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The SLAM problem in dynamic scenes is regarded as a challenge. This article proposes a novel SLAM framework for dynamic environments, which combines neural network and motion information of dynamic objects, making the system more adaptable to dynamic scenes. Specifically, we adopt a fast object detection network, tightly couple the results of the object detection with the geometric information in the SLAM system. Then the feature point extracted from the image is associated with a dynamic probability. By utilizing the feature points which tend to be static, the localization result can be greatly improved in dynamic environments. We perform the experiments both on the public data set and the real environment. The result can demonstrate that the proposed method greatly improves the localization accuracy in a dynamic environment. An open-source version of the source code is available.

Photovoltaic (PV) power generation plant with integrated battery energy storage (BES) is becoming increasingly attractive and necessary as the PV penetration increases. Traditional solutions involve two paralleled inverter systems at the same site. This increases the balance of the system cost as well as the control complexity. Furthermore, high-power step-up transformers are needed to connect to the distribution grid, further increasing the capital cost, land use and installation cost. Combining PV and BES into a single inverter system without the 60Hz step-up transformer is therefore very attractive as the next generation technology for utility scale solar. This effectively calls for the development of a PV+BES Solid State Transformer (PVS-SST). This paper proposes a 13.8kV/3MVA PVS-SST targeting 13.8 kV grid connection on the AC side and 1500V PV farm on the DC side. The PVS-SST utilizes a modular SST concept with total 27 SiC submodules. Each submodule is based on 1700V SiC power MOSFET devices and single stage DAB-based DC/AC power conversion technology. In order to utilize the inevitable parasitic capacitances in the actual hardware, a novel turn-off loss model is proposed and experimentally verified. A comprehensive optimization strategy including the proposed novel turn-off loss model, ZVS range, deadtime calculation, and minimum circulation current is proposed. Medium frequency transformer (MFT) design to achieve very high efficiency and isolation voltage is a grand challenge in the proposed PVS-SST and is discussed in detail. The power-density of the SiC power submodule is 1.6MW/m3 (26W/inch3). The PVS-SST control architecture is discussed with a focus on voltage balancing and real and reactive power controls.

Chylothorax is an uncommon and serious clinical condition, typically induced by trauma, either postsurgical or accidental injury, but the mechanism of chylothorax caused by nephrotic syndrome is still unclear. Here, we report a case of primary nephrotic syndrome with membranous nephropathy (MN) in a 66-year-old man who presented with severe chylothorax. The chylothorax was managed by intercostal chest tube drainage, subcutaneous injection of enoxaparin, and treatment with anti-inflammatory agents and diuretics. After treatment, the patient's pleural effusion decreased, and the chyle gradually became clear. We discuss the causes of MN with chylothorax. We considered that the hypoproteinemia changed the permeability of mucous membranes and lymphatic vessels, leading to leakage of chylous particles and chylous pleural effusion formation. Chylothorax may also have been caused by severe tissue edema, edema of the lymphatic walls, and increased pressure, resulting in increased permeability or rupture of the lymphatic wall, and leakage of chylous fluid into the thoracic cavity. Because of its rarity, we hope this case report will improve clinicians' understanding of MN complications in primary nephrotic syndrome and provide suitable treatment options for future clinical reference.

We systemically identified tuberculosis (TB)-related DNA methylation biomarkers and further constructed classifiers for TB diagnosis. TB-related DNA methylation datasets were searched through October 3, 2020. Limma and DMRcate were employed to identify differentially methylated probes (DMPs) and regions (DMRs). Machine learning methods were used to construct classifiers. The performance of the classifiers was evaluated in discovery datasets and a prospective independent cohort. Eighty-nine DMPs and 24 DMRs were identified based on 67 TB patients and 45 healthy controls from 4 datasets. Nine and three DMRs were selected by elastic net regression and logistic regression, respectively. Among the selected DMRs, two regions (chr3: 195635643–195636243 and chr6: 29691631–29692475) were differentially methylated in the independent cohort (p = 4.19 × 10−5 and 0.024, respectively). Among the ten classifiers, the 3-DMR logistic regression classifier exhibited the strongest performance. The sensitivity, specificity, and area under the curve were, respectively, 79.1%, 84.4%, and 0.888 in the discovery datasets and 64.5%, 90.3%, and 0.838 in the independent cohort. The differential diagnostic ability of this classifier was also assessed. Collectively, these data showed that DNA methylation might be a promising TB diagnostic biomarker. The 3-DMR logistic regression classifier is a potential clinical tool for TB diagnosis, and further validation is needed., Graphical abstract, We systemically identified TB-related DNA methylation biomarkers and constructed diagnostic classifiers. A 3-DMR logistic regression classifier showed excellent performance in discovery datasets and a prospective cohort. DNA methylation might be a promising TB-related biomarker and the 3-DMR logistic regression classifier is a potential clinical tool for TB diagnosis.

This paper presents a bidirectional Thermo-resistive Micro Calorimetric Flow (TMCF) sensor implemented by a 0.18 m CMOS-MEMS technology, while the sensor thickness is thinned to 2.7 m through an in-house developed MEMS fabrication process. For the bidirectional airflow of -6 ~ 6 m/s, the TMCF sensor achieves the highest sensitivity of 453 mV/(m/s), and its highest normalized sensitivity with respect to the signal amplification gain (gain = 250) and the input heating power (1.58 ~ 1.72 mW) is 1150 mV/(m/s)/W. By reducing the heating power to the sub-mW of < 220 W, the TMCF sensor can still give a remarkable sensitivity of 87.4 mV/(m/s). In addition, the developed TMCF sensor has an intrinsic minimum detectable flow velocity (MDFV) of 99 m/s and a response time of 4.8 ms. The performance achieved by this flow sensor enables accurate indoor airflow measurements even when dealing with the extremely low-speed flow (< 0.05 m/s). Furthermore, the high-performance TMCF sensor is applied for remote human motion detection, where different walking speeds and moving patterns of the occupants can be captured. Therefore, this developed CMOS-MEMS sensor will not only be a promising flow sensing node in the HVAC system, but also potentially be used for the non-visible and private occupant counting in buildings/rooms.

Recent advances in small cell lung cancer (SCLC) treatments necessitate a better understanding of real-world health utility scores (HUS) in patients treated under current standards to facilitate robust pharmaco-economic assessments.In this single institution cohort observational study, HUS were evaluated in patients with SCLC through EQ-5D questionnaires at outpatient visits (encounters). In addition, patients completed questionnaires relating to treatment toxicities and cancer symptoms. Clinical and pathological variables were abstracted from electronic medical records and disease status at each patient visit was documented. The impact of these variables on HUS were explored.There were 282 clinical encounters (12% newly diagnosed; 37% stable on treatment; 22% progressing on treatment; 29% stable off therapy/other) in 111 SCLC patients (58% male; 64% extensive stage (ES) SCLC). At the first encounter 29% of patients had an ECOG performance status (PS) ≥ 2. ES-SCLC, bone metastases, female sex, progressive disease and/or PS were each significantly associated with decreased HUS in multivariable analyses. Patients clinically stable on first line therapy had generally steady HUS longitudinally, with differences in HUS between limited disease (LD) and ES patients emerging as treatment progressed. Decreased HUS were associated with increased severity of the majority of measured symptoms (fatigue/tiredness, loss of appetite, pain, drowsiness, shortness of breath, anxiety, depression, and overall well-being; each p0.001), supporting the value of EQ-5D-derived HUS in assessing health utility.Our HUS values in chemotherapy-treated SCLC are clinically relevant and are associated with specific clinico-demographic, symptom and toxicity factors.

