We study the first order phase transition of Euler-Heisenberg-AdS black hole based on free energy landscape. By solving the Fokker-Planck equation, we research the probability distribution of the ...system states. The small (large) black hole can have the chance to switch to the large (small) black hole due to the change of the temperature T or Euler-Heisenberg parameter a. A higher (lower) T corresponds to a larger probability for a large (small) black hole. The coexistent small and large black hole states can be acquired for some conditions. For 0<a≤327Q2, the small-large black hole phase transition can be acquired with a small a. The probability of small (large) black holes will decrease to zero for a large a. For a small a, a higher peak of the first passage time can be acquired for higher (lower) T or smaller (larger) a with the initial small (large) black hole state. For a<0, a smaller (larger) a corresponds to a larger probability for a large (small) black hole. A higher peak of the first passage time can also be obtained for higher (lower) T or smaller (larger) a with initial small (large) black hole state.
Global Sensitivity Analysis (GSA) is key to assisting appraisal of the behavior of hydrological systems through model diagnosis considering multiple sources of uncertainty. Uncertainty sources ...typically comprise incomplete knowledge in (a) conceptual and mathematical formulation of models and (b) parameters embedded in the models. In this context, there is the need for detailed investigations aimed at a robust quantification of the importance of model and parameter uncertainties in a rigorous multi‐model context. This study aims at evaluating and comparing two modern multi‐model GSA methodologies. These are the first GSA approaches embedding both model and parameter uncertainty sources and encompass the variance‐based framework based on Sobol indices (as derived by Dai & Ye, 2015, https://doi.org/10.1016/j.jhydrol.2015.06.034) and the moment‐based approach upon which the formulation of the multi‐model AMA indices (as derived by Dell'Oca et al., 2020, https://doi.org/10.1029/2019wr025754) is based. We provide an assessment of various aspects of sensitivity upon considering a joint analysis of these two approaches in a multi‐model context. Our work relies on well‐established scenarios that comprise (a) a synthetic setting related to reactive transport across a groundwater system and (b) an experimentally‐based study considering heavy metal sorption onto a soil. Our study documents that the joint use of these GSA approaches can provide different while complementary information to assess mutual consistency of approaches and to enrich the information content provided by GSA under model and parameter uncertainty. While being related to groundwater settings, our results can be considered as reference for future GSA studies coping with model and parameter uncertainty.
Key Points
Two modern multi‐model Global Sensitivity Analysis (GSA) approaches are evaluated and compared upon considering two groundwater‐related scenarios
The results of the two multi‐model GSA methods can be markedly different due to their differing theoretical bases
Joint use of the two GSA methods enhances one's ability for model diagnosis and assessment of system behaviors
•The LM is investigated from the energy condition and the crack propagation condition.•An energy release criterion is introduced.•The growth of small cracks is investigated using the R-curve ...approach.•The LM gives a critical condition of crack growth for various notches.•The prediction by the LM may be conservative in some cases.
To consider a mechanistic explanation of the mean stress based line method (called LM) for estimating the notch fatigue limit, the limit values predicted by the LM are investigated from both the energy condition required to create fractured surfaces and the crack propagation condition of the linear elastic fracture mechanism.
Based on the energy condition, an energy release criterion (ERC), was introduced to estimate the notch fatigue limit of Δσnp for crack propagation. It is found that Δσn|ERC,1.58L≅Δσn|LM,2L holds for all the investigated notches. Here, Δσn|ERC,1.58L denotes the predicted value by the ERC with the intrinsic crack length lc=1.58L, and Δσn|LM,2L denotes the predicted value by the LM with the characteristic distance dLM=2L (L is the El Haddad’s material characteristic length). The validity of the LM in predicting the fatigue limit of Δσnp based on stress condition was demonstrated by the correspondence relation between the average stress and the energy release in the relevant zone.
