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Based on the seismic source model in the Fifth Generation Seismic Ground Motion Parameters Zonation Map of China (FGSGMPZMC), a new seismic fault model, the new zonation of seismic risk areas (SRAs), and the estimation of seismicity rates for 2021–2030, this study constructed a new time-dependent seismic source model of China’s mainland, and used the probabilistic seismic hazard analysis method to calculate seismic hazard by selecting the ground motion models (GMMs) suitable for seismic sources in China. It also provided the probabilities of China’s mainland being affected by earthquakes of modified Mercalli intensity (MMI) VI, VII, VIII, IX, and ≥ X in 2021–2030. The spatial pattern of seismic hazards presented in this article is similar to the pattern of the FGSGMPZMC, but shows more details. The seismic hazards in this study are higher than those in the FGSGMPZMC in the SRAs and fault zones that can produce large earthquakes. This indicates that the seismic source model construction in this study is scientific and reasonable. There are certain similarities between the results in this study and those of Rong et al. (2020) and Feng et al. (2020), but also disparities for specific sites due to differences in seismic source models, seismicity parameters, and GMMs. The results of seismic hazard may serve as parameter input for future seismic risk assessments. The hazard results can also be used as a basis for the formulation of earthquake prevention and mitigation policies for China’s mainland.

RNA binding proteins (RBPs) regulate nearly all post-transcriptional processes within cells. To fully understand RBP function, it is essential to identify their in vivo targets. Standard techniques for profiling RBP targets, such as crosslinking immunoprecipitation (CLIP) and its variants, are limited or suboptimal in some situations, e.g. when compatible antibodies are not available and when dealing with small cell populations such as neuronal subtypes and primary stem cells. This review summarizes and compares several genetic approaches recently designed to identify RBP targets in such circumstances. TRIBE (targets of RNA binding proteins identified by editing), RNA tagging, and STAMP (surveying targets by APOBEC-mediated profiling) are new genetic tools useful for the study of post-transcriptional regulation and RBP identification. We describe the underlying RNA base editing technology, recent applications, and therapeutic implications.

The characteristics of seismic temporal distribution represent an important basis for earthquake prediction and seismic hazard analysis. In this paper, based on the seismic catalogs in Taiwan, and using Poisson (exponential distribution), Gamma, Lognormal, Weibull, and Brownian passage time distributions as target models, we adopt the maximum likelihood method for estimating model parameters. The optimal model for describing the temporal distribution of earthquakes in Taiwan is determined according to the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), K-S test, Chi-square test, and coefficient of determination R2 results. The results show that for moderate-strong earthquakes events (MW < 7.0), the Gamma distribution model can well describe the temporal distribution characteristics of earthquakes, while large earthquakes (MW ≥ 7.0) can be described entirely by exponential distribution. In addition, the temporal correlation between earthquakes is also examined through diffusion entropy analysis. The results show that seismic activity features temporal correlation, and earthquakes with relatively small magnitude (MW < 7) are affected by larger events (MW ≥ 7.0), thus suggesting long-term memory in time. In this study, the probability of the occurrence of a major earthquake in Taiwan is also calculated. The results show that the probability of an MW ≥ 7.0 earthquake in Taiwan in the next 10 years reaches 91.3%. The results may be used to inform the selection of seismic time distribution models and the calculation of seismic activity parameters in earthquake prediction and seismic hazard calculation, and hold scientific significance for understanding the mechanism of earthquake genesis.

Arias intensity (IA), as an important seismic parameter, which contains the information of amplitude, frequencies, and duration of ground motion, plays a crucial role in characterizing seismic hazard such as earthquake-induced landslides. In this article, we conducted probabilistic seismic hazard analysis (PSHA) based on IA in China’s north–south seismic belt. We adopted the seismic sources and seismicity parameters used in the fifth generation of the Seismic Ground Motion Parameter Zoning Map of China, and two ground-motion model of IA. The results show that the values of IA are greater than 0.11 m/s in most regions of the north–south seismic belt. The provincial capital cities and most prefecture-level cities in the seismic zone are located in the region with IA-values greater than 0.32 m/s. The values of IA are above 0.54 m/s in the region around the main fault zone. This means that the north–south seismic belt is prone to extremely high-seismic hazard, particularly earthquake-induced landslides. Therefore, it is important to strengthen the evaluation and prevention of earthquake-induced landslides in this area. As we have found significant differences in the values of IA calculated from different ground-motion model, it is necessary to study the ground-motion model of IA for the western geological environment of China. In addition, the PSHA based on IA gives more consideration to the influence of large earthquakes than that based on peak ground acceleration. Therefore, IA plays an important role in seismic design of major engineering projects. The results of this article are of great scientific significance for understanding the seismic hazard of the north–south seismic belt.