Conventional finite element analysis (FEA) performed in electromagnetic-vibration coupling calculation of motor suffers from several significant drawbacks, such as large memory space, high computational cost and heavy reliance on mesh quality for accurate solution. With the traditional meshless method, special attention needs to be paid to correctly impose the boundary condition like FEA. Besides, the matrix is easily​​prone to be ill-conditioned due to introducing large amount of higher order basis functions. We propose a novel multiphyscial coupling method combining FEA and optimized meshless method. The proposed methodology is further evaluated on the vibration analysis of a 12-slot 10-pole permanent magnet synchronous motor (PMSM). Firstly, 2D stator electromagnetic force is simulated and derived based on the local Jacobian derivative method through FEA. The electromagnetic force spectrum is calculated using FFT analysis and further imported into commercial meshless structural simulation software Simsolid for stator harmonic response analysis. Correct force boundary condition and data mapping between meshless and FEA simulation interface is key to the accuracy of the proposed combined multiphysical modeling methodology. This is achieved by introducing a new high dimensional ramp function in the transition region between FEA and meshless domains, which are defined with the shape functions composed of the FEA and meshless method. This function satisfies the continuity and consistency of the displacement function, ensures the convergence of coupled FEA-meshless method. Subsequently, construction of basis function is key to the establishment of convention meshless discrete equation for the elastic problem of rotating machinery. This is designed using moving least square theory in cylindrical coordinate system. The harmonic response with meshless method is analyzed using a mode superposition method to obtain detailed mode shape data, acceleration and displacement distribution of stator. Finally, the tangential continuity and robustness are not well considered in the traditional simulation with FEA coupled meshless method. To mitigate this problem, we propose an optimized meshless method based on modified local basis functions to recalculate the harmonic response motion. Then the coupling electromagnetic-vibration simulation results of traditional coupled FEA-meshelss method, optimized coupled FEA-meshless method and complete FEA coupled method are compared. It is worth noting that optimized method significantly improves accuracy, robustness and computational speed at the same time. In short, the proposed electromagnetic-structure coupling calculation method provides a novel alternative for the multiphysical coupling calculation of rotating machinery combining FEA and meshless simulation methods.

This paper proposes the concept of “sub-wet bulb temperature” for the application of evaporative cooling technology, discusses the principle and implementation approach of the indirect-direct evaporative chiller for producing sub-wet bulb temperature cold water, and puts forward a way to describe the cooling performance of the pre-cooling section of indirect evaporative cooling through “sub-wet bulb efficiency”, using the “cooling efficiency of the water drenching filler on the air side and the water side” to show the cooling performance of the direct evaporative cooling section of the Water drenching filler, and utilizing the “unit's chilled water efficiency” to describe the cooling performance of the whole unit, and then explicit equation for predicting the unit's water supply temperature is derived out. The cooling performance of evaporative cooling chillers under different ambient air pre-cooling types was tested in Xinjiang region. The results showed that the chilled water efficiency of evaporative chillers reached a maximum value of 45.9 under the coil and vertical tube type of indirect evaporative pre-cooling form. At this time, the sub-wet bulb efficiency of the pre-cooling section of indirect evaporative cooling is 52.1%, the cooling efficiency of the water drenching filler on the air side has reached to 59.8%, and the water supply temperature of the unit is 13.7 °C, which is 2.3 °C lower than the wet bulb temperature of ambient air.

An industrial process usually has multiple operating conditions or periods due to various factors such as the fluctuation of raw material quality, differences of worker levels, and changes of product specifications. Industrial data from different operating conditions or periods have different statistical characteristics, namely multimode behavior. In fact, multimode recognition of industrial processes is the first problem to develop effective intelligent manufacturing strategies for engineers. The clustering-based methods can help them characterize multimode behavior in historical databases and group them together with little detailed knowledge of the process. However, these methods are facing the challenges of massive high-dimensional industrial big data and unknown mode number. This study proposes a construction method of complex network to describe the potential relationship in industrial big data. The topological structure of complex network can be acquired by taking the correlation matrix of multi-variables as nodes and the similarity between correlation matrices as edges. On this basis, community detection technology is employed to reveal the aggregation behavior of nodes in network. It takes the maximum modularity as the optimization objective, and partitions each node into one community through greedy search algorithm, where a community denotes a mode of industrial process. Finally, case studies have demonstrated the proposed method has good performance and application prospects.

The kernel principal component analysis (KPCA) is widely used as a fault monitoring tool for complex nonlinear chemical processes in recent years. The cumulative contribution rate that extracts the kernel principal is usually obtained relied on a fixed model, which cannot be employed for time-varying chemical processes. Hence, a novel adaptive kernel principal component analysis (AKPCA) integrating grey relational analysis (GRA) (AKPCA-GRA) is proposed to dynamically monitor the fault occurrence. A moving window integrating the threshold method is used to adaptively extract the kernel principal for chemical processes. Then the corresponding T2 and Q statistics calculated by the selected kernel principal based on the AKPCA decides whether the fault has occurred. Moreover, the GRA method is used to analyze and calculate the correlation coefficient of abnormal features obtained based on the APKCA method, which provides the operational guidance for the nonlinear chemical process to find out the variable causing the fault. Finally, the proposed method is verified using the Tennessee Eastman (TE) process. The case results demonstrate that the proposed method outperforms the KPCA, the KPCA based on the threshold and the moving window principal component analysis, the support vector machine (SVM) and the Logistic Regression (LR) in terms of the missed alarm rate (MAR) and the false alarm rate (FAR), which can effectively analyze the variables causing the fault.

BACKGROUND: It remains unclear if patients with allergic rhinitis (AR) and/or asthma are susceptible to corona virus disease 2019 (COVID-19) infection, severity, and mortality. OBJECTIVE: To investigate the role of AR and/or asthma in COVID-19 infection, severity, and mortality, and assess whether long-term AR and/or asthma medications affected the outcomes of COVID-19. METHODS: Demographic and clinical data of 70,557 adult participants completed SARS-CoV-2 testing between March 16 and December 31, 2020, in the UK Biobank were analyzed. The rates of COVID-19 infection, hospitalization, and mortality in relation to pre-existing AR and/or asthma were assessed based on adjusted generalized linear models. We further analyzed the impact of long-term AR and/or asthma medications on the risk of COVID-19 hospitalization and mortality. RESULTS: Patients with AR of all ages had lower positive rates of SARS-CoV-2 tests (relative risk [RR]: 0.75, 95% confidence interval [CI]: 0.69-0.81, P < .001), with lower susceptibility in males (RR: 0.74, 95% CI: 0.65-0.85, P < .001) than females (RR: 0.8, 95% CI: 0.72-0.9, P < .001). However, similar effects of asthma against COVID-19 hospitalization were only major in participants aged

In current wireless communication and electronic systems, digital signals and electromagnetic (EM) radiation are processed by different modules. Here, we propose a mechanism to fuse the modulation of digital signals and the manipulation of EM radiation on a single programmable metasurface. The programmable metasurface consists of massive subwavelength-scale digital coding elements. A set of digital states of all elements forms simultaneous digital information roles for modulation and the wave-control sequence code of the programmable metasurface. By designing digital coding sequences in the spatial and temporal domains, the digital information and far-field patterns of the programmable metasurface can be programmed simultaneously and instantly in desired ways. For the experimental demonstration of the mechanism, we present a programmable wireless communication system. The same system can realize transmissions of digital information in single-channel modes with beam-steerable capability and multichannel modes with multiple independent information. The measured results show the excellent performance of the programmable system. This work provides excellent prospects for applications in fifth- or sixth-generation wireless communications and modern intelligent platforms for unmanned aircrafts and vehicles.