Also, the growth of small cracks near the notch root is investigated using the R-curve approach. It is found that, as a universal criterion applicable to various notch root radiuses ρ, Δσn|LM,2L gives a critical condition for crack to overcome the typical resistance force represented by the simplified Kitagawa-Takahashi diagram, the values of which is denoted by ΔKth(l)|Kitagawa here. However, to each specified notch root radius ρ,Δσn|LM,2L may be a conservative solution, and theoretically Δσnp⩽Δσn|LM,2L holds. The reason is that: (1) most of the curves of crack driving force at a nominal stress of Δσn|LM,2L are above the resistance curve of ΔKth(l)|Kitagawa; (2) the actual resistance curve of the material is generally below the resistance curve of ΔKth(l)|Kitagawa.
Researches were reported that respiratory diseases can lead to male infertility; however, it is unclear whether there is a relationship between pulmonary fibrosis (PF) and male infertility. This ...study examined the influence of PF on sperm quality and its mechanisms. The key signalling pathway of male infertility caused by PF was predicted based on bioinformatics research. After modelling, we evaluated semen quality. Real‐time quantitative polymerase chain reaction and Western blotting were used to measure the protein and mRNA expression levels of phosphatidylinositol 3‐kinase (PI3K), phosphorylation‐protein kinase B (p‐Akt) and B‐cell lymphoma 2 (Bcl2) in rat testicular cells. Compared with group A (48.77 ± 4.67; 59.77 ± 4.79), the sperm concentration and total sperm viability of group B (8.44 ± 1.71; 15.39 ± 3.48) showed a downward trend (p < 0.05). Western blotting showed that the protein expressions of PI3K, p‐Akt and Bcl2 in the testes of group B (0.30 ± 0.06; 0.27 ± 0.05; 0.15 ± 0.03) was significantly lower than those of group A (0.71 ± 0.07; 0.72 ± 0.06; 0.50 ± 0.06) (p < 0.05). The hypoxic environment induced by PF can inhibit the expression of PI3K, p‐Akt and Bcl2 protein and eventually cause dysfunctional spermatogenesis.
•Sensitivity analysis is performed for sorptive and nonreactive solute macrodispersivity.•The influence of heterogeneity scale on sensitive parameters is discussed.•Different sampling schemes for MC ...analysis are evaluated.
Lagrangian-based transport models provide effective ways of understanding mass transport processes within aquifer systems. The models provide a direct relationship between sparse data on sedimentary architecture (e.g., facies proportions and mean lengths) and physical and geochemical sediment properties (e.g., hydraulic conductivity (K) and sorption distribution coefficient (Kd)) to transport observables such as dispersion. Data sparsity leads to parameter uncertainty, which in turn makes model prediction uncertain. This study identifies the key uncertain inputs for both non-reactive and sorptive solute dispersivity through a global sensitivity analysis. Estimates of the individual and correlation contributions of input parameters to model output are provided. Data from two sites with different scales of heterogeneities are used to evaluate the sensitive parameters of non-reactive dispersivity at different scales. The results show that sorptive solute dispersivity is most sensitive to in-facies mean Kd, followed by Kd variance, while non-reactive plume dispersivity is most sensitive to in-facies mean K, followed by the volume proportions and mean lengths of facies types. When the heterogeneity integral scale increases to 102-103m, hydraulic gradient becomes a non-negligible factor controlling the non-reactive solutes transport. The convergence of the sensitivity indices and the effect of different sampling methods on the results are also evaluated in this study. The results show that the number of input parameters and the complexity of the model determine the sampling size to achieve the ranking convergence of the sensitive indices. Sobol sequence sampling scheme outperforms in terms of convergence rate and accuracy over the Monte Carlo and Latin Hypercube sampling schemes. The results of this study will improve our understanding of the complex model system, and also provide guidance for further field investigation and data collection.
