Relating fragile-to-strong transition to fragile glass via lattice model simulations.

Glass formers are, in general, classified as strong or fragile depending on whether their relaxation rates follow Arrhenius or super-Arrhenius temperature dependence. There are, however, notable exceptions, such as water, which exhibit a fragile-to-strong (FTS) transition and behave as fragile and strong, respectively, at high and low temperatures. In this work, the FTS transition is studied using a distinguishable-particle lattice model previously demonstrated to be capable of simulating both strong and fragile glasses [C.-S. Lee, M. Lulli, L.-H. Zhang, H.-Y. Deng, and C.-H. Lam, Phys. Rev. Lett. 125, 265703 (2020)0031-900710.1103/PhysRevLett.125.265703]. Starting with a bimodal pair-interaction distribution appropriate for fragile glasses, we show that by narrowing down the energy dispersion in the low-energy component of the distribution, a FTS transition is observed. The transition occurs at a temperature at which the stretching exponent of the relaxation is minimized, in agreement with previous molecular dynamics simulations.

Correction: Surface mobility gradient and emergent facilitation in glassy films.

Correction for 'Surface mobility gradient and emergent facilitation in glassy films' by Qiang Zhai et al., Soft Matter, 2024, https://doi.org/10.1039/D4SM00221K.

Surface mobility gradient and emergent facilitation in glassy films.

Confining glassy polymers into films can substantially modify their local and film-averaged properties. We present a lattice model of film geometry with void-mediated facilitation behaviors but free from any elasticity effect. We analyze the spatially varying viscosity to delineate the transport properties of glassy films. The film mobility measurements reported by Yang et al., Science, 2010, 328, 1676 are successfully reproduced. The flow exhibits a crossover from a simple viscous flow to a surface-dominated regime as the temperature decreases. The propagation of a highly mobile front induced by the free surface is visualized in real space. Our approach provides a microscopic treatment of the observed glassy phenomena.

MGL: Mutual Graph Learning for Camouflaged Object Detection.

Camouflaged object detection, which aims to detect/segment the object(s) that blend in with their surrounding, remains challenging for deep models due to the intrinsic similarities between foreground objects and background surroundings. Ideally, an effective model should be capable of finding valuable clues from the given scene and integrating them into a joint learning framework to co-enhance the representation. Inspired by this observation, we propose a novel Mutual Graph Learning (MGL) model by shifting the conventional perspective of mutual learning from regular grids to graph domain. Specifically, an image is decoupled by MGL into two task-specific feature maps - one for finding the rough location of the target and the other for capturing its accurate boundary details. Then, the mutual benefits can be fully exploited by reasoning their high-order relations through graphs recurrently. It should be noted that our method is different from most mutual learning models that model all between-task interactions with the use of a shared function. To increase information interactions, MGL is built with typed functions for dealing with different complementary relations. To overcome the accuracy loss caused by interpolation to higher resolution and the computational redundancy resulting from recurrent learning, the S-MGL is equipped with a multi-source attention contextual recovery module, called R-MGL_v2, which uses the pixel feature information iteratively. Experiments on challenging datasets, including CHAMELEON, CAMO, COD10K, and NC4K demonstrate the effectiveness of our MGL with superior performance to existing state-of-the-art methods. The code can be found at https://github.com/fanyang587/MGL.

Rice nitrogen nutrition monitoring classification method based on the convolution neural network model: Direct detection of rice nitrogen nutritional status.

