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With the advent of the post-epidemic era, the energy consumption characteristics of hotels have changed, which has an important impact on urban energy conservation. In order to contribute to the goal of carbon neutrality, this study discusses the energy-saving operation strategy of hotels considering the impact of the COVID-19 epidemic. Based on the energy consumption characteristics of large public buildings, this paper analyzes the energy consumption distribution and operation characteristics of hotel buildings in detail. By collecting energy consumption data from five typical large hotel buildings in a tourist city in southern China from 2018 to 2022, the impact of COVID-19 on hotel energy consumption and hotel business characteristics was discussed in detail. Combined with the economic development characteristic in the post-epidemic era, this paper explores the energy-saving strategies that hotels can adopt in the context of normalized epidemic prevention and control and obtains the optimal path of low-carbon economic operation of hotel buildings. This study reveals the energy consumption characteristics and energy-saving potential of hotel buildings, and provides enlightenment for hotel management and low-carbon development in the post-epidemic era.

The performance degradation of materials exposed to corrosive atmospheric environments is a serious problem. Corrosion maintenance strategies and cycles are informed largely by historical trends in corrosivity dependent on the location of interest. Assessments are often made with sparse experimental data and are generalized to certain materials and baseline conditions observed in the past. The development of a predictive model which can better inform maintenance strategies and cycles offers opportunities for time savings and cost avoidance. Such a model would need to predict corrosion damage accumulation as a function of material of interest, location of interest, and atmospheric conditions during the period of exposure of interest. Machine learning has recently gained attention as a way to model complex systems and processes. Atmospheric corrosion is certainly a complex process as there are many parameters that influence it which are uncontrolled and vary in difficult to predict ways. A machine learning algorithm would require data to learn from which might include environmental conditions such as temperature, relative humidity, UV light exposure, time of wetness, salt concentration, applied loads, and electrochemical data for substrates, inhibitors, and coatings. The ability of machine learning to determine models and relationships from large data sets is well demonstrated; however, a Bayesian model approach can be more suitable when data is limited, expensive or time consuming to obtain, and expert knowledge can be leveraged to construct the relationships. While certain meteorological variables are well categorized and easy to retrieve other variables like corrosion damage or salt deposition are sparsely reported if measured at all. For this reason, a Bayesian Network Model has been developed to better predict the corrosion damage accumulation of C1010 steel and three different aerospace coating systems applied over AA2024-T351. The network map was constructed from parameters (nodes) which are known to influence corrosion. Mathematical relationships were used to develop relationships between nodes or to calculate new nodes as available. Finite element analysis was used to refine the network map and provide supplemental inputs for features that are difficult to measure experimentally. The model was initially trained from historic corrosion data gathered from collaborators across the DoD. Contemporary experimental data was also gathered in a 19-site survey of field exposure sites across the world. This dataset provided further inputs for training and also data for validation and testing. The methodology behind model construction will be highlighted and model predictions will be compared against experimental results. To date, there has been good correlation between model predictions and experimental results for C1010 steel mass loss, which provides a basis to further extend the model to aerospace coating systems. Figure 1

Long non-coding RNA (LncRNA) Small Nucleolar RNA Host Gene 3 (SNHG3) is involved in the occurrence and development of various cancers. However, the exact function and mechanism of SNHG3 in cervical cancer (CC) are still unclear. In this context, we identified a significant increase of SNHG3 expression in CC tissues. Upregulation of SNHG3 expression was associated with advanced FIGO stage and metastasis, and indicated poor overall survival of the CC patients. Functionally, SNHG3 enhanced the proliferation, migration and invasion of CC cells in vitro, and facilitated CC growth in vivo. Further investigation uncovered that SNHG3 interacted with oncoprotein YAP1, thus suppressing its degradation. Additionally, SNHG3 modulated the transcription of several target genes of YAP1. The oncogenic role of SNHG3 was partially attributable to YAP1. Taken together, our research revealed the prognostic and functional roles for SNHG3 in CC, suggesting that SNHG3 could serve as a biomarker for prognosis and a therapeutic target for CC.

Pyrolysis is a promising and attractive way to convert lignocellulosic biomass into low carbon-emission energy products. To effectively use biomass feedstock with size distribution to produce biofuels, a comprehensive kinetic model of the process, occurring at particle level, is important. In this study, the population balance model (PBM)-distributed activation energy model (DAEM) coupled model is first time developed to predict biomass pyrolysis. The Population balance model is used to present the variable size distribution of solid, decomposed from virgin biomass to porous char. Two different kinetic models are embedded into the conservation equations of mass and energy. They are compared to demonstrate the prediction performance of heating-up time during the pyrolysis process of biomass with a normal size distribution. It is found that non-isothermal kinetics without and with DEAM capture the intra-particle temperature distribution. There is a noticeable difference of heating-up time between single and distributed particle size.

International audience; Objective: Based on the current evidence, review the efficacy and safety profile of pembrolizumab, along with its shortcomings, in an effort to define future research directions. Background: The survival outcome of esophageal cancer (EC) is poor, especially in patients with advanced stage. Palliative surgery, chemotherapy, radiotherapy and chemoradiotherapy have limited efficacy in prolonging the survival time. Currently, immunotherapies, including adoptive cell therapy-based, antibodybased, and vaccine-based therapies, are attracting considerable attention. The mechanism of immunotherapy lies in the modification of immune response and prevention of immune escape. Immunomodulatory agents can block the programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) pathway, thereby allowing lymphocytes to attack tumor cells. This class of drugs has the potential to treat a variety of tumors and may substantially improve overall survival (OS) in some patients. Multiple clinical trials have shown that pembrolizumab has good efficacy and safety, enhances the EC treatment paradigm, and has even become the first-line treatment of choice for patients with PD-L1-positive recurrent or metastatic EC. Methods: We reviewed the results of clinical trials of pembrolizumab for EC and gastroesophageal cancer presented at Embase, PubMed, the American Society of Clinical Oncology (ASCO) annual meetings, and the Cochrane Central Register of Controlled Trials. Conclusions: Pembrolizumab has good efficacy and tolerability profiles, and has emerged as a second-line option for the treatment of PD-L1-positive locally advanced or metastatic ESCC. Pembrolizumab has many promising applications, and further investigations into its mechanisms should be conducted.

