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Abstract We assembled the first gridded burned area (BA) database of national wildfire data (ONFIRE), a comprehensive and integrated resource for researchers, non-government organisations, and government agencies analysing wildfires in various regions of the Earth. We extracted and harmonised records from different regions and sources using open and reproducible methods, providing data in a common framework for the whole period available (starting from 1950 in Australia, 1959 in Canada, 1985 in Chile, 1980 in Europe, and 1984 in the United States) up to 2021 on a common 1° × 1° grid. The data originate from national agencies (often, ground mapping), thus representing the best local expert knowledge. Key opportunities and limits in using this dataset are discussed as well as possible future expansions of this open-source approach that should be explored. This dataset complements existing gridded BA data based on remote sensing and offers a valuable opportunity to better understand and assess fire regime changes, and their drivers, in these regions. The ONFIRE database can be freely accessed at https://zenodo.org/record/8289245 .

Human–machine interaction (HMI) establishes an interconnected bridge between humans and robots and plays a significant role in industry and medical fields. However, the conventional interface is bulky and rigid with a single function. It lacks feedback information to be provided to the user, limiting its application scenarios and the ability to complete complex tasks in a dynamic environment. Herein, a flexible bidirectional (FBD) interface with integrated multimodal sensing and haptic feedback and the development of an FBD‐based closed‐loop HMI platform are presented. The proposed FBD interface offers programmable haptic feedback through a coin vibration motor array to endow the user with better performance in missions. The multimodal sensing array can perceive signals of joint movement and the pressure imposed on the skin. In addition, the FBD interface exhibits significant advantages of flexibility and a compact structure. The experimental tests verify that the multimodal sensing module can accurately perceive various static and dynamic movements of a human. Furthermore, the actuation module can provide diverse haptic vibrations to convey different information to the user. Moreover, successful applications in the scenarios of bilateral robotic teleoperation and assistance of disabled people indicate great potential of the FBD interface for broad applications.

Mg is a typical biodegradable metal widely used for biomedical applications due to its considerable mechanical properties and bioactivity. Biodegradable polymers have attracted great interest owing to their favorable processability and inclusiveness. However, it is challenging for the degradation rates of Mg or polymers to precisely match tissue repair processes, and the significant changes in local pH during degradation hinder tissue repair. The concept of combining Mg with polymers is proposed to overcome the shortcomings of materials, aiming to meet repair needs from various aspects such as mechanics and biology. Therefore, it is essential to systematically understand the behavior of biodegradable Mg/polymer composite (BMPC) from the design, manufacturing, mechanical properties, degradation, and biological effects. In this review, we elaborate on the design concepts and manufacturing strategies of high-strength BMPC, the “structure-function” relationship between the microstructures and mechanical properties of composites, the variation in the degradation rate due to endogenous and exogenous factors, and the establishment of advanced degradation research platform. Additionally, the interplay among composite components during degradation and the biological function of composites under non-responsive/stimuli-responsive platforms are also discussed. Finally, we hope that this review will benefit future clinical applications of “structure-function” integrated biomaterials.

Objective: To determine the use and tendency of drugs for postpartum depression (PPD) in nine cities across China in 2016–2020 in order to provide a reference for drug use in the clinic. Methods: The prescription data of drugs for PPD outpatients in nine cities (Beijing, Chengdu, Guangzhou, Harbin, Hangzhou, Shanghai, Shenyang, Tianjin and Zhengzhou) across China in 2016–2020 were extracted from the Hospital Prescription Analysis Cooperation Project database of the Hospital Pharmacy Professional Committee of Chinese Pharmaceutical Association. A cross-sectional analysis was then conducted of patient age, total prescription quantity, average prescription amount, defined daily doses (DDDs) of drugs, defined daily cost (DDC) of drugs and so on. Results: In 2016–2020, more than half of PPD patients in these nine cities were distributed in first-tier cities (Beijing, Shanghai and Guangzhou), and were mainly aged 30–39 years. During the five-year period, the prescription quantity, total prescription amount and average prescription amount increased by 20.95%, 35.41% and 11.02%, respectively. In terms of prescription frequency and prescription amount, selective serotonin reuptake inhibitors (SSRIs) ranked first, followed by serotonin-norepinephrine reuptake inhibitors (SNRIs). With regard to DDDs, escitalopram, sertraline, paroxetine and venlafaxine ranked high, and sertraline was top year by year. The DDC of vortioxetine and milnacipran was greatest, while that of escitalopram, olanzapine and quetiapine declined sharply after being included in the China centralized drug-procurement program. Conclusion: The number of PPD patients and the total prescription amount in the nine cities across China increased in 2016–2020. SSRIs and SNRIs were the main drugs for PPD treatment. Due to the national centralized drug-procurement policy, there has been a great reduction in the DDC, lightening the economic burden on patients.