A quad-band metamaterial absorber operating in the terahertz region is demonstrated in this paper. The basic cell of the device consists of three metallic strips (forming an asymmetric I-type resonator) placed on both layers of an insulating medium slab and a metallic ground plane. The asymmetric I-type resonator can interact strongly with the incident beam, resulting in four distinct absorption peaks with nearly 100% absorbance. The underlying mechanism of the quad-band absorption is investigated with the aid of their near-field distributions resulting from the calculation results of the numerical simulation. Results further prove that the four distinct absorption peaks exhibit large dependence on the dimension changes of the asymmetric I-type resonator (or three metallic strips). Based on this, we design a kind of terahertz metamaterial absorber which can effectively control the number of absorption peaks by replacing one of the metallic strips with photosensitive silicon. It is revealed that the number of absorption peaks can be adjusted from the dual-band to the quad-band when an external stimulus changes the conductivity of the photosensitive silicon. These absorption properties should have great application prospects in terms of thermal imaging, Raman enhancement, sensing and detection, etc.

Azimuth multichannel synthetic aperture radar (SAR) working in the sliding spotlight mode can effectively achieve ultrahigh resolution and wide swath imaging. However, multichannel sliding spotlight SAR echoes with large pulse bandwidth and azimuth steering angle are difficult to reconstruct and process due to the large range frequency-dependent Doppler centroid varying frequency support. To resolve this problem, two azimuth preprocessing approaches both based on the range frequency-dependent deramping strategy are proposed in this article. In both approaches, echoes are handled by a range frequency-dependent azimuth deramping function at first, which assign the signal measurements to unambiguous Doppler frequencies. Afterward, in the first preprocessing approach, azimuth multichannel raw data can be reconstructed and combined before azimuth upsampling in the conventional two-step preprocessing technique. The other way to handle the deramped multichannel raw data is the modified full aperture azimuth multichannel sliding spotlight reconstruction approach, which embeds azimuth multichannel reconstruction into azimuth convolution between the deramped raw data and the selected range frequency-dependent azimuth deramping function. Furthermore, the azimuth data in the second approach should be resampled to obtain a uniform azimuth sampling interval. Computational complexity and effects on the following imaging algorithm of both approaches are analyzed and compared. Simulation results validate the proposed two azimuth multichannel preprocessing approaches.

In this paper, the performance of a secure massive multiple-input multiple-output (MIMO) system adopting low-resolution digital-to-analog converters (DACs) is analyzed over spatially correlated wireless channels. A tight lower bound for the achievable secrecy rate is derived with artificial noise (AN) transmitted in the null space of the user channels. Using the analytical results, the impact of spatial correlation on the secrecy rate is explicitly evaluated in the presence of low-resolution DACs. The analytical observations reveal that using low-resolution DACs can be beneficial to the secrecy performance compared with ideal DACs, when the channels are strongly correlated and optimal power allocation is not employed., Comment: accepted by IEEE Wireless Communication Letters

BACKGROUND Creutzfeldt-Jakob disease (CJD) is a rare degenerative disease of the central nervous system that can be contagious or hereditary and is a rare cause of rapidly progressive dementia. It almost always results in death within 1-2 years from symptom onset. CASE SUMMARY Here, we report the case of a 57-year-old male who initially experienced dizziness followed by a 1-mo fast decline in memory function. He presented to the local hospital and underwent magnetic resonance imaging and cerebrospinal fluid (CSF) examination, with no definitive diagnosis. However, the symptoms of progressive forgetting worsened. In addition, he exhibited progressive involuntary tremor of the limbs. Then, he came to our hospital, and according to the results of CSF examination, electroencephalography (EEG) and magnetic resonance imaging (MRI) tests and clinical manifestations of cerebellar ataxia, dementia, and myoclonus that rapidly progressed, with a short duration of illness, he was finally diagnosed with sporadic CJD (sCJD). CONCLUSION This case report aims to create awareness among physicians to emphasize auxiliary examination, CSF examination, EEG and MRI tests and recognition of cerebellar ataxia, dementia, and myoclonus that rapidly progress to prompt pursuit of an early diagnosis and identification of sCJD and to reduce complications.

We present an electron backscattered diffraction (EBSD)-trained deep learning (DL) method integrating traditional material characterization informatics and artificial intelligence for a more accurate classification and quantification of complex microstructures using only regular scanning electron microscope (SEM) images. In this method, EBSD analysis is applied to produce accurate ground truth data for guiding the DL model training. An U-Net architecture is used to establish the correlation between SEM input images and EBSD ground truth data using only small experimental datasets. The proposed method is successfully applied to two engineering steels with complex microstructures, i.e., a dual-phase (DP) steel and a quenching and partitioning (Q&P) steel, to segment different phases and quantify phase content and grain size. Alternatively, once properly trained the method can also produce quasi-EBSD maps by inputting regular SEM images. The good generality of the trained models is demonstrated by using DP and Q&P steels not associated with the model training. Finally, the method is applied to SEM images with various states, i.e., different imaging modes, image qualities and magnifications, demonstrating its good robustness and strong application ability. Furthermore, the visualization of feature maps during the segmenting process is utilised to explain the mechanism of this method's good performance.

PURPOSE To confirm the prognostic value of radiologic extranodal extension (rENE) and its role in clinical-N classification in nasopharyngeal carcinoma (NPC) treated in a western institution. METHODS AND MATERIALS NPC treated between 2010 and 2017 were included. Pre-treatment MRI were reviewed for unequivocal rENE and its grade: grade-1: tumour invading through any nodal capsule but confined to perinodal fat; grade-2: ≥2 adjacent nodes forming a coalescent nodal mass; grade-3: tumour extending beyond perinodal fat to invade/encase adjacent structures. Overall survival (OS) and disease-free survival (DFS) were compared between rENE-positive (rENE+) and rENE-negative (rENE-) patients. Multivariable analysis (MVA) confirmed the prognostic importance of rENE and its grade. Staging schemas including rENE in N-classification were proposed and their performance evaluated. RESULTS A total of 274 patients were eligible (43 cN0; 231 cN-positive). rENE was identified in 83/231 (36%) cN-positive, including grade 1/2/3 rENE in 14/58/11 cases. Compared to rENE-, rENE+ patients had a lower OS (68% vs 89%, p

To improve the efficiency of cable force adjustment of composite saddle anchor span of single-tower single-span ground-anchored suspension bridge, a strain incremental adjustment method is proposed. The analytical calculation model is established according to the relative spatial position of the cable strand and the saddle groove of the composite saddle, and the target cable force of the cable strands is calculated by the target position of the composite saddle in the cable-stayed bridge and construction phases. Considering the coupling relationship between the cable strand and the composite saddle, the calculation formula of the change in main span main cable force and anchor span cable force after the adjustment of a single cable strand is derived. Based on the condition of equilibrium of forces along the slip surface of the composite saddle, the slip amount of composite saddle after a round of cable strand adjustment is obtained, then the adjustment amount of actual construction of the cable strands is also obtained through the strain incremental adjustment method. With the help of a numerical simulation platform, the calculation program of the cable force adjustment of composite saddle anchor span is established by an iterative solution method. In this paper, taking the Jinsha River Bridge at Hutiao Gorge as a research object, the adjustment of cable force of composite saddle anchor span is analyzed and calculated. The research results indicate that the calculated cable force is obtained by the strain incremental adjustment method, and it is similar to the measured cable force. The cable strand adjustment and optimization method avoids excessive repeated stretching and relaxation of a single cable strand in the process of multiple rounds of cable strand adjustment and reduces the amount of construction adjustment. This method can effectively reduce the times of cable strand adjustment and improve the efficiency of adjusting the anchor span cable force.

