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The aim of this study was to develop a simple but effective nomogram to predict risk of septic cardiomyopathy (SCM) in the intensive care unit (ICU). We analyzed data from patients who were first admitted to the ICU for sepsis between 2008 and 2019 in the MIMIC-IV database, with no history of heart disease, and divided them into a training cohort and an internal validation cohort at a 7:3 ratio. SCM is defined as sepsis diagnosed in the absence of other cardiac diseases, with echocardiographic evidence of left (or right) ventricular systolic or diastolic dysfunction and a left ventricular ejection fraction (LVEF) of less than 50%. Variables were selected from the training cohort using the Least Absolute Shrinkage and Selection Operator (LASSO) regression to develop an early predictive model for septic cardiomyopathy. A nomogram was constructed using logistic regression analysis and its receiver operating characteristic (ROC) and calibration were evaluated in two cohorts. A total of 1562 patients participated in this study, with 1094 in the training cohort and 468 in the internal validation cohort. SCM occurred in 13.4% (147 individuals) in the training cohort, 16.0% (75 individuals) in the internal validation cohort. After adjusting for various confounding factors, we constructed a nomogram that includes SAPS II, Troponin T, CK-MB index, white blood cell count, and presence of atrial fibrillation. The area under the curve (AUC) for the training cohort was 0.804 (95% CI 0.764–0.844), and the Hosmer–Lemeshow test showed good calibration of the nomogram (P = 0.288). Our nomogram also exhibited good discriminative ability and calibration in the internal validation cohort. Our nomogram demonstrated good potential in identifying patients at increased risk of SCM in the ICU. [ABSTRACT FROM AUTHOR]

Process monitoring plays a pivotal role in elucidating the intricate interplay among process, structure, and property in additive manufacturing production. The control of powder spreading affects not only particle adhesion but also rearrangement, both of which are indispensable constituents in the selective laser melting (SLM) process. To develop a novel monitoring process, this study proposed a convolutional Takagi–Sugeno–Kang fuzzy neural network (C-TSKFNN) to assess images with uneven powder distribution. The performance of the model was compared with that of conventional image analysis and state-of-the-art deep learning models. With its fusion layer and TSKFNN design, the C-TSKFNN model retains the distinctive characteristics of input images and minimizes expenditures through trainable parameters. The experimental results demonstrated that the average F1 score of the C-TSKFNN model achieved 97.07% and that it had the lowest standard deviation compared to state-of-the-art deep learning models. The trainable parameters were only 103,506, which is lower than those of models. Defect information was also provided locally through a model interpretation technique, facilitating the monitoring of SLM manufacturing. [ABSTRACT FROM AUTHOR]

The incidence of Lyme borreliosis has risen, accompanied by persistent symptoms. The innate immune system and related cytokines are crucial in the host response and symptom development. We characterized cytokine production capacity before and after antibiotic treatment in 1,060 Lyme borreliosis patients. We observed a negative correlation between antibody production and IL-10 responses, as well as increased IL-1Ra responses in patients with disseminated disease. Genome-wide mapping the cytokine production allowed us to identify 34 cytokine quantitative trait loci (cQTLs), with 31 novel ones. We pinpointed the causal variant at the TLR1-6-10 locus and validated the regulation of IL-1Ra responses at transcritpome level using an independent cohort. We found that cQTLs contribute to Lyme borreliosis susceptibility and are relevant to other immune-mediated diseases. Our findings improve the understanding of cytokine responses in Lyme borreliosis and provide a genetic map of immune function as an expanded resource. Common genetic variants can affect an individual's immune response to pathogens. Here, the authors uncover and characterize variants regulating cytokine responses in Lyme Borreliosis in 1,060 patients. [ABSTRACT FROM AUTHOR]

In a streaming environment, the characteristics and labels of instances may change over time, forming concept drifts. Previous studies on data stream learning generally assume that the true label of each instance is available or easily obtained, which is impractical in many real-world applications due to expensive time and labor costs for labeling. To address the issue, an active broad learning based on multi-objective evolutionary optimization is presented to classify non-stationary data stream. The instance newly arrived at each time step is stored to a chunk in turn. Once the chunk is full, its data distribution is compared with previous ones by fast local drift detection to seek potential concept drift. Taking diversity of instances and their relevance to new concept into account, multi-objective evolutionary algorithm is introduced to find the most valuable candidate instances. Among them, representative ones are randomly selected to query their ground-truth labels, and then update broad learning model for drift adaption. More especially, the number of representative is determined by the stability of adjacent historical chunks. Experimental results for 7 synthetic and 5 real-world datasets show that the proposed method outperforms five state-of-the-art ones on classification accuracy and labeling cost due to drift regions accurately identified and the labeling budget adaptively adjusted. [ABSTRACT FROM AUTHOR]

Micron-level flaws on component surface can seriously affect the optical and mechanical properties of optics, so it is significant to accurately classify and repair surface flaws. However, the small scale, multiple categories, and complex characteristics of surface flaws make the accurate classification a great challenge in the field of precision optical engineering. In this work, a novel automated classification approach is proposed for multi-classification of flaws. Images of flaws illuminated by multi-light sources are automatically acquired by classification equipment to enrich the characteristics of flaws, and a series of automated workflows are set up to accomplish flaw detection, classification, and mitigation. SingleCNN-MergeRGB, a feature extraction structure based on a single convolutional neural network (CNN) and multi-light source fusion, is constructed to extract the integrated features of flaws under different illumination. The experimental results show that SingleCNN-MergeRGB has stronger capability of feature description compared with single light source and other feature extraction networks. The integrated deep learning architecture SingleCNN-MergeRGB + SVM and prediction probability threshold adjustment strategy are proposed to improve the accuracy of flaw classification and correct failure cases. Validation results on the test set show that the proposed flaw classification method obtains an accuracy of 96.34% and a recall rate of 100%. The experiments demonstrate the effectiveness of the automatic classification equipment and methods in this work in the classification of surface flaws in large-aperture optical components. [ABSTRACT FROM AUTHOR]

