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Optical properties and high-order stimulated Raman scattering (SRS) generation in a homemade CVD diamond crystal with 3 × 3 mm2 aperture are investigated in this paper. The high order of the Raman laser has been studied theoretically and demonstrated experimentally. By simulating the Stokes components at different pump intensities and the divergence angles, the pump source was well matched with the size of the crystal. Pumped by using a 1064 nm picosecond laser, five coaxial wavelengths were obtained for the first time based on the CVD diamond at 932 nm, 1064 nm, 1240 nm, 1485 nm, and 1851 nm. This work provides a reference for further development of the optical grade diamond crystal with a large aperture.

Xing-Liang Wang,1 Chao Peng,2 You-Wei Tu,2 Yun-Peng Liu,2 Wei Zhang,2 Yan Zhang,2 Guo-Jun Hua3 1Department of Orthopedics, Wuxi Second People’s Hospital, Wuxi, 214000, People’s Republic of China; 2Department of Orthopedic Surgery, The No.904 Hospital of People’s Liberation Army, Wuxi 214000, People’s Republic of China; 3Department of Orthopedic Surgery, Wuxi No.2 Chinese Medicine Hospital, Wuxi, 214000, People’s Republic of ChinaCorrespondence: Guo-Jun HuaDepartment of Orthopedic Surgery, Wuxi No.2 Chinese Medicine Hospital, Wuxi, 214000, People’s Republic of ChinaEmail hgj13061@163.comXing-Liang WangDepartment of Orthopedics, Wuxi Second People’s Hospital, Wuxi, 214000, People’s Republic of ChinaEmail 15006176567@163.comPurpose: Recurrent patellar dislocation (RPD) is the most common complication of patellar instability and the medial patellofemoral ligament (MPFL) reconstruction has become its reference treatment. Lateral patellar retinaculum (LPR) release used to be performed in association with MPFL reconstruction. The aim of this study was to investigate the added values of MPFL reconstruction plus LPR release for RPD.Methods: After Institutional Review Board approval, RPD patients from October 2014 to April 2019 were randomly assigned into two groups (isolated MPFL reconstruction [Group I] and MPFL reconstruction plus LPR release [Group II]) and prospectively assessed until 12 months after surgery. Knee joints with flexion of 20° were scanned by a 64-row CT scanner. Congruence angle (CA), patella tilt angle (PTA), lateral patellofemoral angle (LPFA), tibial tuberosity-trochlear groove distance and patellar tilt with the quadriceps relaxed and contracted were measured. Knee function was assessed by Lysholm knee score and International Knee Documentation Committee (IKDC) score. Patients were followed up for at least 12 months.Results: A total of 87 RPD patients (45 for Group I and 42 for Group II) were selected in this study. Preoperative clinical characteristics were not significantly different across groups. No serious complications were noted in either group. It was statistically insignificant between the two group patients in terms of postoperative patella associated measurements (P > 0.05 for all). The Lysholm score and IKDC score of Group I (84.5 ± 7.1 and 87.9 ± 7.2) were significantly less than that of Group II (89.7 ± 8.7 and 93.1 ± 7.7), which indicated the better knee function of Group II.Conclusion: LPR release plus MPFL reconstruction provides additional benefits compared with isolated MPFL reconstruction in knee function. A combination of surgical treatments for RPD should be recommended.Keywords: recurrent patella dislocation, medial patellofemoral ligament reconstruction, lateral patellar retinaculum release, prospective, combination treatment

This special section is formed by 15 articles of outstanding quality that together comprise a snapshot of cutting edge automated machine learning (AutoML) research.

Objective Peripheral neuropathies in HIV-infected patients are highly debilitating because of neuropathic pain and physical disabilities. We defined prevalence and associated predictive variables for peripheral neuropathy subtypes in a cohort of persons living with HIV (PWH). Design Adult PWH in clinical care were recruited to a longitudinal study examining neurological complications. Methods Each subject was assessed for symptoms and signs of peripheral neuropathy and demographic, laboratory and clinical variables. Univariate, multiple logistic regression and machine learning analyses were performed by comparing patients with and without peripheral neuropathy. Results Three patient groups were identified: those with peripheral neuropathies (PNP, n = 111) that included HIV-associated distal sensory polyneuropathy (DSP, n = 90) or mononeuropathy (MNP, n = 21), and those without neuropathy (NNP, n = 408). Univariate analyses showed multiple variables differed significantly between the NNP and PNP groups including age, estimated HIV-1 duration, education, employment, neuropathic pain, peak viral load, polypharmacy, diabetes, cardiovascular disorders, AIDS, and prior neurotoxic nucleoside antiretroviral drug exposure. Classification algorithms distinguished those with PNP, all with area under the receiver operating characteristic curve (AUROC) values of >0.80. Random forest models showed greater accuracy and AUROC values compared with the multiple logistic regression analysis. Relative importance plots showed that the foremost predictive variables of PNP were HIV-1 duration, peak plasma viral load, age, and low CD4 T-cell levels. Conclusions PNP in HIV-1 infection remains common affecting 21.4% of patients in care. Machine learning models uncovered variables related to PNP that were undetected by conventional analyses, emphasizing the importance of statistical algorithmic approaches to understanding complex neurological syndromes.

Electric vehicles (EVs) currently face formidable challenges in promotion, i.e., short driving ranges, long charging times, and few charging stations, thereby limiting their acceptability to taxi drivers. Leveraging massive-scale taxi GPS trajectory data, we present a novel real-time route recommendation system for electric taxi (ET) drivers. Taxi travel knowledge, including the probability of picking up passengers and the distribution of destinations, is learned from the raw GPS trajectories. Considering the cascading effect of route decision making, consecutive ET actions are modeled with an action tree. The corresponding expected net revenue is estimated based on the learned knowledge. A prototype online system is developed for providing route recommendations, e.g., when to go to a charging station or cruise on certain roads. An experiment in Shenzhen demonstrates that the average daily net revenue of ET drivers is better than those of 76.2% of gasoline taxi drivers. The presented approach not only increases the revenue of ET drivers in the short term but also improves the viability of EVs in the long run.