The nitrogen nutrition status affects the main factors of rice yield. In traditional rice nitrogen nutrition monitoring methods, most experts enter the farmland to observe leaf color and growth and apply an appropriate amount of nitrogen fertilizer according to the results. However, this method is labor- and time-consuming. To realize automatic rice nitrogen nutrition monitoring, we constructed the Jiangxi rice nitrogen nutrition monitoring model based on a convolution neural network (CNN) using the same region rice canopy image in different generation periods. Our CNN model was evaluated using multiple evaluation criteria (Accuracy, Recall, Precision, and F1 score). The results show that the same CNN model could distinguish the rice nitrogen nutrition status in different periods, which can completely realize the automatic discrimination of nitrogen nutrition status so as to guide the scientific nitrogen application of rice in this area. This will greatly improve the discrimination efficiency of the nitrogen nutrition status and reduce the time and labor cost. The application of the proposed method also proved that the CNN model can be applied in the discrimination of the nitrogen nutrition status. Among CNN models, GoogleNet model proposed a CNN architecture named Inception which can improve the depth of the network and extract higher-level features without changing the amount of calculation of the model. The GoogleNet model achieved the highest accuracy, 95.7%.

Taxonomic status of Rana nigromaculata mongolia and the validity of Pelophylax tenggerensis (Anura, Ranidae).

The Black-spotted Pond Frog, Pelophylax nigromaculatus, is widely distributed across mainland China, Korean Peninsula, and Japan. The taxonomic relationships among P. n. nigromaculatus, Rana nigromaculata mongolia (sensu P. n. mongolicus), and P. tenggerensis have long been ambiguous. Here we examine the topotype specimens of P. tenggerensis and R. n. mongolia, and provide phylogenic analyses based on four mitochondrial DNA sequences. The combined evidences from morphology and molecular phylogeny have shown the distinct specific-level of P. n. mongolicus that distant from P. nigromaculatus, while indicating the homogeneity between P. n. mongolicus and P. tenggerensis. Thus, we suggest elevating P. n. mongolicus as a full species Pelophylax mongolicus comb. nov., and place P. tenggerensis to be a secondary synonym of P. mongolicus comb. nov.

Correlation between the warning symptoms and prognosis of cardiac arrest.

BACKGROUND: A low survival rate in patients with cardiac arrest is associated with failure to recognize the condition in its initial stage. Therefore, recognizing the warning symptoms of cardiac arrest in the early stage may play an important role in survival. AIM: To investigate the warning symptoms of cardiac arrest and to determine the correlation between the symptoms and outcomes. METHODS: We included all adult patients with all-cause cardiac arrest who visited Peking University Third Hospital or Beijing Friendship Hospital between January 2012 and December 2014. Data on population, symptoms, resuscitation parameters, and outcomes were analysed. RESULTS: Of the 1021 patients in the study, 65.9% had symptoms that presented before cardiac arrest, 25.2% achieved restoration of spontaneous circulation (ROSC), and 7.2% survived to discharge. The patients with symptoms had higher rates of an initial shockable rhythm (12.2% vs 7.5%, P = 0.020), ROSC (29.1% vs 17.5%, P = 0.001) and survival (9.2% vs 2.6%, P = 0.001) than patients without symptoms. Compared with the out-of-hospital cardiac arrest (OHCA) without symptoms subgroup, the OHCA with symptoms subgroup had a higher rate of calls before arrest (81.6% vs 0.0%, P < 0.001), health care provider-witnessed arrest (13.0% vs 1.4%, P = 0.001) and bystander cardiopulmonary resuscitation (15.5% vs 4.9%, P = 0.002); a shorter no flow time (11.7% vs 2.8%, P = 0.002); and a higher ROSC rate (23.8% vs 13.2%, P = 0.011). Compared to the in-hospital cardiac arrest (IHCA) without symptoms subgroup, the IHCA with symptoms subgroup had a higher mean age (66.2 ± 15.2 vs 62.5 ± 16.3 years, P = 0.005), ROSC (32.0% vs 20.6%, P = 0.003), and survival rates (10.6% vs 2.5%, P < 0.001). The top five warning symptoms were dyspnea (48.7%), chest pain (18.3%), unconsciousness (15.2%), paralysis (4.3%), and vomiting (4.0%). Chest pain (20.9% vs 12.7%, P = 0.011), cardiac etiology (44.3% vs 1.5%, P < 0.001) and survival (33.9% vs 16.7%, P = 0.001) were more common in males, whereas dyspnea (54.9% vs 45.9%, P = 0.029) and a non-cardiac etiology (53.3% vs 41.7%, P = 0.003) were more common in females. CONCLUSION: Most patients had warning symptoms before cardiac arrest. Dyspnea, chest pain, and unconsciousness were the most common symptoms. Immediately recognizing these symptoms and activating the emergency medical system prevents resuscitation delay and improves the survival rate of OHCA patients in China.