Background and purposeEarly diagnosis is important for treatment and prognosis of obstructive sleep apnea (OSA)in children. Polysomnography (PSG) is the gold standard for the diagnosis of OSA. However, due to various reasons, such as inconvenient implementation, less equipped in primary medical institutions, etc., it is less used in children, especially in young children. This study aims to establish a new diagnostic method with imaging data of upper airway and clinical signs and symptoms.MethodsIn this retrospective study, clinical and imaging data were collected from children ≤10 years old who underwent nasopharynx CT scan(low-dose protocol)from February 2019 to June 2020,including 25 children with OSA and 105 non-OSA. The information of the upper airway (A-line; N-line; nasal gap; upper airway volume; upper and lower diameter, left and right diameter and cross-sectional area of the narrowest part of the upper airway) were measured in transaxial, coronal, and sagittal images. The diagnosis of OSA and adenoid size were given according to the guidelines and consensus of imaging experts. The information of clinical signs, symptoms, and others were obtained from medical records. According to the weight of each index on OSA, the indexes with statistical significance were screened out, then were scored and summed up. ROC analysis was performed with the sum as the test variable and OSA as the status variable to evaluate the diagnostic efficacy on OSA.ResultsThe AUC of the summed scores (ANMAH score) of upper airway morphology and clinical index for the diagnosis of OSA was 0.984 (95% CI 0.964–1.000). When sum = 7 was used as the threshold (participants with sum>7 were considered to have OSA), the Youden’s index reached its maximum at which point the sensitivity was 88.0%, the specificity was 98.1%, and the accuracy was 96.2%.ConclusionThe morphological data of the upper airway based on CT volume scan images combined with clinical indices have high diagnostic value for OSA in children; CT volume scanning plays a great guiding role in the selection of treatment scheme of OSA. It is a convenient, accurate and informative diagnostic method with a great help to improving prognosis.Highlights– Early diagnosis of OSA in children is very important for the treatment.– However, the traditional diagnostic gold-standard PSG is difficult to implement.– This study aims to explore convenient and reliable diagnostic methods for children.– A new diagnostic model was established combining CT with signs and symptoms.– The diagnostic method in this study is highly effective, informative, and convenient.

Fuel moisture content is a highly variable property that dictates the ignition and combustion potentials of wildfire fuels. The Canadian Fire Weather Index (FWI) System—a subset of the established Canadian Forest Fire Danger Rating System—relies solely on weather observations to track fuel moisture and compute indices of fire potential. Ancillary environmental measures, such as lake levels in non-regulated lake systems, may integrate climatic and landscape factors that better reflect environmental moisture deficits and thereby complement the FWI System. Accordingly, we investigated whether inter-annual variation in lake levels has potential to serve as an indicator of regional fire activity using a quasi-binomial regression approach. This study combines annual measurements of fire activity, lake level, and other climatic variables from the Boreal Shield and Boreal Plain ecozones of Canada from 1980 to 2019 to determine whether variation in regional area burned can be explained by lake-level fluctuation, and whether this explanatory power differs by ecozone. Results indicated that lake-level fluctuation is a significant predictor of regional area burned for many lakes (28–48%). It often performs as well as or better than traditional fire-weather metrics (such as temperature and precipitation), and this relationship is stronger on the Boreal Shield compared to the Boreal Plain. Lake-level fluctuation provides information on fuel availability unaccounted for by traditional fire-weather metrics, suggesting that this variable could be added to the suite of environmental indicators of regional fire activity in Canada.

The objective of this study was to evaluate the effects of potato vine and leaf mixed silage (PVS) on rumen fermentation and the microbe in ruminants and to improve the utilization of PVS resources in ruminants through in vitro gas production and feeding trials. The experiment was divided into three groups: PVS1 (50% corn + 50% potato vine and leaf silage), PVS2 (75% potato vine and leaf + 15% rice straw + 10% cornmeal silage) and whole-plant corn silage (CS). The in vitro gas production results showed that there was a significant reduction in PVS groups in the indexes of total gas (p < 0.05) and CH4 production (p < 0.05). The digestibility of dry matter (p < 0.05), neutral detergent fiber (NDF) (p < 0.05), and acid detergent fiber (ADF) (p < 0.05) at 48 h were decreased in the PVS group. For the rumen fermentation indexes, the pH (p < 0.05), microbial crude protein (MCP) (p < 0.05), and acetate to propionate (p < 0.05) showed an increase in the PVS group, but a decrease in the total volatile fatty acid concentration (p < 0.05). In the feeding trial, different silages in diets had no significant effect on the rumen fermentation indexes (p > 0.05). In the rumen microbe composition, the PVS diet significantly reduced the abundance of Prevotella (p < 0.05) compared with the CS diet group. The PVS2 diet significantly increased the abundance of the Lachnospiraceae_XPB1014_group (p < 0.05) and Bacteroidales_bacterium_Bact_22 (p < 0.05) compared with the CS diet group. In conclusion, PVS had no negative effect on rumen fermentation characteristics and rumen microbial flora and could significantly reduce rumen gas production compared to CS, positively mitigating animal husbandry CH4 emissions and environmental protection.

In order to acquire scientific evidence for the application of thiamethoxam (TMX) in Agaricus bisporus cultivation, residue and dissipation experiments for field trials were performed with the application of TMX in compost and casing soil, respectively. An effective QuEChERS method was established to analyze TMX and its two metabolites, clothianidin (CLO) and thiamethoxam-urea (TMX-urea), in compost, casing soil, and fruiting bodies. The results indicated that the TMX dissipation half-lives (t1/2) at dosages of 10 and 50 mg kg−1 were 19.74 d (day) and 28.87 d in compost and 33.54 d and 42.59 d in casing soil, individually. TMX, CLO, and TMX-urea were observed after TMX application in compost and casing soil. For TMX applied to the casing soil, only TMX residues were detected in fruiting bodies with bioconcentration factors (BCFs) of 0.0003~0.0009. In addition, both the chronic risk quotient (RQ) and acute risk quotient (HQ) values of TMX in fruiting bodies were far less than 1, which means the dietary health risks to humans were acceptable. However, in the TMX application to the compost, these analytes were not detected in the fruiting bodies. This suggested that the application of TMX in compost was safer than in casing soil during A. bisporus cultivation.