With the promotion of low-carbon travel, pedestrian network plays an important role in many location-based applications, such as pedestrian navigation and refined traffic management. Due to the lack of systematic data acquisition mechanics, the accuracies and detail levels of pedestrian network data are hardly capable of satisfying the demands of such transportation applications. Presently, various mobile phone apps recorded and stored users’ movement trajectories, which provide a valuable data source for pedestrian network construction. Hence, this article proposes a crowdsourcing-based system for generating pedestrian network that encompasses three key components of crowdsourced walking trajectory data filtering, pedestrian network construction and evaluation of pedestrian network. Self-collected data and open platform data were used to evaluate the proposed system. Experimental results demonstrate that the proposed method can accurately and completely extract pedestrian network. Moreover, the pedestrian network can be updated in a timely manner by the proposed method. The data collection application and the collected data are available to the public.

Pansharpening fuses a low spatial resolution multi-spectral (MS) image with the corresponding panchromatic (PAN) image to obtain a high spatial resolution MS (HRMS) image. Traditional fusion methods may easily cause a spectral or spatial distortion when injecting details into an MS image. To preserve the spectral and spatial information, an efficient pansharpening model based on conditional random fields (CRFs) is proposed. With this model, a state feature function is designed to force the HRMS image filtered using a blur function to be consistent with the up-sampled MS image and retain the spectral fidelity. To obtain a proper blur function, a new filter-acquisition method is proposed for the unified CRF-based model. Meanwhile, a transition feature function is defined to enable the transition of HRMS pixels to follow the gradient of a PAN image and ensure the sharpness of the fused image. Considering the characteristics of the gradient domain, a total variation regularization is designed to make the gradient of the HRMS image sparse. Finally, the augmented Lagrangian function of the model is solved by employing an alternating direction method of the multipliers. Experiment results indicate that, compared with previous state-of-the-art pansharpening methods, the proposed method can achieve the best fusion results with high computational efficiency.

PA2G4 plays a dual role in tumors. However, the correlation of its expression with clinical feature and prognosis has never been reported in nasopharyngeal carcinoma (NPC). Using immunohistochemical staining, we examined PA2G4 protein level in clinicopathologically characterized 201 NPC cases (138 male and 63 female) with age ranging from 21 to 83 years and 45 nasopharyngeal (NP) tissues. Statistical methods were used to assess the difference in PA2G4 expression and its relationship with clinical parameters and prognosis in NPC. Immunohistochemical analysis showed that the protein expression of PA2G4 examined in NPC tissues was higher than that in the nasopharyngeal tissues (P=0.005). In addition, high levels of PA2G4 protein were positively correlated with tumor size (T classification) (P

Preterm birth (PTB) is an important cause of infant morbidity and mortality around the world. A good understanding of its associations with relevant factors is essential for an effective reduction ...

Background Evaluation of fluid responsiveness during veno-arterial extracorporeal membrane oxygenation (VA-ECMO) support is crucial. The aim of this study was to investigate whether changes in left ventricular outflow tract velocity–time integral (ΔVTI), induced by a Trendelenburg maneuver, could predict fluid responsiveness during VA-ECMO. Methods This prospective study was conducted in patients with VA-ECMO support. The protocol included four sequential steps: (1) baseline-1, a supine position with a 15° upward bed angulation; (2) Trendelenburg maneuver, 15° downward bed angulation; (3) baseline-2, the same position as baseline-1, and (4) fluid challenge, administration of 500 mL gelatin over 15 min without postural change. Hemodynamic parameters were recorded at each step. Fluid responsiveness was defined as ΔVTI of 15% or more, after volume expansion. Results From June 2018 to December 2019, 22 patients with VA-ECMO were included, and a total of 39 measurements were performed. Of these, 22 measurements (56%) met fluid responsiveness. The R2 of the linear regression was 0.76, between ΔVTIs induced by Trendelenburg maneuver and the fluid challenge. The area under the receiver operating characteristic curve of ΔVTI induced by Trendelenburg maneuver to predict fluid responsiveness was 0.93 [95% confidence interval (CI) 0.81–0.98], with a sensitivity of 82% (95% CI 60–95%), and specificity of 88% (95% CI 64–99%), at a best threshold of 10% (95% CI 6–12%). Conclusions Changes in VTI induced by the Trendelenburg maneuver could effectively predict fluid responsiveness in VA-ECMO patients. Trial registration ClinicalTrials.gov, NCT 03553459 (the TEMPLE study). Registered on May 30, 2018

Remote sensing image fusion is to fuse low spatial resolution multispectral (MS) images with high spatial resolution panchromatic (PAN) images to get high spatial resolution multispectral images. The component substitute (CS)-based methods are popular approaches for their high efficiency and high spatial resolution. However, they may produce spectral distortion, especially when there are large radiometric differences between PAN images and MS images. For tackling this problem, a new framework based on the CS model with fuzzy logic and salience measure is proposed. In order to get details that are highly relevant to MS image, a novel fuzzy logic rule based on the global salience measure is designed to fuse the details extracted from both PAN image and MS image. Furthermore, to better preserve the edges of the fused image, a new edge-preserving algorithm is defined to fuse the edges from the PAN image and MS image according to the local salience measure. A series of experiments are conducted and analyzed on both simulated images and real images from the data sets of four satellites to illustrate the effectiveness of the proposed method. Compared with some state-of-the-art methods, our method performs the best in both objective and subjective evaluations. Besides, our method has a low computational cost and is suitable for practical application.

Image‐guided pulsed focused ultrasound (pFUS) is a non‐invasive technique that can increase tropism of intravenously (IV)‐infused mesenchymal stromal cells (MSC) to sonicated tissues. MSC have shown promise for cardiac regenerative medicine strategies but can be hampered by inefficient homing to the myocardium. This study sonicated the left ventricles (LV) in rats with magnetic resonance imaging (MRI)‐guided pFUS and examined both proteomic responses and subsequent MSC tropism to treated myocardium. T2‐weighted MRI was used for pFUS targeting of the entire LV. pFUS increased numerous pro‐ and anti‐inflammatory cytokines, chemokines, and trophic factors and cell adhesion molecules in the myocardial microenvironment for up to 48 hours post‐sonication. Cardiac troponin I and N‐terminal pro‐B‐type natriuretic peptide were elevated in the serum and myocardium. Immunohistochemistry revealed transient hypoxia and immune cell infiltration in pFUS‐targeted regions. Myocardial tropism of IV‐infused human MSC following pFUS increased twofold‐threefold compared with controls. Proteomic and histological changes in myocardium following pFUS suggested a reversible inflammatory and hypoxic response leading to increased tropism of MSC. MR‐guided pFUS could represent a non‐invasive modality to improve MSC therapies for cardiac regenerative medicine approaches.