The temporal distribution of earthquakes provides important basis for earthquake prediction and seismic hazard analysis. The relatively limited records of strong earthquakes have often made it difficult to study the temporal distribution models of regional strong earthquakes. However, there are hundreds of years of complete strong earthquake records in North China Seismic Zone, providing abundant basic data for studying temporal distribution models. Using the data of M ≥ 6.5 earthquakes in North China as inputs, this paper estimates the model parameters using the maximum likelihood method with exponential, Gamma, Weibull, Lognormal and Brownian passage time (BPT) distributions as target models. The optimal model for describing the temporal distribution of earthquakes is determined according to Akaike information criterion (AIC), determination coefficient R2 and Kolmogorov-Smirnov test (K-S test). The results show that Lognormal and BPT models perform better in describing the temporal distribution of strong earthquakes in North China. The mean recurrence periods of strong earthquakes (M ≥ 6.5) calculated based on these two models are 8.1 years and 13.2 years, respectively. In addition, we used the likelihood profile method to estimate the uncertainty of model parameters. For the BPT model, the mean and 95% confidence interval of recurrence interval µ is 13.2 (8.9–19.1) years, and the mean and 95% confidence interval of α is 1.29 (1.0-1.78). For the Lognormal model, the mean value and 95% confidence interval of v is 2.09 (1.68–2.49), the mean value exp (v) corresponding to earthquake recurrence interval is 8.1 (5.4–12.1) years. In this study, we also calculated the occurrence probability of M ≥ 6.5 earthquakes in North China Seismic Zone in the future, and found that the probability and 95% confidence interval in the next 10 years based on the BPT model is 35.3% (26.8%-44.9%); the mean value and 95% confidence interval of earthquake occurrence probability based on the Lognormal distribution is 35.4% (22.9%-49.7%); the mean probability and 95% confidence interval based on the Poisson model is 53.1% (41.1%-64%). The results of this study may provide important reference for temporal distribution model selection and earthquake recurrence period calculation in future seismic hazard analysis in North China.

Pedestrian detection based on visual sensors has made significant progress, in which region proposal is the key step. There are two mainstream methods to generate region proposals: anchor-based and anchor-free. However, anchor-based methods need more hyperparameters related to anchors for training compared with anchor-free methods. In this paper, we propose a novel multiscale anchor-free (MSAF) region proposal network to obtain proposals, especially for small-scale pedestrians. It usually has several branches to predict proposals and assigns ground truth according to the height of pedestrian. Each branch consists of two components: one is feature extraction, and the other is detection head. Adapted channel feature fusion (ACFF) is proposed to select features at different levels of the backbone to effectively extract features. The detection head is used to predict the pedestrian center location, center offsets, and height to get bounding boxes. With our classifier, the detection performance can be further improved, especially for small-scale pedestrians. The experiments on the Caltech and CityPersons demonstrate that the MSAF can significantly boost the pedestrian detection performance and the log-average miss rate (MR) on the reasonable setting is 3.97% and 9.5%, respectively. If proposals are reclassified with our classifier, MR is 3.38% and 8.4%. The detection performance can be further improved, especially for small-scale pedestrians.

Vessel segmentation is critical for disease diagnosis and surgical planning. Recently, the vessel segmentation method based on deep learning has achieved outstanding performance. However, vessel segmentation remains challenging due to thin vessels with low contrast that easily lose spatial information in the traditional U-shaped segmentation network. To alleviate this problem, we propose a novel and straightforward full-resolution network (FR-UNet) that expands horizontally and vertically through a multiresolution convolution interactive mechanism while retaining full image resolution. In FR-UNet, the feature aggregation module integrates multiscale feature maps from adjacent stages to supplement high-level contextual information. The modified residual blocks continuously learn multiresolution representations to obtain a pixel-level accuracy prediction map. Moreover, we propose the dual-threshold iterative algorithm (DTI) to extract weak vessel pixels for improving vessel connectivity. The proposed method was evaluated on retinal vessel datasets (DRIVE, CHASE_DB1, and STARE) and coronary angiography datasets (DCA1 and CHUAC). The results demonstrate that FR-UNet outperforms state-of-the-art methods by achieving the highest Sen, AUC, F1, and IOU on most of the above-mentioned datasets with fewer parameters, and that DTI enhances vessel connectivity while greatly improving sensitivity. The code is available at: https://github.com/lseventeen/FR-UNet.