With an upsurge of biodegradable metal implants, the research and application of Mg alloys in the gastrointestinal environment of the digestive tract have been of great interest. Digestive enzymes, mainly pepsin in the stomach and pancreatin in the small intestine, are widespread in the gastrointestinal tract, but their effect on the degradation of Mg alloys has not been well understood. In this study, we investigated the impacts of pepsin and pancreatin on the degradation of Mg-2Zn alloy wires. The results showed that the pepsin and pancreatin had completely different even the opposite effects on the degradation of Mg, although they both affected the degradation product layer. The degradation rate of Mg wire declined with the addition of pepsin in simulated gastric fluid (SGF) but rose with the addition of pancreatin in simulated intestinal fluid (SIF). The opposite trends in degradation rate also resulted in completely different degradation morphologies in wires surface, where the pitting corrosion in SGF was inhibited because of the physical barrier effect of pepsin adsorption. In contrast, the adsorption of pancreatin affected the integrity of magnesium hydrogen phosphate film, causing a relatively uneven degraded surface. These results may help us to understand the role of different digestive enzymes in the degradation of magnesium and facilitate the development and clinical application of magnesium alloy implanted devices for the digestive tract.

Extravillous trophoblast invasion disorder caused by oxidative stress is involved in the pathogenesis of preeclampsia (PE). In order to identify whether hydrogen sulfide (H2S) can prevent oxidative stress injury in extravillous trophoblasts. HTR-8/SVneo cells were detected by H2S inhibiting H2O2 induced oxidative mitochondrial damage. Reactive oxygen species (ROS) were detected, as well as malondialdehyde (MDA), catalase (CAT), and superoxide dismutase (SOD). JC-1 detected the potential of the mitochondrial membrane in this experiment. Then to detect the expression level of the apoptosis-inducing protein B-cell lymphoma-2 (Bcl-2) associated X protein (Bax), caspase 3, p53, p-p53, the apoptosis-inhibiting protein Bcl-2, PRAP, and the mitochondria fission protein Drp1, p-Drp1. CCK-8 assay, it was demonstrated that cell proliferation in the NaHS group was significantly higher than that in the Mod group, indicating that H2S may induce cell proliferation. Transwell assay elucidated that cell invasion in the NaHS group was recovered compared to the Mod group. ROS concentration no matter in cells or mitochondria was decreased by NaHS, which we could get from the comparison between the Mod group, PAG group, and NaHS group. The concentration of MDA was significantly lower in the NaHS group, and the concentration of SOD was extremely high in the NaHS group. Utilized JC-1 to detect mitochondrial membrane potential and found that cells from the NaHS group had a stable potential while cells from the Mod group and PAG group partly lost their potential, which could demonstrate that NaHS could maintain mitochondrial membrane potential. The western blot results revealed that p-Drp1 had a significant decline in the NaHS group, which means mitochondria fission was decreased in the NaHS group. The expression level of Bax and caspase 3 was significantly lower than in the Mod group and PAG group, and the expression level of Bcl-and PRAP was significantly higher in the NaHS group. That could prove that NaHS protect HTR-8/SVneo cell by inhibiting cell apoptosis. These promising results show that H2S elicits its effects on cell apoptosis by decreasing ROS concentration, maintaining mitochondrial membrane stability, and promoting apoptosis-inhibiting protein expression in cells.

Abstract Human exposure to wildfire is increasing in many regions globally—a trend likely to continue as climate change drives increases in wildfire activity and human populations continue to expand into fire‐prone landscapes. In Canada, this trend is reflected by a steady increase in the annual number of wildfire evacuations since the 1980s. Evacuations can be costly and cause severe stress, even when homes remain undamaged. Because many factors driving community vulnerability are likely correlated, classifying at‐risk communities into groups whose members share common drivers of wildfire vulnerability will be helpful in identifying the key wildfire evacuation “syndromes” that are repeated in different parts of the landscape. Understanding these syndromes will aid in anticipating and mitigating the effects of future fire exposure. Here, we classify the populated places across Canada's forested regions into 19 groups using variables describing their potential vulnerability to wildfire, including the surrounding land cover, land use and infrastructure, and the local fire regime. Then, we evaluate the utility of these groups by comparing actual wildfire exposure among the groups using a unique dataset of 1043 wildfire evacuations from 1980 to 2019. We identified three main evacuation syndromes that represent 79% of all evacuations and are distinct in their geographic distribution, the characteristics of the fires that drove the evacuations, the communities exposed, and the likely mode of evacuation. In remote areas dominated by conifer forest, evacuations were driven primarily by lightning‐ignited fires in the summer. Exposed communities typically lacked access to the road network, making it important to plan for evacuation by air. In less remote mixedwood forest areas, evacuations were driven largely by human‐ignited fires in the spring, and most communities had access to major roads. In interior British Columbia, evacuations were mainly in the summer and driven by both lightning‐ and human‐ignited fires. These areas experienced the greatest increase in evacuation frequency over the last two decades, reflecting the local trend of increasing wildfire activity. These differences highlight how the major risk factors vary spatially across the forested regions and temporally over the fire season—knowledge that will facilitate more effective planning for future fire seasons.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and among the leading causes of death in both men and women. Rectal cancer (RC) is particularly challenging compared with colon cancer as the treatment after diagnosis of RC is more complex on account of its narrow anatomical location in the pelvis adjacent to the urogenital organs. More and more existing studies have begun to refine the research on RC and colon cancer separately. Early diagnosis and multiple treatment strategies optimize outcomes for individual patients. However, the need for more accurate and precise models to facilitate RC research is underscored due to the heterogeneity of clinical response and morbidity interrelated with radical surgery. Organoids generated from biopsies of patients have developed as powerful models to recapitulate many aspects of their primary tissue, consisting of 3-D self-organizing structures, which shed great light on the applications in both biomedical and clinical research. As the preclinical research models for RC are usually confused with colon cancer, research on patient-derived RC organoid models enable personalized analysis of cancer pathobiology, organizational function, and tumor initiation and progression. In this review, we discuss the various applications of patient-derived RC organoids over the past two years in basic cancer biology and clinical translation, including sequencing analysis, drug screening, precision therapy practice, tumor microenvironment studies, and genetic engineering opportunities.