Giant pulmonary bullae (GPB) is rare. The aim of this study was to evaluate the functional results of video-assisted thoracic surgery (VATS) in the treatment of GPB and the factors associated with complications following VATS resection for GPB.From January 2010 to January 2015, 44 GPB patients underwent surgery with VATS. Individual GPB patient characteristics and surgical outcomes were evaluated. The patients were separated into two groups (an emphysematous group and a nonemphysematous group), and differences between the respective groups were investigated.Although there were no mortalities within a 30-d postoperative period among the 44 GPB patients treated surgically with VATS, 28 experienced postoperative complications, of which the most common were air leaks. VATS for GPB resulted in obvious improvements in symptoms and lung function in the majority of cases. Among 26 patients with preoperative dyspnea, the symptoms of 22 patients (84.62%) improved after treatment with VATS resection for GPB, and the mean forced expiratory volume in 1 s increased from 2.24 L preoperatively to 2.5 L postoperatively (P = 0.02). The complication rate of patients aged48 y, who smoked and had emphysema, was significantly higher than that of those who did not smoke and did not have emphysema (79.2% versus 45%, P = 0.019; 85.7% versus 25%, P 0.05; 88% versus 31.6%, P 0.05). These characteristics could be associated with complications.VATS resection is a safe and effective treatment for GPB and leads to improvements in symptoms and lung function. Patients48 y, who smoked and had emphysema, were more likely to experience postoperative complications. There could be a relationship between these characteristics and the patients' postoperative complications.

Hydrogels are the attractive biomaterials for biomedical applications. The dual-stimuli-responsive system, which is sensitive to both temperature and UV irradiation, was achieved through the self-assembly of amphiphilic block copolymers in aqueous solution and the cleavage of ο-nitrobenzyl (NB) ester groups under UV irradiation. The copolymer of poly(e-caprolactone)-b-ο-nitrobenzyl-poly(ethylene glycol)-ο-nitrobenzyl-b-poly(e-caprolactone) (PCL-NB-PEG-NB-PCL) was prepared by ring-opening polymerization (ROP) and nucleophilic substitution reaction of e-caprolactone (e-CL) using photo-sensitized polyethylene glycol as an initiator. After blending with poly(e-caprolactone)-b-poly(ethylene glycol)-b-poly(e-caprolactone) (PCL-PEG-PCL), the system exhibited the promising dual sensitivity with wide gel-phase window and controllable sensitive properties. The structures and dual-responsive behaviors were characterized by 1H-NMR, GPC, DMA, UV–Vis, DLS and SEM. The results demonstrated the temperature and photo-sensitivity of the synthesized hydrogel and indicated that the blending of these two copolymers can easily adjust the phase transition temperature and broaden the gel-phase window through the content of NB groups in PCL-NB-PEG-NB-PCL and the hydrophilic/hydrophobic balance of system.

Utilizing the interference of shock and expansion waves, supersonic biplane can reduce the wave drag remarkably. However, the supersonic biplane is only designed at special conditions, so that it has poor performance at off-design conditions. To analyze supersonic biplane's aerodynamic characteristics at off-design conditions, the non-instructive probabilistic collocation method has been employed to achieve uncertainty quantification. Besides, Sobol global sensitivity is adopted to accurately evaluate the influence of the input uncertainty parameters. The uncertainty parameters are Mach number and the angle of attack which both satisfy special normal distributions. Aerodynamic coefficients and pressure distribution from the biplane's surface as well as flow filed are studied. The results of uncertainty quantification show that the main reason for aerodynamic characteristics fluctuations is the pressure pulsation from the maximum thickness of the lower airfoil's upper surface. The results of global sensitivity show that Mach number is the most important factor for the variation of aerodynamic performance.

Background: YouTube is a valuable source of medical videos, but the quality of the videos is difficult to determine. This study aimed to estimate the quality by characteristics of the surgeon and by view rate. Methods: The term, “pulmonary lobectomy”, as a keyword was searched for on the YouTube search engine with the filter set to sort videos by view rate. The data of the first 100 videos were gathered and analyzed. A search was performed for any surgeon who was featured in a video or who posted a live video on Scopus to ascertain the h-index and lung-related publication history. Results: There were approximately 8,650 videos that were found using “pulmonary lobectomy” as the search term. In the top 100 videos, there were 79 live surgical videos, 12 academic informational videos, 5 patient interviews, and 4 other miscellaneous videos. A primary surgeon was identified in 54 of the 79 (68%) live surgeries, with the majority of these surgeons having an adequate academic affiliation such as an h-index and academic publications. Conclusions: There are a large amount of YouTube videos on pulmonary lobectomy with acceptable quality, and these videos may have great potential to improve surgical education. But trainees should critically examine the quality of video content. Furthermore, these surgical videos should be improved in quality before they can be used in medical teaching.