From childhood to adolescence, the spatiotemporal development pattern of the human brain white matter connectome and its underlying transcriptomic and cellular mechanisms remain largely unknown. With a longitudinal diffusion MRI cohort of 604 participants, we map the developmental trajectory of the white matter connectome from global to regional levels and identify that most brain network properties followed a linear developmental trajectory. Importantly, connectome-transcriptomic analysis reveals that the spatial development pattern of white matter connectome is potentially regulated by the transcriptomic architecture, with positively correlated genes involve in ion transport- and development-related pathways expressed in excitatory and inhibitory neurons, and negatively correlated genes enriches in synapse- and development-related pathways expressed in astrocytes, inhibitory neurons and microglia. Additionally, the macroscale developmental pattern is also associated with myelin content and thicknesses of specific laminas. These findings offer insights into the underlying genetics and neural mechanisms of macroscale white matter connectome development from childhood to adolescence. Joint connectomic and transcriptomic analyses of longitudinal dMRI data reveal the multiscale developmental pattern of the human white matter connectome from childhood to adolescence. [ABSTRACT FROM AUTHOR]

The formation of biofilms is closely associated with persistent and chronic infections, and physiological heterogeneity such as pH and oxygen gradients renders biofilms highly resistant to conventional antibiotics. To date, effectively treating biofilm infections remains a significant challenge. Herein, we report the fabrication of micellar nanoparticles adapted to heterogeneous biofilm microenvironments, enabling nitric oxide (NO) release through two distinct photoredox catalysis mechanisms. The key design feature involves the use of tertiary amine (TA) moieties, which function as sacrificial agents to avoid the quenching of photocatalysts under normoxic and neutral pH conditions and proton acceptors at acidic pH to allow deep biofilm penetration. This biofilm-adaptive NO-releasing platform shows excellent antibiofilm activity against ciprofloxacin-resistant Pseudomonas aeruginosa (CRPA) biofilms both in vitro and in a mouse skin infection model, providing a strategy for combating biofilm heterogeneity and biofilm-related infections. Biofilms are heterogeneous and difficult to treat. Here, the authors report the preparation of micellar nanoparticles specifically for the treatment of biofilm, that release nitric oxide through two distinct photoredox catalysis mechanisms. [ABSTRACT FROM AUTHOR]

We investigate the Z b , Z c and Z cs states within the chiral effective field theory framework and the S-wave single channel molecule picture. With the complex scaling method, we accurately solve the Schrödinger equation in momentum space. Our analysis reveals that the Z b (10610) , Z b (10650) , Z c (3900) and Z c (4020) states are the resonances composed of the S-wave (B B ¯ ∗ + B ∗ B ¯) / 2 , B ∗ B ¯ ∗ , (D D ¯ ∗ + D ∗ D ¯) / 2 and D ∗ D ¯ ∗ , respectively. Furthermore, although the Z cs (3985) and Z cs (4000) states exhibit a significant difference in width, these two resonances may originate from the same channel, the S-wave (D s D ¯ ∗ + D s ∗ D ¯) / 2 . Additionally, we find two resonances in the S-wave D s ∗ D ¯ ∗ channel, corresponding to the Z cs (4123) and Z cs (4220) states that await experimental confirmation. [ABSTRACT FROM AUTHOR]

Background: The disease burden attributable to chronic obstructive pulmonary disease (COPD) is significant worldwide. Some studies have linked exposure to air pollution to COPD, but there has been little research on this. Methods: We aimed to assess the COPD-related disease burden attributable to air pollution from multiple epidemiological perspectives. This study conducted a three-stage analysis. Firstly, we reported on the burden of disease worldwide in 2019 by different subgroups including sex, age, region, and country. Secondly, we studied the trends in disease burden from 1990 to 2019. Finally, we explored the association of some national indicators with disease burden to look for risk factors. Results: In 2019, the death number of COPD associated with air pollution accounted for 2.32% of the total global death, and the number of DALY accounted for 1.12% of the global DALY. From 1990 to 2019, the death number of COPD associated with air pollution increased peaked at 1.41 million in 1993, fluctuated, and then declined. We found the same temporal pattern of DALY. The corresponding age-standardized rates had been falling. At the same time, the burden of COPD associated with air pollution was also affected by some national indicators. Conclusions: This study indicated that air pollution-related COPD contributed to a significant global disease burden. We called for health policymakers to take action and interventions targeting vulnerable countries and susceptible populations. [ABSTRACT FROM AUTHOR]

In this work, we evaluated the widths of the pionic and radiative transitions from the T c s ¯ 0 + (2900) to the D s 1 + (2460) in the D s 1 + (2460) molecular frame and the D s 1 + (2460) charmed-strange meson frame. Our estimations demonstrate that the transition widths in the D s 1 + (2460) molecular frame are much larger than those in the the D s 1 + (2460) charmed-strange meson frame. Specifically, the ratio of the widths of Γ (T c s ¯ 0 + (2900) → D s 1 + π 0) and Γ (T c s ¯ 0 + (2900) → D + (0) K 0 (+)) is estimated to be around 0.1 in the D s 1 + (2460) charmed-strange meson frame, whereas the lower limit of this ratio is 0.67 in the D s 1 + (2460) molecular frame. Thus, the aforementioned ratio could be employed as a tool for testing the nature of the D s 1 + (2460) . [ABSTRACT FROM AUTHOR]

Photonic crystals (PCs) with slow photon effect and multiple scattering for its three-dimensional ordered structure have been applied to improve light utilization and enhance photocatalytic activity. A ternary-structured photocatalyst was prepared. Bi2MoO6 was first sensitized by graphite-carbon nitride quantum dots (g-CNQDs) by in situ coupling via a hydrothermal method. The best performance of Bi2MoO6/g-CNQDs was 3.56 times higher than that of Bi2MoO6. The introduction of g-CNQDs improved both the light absorption range and charge transfer efficiency for Bi2MoO6/g-CNQDs composites. Furthermore, because of the combination of the g-CNQDs with the Bi2MoO6 nanosheets, the separation efficiency of photogenerated carriers was improved and the recombination rate was greatly reduced. To further improve light utilization, SiO2 PCs were composited to the above Bi2MoO6/g-CNQDs by spin coating to obtain ternary-structured Bi2MoO6/g-CNQDs/SiO2 PCs. The effect of the photonic band gap (PBG) of PCs on photocatalytic activity was investigated, and the photocatalytic activity was highest when the PBG was located near the absorption peak of g-CNQDs at 464 nm, which was 5.56 times higher than that of pure Bi2MoO6. The farther the photonic PBG is away from the absorption edge of g-CNQDs, the lower the photocatalytic activity of the composite membranes. This work provides a way to construct multiple-structured photocatalysts with high photocatalytic activity and confirms that PCs with precisely tuned band gap will substantially enhance the activity of photocatalysts. Highlights: A ternary-structured photocatalyst Bi2MoO6/g-CNQDs/SiO2 PCs was synthesized. Light harvesting is enhanced and the separation efficiency of photogenerated carriers is improved. The optimized Bi2MoO6/g-CNQDs/SiO2 PCs exhibit excellent photodegradation efficiency. As-prepared composite film photocatalyst has excellent reproducibility and stability. [ABSTRACT FROM AUTHOR]