Abstract We aim to assess the influence of phylogenetic scale on the relationships of taxonomic and phylogenetic turnovers with environment for angiosperms in China. Specifically, we quantify the effects of contemporary climate on β‐diversity at different phylogenetic scales representing different evolutionary depths of angiosperms. We sampled a latitudinal gradient and a longitudinal gradient of angiosperm assemblages across China (each ≥3400 km). Species composition in each assemblage was documented. Three metrics of β‐diversity (βsim.tax measuring taxonomic β‐diversity; βsim.phy and Dpw measuring tip‐ and basal‐weighted phylogenetic β‐diversity, respectively) were quantified among assemblages at sequential depths in the evolutionary history of angiosperms from the tips to deeper branches. This was done by slicing the angiosperm phylogenetic tree at six evolutionary depths (0, 15, 30, 45, 60, and 75 million years ago). β‐diversity at each evolutionary depth was related to geographic and climatic distances between assemblages. In general, the relationship between β‐diversity and climatic distance decreased from shallow to deep evolutionary time slice for all the three metrics. The slopes of the decreasing trends for βsim.tax and βsim.phy were much steeper for the latitudinal gradient than for the longitudinal gradient. The decreasing trend of the strength of the relationship was monotonic in all cases except for Dpw across the longitudinal gradient. Geographic distance between assemblages explained little variation in β‐diversity that was not explained by climatic distance. Our study shows that the strength of the relationship between β‐diversity and climatic distance decreases conspicuously from shallow to deep evolutionary depth for the latitudinal gradient, but this decreasing trend is less steep for the longitudinal gradient than for the latitudinal gradient, which likely reflects the influence of historical processes (e.g., the collision of the Indian plate with the Eurasian plate) on β‐diversity.

Ataxia telangiectasia mutated (ATM) plays an essential role in DNA damage response and the maintenance of genomic stability. However, the role of ATM in regulating the function of adult neural stem cells (NSCs) remains unclear. Here we report that ATM deficiency led to accumulated DNA damage and decreased DNA damage repair capacity in neural progenitor cells. Moreover, we observed ATM ablation lead to the short-term increase of proliferation of neural progenitor cells, resulting in the depletion of the NSC pool over time, and this loss of NSC quiescence resulted in accelerated cell senescence. We further apply RNA sequencing to unravel that ATM knockout significantly affected Notch signaling pathway, furthermore, notch activation inhibit the abnormal increased proliferation of ATM–/– NSCs. Taken together, these findings indicate that ATM can serve as a key regulator for the normal function of adult NSCs by maintaining their stemness and preventing cellular senescence primarily through Notch signaling pathway.

Abstract Rechargeable aqueous zinc-ion batteries (ZIBs) have been gaining increasing interest for large-scale energy storage applications due to their high safety, good rate capability, and low cost. However, the further development of ZIBs is impeded by two main challenges: Currently reported cathode materials usually suffer from rapid capacity fading or high toxicity, and meanwhile, unstable zinc stripping/plating on Zn anode seriously shortens the cycling life of ZIBs. In this paper, metal–organic framework (MOF) materials are proposed to simultaneously address these issues and realize high-performance ZIBs with Mn(BTC) MOF cathodes and ZIF-8-coated Zn (ZIF-8@Zn) anodes. Various MOF materials were synthesized, and Mn(BTC) MOF was found to exhibit the best Zn2+-storage ability with a capacity of 112 mAh g−1. Zn2+ storage mechanism of the Mn(BTC) was carefully studied. Besides, ZIF-8@Zn anodes were prepared by coating ZIF-8 MOF material on Zn foils. Unique porous structure of the ZIF-8 coating guided uniform Zn stripping/plating on the surface of Zn anodes. As a result, the ZIF-8@Zn anodes exhibited stable Zn stripping/plating behaviors, with 8 times longer cycle life than bare Zn foils. Based on the above, high-performance aqueous ZIBs were constructed using the Mn(BTC) cathodes and the ZIF-8@Zn anodes, which displayed an excellent long-cycling stability without obvious capacity fading after 900 charge/discharge cycles. This work provides a new opportunity for high-performance energy storage system.