Earthquakes are among the most devastating natural disasters in China, causing serious casualties and property losses. To effectively reduce catastrophic risk, it is important to establish an earthquake catastrophe insurance system based on the earthquake catastrophe model, of which seismic hazard analysis is a main module. Probabilistic seismic-hazard analysis uses the potential source model, seismicity model, and ground-motion attenuation model, as well as the probability method to obtain the seismic hazard value of a given point. However, because the influence of a single seismic event is required when the earthquake catastrophe model is used for risk analysis, a series of single events needs to be generated according to the potential source model so as to calculate the influence of each event on the given point. In this study, based on the seismicity model (potential sources and their seismicity parameters) used in compiling the fifth generation of Seismic Ground Motion Parameter Zoning Map of China, we use the Monte Carlo method to simulate seismic events conforming to temporal, spatial, and intensity distribution of China’s seismic activities. In the simulation process, we follow the Poisson distribution in occurrence time and the Gutenberg–Richter law in magnitude distribution, and we use potential sources and earthquake occurrence rates to describe spatial distribution. The simulated seismic events include the following parameters: date (year, month, and day), location (longitude and latitude), depth, magnitude, and attitude of seismogenic faults. The simulated seismic event set can support earthquake risk analysis in the earthquake catastrophe model and has been applied in the earthquake catastrophe model of China.

Background A variety of diabetes self-management instruments have been developed but few of them consist of the preparedness for diabetes self-management behavior. The novel psychometric evaluation tool “the LMC Skills, Confidence & Preparedness Index (SCPI)” measures three key aspects of a patient’s diabetes self-management: knowledge of the skill, confidence in being able to perform skill and preparedness to implement the skill. The objective of this study was to translate, adapt and validate the SCPI for use in Chinese adult patients with type 2 diabetes. Methods This study followed the guideline recommended by the American Academy of Orthopaedic Surgeons Evidence Based Medicine Committee (AAOS) to indigenize the scale. Forward and back translation, and cross-cultural language debugging were completed according to the recommended steps. A convenience sample of Chinese patients with type 2 diabetes (n = 375) were recruited from a university-affiliated hospital in Shanghai. The validity (criterion, discriminant validity, and construct validity), reliability (internal consistency and test–retest reliability) and the interpretability of the instrument were examined. The content validity was calculated by experts’ evaluation. Results The Chinese version of SCPI (C-SCPI) has good internal consistency with a Cronbach’s alpha of 0.92. The ceiling effects of the preparedness subscales is 21%. The criterion validity of three dimensions of C-SCPI was established with significantly moderate correlations between the DKT, DES-SF and SDSCA (p 2/df = 2.775, RMSEA = 0.069, CFI = 0.903, GFI = 0.873, TLI = 0.889, IFI = 0.904. The test–retest reliability coefficient was 0.61 (p Conclusion We established a Chinese version of SCPI through translation and cross-cultural adaptation. The C-SCPI is reliable and valid for assessment of the level of self-management in Chinese patients with type 2 diabetes.

An earthquake catalog based on a unified magnitude scale is an important prerequisite for analyses of seismic activities and seismic hazards. To unify the magnitude scales of earthquakes in China’s seas and neighboring regions, we developed conversion relationships between surface- and body-wave magnitudes and the global centroid moment tensor (GCMT) and National Research Institute for Earth Science and Disaster Resilience (NIED) moment magnitudes for shallow and intermediate- and deep-focus earthquakes in China’s seas and adjacent areas. We employed data collected by the Chinese Earthquake Network Center, GCMT, and NIED for earthquakes of magnitude 4.5 and higher in China’s seas and neighboring regions from 1976 to 2018. We used the linear least squares regression method and the orthogonal regression method to fit the seismic data under different magnitude ranges and different focal depth ranges. The results provided empirical formulas to unify magnitude scales for the earthquakes in China’s seas and neighboring regions and also provided an important basis for seismic catalog integrity analyses and seismic activity studies for this area. The results are significant for seismic hazard analyses, seismic zoning, and mid- and long-term forecast analyses of seismic activities in the area.

