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The dynamic damage of surrounding rock masses has a great impact on the tunnel stability during the drilling and blasting construction processes. However, traditional FEM has some difficulties in simulating the blast damage processes of rock masses during mesh re-divisions. In our work, the smoothing kernel function in traditional SPH method has been improved, and the momentum equation considering the blasting load is derived, which realizes the modeling of the dynamic damage evolution processes under the SPH framework. Firstly, two typical examples are numerically simulated: 1) Upper slow and lower steep “Y” shaped fissure and 2) Upper short and lower long “Y” shaped fissure. The simulation results are compared with previous experimental results to verify the correctness of the SPH method. Then, the progressive blast damage processes are simulated, and the effects of different stress wave loading modes, different pre-existing fissure distances, different fissure dip angles as well as different ground stress levels on the blast cracking morphologies are investigated. Results show that: The blast cracks first appear around the blast hole, then the radial cracks propagate to the model boundary; The radial crack length increases with the increase of peak blast stress wave; The length of the horizontal radial crack decreases and the length of the vertical radial crack increases with the increase of the horizontal ground stress; The existence of pre-existing fissure prevents the further extension of the blasting cracks, and the increase of the fissure dip angle leads to the crack propagation at the fissure tips; The increase of fissure distance leads to the larger crack propagation in the around the fissure; The damage count increases with the increase of peak blast stress wave; The increase of the ratio of horizontal stress to vertical stress decreases the damage count; The damage counts increase with the increase of fissure dip angles; The damage degree of the model increases with the increase of the fissure distance.

With the decrease in energy storage costs and the popularization of the shared economy principle, shared energy storage (SES) has been gradually deployed in the residential community to reduce energy costs. However, centralized trading platforms for SES trading are rare in the residential community, so it is difficult for users with the trading demands to search for appropriate trading partners and make a deal. To address the above problem, a decentralized trading mechanism of SES considering the preference of trading subjects is proposed to enable the users in the residential community to trade in the absence of centralized trading platforms. The cost-based price models are built to determine the acceptable price ranges for SES users, DG users and power consumers, which will be used as the basis for the quotation in the process of decentralized trading. Moreover, based on a multinomial logit model and an improved Rubinstein model, the trading partner selection method and the negotiation strategy are proposed to be adopted in the decentralized trading mechanism. Through the autonomous selection of trading partners and multiple rounds of negotiation and quotation, the trading probability of the users can be improved. Numerical simulation studies show that the proposed decentralized trading mechanism can achieve a higher sale rate of SES trading. All types of users can obtain revenue or reduce energy costs through SES trading.

As the largest developing country in the world, China has promised to peak the carbon dioxide emissions before 2030 and achieve carbon neutrality before 2060 to mitigate the greenhouse effect. In the meantime, the electric power industry is playing a key role in achieving this ambitious target through “electricity substitution” and “clean substitution” strategies and constructing the “new type of power system”. Given this background, a specific and detailed model for the electric power supply structure transformation (EPSST) model is proposed in this rapid communication for the first time, which helps to analyse the transformation more reasonably. The proposed EPSST model aims to minimize the total costs for electric power supply structure transformation with the carbon neutrality constraints considered. Besides, the other constraints associated with the construction and retirement of different types of power plants, the balance between power supply and demand, and carbon sinks are also considered. Two scenarios aiming to achieve carbon neutrality before 2060 and 2055 are respectively studied and corresponding analyses for the transformation are also performed. The results show the feasibility of the proposed EPSST model and finally a macroscopic forecast for the future electric power industry is given.