With the development of blockchain technologies, many Ponzi schemes disguise themselves under the veil of smart contracts. The Ponzi scheme contracts cause serious financial losses, which has a bad ...effect on the blockchain. Existing Ponzi scheme contract detection studies have mainly focused on extracting hand-crafted features and training a machine learning classifier to detect Ponzi scheme contracts. However, the hand-crafted features cannot capture the structural and semantic feature of the source code. Therefore, in this study, we propose a Ponzi scheme contract detection method called MTCformer (Multi-channel Text Convolutional Neural Networks and Transofrmer). In order to reserve the structural information of the source code, the MTCformer first converts the Abstract Syntax Tree (AST) of the smart contract code to the specially formatted code token sequence via the Structure-Based Traversal (SBT) method. Then, the MTCformer uses multi-channel TextCNN (Text Convolutional Neural Networks) to learn local structural and semantic features from the code token sequence. Next, the MTCformer employs the Transformer to capture the long-range dependencies of code tokens. Finally, a fully connected neural network with a cost-sensitive loss function in the MTCformer is used for classification. The experimental results show that the MTCformer is superior to the state-of-the-art methods and its variants in Ponzi scheme contract detection.
Stem cell transplantation has been generally considered as promising therapeutics in preserving or recovering functions of lost, damaged, or aging tissues. Transplantation of primordial germ cells ...(PGCs) or oogonia stem cells (OSCs) can reconstitute ovarian functions that yet sustain for only short period of time, limiting potential application of stem cells in preservation of fertility and endocrine function. Here, we show that mTOR inhibition by INK128 extends the follicular and endocrine functions of the reconstituted ovaries in aging and premature aging mice following transplantation of PGCs/OSCs. Follicular development and endocrine functions of the reconstituted ovaries by transplanting PGCs into kidney capsule of the recipient mice were maintained by INK128 treatment for more than 12 weeks, in contrast to the controls for only about 4 weeks without receiving the mTOR inhibitors. Comparatively, rapamycin also can prolong the ovarian functions but for limited time. Furthermore, our data reveal that INK128 promotes mitochondrial function in addition to its known function in suppression of immune response and inflammation. Taken together, germline stem cell transplantation in combination with mTOR inhibition by INK128 improves and extends the reconstituted ovarian and endocrine functions in reproductive aging and premature aging mice.
In this manuscript, Heng et al. report that mTOR inhibition by INK128 extends functions of ovarian reconstituted from transplantation of primordial germ cells/oogonia stem cells using various mouse models such as young mouse model, natural aging, premature aging mouse by knockout of telomerase, and immunodeficient mice. Moreover, INK128 greatly elevates mitochondria functions and suppresses inflammation and immunoresponses in the reconstituted ovaries.
For a complex hydrologic system with multiple processes and process interactions, global sensitivity analysis is often used to identify important or influential parameters for model development and ...improvement. The identification is complicated by process model uncertainty, when a system process can be represented by multiple process models. This study develops a new total‐effect process sensitivity index to identify influential processes under model uncertainty. This is done by extending Sobol's total‐effect parameter sensitivity index for one system model to total‐effect process sensitivity index for multiple system models to account for uncertainty in process models and model parameters. The total‐effect process sensitivity index includes not only the first‐order process sensitivity index for measuring the importance of individual processes but also higher‐order indices that account for process interactions. The total‐effect process sensitivity index can identify an influential process that itself and its interactions with other processes influence a model output. The total‐effect process sensitivity index is applied to two numerical examples: (a) Sobol's G*‐functions with analytical solutions of first‐order and total‐effect process sensitivity indices, and (b) groundwater flow models with interactions between recharge, geology, and snowmelt processes. The second evaluation shows that, due to second‐order and higher‐order process interactions, the first‐order and total‐effect process sensitivity indices give different process ranking. It is thus necessary to estimate both first‐order and total‐effect process sensitivity indices to appreciate the difference between the first‐order impact of a process alone and the overall total‐effect impact of the process itself and its interactions with other processes on a model output.
Plain Language Summary
When studying a complex hydrologic system, it is necessary to identify non‐influential processes of the system so that limited resources are not spent on improving our understanding of these processes. On the other hand, it is important to identify influential processes of the system so that limited resources can be efficiently spent on better understanding the influential processes. Identification of the influential and non‐influential processes is difficult when a process can be represented by several plausible process models because it is not always clear which process model to choose. To resolve this issue, we develop a new total‐effect process sensitivity index that considers all the plausible process models without choosing one model and discarding other models. This is done by integrating the model averaging method with the Sobol's total‐effect parameter sensitivity index. We use two numerical examples to verify computer codes and to demonstrate how to use the index to identify influential and non‐influential processes. Applied to groundwater flow modeling, our new index demonstrates that accounting for interactions between recharge, geology, and snowmelt processes gives a ranking of process influence that is different from the ranking of process importance based on the first‐order process sensitivity index.
