester textiles by employing MgCl2 as the activation and template agents. The influences of different preparation conditions on textual property and crystalline structure of carbon were identified by N2 adsorption-desorption isotherms and X-ray diffraction. The optimum pyrolysis temperature, time and mixing ratio for MgCl2/waste polyester textiles are 900 °C, 1.5 h and 5:5 with the carbon thus obtained manifested a surface area of 1307 m2/g, total pore volume of 3.56 cm3/g of which 98% is mesopore. The effect of MgCl2 on the full-cycle pyrolysis pathway of waste polyester textiles was systematically investigated by various characterization methods to explore the pore-forming mechanism of activated carbon. The results demonstrated that MgCl2 was capable of catalyzing the dehydrogenation, decarboxylic and cross-linking reaction of waste polyester textiles and inhibited the formation of tars during pyrolysis process, indicating that the addition of MgCl2 was conducive to the formation of carbonaceous materials and open pores. Meanwhile, acted as the template, MgO particles derived from the decomposition of MgCl2 could develop massive homogeneous mesopores in the carbon matrix.

This letter introduces a novel grayscale-inversion and rotation invariant descriptor, called sorted local gradient pattern, for texture classification. First, we propose two complementary local gradient patterns (LGP), the center-to-ring LGP (LGP_CR) and the ring-to-ring LGP (LGP_RR), to encode rich gradient information present in a local neighborhood. Then, we propose to enhance LGP by encoding pixels' intensity information. This is achieved by sorting image pixels into two categories via a dominant intensity order measure, followed by extracting LGP features over the categorized pixels. As a result, local gradient information and global intensity order information are both encoded into our descriptor in a way that is robust to grayscale-inversion and rotation changes. Experiments on three texture databases demonstrate that the proposed descriptor achieves state-of-the-art classification results in the presence of linear and even nonlinear grayscale-inversion changes.

Minimizing the breakdown voltage and discharge current required to initiate direct in-liquid discharges, thus lowering power-source requirements and avoiding electrode ablation, is crucial for industrial applications of in-liquid plasmas. Here we demonstrate such considerable reductions by employing movable electrodes, without changing the electrode configuration or increasing the system complexity. The new mechanism is based on electrostatic electrode attraction resulting in a reduction in the discharge spacing by up to 6 times and facilitating a plasma initiation at lower breakdown voltages. The accumulated charges consumed by the discharge revert the electrodes to the initial positions, forming a gliding arc between the enlarged gaps and thus inhibiting current increases and electrode ablation.

The unbalanced carrier injection is a key factor that deteriorates the performance of blue InP quantum dot light-emitting diodes (QLEDs). Therefore, to achieve efficient blue InP QLEDs, an effective strategy that balances carrier injection through enhancing the hole injection and transport is in demand. In this study, we introduced an ultrathin MoO3 electric dipole layer between the hole injection layer and the hole transport layer (HTL) to form a pair of dipole-induced built-in electric fields with forward resultant direction to enhance hole injection and facilitate the balance of carrier injection. Meanwhile, the p-doping effect by MoO3 leads to increased carrier concentration and decreased trap density of interfacial HTL, therefore improved its effective hole mobility. Consequently, the maximal external quantum efficiency of blue InP QLEDs was enhanced from 1.0% to 2.1%. This work provides an effective method to balance carrier injection by modulating hole injection and transport, indicating the feasibility to realize high-efficiency QLEDs.