The optimization of power purchasing is the crucial part to enhance the core competitiveness of electricity retailers, which can help electricity retailers achieve economic efficiency improvement and risk reduction. Therefore, a power purchasing optimization model of electricity retailers based on IGDT is proposed in this paper. Firstly, considering the multiple uncertainties faced by electricity retailers when participating in the multi-time scale markets, the profits and risks of power purchasing strategies are quantified. Then, a power purchasing optimization model based on IGDT is constructed, which can assess the robustness of its purchasing strategies against load fluctuation under expected utility. Finally, the case studies using the data of a provincial power market in China illustrate that the proposed optimization model can effectively provide power purchasing strategies with robustness to balance the profit and risk of the electricity retailer, and as the risk attitude tends to be conservative, the proportion of power purchasing through bilateral contracts increases while the load fluctuation range that can be resisted decreases.

Staphylococcus aureus is an opportunistic foodborne pathogen occasionally isolated from diarrhea patients. In recent years, increasing studies have reported the detection of S. aureus in food poisoning incidents due to food contamination in the North and South of China. However, the epidemiology and genetic characteristics of S. aureus from food poisoning incidents in Eastern China remain unknown. The present study examined the genetic characteristics, antimicrobial resistance, and virulent factors of multidrug-resistant S. aureus isolated from 22 food poisoning incidents reported by the hospitals and health centers in Eastern China from 2011 to 2021. A total of 117 resistant and enterotoxigenic S. aureus isolates were collected and sequenced, among which 20 isolates were identified as methicillin resistant. Genetic analysis revealed 19 distinct CC/ST types, with CC6, CC22, CC59, CC88, and CC398 being the most frequent variants in methicillin-resistant S. aureus (MRSA). A considerable shift in CC types from CC1 to CC398 between 2011 and 2021 was observed in this study, indicating that CC398 may be the main epidemic strain circulating in the current food poisoning incidents. Additionally, genes for enterotoxins were detected in 55 isolates, with a prevalence of 27.8% (27/97) for methicillin-sensitive variants and 35.0% (7/20) for MRSA. The scn gene was detected in 59.0% of the isolates, demonstrating diverse contaminations of S. aureus among livestock-to-human transmission. Of the 117 isolates, only ten isolates displayed multi-drug resistance (MDR) to penicillin, tetracycline, and macrolides. None of the 117 foodborne S. aureus isolates tested positive for vanA in this study. Together, the present study provided phylogenetic characteristics of S. aureus from food poisoning incidents that emerged in Eastern China from 2011 to 2021. Our results suggested that these diarrhea episodes were hypotonic and merely transient low-MDR infections, however, further research for continued surveillance given the detection of virulence and antimicrobial resistance determinants is required to elucidate the genomic characteristics of pathogenic S. aureus in food poisoning incidents in the context of public health.

The Thermo-Hydro-Mechanical-Damage (THMD) process inside rock structures is a complex multi-field coupling problem, which is also regarded as the hotspot worldwide. In view of this situation, a fracture mark ξ is introduced to reflect the “active” or “failure” mode of Smoothed Particle Hydrodynamics (SPH) particles, which can simulate rock progressive cracking characteristics. The solid-water interaction modes and the damaged particles - water particles transformation algorithms are embedded into traditional SPH program to simulate the water-stress coupling problems. The heat conduction equations are programmed into SPH, which can reach the goal of modeling the temperature-stress coupling problems. Results show that: By coupling the parameter transformations between water and solid particles, the thermo-hydro-mechanical-damage simulation is then realized. Three numerical examples are carried out to validate the improved THMD method. Finally, an engineering numerical model of a typical tunnel is established, and the THMD coupling processes under complex conditions are simulated, which shows that the improved SPH method can simulate rock THMD multi-field coupling problems. The research results will help understanding the rock THMD coupling mechanisms, meanwhile, it can also promote the applications of SPH method into THMD modeling.

The applications of Smoothed Particle Hydrodynamics (SPH) into the chemical - mechanical - damage coupling problems of cement - based materials have been rarely investigated. Based on this background, the diffusion equations of chemical ion concentration in SPH form are derived. Traditional kernel function in SPH is improved by introducing the ion concentration damage coefficient Dc. Firstly, the chemical corrosion processes of a semicircular corrosion pit are simulated, and the rationality is verified by comparing with previous experimental results. Then the effects of different bedding direction, random aggregates and their anisotropy degrees on the chemical corrosion processes are discussed. Finally, a chemical-stress-damage coupling model is established to simulate the crack propagation processes. The research results can provide some references for the comprehensive understandings of the chemical-stress-damage coupling laws, as well as the applications of SPH method into the chemical-stress-damage coupling simulations of cement-based materials.