Toxic epidermal necrolysis with systemic lupus erythematosus: case report and review of the literature.

Toxic epidermal necrolysis (TEN) and Stevens-Johnson syndrome (SJS) are potentially fatal mucocutaneous diseases characterized by extensive necrosis and exfoliation of the epidermis. TEN and SJS are most often caused by various kinds of drugs. Other risk factors for SJS/TEN include pneumonia infection, HIV infection, genetic factors, underlying immune diseases, and tumors. SJS and TEN were first identified in 1922, but at present, a widely recognized view is that SJS and TEN represent phases in the continuous progress of the same disease. SJS/TEN has a very high mortality, but is rare, and cases of SJS/TEN combined with systemic lupus erythematosus (SLE) are even less common. Occasionally, acute cutaneous manifestations of SLE and SJS/TEN can be phenotypically similar, both causing extensive epidermal necrosis. In this paper, we present a recent case of a 32-year-old female SLE patient with a drug-induced (the health product, astaxanthin) TEN/SJS. To provide context to this case, we have reviewed relevant case studies published in English, accessed via PubMed databases. The search covers all published case studies from 1988 to 2019. We collected a total of 30 cases in the literature, and analyzed their characteristics from the aspects of gender, suspicious medication history, and treatment in order to expand clinicians' approach to diagnosis and treatment.

Preparation and Characterisation of Polyurethane Acrylate-Based Titanium Dioxide Pigment for Blue Light-Curable Ink.

Herein, a polyurethane acrylate-based TiO2 (PU-TiO2) was fabricated using a two-step method. First, a polyurethane prepolymer was prepared. Second, PU-TiO2 was prepared using amino-modified TiO2 (A-TiO2). The best synthesis process of the polyurethane prepolymer was when the reaction temperature was 80 °C, the reaction time was 3 h and the R-value of the polyurethane acrylate was 2. Next, the influence of the A-TiO2 content on the structure and performance of PU-TiO2 was examined. The analysis of the rheological properties of the PU-TiO2 ink indicated that its viscosity gradually increased as the A-TiO2 content increased. The tensile performance of film improved because of the presence of A-TiO2. The photo-polymerisation and photo-rheological performance indicated that the PU-TiO2 structure changed from a hyperbranched structure with TiO2 as the core to a segmented structure, as the A-TiO2 content was 3%.

Impact Measurement of COVID-19 Lockdown on China's Electricity-Carbon Nexus.

Lockdown measures to prevent the spread of coronavirus disease 2019 (COVID-19) resulted in the plummeting of China's overall electric-power demand and production. To date, power generation remains one of the largest carbon dioxide (CO2) emitting sectors of China on account of its high carbon intensity. Within this context, our study seeks to measure the impacts of COVID-19 lockdown on the electricity-power related carbon footprints on both generation and consumption sides. Built on statistical data of electricity generation and consumption released by the National Bureau of Statistics of China (NBSC), we calculate he nationwide electricity related CO2 emission changes in regional, economic-sectoral and technological dimensions during January-April 2020, when the strictest lock-down measures were taken in China and compare the results with the same months of the year prior. Our results show that both east and central China power grids witnessed drastic reduction (15.0% and 13.8%) in electricity-generation caused CO2 emissions; and the biggest falls of provincial-scale electricity-generation CO2 emission took place in Hubei (27.3%). Among China's electricity production mix, coal remains the biggest CO2 emitter and contributed 95.7% of the overall nationwide reduction. The most significant decline of the nationwide consumptive-electricity carbon footprint was by 10.1% in February, with the secondary economic sector the biggest contributor.