Ammonia is one of our most important industrial chemicals supporting the global food supply as the major crop fertilizer. Moreover, it is increasingly being promoted as a promising carbon-free fuel source, and an energy storage and transportation medium. However, the current approach for ammonia synthesis, known as the Haber-Bosch process, requires large-scale infrastructure preventing the designs of decentralization. The process consumes a large fossil fuel input leading it to be a major source of CO2 emissions. Plasma-enabled ammonia synthesis provides a clean, sustainable and flexible alternative, where the process is driven by the use of plasmas that activate the source gas(es). However, atmospheric plasmas are complex due to their highly reactive environment (energetic electrons, reactive oxygen and nitrogen species, UV photons, electric field effects, and others), resulting in a challenging scientific issue for both plasma researchers and chemical engineers. The review summarizes the current state-of-the-art of plasma-enabled ammonia synthesis, and provides insights into the fundamental physio-chemistry of plasma activation, including the excitation, dissociation and ionization of feedstocks, as well as the underlying mechanisms for the reaction dynamics of reactive species in the highly-reactive plasma environment. Finally, the opportunities and challenges for this plasma-enabled technology are outlined to approach a sustainable and flexible ammonia industry.

Government policy has a significant effect on rural–urban land conversion, ultimately affecting sustainable urban land use. Unlike most studies that have centred on the effects of local land-use policies, such as regulations and taxes, the present study investigates the effect of the innovation-driven development policy initialised recently by China on urban land growth at the national level. Although the geography of innovation, high-tech agglomeration and sectoral restructuring are place-based activities, existing evidence shows several links between urban innovation and urban land growth. However, only a few empirical studies have examined their relationships to date. Thus, we aim to determine the effect of urban innovation on the size and the spatial distribution of urban land using a statistical dataset from 2007 to 2015 and a spatial data source at two-time points for 230 Chinese cities. We employ three fixed effects models to control for the possible correlation between independent variables and unobservable city-level effects. Our results indicate that urban innovation has indeed driven urban land growth but does not make the urban landscape more scattered than before. Further examinations suggest that the urban innovation effect varies across the whole country, and the innovation-urban land growth connection relies on the geographic location rather than the economy size.

This paper proposes a novel feature representation method for color images, namely quaternionic extended local binary pattern (QxLBP) with adaptive structural pyramid pooling (ASPP). First, we propose a QxLBP operator to encode local neighboring information and complementary modulus and phase information in the quaternion domain of color images. In QxLBP, an extended quaternionic representation (EQR) is proposed which introduces an information term into the real part of a quaternion. The resulting EQR enables us to flexibly encode discriminative features and handle multichannel image data. Second, we propose ASPP as a multiresolution pooling way to aggregate local features. Unlike the traditional spatial pyramid pooling which is sensitive to image rotation and spatial changes, ASPP is structure-oriented pooling which can adaptively aggregate the encoded features into multiresolution histogram representations. Experiments on four benchmark image datasets demonstrate that the proposed method achieves the state-of-the-art performance for color texture classification and scene categorization.

Catastrophic tunnel collapses usually start with the partial failure of tunnel linings. However, research on the mechanism of such progressive collapses is limited. Among such collapses, a considerable number of accidents have arisen from the construction of a connecting passage, which requires removing segments at the springline. Therefore, in this study, a series of customized model tests were conducted to investigate the mechanism underlying tunnel collapse due to this operation. The test results showed that the inrush of the sand due to the removal of a certain segment at the springline may lead to the loss of soil resistance around the openings, resulting in a sudden increase in the bending moments of the adjacent linings. In particular, an increase in the cover-depth-to-diameter ratio (C/D) can aggravate the development of the maximum bending moment, although it has little influence on the affected length of the tunnel. To address the load sustained by the segments and joints during collapse that the model tests fail to show, 3D numerical analyses based on the load-structure model were performed. Via comparison with existing failure criteria for both segments and joints, the safety of the adjacent tunnel linings can be evaluated.

A new image sparse representation tool—adaptive contourlet transform (ACT) is introduced in this letter. Adaptive directional partitioning schemes in ACT can match the arbitrary orientation distribution of natural image, which brings sparser representation. The proposed ACT is based on pseudopolar Fourier transform that has similar geometrical structure to fan filter. This characteristic helps ACT out of the difficulty of designing traditional directional filter bank. Simulation results demonstrate that ACT can provide more efficient image sparse representation compared to contourlet transform.