Online-to-offline (O2O) commerce connecting service providers and individuals to address daily human needs is quickly expanding. In particular, on-demand food, whereby food orders are placed online by customers and delivered by couriers, is becoming popular. This novel urban food application requires highly efficient and scalable real-time delivery services. However, it is difficult to recruit enough couriers and route them to facilitate such food ordering systems. This paper presents an online crowdsourced delivery (OCD) approach for on-demand food. Facilitated by Internet-of-Things and 3G/4G/5G technologies, public riders can be attracted to act as crowdsourced workers delivering food by means of shared bicycles or electric motorbikes. An online dynamic optimization framework comprising order collection, solution generation, and sequential delivery processes is presented. A hybrid metaheuristic solution process integrating the adaptive large neighborhood search and tabu search approaches is developed to assign food delivery tasks and generate high-quality delivery routes in a real-time manner. The crowdsourced riders are dynamically shared among different food providers. Simulated small-scale and real-world large-scale on-demand food delivery instances are used to evaluate the performance of the proposed approach. The results indicate that the presented crowdsourced food delivery approach outperforms traditional urban logistics. The developed hybrid optimization mechanism is able to produce high-quality crowdsourced delivery routes in less than 120 s. The results demonstrate that the presented OCD approach can facilitate city-scale on-demand food delivery.

Understanding population distribution has excellent applications for planning and provision of municipal services. This study aims to explore the space-time structure of population distribution wit...

BACKGROUND: Acute type A aortic dissection (aTAAD) is associated with a high incidence of prolonged postoperative invasive mechanical ventilation. We aimed to assess whether sequential noninvasive ventilation (NIV) could facilitate early extubation postoperatively after a spontaneous breathing trial (SBT) failure among aTAAD patients. METHODS: Beginning in December 2016, we transitioned our weaning strategy from repeated SBT until success (phase 1) to extubation concomitant with sequential NIV (phase 2) for subjects who failed their first SBT. The primary outcomes were re-intubation rate, duration of invasive ventilation, and total duration of ventilation. RESULTS: During the study period, 78 subjects with aTAAD failed their first postoperative SBT (38 subjects in phase 1 and 40 subjects in phase 2). Subjects extubated with sequential NIV had shorter median (interquartile range [IQR]) duration of invasive ventilation of 39.5 (30.8–57.8) h vs 89.5 (64–112) h (P CONCLUSIONS: Early extubation followed by sequential NIV significantly reduced duration of invasive ventilation and length of ICU stay without increasing re-intubation rate in postoperative subjects with aTAAD who failed their first SBT.

Background The present study aimed at comparing the success rate and safety of proximal versus distal approach for ultrasound (US)-guided axillary vein catheterization (AVC) in cardiac surgery patients susceptible to bleeding. Methods In this single-center randomized controlled trial, cardiac surgery patients susceptible to bleeding and requiring AVC were randomized to either the proximal or distal approach group for US-guided AVC. Patients susceptible to bleeding were defined as those who received oral antiplatelet drugs or anticoagulants for at least 3 days. Success rate, catheterization time, number of attempts, and mechanical complications within 24 h were recorded for each procedure. Results A total of 198 patients underwent randomization: 99 patients each to the proximal and distal groups. The proximal group had the higher first puncture success rate (75.8% vs. 51.5%, p p = 0.04) than the distal group. However, the overall success rates between the two groups were similar (99.0% vs. 99.0%; p = 1.00). Moreover, the proximal group had fewer average number of attempts (p p p Conclusions For cardiac surgery patients susceptible to bleeding, both proximal and distal approaches for US-guided AVC can be considered as feasible and safe methods of central venous cannulation. In terms of the first puncture success rate and cannulation time, the proximal approach is superior to the distal approach. Trial registration Clinicaltrials.gov, NCT03395691. Registered January 10, 2018, https://clinicaltrials.gov/ct2/show/NCT03395691?cond=NCT03395691&draw=1&rank=1.

We present the results of recent challenges in Automated Computer Vision (AutoCV, renamed here for clarity AutoCV1 and AutoCV2, 2019), which are part of a series of challenge on Automated Deep Learning (AutoDL). These two competitions aim at searching for fully automated solutions for classification tasks in computer vision, with an emphasis on any-time performance. The first competition was limited to image classification while the second one included both images and videos. Our design imposed to the participants to submit their code on a challenge platform for blind testing on five datasets, both for training and testing, without any human intervention whatsoever. Winning solutions adopted deep learning techniques based on already published architectures, such as AutoAugment, MobileNet and ResNet, to reach state-of-the-art performance in the time budget of the challenge (only 20 minutes of GPU time). The novel contributions include strategies to deliver good preliminary results at any time during the learning process, such that a method can be stopped early and still deliver good performance. This feature is key for the adoption of such techniques by data analysts desiring to obtain rapidly preliminary results on large datasets and to speed up the development process. The soundness of our design was verified in several aspects: (1) Little overfitting of the on-line leaderboard providing feedback on 5 development datasets was observed, compared to the final blind testing on the 5 (separate) final test datasets, suggesting that winning solutions might generalize to other computer vision classification tasks; (2) Error bars on the winners’ performance allow us to say with confident that they performed significantly better than the baseline solutions we provided; (3) The ranking of participants according to the any-time metric we designed, namely the Area under the Learning Curve, was different from that of the fixed-time metric, i.e. AUC at the end of the fixed time budget. We released all winning solutions under open-source licenses. At the end of the AutoDL challenge series, all data of the challenge will be made publicly available, thus providing a collection of uniformly formatted datasets, which can serve to conduct further research, particularly on meta-learning.

This paper proposes a novel data indexing scheme, the distributed access pattern R-tree (DAPR-tree), for spatial data retrieval in a distributed computing environment. As compared to traditional di...