Anomalous event detection in giant amount surveillance footage in real world is currently an active research area. Variery and rareness of the anomaly events is still a thorny challenge to deal with. In this paper, we propose a multi-stage fusion instance learning method (MFIL) for inferring anomalous event pattern and predicting anomaly appearance in videos. We propose object-aware model and action-aware model to represent regularities of human objects and actions among frames exploiting cascaded deep network models. Furthermore we improve and represent fusion instance learning method for fetching and maximizing anomaly scores via object and action regularities in anomalous sequences from videos. We validate the performance of MFIL on action movie and UCF-Crime respectively, both contain anomalous and violent events. Experimental results demonstrated that MFIL is effective for anomalous event detection in videos gathered from real world. [ABSTRACT FROM AUTHOR]

Small fused silica components with complex structure, such as hemispherical shell resonator in inertial navigation system, are the core components of the equipment in precision optics, aerospace, and other fields. Due to the hard and brittle characteristics of fused silica, these components easily form surface defects in grinding process. This restricts the improvement of equipment performance. The small ball-end permanent-magnet magnetorheological polishing can remove the surface defects of these workpieces. However, due to the high hardness of fused silica, the material removal rate in the polishing process is low. This makes it difficult to increase production and reduce costs. In this research, a method to improve the polishing efficiency by the promoting effect of water-bath heating and NaOH addition on polishing velocity and chemical reaction is proposed. The promotion mechanism is studied. It is found that adding NaOH to magnetorheological fluid can not only promote the chemical removal of fused silica by abrasive particles, but also soften the surface and subsurface of workpiece through chemical reaction to improve the mechanical removal of abrasive particles. Meanwhile, adding NaOH can reduce the zero-field viscosity of magnetorheological fluid. This can increase the polishing velocity of abrasive particles and the number of abrasive particles participating in material removal per unit time. Moreover, increasing the temperature of alkaline magnetorheological fluid by water-bath heating can not only improve the chemical reaction rate to generate more reaction product per unit time, but also further reduce the zero-field viscosity of magnetorheological fluid to increase the polishing velocity. The experimental result shows that when the magnetorheological fluid temperature is 60 °C and the pH value is 14, the material removal rate can be increased by 287%, and the polished surface roughness Sa can be reduced from 208.4 to 12.3 nm. [ABSTRACT FROM AUTHOR]

Myeloid cells, crucial players in antitumoral defense, are affected by tumor-derived factors and treatment. The role of myeloid cells and their progenitors prior to tumor infiltration is poorly understood. Here we show single-cell transcriptomics and functional analyses of the myeloid cell lineage in patients with non-medullary thyroid carcinoma (TC) and multinodular goiter, before and after treatment with radioactive iodine compared to healthy controls. Integrative data analysis indicates that monocytes of TC patients have transcriptional upregulation of antigen presentation, reduced cytokine production capacity, and overproduction of reactive oxygen species. Interestingly, these cancer-related pathological changes are partially removed upon treatment. In bone marrow, TC patients tend to shift from myelopoiesis towards lymphopoiesis, reflected in transcriptional differences. Taken together, distinct transcriptional and functional changes in myeloid cells arise before their infiltration of the tumor and are already initiated in bone marrow, which suggests an active role in forming the tumor immune microenvironment. Myeloid cells contribute to the tumor microenvironment of thyroid cancers, but their functional relevance is lesser known. Here authors show that myeloid cells infiltrating non-medullary thyroid carcinomas upregulate their antigen presentation-related genes, release less cytokines and over-produce reactive oxygen species, with transcriptional changes already present in extra-tumoral myeloid cells. [ABSTRACT FROM AUTHOR]

Existing studies suggested that ambient temperature may affect the attack of acute appendicitis. However, the identification of the quantitative effect and vulnerable populations are still unknown. The purposes of this study were to quantify the impact of daily mean temperature on the hospitalization of acute appendicitis and clarify vulnerable groups, further guide targeted prevention of acute appendicitis in Tongling. Daily data of cases and meteorological factors were collected in Tongling, China, during 2015–2019. Time stratified case-crossover design and conditional logistic regression model were used to evaluate the odds ratio (OR) of ambient temperature on hospitalizations for acute appendicitis. Stratified analyses were performed by sex, age, and marital status. The odds ratio (OR) of hospitalizations for acute appendicitis increased by 1.6% for per 1 ℃ rise in mean temperature at lag3[OR = 1.016, 95% confidence interval (CI): 1.004–1.028]. In addition, our results suggest it is in the women that increased ambient temperature is more likely to contribute to acute appendicitis hospitalizations; we also found that the married are more susceptible to acute appendicitis hospitalizations due to increased ambient temperature than the unmarried; people in the 21–40 years old are more sensitive to ambient temperature than other age groups. The significant results of the differences between the subgroups indicate that the differences between the groups are all statistically significant. The elevated ambient temperatures increased the risk of hospitalizations for acute appendicitis. The females, married people, and patients aged 21–40 years old were more susceptible to ambient temperature. These findings suggest that more attention should be paid to the impact of high ambient temperature on acute appendicitis in the future. [ABSTRACT FROM AUTHOR]

Speeding up the transmission of information carried by waves is of fundamental interest for wave physics, with pivotal significance for underwater communications. To overcome the current limitations in information transfer capacity, here we propose and experimentally validate a mechanism using multipath sound twisting to realize real-time high-capacity communication free of signal-processing or sensor-scanning. The undesired channel crosstalk, conventionally reduced via time-consuming postprocessing, is virtually suppressed by using a metamaterial layer as purely-passive demultiplexer with high spatial selectivity. Furthermore, the compactness of system ensures high information density crucial for acoustics-based applications. A distinct example of complicated image transmission is experimentally demonstrated, showing as many independent channels as the path number multiplied by vortex mode number and an extremely-low bit error rate nearly 1/10 of the forward error correction limit. Our strategy opens an avenue to metamaterial-based high-capacity communication paradigm compatible with the conventional multiplexing mechanisms, with far-reaching impact on acoustics and other domains. Here, the authors demonstrate multipath twisting of acoustic waves with a thin metamaterial layer enabling high-speed transfer of information with no time-consuming post-processing or sensor scanning, showing important application potential in underwater communication. [ABSTRACT FROM AUTHOR]