A primary element of modern wildfire management is to aggressively suppress small fires before they become large, but benefits can be offset by the fact that these practices promote older forests that are more ‘flammable’. Here the authors show that this downside puts numerous human communities at elevated risk of fires in boreal Canada.

Ultraviolet-C radiation sources are important for disinfection and photochemical water purification, but development of persistent phosphors is needed for other applications. Here the authors report praseodymium-doped silicate ultraviolet-C persistent phosphors for self-sustained glowing tags in bright light.

Time-varying system identification is an appealing but challenging research area. Existing identification algorithms are usually subject to either low estimation accuracy or bad numerical stability. These deficiencies motivate the development of an iterative learning identification algorithm in this paper. Three distinguished features of the proposed method result in the achievement of high estimation accuracy and high numerical stability: i) recursion along the iteration axis, ii) bias compensation, and iii) singular value decomposition (SVD). Firstly, an extra iteration axis associated with the original time axis is introduced in the parameter estimation process. A norm-optimal identification approach with the balance between convergence speed and noise robustness is then proposed along the iteration axis, followed by further analysis on the accuracy and the numerical stability. Secondly, in order to eliminate the estimation bias in the presence of noise and thus to improve the accuracy, a bias compensation algorithm along the iteration axis is proposed. Thirdly, a SVD-based update algorithm for the covariance matrix is developed to avoid the possible numerical instability during iterations. Numerical examples are finally provided to validate the algorithm and confirm its effectiveness.

Abstract Aqueous rechargeable Zn/MnO2 zinc-ion batteries (ZIBs) are reviving recently due to their low cost, non-toxicity, and natural abundance. However, their energy storage mechanism remains controversial due to their complicated electrochemical reactions. Meanwhile, to achieve satisfactory cyclic stability and rate performance of the Zn/MnO2 ZIBs, Mn2+ is introduced in the electrolyte (e.g., ZnSO4 solution), which leads to more complicated reactions inside the ZIBs systems. Herein, based on comprehensive analysis methods including electrochemical analysis and Pourbaix diagram, we provide novel insights into the energy storage mechanism of Zn/MnO2 batteries in the presence of Mn2+. A complex series of electrochemical reactions with the co-participation of Zn2+, H+, Mn2+, SO4 2−, and OH− were revealed. During the first discharge process, co-insertion of Zn2+ and H+ promotes the transformation of MnO2 into Zn x MnO4, MnOOH, and Mn2O3, accompanying with increased electrolyte pH and the formation of ZnSO4·3Zn(OH)2·5H2O. During the subsequent charge process, Zn x MnO4, MnOOH, and Mn2O3 revert to α-MnO2 with the extraction of Zn2+ and H+, while ZnSO4·3Zn(OH)2·5H2O reacts with Mn2+ to form ZnMn3O7·3H2O. In the following charge/discharge processes, besides aforementioned electrochemical reactions, Zn2+ reversibly insert into/extract from α-MnO2, Zn x MnO4, and ZnMn3O7·3H2O hosts; ZnSO4·3Zn(OH)2·5H2O, Zn2Mn3O8, and ZnMn2O4 convert mutually with the participation of Mn2+. This work is believed to provide theoretical guidance for further research on high-performance ZIBs.

The protective effects of repetitive transcranial magnetic stimulation (rTMS) on myelin integrity have been extensively studied, and growing evidence suggests that rTMS is beneficial in improving cognitive functions and promoting myelin repair. However, the association between cognitive improvement due to rTMS and changes in brain lipids remains elusive. In this study, we used the Y-maze and 3-chamber tests, as well as a mass spectrometry-based lipidomic approach in a CPZ-induced demyelination model in mice to assess the protective effects of rTMS on cuprizone (CPZ)-induced cognitive impairment and evaluate changes in lipid composition in the hippocampus, prefrontal cortex, and striatum. We found that CPZ induced cognitive impairment and remarkable changes in brain lipids, specifically in glycerophospholipids. Moreover, the changes in lipids within the prefrontal cortex were more extensive, compared to those observed in the hippocampus and striatum. Notably, rTMS ameliorated CPZ-induced cognitive impairment and partially normalized CPZ-induced lipid changes. Taken together, our data suggest that rTMS may reverse cognitive behavioral changes caused by CPZ-induced demyelination by modulating the brain lipidome, providing new insights into the therapeutic mechanism of rTMS.

Nonylphenol (NP) is considered to be an environmentally toxic, endocrine-disrupting chemical that affects humans and ecosystems. Adsorption is one of the most promising approaches for the removal of nonylphenol contamination from water. Herein, in order to design an adsorbent with high adsorption capacity, magnesium silicate with different Mg/Si ratios was successfully synthesized by a sol–gel method at 60 °C. Magnesium silicate with a Mg/Si ratio of 1:6 was found to possess the best adsorption performance, with maximum 4−NP sorption 30.84 mg/g under 25 °C and 0.2 g/L adsorbent dose. The adsorption was negatively affected by increasing adsorbent dose and temperature. The kinetics and isotherm of 4−NP adsorption by Mg/Si were well described by the pseudo−second−order and Sips model, respectively, and behavior was proven to be physisorption−enhanced by a chemical effect. Detailed characterization by XRD, BET, and SEM confirmed that the magnesium silicate possesses an amorphous, mesoporous structure. The study will contribute to the applicability of cheap magnesium silicate for removal of NP contamination in water.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The vibration signal of rotating machinery compound faults acquired in actual fields has the characteristics of complex noise sources, the strong background noise, and the nonlinearity, causing the traditional blind source separation algorithm not be suitable for the blind separation of rotating machinery coupling fault. According to these problems, an extraction method of multisource fault signals based on wavelet packet analysis (WPA) and fast independent component analysis (FastICA) was proposed. Firstly, according to the characteristic of the vibration signal of rotating machinery, an effective denoising method of wavelet packet based on average threshold is presented and described to reduce the vibration signal noise. In the method, the thresholds of every node of the best wavelet packet basis are acquired and averaged, and then the average value is used as a global threshold to quantize the decomposition coefficient of every node. Secondly, the mixed signals were separated by using the improved FastICA algorithm. Finally, the results of simulations and real rotating machinery vibration signals analysis show that the method can extract the rotating machinery fault characteristics, verifying the effectiveness of the proposed algorithm.