Summary: N6-methyladenosine (m6A) methyltransferase Mettl3 is involved in conventional T cell immunity; however, its role in innate immune cells remains largely unknown. Here, we show that Mettl3 intrinsically regulates invariant natural killer T (iNKT) cell development and function in an m6A-dependent manner. Conditional ablation of Mettl3 in CD4+CD8+ double-positive (DP) thymocytes impairs iNKT cell proliferation, differentiation, and cytokine secretion, which synergistically causes defects in B16F10 melanoma resistance. Transcriptomic and epi-transcriptomic analyses reveal that Mettl3 deficiency disturbs the expression of iNKT cell-related genes with altered m6A modification. Strikingly, Mettl3 modulates the stability of the Creb1 transcript, which in turn controls the protein and phosphorylation levels of Creb1. Furthermore, conditional targeting of Creb1 in DP thymocytes results in similar phenotypes of iNKT cells lacking Mettl3. Importantly, ectopic expression of Creb1 largely rectifies such developmental defects in Mettl3-deficient iNKT cells. These findings reveal that the Mettl3-m6A-Creb1 axis plays critical roles in regulating iNKT cells at the post-transcriptional layer.

The tropospheric impact of Arctic ozone loss events is still debatable. In this study we investigate that question, using the ERA5 reanalysis and long-term integration by a climate-chemistry coupled model (CESM2-WACCM). We begin with the frequency of Arctic ozone loss events. On average, such events occur once in early spring every 14−15 years in ERA5 data and in the model, both of which estimate that roughly 40% of the strong polar vortex events in March are coupled with Arctic ozone loss, the remaining 60% being uncoupled. The composite difference between the two samples might be attributed to the pure impact of the Arctic ozone loss — that is, to ozone loss alone, without the concurrent impact of strong polar vortices. Arctic ozone loss is accompanied by an increase in total ozone in midlatitudes, with the maximum centered in the Central North Pacific. Contrasting Arctic ozone loss events with pure strong polar vortex events that are uncoupled with ozone loss, observations confirm that the stratospheric Northern Annular Mode reverses earlier for the former. For pure strong vortex events in early spring (without Arctic ozone loss), the cold anomalies can extend from the stratosphere to the middle troposphere; when such events are strong, the near surface warm anomalies are biased toward the continents. In contrast, during the other 40% of strong early-spring polar vortex events, those coupled with ozone loss, a concurrent and delayed warming of the near surface over the Arctic and its neighboring areas is observed, due to vertical redistribution of solar radiation by the change in the ozone.

The simulation of crack propagation processes in rock engineering has been not only a research hot spot among scholars but also a challenge. Based on this background, a new numerical method named improved kernel of smoothed particle hydrodynamics (IKSPH) has been put forward. By improving the kernel function in the traditional smoothed particle hydrodynamics (SPH) method, the brittle fracture characteristics of the base particles are realized. The particle domain searching method (PDSM) has also been put forward to generate the arbitrary complex fissure networks. Three numerical examples are analyzed to validate the efficiency of IKSPH and PDSM, which can correctly reveal the morphology of wing crack and the laws of crack coalescence compared with previous experimental and numerical studies. Finally, a rock slope model with complex joints is numerically simulated and the progressive failure processes are exhibited, which indicates that the IKSPH method can be well applied to rock mechanics engineering. The research results showed that IKSPH method reduces the programming difficulties and avoids the traditional grid distortion, which can provide some references for the application of IKSPH to rock mechanics engineering and the understanding of rock fracture mechanisms.