The delicacy of nature prompted scientists to create functional or responsive biomaterials using existing natural components. Here we reported novel thermo-gelling hydrogels based on methyl poly (ethylene glycol)-poly (L-valine) (mPEG-L-PV) diblock copolymer solutions, which exhibited well-defined sol–gel transition at a temperature range from 10 °C to 40 °C. The β-sheet was the dominant secondary structure for poly(L-PV) block when the molecular weight of the polypeptide ranged from 277 Da to 1138 Da. The formation of mPEG–L-PV clear sol solutions was related to the stable nanostructures that were aggregated clusters of poly(L-PV) β-sheet filaments and stabilized by the hydrophilic PEG segments. The block length of poly(L-PV) significantly affected the secondary structures of polypeptide and the morphology of assembled filaments, which resulted in different thermo-gelling behavior of the copolymer solutions. The occurrence of sol–gel transition with temperature was primarily due to the dehydration effect of PEG block, whereas in the case of the copolymer with a lower molecular weight of poly(L-PV) block, the change of polypeptide secondary structures also contributed to the formation of the gel. This paper provides fundamental information about the strong dependence of polypeptide block length on the nano-assembly morphology as well as thermosensitive behavior of polypeptide-based hydrogels.

To ensure the reliability of software system, software developers have to keep track of the severity of bug reports, and fix critical bugs as soon as possible. Recently, automatic methods to identify the severity of bug reports have emerged as a promising tool to lessen the work burden of software developers. However, most of such methods are supervised and data-driven models which fail to provide favorable performance in the presence of insufficient labeled sample or limited training data. In order to tackle with these issues, we propose an incremental learning for bug reports recognition. According to this framework of incremental learning, one active learning method is developed for tagging unlabeled bug reports, meanwhile, a sample augmentation method is utilized for sufficient training data. Both of these methods are based on uncertainty which is correlated to the informativeness and the classification risk of samples. Moreover, different types of connectionist models are employed to identify bug reports, and comprehensive experiments on real bug report datasets demonstrate that the generalization abilities of these models can be improved by this proposed incremental learning.

With the rapid development of electronic technology, the use of portable and wearable electronics hasbeen widely. In order to eliminate the dependency of low-power electronic devices on batteries and the associated requirement of periodic replacement, researchers have begun investigating methods of generating energy from ambient sources. An airflow energy harvester for human motion is typically composed of a spring-mass system with an air pump connected in parallel with a spring and a turbine. Recent studies have proposed some airflow energy harvesting devices. However, these studies are focused on structural design and little attention has been devoted to the energy conversion process. There are two processes for energy conversion: human motion to airflow energy, then airflow energy to electricity. Focus on the energy conversion, this paper proposes a way to evaluate the energy of the airflow from the perspective of damping at harmonic excitations. The model of an airflow energy harvester for human motion composed of a spring-mass system with an air pump connected in parallel with a spring and a turbine is built, and the balance force analysis is carried out. Comparing the mathematical models and the force analysis equations, the regular pattern of the damping change of the system during the vibration is defined. The simulation isperformed, the result indicates that the energy of the airflow which the vibration system provides is related to the damping of the system. This paper provides a new method toanalyzethe energy conversion process, which helps to measure the efficiency of the airflow energy harvester preferably.

The P(CL-PDO)-PEG-(P(CL-PDO)(PECP) copolymer hydrogel is an attractive thermogelling material for practical applications due to the fast dissolution of the copolymer in water and good stability of ...

Recently, bearing health condition monitoring has attracted considerable attention due to its great significance to prolong the lifespan and improve the system reliability of key industrial equipments. For the purpose of improving the reliability and effectiveness of energy harvesting in the monitoring node of industrial equipments, this paper proposes circular Halbach electromagnetic energy harvesters for extracting the electrical energy from the rotational motion of bearings to supply the monitoring units. The magnetic distribution model of the circular Halbach array is derived to investigate the magnetic field enhancement using different arrangement modes and structural parameters. The effect of gap, magnetic shape and distribution radius on the magnetic field is numerically discussed to obtain the proper configuration of circular Halbach array for performance enhancement. The experimental results of the fabricated prototype demonstrate the effectiveness of the proposed model and optimization design for enhancing the energy harvesting performance. Moreover, voltage response and power output under different connection modes of multi-coil are experimentally discussed for increasing efficiency and reducing the cost and difficulty of interface circuits. Under the rotational speed from 600 rpm to 1000 rpm, the proposed harvester can generate the voltage of 2.79–4.59 V and the maximum average power of 50.8–131.1 mW.

During ascent of launcher, the unsteady aerodynamic loads associated with transonic buffet flow have become of considerable concern. To study the unsteady dynamics of buffet flow, delayed detached-eddy simulations of a hammerhead configuration have been conducted at transonic Mach numbers. The results, including mean Cp, Cp rms , PSD and Schlieren visualizations, were validated by the measurements obtained from the wind-tunnel experiments. Nevertheless, to perform a good validation for unsteady loads, the numerical data needed to be filtered according to the data acquisition used in the experiments. The studies were performed by means of instantaneous, statistical, spectral and cross-spectral analysis of the numerical data, which identify the fluid dynamic mechanism that produces a relatively strong buffet environment. The mechanism involves a sequence of vortex, which is shed downstream, merges together, and ultimately impinges on the wall leading to large fluctuations. Besides, the cross-spectral analysis also revealed that the subsequent large scale and low frequency vortex shedding of the developed shear layer provides a strong influence on the flows around cone–cylinder conjunction. The fluctuations in this area are highly sensitive to Mach numbers, and the peak of Cp rms appears at Ma ≈ 0.81.