The development of mobile Internet, smartphones, and location-based services has enabled ridesourcing, which pools vehicles and drivers to provide on-demand travel services. As an alternative transportation option, ridesourcing has significant impacts on urban travel. However, the unique mobility pattern of ridesourcing and its impact on vehicle electrification have not been well studied. To address this gap, this paper presents a comparative, big-data-driven framework to characterize the ridesourcing mobility pattern, and evaluate the acceptance potential of electric vehicles for ridesourcing in comparison with other types of vehicle use. Multi-temporal resolution ridesourcing trips are extracted from raw GPS trajectories. The patterns of three urban travel (household, ridesourcing, and taxis) are extracted from GPS trajectories in Beijing, and compared. The electrification potentials of these types of travel under different charging levels are then evaluated. The results demonstrate that mobility patterns of household, ridesourcing, and taxi drivers are similar when a single trip is considered but differ significantly when total vehicle travel is considered. We show that potential acceptance of electric vehicles decreases significantly from household to ridesourcing and taxi vehicle use. These findings provide useful insights into of the role vehicle electrification can play in sustainability of urban personal transportation across a range of drivers.

Objectives Stroke volume variation (SVV) has been used to predict fluid responsiveness. The authors hypothesized the changes in SVV induced by passive leg raising (PLR) might be an indicator of fluid responsiveness in patients with protective ventilation after cardiac surgery. Design A prospective single-center observational study. Setting A single cardiac surgery intensive care unit at a tertiary hospital. Participants A total of 123 patients undergoing cardiac surgery with hemodynamic instability. Tidal volume was set between 6 and 8 mL/kg of ideal body weight. Interventions PLR maneuver, fluid challenge. Measurements and Main Results SVV was continuously recorded using pulse contour analysis before and immediately after a PLR test and after fluid challenge (500 mL of colloid given over 30 min). Sixty-three (51.22%) patients responded to fluid challenge, in which PLR and fluid challenge significantly increased the SV and decreased the SVV. The decrease in SVV induced by PLR was correlated with the SV changes induced by fluid challenge. A 4% decrease in the SVV induced by PLR-discriminated responders to fluid challenge with an area under the curve of 0.90. The gray zone identified a range of SVV changes induced by PLR (between –3.94% and –2.91%) for which fluid responsiveness could not be predicted reliably. The gray zone included 15.45% of the patients. The SVV at baseline predicted fluid responsiveness with an area under the curve of 0.72. Conclusions Changes in the SVV induced by PLR predicted fluid responsiveness in cardiac surgical patients with protective ventilation.

Two-dimensional (2D) topological insulators (TIs) have attracted a lot of attention owing to their striking optical nonlinearity. However, the ultra-low saturable intensity (SI) of TIs resulting from the bulk conduction band limits their applications, such as in mode-locking solid-state lasers. In this work, through fabricating a graphene/Bi2Te3 heterojunction which combines monolayer graphene and a Bi2Te3 nanoplate, the optical nonlinearities are analyzed. Moreover, the thickness-dependent characteristics are also investigated by varying the thickness of the Bi2Te3 when synthesizing the heterojunctions. Furthermore, with the aid of the estimated junction electron escape time, a model of the photo-excited carrier-transfer mechanism is proposed and used to describe the phenomena of depression of ultra-low saturable absorption (SA) from the Bi2Te3 bulk band. The increased modulation depth of the graphene/Bi2Te3 heterojunction can accordingly be realized in more detail. In addition, a Q-switched solid-state laser operating at 1064 nm with heterojunction saturable absorbers is built up and characterized for validating the proposed model. The laser performance with varied Bi2Te3 thickness, such as pulse duration and repetition rate, agrees quite well with our proposed model. Our work demonstrates the functionality of optical nonlinear engineering by tuning the thickness of the graphene/Bi2Te3 heterojunction and demonstrates its potential for applications.

Objective To compare outcomes between intensivist-directed and cardiac surgeon-directed care delivery models. Design This retrospective, historical-control study was performed in a cohort of adult cardiac surgical patients at Zhongshan Hospital (Fudan University, China). During the first phase (March to August 2015), cardiac surgeons were in charge of postoperative care while intensivists were in charge during the second phase (September 2015–June 2016). Both phases were compared regarding successful extubation rate, intensive care unit (ICU) length of stay (LOS), and in-hospital mortality. Setting Tertiary Zhongshan Hospital (Fudan University, China). Patients Consecutive adult patients admitted to the cardiac surgical ICU (CSICU) after heart surgery. Interventions Phase I patients treated by cardiac surgeons, and phase II patients treated by intensivists. Main variables of interest Successful extubation, ICU LOS and in-hospital mortality. Results A total of 1792 (phase I) and 3007 patients (phase II) were enrolled. Most variables did not differ significantly between the two phases. However, patients in phase II had a higher successful extubation rate (99.17% vs. 98.55%; p = 0.043) and a shorter median duration of mechanical ventilation (MV) (18 vs. 19 h; p 48 h, those in phase II had a comparatively higher successful extubation rate (p = 0.033), shorter ICU LOS (p = 0.038) and a significant decrease in in-hospital mortality (p = 0.039). Conclusions The intensivist-directed care model showed improved rates of successful extubation and shorter MV durations after cardiac surgery.

Background Yunnan has the highest rates of HIV in China. Other treatable sexually transmitted infections (STIs) are associated with accelerated HIV transmission and poor ART outcomes, but are only diagnosed by syndromic algorithms. Methods We recruited 406 HIV-positive participants for a cross-sectional study (204 ART-naive and 202 receiving ART). Blood samples and first-voided urine samples were collected. Real-time polymerase chain reaction methods were used for diagnosing Chlamydia trachomatis (CT), Neisseria gonorrhea (NG) and Mycoplasma genitalium (MG). Syphilis and herpes simplex virus type 2 (HSV-2) tests were also performed. Results Among the 406 participants, the overall prevalence of STIs was 47.0% and 45.1% in ART-naive individuals and 49.0% in individuals receiving ART, respectively. The testing frequencies were 11.6% (11.8% vs. 11.4%), 33.2% (29.4% vs. 37.1%), 3.2% (3.4% vs. 3.0%), 2.0% (3.4% vs. 0.5%) and 4.7% (6.4% vs. 3.0%) for active syphilis, HSV-2, CT, NG and MG, respectively. The percentage of multiple infections in both groups was 10.8% (22/204) in ART-naive participants and 9.9% (20/202) in participants receiving ART. Female sex, an age between 18 and 35 years, ever injecting drugs, homosexual or bisexual status, HIV/HBV coinfection, and not receiving ART were identified as risk factors. Self-reported asymptomatic patients were not eliminated from having a laboratory-diagnosed STI. Conclusions The STI prevalence was 47.0% (45.1% vs. 49.0%), and HSV-2, syphilis and MG were the most common STIs in HIV-infected individuals. We found a high prevalence (6.4%) of MG in ART-naive individuals. HIV-positive individuals tend to neglect or hide their genital tract discomfort; thus, we suggest strengthening STI joint screening and treatment services among HIV-infected individuals regardless of whether they describe genital tract discomfort.