Lakes provide water-related ecosystem services that support human life and production. Nevertheless, climate changes and anthropogenic interventions remarkably altered lake and basin hydrology in recent decades, which pose a significant threat to lacustrine ecosystems. Therefore, assessments of lacustrine ecosystems require the spatial and temporal characteristics of key physical and human-dimensional attributes for lakes and lake basins. To facilitate stakeholders obtaining comprehensive data of lake basins in China, we compiled the comprehensive data set for China's lake basins (CODCLAB) mostly from publicly available data sources based on spatial analysis and mathematical statistics methods in this study. The CODCLAB is available in three data formats, including raster layers (Level 1) in "tiff" format, vector shapefiles (Level 2), and attribute tables (Level 3). It covers 767 lakes (>10 km2) in China and their basin extent associating with 34 variables organized into five categories: Hydrology, Topography, Climate, Anthropogenic, and Soils. This unique database will provide basic data for research on the physical processes and socioeconomic activities related to these lakes and their basins in China and expect to feed a broad user community for their application in different areas. Measurement(s) Hydrology, Topography, Climate, Anthropogenic, and Soils for China's lake basins Technology Type(s) spatial analysis and mathematical statistics Factor Type(s) CODCLAB_Level1 • CODCLAB_Level2 • CODCLAB_Level3 Sample Characteristic - Location China's lake basins [ABSTRACT FROM AUTHOR]

Assessing the stability characteristics of high rock slope under rainfall via theoretical research, numerical simulation, and field monitoring is of great implications for safety construction in open-pit mine engineering. Thus, based on the Hoke-Brown criterion, instantaneous internal friction angle and cohesion of high-slope rock mass under high stress conditions were deduced, and a nonlinear strength reduction method for high rock slope was established. The safety factors of the open-pit mine were calculated by COMSOL Multiphysics, which considering the high rock southwest slope and detected rainfall in Dagushan Open-pit Mine, China. The results showed that high rock slope stability could be more accurately analyzed by the proposed method due to its full consideration of slope stress state effect compared with the equivalent Mohr- Coulomb method. When the slope is low, the difference between the calculation results of the equivalent Mohr- Coulomb method and the proposed method is small, but with the increase of the slope height, the difference between the two calculation results gradually increases. When the transient saturated is formed in the slope surface layer and gradually increases, the reduction rate of the factor of safety (FOS) gradually increases. When the total rainfall is the same, the effect of short-term heavy rainfall on slope stability is less than that of long-term ordinary rainfall. The results obtained form this work provided important insights into the stability of high rock slope and rainfall infiltration in open-pit mine, and the safety factor is crucial for guiding the mining process design. [ABSTRACT FROM AUTHOR]

The research on surface texture is developing from single macro-texture to composite micro-nano texture. The current research on the anti-friction mechanism and theoretical models of textures is relatively weak. Studying the characteristics of different types of surface textures and determining the applicable working conditions of each texture is the focus of current research. In this paper, a mathematical model of hydrodynamic lubrication is established based on Navier–Stokes equations. The FLUENT software is used to simulate and analyze the four texture models, explore the dynamic pressure lubrication characteristics of different texture types, and provide data support for texture optimization. The key variable values required by the mathematical model are obtained through the simulation data. The friction coefficient of the texture under different working conditions was measured through friction and wear experiments, and the mathematical model was verified by the experimental results. The research results show that circular texture is suitable for low to medium speed and high load conditions, chevron texture is suitable for medium to high speed and medium to high load conditions, groove texture is suitable for high speed and low load conditions, and composite texture is suitable for high speed and medium to high load conditions. Comparing the experimental results with the results obtained by the mathematical model, it is found that the two are basically the same in the ranking of the anti-friction performance of different textures, and there is an error of 10%−40% in the friction coefficient value. In this study, a mathematical model of hydrodynamic lubrication was proposed, and the solution method of the optimal surface texture model was determined. [ABSTRACT FROM AUTHOR]

Online action detection (OAD) is a practical yet challenging task, which has attracted increasing attention in recent years. A typical OAD system mainly consists of three modules: a frame-level feature extractor which is usually based on pre-trained deep Convolutional Neural Networks (CNNs), a temporal modeling module, and an action classifier. Among them, the temporal modeling module is crucial which aggregates discriminative information from historical and current features. Though many temporal modeling methods have been developed for OAD and other topics, their effects are lack of investigation on OAD fairly. This paper aims to provide an empirical study on temporal modeling for OAD including four meta types of temporal modeling methods, i.e. temporal pooling, temporal convolution, recurrent neural networks, and temporal attention, and uncover some good practices to produce a state-of-the-art OAD system. Many of them are explored in OAD for the first time, and extensively evaluated with various hyper parameters. Furthermore, based on our empirical study, we present several hybrid temporal modeling methods. Our best networks, i.e. , the hybridization of DCC, LSTM and M-NL, and the hybridization of DCC and M-NL, which outperform previously published results with sizable margins on THUMOS-14 dataset (48.6% vs. 47.2%) and TVSeries dataset (84.3% vs. 83.7%). [ABSTRACT FROM AUTHOR]

This paper proposes an evolutionary fuzzy neural network (EFNN) for tool wear prediction. Material chips are affected by the cutting conditions during the cutting process. Different tool wear statuses cause material chips to have different colors; thus, the color of a material chip can be a crucial factor in tool wear prediction. In this study, the cutting time and International Commission on Illumination (CIE) xy value were used as the input of the proposed EFNN, and the output was the predicted degree of tool wear. The experimental results indicate that the proposed EFNN with the dynamic group cooperative particle swarm optimization (PSO) algorithm resulted in a smaller mean absolute percentage error (2.83%) than did the backpropagation neural network (9.72%), PSO (7.42%), quantum-based PSO (8.59%), and cooperative PSO (4.09%) algorithms. [ABSTRACT FROM AUTHOR]