The “dual-carbon” policy underscores the crucial importance of a secure and stable natural gas supply to ensure the reliable operation of power systems. In high-load areas with a high proportion of gas-fired units and no alternative energy supply, urgent attention needs to be paid to the impact of natural gas loss on power system reliability. Given this background, a method to evaluate power system reliability that considers natural gas supply fluctuations is proposed. In this method, a reliability model of the natural gas supply chain based on the minimal cut set theory is constructed and the influence of policy regulations and economic market factors on system components is quantified. Then, a reliability-evaluation model for a power system that considers gas loss is constructed, and a non-sequential Monte Carlo simulation is used to solve it. Afterward, a reliability-evaluation method considering the power system reserve capacity is proposed. Finally, case studies on a natural gas system with a 14-node power system of a certain area are performed to verify the effectiveness of the proposed method, and the simulation results demonstrate that the reliability of the energy supply directly affects the reliability of the power system.

Staphylococcus aureus is an opportunistic pathogen that causes invasive infections in humans. In recent years, increasing studies have focused on the prevalence of S. aureus infections in adults; however, the epidemiology and molecular characteristics of S. aureus from Chinese pediatric patients remain unknown. The present study examined the population structure, antimicrobial resistance, and virulent factors of methicillin-resistant and -susceptible S. aureus isolated from Chinese pediatric patients from one medical center in eastern China. A total of 81 cases were screened with positive S. aureus infections among 864 pediatric patients between 2016 and 2022 in eastern China. Molecular analysis showed that ST22 (28.4%) and ST59 (13.6%) were the most typical strains, and associations between different clonal complex (CC) types/serotype types (ST) and the age of pediatric patients were observed in this study. CC398 was the predominant type in neonates under 1 month of age, while CC22 was mainly found in term-infant (under 1 year of age) and toddlers (over 1 year of age). Additionally, 17 S. aureus isolates were resistant to at least three antimicrobials and majority of them belonged to CC59. The blaZ gene was found in 59 isolates and mecA gene was present in 26 strains identified as methicillin-resistant. Numerous virulent factors were detected in S. aureus isolated from present pediatric patients. Remarkably, lukF-PV and lukS-PV were dominantly carried by CC22, tsst-1 genes were detected in CC188, CC7, and CC15, while exfoliative toxin genes were found only in CC121. Only 41.98% of the S. aureus isolates possessed scn gene, indicating that the sources of infections in pediatric patients may include both human-to-human transmissions as well as environmental and nosocomial infections. Together, the present study provided a phylogenetic and genotypic comparison of S. aureus from Chinese pediatric patients in Suzhou city. Our results suggested that the colonization of multi-drug resistant isolates of S. aureus may raise concern among pediatric patients, at least from the present medical center in eastern China.

T follicular helper (TFH) cells are specialized effector CD4+ T cells that are critical in humoral immunity, but the function of post-transcriptional regulation is not clearly defined. Here, the authors demonstrate that RNA methylation is important for TFH effector differentiation and subsequent antibody formation through stabilization of Tcf7 transcripts.

In order to reduce the influence of differences in human characteristics on the blood pressure prediction model and further improve the accuracy of blood pressure prediction, this paper establishes support vector machine regression model and random forest regression model for accurate blood pressure measurement. First, the photoelectric method is used to obtain the photoelectric plethysmography signal (PPG) and ECG signals from people of different ages, and the blood pressure value is roughly estimated based on the high-quality physiological signals and the vascular elastic cavity model; then the human body characteristics are used as the input parameters of the blood pressure prediction model, and the model parameters are used to find the best parameter combination to improve the prediction performance of the model; finally, through a lot of training and learning, the best blood pressure prediction model is selected to achieve accurate measurement of blood pressure values. It has been verified by experiments that the average absolute error of diastolic and systolic blood pressure based on the random forest optimization model meets the standard of less than 5mmHg formulated by AAMI (American Medical Instrument Promotion Association), which is better consistent with the method of mercury sphygmomanometer, and has more excellent performance than support vector machine regression model under the same conditions.