Cold metal transfer (CMT) additive manufacturing (AM) is widely used for its efficiency and low cost, in order to improve the efficiency the manufacturing,this study carried out CMT arc modes and i...

Patents, as technological innovation with commercial values, play a significant role for increasing enterprise and national competitiveness. Personalized recommendation in online patent marketplace would help patent buyers effectively identify their demands from the deluge of patents. However, state-of-the-art patent recommendation methods focus mainly on increasing recommendation effectiveness while ignoring patent quality and recommendation explainability. The glut of low-quality products in patent trading platforms reduces patent buyers’ trust and would further damage the patent market due to their weak technological competitiveness and low market potential. Besides, there is a need to differentiate the varied semantics (e.g., textual content, patent classification and citation) enriched in patent documents when recommending patents to potential buyers. To solve the problems, this research proposed a framework of personalized patent recommendation system by leveraging hybrid patent analysis. The system designs an improved high-quality patent identification method by including patent inventors’ reputation as a new indicator. Moreover, an innovative patent preference analysis is proposed by analyzing a potential buyer’s intra-collection patent citation network. Last, the content-based strategy, classification-based strategy and citation-based strategy are separately introduced for transparent patent recommendation. The offline experiment on patent quality indicators reveals that inventor reputation as a new quality indicator helps identify high-quality patents besides the widely-used quality indicators. The simulation experiment of patent recommendation validates the effectiveness of different recommendation strategies. The proposed recommendation framework was implemented on a real-world patent trading platform and achieved good performance.

Anti-CD19 chimeric antigen receptor (CAR) T cell therapy has shown impressive efficacy in treating B-cell malignancies. A single-center phase I dose-escalation study was conducted to evaluate the safety and efficacy of T cells transduced with CBM.CD19 CAR, a second-generation anti-CD19 CAR bearing 4-1BB costimulatory molecule, for the treatment of patients with refractory diffuse large B-cell lymphoma (DLBCL). Ten heavily treated patients with refractory DLBCL were given CBM.CD19 CAR-T cell (C-CAR011) treatment. The overall response rate was 20% and 50% at 4 and 12 weeks after the infusion of C-CAR011, respectively, and the disease control rate was 60% at 12 weeks after infusion. Treatment-emergent adverse events occurred in all patients. The incidence of cytokine release syndrome in all grades and grade ⩾ 3 was 90% and 0, respectively, which is consistent with the safety profile of axicabtagene ciloleucel and tisagenlecleucel. Neurotoxicity or other dose-limiting toxicities was not observed in any dose cohort of C-CAR011 therapy. Antitumor efficacy was apparent across dose cohorts. Therefore, C-CAR011 is a safe and effective therapeutic option for Chinese patients with refractory DLBCL, and further large-scale clinical trials are warranted.

The development of remote frequency transfer techniques, especially the appearance of optical clocks with unprecedented stability, has prompted geoscientists to study their applications in geodesy. Using remote frequency transfer technique, by frequency comparison of two optical clocks at two points P and Q connected by optical fibers, one can measure the signal's frequency shift between them, and the geopotential difference between them can be determined based on the gravity frequency shift equation. Given the orthometric height of P, the orthometric height of Q can be determined. Since the present stability of the optical clock has achieved 1 × 10−18 or better and comparing the frequency transfer via optical fiber provides stability at 10−19 level, the optical clock network enables determining the orthometric height at centimeter-level. This study provides a formulation to determine the height difference at one-centimeter level between two points on the ground based on the optical fiber frequency transfer technique.

We present a vertically aligned multiwall carbon nanotube (VA-MWCNT) based humidity sensor with low cost and simple fabrication method compatible with mass production. The VA-MWCNT is well aligned and possesses an interconnect topography. Initially, the VA-MWCNT showed superhydrophobic characteristics, which are not suitable for humidity sensing. Therefore, to protect the topography of the material and make the surface more hydrophilic, a low cost and easy handling treatment method was adopted with O2 plasma surface functionalization. The fabricated device showed good linearity at the range of 40% RH–90% RH, low hysteresis ( H = 1.5%RH), fast response (3.3 s), high stability ( Cv Rr _max 0.6% ), demonstrating excellent performance in both static and dynamic measurements. The high performance and low-cost fabrication methods make the VA-MWCNT-based sensor a promising candidate for the application of humidity sensing. Moreover, benefiting from the simple fabrication process, it can be easily extended to resistive sensing fusion with the integration of the temperature sensor and flow sensor for more complex applications.

This letter investigates a wireless communication system deploying distributed reconfigurable intelligent surfaces (RISs). Existing works have assumed that perfect timing synchronization is available among all the cooperative RISs. For practical considerations, we first study cooperative reflection design for multi-RIS-aided communication systems taking into account timing synchronization errors. We aim to minimize the mean-squared error of the recovered data in the presence of timing offsets subject to the unit modulus constraints imposed on the phase shifts of the RISs. In order to handle this sophisticated nonconvex problem, we develop a computationally-efficient algorithm based on the majorization-minimization framework where the RIS phase shift matrices and the timing offset equalizer are respectively developed in a semi-closed form and a closed form. Numerical examples validate the improved performance of our proposed design compared with various schemes.

In this paper, we report an optimized CMOS compatible MEMS thermoresistive calorimetric air velocity (TMCV) sensor to measure small air velocity in an indoor environment for the application of human thermal comfort sensing. The sensor is comprised of two upstream thermistors, two downstream thermistors, and a micro-heater placed in between the upstream thermistors and downstream thermistors. The dimensions of the sensor were optimized to achieve better linearity and accuracy in the tiny air velocity (−1 m/s to 1 m/s) range based on the CFD simulation. Furthermore, to reduce the heating power and increase the normalized sensitivity, the sensor was completely released from the substrate using the DRIE process. The sensor was successfully tested both in a lab in a wind tunnel and a real indoor environment. The sensor achieved a maximum sensitivity of 340.2 mV/(m/s), and normalized sensitivity, with respect to heating power and gain, of $354.37~\mu \text{V}$ /(m/s)/mW within −5 m/s to 5 m/s air velocity range. The normalized sensitivity achieved by our sensor is much higher than most of the reported TMCV sensors. Besides, the sensor obtained a good linearity ( ${R}^{2}=0.9996$ ) and accuracy (±0.0236 m/s) within the small air velocity range meeting the standard accuracy requirement ( $0~\sim ~0.5$ m/s) produced by the HVAC system. The experimental results indicated that our sensor is quite suitable for smart HVAC system integration in the era of the Internet of Things (IoT).