PURPOSE Research regarding cellular responses at different oxygen concentrations (OCs) is of immense interest within the field of radiobiology. Therefore, this study aimed to develop a mechanistic model to analyze cellular responses at different OCs. METHODS A DNA damage model (the different cell oxygen level DNA damage [DICOLDD] model) that examines the oxygen effect was developed based on the oxygen fixation hypothesis, which states that dissolved oxygen can modify the reaction kinetics of DNA-derived radicals generated by ionizing radiation. The generation of DNA-derived radicals was simulated using the Monte Carlo method. The decay of DNA-derived radicals due to the competing processes of chemical repair, oxygen fixation, and intrinsic damaging was described using differential equations. The DICOLDD model was fitted to the previous experimental data obtained under different irradiation configurations and validated by calculating the yields of DNA double-strand breaks (DSBs) after exposure to 137 Cs as well as cell survival fractions (SFs) using a mechanistic model of cellular survival. Moreover, we used the DICOLDD model to calculate DNA DSB damage yields after irradiation with 0.5-50 MeV protons. RESULTS Generally, DSB yields calculated after exposure to 137 Cs at different OCs correspond to statistical uncertainties of previous experimental results. Calculated SFs of CHO and V79 cells exposed to photons, protons, and alpha particles at different OCs generally concur with those obtained in previous studies. Our results demonstrated that the variation in DSB yields was less than 10% when the cellular OC decreased from 21% to 5%. Additionally, DSB yields changed drastically when OC dropped below 1%. CONCLUSIONS We developed a DNA damage model to evaluate the oxygen effect and provide evidence that a reaction-kinetic model of DNA-derived radicals induced by ionizing radiation suffices to explain the observed oxygen effects. Therefore, the DICOLDD model is a powerful tool for the analysis of cellular responses at different OCs after exposure to different types of radiation.

Background Primitive neuroectodermal tumor (PNET) is a relatively rare malignant small round cell tumor, and the occurrence of cervical PNET during pregnancy is extremely rare. Case presentation A case of pregnancy complicated by PNET at our hospital was reported. A 19-year-old pregnant woman presented to the hospital due to multiple instances of vaginal bleeding during the first and second trimesters. She was initially considered for threatened abortion but was ultimately diagnosed with cervical PNET. No standard treatment plan has been developed for pregnant women with this tumor. After completing the necessary examinations, doctors cooperated with the patient and her family to develop a surgical treatment plan. The patient recovered well after surgery, but she refused radiotherapy and chemotherapy. After nearly 3 years of follow-up visits, the patient is alive with no signs of recurrence. Conclusions PNET during pregnancy is a rare but complex condition. It is necessary to devise an individualized treatment plan according to gestational age. Timely surgical treatment can significantly prolong the survival time of patients but may also lead to fetal loss and the inability to carry a pregnancy.

PURPOSE This study aimed to evaluate whether high-energy X-rays (HEXs) of the PARTER (platform for advanced radiotherapy research) platform built on CTFEL (Chengdu THz Free Electron Laser facility) can produce ultrahigh dose rate (FLASH) X-rays and trigger the FLASH effect. MATERIALS AND METHODS EBT3 radiochromic film and fast current transformer (FCT) devices were used to measure absolute dose and pulsed beam current of HEXs. Subcutaneous tumor-bearing mice and healthy mice were treated with sham, FLASH, and conventional dose rate radiotherapy (CONV), respectively to observe the tumor control efficiency and normal tissue damage. RESULTS The maximum dose rate of HEXs of PARTER was up to over 1000 Gy/s. Tumor-bearing mice experiment showed a good result on tumor control (p

Background The mental health of cancer patients is attracting increasing attention. Thus, an efficient mental health preliminary screening questionnaire (MHPSQ) for cancer patients is required. This study sought to develop an MHPSQ, test its reliability and validity, and administer it among cancer patients. Methods A literature review and interviews with 8 patients were conducted to determine the questionnaire item pool, and experts were consulted to confirm the first draft. Next, 150 cancer patients were selected for the project analysis and validity assessment to develop the final document; 400 patients were then selected for the reliability and validity tests. After which, 1,000 patients were assessed using the Self-Rating Anxiety Scale, Self-Rating Depression Scale (SDS), and MHPSQ, and the completion times for each scale were evaluated. Finally, the specificity and sensitivity of the MHPSQ were then determined. Results Four factors (i.e., mood, sleep, social function, and interpersonal relationships) were ultimately retained as MHPSQ items. MHPSQ's Cronbach's α and test-retest reliability were 0.76 and 0.92, respectively. The time required to complete the MHPSQ was 83.90±19.00 s. Its sensitivity and specificity were 92.4% and 98.5%, respectively. Conclusions The MHPSQ has good reliability and validity. Comprising only 4 items, it is easy to operate and effectively identifies patients with psychological abnormalities.

This paper analyzes the requirements of improving the efficiency of human-machine interaction in civil aircraft cockpit, identifies the disadvantages of human-machine interaction efficiency and cognition in aircraft cockpit that has used touch screen, and analyzes the interactive characteristics of touch screen in operation. Based on the concept of safety, efficient and comfortable control, this paper expounds the development demand and trend of touch control of civil aircraft cockpit in future. Finally, for the purpose of ensuring control safety and improving control efficiency, an integrated design of touch control and information display based on the synoptic page is proposed, so as to realize the requirements of efficient cognition and convenient control, improve the touch usability, reduce the workload and human errors for pilot.

Background Lung cancer is the most threatening malignant tumor to human health and life. Using a variety of machine learning algorithms and statistical analyses, this paper explores, discovers and demonstrates new indicators for the early diagnosis of lung cancer and their diagnostic performance from large samples of clinical data in the real world. Methods By applying machine learning methods, including minimum description length (MDL), naive Bayesian (NB), K-means (KM), nonnegative matrix factorization (NMF), and decision tree (DT), based on large sample data of 2,502 patients, we built a classification model and systematically explored differences in fibrinogen levels in different clinical stages of lung cancer between the sexes. We also validated the reliability of the model by testing it on a validation cohort of 447 patients. This report adheres to the "Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis" (TRIPOD) statement for the reporting of prediction models. Results The analysis revealed significant differences in fibrinogen levels, pleural effusion, chlorine levels, A-G ratio, glutamic-oxaloacetic transaminase and alkaline phosphatase levels as well as in sex composition between the early-stage lung cancer group and the middle-late-stage lung cancer group. The classification model created by the combination of fibrinogen, alkaline phosphatase and sex demonstrated good performance with an AUC of 73.5%. In addition, in males, a fibrinogen level of 2.94 g/L could initially serve as the upper limit for determining the early-stage lung cancer group, but a level of 3.91 g/L could be preliminarily used as a reference threshold for the lower limit for middle- to late-stage lung cancer. This latter level could also serve as the upper limit of the critical value for early-stage lung cancer in females. Conclusions An integrated application based on supervised and unsupervised machine learning algorithms could effectively explore the potential links contained in the clinical data and reveal the differences in fibrinogen levels in different clinical stages of lung cancer between the sexes, which could provide a new reference basis for lung cancer staging.