Key Points
A new total‐effect process sensitivity index is derived to account for process interactions under process model and parameter uncertainty
The total‐effect process sensitivity index has a first‐order term for process importance and higher‐order terms for process interactions
Accounting for process interactions allows for identifying influential system processes and/or screening non‐influential system processes
Abstract
Nitric oxide (NO) is a multifunctional gaseous molecule that plays important roles in mammalian reproductive functions, including follicular growth and development. Although our previous ...study showed that NO mediated 3,5,3′-triiodothyronine and follicle-stimulating hormone–induced granulosa cell development via upregulation of glucose transporter protein (GLUT)1 and GLUT4 in granulosa cells, little is known about the precise mechanisms regulating ovarian development via glucose. The objective of the present study was to determine the cellular and molecular mechanism by which NO regulates GLUT expression and glucose uptake in granulosa cells. Our results indicated that NO increased GLUT1/GLUT4 expression and translocation in cells, as well as glucose uptake. These changes were accompanied by upregulation of cyclic guanosine monophosphate (cGMP) level and cGMP-dependent protein kinase (PKG)-I protein content. The results of small interfering RNA (siRNA) analysis showed that knockdown of PKG-I significantly attenuated gene expression, translocation, and glucose uptake. Moreover, the PKG-I inhibitor also blocked the above processes. Furthermore, NO induced cyclic adenosine monophosphate response element binding factor (CREB) phosphorylation, and CREB siRNA attenuated NO-induced GLUT expression, translocation, and glucose uptake in granulosa cells. These findings suggest that NO increases cellular glucose uptake via GLUT upregulation and translocation, which are mediated through the activation of the cGMP/PKG pathway. Meanwhile, the activated CREB is also involved in the regulation. These findings indicate that NO has an important influence on the glucose uptake of granulosa cells.
NO increases cellular glucose uptake via GLUT upregulation and translocation, which are mediated through the activation of the cGMP/PKG pathway.
Abstract
Cytochrome P450 lanosterol 14α-demethylase (CYP51) is a key enzyme in sterol and steroid biosynthesis that is involved in folliculogenesis and oocyte maturation, which is regulated by ...follicle-stimulating hormone (FSH), as a key reproductive hormone during follicular development. Thyroid hormone (TH) is also important for normal reproductive function. Although 3,5,3′-triiodothyronine (T3) enhances FSH-induced preantral follicle growth, whether and how TH combines with FSH to regulate CYP51 expression during the preantral to early antral transition stage is unclear. The objective of this study was to determine the cellular and molecular mechanisms by which T3 and FSH regulate CYP51 expression and steroid biosynthesis during preantral follicle growth. Our results indicated that CYP51 expression was upregulated in granulosa cells by FSH, and this response was enhanced by T3. Moreover, knockdown CYP51 decreased cell viability. Meanwhile, gene knockdown also blocked T3 and FSH-induced estradiol (E2) and progesterone (P4) synthesis. These changes were accompanied by upregulation of phospho-GATA-4 content. Results of small interfering RNA analysis showed that knockdown of GATA-4 significantly diminished CYP51 gene expression as well as E2/P4 levels. Furthermore, thyroid hormone receptor β was necessary to the activation of phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt), which was required for the regulation of CYP51 expression; activated GATA-4 was also involved these processes. Our data demonstrate that T3 and FSH cotreatment potentiates cellular development and steroid biosynthesis via CYP51 upregulation, which is mediated through the activation of the PI3K/Akt pathway. Meanwhile, activated GATA-4 is also involved in this regulatory system. These findings suggest that CYP51 is a mediator of T3 and FSH-induced follicular development.
T3 and FSH regulate CYP51 expression in mice ovary.
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