It has previously been reported that human adipose-derived stem cells (hASCs) can promote the regeneration of damaged tissues in rats with liver failure through a ‘paracrine effect’. Here we demonstrate a therapeutic effect of hASCs derived Extracellular Vesicles (EVs) on rat models with acute liver failure, as shown by the improvement of the survival rate by >70% compared to controls. Gene sequencing of rat liver revealed an increase in human long-chain non-coding RNA (lncRNA) H19 after hASC-derived EVs transplantation. When the H19 coding sequence was silenced in hASCs and EVs were then collected for treatment of rats with liver failure, we saw a decrease in the survival rate to 40%, compared to treatment with EVs generated from non-silenced hASCs. These data indicate that lncRNA H19 may be a potential therapeutic target for the treatment of liver failure. Keywords: Extracellular vesicles, Adipose-derived stem cells, Regeneration, Liver failure, LncRNA

In order to improve the performance of the denoising method for vibration signals of rotating machinery, a new method of signal denoising based on the improved median filter and wavelet packet technology is proposed through analysing the characteristics of noise components and relevant denoising methods. Firstly, the window width of the median filter is calculated according to the sampling frequency so that the impulse noise and part of the white noise can be effectively filtered out. Secondly, an improved self-adaptive wavelet packet denoising technique is used to remove the residual white noise. Finally, useful vibration signals are obtained after the previous processing. Simulation signals and rotor experimental vibration signals were used to verify the performance of the method. Experiment results show that the method can not only effectively eliminate the mixed complex noises but also preserve the fault character details, which demonstrates that the proposed method outperforms the method based on the wavelet-domain median filter.

An effective and sensitive method is necessary for the determination of polybrominated diphenyl ethers (PBDEs) pollutants in water. In this study, effervescent-assisted dispersive liquid-liquid microextraction with solidification of the aqueous phase (EA-DLLME-SAP), followed by Gas Chromatography-Tandem Mass Spectrometry (GC-MS-MS) quantitative analysis, was established for the preconcentration and determination of PBDEs in real environmental water samples. 1,1,2,2-Tetrachloroethane was used as the extractant and directly dispersed into the water phase of the aqueous samples with the aid of a large number of carbon dioxide bubbles generated via the acid-base reaction of acetic acid and sodium bicarbonate, which did not require the use of a dispersant during the extraction process. The key factors affecting the extraction recovery were optimized, and an internal standard was used for quantitative analysis, which gave good linearity ranges of 1–100 ng·L−1 (BDEs 28, 47, 99, and 100), 2–200 ng·L−1 (BDEs 153, 154, and 183) and 5–500 ng·L−1 (BDE 209) with limits of quantification in the range of 1.0–5.0 ng·L−1. The accuracy was verified with relative standard deviations < 8.5% observed in tap, lake, river and reservoir water samples with relative recoveries ranging from 67.2 to 102.6%. The presented method contributes to the determination of PBDEs in environmental water samples.

Understanding climate change impacts on wildland fire activity has been constrained by the high uncertainty embedded in the prediction of fire size (FS), annual number of fires (ANF), and annual area burned (AAB). While there has been a sustained effort to make connections between fire weather and fire activity, most studies have focused on individual parameters instead of treating them as a connected group. This study explores the intrinsic relationships among the major parameters of fire activity and how they relate to fire-conducive weather conditions to determine optimal prediction models. We found maximum number of fire spread days and maximum FS best predict ANF and AAB, respectively. Assessing the robustness of these relationships across Canada’s ecozones showed they are stronger in the Cordillera than in the Shields and Plains and more universal for AAB than for ANF. We also found skewness of FS distributions may play an important role in relationship strength. These relationships provide a unique way to model future fire activities under changing climate conditions.

Abstract Introduction The Canadian Forest Fire Danger Rating System (CFFDRS) is a globally known wildland fire risk assessment system, and two major components, the fire weather index system and the fire behavior prediction system, have been extensively used both nationally and internationally to aid operational wildland fire decision making. Methods In this paper, we present an overview of an R package cffdrs, which is developed to calculate components of the CFFDRS, and highlight some of its functionality. In particular, we demonstrate how these functions could be used for large data analysis. Results and Discussion With this cffdrs package, we provide a portal for not only a collection of R functions dealing with all available components in CFFDRS but also a platform for various additional developments that are useful for the understanding of fire occurrence and behavior. This is the first time that all relevant CFFDRS methods are incorporated into the same platform, which can be accessed by both the management and research communities.