Life Cycle Impact Assessment of Garbage-Classification Based Municipal Solid Waste Management Systems: A Comparative Case Study in China.

Confronted with a series of problems caused by surging generation of municipal solid waste (MSW), the Chinese central and local governments have promulgated and implemented policies to deal with them, including promotions of the classification of MSW. However, to date, practical knowledge and understanding about benefits for garbage classification from its environmental performance perspective is still limited. The present study is purposed to comprehensively investigate the environmental effects of garbage classification on municipal solid waste management (MSWM) systems based on three proposed garbage classification scenarios in China, via a comparative life cycle impact assessment (LCIA). Taking advantage of Impact Assessment of Chemical Toxics (IMPACT) 2002+ method, this comparative LCIA study can quantitatively evaluate midpoint, endpoint, and single scored life cycle impacts for the studied MSWM systems. A Monte Carlo uncertainty analysis is carried out to test the effectiveness and reliabilities of the LCIA results. The LCIA and uncertainty analysis results show that MSWM systems based on various garbage classification scenarios have significant variations in the studied midpoint, endpoint, and single scored environmental impacts. Different garbage classification scenarios have their individual environmental-friendly superiority for specific impact categories. Overall, results of this study demonstrate that MSW treatment systems integrated with garbage classification are more environmentally friendly by comparison with non-classification; and that the more elaborate the level of MSW classification, the smaller its impacts on the environment.

Clinical and imaging characteristics of hematologic disease complicated by air leak syndrome: A STROBE-compliment observational study.

There are limited systematic studies on hematologic disease complicated by air leak syndrome (ALS). Physicians in radiology departments and hematology departments have a limited awareness of ALS.The aim of this study was to explore the similarities and differences in clinical data between the clinical group and imaging group in patients with hematologic disease complicated by ALS.Clinical and CT data for 59 patients with hematologic disease complicated by ALS in our hospital were retrospectively reviewed. Patients were assessed by clinical grouping and image grouping. Data were compared between groups, and P < .05 was considered statistically significant.Dyspnea occurred more often in the allo-HSCT (allogeneic hematopoietic stem cell transplantation) group than that in the non-allo-HSCT group (68.8% vs 4.7%, P < .001), there were statistically significant differences in inducing factors between groups, and differences in other aspects were not statistically significant. Chest tightness and dyspnea occurred more often in the allo-HSCT with BO/BOOP (bronchiolitis Obliteran/bronchiolitis obliterans organizing pneumonia) group than those in the allo-HSCT without BO/BOOP group (80.0% vs 9.1%, P = .013), and differences in other aspects were not statistically significant. Chest pain occurred more often in the HPT (hydropneumothorax) group than that in the other 3 groups (pure pneumothorax [PT], pulmonary interstitial emphysema [PIE], complex ALS) (71.4% vs 11.1%, 0.0%, and 26.5%, P = .005); ALS thickness in the HPT group was greater than that in the other 2 groups (PIE and complex ALS) (19.7 vs 3.5 cm and 9.5 cm, P = .001); catheter drainage occurred more often in the HPT group than that in the other three groups (PT, PIE, complexALS) (64.3% vs 22.2%, 0.0%, and 2.9%, P = .001).ALS is a high risk in male patients who have a low BMI, have leukemia as a basic disease, and have basic lung diseases (eg, BO/BOOP). CT types are mainly complex ALS, HPT, and pure PT. In addition, clinical symptoms for patients in the HPT group are severe, and there is a high prevalence of catheter drainage.

Life Cycle Assessment on Wave and Tidal Energy Systems: A Review of Current Methodological Practice.