In this study, we use a spatially smoothed seismicity procedure for seismic hazard analysis in North China seismic zone by establishing four spatially smoothed seismicity models according to the seismic catalogs of North China and calculating peak ground acceleration (PGA) values with 10% probability of exceedance in 50 years. The results show considerable differences between seismic hazards based on different models in certain areas, which is attributable to disparities in the seismicity levels of the four seismic models in those areas. In general, seismic hazard based on different models can be used as reference to evaluate uncertainty. In this paper, we also compare the mean PGA based on four spatially smoothed seismicity models with another PGA calculated using the zoning method based on surface seismic sources adopted for generating the Seismic Ground Motion Parameter Zonation Map of China, and find that the results of the two methods are largely similar, both of which can reflect the seismic hazard level of North China. However, there are differences at certain points, which are because the zoning approach adopts the same earthquake occurrence rate in the seismic source, while the spatially smoothed seismicity approach has different occurrence rates at different points. The discrepancies between the two can be attributed to differences in the principles adopted when potential seismic sources are classified. In particular, the PGA values of Beijing with 10% probability of exceedance in 50 years is 177.0cm/s2, 214.2 cm/s2, 252.8 cm/s2, and 187.5 cm/s2 in four spatial seismicity models, respectively. These PGA values are very important for evaluating the uncertainty of seismic hazard in Beijing. This study is an attempt to perform seismic hazard analysis using spatially smoothed seismicity models in China and recommends using this approach for areas where seismic sources are not clearly identified.

RNA translation is tightly regulated to ensure proper protein expression in cells and tissues. Translation is often assayed with biochemical assays such as ribosome profiling and TRAP, which are effective in many contexts. These assays are however not ideal with limiting amounts of biological material when it can be difficult or even impossible to make an extract with sufficient signal or sufficient signal:noise. Because of our interest in translational regulation within the few Drosophila adult circadian neurons, we fused the ADAR catalytic domain (ADARcd) to several small subunit ribosomal proteins and assayed mRNA editing in Drosophila S2 cells. The strategy is named RiboTRIBE and is analogous to a recently published APOBEC-based method. The list of RiboTRIBE-edited transcripts overlaps well with ribosome profiling targets, especially with more highly ranked targets. There is also an enriched number of editing sites in ribosome-associated mRNA comparing to total mRNA, indicating that editing occurs preferentially on polyribosome-associated transcripts. The use of cycloheximide to freeze translating ribosomes causes a substantial increase in the number of RiboTRIBE targets, which is decreased by pretreating cells with the chain terminating drug puromycin. NOTE: Additional experiments performed after first submitting this manuscript to BioRxiv estimate that less than 5% of Rps28b-ADAR is ribosome-associated. This is because the vast majority of the fusion protein sediments at the top of a polyribosome gradient. We therefore suggest that most editing reported in the manuscript is not catalyzed by ribosome-associated ADAR (10/2/2021).

Additional file 1. Process of cross-cultural adaptation & General information of experts & Modified content after interviewing.

We used a relatively new method, HyperTRIBE, to identify in vivo RNA targets of the translation inhibitor 4E-BP., 4E-BP (eIF4E-BP) represses translation initiation by binding to the 5′ cap–binding protein eIF4E and inhibiting its activity. Although 4E-BP has been shown to be important in growth control, stress response, cancer, neuronal activity, and mammalian circadian rhythms, it is not understood how it preferentially represses a subset of mRNAs. We successfully used HyperTRIBE (targets of RNA binding proteins identified by editing) to identify in vivo 4E-BP mRNA targets in both Drosophila and mammals under conditions known to activate 4E-BP. The protein associates with specific mRNAs, and ribosome profiling data show that mTOR inhibition changes the translational efficiency of 4E-BP TRIBE targets more substantially compared to nontargets. In both systems, these targets have specific motifs and are enriched in translation-related pathways, which correlate well with the known activity of 4E-BP and suggest that it modulates the binding specificity of eIF4E and contributes to mTOR translational specificity.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two related neurodegenerative diseases that present with similar TDP-43 pathology in patient tissue. TDP-43 is an RNA-binding protein which forms aggregates in neurons of ALS and FTD patients as well as in a subset of patients diagnosed with other neurodegenerative diseases. Despite our understanding that TDP-43 is essential for many aspects of RNA metabolism, it remains obscure how TDP-43 dysfunction contributes to neurodegeneration. Interestingly, altered neuronal dendritic morphology is a common theme among several neurological disorders and is thought to precede neurodegeneration. We previously found that both TDP-43 overexpression (OE) and knockdown (KD) result in reduced dendritic branching of cortical neurons. In this study, we used TRIBE (targets of RNA-binding proteins identified by editing) as an approach to identify signaling pathways that regulate dendritic branching downstream of TDP-43. We found that TDP-43 RNA targets are enriched for pathways that signal to the CREB transcription factor. We further found that TDP-43 dysfunction inhibits CREB activation and CREB transcriptional output, and restoring CREB signaling rescues defects in dendritic branching. Finally, we demonstrate, using RNA sequencing, that TDP-43 OE and KD cause similar changes in the abundance of specific messenger RNAs, consistent with their ability to produce similar morphological defects. Our data therefore provide a mechanism by which TDP-43 dysfunction interferes with dendritic branching, and may define pathways for therapeutic intervention in neurodegenerative diseases.