Unmanned aerial vehicle (UAV) photogrammetry without ground control points (GCPs) can effectively improve production efficiency and reduce production costs; this method is especially advantageous in areas that are difficult for people to reach. However, there are a series of problems in UAV photogrammetry without GCPs. One of the main problems is that the accurate camera parameters cannot be obtained through the on-the-job calibration method; furthermore, the inaccurate principal distance will have a serious impact on the elevation accuracy of object points. The other one is that the projection deformation and earth curvature also have impacts on the elevation accuracy, when the mapping task is carried out in the map projection frame. This article explains the specific reasons of elevation errors and proposes an effective solution. First, the camera self-calibration is performed in a geocentric frame with control strips. Then, the exterior orientation elements of the images are calculated in the map projection frame without control strips. Finally, the elevation errors that are caused by the map projection deformation and the earth’s curvature are corrected. The experimental results show that the proposed method can achieve accurate mapping, and the elevation accuracy has been significantly improved.

Reconfigurable intelligent surfaces (RISs) can shape the wireless environment for enhancing the communication performance. In this letter, we propose a cooperative multi-RIS assisted transmission scheme for a millimeter-wave multi-antenna orthogonal frequency division multiplexing system. We first put forward a delay matching based scheme for simultaneously estimating the multipath channels and the transmission delays of distributed RISs, which requires limited training overhead and feedback. Based on this scheme, we obtain a closed-form solution for the RIS phase shift. Then, we derive an analytical expression of the downlink rate, which is proved to increase logarithmically with the square number of RIS reflecting elements. Simulations are conducted to verify these observations.

Recyclable thermosets and thermoset composites with covalent adaptable networks (CANs, or dynamic covalent networks) have attracted considerable attention in recent years due to the combined merits of excellent mechanical and thermal properties, and chemical stabilities of traditional thermosets and recyclable, remoldable, and reprocessable attributes of thermoplastics. In this paper, we present an overview of the current strategies for synthesizing recyclable thermosets based on CANs, which involve recyclability, reprocessability, and possible rehealability. The recent literature examples are categorized based on the underlying controlled-cleavable linkages such as transesterification, DA/retro-DA chemistry, imine bonds, disulfide metathesis, dynamic B-O bonds, hemiaminals/hexahydrotriazines, and acetal linkages. Various degradation and malleability methods and resulting mechanical properties of the recycled thermosets and thermoset composites are presented. The emerging applications of recyclable thermosets and thermoset composites, with emphasis on their usage in adhesives, biomedical materials, wearable devices, coatings, and 3D printing materials, are also illustrated. Finally, a perspective on the challenges and future perspectives is briefly summarized.

Background The imaging features of focal liver lesions (FLLs) are diverse and complex. Diagnosing FLLs with imaging alone remains challenging. We developed and validated an interpretable deep learning model for the classification of seven categories of FLLs on multisequence MRI and compared the differential diagnosis between the proposed model and radiologists. Methods In all, 557 lesions examined by multisequence MRI were utilised in this retrospective study and divided into training–validation (n = 444) and test (n = 113) datasets. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the performance of the model. The accuracy and confusion matrix of the model and individual radiologists were compared. Saliency maps were generated to highlight the activation region based on the model perspective. Results The AUC of the two- and seven-way classifications of the model were 0.969 (95% CI 0.944–0.994) and from 0.919 (95% CI 0.857–0.980) to 0.999 (95% CI 0.996–1.000), respectively. The model accuracy (79.6%) of the seven-way classification was higher than that of the radiology residents (66.4%, p = 0.035) and general radiologists (73.5%, p = 0.346) but lower than that of the academic radiologists (85.4%, p = 0.291). Confusion matrices showed the sources of diagnostic errors for the model and individual radiologists for each disease. Saliency maps detected the activation regions associated with each predicted class. Conclusion This interpretable deep learning model showed high diagnostic performance in the differentiation of FLLs on multisequence MRI. The analysis principle contributing to the predictions can be explained via saliency maps.

Owing to the ever increasing of information privacy requirement, covert communication has gained more and more attention, whose effective range is limited by the trade-off between the covertness and the transmit power. Benefiting from the high mobility and easy deployment, unmanned aerial vehicles (UAVs) can be utilized to expand the range of covert networks. Thus, we propose a UAV-relayed covert communication scheme with finite blocklength to maximize the effective transmission bits from the transmitter to the legitimate receiver against a flying warden. The transmitter adopts the maximum ratio transmission and the relay performs Gaussian signalling transmission to cause uncertainty at the warden. First, the optimal detection thresholds are derived at the warden towards the transmitter and the relay, respectively. Then, the hovering location of the warden is optimized to maximize the summation of relative entropies from the transmitter and the relay, which can greatly threaten the covertness. With this worst covert situation, the blocklength and transmit power at the transmitter and the relay are jointly optimized under the constraint of the end-to-end error detection probability to maximize the effective transmission rate from the transmitter to the legitimate receiver. Numerical results are provided to demonstrate the effectiveness of the proposed UAV-relayed covert communication scheme.

Background A universally acknowledged cancer staging system considering all aspects of the T‐, N‐, and M‐classifications for middle ear squamous cell carcinoma (MESCC) remains absent, limiting the clinical management of MESCC patients. Materials and Methods A total of 214 MESCC patients were extracted from the SEER (the Surveillance, Epidemiology, and End Results) database between 1973 and 2016. The relationships between patient’s characteristics and prognoses were analyzed by Kaplan–Meier and Cox proportional hazards regression models. Novel staging schemes for MESCC were designed by adjusted hazard ratio (AHR) modeling method according to the combinations of Stell’s T‐classification and the eighth AJCC N‐ and M‐classifications, of which performances were evaluated based on five criteria: hazard consistency, hazard discrimination, explained variation, likelihood difference, and balance. Results T‐classification was the most significant prognostic factor for MESCC patients in multivariable analysis (p = 0.021). The N‐ and M‐classifications also had obvious prognostic effect but were not statistically significant by multivariate analysis due to the limited metastasis events. Three novel staging schemes (AHR‐Ⅰ–Ⅲ models, different combination of T‐ and N‐classifications) and ST (solely derived from Stell’s T‐classification) were developed, among which the AHR‐Ⅰ staging scheme performed best. Conclusions Tumor extension, quantified by Stell’s T‐classification, is the most significant prognostic factor for MESCC patients. However, our AHR‐Ⅰ staging scheme, a comprehensive staging scheme that integrating T‐, N‐, and M‐classifications, might be an optimal option for clinical practitioners to predict MESCC patients’ prognosis and make proper clinical decisions., All of Stell’s T‐classification, N‐ and M‐classifications of the eighth AJCC staging system for head and neck cancer showed obvious prognostic effects in middle ear squamous cell carcinoma (MESCC) patients. Stell’s T‐classification is the most significant as well as an independent prognostic factor for MESCC patients. Our newly developed AHR‐Ⅰ staging scheme displayed better performance than the Stell’s T‐classification in almost all existing criterion, which stresses the importance of a comprehensive staging scheme integrating T‐, N‐, and M‐classifications for MESCC and provides a new perspective for clinical practitioner who solely rely on tumor extension for making clinical decisions.