Recent decades have witnessed wave and tidal energy technology receiving considerable attention because of their low carbon emissions during electricity production. However, indirect emissions from their entire life cycle should not be ignored. Therefore, life cycle assessment (LCA) has been widely applied as a useful approach to systematically evaluate the environmental performance of wave and tidal energy technologies. This study reviews recent LCA studies on wave and tidal energy systems for stakeholders to understand current status of methodological practice and associated inherent limitations and reveal future research needs for application of LCA on wave and tidal technologies. The conformance of the selected LCAs to ISO 14040 (2006) and 14044 (2006) are critically analyzed in strict accordance with the ISO stepwise methodologies, namely, goal and scope definition, life cycle inventory (LCI) analysis, as well as life cycle impact assessment (LCIA). Our systematically screening of these studies indicates that few of the selected studies are of strict conformance with ISO 14040 and 14044 standards, which makes the results unreliable and thus further reduces the confidence of interested stakeholders. Further, our review indicates that current LCA practice on wave and tidal energies is lacking consideration of temporal variations, which should be addressed in future research, as it causes inaccuracy and uncertainties.

Distribution and drug resistance of pathogenic bacteria in emergency patients.

BACKGROUND: Antibiotic resistance has become a global threat for human health, calling for rational use of antibiotics. AIM: To analyze the distribution and drug resistance of the bacteria, providing the prerequisite for use of antibiotics in emergency patients. METHODS: A total of 2048 emergency patients from 2013 to 2017 were enrolled. Their clinical examination specimens were collected, followed by isolation of bacteria. The bacterial identification and drug susceptibility testing were carried out. RESULTS: A total of 3387 pathogens were isolated. The top six pathogens were Acinetobacter baumannii (660 strains), Staphylococcus aureus (436 strains), Klebsiella pneumoniae (347 strains), Pseudomonas aeruginosa (338 strains), Escherichia coli (237 strains), and Candida albicans (207 strains). The isolation rates of these pathogens decreased year by year except Klebsiella pneumoniae, which increased from 7.1% to 12.1%. Acinetobacter baumannii is a widely-resistant strain, with multiple resistances to imipenem, ciprofloxacin, minocycline and tigecycline. The Staphylococcus aureus had high resistance rates to levofloxacin, penicillin G, and tetracycline. But the susceptibility of it to vancomycin and tigecycline were 100%. Klebsiella pneumoniae had high resistance rates to imipenem, cefoperazone/sulbactam, amikacin, and ciprofloxacin, with the lowest resistance rate to tigecycline. The resistance rates of Pseudomonas aeruginosa to cefoperazone/sulbactam and imipenem were higher, with the resistance rate to amikacin below 10%. Besides, Escherichia coli had high resistance rates to ciprofloxacin and cefoperazone/sulbactam and low resistance rates to imipenem, amikacin, and tigecycline. CONCLUSION: The pathogenic bacteria isolated from the emergency patients were mainly Acinetobacter baumannii, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli, and Candida albicans. The detection rates of drug-resistant bacteria were high, with different bacteria having multiple drug resistances to commonly used antimicrobial agents, guiding the rational use of drugs and reducing the production of multidrug-resistant bacteria.

A Novel Approach to Droplet's 3D Shape Recovery Based on Mask R-CNN and Improved Lambert⁻Phong Model.

Aiming at the demand for extracting the three-dimensional shapes of droplets in microelectronic packaging, life science, and some related fields, as well as the problems of complex calculation and slow running speed of conventional shape from shading (SFS) illumination reflection models, this paper proposes a Lambert⁻Phong hybrid model algorithm to recover the 3D shapes of micro-droplets based on the mask regions with convolutional neural network features (R-CNN) method to extract the highlight region of the droplet surface. This method fully integrates the advantages of the Lambertian model's fast running speed and the Phong model's high accuracy for reconstruction of the highlight region. First, the Mask R-CNN network is used to realize the segmentation of the highlight region of the droplet and obtain its coordinate information. Then, different reflection models are constructed for the different reflection regions of the droplet, and the Taylor expansion and Newton iteration method are used for the reflection model to get the final height of all positions. Finally, a three-dimensional reconstruction experimental platform is built to analyze the accuracy and speed of the algorithm on the synthesized hemisphere image and the actual droplet image. The experimental results show that the proposed algorithm based on mask R-CNN had better precision and shorter running time. Hence, this paper provides a new approach for real-time measurement of 3D droplet shape in the dispensing state.