RNA-binding proteins (RBPs) accompany RNA from birth to death, affecting RNA biogenesis and functions. Identifying RBP-RNA interactions is essential to understanding their complex roles in different cellular processes. However, detecting in vivo RNA targets of RBPs, especially in a small number of discrete cells, has been a technically challenging task. We previously developed a novel technique called TRIBE (targets of RNA-binding proteins identified by editing) to overcome this problem. TRIBE expresses a fusion protein consisting of a queried RBP and the catalytic domain of the RNA-editing enzyme ADAR (adenosine deaminase acting on RNA) (ADARcd), which marks target RNA transcripts by converting adenosine to inosine near the RBP binding sites. These marks can be subsequently identified via high-throughput sequencing. In spite of its usefulness, TRIBE is constrained by a low editing efficiency and editing-sequence bias from the ADARcd. Therefore, we developed HyperTRIBE by incorporating a previously characterized hyperactive mutation, E488Q, into the ADARcd. This strategy increases the editing efficiency and reduces sequence bias, which markedly increases the sensitivity of this technique without sacrificing specificity. HyperTRIBE provides a more powerful strategy for identifying RNA targets of RBPs with an easy experimental and computational protocol at low cost, that can be performed not only in flies, but also in mammals. The HyperTRIBE experimental protocol described below can be carried out in cultured Drosophila S2 cells in 1 week, using tools available in a common molecular biology laboratory; the computational analysis requires 3 more days.

Disaster preparedness is critical for reducing potential impact. This paper contributes to current knowledge of disaster preparedness using representative national sample data from China, which faces high earthquake risks in many areas of the country. The adoption of earthquake preparedness activities by the general public, including five indicators of material preparedness and five indicators of awareness preparedness, were surveyed and 3245 respondents from all 31 provinces of Mainland China participated in the survey. Linear regression models and logit regression models were used to analyze the effects of potential influencing factors. Overall, the preparedness levels are not satisfied, with a material preparation score of 3.02 (1–5), and awareness preparation score of 2.79 (1–5), nationally. Meanwhile, residents from western China, which has higher earthquake risk, have higher degrees of preparedness. The concern for disaster risk reduction (DRR) and the concern for building safety and participation in public affairs are consistent positive predictors of both material and awareness preparedness. The demographic and socioeconomic variables' effects, such as gender, age, education, income, urban/rural division, and building size, vary according to different preparedness activities. Finally, the paper concludes with a discussion of the theoretical contribution and potential implementation.

Taiyuan is a city in Shanxi Province, China, and possesses serious seismic hazard. In this study, we constructed a time-dependent seismic hazard model for Taiyuan and the surrounding area based on several major-earthquake seismogenic structures for which historical and paleoseismic event data were available. With the time-dependent model, we calculated the distribution of peak ground acceleration with 10% probability of exceedance in the next 50 years in Taiyuan and the surrounding area, and compared the results with those calculated using the time-independent model. The results showed that the entire area around Taiyuan has a higher seismic hazard with the time-dependent model than that with the time-independent model. The Jiaocheng and Hengshan faults have much higher seismic hazard. Applying the model only to Taiyuan showed that the city has higher seismic hazard with the time-dependent model than that with the time-independent model. In particular, in the western part of Taiyuan, the seismic hazard is quite high because of the proximity of the area to the Jiaocheng Fault.