Mesenchymal stem cells (MSCs) are adult stem cells from mesoderm with multi potential differentiation, and are being widely studied as a promising treatment for autoimmune diseases. The main inflammatory factors of experimental autoimmune uveitis (EAU) are T helper type 1 (Th1) and Th17. Regulatory B cells (Bregs) are a newly designated B cell subgroup, which has been proved to play a key role in regulating inflammation, autoimmunity and cancer. In this regard, we establish the EAU model by injecting interphotoreceptor retinoid-binding protein combined with complete Freund's adjuvant into the tail vein and bilateral thighs of rats, and inject MSCs or equal volume of phosphate buffer saline intraperitoneally on the day of immunization. Dynamic changes of cell subsets and cytokine expression are tested at different time periods to explore the relationship between MSCs treatment and disease prognosis during EAU course. Our results suggest that compared with the model control group, MSCs treatment can significantly reduce the production of Th1 and Th17 cytokines during EAU, while the production of regulatory B cells (Bregs) cytokines is significantly increased. At the same time, MSCs can reduce the proportion of Th17 in lymphocytes while the proportion of Bregs is elevated, thus inhibiting the differentiation and activity of interleukin in EAU rats. All this results provide more powerful evidence for cell therapy of autoimmune uveitis.

OBJECTIVE This study was performed to assess the effects of vitamin D deficiency/insufficiency combined with a high body mass index (BMI) on paraspinal muscle (PSM) atrophy and pain intensity in postmenopausal women with lower back pain (LBP). METHODS In total, 365 postmenopausal women were analyzed in the study. We divided the women into four groups according to BMI and vitamin D status. Outcome measurements included PSM atrophy, fatty infiltration (FI) and severity of LBP. Binary logistic regression was used to analyze the odds ratio (OR), and the interaction between the BMI and vitamin D status was tested. RESULTS Compared with the control group, the high BMI with vitamin D deficiency/insufficiency group had a significantly increased risk of FI > grade 2 (OR = 10.69, p 3 (OR = 4.76, p

To evaluate the efficacy of acupuncture combined with rehabilitation training in patients with intensive care unit (ICU)-acquired muscle weakness (ICUAW), a single-blinded, randomized, sham-controlled clinical trial is designed for execution. In total, 56 participants with ICUAW will be randomly assigned to the treatment and control groups with 28 participants in each group. The participants will be treated with acupunctures or sham procedures at LI15, LI11, ST36, GB34, and ST31, 5 times per week for a total of 20 sessions in 4 weeks while they will receive rehabilitation training. Patients will be followed up every month for 3 months after treatment. The primary outcomes include changes in quadriceps femoris muscle area, thickness, vastus intermediate muscle thickness, subcutaneous tissue thickness, and ultrasonic intensities of the rectus femoris. The secondary outcomes consist of the modified Barthel index score and the Medical Research Council total score. Participants’ mechanical ventilation, the rate of detachment at the second week, the 28-day survival rate, and the occurrence of adverse reactions will be measured, and any side effects will be reported and recorded. Patient outcomes between the treatment and control groups will be compared and statistically tested. We anticipate that the therapeutic regimen of acupuncture combined with rehabilitation training would be more effective than the rehabilitation training alone for the treatment of the ICUAW. The findings of this study could help develop a better strategy for the treatment of the ICUAW disease and explore a clinical application of an acupuncture technique. Trial registration: Chinese Clinical Trial Register ChiCTR2000038779. Registered 30 September, 2020, https://www.chictr.org.cn/showproj.aspx?proj=62284.

Germline variants might predict cancer progression. Bevacizumab improves overall survival (OS) in patients with advanced cancers. No biomarkers are available to identify patients that benefit from bevacizumab. A meta-analysis of genome-wide association studies (GWAS) was conducted in 1,520 patients from Phase III trials (CALGB 80303, 40503, 80405 and ICON7), where bevacizumab was randomized to treatment without bevacizumab. We aimed to identify genes and single nucleotide polymorphisms (SNPs) associated with survival independently of bevacizumab treatment or through interaction with bevacizumab. A cause-specific Cox model was used to test the SNP-OS association in both arms combined (prognostic), and the effect of SNPs-bevacizumab interaction on OS (predictive) in each study. The SNP effects across studies were combined using inverse variance. Findings were tested for replication in advanced colorectal and ovarian cancer patients from The Cancer Genome Atlas (TGCA). In the GWAS meta-analysis, patients with rs680949 in PRUNE2 experienced shorter OS compared to patients without it (P = 1.02 × 10-7 , hazard ratio [HR] = 1.57, 95% confidence interval [CI] 1.33-1.86), as well as in TCGA (P = .0219, HR = 1.58, 95% CI 1.07-2.35). In the GWAS meta-analysis, patients with rs16852804 in BARD1 experienced shorter OS compared to patients without it (P = 1.40 × 10-5 , HR = 1.51, 95% CI 1.25-1.82) as well as in TCGA (P = 1.39 × 10-4 , HR = 3.09, 95% CI 1.73-5.51). Patients with rs3795897 in AGAP1 experienced shorter OS in the bevacizumab arm compared to the nonbevacizumab arm (P = 1.43 × 10-5 ). The largest GWAS meta-analysis of bevacizumab treated patients identified PRUNE2 and BARD1 (tumor suppressor genes) as prognostic genes of colorectal and ovarian cancer, respectively, and AGAP1 as a potentially predictive gene that interacts with bevacizumab with respect to patient survival.

Background Outbreaks of dengue fever are often found among Dai ethnical communities along China-Myanmar border. The objective of this study was: 1) to investigate residents’ health perceptions, knowledge and control willingness to participate in dengue control and 2) to identify factors associated with control willingness among the Dai ethnic community. Methods This is a mixed method study of a cross-sectional design, in which qualitative in-depth interviews and quantitative household questionnaire surveys are included. Results Questionnaire was administered to 261 household heads, and in-depth interview was conducted with 18 key informants. Of them, many participants (70%, 182/259) and 12 key informants (66.7%) from the two rural communities believed that the Lord Buddha would protect the good people. Majority of the participants (81.4%, 206/253) knew that fever was one of dengue fever symptoms and most of them (82.2%, 213/259) indicated that mosquitoes could transmit dengue fever. However, only one third of the participants (30.1%, 78/259) indicated the perceived susceptibility of dengue fever, and only a half of them (50.2%, 130/259) indicated the perceived severity of dengue fever. Multivariate logistic analysis (MLA) indicated that the participants with family wealth index (FWI) 4–5 (OR: 22.9728; 95%CI: 2.4257–217.5688, p = 0.0063) were more likely to turn containers upside down (TCUD) compared to those with FWI 1–3; and the participants in the urban community (OR: 0.0239; 95%CI: 0.0019–0.3032, p = 0.004) were less likely to TCUD compared to those in the two rural communities. Around one third of the participants (36.8%, 96/239) reported that they were willing to seek treatment first for dengue fever from public health facilities. The MLA identified that the participants with the perceived severity of dengue fever (OR: 5.0564; 95%CI: 2.0672–12.3683, p = 0.0004), and with beliefs of sound hygiene helpful to people’s health (OR: 11.5671; 95%CI: 2.0505–65.2502, p = 0.0055) were more likely to seek treatment first for dengue fever from the public health facilities. Conclusion The study finds that most of Dai people have sound knowledge. However, health educational interventions should target to promote the perceived susceptibility and the perceived severity of dengue fever among Dai people.