Sewer pipe is an essential infrastructure in the city as it undertakes the transportation and circulation of wastewater resources. But sewer pipe it is easy to have faults and cause serious secondary urban accidents, such as road holes and road collapse. Because of the complex underground circumstance, inspecting large-area sewer pipes using closed-circuit television or periscope television is difficult. In this study, we proposed a collaborative sewer pipe inspection approach by using novel low-cost pipe robotic capsules, which capture the images of the pipeline inner walls when floating with the water flow. A set of workers collaboratively drop and salvage capsules to cover a large-area pipe network. The routes of workers and pipe capsules are optimized by a meta-heuristic algorithm integrating local search and simulated annealing. The deep neural network is used to recognize faults from raw captured images. A field experiment in Shenzhen was conducted to evaluate the performance of the proposed approach. The results demonstrate that it outperforms the naive inspection method with a shorter travel distance and less waiting time. It is also effective for inspecting the large-area sewer pipe networks with an overall precision of 0.92. It will help us to eliminate the potential safety risk of the public and promote the level of urban governance.

Background: Cardiopulmonary support, as extracorporeal membrane oxygenation (ECMO) or mechanical ventilation (MV), is crucial for ICU patients. However, some of these patients are difficult to wean. Therefore, we aimed to assess the efficacy and safety of levosimendan in facilitating weaning from cardiorespiratory support in this patient population.Methods: We searched for potentially relevant articles in PubMed, Embase, China National Knowledge Infrastructure, Wanfang, and the Cochrane database from inception up to Feb 30, 2021. Studies focusing on weaning data in MV/ECMO adult patients who received levosimendan compared to controls were included. We used the Cochrane risk of bias tool or the Newcastle-Ottawa Quality Assessment Scale to evaluate the study quality. The primary outcome was the weaning rate from MV/ECMO. Secondary outcomes were mortality, duration of MV, and ICU stay. Subgroup analysis, sensitivity analysis, and publication bias were also conducted.Results: Eighteen studies with 2,274 patients were included. The quality of the included studies was low to moderate. Overall, levosimendan effectively improved weaning rates from MV/ECMO [odds ratio (OR) = 2.32; 95%CI, 1.60–3.36; P < 0.00001, I2 = 68%]. Subgroup analyses confirmed the higher successful weaning rates in ventilated patients with low left ventricular ejection fractions (OR = 4.06; 95%CI, 2.16–7.62), patients with ECMO after cardiac surgery (OR = 2.04; 95%CI, 1.25–3.34), and patients with ECMO and cardiogenic shock (OR = 1.98; 95%CI, 1.34–2.91). However, levosimendan showed no beneficial effect on patients with MV weaning difficulty (OR = 2.28; 95%CI, 0.72–7.25). Additionally, no differences were found concerning the secondary outcomes between the groups.Conclusions: Levosimendan therapy significantly increased successful weaning rates in patients with cardiopulmonary support, especially patients with combined cardiac insufficiency. Large-scale, well-designed RCTs will be needed to define the subgroup of patients most likely to benefit from this strategy.

Background Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of coronavirus disease 2019 (COVID-19) and for monitoring its progress. The present study aimed to assess the association between steroid therapy and quantitative CT parameters in a longitudinal cohort with COVID-19. Methods Between February 7 and February 17, 2020, 72 patients with severe COVID-19 were retrospectively enrolled. All 300 chest CT scans from these patients were collected and classified into five stages according to the interval between hospital admission and follow-up CT scans: Stage 1 (at admission); Stage 2 (3–7 days); Stage 3 (8–14 days); Stage 4 (15–21 days); and Stage 5 (22–31 days). QCT was performed using a threshold-based quantitative analysis to segment the lung according to different Hounsfield unit (HU) intervals. The primary outcomes were changes in percentage of compromised lung volume (%CL, − 500 to 100 HU) at different stages. Multivariate Generalized Estimating Equations were performed after adjusting for potential confounders. Results Of 72 patients, 31 patients (43.1%) received steroid therapy. Steroid therapy was associated with a decrease in %CL (− 3.27% [95% CI, − 5.86 to − 0.68, P = 0.01]) after adjusting for duration and baseline %CL. Associations between steroid therapy and changes in %CL varied between different stages or baseline %CL (all interactions, P P P Conclusions Steroid administration was independently associated with a decrease in %CL, with interaction by duration or disease severity in a longitudinal cohort. The quantitative CT parameters, particularly compromised lung volume, may provide a useful tool to monitor COVID-19 progression during the treatment process. Trial registration Clinicaltrials.gov, NCT04953247. Registered July 7, 2021, https://clinicaltrials.gov/ct2/show/NCT04953247

Diabetes prediction is an important data science application in the social healthcare domain. There exist two main challenges in the diabetes prediction task: data heterogeneity since demographic and metabolic data are of different types, data insufficiency since the number of diabetes cases in a single medical center is usually limited. To tackle the above challenges, we employ gradient boosting decision trees (GBDT) to handle data heterogeneity and introduce multi-task learning (MTL) to solve data insufficiency. To this end, Task-wise Split Gradient Boosting Trees (TSGB) is proposed for the multi-center diabetes prediction task. Specifically, we firstly introduce task gain to evaluate each task separately during tree construction, with a theoretical analysis of GBDT's learning objective. Secondly, we reveal a problem when directly applying GBDT in MTL, i.e., the negative task gain problem. Finally, we propose a novel split method for GBDT in MTL based on the task gain statistics, named task-wise split, as an alternative to standard feature-wise split to overcome the mentioned negative task gain problem. Extensive experiments on a large-scale real-world diabetes dataset and a commonly used benchmark dataset demonstrate TSGB achieves superior performance against several state-of-the-art methods. Detailed case studies further support our analysis of negative task gain problems and provide insightful findings. The proposed TSGB method has been deployed as an online diabetes risk assessment software for early diagnosis., 11 pages (2 pages of supplementary), 10 figures, 7 tables. Accepted by ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021)