A particle swarm optimization (PSO) algorithm which can dynamically adjust learning factors is proposed to solve the problems of low efficiency and unstable operation of traditional industrial robots. The method uses piecewise polynomial interpolation to fit the trajectory, and uses an improved particle swarm algorithm to optimize the trajectory of industrial robots with time as a fitness function. This method effectively combines the piecewise polynomial interpolation function with PSO, avoids the complex process of particle swarm algorithm to construct the adaptation function, and improves the problem that the traditional PSO is more likely to fall into local extreme value in the early stage and convergence speed is slow in the later stage. Through experiments to obtain the motion pose, velocity and acceleration trajectory of each joint of the manipulator, we can know that this method can effectively realize the trajectory optimization of the industrial robot, and ensure the stability of the overall operation while improving the operating efficiency.

The environment project in the greater Mekong sub-region was the largest multi-field environmental cooperation launched by six countries (China, Vietnam, Laos, Myanmar, Thailand and Cambodia) in 2006, since the cooperation mechanism was established by Asian Development Bank (ADB) in 1992. How to establish the indicators to assess the achievements of the biological corridor construction and the status of ecological environment quantitatively is one of the prerequisites for the future project ongoing phase. The popular Pressure-State-Response (PSR) framework was employed in this study to assess the natural and human pressure, the healthy state of regional natural environment, and the subsequent response of ecosystem dynamic change in the Greater Mekong Subregion. Instead of using surveying based data as driving parameters, large amount of driving factors were retrieved from multi-source remote sensing data from 2000 to 2017, which provides access to larger updated and real-time databases, more tangible data allowing more objective goal management, and better spatially covered. The driving factors for pressure analysis included digital elevation, land surface temperature, evapotranspiration, light index, road network map, land cover dynamic change and land use degree, which were derived directly and indirectly from remote sensing. The indicators for state evaluation were composed of vegetation index, leaf area index, and fractional vegetation cover from remote sensing directly. The comprehensive response index was mainly determined by the pressure and state indicators. Through the analysis based on an overlay technique, it showed that the ecological environment deteriorated firstly from 2000 to 2010 and then started to improve from 2010 to 2017. The proofs indicated that the natural forest and wetland ecosystems were improved and the farmland area was decreased between 2000 and 2017. This study explored effective indicators from remote sensing for the ecological and environmental assessment, which can provide a strong decision-making basis for promoting the sustainable development of the ecological environment in the greater Mekong subregion, as well as the technological support for the construction of the biodiversity corridor.

With the development of e-commerce, delivery time is regarded as a key competitive advantage in an oligopoly market, as shortening the delivery time can stimulate demand for products. Many firms adopt a variety of strategies to shorten delivery time, and holding sufficient inventory is reported as an effective way. This study integrates a market share attraction model based on delivery time competition with the traditional inventory model to determine the optimal delivery time and order quantity. With the use of supermodular game method, we investigate the effect of changes in marketing and operations factors on the equilibrium delivery time and order quantity in non-dominated and dominated oligopolistic markets. The results reveal that the equilibrium delivery time and order quantity exhibit a directional response to changes in marketing and operations factors, and the response differs between the non-dominated oligopoly and the dominated oligopoly. Furthermore, under a cooperative oligopolistic market with asymmetry, it is beneficial for the firms with high competitive strength to adopt the delivery time strategy, but it fails to do so for the firm with the low competitive strength. Lastly, numerical analysis suggests that marketing factors play a more important role in affecting equilibrium measures than operations factors.

Serverless computing is a new cloud programming and deployment paradigm that is receiving wide-spread uptake. Serverless offerings such as Amazon Web Services (AWS) Lambda, Google Functions, and Azure Functions automatically execute simple functions uploaded by developers, in response to cloud-based event triggers. The serverless abstraction greatly simplifies integration of concurrency and parallelism into cloud applications, and enables deployment of scalable distributed systems and services at very low cost. Although a significant first step, the serverless abstraction requires tools that software engineers can use to reason about, debug, and optimize their increasingly complex, asynchronous applications. Toward this end, we investigate the design and implementation of GammaRay, a cloud service that extracts causal dependencies across functions and through cloud services, without programmer intervention. We implement GammaRay for AWS Lambda and evaluate the overheads that it introduces for serverless micro-benchmarks and applications written in Python.