The demand response realizes the flexible energy utilization on the user side and promotes the energy utilization efficiency in the multi-energy micro-grid system. This paper establishes a two-dimensions price-based demand response model with both vertical load transfer and horizontal energy conversion. Considering a variety of renewable energy resources and energy storage, this paper studies the optimal scheduling of multi-energy micro-grid system with the feedback of residual power sold to the external grid, so as to maximize the revenue of a multi-energy micro-grid system operators. A case study shows that the two-dimensions price-based demand response can not only effectively reduce the energy consumption cost of users, but also improve the benefits of multi-energy micro-grid system.

Novel camellia-structured Z-scheme BiOBr/g-C3N4/Bi2O2CO3 was simply prepared by a hydrothermal method and photodegraded Rhodamine B under visible light within 60 min with much higher degradation efficiency (98%) contrasted with pure BiOBr, g-C3N4 and Bi2O2CO3. Radical trapping experiments exhibited the main reactive species (·O2-) during degradation process. The formation of Z-scheme heterojunction improved rate of charge separation, enhanced absorption of visible light and thus promoted the photocatalytic activity. The Z-scheme heterojunction is a promising material for the removal of dye in effluents.

In order to improve the production efficiency of the fungus industry, save the planting cost of the fungus industry and build an efficient production mode of the fungus industry. We are based on Internet plus's “smart bacteria industry” and supported by Internet of Things technology. The fungus intelligent greenhouse is constructed, and the ZigBee protocol stack and networking are used to realize the crop environmental monitoring system. The accurate acquisition and stable transmission of environmental temperature, Humidity, gas concentration, light intensity and other data are formed, and the remote monitoring and management system for agricultural production is constructed.

Physical ergonomics evaluation of civil aircraft cockpit control devices has become increasingly important for aircraft engineers when designing pilot-centered cockpit. This paper puts forward the principles for physical ergonomics design of control devices, as well as a physical ergonomics evaluation method for cockpit control devices based on flight scenarios in virtual environment to demonstrate how digital human modeling software can be used effectively for such evaluation. Three digital pilot models are generated from anthropometric database, representative of the shortest, average and tallest Chinese pilot population, and interfaced with digital prototype of cockpit control devices in RAMSIS software for physical ergonomics design analysis of the control devices. The analysis mainly includes the control device’s appearance, range of movement, operating force, and the analysis results can be used to achieve design iteration of cockpit control devices.

Smart Substation becomes more vulnerable to cyber attacks due to the high integration of information technologies, so it is essential to detect intrusion behaviour by abnormal traffic analysis in smart substations. Although there have been many detection methods for abnormal traffic, the existing ones all focus on the format check of a single field of the industrial transmission protocol, and ignore the deep coupling relationships among multiple protocol fields, which lead to more or less false detections and missed detections. To overcome this problem and further improve the detection accuracy, in this paper, we propose an abnormal traffic detection method based on the coupling field extraction and the density-based spatial clustering of applications with noise (DBSCAN). By using correlation analysis to extract the coupling fields of the protocol fields and using DBSCAN to remove the noise in the coupling fields, the deep coupling relationship between the coupling fields can be mined by the piecewise linear function fitting method, and used to detect abnormal traffic. The simulation results on 10,000 frames traffic prove that the proposed detection method can effectively identify the abnormal traffic.

Background Considering the increase in the proportion of lung adenocarcinoma (LUAD) cases among all lung cancers and its considerable contribution to cancer‐related deaths worldwide, we sought to identify novel oncogenes to provide potential targets and facilitate a better understanding of the malignant progression of LUAD. Methods The results from the screening of transcriptome and survival analyses according to the integrated Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) data were combined, and a promising risk biomarker called meiotic nuclear divisions 1 (MND1) was selectively acquired. Cell viability assays and subcutaneous xenograft models were used to validate the oncogenic role of MND1 in LUAD cell proliferation and tumor growth. A series of assays, including mass spectrometry, co‐immunoprecipitation (Co‐IP), and chromatin immunoprecipitation (ChIP), were performed to explore the underlying mechanism. Results MND1 up‐regulation was identified to be an independent risk factor for overall survival in LUAD patients evaluated by both tissue microarray staining and third party data analysis. In vivo and in vitro assays showed that MND1 promoted LUAD cell proliferation by regulating cell cycle. The results of the Co‐IP, ChIP and dual‐luciferase reporter assays validated that MND1 competitively bound to tumor suppressor Kruppel‐like factor 6 (KLF6), and thereby protecting E2F transcription factor 1 (E2F1) from KLF6‐induced transcriptional repression. Luciferase reporter and ChIP assays found that E2F1 activated MND1 transcription by binding to its promoter in a feedback manner. Conclusions MND1, KLF6, and E2F1 form a positive feedback loop to regulate cell cycle and confer DDP resistance in LUAD. MND1 is crucial for malignant progression and may be a potential therapeutic target in LUAD patients., In this study, a novel cell cycle regulator named meiotic nuclear divisions 1 (MND1) was firstly screened out as a potential oncogene in LUAD using different bioinformatic and statistical analyses. In mechanism, MND1 could directly bind to tumor suppressor kruppel‐like factor 6 (KLF6) to protect E2F1 from the transcriptional repression of KLF6. Interestingly, in return, E2F1 could activate MND1 transcription by binding to a specific site in the promoter region of MND1.