Extreme multi-label learning (XML) works to annotate objects with relevant labels from an extremely large label set. Many previous methods treat labels uniformly such that the learned model tends to perform better on head labels, while the performance is severely deteriorated for tail labels. However, it is often desirable to predict more tail labels in many real-world applications. To alleviate this problem, in this work, we show theoretical and experimental evidence for the inferior performance of representative XML methods on tail labels. Our finding is that the norm of label classifier weights typically follows a long-tailed distribution similar to the label frequency, which results in the over-suppression of tail labels. Base on this new finding, we present two new modules: (1)ReRank works to re-rank the predicted score, which significantly improves the performance on tail labels by eliminating the effect of label-priors; (2)Taug augments tail labels via a decoupled learning scheme, which can yield more balanced classification boundary. We conduct experiments on commonly used XML benchmarks with hundreds of thousands of labels, showing that the proposed methods improve the performance of many state-of-the-art XML models by a considerable margin (6% performance gain with respect to PSP@1 on average). Anonymous source code is available at https://github.com/ReRANK-XML/rerank-XML.

Face sketch-photo synthesis is a significant challenge task in computer vision area, due to the blurred facial details and color distortion produced by the existing approaches. In this paper, we propose a realistic face sketch-photo synthesis method based on residual enhancement network. In the network, a residual enhancement module is constructed and embedded in U-Net to improve the feature representation capability of the deep network. In addition, a detail loss and a perception loss are adopted to constrain the synthesized image has abundant detail and realistic photo style. Experimental results on multiple face sketch datasets indicate that the proposed method obtains superior performance than the state-of-the-art methods, both in terms of visual perception and objective evaluations.

Hanbin Zhang,1 Wenrui Lin,2 Dongting Chen,1 Kenie Wang,3 Wei Tu,4 Huiwen Lin,4 Kun Li,4 Shangzhu Ye,5 Tianwang Guan,6 Yuerong Chen4 1Department of Clinical Medicine, The Second Clinical College of Guangzhou Medical University, Guangzhou, People’s Republic of China; 2Department of Clinical Medicine, The Sixth Clinical College of Guangzhou Medical University, Guangzhou, People’s Republic of China; 3The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, People’s Republic of China; 4Department of Oncology, Jinshazhou Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China; 5Department of Ophthalmology and Otorhinolaryngology, Yangjiang Hospital of Traditional Chinese Medicine, Yangjiang, People’s Republic of China; 6Department of Cardiology, Laboratory of Heart Center, Zhujiang Hospital, Southern Medical University, Guangzhou, People’s Republic of ChinaCorrespondence: Tianwang GuanDepartment of Cardiology, Laboratory of Heart Center, Zhujiang Hospital, Southern Medical University, Guangzhou, People’s Republic of ChinaTel +8620-61643888Email guantianwang@163.comYuerong ChenDepartment of Oncology, Jinshazhou Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of ChinaTel +8620-81116661Email 604910344@qq.comPurpose: Male breast cancer (MBC) is a rare disease that tends to occur in elderly men. Little is known about the causes of death in MBC because of the small sample size of most studies. This study aimed to investigate the causes of death in MBC patients.Patients and Methods: MBC patient data were obtained from the Surveillance, Epidemiology, and End Results database (1975– 2016). Time trends of MBC mortality in the US population were analyzed using Joinpoint software. We calculated the proportion of each cause of death in the overall cohort and in different patient subgroups. Competing risk models were used to calculate cumulative mortality at different follow-up times. The risk of cardiovascular death (CVD) in MBC patients was compared to that of the age-matched general population by calculating standardized mortality ratio (SMR).Results: In total, 6426 patients were included in the analysis. MBC mortality rate increased between 2004 and 2019 (annual percentage change=1.16, 95% confidence interval [CI]: 0.50, 1.80). There were 1757 patients (27.3%) who died of non-breast cancer causes. CVD was the leading cause of death in patients who were elderly or had localized disease. MBC patients had a 6.58-fold higher risk of CVD than the general population (SMR=6.58, 95% CI: 6.14, 7.05).Conclusion: Non-breast cancer death accounts for the majority of deaths in MBC patients who are elderly or have localized cancer. Compared to the general population, MBC patients have an increased risk of CVD. These results highlight the importance of monitoring cardiovascular comorbidities in MBC patients.Keywords: male breast cancer, cardio-oncology, elderly patients, cause of death, non cancer death, cardiovascular death

Supplemental Digital Content is available in the text, Background: Clinical outcomes of undifferentiated arthritis (UA) are diverse, and only 40% of patients with UA develop rheumatoid arthritis (RA) after 3 years. Discovering predictive markers at disease onset for further intervention is critical. Therefore, our objective was to analyze the clinical outcomes of UA and ascertain the predictors for RA development. Methods: We performed a prospective, multi-center study from January 2013 to October 2016 among Chinese patients diagnosed with UA in 22 tertiary-care hospitals. Clinical and serological parameters were obtained at recruitment. Follow-up was undertaken in all patients every 12 weeks for 2 years. Predictive factors of disease progression were identified using multivariate Cox proportional hazards regression. Results: A total of 234 patients were recruited in this study, and 17 (7.3%) patients failed to follow up during the study. Among the 217 patients who completed the study, 83 (38.2%) patients went into remission. UA patients who developed RA had a higher rheumatoid factor (RF)-positivity (42.9% vs. 16.8%, χ2 = 8.228, P = 0.008), anti-cyclic citrullinated peptide (CCP) antibody-positivity (66.7% vs. 10.7%, χ2 = 43.897, P

Objectives. The present study aimed to evaluate prognostic value of inflammatory markers for in-hospital mortality and renal complication in patients undergoing surgery for acute type A aortic diss...