The North–South Seismic Zone is a well-known seismotectonic zone in China that frequently experiences major earthquakes. A new probabilistic seismic hazard assessment (PSHA) for this zone is required. In this study, we perform a new PSHA for the North–South Seismic Zone with new models, including a fault source model and a time-dependent seismicity model of major-earthquake seismogenic structures. We demonstrate that the seismic hazard in areas near faults calculated using the fault source model is higher than that calculated using the area model. Faults close to their expected recurrence time for major earthquakes have high seismic hazard. Areas of high seismic hazard in the North–South Seismic Zone between 2016 and 2065 are the Moxi Segment of the Xianshuihe Fault, the Anninghe Fault, and the Daliangshan Fault. High-seismic-hazard areas between 2066 and 2115 are the Luhuo and Zheduotang segments of the Xianshuihe Fault and the Anninghe Fault. The Moxi Segment of the Xianshuihe Fault has the highest seismic hazard over the next 50 years.

Disaster preparedness is critical for reducing potential impact. This paper contributes to current knowledge of disaster preparedness using a representative national sample data from China, which faces high earthquake risks in many areas of the country. The adoption of earthquake preparedness activities by the general public, including five material preparation, and five awareness preparation were surveyed, and 3,245 respondents from all of the 31 provinces of mainland China participated in the survey. Linear regression models and Logit regression models were used to analyze the effects of potential influencing factors. Overall, the preparedness levels are not satisfied, with a material preparation score of 3.02 (1–5), and awareness preparation score of 2.79 (1–5), nationally. Meanwhile, residents from west China where have higher earthquake risk have higher preparedness degrees. The concern of disaster risk reduction, the concern of building safety and participation in public affairs are consistent positive predictors of both material and awareness preparedness. The demographic and socioeconomic variables' effects, such as gender, age, education, income, urban/rural division, and occupied building type, vary according to different preparedness activities. Finally, the paper concludes with a discussion of the theoretical contribution and potential implementation.

We previously developed TRIBE, a method for the identification of cell-specific RNA binding protein targets. TRIBE expresses an RBP of interest fused to the catalytic domain (cd) of the RNA editing enzyme ADAR and performs Adenosine-to-Inosine editing on RNA targets of the RBP. However, target identification is limited by the low editing efficiency of the ADARcd. Here we describe HyperTRIBE, which carries a previously characterized hyperactive mutation (E488Q) of the ADARcd. HyperTRIBE identifies dramatically more editing sites, many of which are also edited by TRIBE but at a much lower editing frequency. HyperTRIBE therefore more faithfully recapitulates the known binding specificity of its RBP than TRIBE. In addition, separating RNA binding from the enhanced editing activity of the HyperTRIBE ADAR catalytic domain sheds light on the mechanism of ADARcd editing as well as the enhanced activity of the HyperADARcd.

This paper proposes a method of lossless micromagnetic detection in the geomagnetic field for detecting traces of carbon impurity defects in crystalline silicon. The magnetization tests show that crystalline silicon is a diamagnetic substance with a stronger relative permeability than carbon. Micromagnetic decay theory is gained according to the energy decay. When the geomagnetic field penetrates through the materials, the apparent magnetic susceptibility can be calculated and subsequently used to project the images. The resulting image clearly showed the location of the defects. Test results are proved by the metallographic phase and spectral analysis. New method and ideas are provided for effective detection of trace carbon impurity defects in the crystalline silicon.

Hepatocellular carcinoma (HCC) is among the commonest kind of malignant tumors, which accounts for more than 500,000 cases of newly diagnosed cancer annually. Many microarray studies for identifying differentially expressed genes (DEGs) in HCC have been conducted, but results have varied across different studies. Here, we performed a meta-analysis of publicly available microarray Gene Expression Omnibus datasets, which covers five independent studies, containing 753 HCC samples and 638 non-tumor liver samples. We identified 192 DEGs that were consistently up-regulated in HCC vs. normal liver tissue. For the 192 up-regulated genes, we performed Kyoto Encyclopedia of Genes and Genomes pathway analysis. To our surprise, besides several cell growth-related pathways, spliceosome pathway was also up-regulated in HCC. For further exploring the relationship between spliceosome pathway and HCC, we investigated the expression data of spliceosome pathway genes in 15 independent studies in Nextbio database ( https://www.nextbio.com/b/nextbioCorp.nb ). It was found that many genes of spliceosome pathway such as HSPA1A, SNRPE, SF3B2, SF3B4 and TRA2A genes which we identified to be up-regulated in our meta-analysis were generally overexpressed in HCC. At last, using real-time PCR, we also found that BUD31, SF3B2, SF3B4, SNRPE, SPINK1, TPA2A and HSPA1A genes are significantly up-regulated in clinical HCC samples when compared to the corresponding non-tumorous liver tissues. Our study for the first time indicates that many genes of spliceosome pathway are up-regulated in HCC. This finding might put new insights for people's understanding about the relationship of spliceosome pathway and HCC.