Performance of Simplified Acute Physiology Score 3 In Predicting Hospital Mortality In Emergency Intensive Care Unit.

BACKGROUND: Since the 1980s, severity of illness scoring systems has gained increasing popularity in Intensive Care Units (ICUs). Physicians used them for predicting mortality and assessing illness severity in clinical trials. The objective of this study was to assess the performance of Simplified Acute Physiology Score 3 (SAPS 3) and its customized equation for Australasia (Australasia SAPS 3, SAPS 3 [AUS]) in predicting clinical prognosis and hospital mortality in emergency ICU (EICU). METHODS: A retrospective analysis of the EICU including 463 patients was conducted between January 2013 and December 2015 in the EICU of Peking University Third Hospital. The worst physiological data of enrolled patients were collected within 24 h after admission to calculate SAPS 3 score and predicted mortality by regression equation. Discrimination between survivals and deaths was assessed by the area under the receiver operator characteristic curve (AUC). Calibration was evaluated by Hosmer-Lemeshow goodness-of-fit test through calculating the ratio of observed-to-expected numbers of deaths which is known as the standardized mortality ratio (SMR). RESULTS: A total of 463 patients were enrolled in the study, and the observed hospital mortality was 26.1% (121/463). The patients enrolled were divided into survivors and nonsurvivors. Age, SAPS 3 score, Acute Physiology and Chronic Health Evaluation Score II (APACHE II), and predicted mortality were significantly higher in nonsurvivors than survivors (P < 0.05 or P < 0.01). The AUC (95% confidence intervals [CI s]) for SAPS 3 score was 0.836 (0.796-0.876). The maximum of Youden's index, cutoff, sensitivity, and specificity of SAPS 3 score were 0.526%, 70.5 points, 66.9%, and 85.7%, respectively. The Hosmer-Lemeshow goodness-of-fit test for SAPS 3 demonstrated a Chi-square test score of 10.25, P = 0.33, SMR (95% CI) = 0.63 (0.52-0.76). The Hosmer-Lemeshow goodness-of-fit test for SAPS 3 (AUS) demonstrated a Chi-square test score of 9.55, P = 0.38, SMR (95% CI) = 0.68 (0.57-0.81). Univariate and multivariate analyses were conducted for biochemical variables that were probably correlated to prognosis. Eventually, blood urea nitrogen (BUN), albumin,lactate and free triiodothyronine (FT3) were selected as independent risk factors for predicting prognosis. CONCLUSIONS: The SAPS 3 score system exhibited satisfactory performance even superior to APACHE II in discrimination. In predicting hospital mortality, SAPS 3 did not exhibit good calibration and overestimated hospital mortality, which demonstrated that SAPS 3 needs improvement in the future.

2,2'-Fluorine mono-carbonyl curcumin induce reactive oxygen species-Mediated apoptosis in Human lung cancer NCI-H460 cells.

In this paper, we synthesized three fluorine-substituted mono-carbonyl curcumin analogs and evaluated their cytotoxicity against several cancer cells by the MTT assay. The results exhibited that all the three compounds were more active than the leading curcumin. Especially, 2,2'-F mono-carbonyl curcumin, 1a, surfaced as an important lead compound displaying almost 4-fold cytotoxicity relative to curcumin. More importantly, 1a was more stable in (RPMI)-1640 medium and more massive uptake than curcumin, which may be relationship to their cytotoxicity, apoptotic acitivity and reactive oxygen species generation. And then, the generation of reactive oxygen species can disrupt the intracellular redox balance, induce lipid peroxidation, cause the collapse of the mitochondrial membrane potential and ultimately lead to apoptosis. The results not only suggest that 2,2'-F mono-carbonyl curcumin (1a) may cause cancer cells apoptosis through reactive oxygen species-Mediated pathway, but also gives us an important information for design of mono-carbonyl curcumin analog.