AbstractThe behavioral characteristics of multiple cracks are important factors leading to material failures. However, to date, the fracturing and interactions of internal cracks have received minimal research due to the challenges in creating real internal cracks in brittle solids without incurring any damages to the surfaces. Therefore, this study investigated the fracturing processes and interactions between two parallel penny-shaped internal cracks under tensile stress conditions using both experimental and numerical simulation methods. Glass was used as the experimental material in this study. The results showed that the vertical spacing d between the two cracks was an important factor which affected both the crack interactions and the failure loads. When the d was small, attraction and coalescence occurred between the two cracks. However, when the d was large, the fracturing was observed to occur in the plane where one crack was located. A crack propagation arc appeared in all of the examined specimens. The loads of the crack initiation and the strength levels of the specimens were determined to be positively related to the crack spacing d. It was found that the larger the d was, the larger the crack initiation load and tensile strength values would be. In the present study, the crack paths in the numerical simulations based on the MTS criterion were determined to be consistent with the experiment results.

The underlying mechanisms of thymocyte development and lineage determination remain incompletely understood, and the emerging evidences demonstrated that RNA binding proteins (RBPs) are deeply involved in governing T cell fate in thymus. Serine/arginine-rich splicing factor 1 (SRSF1), as a classical splicing factor, is a pivotal RBP for gene expression in various biological processes. Our recent study demonstrated that SRSF1 plays essential roles in the development of late thymocytes by modulating the T cell regulatory gene networks post-transcriptionally, which are critical in response to type I interferon signaling for supporting thymocyte maturation. Here, we report SRSF1 also contributes to the determination of the CD8+ T cell fate. By specific ablation of SRSF1 in CD4+CD8+ double positive (DP) thymocytes, we found that SRSF1 deficiency impaired the maturation of late thymocytes and diminished the output of both CD4+ and CD8+ single positive T cells. Interestingly, the ratio of mature CD4+ to CD8+ cells was notably altered and more severe defects were exhibited in CD8+ lineage than those in CD4+ lineage, reflecting the specific function of SRSF1 in CD8+ T cell fate decision. Mechanistically, SRSF1-deficient cells downregulate their expression of Runx3, which is a crucial transcriptional regulator in sustaining CD8+ single positive (SP) thymocyte development and lineage choice. Moreover, forced expression of Runx3 partially rectified the defects in SRSF1-deficient CD8+ thymocyte maturation. Thus, our data uncovered the previous unknown role of SRSF1 in establishment of CD8+ cell identity.

The possible impact of various Arctic polar vortex regimes for the stratosphere on the Northern Hemisphere extratropics has not been fully understood. Previous study has classified the stratospheric Arctic vortex to six regimes using the k-mean clustering algorithm based on the ERA5 reanalysis. The stability and robustness of the classification is further verified with a much longer model dataset and historical integrations from CESM2-WACCM. Consistent with the reanalysis, we clustered the Arctic stratospheric polar vortex forms into six patterns, named as homogeneously-intensified and -weakened regimes (HI, HW), North America-intensified and -weakened regimes (NAI, HAW), and Eurasia-intensified and -weakened regimes (EUI, EUW). A zonally uniform positive (negative) Northern Annular Mode (NAM) pattern develops during the HI (HW) regime from the stratosphere to troposphere. The NAM-like pattern shifts toward the western hemisphere with the largest negative (positive) anomalous height center shifting to North America during the NAI (NAW) regime. In contrast, the maximum polar anomaly center moves towards polar Eurasia during the EUI (EUW) regime. The HI, NAI, and EUW regimes are accompanied with weakened wave activities, while the HW, NAW, and EUI regimes are preceded by enhanced planetary waves. Accordingly, persistent anomalies of warmth (coldness) exist over midlatitude Eurasia and North America during the HI (HW). Anomalous warmth (coldness) centers exist in northern Eurasia, while anomalous coldness (warmth) centers exist around the Mediterranean Sea during the NAI (NAW) regime. Anomalous warmth (coldness) centers develop in East Asia in the EUI (EUW) periods. The rainfall anomaly distributions also vary with the stratospheric polar vortex regime. The frequency for stratospheric regimes during SSWs and strong vortex events is also assessed and consistent with previous findings.