Forest understory vegetation is an important characteristic of the forest. Predicting and mapping understory is a critical need for forest management and conservation planning, but it has proved difficult with available methods to date. LiDAR has the potential to generate remotely sensed forest understory structure data, but this potential has yet to be fully validated. Our objective was to examine the capacity of LiDAR point cloud data to predict forest understory cover. We modeled ground-based observations of understory structure in three vertical strata (0.5 m to < 1.5 m, 1.5 m to < 2.5 m, 2.5 m to < 3.5 m) as a function of a variety of LiDAR metrics using both mixed-effects and Random Forest models. We compared four understory LiDAR metrics designed to control for the spatial heterogeneity of sampling density. The four metrics were highly correlated and they all produced high values of variance explained in mixed-effects models. The top-ranked model used a voxel-based understory metric along with vertical stratum (Akaike weight = 1, explained variance = 87%, cross-validation error = 15.6%). We found evidence of occlusion of LiDAR pulses in the lowest stratum but no evidence that the occlusion influenced the predictability of understory structure. The Random Forest model results were consistent with those of the mixed-effects models, in that all four understory LiDAR metrics were identified as important, along with vertical stratum. The Random Forest model explained 74.4% of the variance, but had a lower cross-validation error of 12.9%. We conclude that the best approach to predict understory structure is using the mixed-effects model with the voxel-based understory LiDAR metric along with vertical stratum, because it yielded the highest explained variance with the fewest number of variables. However, results show that other understory LiDAR metrics (fractional cover, normalized cover and leaf area density) would still be effective in mixed-effects and Random Forest modelling approaches.

The influence of soil fumigation on microorganisms involved in transforming nitrogen remains little understood, despite the use of fumigants for many decades to control soil-borne pathogens and plant-parasitic nematodes. We used real-time PCR (quantitative polymerase chain reaction) and 16S rRNA gene amplicon sequencing techniques to monitor changes in the diversity and community structure of microorganisms associated with nitrogen transfer after the soil was fumigated with dazomet (DZ). We also examined nitrous oxide (N2O) emissions from these microorganisms present in fumigated fluvo-aquic soil and lateritic red soil. Fumigation with DZ significantly reduced the abundance of 16S rRNA and nitrogen cycling functional genes (nifH, AOA amoA, AOB amoA, nxrB, narG, napA, nirK, nirS, cnorB, qnorB, and nosZ). At the same time, N2O production rates increased between 9.9 and 30 times after fumigation. N2O emissions were significantly correlated with NH4+, dissolved amino acids and microbial biomass nitrogen, but uncorrelated with functional gene abundance. Diversity indices showed that DZ temporarily stimulated bacterial diversity as well as caused a significant change in bacterial community composition. For example, DZ significantly decreased populations of N2-fixing bacteria Mesorhizobium and Paenibacillus, nitrifiers Nitrosomonas, and the denitrifiers Bacillus, Pseudomonas, and Paracoccus. The soil microbial community had the ability to recover to similar population levels recorded in unfumigated soils when the inhibitory effects of DZ fumigation were no longer evident. The microbial recovery rate, however, depended on the physicochemical properties of the soil. These results provided useful information for environmental safety assessments of DZ in China, for improving our understanding of the N-cycling pathways in fumigated soils, and for determining the potential responses of different N-cycling groups after fumigation.

Anaerobic soil disinfestation (ASD) is widely used to control soilborne diseases in organic crop production. The effect of ASD used different sealed films on soilborne pathogens and strawberry growth was evaluated in two laboratory studies and two field trials. Under maltose as carbon sources, 28 °C temperature and 30% of soil moisture optimal conditions ASD decreased Fusarium spp. and Phytophthora spp. by 100%. ASD used maltose as an organic amendment and sealed with totally impermeable film (TIF) obtained the highest suppression (>96%) against Fusarium spp. and Phytophthora spp. (>91%). According to the laboratory results, the efficacy of ASD utilizing 6 or 9 t/ha maltose and sealing with TIF was evaluated and compared with reference treatment with chloropicrin (Pic) or solarization (Sol) in the field trials. Compared with the untreated soil, ASD treatments greatly reduced the pathogenic population of Fusarium spp. and Phytophthora spp., and successfully controlled the damage of fusarium wilt with evidence of lower mortality (6%). ASD significantly increased soil nutrition promoted plant growth and increased strawberry yield, which was similar as the Pic, but better than Sol treatment. The analyzed fungal and bacterial microbiota did not show significant differences in the taxonomic richness and diversity between the compared treatments. Nevertheless, the abundance of some bacterial and fungal taxa tended to change between treated. The evidence showed that adding maltose and sealing TIF for ASD has the potential to replace Pic for pathogen control in commercial strawberry production.

Feature extraction plays a crucial role in the diagnosis of rotating machinery faults. However, the vibration signals measured are inherently complex and non-stationary and the features of faulty signals are often submerged by noise. The principle and method of blind source separation are introduced, and we point out that the blind source separation algorithm is invalid in an environment of strong impulse noise. In order to solve the problem of fast separation of multi-sensor signals in an environment of strong impulse noise, first, the window width of the median filter (MF) is calculated according to the sampling frequency, so that the impulse noise and part of the white noise can be effectively filtered out. Next, the filtered signals are separated by the improved second-order blind identification (SOBI) algorithm. At the same time, the method is tested on the strong pulse background noise and rub impact dataset. The results show that this method has higher efficiency and accuracy than the direct separation method. It is possible to apply the method to real-time signal analysis due to its speed and efficiency.