With the massive deployment of IoT devices, the management of IoT devices becomes more and more important. In this paper, We only need the packet length the device sent to serves in 180s to identify the device. We evaluated the algorithms K-Nearest Neighbor, Random Forest, Suport Vector Machine and Multilayer Perceptron for classification. The results show that the Random Forest is the best and can achieve 99.6% if accuracy in the identification of devices. We also ranked the importance of 10 features related to packet length. Using the five most important features (media, mean, skewness, absolute energy, standard deviation and of packet length), we can achieve 99.5% accuracy on the public dataset and 99.29% accuracy on our dataset.

PURPOSE/OBJECTIVE(S) Ultrahigh dose-rate (FLASH) radiotherapy has attracted immense attention because of its tumor control efficiency and healthy tissue protection during preclinical experiments with electrons, kilo-voltage X-rays, and protons. Using high-energy X-rays (HEXs) in FLASH is advantageous owing to its deep penetration, small divergence, and cost-effectiveness. We did this experiment to find out whether PARTER (platform for advanced radiotherapy research) platform built on CTFEL (Chengdu THz Free Electron Laser facility) can trigger FLASH effect. MATERIALS/METHODS Subcutaneous tumor-bearing mice and healthy mice were treated with sham, FLASH, and conventional (CONV) radiotherapy respectively to observe the tumor control and normal tissue damage under different radiation conditions. With a high-current and high-energy superconducting linear accelerator, FLASH with a good dose rate and high penetration was achieved. Breast cancers artificially induced in BAL b/c mice were efficiently controlled, and normal tissues surrounding the thorax/abdomen in C57BL/6 mice were protected from radiation with HEX-FLASH (HEX with FLASH). Theoretical analyses of cellular responses following HEX-FLASH irradiation were performed to interpret the experimental results and design further experiments. RESULTS HEX-FLASH was implemented using the superconducting LINAC with the maximum mean dose rate up to over 1000 Gy/s. Tumor-bearing mice experiment showed a good result on tumor control (F = 25.14, P < 0.0001) and significantly different in survival curves (P < 0.005) among the three groups. In the thorax-irradiated healthy mice experiment, there was a statistically significant difference (P = 0.038) in survival among the three groups. The hazard ratio (HR) was 0.19, 95% confidence intervals (CIs) was 0.035-1.010, and P was 0.0486 between the FLASH and CONV groups; therefore, the risk of death decreased by 81% in the FLASH group compared with that in the CONV group. Although the survival time of healthy mice irradiated on abdomen in the FLASH group was undoubtedly higher (62.5 % of mice were still alive when we stopped observation) than that in the CONV group (7 days), the difference in survival between the two groups was not statistically significant (HR 0.369; 95% CI 0.113-1.202; P = 0.0735). Despite this, the survival trend of mice treated with HEX-FLASH radiotherapy was better. We demonstrated theoretical cellular response analysis of the FLASH effect based on the ROD hypothesis and it showed consistent radioprotective effects in normal cells under FLASH irradiation. CONCLUSION This study highlights the generation of HEX-FLASH for the first time and its potential in future clinical applications.

In this paper, considering the frequency stability problem that may occur in the asynchronous power grid with DC-interconnected, an emergency control method based on convolutional neural networks (CNN) which gives the advantages such as the timeliness of data-driven methods in emergency control of power system is proposed. This method uses the CNN model to synchronously generate frequency prediction and optimal strategies for frequency stability coordination control, including the combination of emergency DC emergency power support and automatic load shedding control. Simulation analysis shows that this method not only has good accuracy and effectiveness, but also greatly improves the timeliness of control, and is suitable for the online application of grid frequency stability emergency control.

The emergence of dual frequency global navigation satellite system (GNSS) chip actively promotes the progress of precise point positioning (PPP) technology in Android smartphones. However, some characteristics of GNSS signals on current smartphones still adversely affect the positioning accuracy of multi-GNSS PPP. In order to reduce the adverse effects on positioning, this paper takes Huawei Mate30 as the experimental object and presents the analysis of multi-GNSS observations from the aspects of carrier-to-noise ratio, cycle slip, gradual accumulation of phase error, and pseudorange residual. Accordingly, we establish a multi-GNSS PPP mathematical model that is more suitable for GNSS observations from a smartphone. The stochastic model is composed of GNSS step function variances depending on carrier-to-noise ratio, and the robust Kalman filter is applied to parameter estimation. The multi-GNSS experimental results show that the proposed PPP method can significantly reduce the effect of poor satellite signal quality on positioning accuracy. Compared with the conventional PPP model, the root mean square (RMS) of GPS/BeiDou (BDS)/GLONASS static PPP horizontal and vertical errors in the initial 10 min decreased by 23.71% and 62.06%, respectively, and the horizontal positioning accuracy reached 10 cm within 100 min. Meanwhile, the kinematic PPP maximum three-dimensional positioning error of GPS/BDS/GLONASS decreased from 16.543 to 10.317 m.

Full aperture polishing (FAP) is the key application process that realizes low damage and ultra-smooth surface in the fabrication of large plane optical element. The polishing pad plays a vital role as a significant part in FAP. When the material of element is removed, the contact surface of pad also appears non-uniform wear, which is detrimental to polishing accuracy and efficiency. In this work, wear density (WD) is proposed to characterize wear uniformity of pad, and relative wear (RW) is used to represent the wear degree. Based on the wear density distribution model, the effect of process parameters on the pad wear is investigated. It is pointed out that when the speed difference between the element and the polishing plate is 0.2r/min to 0.5r/min, the wear track distribution of pad is relatively uniform. Furthermore, the results showed that swing has the greatest influence on the wear non-uniformity, while the traverse velocity is the smallest. In order to reduce the serious local wear, the swing can be increased according to the diameter of the polishing plate. This provides a good guidance for the optimization of FAP process.