Physical metallurgical (PM) and data-driven approaches can be independently applied to alloy design. Steel technology is a field of physical metallurgy around which some of the most comprehensive understanding has been developed, with vast models on the relationship between composition, processing, microstructure and properties. They have been applied to the design of new steel alloys in the pursuit of grades of improved properties. With the advent of rapid computing and low-cost data storage, a wealth of data has become available to a suite of modelling techniques referred to as machine learning (ML). ML is being emergingly applied in materials discovery while it requires data mining with its adoption being limited by insufficient high-quality datasets, often leading to unrealistic materials design predictions outside the boundaries of the intended properties. It is therefore required to appraise the strength and weaknesses of PM and ML approach, to assess the real design power of each towards designing novel steel grades. This work incorporates models and datasets from well-established literature on marageing steels. Combining genetic algorithm (GA) with PM models to optimise the parameters adopted for each dataset to maximise the prediction accuracy of PM models, and the results were compared with ML models. The results indicate that PM approaches provide a clearer picture of the overall composition-microstructure-properties relationship but are highly sensitive to the alloy system and hence lack on exploration ability of new domains. ML conversely provides little explicit physical insight whilst yielding a stronger prediction accuracy for large-scale data. Hybrid PM/ML approaches provide solutions maximising accuracy, while leading to a clearer physical picture and the desired properties.

Background Innate lymphoid cells (ILCs), as an important group of innate immunity, could respond rapidly to Mycobacterium tuberculosis (Mtb) infection. In this research, we studied the phenotypic changes of circulatory ILCs in active tuberculosis (TB) disease. Methods We recruited 40 patients with active Mtb infection (TB group) and 41 healthy subjects (NC group), and collected their clinical information and peripheral blood. Circulating ILCs, ILC subsets, dendritic cells (DCs), macrophages, and the production of cytokines in ILCs were tested by flow cytometry (FCM). Enzyme-linked immunosorbent assay (ELISA) was used to detect plasma IL-23. Results Compared with healthy control, total ILCs (0.73% vs. 0.42%, P = 0.0019), ILC1 (0.55% vs. 0.31%, P = 0.0024) and CD117+ ILC2 (0.02% vs. 0.01%, P = 0.0267) were upregulated in TB group. The total IL-17+ lymphocytes were elevated (3.83% vs. 1.76%, P = 0.0006) while the IL-22+ lymphocytes remained unchanged. Within ILC subsets, ILC3, CD117+ ILC2 and ILC1 in TB group all expressed increased IL-17 (15.15% vs. 4.55%, 19.01% vs. 4.57%, 8.79% vs. 3.87%, P P = 0.0557). Plasma IL-23 in TB group was positively correlated to IL-17+ ILC3 (r = 0.4435, P = 0.0141), IL-17+CD117+ ILC2 (r = 0.5385, P = 0.0021) and IL-17+ ILC1(r = 0.3719, P = 0.0430). TB group also had elevated DCs (9.35% vs. 6.49%, P + ILCs was related to severer inflammatory status and poorer clinical condition. Conclusions In active TB disease, circulatory ILCs were upregulated and exhibited IL-17-expressing phenotype. This may expand the understanding of immune reaction to Mtb infection.

This study (ORIENT-4) aimed to assess the efficacy and safety of sintilimab, a humanized anti-PD-1 antibody, in patients with relapsed/refractory extranodal NK/T cell lymphoma (r/r ENKTL). ORIENT-4 is a multicenter, single-arm, phase 2 clinical trial (NCT03228836). Patients with r/r ENKTL who failed to at least one asparaginase-based regimen were enrolled to receive sintilimab 200 mg intravenously every 3 weeks for up to 24 months. The primary endpoint was the objective response rate (ORR) based on Lugano 2014 criteria. Twenty-eight patients with r/r ENKTL were enrolled from August 31, 2017 to February 7, 2018. Twenty-one patients (75.0%, 95% CI: 55.1–89.3%) achieved an objective response. With a median follow-up of 30.4 months, the median overall survival (OS) was not reached. The 24-month OS rate was 78.6% (95% CI, 58.4–89.8%). Most treatment-related adverse events (TRAEs) were grade 1–2 (71.4%), and the most common TRAE was decreased lymphocyte count (42.9%). Serious adverse events (SAEs) occurred in 7 (25.0%) patients, and no patient died of adverse events. Sintilimab is effective and well tolerated in patients with r/r ENKTL and could be a novel therapeutic approach for the control of ENKTL in patients.

In the current eighth edition head and neck TNM staging, extranodal extension (ENE) is an adverse feature in oral cavity squamous cell cancer (OSCC). The previous seventh edition N1 with ENE is now staged as N2a. Seventh edition N2+ with ENE is staged as N3b in the eighth edition. We evaluated its potential impact on patients treated with surgery and postoperative intensity-modulated radiotherapy (IMRT).OSCC patients treated with primary surgery and adjuvant (chemo)radiotherapy between January 2005 and December 2014 were reviewed. Cohorts with pathological node-negative (pN-), pathological node-positive without ENE (pN+_pENE-) and pathological node-positive with ENE (pN+_pENE+) diseases were compared for local control, regional control, distant control and overall survival. The pN+ cohorts were further stratified into seventh edition N-staging subgroups for outcomes comparison.In total, 478 patients were evaluated: 173 pN-; 159 pN+_pENE-; 146 pN+_pENE+. Outcomes at 5 years were: local control was identical (78%) in all cohorts (P = 0.892), whereas regional control was 91%, 80% and 68%, respectively (P0.001). Distant control was 97%, 87%, 68% (P0.001) and overall survival was 75%, 53% and 39% (P0.001), respectively. Overall survival for N1 and N2a subgroups was not significantly different. In the seventh edition N2b subgroup of pENE- (n = 79) and pENE+ (n = 79) cohorts, overall survival was 67% and 37%, respectively. In the seventh edition N2c subgroups, overall survival for pENE- (n = 17) and pENE+ (n = 38) cohorts was 65% and 35% (P = 0.08), respectively. Overall, an additional 128 patients (42% pN+) were upstaged as N3b.When eighth edition staging was applied, stage migration across the N2-3 categories resulted in expected larger separations of overall survival by stage. Patients treated with primary radiation without surgical staging should have outcomes carefully monitored. Strategies to predict ENE preoperatively and trials to improve the outcomes of pENE+ patients should be explored.

Nearly-zero energy buildings (NZEB) would effectively improve building energy efficiency and promote building electrification. By using a carbon emission model integrated into a bottom-up mid-to-long term energy consumption model, this study analyzes the contribution of NZEB standards to carbon emission targets in the urban area of China by 2060. Three scenarios are set, namely BAU, steady development (S1), and high-speed development (S2). For BAU, the total carbon emissions will reach a peak of 1.94 Gt CO2 by 2040. In S1 scenario, total building carbon emissions will reach the peak of 1.72 Gt CO2 by 2030. In S2 scenario, the carbon emissions will reach a peak by 2025 with 1.64 Gt CO2. Under S1 scenario, which features consistency with NZEB market development and periodic improvement of building energy-efficiency standards, the carbon emission peak in 2030 will be accomplished. To achieve carbon neutrality by 2060, the upgrading of building energy standards to NZEB will contribute 50.1%, while zero-carbon electricity contribution is 49.9%. It is concluded that 2025, 2030, and 2035 could be set as mandatory enforcement years for ultra-low energy buildings, NZEB and zero energy building (ZEB), respectively.