T cell factor 1 (Tcf1) is known as a critical mediator for natural killer (NK) cell development and terminal maturation. However, its essential targets and precise mechanisms involved in early NK progenitors (NKP) are not well clarified. To investigate the role of Tcf1 in NK cells at distinct developmental phases, we employed three kinds of genetic mouse models, namely, Tcf7fl/flVavCre/+, Tcf7fl/flCD122Cre/+ and Tcf7fl/flNcr1Cre/+ mice, respectively. Similar to Tcf1 germline knockout mice, we found notably diminished cell number and defective development in BM NK cells from all strains. In contrast, Tcf7fl/flNcr1Cre/+ mice exhibited modest defects in splenic NK cells compared with those in the other two strains. By analyzing the published ATAC-seq and ChIP-seq data, we found that Tcf1 directly targeted 110 NK cell-related genes which displayed differential accessibility in the absence of Tcf1. Along with this clue, we further confirmed that a series of essential regulators were expressed aberrantly in distinct BM NK subsets with conditional ablating Tcf1 at NKP stage. Eomes, Ets1, Gata3, Ikzf1, Ikzf2, Nfil3, Runx3, Sh2d1a, Slamf6, Tbx21, Tox, and Zeb2 were downregulated, whereas Spi1 and Gzmb were upregulated in distinct NK subsets due to Tcf1 deficiency. The dysregulation of these genes jointly caused severe defects in NK cells lacking Tcf1. Thus, our study identified essential targets of Tcf1 in NK cells, providing new insights into Tcf1-dependent regulatory programs in step-wise governing NK cell development.

In modern industrial engineered systems, variant working conditions disturb the distributions of machines' operational data, which results in different feature distributions (DFD) problems for fault prognostics. Domain adaptation (DA) have been proved good at dealing DFD problems, and several deep DA-based methods have been also proposed in fault prognostics filed. However, existing methods refer to the DA tasks from one working condition to another, without considerations of transferring between datasets under complex working conditions. The prior distribution of working conditions will influence the distributions of machines' operational data, and few studies take prior distribution of working conditions into consideration of DA for fault prognostics. Thus, in this paper, a working-condition-based deep domain adaptation network (Deep wcDAN) is proposed to overcome the DFD problems caused by variant complex working conditions. In the proposed method, CNNs combines LSTMs with domain adaptive transfer technique to minimize the distribution discrepancy between training and testing datasets. Furthermore, a working-condition-based MMD (wcMMD) is proposed to optimize the DA process based on the prior distribution of each working condition. The performance of proposed model is evaluated and the negative transfer effects have been analyzed based on C-MAPSS datasets. The results show that the proposed method performs better than baseline methods on predicting remaining useful life (RUL) with DFD problems.

The kinase PDK1 is a crucial regulator for immune cell development by connecting PI3K to downstream AKT signaling. However, the roles of PDK1 in CD4+ T cell differentiation, especially in T follicular helper (Tfh) cell, remain obscure. Here we reported PDK1 intrinsically promotes the Tfh cell differentiation and germinal center responses upon acute infection by using conditional knockout mice. PDK1 deficiency in T cells caused severe defects in both early differentiation and late maintenance of Tfh cells. The expression of key Tfh regulators was remarkably downregulated in PDK1-deficient Tfh cells, including Tcf7, Bcl6, Icos, and Cxcr5. Mechanistically, ablation of PDK1 led to impaired phosphorylation of AKT and defective activation of mTORC1, resulting in substantially reduced expression of Hif1α and p-STAT3. Meanwhile, decreased p-AKT also suppresses mTORC2-associated GSK3β activity in PDK1-deficient Tfh cells. These integrated effects contributed to the dramatical reduced expression of TCF1 and ultimately impaired the Tfh cell differentiation.