The cellular response to ionizing radiation continues to be of significant research interest in cancer radiotherapy, and DNA is recognized as the critical target for most of the biologic effects of radiation. Incident particles can cause initial DNA damages through physical and chemical interactions within a short time scale. Initial DNA damages can undergo repair via different pathways available at different stages of the cell cycle. The misrepair of DNA damage results in genomic rearrangement and causes mutations and chromosome aberrations, which are drivers of cell death. This work presents an integrated study of simulating cell response after proton irradiation with energies of 0.5-500 MeV (LET of 60-0.2 keV/µm). A model of a whole nucleus with fractal DNA geometry was implemented in TOPAS-nBio for initial DNA damage simulations. The default physics and chemistry models in TOPAS-nBio were used to describe interactions of primary particles, secondary particles, and radiolysis products within the nucleus. The initial DNA double-strand break (DSB) yield was found to increase from 6.5 DSB/Gy/Gbp at low-linear energy transfer (LET) of 0.2 keV/µm to 21.2 DSB/Gy/Gbp at high LET of 60 keV/µm. A mechanistic repair model was applied to predict the characteristics of DNA damage repair and dose response of chromosome aberrations. It was found that more than 95% of the DSBs are repaired within the first 24 h and the misrepaired DSB fraction increases rapidly with LET and reaches 15.8% at 60 keV/µm with an estimated chromosome aberration detection threshold of 3 Mbp. The dicentric and acentric fragment yields and the dose response of micronuclei formation after proton irradiation were calculated and compared with experimental results.

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 26%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

BACKGROUND In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. OBJECTIVE The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. METHODS We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. RESULTS After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. CONCLUSIONS Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

BackgroundIn December 2019, some COVID-19 cases were first reported and soon the disease broke out. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus.MethodsWe adopted the Huike database to extract news articles about coronavirus from major press media, between January 1st, 2020, to February 20th, 2020. The data were sorted and analyzed by Python software and Python package Jieba. We sought a suitable topic number using the coherence number. We operated Latent Dirichlet Allocation (LDA) topic modeling with the suitable topic number and generated corresponding keywords and topic names. We divided these topics into different themes by plotting them into two-dimensional plane via multidimensional scaling.FindingsAfter removing duplicates, 7791 relevant news reports were identified. We listed the number of articles published per day. According to the coherence value, we chose 20 as our number of topics and obtained their names and keywords. These topics were categorized into nine primary themes based on the topic visualization figure. The top three popular themes were prevention and control procedures, medical treatment and research, global/local social/economic influences, accounting for 32·6%, 16·6%, 11·8% of the collected reports respectively.InterpretationThe Chinese mass media news reports lag behind the COVID-19 outbreak development. The major themes accounted for around half the content and tended to focus on the larger society than on individuals. The COVID-19 crisis has become a global issue, and society has also become concerned about donation and support as well as mental health. We recommend that future work should address the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.FundingNational Social Science Foundation of China (18CXW021)Evidence before this studyThe novel coronavirus related news reports have engaged public attention in China during the COVID-19 crisis. Topic modeling of these news articles can produce useful information about the significance of mass media for early health communication. We searched the Huike database, the most professional Chinese media content database, using the search term “coronavirus” for related news articles published from January 1st, 2020, to February 20th, 2020. We found that these articles can be classified into different themes according to their emphasis, however, we found no other studies apply topic modeling method to study them.Added value of this studyTo our knowledge, this study is the first to investigate the patterns of health communications through media and the role the media have played and are still playing in the light of the current COVID-19 crisis in China with topic modeling method. We compared the number of articles each day with the outbreak development and identified there’s a delay in reporting COVID-19 outbreak progression for Chinese mass media. We identify nine main themes for 7791 collected news reports and detail their emphasis respectively.Implications of all the available evidenceOur results show that the mass media news reports play a significant role in health communication during the COVID-19 crisis, government can strengthen the report dynamics and enlarge the news coverage next time another disease strikes. Sentiment analysis of news data are needed to assess the actual effect of the news reports.

Controls in aircraft cockpit shall be accessible and usable for pilots in different body sizes. The appropriate representative of pilot population that should be taken into account in accessibility design is identified in this paper. General requirements for accessibility design are proposed. According to different operation frequencies, urgencies, and duration of the controls, a principle of arranging cockpit controls in different accessible areas is proposed. Finally, the cockpit accessibility test evaluation procedures and attentions are introduced.

In order to realize the large-scale and normal implementation of power-to-gas technology, as well as the large-capacity storage and long-distance transportation of gas in the later stage of electric hydrogen production, a power-to-gas technology with real-time energy conversion characteristics and large-scale energy storage characteristics is studied in this paper. Firstly, the water-electricity-gas coupling process between the electrolytic cell and the methanation reactor in the power-to-gas system is discussed in detail, and the model of the power-to-gas system based on the coordination of real-time energy conversion and large-scale energy storage is proposed. Then, based on a multi-energy coupling regional integrated energy system, a highly decoupled multi-step modelling method is adopted to construct its optimal operation model, and the equivalent variable substitution method is used to transform it into a linear programming problem. Finally, the calculation results show that the proposed power-to-gas technology can further improve the energy utilization efficiency due to the complementary characteristics of the two functions, so as to effectively promote the implementation of large-scale power-to-gas projects in the future.

Energy crisis and environmental pollution have expedited the transition of the energy system. Global use of low-carbon energy has increased from 1:6.16 to 1:5.37. Smart energy systems have received significant support and development to accelerate the development of smart cities and achieve the carbon neutrality goal. As a result of analyzing recent related publications and weighing their merits and downsides, it is determined that a more comprehensive and objective analysis of the main technologies underlying smart energy systems is necessary for the context of the new era. We report thoroughly on the six important hotspot technologies in smart energy systems, and undertake a comparative analysis of each technology's performance features, application status, and challenges. The ten key obstacles to developing a smart energy system are examined in terms of technology constraints, the social environment, human survival, and extreme climate circumstances. The four opportunities that smart energy systems confront in the digital age are examined in terms of governmental support, technology innovation, and public participation. The purpose of this research is to advance the creation of smart energy systems and the sustainable development of society in two ways: i) Smart energy system research should begin with a combination of technological innovation and practical application; ii) Key technologies in smart energy systems should consider the needs of people's livelihoods to evolve in a more intelligent and diverse path.