High-order pattern formation in an optically pumped semiconductor laser (OPSL) under a selective pumping with varying spatial overlap between the pump beam and transverse modes is explored. In contrast to transverse pattern generation by off-axis pumped solid-state lasers where the mode order can be flexibly increased, experimental results reveal that the selective pumping fails to realize high-order mode operation in OPSLs when the pump-to-mode size ratio and pump power are insufficiently large. On the other hand, several high-order patterns belonging to the Hermite-Laguerre-Gaussian (HLG) modes are observed when scanning a large-ratio pump beam to specific positions on the gain chip. These HLG modes are experimentally confirmed to mainly originate from the transverse non-uniformity of present OPSL chip, while their structural features cannot be simply correlated with the pump scanning positions. Nevertheless, it is believed that the first-time observation of pure HLG modes under the large-ratio pumping can offer useful insights into the high-order pattern manipulation in OPSLs.

Neurocognitive impairment (NCI) among HIV-infected patients is heterogeneous in its reported presentations and frequencies. To determine the prevalence of NCI and its associated subtypes as well as predictive variables, we investigated patients with HIV/AIDS receiving universal health care. Recruited adult HIV-infected subjects underwent a neuropsychological (NP) test battery with established normative (sex-, age-, and education-matched) values together with assessment of their demographic and clinical variables. Three patient groups were identified including neurocognitively normal (NN, n = 246), HIV-associated neurocognitive disorders (HAND, n = 78), and neurocognitively impaired-other disorders (NCI-OD, n = 46). Univariate, multiple logistic regression and machine learning analyses were applied. Univariate analyses showed variables differed significantly between groups including birth continent, quality of life, substance use, and PHQ-9. Multiple logistic regression models revealed groups again differed significantly for substance use, PHQ-9 score, VACS index, and head injury. Random forest (RF) models disclosed that classification algorithms distinguished HAND from NN and NCI-OD from NN with area under the curve (AUC) values of 0.87 and 0.77, respectively. Relative importance plots derived from the RF model exhibited distinct variable rankings that were predictive of NCI status for both NN versus HAND and NN versus NCI-OD comparisons. Thus, NCI was frequently detected (33.5%) although HAND prevalence (21%) was lower than in several earlier reports underscoring the potential contribution of other factors to NCI. Machine learning models uncovered variables related to individual NCI types that were not identified by univariate or multiple logistic regression analyses, highlighting the value of other approaches to understanding NCI in HIV/AIDS.

Acute Respiratory Distress Syndrome (ARDS) and its complications remain lifethreatening conditions for critically ill patients. The present therapeutic strategies such as prone positioning ventilation strategies, nitric oxide inhalation, restrictive intravenous fluid management, and extracorporeal membrane oxygenation (ECMO) do not contribute much to improving the mortality of ARDS. The advanced understanding of the pathophysiology of acute respiratory distress syndrome suggests that gene-based therapy may be an innovative method for this disease. Many scientists have made beneficial attempts to regulate the immune response genes of ARDS, maintain the normal functions of alveolar epithelial cells and endothelial cells, and inhibit the fibrosis and proliferation of ARDS. Limitations to effective pulmonary gene therapy still exist, including the security of viral vectors and the pulmonary defense mechanisms against inhaled particles. Here, we summarize and review the mechanism of gene therapy for acute respiratory distress syndrome and its application.

Automated Machine Learning (AutoML) aims to build an appropriate machine learning model for any unseen dataset automatically, i.e., without human intervention. Great efforts have been devoted on AutoML while they typically focus on supervised learning. In many applications, however, semisupervised learning (SSL) are widespread and current AutoML systems could not well address SSL problems. In this paper, we propose to present an automated learning system for SSL (AUTO-SSL). First, meta-learning with enhanced meta-features is employed to quickly suggest some instantiations of the SSL techniques which are likely to perform quite well. Second, a large margin separation method is proposed to fine-tune the hyperparameters and more importantly, alleviate performance deterioration. The basic idea is that, if a certain hyperparameter owns a high quality, its predictive results on unlabeled data may have a large margin separation. Extensive empirical results over 200 cases demonstrate that our proposal on one side achieves highly competitive or better performance compared to the state-of-the-art AutoML system AUTO-SKLEARN and classical SSL techniques, on the other side unlike classical SSL techniques which often significantly degenerate performance, our proposal seldom suffers from such deficiency.

Automatic machine learning (AutoML) aims at automatically choosing the best configuration for machine learning tasks. However, a configuration evaluation can be very time consuming particularly on learning tasks with large datasets. This limitation usually restrains derivative-free optimization from releasing its full power for a fine configuration search using many evaluations. To alleviate this limitation, in this paper, we propose a derivative-free optimization framework for AutoML using multi-fidelity evaluations. It uses many lowfidelity evaluations on small data subsets and very few highfidelity evaluations on the full dataset. However, the lowfidelity evaluations can be badly biased, and need to be corrected with only a very low cost. We thus propose the Transfer Series Expansion (TSE) that learns the low-fidelity correction predictor efficiently by linearly combining a set of base predictors. The base predictors can be obtained cheaply from down-scaled and experienced tasks. Experimental results on real-world AutoML problems verify that the proposed framework can accelerate derivative-free configuration search significantly by making use of the multi-fidelity evaluations.

Nonalcoholic fatty liver disease (NAFLD) enhances the growth and recurrence of colorectal cancer (CRC) liver metastasis. With the rising prevalence of NAFLD, a better understanding of the molecular mechanism underlying NAFLD-associated liver metastasis is crucial. Tumor-associated macrophages (TAMs) constitute a large portion of the tumor microenvironment that promotes tumor growth. NOD-like receptor C4 (NLRC4), a component of an inflammasome complex, plays a role in macrophage activation and interleukin (IL)-1β processing. We aimed to investigate whether NLRC4-mediated TAM polarization contributes to metastatic liver tumor growth in NAFLD. Wild-type and NLRC4-/- mice were fed low-fat or high-fat diet for 6 weeks followed by splenic injection of mouse CRC MC38 cells. The tumors were analyzed 2 weeks after CRC cell injection. High-fat diet-induced NAFLD significantly increased the number and size of CRC liver metastasis. TAMs and CD206-expressing M2 macrophages accumulated markedly in tumors in the presence of NAFLD. NAFLD up-regulated the expression of IL-1β, NLRC4, and M2 markers in tumors. In NAFLD, but not normal livers, deletion of NLRC4 decreased liver tumor growth accompanied by decreased M2 TAMs and IL-1β expression in tumors. Wild-type mice showed increased vascularity and vascular endothelial growth factor (VEGF) expression in tumors with NAFLD, but these were reduced in NLRC4-/- mice. When IL-1 signaling was blocked by recombinant IL-1 receptor antagonist, liver tumor formation and M2-type macrophages were reduced, suggesting that IL-1 signaling contributes to M2 polarization and tumor growth in NAFLD. Finally, we found that TAMs, but not liver macrophages, produced more IL-1β and VEGF following palmitate challenge. Conclusion: In NAFLD, NLRC4 contributes to M2 polarization, IL-1β, and VEGF production in TAMs, which promote metastatic liver tumor growth.