Known as one efficient upconversion luminescent material, Rare-earth ions doped natrium yttrium fluoride NaYF4:Yb/Re has broad application prospects. However, due to the limitation of the existing preparation methods, it is difficult to realize industrial production. In this paper, the upconversion luminescence microparticles, rare earth ions doped Natrium Yttrium Fluoride NaYF4:Yb/Er, were synthesized productively by impinging stream method. Synthesis conditions were optimized as EDTA: Ln to 0.5 and NaF: Ln to 6 (Ln represents the sum of moles of Y, Yb, and Er), reacting temperature and time to 50 °C and 3 h to obtain a high yield of 99.92% and particle with good monodispersity. To get strong upconversion luminescence, the effect of the calcination temperature and the amount of EDTA were investigated. The bright upconversion emissions by excited with laser radiation at 975 nm were found at 510–690 nm. The higher the calcination temperature, the stronger the luminescence and the strongest luminescence occurs when calcined at 600 °C. And the adding of EDTA will decrease the luminescence intensity. However, the sintering of particles at high temperatures and aggregation of particles without EDTA are unfavorable for the application of the products. Based on the above considerations, the optimal calcination temperature was determined at 450 °C, and the ratio of EDTA: Ln is preferred at 0.5. The impinging stream method to prepare upconversion material has the advantages of being simple in the process and equipment, high in output, low in investment, and convenient to be applied and popularized. Highlights: Mass Production of up-conversion luminescence materials is illustrated. NaYF4:Yb/Er microparticles were synthesized by the novel impinging stream method. Products with high yield of 99.92% and good mono-dispersity could be obtained at optimal condition. The hexagonal crystals were obtained by calcinations at 450 °C, and it can emit bright up-conversion emissions of at 510–690 nm. [ABSTRACT FROM AUTHOR]

Current development of temperature-related health early warning systems mainly arises from knowledge of temperature-related mortality or hospital-based morbidity. However, due to the delay in data reporting and limits in hospital capacity, these indicators cannot be used in health risk assessments timely. In this study, we examine temperature impacts on emergency ambulance and discuss the benefits of using this near real-time indicator for risk assessment and early warning. We collected ambulance dispatch data recording individual characteristics and preliminary diagnoses between 2015 and 2016 in Shenzhen, China. Distributed lag nonlinear model was used to examine the effects of high and low temperatures on ambulance dispatches during warm and cold seasons. Lag effects were also assessed to evaluate the sensitivity of ambulance dispatches in reflecting immediate health reactions. Stratified analyses by gender, age, and a wide range of diagnoses were performed to identify vulnerable subgroups. Disease-specific numbers of ambulance dispatches attributable to non-optimal temperature were calculated to determine the related medical burdens. Effects of temperature on ambulance dispatches appeared to be acute on the current day. Males, people aged 18–44 years, were more susceptible to non-optimal temperatures. Highest RR during heat exposure by far was for urinary disease, alcohol intoxication, and traumatic injury, while alcohol intoxication and cardiovascular disease were especially sensitive to cold exposure, causing the main part of health burden. The development of local health surveillance systems by utilizing ambulance dispatch data are important for temperature impact assessments and medical resource reallocation. [ABSTRACT FROM AUTHOR]

Introduction: Skin and soft structure infections (SSTIs) caused by methicillin-resistant Staphylococcus aureus (MRSA) pose serious health risks and cause significant cost burdens, and a conclusive recommendation about antibiotics has not yet been generated. Therefore, we performed this updated network meta-analysis to determine the preferred drug for the treatment of MRSA-caused SSTIs. Methods: We searched PubMed, Embase, and Cochrane Library to identify any potentially eligible randomized controlled trials (RCTs) investigating the comparative efficacy and safety of any two of vancomycin, linezolid, tedizolid, and daptomycin in MRSA-caused SSTIs. All statistical analyses were conducted with RevMan, ADDIS, and STATA software. Results: Twenty eligible RCTs involving 7804 patients were included for the final analysis. Direct meta-analysis suggested that linezolid was superior to vancomycin in improving clinical (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.07–1.99; P = 0.02) and microbiological (OR, 1.89; 95% CI, 1.24–2.86; P = 0.003) success, which were all confirmed by network meta-analyses. No statistical differences were identified regarding other comparisons. Meanwhile, there were no significant differences between any two antibiotics related to safety. Moreover, ranking probabilities indicated that linezolid had the highest probability of being ranked best in terms of clinical and microbiological success. Conclusion: Based on the limited evidence, linezolid may be a preferred antibiotic for the treatment of MRSA-caused SSTIs because it showed superiority in clinical and microbiological success without difference regarding safety. [ABSTRACT FROM AUTHOR]

Dengue transmission is climate-sensitive and permissive conditions regularly cause large outbreaks in Asia-Pacific area. As climate change progresses, extreme weather events such as heatwaves and unusually high rainfall are predicted more intense and frequent, but their impacts on dengue outbreaks remain unclear so far. This paper aimed to investigate the relationship between extreme weather events (i.e., heatwaves, extremely high rainfall and extremely high humidity) and dengue outbreaks in China. We obtained daily number of locally acquired dengue cases and weather factors for Guangzhou, China, for the period 2006–2015. The definition of dengue outbreaks was based on daily number of locally acquired cases above the threshold (i.e., mean + 2SD of daily distribution of dengue cases during peaking period). Heatwave was defined as ≥2 days with temperature ≥ 95th percentile, and extreme rainfall and humidity defined as daily values ≥95th percentile during 2006–2015. A generalized additive model was used to examine the associations between extreme weather events and dengue outbreaks. Results showed that all three extreme weather events were associated with increased risk of dengue outbreaks, with a risk increase of 115–251% around 6 weeks after heatwaves, 173–258% around 6–13 weeks after extremely high rainfall, and 572–587% around 6–13 weeks after extremely high humidity. Each extreme weather event also had good capacity in predicting dengue outbreaks, with the model's sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve all exceeding 86%. This study found that heatwaves, extremely high rainfall, and extremely high humidity could act as potential drivers of dengue outbreaks. [ABSTRACT FROM AUTHOR]

The use of high-temperature fuel cells as a power technology can improve the efficiency of electricity generation and achieve near-zero emissions of carbon dioxide. This work explores the performance of a 10 kW high-temperature molten carbonate fuel cell. The key materials of a single cell were characterized and analyzed using X-ray diffraction and scanning electron microscopy. The results show that the pore size of the key electrode material is 6.5 µm and the matrix material is α-LiAlO2. Experimentally, the open circuit voltage of the single cell was found to be 1.23 V. The current density was greater than 100 mA/cm2 at an operating voltage of 0.7 V. The 10 kW fuel cell stack comprised 80 single fuel cells with a total area of 2000 cm2 and achieved an open circuit voltage of greater than 85 V. The fuel cell stack power and current density could reach 11.7 kW and 104.5 mA/cm2 at an operating voltage of 56 V. The influence and long-term stable operation of the stack were also analyzed and discussed. The successful operation of a 10 kW high-temperature fuel cell promotes the large-scale use of fuel cells and provides a research basis for future investigations of fuel cell capacity enhancement and distributed generation in China. [ABSTRACT FROM AUTHOR]