Aims Minimally manipulated cells, such as autologous bone marrow concentrates (BMC), have been investigated in orthopaedics as both a primary therapeutic and augmentation to existing restoration procedures. However, the efficacy of BMC in combination with tissue engineering is still unclear. In this study, we aimed to determine whether the addition of BMC to an osteochondral scaffold is safe and can improve the repair of large osteochondral defects when compared to the scaffold alone. Methods The ovine femoral condyle model was used. Bone marrow was aspirated, concentrated, and used intraoperatively with a collagen/hydroxyapatite scaffold to fill the osteochondral defects (n = 6). Tissue regeneration was then assessed versus the scaffold-only group (n = 6). Histological staining of cartilage with alcian blue and safranin-O, changes in chondrogenic gene expression, microCT, peripheral quantitative CT (pQCT), and force-plate gait analyses were performed. Lymph nodes and blood were analyzed for safety. Results The results six months postoperatively showed that there were no significant differences in bone regrowth and mineral density between BMC-treated animals and controls. A significant upregulation of messenger RNA (mRNA) for types I and II collagens in the BMC group was observed, but there were no differences in the formation of hyaline-like cartilage between the groups. A trend towards reduced sulphated glycosaminoglycans (sGAG) breakdown was detected in the BMC group but this was not statistically significant. Functional weightbearing was not affected by the inclusion of BMC. Conclusion Our results indicated that the addition of BMC to scaffold is safe and has some potentially beneficial effects on osteochondral-tissue regeneration, but not on the functional endpoint of orthopaedic interest. Cite this article: Bone Joint Res 2021;10(10):677–689.

We determined the influence of gastro-oesophageal reflux disease (GERD) on quality of life (QOL) before and after functional-endoscopic-sinus-surgery (FESS) for chronic rhinosinusitis (CRS).Medically-recalcitrant CRS patients were recruited prior to FESS. GERD was diagnosed endoscopically. QOL was compared between patients withOf 187 CRS patients receiving FESS, 40 had GERD. Pre-operative QOL was significantly worse in CRS patients withCompared to CRS patients without GERD, those with GERD experienced poorer pre-operative QOL and greater QOL improvement after FESS.Associazione della malattia da reflusso gastroesofageo e la qualità di vita dei pazienti affetti da rinosinusite cronica.Abbiamo determinato l’impatto della malattia da reflusso gastroesofageo (GERD) sulla qualità della vita (QOL) prima e dopo chirurgia endoscopica funzionale nasosinusale (FESS) nel trattamento della rinosinusite cronica (CRS).I pazienti con CRS refrattari alle terapie mediche sono stati reclutati prima della FESS. La diagnosi di GERD è stata raggiunta endoscopicamente. La qualità della vita è stata confrontata tra pazienti con e senza GERD al basale e a un anno dopo la FESS.Dei 187 pazienti con CRS sottoposti a FESS, 40 erano affetti da GERD. La qualità della vita prima dell’intervento era significativamente peggiore nei pazienti affetti da CRS e con GERD rispetto a quelli senza GERD. I punteggi preoperatori della qualità della vita in relazione alla GERD (GERD-HRQL) e dell’indice dei sintomi da reflusso (RSI) sono stati correlati ciascuno con i punteggi SNOT-22 preoperatori. Rispetto ai pazienti con CRS senza GERD, i pazienti con GERD hanno dimostrato miglioramenti della SNOT-22 più significativi dopo trattamento FESS, i valori SNOT-22 postoperatori non erano più significativamente differenti tra i gruppi con GERD e senza GERD. Tuttavia, dopo la FESS, nei pazienti con CRS senza poliposi nasale (a differenza di quelli con poliposi nasale), il gruppo GERD (contro non-GERD) ha avuto una maggiore disfunzione del sonno e sintomi otologici/facciali.Rispetto ai pazienti con CRS senza GERD, quelli con GERD hanno beneficiato di un miglioramento della QOL maggiore dopo trattamento FESS.

COVID-19 is a disease caused by SARS-CoV-2, which has led to more than 4 million deaths worldwide. As a result, there is a worldwide effort to develop specific drugs for targeting COVID-19. Papain-like protease (PLpro) is an attractive drug target because it has multiple essential functions involved in processing viral proteins, including viral genome replication and removal of post-translational ubiquitination modifications. Here, we established two assays for screening PLpro inhibitors according to protease and anti-ISGylation activities, respectively. Application of the two screening techniques to the library of clinically approved drugs led to the discovery of tanshinone IIA sulfonate sodium and chloroxine with their IC50 values of lower than 10 μM. These two compounds were found to directly interact with PLpro and their molecular mechanisms of binding were illustrated by docking and molecular dynamics simulations. The results highlight the usefulness of the two developed screening techniques for locating PLpro inhibitors.

Background Second head and neck neuroendocrine carcinoma (NEC) after radical radiotherapy for nasopharyngeal carcinoma (NPC) treatment is rarely reported. The prognosis of second cancer is poor, and our research focuses on finding a breakthrough in the treatment. In this study, we aimed to investigate clinicopathological characteristics and to identify the genomic landscape of second head and neck NECs. Methods We collected five second head and neck NEC cases in the recent three years from our patient database. Clinicopathological data and images were obtained. Genomic analysis was performed using high-throughput second generation sequencing. KEGG pathway enrichment analyses between high-frequency mutations were performed using the STRING database. Results All patients had been diagnosed with second NEC, according to the pathological observations. The interval between diagnosis of NPC and NEC ranged from 10 to 18 years. Two patients had brain or liver metastasis at three and nine months, respectively, after the diagnosis of NEC. Three patients died of the disease with the overall survival time ranging from three to nine months. Commonly altered genes (50%) in second head and neck NECs included TP53, RB1, NOTCH2, PTEN, POLG, KMT2C, U2AF1, EPPK1, ELAC2, DAXX, COL22A1, and ABL1. Those genetic lesions might affect p53 signaling, MAPK signaling, PI3K-Akt signaling, sphingolipid signaling, and neurotrophin signaling pathways. Conclusions Second head and neck NECs had poor prognosis. We revealed, for the first time, the mutational landscape, high-frequency somatic mutations, and potential signaling pathways of second head and neck NECs. Its optimal treatment model needs to be further studied in future clinical trials.

Purpose The aim of this study was to establish individualized nomograms to predict survival outcomes in older female patients with stage IV breast cancer who did or did not undergo local surgery, and to determine which patients could benefit from surgery. Methods A total of 3,129 female patients with stage IV breast cancer aged ≥70 years between 2010 and 2015 were included in the Surveillance, Epidemiology, and End Results program. Multivariate Cox regression analysis was used to identify risk factors for overall survival (OS) and breast cancer-specific survival (BCSS). Survival analysis was performed using the Kaplan–Meier plot and log-rank test. Nomograms and risk stratification models were constructed. Results Patients who underwent surgery had better OS (HR = 0.751, 95% CI [0.668–0.843], P, Graphical abstract Image 1, Highlights • The effect of surgery in older patients with stage IV breast cancer (BC) is discussed. • The proportion of older patients with stage IV BC who underwent surgery declined. • A specific group of older patients with stage IV BC can benefit from surgery. • Nomograms can be used to predict the prognosis of older patients with stage IV BC.