The recent boom of sharing economy along with its technological underpinnings have brought new opportunities to urban transport ecosystems. Today, a new mobility option that provides station-less bike rental services is emerging. While previous studies mainly focus on analyzing station-based systems, little is known about how this new mobility service is used in cities. This research proposes an analytical framework to unravel the landscape and pulses of cycling activities from a dockless bike-sharing system. Using a four-month GPS dataset collected from a major bike-sharing operator in Singapore, we reconstruct the temporal usage patterns of shared bikes at different places and apply an eigendecomposition approach to uncover their hidden structures. Several key built environment indicators are then derived and correlated with bicycle usage patterns. According to the analysis results, cycling activities on weekdays possess a variety of temporal profiles at both trip origins and destinations, highlighting substantial variations of bicycle usage across urban locations. Strikingly, a significant proportion of these variations is explained by the cycling activeness in the early morning. On weekends, the overall variations are much smaller, indicating a more uniform distribution of temporal patterns across the city. The correlation analysis reveals the role of shared bikes in facilitating the first- and last-mile trips, while the contribution of the latter (last-mile) is observed to a limited extent. Some built environment indicators, such as residential density, commercial density, and number of road intersections, are correlated with the temporal usage patterns. While others, such as land use mixture and length of cycling path, seem to have less impact. The study demonstrates the effectiveness of eigendecomposition for uncovering the system dynamics. The workflow developed in this research can be applied in other cities to understand this new-generation system as well as the implications for urban design and transport planning.

Background Three-dimensional color flow Doppler (3DCF) is a new convenient technique for cardiac output (CO) measurement. However, to date, no one has evaluated the accuracy of 3DCF echocardiography for CO measurement after cardiac surgery. Therefore, this single-center, prospective study was designed to evaluate the reliability of three-dimensional color flow and two-dimensional pulse wave Doppler (2D-PWD) transthoracic echocardiography for estimating cardiac output after cardiac surgery. Methods Post-cardiac surgical patients with a good acoustic window and a low dose or no dose of vasoactive drugs (norepinephrine

Although people may recognize urban vibrancy when they see or sense it, developing direct and comprehensive measures of urban vibrancy remains a challenge. In the context of intense global competition, there is an increased realization that urban vibrancy is vital to the social and economic sustainability of cities. Such vibrancy may be significantly shaped by the urban built environment, yet we know little about the close connections between vibrancy and urban built environments. Empowered by newly available sources of spatial big data, which provide enormous amounts of information on both human dynamics and the built environment, this paper proposes a framework for evaluating and characterizing urban vibrancy. Thus far, vibrancy measures have mostly used single-source data that hardly reflect the multifaceted manifestations of urban vibrancy. Therefore, we propose a more comprehensive measure of urban vibrancy, extracted as the common latent factor from multiple surface attributes. Using the proposed framework, we evaluated and mapped the spatial dynamics of vibrancy in Shanghai, a typical large city in post-reform China, and investigated the associations between vibrancy and various urban built environment indicators. The evidence shows that the horizontal built-up density, rather than vertical height, is the leading generator of vibrancy in Shanghai, followed by the density and mixture of urban functions, accessibility, and walkability. In this vein, we contribute to current debates and future planning practices regarding vibrant spaces in large cities. This proposed evaluation framework, equipped with spatial big data, can benefit future urban studies.

Sparse coding technique is usually applied for feature representation. To learn discriminative features for visual recognition, a dictionary learning method, called Paired Discriminative K-SVD (PD-KSVD), is presented in this paper. Firstly, to reduce the reconstruction error of positive class while increasing the errors of negative classes, the scheme inverted signal is applied to the negative training samples. Then, the class-specific sub-dictionaries are learned from pairs of positive and negative classes to jointly achieve high discrimination and low reconstruction errors for sparse coding. Multiple sub-dictionaries are concatenated with respect to the same negative class so that the non-zero sparse coefficients can be discriminatively distributed to improve classification accuracy. Last, sparse coefficients are solved via the concatenated sub-dictionaries and used to train the classifier. Compared to the existing dictionary learning methods, PD-KSVD method achieves superior performance in a variety of visual recognition tasks on several publicly available datasets.

Acute kidney injury (AKI) is a common and potential life-threatening disease in patients admitted to hospital, affecting 10%–15% of all hospitalizations and around 50% of patients in the intensive care unit. Severe, recurrent, and uncontrolled AKI may progress to chronic kidney disease or end-stage renal disease. AKI thus requires more efficient, specific therapies, rather than just supportive therapy. Mesenchymal stem cells (MSCs) are considered to be promising cells for cellular therapy because of their ease of harvesting, low immunogenicity, and ability to expand in vitro. Recent research indicated that the main therapeutic effects of MSCs were mediated by MSC-derived extracellular vesicles (MSC-EVs). Furthermore, compared with MSCs, MSC-EVs have lower immunogenicity, easier storage, no tumorigenesis, and the potential to be artificially modified. We reviewed the therapeutic mechanism of MSCs and MSC-EVs in AKI, and considered recent research on how to improve the efficacy of MSC-EVs in AKI. We also summarized and analyzed the potential and limitations of EVs for the treatment of AKI to provide ideas for future clinical trials and the clinical application of MSC-EVs in AKI.

In this paper, a new approach to image based visual servoing with laser pointer is developed. The laser pointer has been adopted and the triangular method has been used to