Heat shock protein 70 (Hsp70) plays an important role in plant development. It is closely related to the physiological process of cell development and the response to abiotic and biological stress. However, the classification and evolution of Hsp70 genes in bread wheat, wild emmer wheat and Aegilops tauschii are still unclear. Therefore, this study conducted a comprehensive bioinformatics analysis of Hsp70 gene in three species. Among these three species, 113, 79 and 36 Hsp70 genes were identified. They are divided into six subfamilies. Group vi-1 is different from Arabidopsis thaliana. It may be the result of early evolutionary segregation. The number of exons in different subfamilies (from 1 to 13) was different, but the distribution patterns of exons / introns in the same subfamily were similar. The results of Hsp70 promoter region analysis showed that the cis-regulatory elements of A. tauschii and wild emmer wheat were different from those of wheat. In addition, CpG island proportion of wild emmer Hsp70 was higher than that of wheat, which may be the molecular basis of heat resistance of wild wheat relative to cultivated wheat. Further comprehensive analysis of chromosome location and repeat events of Hsp70 gene showed that whole-genome duplication and tandem duplication events contributed to the evolution and expansion of Hsp70 gene in wheat. The results of non-synonymous substitution and synonymous substitution analysis showed that Hsp70 genes of three species had undergone purification selection. The expression profile analysis showed that Hsp70 gene was highly expressed in the roots during the vegetative growth period. In addition, TaHsp70 gene was highly expressed under various stress. The identification, classification and evolution of Hsp70 in wheat and its relatives provided a basis for further research on its evolution and its molecular mechanism in response to stress. [ABSTRACT FROM AUTHOR]

The surface reforming method of metal superhydrophobic surface usually utilizes organic matter, which has the problems of serious environmental pollution, high thermal resistance, low processing efficiency, as well as easy to fall off. According to the application requirements of steam condensation heat transfer on copper surface, a laser micro-/nano-texturing technology assisted by green post-processing method is proposed in this study. In this technology, a nano-second laser was used to texture the surface of pure copper, which will undergo heat treatment to prepare a superhydrophobic surface with micro-/nano-level structures. Scanning electron microscopy and X-ray photoelectron spectroscopy were used to analyze the microstructure changes. A contact angle tester was used to measure the wettability of the surfaces and surface Gibbs energy. Furthermore, steam condensation system was set up to assess surface heat transfer performance. The results show that the laser micro-/nano-textured copper surface has a superhydrophilic contact angle of 4°; after heat treatment, it reaches 161° and became a superhydrophobic surface. As the heat treatment promotes fully oxidation of the textured copper surface, the surface energy is greatly reduced. Due to the formation of nanoscale CuO "clusters" transferred from laser-textured Cu2O by heat treatment, the superhydrophobic surface blocks the growth of condensate droplets and increases the condensation heat transfer coefficient by 4 times to 730.4 W m−2 K−1. It provides a green non-chemical treatment method for heat transfer applications of copper alloy components in the fields of energy, chemical engineering, refrigeration, microelectronics, and batteries. [ABSTRACT FROM AUTHOR]

The rapid development of e-commerce has resulted in optimization of the industrial structure of Chinese enterprises and has improved the Chinese economy. E-commerce transaction volume is an evaluation index used to determine the development level of e-commerce. This study proposed a model for forecasting e-commerce transaction volume. First, a hybrid moth–flame optimization algorithm (HMFO) was proposed. The convergence ability of the HMFO algorithm was analyzed on the basis of test functions. Second, using data provided by the China Internet Network Information Center, factors influencing e-commerce transaction volume were analyzed. The input variables of the e-commerce transaction volume prediction model were selected by analyzing correlation coefficients. Finally, a hybrid extreme learning machine and hybrid-strategy-based HMFO (ELM-HMFO) method was proposed to predict the volume of e-commerce transactions. The prediction results revealed that the root mean square error of the proposed ELM-HMFO model was smaller than 0.5, and the determination coefficient was 0.99, which indicated that the forecast e-commerce transaction volume was satisfactory. The proposed ELM-HMFO model can promote the industrial upgrading and development of e-commerce in China. [ABSTRACT FROM AUTHOR]

Direct formation of ultra-small nanoparticles on carbon supports by rapid high temperature synthesis method offers new opportunities for scalable nanomanufacturing and the synthesis of stable multi-elemental nanoparticles. However, the underlying mechanisms affecting the dispersion and stability of nanoparticles on the supports during high temperature processing remain enigmatic. In this work, we report the observation of metallic nanoparticles formation and stabilization on carbon supports through in situ Joule heating method. We find that the formation of metallic nanoparticles is associated with the simultaneous phase transition of amorphous carbon to a highly defective turbostratic graphite (T-graphite). Molecular dynamic (MD) simulations suggest that the defective T-graphite provide numerous nucleation sites for the nanoparticles to form. Furthermore, the nanoparticles partially intercalate and take root on edge planes, leading to high binding energy on support. This interaction between nanoparticles and T-graphite substrate strengthens the anchoring and provides excellent thermal stability to the nanoparticles. These findings provide mechanistic understanding of rapid high temperature synthesis of metal nanoparticles on carbon supports and the origin of their stability. Metal nanoparticle-decorated carbon supports are vital for many applications, ranging from energy storage and catalysis to filtration and environmental remedies. Here, using real-time electron microscopy of a single carbon nanofiber during Joule heating, the authors report atomistic mechanisms responsible for nucleation and stabilization of nanoparticles on amorphous carbon supports. [ABSTRACT FROM AUTHOR]

Broadband acoustic absorbers with thin thickness are highly desired in practical situations such as architectural acoustics, yet it is still challenging to achieve high absorption by using structure with limited thickness. Here we report the theoretical optimal design, numerical simulation and experimental demonstration of a planar acoustic absorber capable of producing broadband sound absorption with deep-subwavelength thickness. The mechanism is that, we use a hybrid design of individual unit cell comprising multiple resonators with a coiled configuration for expanding the working bandwidth and downscaling the resulting device, and, on the other hand, the geometries of the constituent resonance elements are optimally designed by using genetic algorithm. Based on an analytical formula we derive for an efficient prediction of the absorption efficiency, the optimization process is accelerated and gives rise to an optimally maximized amount of absorbed energy with limited device thickness. As a result, the proposed absorber features planar profile, broad bandwidth, wide absorbing angle (the absorber works well when the incident angle of sound wave reaches 60°) and thin thickness (< 1/25 wavelength). In addition, the proposed scheme does not rely on extra sound-absorptive materials or the type of constituent solid material, which significantly simplifies the sample fabrication and improves the application potential of resulting device. The measured data agree well with the theoretical predictions, showing high sound absorption in the prescribed frequency range. We envision our design to further improve the performance of acoustic absorbers and find applications in practical situations in need of elimination of broadband acoustic waves within limited spaces. [ABSTRACT FROM AUTHOR]