During the operation of rotating machinery, the vibration signals measured by sensors are the aliasing signals of various vibration sources, and they contain strong noises. Conventional signal processing methods have difficulty separating the aliasing signals, which causes great difficulties in the condition monitoring and fault diagnosis of the equipment. The principle and method of blind source separation are introduced, and it is pointed out that the blind source separation algorithm is invalid in strong pulse noise environments. In these environments, the vibration signals are first de-noised with the median filter (MF) method and the de-noised signals are separated with an improved joint approximate diagonalization of eigenmatrices (JADE) algorithm. The simulation results found here verify the effectiveness of the proposed method. Finally, the vibration signal of the hybrid rotor is effectively separated by the proposed method. A new separation approach is thus provided for vibration signals in strong pulse noise environments.

The broad consensus indicates that climate change will cause larger and more frequent fires, resulting in a growing annual area burned (AAB) in much of Canada. Our ability to predict future changes in fire size (FS) and AAB is limited due to the uncertainty embedded in climate change models and our inability to quantify the complex interactions between the changing environment and fire activity. In this study, we introduce a new method to predict future FS and AAB across Canada over the 21st century based on fire-conducive weather and how it translates to on-the-ground fire spread (i.e. spread days). We found that the potential for an extreme fire year (99th percentile of AAB) could quadruple by the end of the century across Canada, and ≥ 10 times more common in the boreal biome. Specifically, FS and AAB may increase 20%–64% and 25%–93%, respectively, and the average fire year under the extreme climate scenario may burn ∼11 Mha, which is ∼4 Mha higher than the most extreme fire year in Canada’s modern history (∼7 Mha). Our results demonstrate that by accounting for the strong nonlinear expansion of wildfires as a function of number of fire spread days, even conservative climate-change scenarios may yield significant increase in fire activity.

Recent human-interface wildfires around the world have raised concerns regarding the reliability of freshwater supply flowing from severely burned watersheds. Degraded source water quality can often be expected after severe wildfire and can pose challenges to drinking water facilities by straining treatment response capacities, increasing operating costs, and jeopardizing their ability to supply consumers. Identifying source watersheds that are dangerously exposed to post-wildfire hydrologic changes is important for protecting community drinking-water supplies from contamination risks that may lead to service disruptions. This study presents a spatial index of watershed exposure to wildfires in the province of Alberta, Canada, where growing water demands coupled with increasing fire activity threaten municipal drinking-water supplies. Using a multi-criteria analysis design, we integrated information regarding provincial forest cover, fire danger, source water volume, source-water origin (i.e., forested/un-forested), and population served. We found that (1) >2/3 of the population of the province relies on drinking-water supplies originating in forested watersheds, (2) forest cover is the most important variable controlling final exposure scores, and (3) watersheds supplying small drinking water treatment plants are particularly exposed, especially in central Alberta. The index can help regional authorities prioritize the allocation of risk management resources to mitigate adverse impacts from wildfire. The flexible design of this tool readily allows its deployment at larger national and continental scales to inform broader water security frameworks.

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Wildfires and outbreaks of the spruce budworm, Choristoneura fumiferana (Clem.), are the two dominant natural disturbances in Canada’s boreal forest. While both disturbances have specific impacts on forest ecosystems, it is increasingly recognized that their interactions also have the potential for non-linear behavior and long-lasting legacies on forest ecosystems’ structures and functions. Previously, we showed that, in central Canada, fires occurred with a disproportionately higher frequency during a ‘window of opportunity’ following spruce budworm defoliation. In this study, we use Ontario’s spatial databases for large fires and spruce budworm defoliation to locate where these two disturbances likely interacted. Classification tree and Random Forest procedures were then applied to find how spruce budworm defoliation history, climate, and forest conditions best predict the location of such budworm–fire interactions. Results indicate that such interactions likely occurred in areas geographically bound by hardwood content in the south, the prevalence of the three major spruce budworm host species (balsam fir, white spruce and black spruce) in the north, and climate moisture in the west. The occurrence of a spruce budworm–fire interaction inside these boundaries is related to the frequency of spruce budworm defoliation. These patterns provide a means of distinguishing regions where spruce budworm attacks are likely to increase fire risk.

In the face of climate change, predicting and understanding future fire regimes across Canada is a high priority for wildland fire research and management. Due in large part to the difficulties in obtaining future daily fire weather projections, one of the major challenges in predicting future fire activity is to estimate how much of the change in weather potential could translate into on-the-ground fire spread. As a result, past studies have used monthly, annual, or multi-decadal weather projections to predict future fires, thereby sacrificing information relevant to day-to-day fire spread. Using climate projections from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), historical weather observations, MODIS fire detection data, and the national fire database of Canada, this study investigated potential changes in the number of active burning days of wildfires by relating ‘spread days’ to patterns of daily fire-conducive weather. Results suggest that climate change over the next century may have significant impacts on fire spread days in almost all parts of Canada’s forested landmass; the number of fire spread days could experience a 2-to-3-fold increase under a high CO _2 forcing scenario in eastern Canada, and a greater than 50% increase in western Canada, where the fire potential is already high. The change in future fire spread is critical in understanding fire regime changes, but is also imminently relevant to fire management operations and in fire risk mitigation.