The excavation damage of deep tunnels is one of the most important factors contributing to the failure of tunnel structures. In order to investigate the influence of tunnel shapes and fissure geometries, the kernel function in the traditional SPH method has been improved, which can realize the brittle fracture characteristics of particles and can be called the Improved Kernel of Smoothed Particle Hydrodynamics (IKSPH-2D). Meanwhile, the random fissure generation method in IKSPH has been put forward. Different tunnel shapes, fissure geometries, and locations are considered during the simulation of tunnel excavation, and results show that (1) the typical “V”-shaped shear damage zones appear after the tunnel excavation, which is consistent with engineering practice. Meanwhile, tunnel excavation also has an “activating” effect on the preexisting fissures. (2) The stability of circular-shaped tunnel is the best, while horseshoe shaped tunnel is worse, and the “U”-shaped tunnel is the worst. (3) Fissures with small and large dip angles have the greatest influence on the stability of tunnel excavation. With the increase of fissure numbers and lengths, the tunnel tends to be instable. (4) The IKSPH method gets free from traditional grids in FEM, which can dynamically reflect the fracture processes of tunnel excavation. Meanwhile, developing 3D IKSPH parallel program will be the future directions.

The predictions of failure zone during the foundation excavations will provide important guidance for the safety constructions of engineering structures. Based on this background, the smoothing kernel function in the traditional SPH method has been improved. The failure mark η is introduced into the program to realize the failure characteristics of particles at meso–scale. The “Killing Particle Method” has also been proposed, which can realize the simulations of complex excavation processes. The whole progressive failure processes of the excavation of a foundation pit are numerically simulated and the results show that (1) the failure zone of the excavated foundation pit without retaining walls appears at the corner and then gradually develops into the deep. However, the failure zone of the excavated foundation pit with retaining walls only develops longitudes along the retaining wall. (2) The stiffness of retaining wall has a great impact on the failure zone of foundation pit excavation. The greater the stiffness of retaining wall, the greater the damage degree. (3) The rationality of the proposed method is verified by the comparisons of the simulation results of the proposed method with the ABAQUS numerical examples and the engineering practices. Future research directions should focus on developing the 3D parallel IKSPH programs. The research results can provide some references for the applications of SPH method into predicting the failure zone of foundation pit excavations and ensuring the safety of engineering constructions.

This study used numerical analysis to carry out a large number of numerical model calculations based on a new semicircular bend (SCB) model. Instead of existing numerical computation methods (J-integral), the M-integral method was used to calculate the mixed mode fracture parameters (KI, KII, and KIII), investigate the influence of the geometry and material parameters on the fracture behavior under mixed mode I/III loading, and predict the fracture path. The results revealed that the limitations in the scope of the mixity parameter Me in the previous studies can be overcome to a certain extent. The range of Me was established under different Poisson ratios and can be used as a reference for actual material testing. The simulation path is in good agreement with the experimentally obtained fracture path, and the proposed method can be used to simulate the fracture path under mixed mode I/III loading.

GA binding protein (GABP) is a ubiquitously expressed transcription factor that regulates the development of multiple cell types, including osteoblast, hematopoietic stem cells, B cells and T cells. However, so little is known about its biological function in the development of central nervous system. In this report, we show that GABP is highly expressed in neural stem/progenitor cells (NSPCs) and down-regulated in neurons, and that GABPβ1 is required for the proper proliferation of NSPCs. Knockdown of GABPα resulted in an elevated expression level of GABPβ1, and GABPβ1 down-regulation significantly decreased the proliferation of NSPCs, whereas GABPβ2 knockdown did not result in any changes in the proliferation of NSPCs. We observed that there was nearly a 21-fold increase of the GABPβ1S mRNA level in GABPβ1L KO NSPCs compared to WT cells, and knocking down of GABPβ1S in GABPβ1L KO NSPCs could further reduce their proliferation potential. We also found that knockdown of GABPβ1 promoted neuronal and astrocytic differentiation of NSPCs. Finally, we identified dozens of downstream target genes of GABPβ1, which are closely associated with the cell proliferation and differentiation. Collectively, our results suggest that both GABPβ1L and GABPβ1S play an essential role in regulating the proper proliferation and differentiation of NSPCs. Keywords: GABP, Neural stem cell, GABPβ1L, GABPβ1S, Cell proliferation, Neurogenesis