The surface and grain boundary scattering impact on the electrical and thermal conduction in the thin metallic films coated on organic substrates has not been studied thoroughly. In this work, we study heat and electron transport in the 6.4 nm thin Au films supported by polyimide (PI) substrate using the transient electro-thermal technique. Thermal and electrical conductivities of 6.4 nm thin Au film are much smaller than bulk value. The thermal and electrical conductivities of 6.4 nm Au film deposited on the PI fiber are reduced by 59.3% and 76.8% in the comparison with the value of bulk Au. For PI film, the reduction of thermal and electrical conductivities is 47.9% and 46.3%. Lorenz numbers of 6.4 nm Au film supported by PI fiber and PI film are 4.51 × 10−8 WΩK−2 and 2.12 × 10−8 WΩK−2, respectively. The thermal conductivities of PI fiber and PI film are 0.87 Wm−1K−1 and 0.44 Wm−1K−1. The results reveal that PI is a suitable substrate material in the flexible electronic devices field. [ABSTRACT FROM AUTHOR]

In general, it needs to take about nearly 10 grid points inside a wall boundary layer for low accuracy order methods to get satisfactory wall-normal gradient related results, such as friction coefficient and wall heat flux. If there exist extreme points inside the boundary layer, this situation becomes even worse. In this work, with the help of the analytic solution of the one-dimensional steady compressible Navier-Stokes equations under some restrictions, we show that the flow variables actually vary in the form of an exponential function instead of a polynomial one inside the boundary layer. Then, we propose an exponential space for approximating the solutions inside the boundary layer and numerically implementing it in the frame of direct discontinuous Galerkin (DDG) method. We show that the DDG methods based on the exponential boundary-layer space give much better numerical results for both conservative variables and wall-normal gradients than those with the standard polynomial space. Generally only 1–2 grid points inside the boundary layer are demanded to resolve the wall boundary layer to obtain satisfactory wall-normal gradients under the exponential space. Preliminary extension to two-dimensional laminar boundary-layer flow shows a similar performance of the proposed exponential boundary-layer space, exhibiting its potential applications in high dimensions. [ABSTRACT FROM AUTHOR]

Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to deploy and score. Therefore, we developed a digital ambulatory verbal memory test with automated scoring, and repeated self-administration via smart devices. One hundred and four adults participated, comprising 25 patients with serious mental illness and 79 healthy volunteers. The study design was successful with high quality speech recordings produced to 92% of prompts (Patients: 86%, Healthy: 96%). The story recalls were both transcribed and scored by humans, and scores generated using natural language processing on transcriptions were comparable to human ratings (R = 0.83, within the range of human-to-human correlations of R = 0.73–0.89). A fully automated approach that scored transcripts generated by automatic speech recognition produced comparable and accurate scores (R = 0.82), with very high correlation to scores derived from human transcripts (R = 0.99). This study demonstrates the viability of leveraging speech technologies to facilitate the frequent assessment of verbal memory for clinical monitoring purposes in psychiatry. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) acoustic vortex allows new physics and applications different from three-dimensional counterparts, yet existing mechanisms usually have to rely on active array composed of transducers which may result in complexity, high cost and, in particular, undesired spatial aliasing effect. We propose to generate 2D acoustic vortex inside an enclosed metasurface illuminated by axisymmetric wave carrying no orbital angular momentum. We derive the criterion on unit size for eliminating spatial aliasing effect which is challenging for conventional active approaches and design a membrane-based metasurface to implement our mechanism. The performance of our strategy is demonstrated via precise production of different orders of non-aliased vortices regardless of center-to-center alignment, with undistorted Bessel-like pattern extending to the whole inner region. We anticipate our design with simplicity, compactness, precision and flexibility to open up possibility to design novel vortex devices and find important applications in diverse scenarios such as on-chip particle manipulations. [ABSTRACT FROM AUTHOR]

Natural products are the important source for the discovery of more potent anti-HIV agents. In this study, six daphnane diterpenoids including three unreported structures were isolated from Trigonostemon lii, which showed significant activities against HIV-1 strains replication in the nanomolar/picomolar range. Meanwhile, these diterpenoids significantly inhibited the fusion of H9/HIV-1 IIIB cells with uninfected C8166 cells, with the EC50s from 1.06 to 8.73 ng/mL, and did not show any inhibition activities against HIV-1 reverse transcriptase. Moreover, all of the diterpenoids shows significant inhibitions against T20-resistan HIV-1 strains, PNL4-3gp41(36G)V38E, N42S and pNL4-3gp41(36G)V38A, N42T. The results revealed that the six diterpenoids could be a new type of potential lead candidate as an HIV entry inhibitor, particularly for those infected by T20-resistant variants. [ABSTRACT FROM AUTHOR]

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Introduction: The effect of dipeptidyl peptidase-4 (DDP-4) inhibitors versus α-glucosidase inhibitors (AGIs) on the treatment of type 2 diabetes mellitus (T2DM) in a real-world setting is unknown. The aim of this real-world study was to compare the glucose-lowering effect and tolerability of vildagliptin as add-on to metformin monotherapy (VM) and AGI as add-on to metformin monotherapy (AM) in Chinese patients with T2DM. Methods: This was a subgroup analysis of the China Prospective Diabetes Study, a post-marketing, prospective, observational, real-world study conducted at 52 centers in China. T2DM patients with inadequate glycemic control on metformin monotherapy who received VM or AM were included. The composite primary endpoint was glycemic control (hemoglobin A1c [HbA1c] < 7%) after 12 months in the absence of tolerability events (hypoglycemia, weight gain ≥ 3%, or gastrointestinal events leading to treatment discontinuation). Propensity score matching (PSM) was used to balance the two groups. Results: The success rates of the composite endpoint were higher in the VM group (n = 604/159 before/after PSM) than in the AM group (n = 159/157 before/after PSM), but the difference was not statistically significant (before PSM: 53.0 vs. 46.5%, P = 0.148; after PSM: 56.7 vs. 45.9%, P = 0.055). The glycemic control rate and HbA1c reduction were similar between groups at 3, 6, and 12 months. Compared with the AM group, the VM group had lower risks of any tolerability event (relative risk [RR] 0.53, 95% confidence interval [CI] 0.33–0.83, P = 0.006), of any adverse event (AE) (RR 0.64, 95% CI 0.41–1.00, P = 0.049), and of any serious AE (RR 0.45, 95% CI 0.25–0.81, P = 0.007). Conclusion: The results of this real-world study suggest that vildagliptin as add-on to metformin monotherapy had a similar glucose-lowering effect to AGI as add-on to metformin monotherapy, but with better safety. [ABSTRACT FROM AUTHOR]