Our previous study of interleukin-2 (IL-2) signaling found that redox factor-1 (Ref-1) mRNA was upregulated by IL-2. In this study, we further studied the function of Ref-1 in the potential redox regulation of IL-2 signaling in BA/F3β cells. Western blot analysis confirmed that IL-2 stimulation increases Ref-1 protein. Flow cytometric assay by using 2′,7′-dichlorofluorescin diacetate indicated that IL-2 stimulation results in an oxidative shift of intracellular environment. However, IL-2-induced activator protein-1 (AP-1) is oxidation-sensitive. Gel shift assays of nuclear extracts immunodepleted of Ref-1 protein demonstrated that IL-2-induced AP-1 DNA binding is dependent on the presence of Ref-1. This was further confirmed by the restoration of AP-1 DNA binding upon the re-addition of immunoprecipitated Ref-1. Additionally, reporter gene assays showed that AP-1 transcriptional activity was enhanced by the overexpression of Ref-1 and attenuated by the introduction of antisense Ref-1. These results suggest that the induction of Ref-1 ensures AP-1 activation in the intracellular oxidative environment of IL-2-stimulated BA/F3β cells.

IL-2 is the major regulatory cytokine of the immune system. It plays a key role in T cell survival, growth and activation. IL-2 may induce the expression of multiple genes including some cytokine genes. The induction of these genes is triggered by different signal pathways, one of them being the Jak-STAT signal pathway. The genes regulated by this pathway remain to be determined. By studying IL-2-inducible genes, we have confirmed that the TNF-beta gene is one of the immediate early genes activated by IL-2. By analysis of the DNA sequences around 180-300 bases upstream of the transcription initiation point of the mouse TNF-beta gene, we demonstrate that there is a STAT5 binding site which is essential to the inducibility of the TNF-beta gene. Furthermore, in BA/F3 cells co-transfected with the STAT5A gene and IL-2R beta gene, the activation of the TNF-beta gene promoter by IL-2 was greatly promoted, whereas the TNF-beta gene promoter became IL-2-non-inducible if the STAT5A gene was substituted with a dominant negative STAT5A, i.e. a C-terminally truncated mutant. Taken together, our results show that the Jak-STAT signal pathway is involved in induction of the TNF-beta gene in cells stimulated by IL-2.

Background The molecular history of animal evolution from single-celled ancestors remains a major question in biology, and little is known regarding the evolution of cell cycle regulation during animal emergence. In this study, we conducted a comprehensive evolutionary analysis of CDK and cyclin proteins in metazoans and their unicellular relatives. Results Our analysis divided the CDK family into eight subfamilies. Seven subfamilies (CDK1/2/3, CDK5, CDK7, CDK 20, CDK8/19, CDK9, and CDK10/11) are conserved in metazoans and fungi, with the remaining subfamily, CDK4/6, found only in eumetazoans. With respect to cyclins, cyclin C, H, L, Y subfamilies, and cyclin K and T as a whole subfamily, are generally conserved in animal, fungi, and amoeba Dictyostelium discoideum. In contrast, cyclin subfamilies B, A, E, and D, which are cell cycle-related, have distinct evolutionary histories. The cyclin B subfamily is generally conserved in D. discoideum, fungi, and animals, whereas cyclin A and E subfamilies are both present in animals and their unicellular relatives such as choanoflagellate Monosiga brevicollis and filasterean Capsaspora owczarzaki, but are absent in fungi and D. discoideum. Although absent in fungi and D. discoideum, cyclin D subfamily orthologs can be found in the early-emerging, non-opisthokont apusozoan Thecamonas trahens. Within opisthokonta, the cyclin D subfamily is conserved only in eumetazoans, and is absent in fungi, choanoflagellates, and the basal metazoan Amphimedon queenslandica. Conclusions Our data indicate that the CDK4/6 subfamily and eumetazoans emerged simultaneously, with the evolutionary conservation of the cyclin D subfamily also tightly linked with eumetazoan appearance. Establishment of the CDK4/6-cyclin D complex may have been the key step in the evolution of cell cycle control during eumetazoan emergence.