Nano-antibodies possess great potential in many applications. However, they are naturally derived from heavy chain-only antibodies (HcAbs), which lack light chains and the CH1 domain, and are only found in camelids and sharks. In this study, we investigated whether the precise genetic removal of the CH1 exon of the γ1 gene enabled the production of a functional heavy chain-only IgG1 in mice. IgG1 heavy chain dimers lacking associated light chains were detected in the sera of the genetically modified mice. However, the genetic modification led to decreased expression of IgG1 but increased expression of other IgG subclasses. The genetically modified mice showed a weaker immune response to specific antigens compared with wild type mice. Using a phage-display approach, antigen-specific, single domain VH antibodies could be screened from the mice but exhibited much weaker antigen binding affinity than the conventional monoclonal antibodies. Although the strategy was only partially successful, this study confirms the feasibility of producing desirable nano-bodies with appropriate genetic modifications in mice.

[This corrects the article DOI: 10.1371/journal.pone.0154238.].

Porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most devastating pathogens in the swine industry worldwide. Due to the lack of robust cell lines and small animal models, the pathogenesis of PRRSV infection and mechanism for protective vaccination are still not yet well understood. To obtain useful cell lines, several groups have attempted to construct different transgenic cell lines with three PRRSV receptors: CD163, CD169, and CD151. The results showed that CD163 is essential for PRRSV entry into target cells and replication, and both CD169 and CD151 play key roles during PRRSV infection. However, their interplay and combined effect remains unclear. In this study, we generated transgenic BHK-21 derived cell lines co-expressing different combinations of the three receptors, which were transfected with CD163 alone, or the combination of CD163 and CD169, or the combination of CD163 and CD151, or the combination of CD163, CD169, and CD151 using the PiggyBac transposon system. Our results showed that the synergistic interaction among the three receptors was important to improve the susceptibility of cells during PRRSV infection. Through a series of comparable analyses, we confirmed that the cell line co-expressing triple receptors sustained viral infection and replication, and was superior to the current cell platform used for the PRRSV study, MARC-145 cells. Moreover, we found that PRRSV infection of the transgenic cell lines could trigger IFN-stimulated gene responses similar to those of porcine alveolar macrophages and MARC-145 cells. In summary, we developed a stable transgenic cell line susceptible to PRRSV, which may not only provide a useful tool for virus propagation, vaccine development, and pathogenesis studies, but also establish the foundation for small animal model development.

Predictive maintenance plays an important role in modern Cyber-Physical Systems (CPSs) and data-driven methods have been a worthwhile direction for Prognostics Health Management (PHM). However, two main challenges have significant influences on the traditional fault diagnostic models: one is that extracting hand-crafted features from multi-dimensional sensors with internal dependencies depends too much on expertise knowledge; the other is that imbalance pervasively exists among faulty and normal samples. As deep learning models have proved to be good methods for automatic feature extraction, the objective of this paper is to study an optimized deep learning model for imbalanced fault diagnosis for CPSs. Thus, this paper proposes a weighted Long Recurrent Convolutional LSTM model with sampling policy (wLRCL-D) to deal with these challenges. The model consists of 2-layer CNNs, 2-layer inner LSTMs and 2-Layer outer LSTMs, with under-sampling policy and weighted cost-sensitive loss function. Experiments are conducted on PHM 2015 challenge datasets, and the results show that wLRCL-D outperforms other baseline methods.