Short-term efficacy, adverse effects and the impact on quality of life (QoL) of a concomitant treatment with intensity-modulated radiation therapy (IMRT) and temozolomide (TMZ) in patients with brain metastases (BMs) from lung adenocarcinoma were evaluated. This study sought to confirm the benefit of adding TMZ to IMRT in patients with BMs from lung adenocarcinoma. Nine patients were enrolled and received a dose of 30 Gy in 10 daily fractions to clinical tumor volume (CTV) according to IMRT, then additional dose of 9 Gy in 3 fractions of IMRT was delivered to gross tumor volume (GTV) only with concomitant TMZ (75 mg/m2/day) orally during RT for 3 weeks. One patient achieved complete response (CR) (11.1%), 6 patients obtained partial response (PR) (66.7%), and there were no patients in progression. Therefore, objective response (OR) reached 77.8%. The main adverse effects included neutropenia, anemia, vomiting, fatigue and dizziness. Grade ≥3 of hematologic toxicities did not occur. However, the other 9 patients who received only intensity-modulated radiation had much worse results. The CR was 0, PR rate was 44.4%, OR rate was 44.4%. The results indicated that the benefit of adding TMZ to IMRT was confirmed in patients with BMs from lung adenocarcinoma. The treatment was active, a significant OR was observed, and achieved an improvement in QoL demonstrated by QoL grade (p

As radon is one of the most important natural radiation sources, its radiation hazard has always been a concern. α and β particles emitted by short-lived radioactive radon progeny nuclides could result in a high local dose and induce radiation damage to the respiratory tract. A detailed respiratory tract model needs to be built and dose distribution in the respiratory tract should be studied to reflect the characteristics of energy deposition caused by radon and its progeny. Therefore, in the present work, a dosimetric study was conducted on the respiratory tract and non-uniform dose distribution in the bronchial region was studied. First, a detailed voxel respiratory tract model was established based on the anatomic bronchial parameters of an adult Chinese male. The dimensional parameters of the tracheo-bronchial tree of an adult male adopted in ICRP Publication 66 (ICRP 1994 Human Respiratory Tract Model for Radiological Protection ICRP Publication 66 (Oxford: Pergamon)), featured by consecutive 16 generations of bronchi structures to express the irregular structure of the respiratory tract and the radiosensitive tissues in the bronchial region, were also built for dosimetric study. Then the deposition and clearance models recommended by ICRP were used to analyse the regional deposition and transfer in the respiratory tract, and a fluid dynamic simulation was used to obtain 3D distribution of radon progeny aerosol particles in the bronchial region. The result showed that the highest deposition fraction density occurs at the first and second generations of bronchi. Furthermore, the detailed voxel respiratory tract model along with the Monte Carlo method were used to obtain dose distribution in the BB region. It was found that the dose distribution in the respiratory tract is very non-uniform and the maximum voxel dose is about 30 times higher than the average voxel dose. The dose conversion factor (DCF) for lung in the home environment derived with the dosimetry method in the present work is 9.86 mSv·WLM-1. Sensitivity analysis was performed for the parameters involved in the DCF calculation and it was found that the unattached fraction and breathing rate influence the DCF the most.

Phase change materials (PCMs) have been widely used as efficient materials in latent heat thermal storage systems for various applications. The poor thermal conductivity of most organic phase change materials (OPCMs), however, has long been considered as one of big obstacles hindering their practical applications. Here, we report the first examples of Manganese dioxide nanowires and nanotubes based PCM nanocomposites (named as MnO2 NWs/PCM and MnO2 NTs/PCM) with enhanced thermal conductivity by simply using MnO2 nanowires and nanotubes as efficient nanofillers. The PCMs nanocomposites show high latent heat ranging from 140.1 J g−1 to 206.1 J g−1. The thermal conductivity of PCM nanocomposites were dramatically enhanced by incorporation of Manganese dioxide nanowires and nanotubes with a maximum value of 377.16% of that of pure PA achieved, which is nearly two times of that of control. X-ray diffraction (XRD) analysis shows that the incorporation of nanofillers does not change the crystalline structure of OPCMs while lowering its crystalline size. The PCM nanocomposites also show excellent thermal stability of recyclability. Only a slight loss of 2.8% in latent heat was observed after 100 times of melting/cooling cycles. Based on their high heat storage performance, excellent thermal conductivity and thermal stability of recyclability, the as-prepared PCM nanocomposites may have great potentials for energy saving applications.

A novel magnetic Fe3O4/graphene composite (FGC) was fabricated by a facile one-step reaction route and shown to be effective for sorbing U(VI) from aqueous solution. The structure, properties and application of the prepared FGC composite were well evaluated. The high saturation magnetization (45.6 emu/g) made FGC easier to be separated from the media within several seconds under an external magnetic. Effects of different ambient conditions (i.e., pH and ionic strength, contact time, temperatures) on sorption behaviors of U(VI) on FGC were carried out by batch experiments. According to the calculation of Langmuir model, the maximum sorption capacity of U(VI) on the FGC at pH 5.5 and 298 K was 176.47 mg/g. The sorption was correlated with the effects of pH, contact time, and temperature. X-ray photoelectron spectroscopy analysis revealed that U(VI) was sorbed on FGC via oxygen-containing functional groups. This work demonstrated that FGC could be recycled and used as an effective recyclable sorbent for sorption of U(VI).