Probiotics are intended to provide health benefits when consumed, generally by improving or restoring the gut flora. The health problems of forest musk deer (FMD, Moschus berezovskii), a threatened species currently under conservation, restrict the development of captive musk deer. This study was conducted with the aim of analyzing the effects of forest musk deer compound probiotics (FMDPs) on weight, immunity performance and fecal microbiota in FMD by measuring average daily weight gain (ADG) and immune-related factors and by using high-throughput 16S rRNA sequencing to investigate differences in the fecal microbiota among the control group (4 samples), treatment group A (4 samples) and treatment group B (4 samples). The results showed that the ADG of treatment groups A and B was significantly higher than that of the control group (p = 0.032, p = 0.018). The increase in IgA and IgG levels in treatment group B was significantly higher than that in the control group (p = 0.02, p = 0.011). At the phylum and genus levels, the difference in bacterial community structure was significant between treatment group B and the control group. Both the alpha diversity and beta diversity results showed significant differences in the microbiota of FMD before and after FMDP feeding. In summary, the results indicated that FMDPs could promote the growth of growing FMD, improve immunity and balance the role of intestinal microbes. [ABSTRACT FROM AUTHOR]

In the precision manufacturing process, accuracy and precision are crucial when designing a workpiece inspection system. An efficient system minimizes inefficiencies caused by workpieces failing to meet customer needs and delays caused by slow workpiece inspection. In this study, a workpiece inspection system for measuring path planning is proposed that uses the given coordinate of inspection points discerned from 3D images. Then, an adaptive-group-based differential evolution (AGDE) algorithm is used to optimize the measuring path. The AGDE algorithm incorporates the grouping concept into conventional differential evolution, and this improves local search ability through referencing the direction of the best solution in each group. By using the proposed method, the shortest non-colliding measuring path is obtained. Moreover, the proposed workpiece inspection system shortens the workpiece inspection time and achieves faster performance than manual measuring path planning under multiple workpiece inspection points. [ABSTRACT FROM AUTHOR]

Laser cleaning has been widely used in manufacturing industries due to its lower pollution and higher cleaning precision and efficiency compared with traditional ways. However, laser cleaning would inevitably induce processing roughness on the workpiece surface and only a few researches have been conducted to this field. In this work, the influence of process parameters on surface roughness was explored in detail. The results showed that process parameters changed surface roughness by changing energy density and overlap ratio. And surface roughness was showed linear positive correlation with energy density. At same energy density, surface roughness will first increase and then decrease with increasing overlap ratios. The maximum roughness was in the range of 50 to 66.7%. It could be explained that after laser irradiation, the sample surface absorbed pulse energy and formed craters. The rim and craters made the sample surface coarse. Due to the depth and diameter of craters were dependent on energy density, the roughness increased with increasing energy densities. The adjacent craters will also change the height of rim and depth of crater with different overlap ratios. It led to different surface roughness. [ABSTRACT FROM AUTHOR]

To study the formation mechanism of a conductive layer in a laser-processed AlN ceramic plate, nanosecond laser treatment on an AlN ceramic was performed to generate an Al layer, which created conductivity on the surface. Changes in the resistance for different energy densities, pulse durations, line spacings and scanning speeds were studied by means of XPS and scanning electron microscopy. The results show that the resistance is inversely proportional to the duration of the pulse in the case of low energy density or low scanning speed. At a higher energy density or a higher scanning speed, the resistance is proportional to the duration of the pulse. The variation in the resistance as a function of line spacing is related to the energy density. As the energy density increases, the resistance value decreases slowly at first and then maintains an upward trend. The resistance is proportional to the scanning speed. [ABSTRACT FROM AUTHOR]

Manufacturers of printed circuit boards (PCBs) typically use automated optical inspection (AOI) machines to test their PCBs. However, AOI machines employ conventional image-processing methods. If the integrated circuit (IC) components are not identical to the golden samples, then the AOI machine registers those IC components as flaws. Conventional image-processing methods cause misjudgments and increase the cost of manual reviews. Character-verification and image-classification systems are proposed in this paper for detecting misplaced, missing, and reversed-polarity parts. The regions of IC components can be identified on PCBs by using the contour border-detection method. Through the proposed convolutional neural network (CNN) structure and refinement mechanism, the characters can be successfully recognized. The image-classification system was applied only to images with blurry characters. Different CNN learning structures were used in both systems, and the refinement mechanism was used in both systems to improve the results. The proposed character-verification and image-classification methods achieved 98.84% and 99.48% passing rates, and the amount of required training time was less than that of other methods, demonstrating the proposed methods' greater effectiveness. [ABSTRACT FROM AUTHOR]

Ambient temperature is an important determinant of mortality and morbidity, making it necessary to assess temperature-related burden of disease (BD) for the planning of public health policies and adaptive responses. To systematically review existing epidemiological evidence on temperature-related BD, we searched three databases (PubMed, Web of Science, and Scopus) on 1 September 2018. We identified 97 studies from 56 counties for this review, of which 75 reported the fraction or number of health outcomes (include deaths and diseases) attributable to temperature, and 22 reported disability-adjusted life years (include years of life lost and years lost due to disability) related to temperature. Non-optimum temperatures (i.e., heat and cold) were responsible for > 2.5% of mortality in all included high-income countries/regions, and > 3.0% of mortality in all included middle-income countries. Cold was mostly reported to be the primary source of mortality burden from non-optimum temperatures, but the relative role of three different temperature exposures (i.e., heat, cold, and temperature variability) in affecting morbidity and mortality remains unclear so far. Under the warming climate scenario, almost all projections assuming no population adaptation suggested future increase in heat-related but decrease in cold-related BD. However, some studies emphasized the great uncertainty in future pattern of temperature-related BD, largely depending on the scenarios of climate, population adaptation, and demography. We also identified important discrepancies and limitations in current research methodologies employed to measure temperature exposures and model temperature-health relationship, and calculate the past and project future temperature-related BD. Overall, exposure to non-optimum ambient temperatures has become and will continue to be a considerable contributor to the global and national BD, but future research is still needed to develop a stronger methodological framework for assessing and comparing temperature-related BD across different settings. [ABSTRACT FROM AUTHOR]