Noise-induced stochastic switching of microcargoes transport in artificial microtubule.

Synchronization plays an important role in propelling microrobots, especially for those driven by an external magnetic field. Here, we substantially contribute to the understanding of a novel out-of-sync phenomenon called "slip-out", which has been recently discovered in experiments of an artificial microtubule (AMT). In a deterministic situation, we interpret and quantitatively characterize the switching in such a system between the stick and slip modes, whose different combinations over time define four long-term states. The stick-and-slip state is the most typical "slip-out" state with periodic switching, caused by both the phase lock between the microrod and the magnetic field, and the time-dependent magnetic moment. We then illustrate that thermal noise leads to stochastic switching by stimulating the phase difference across a specific threshold randomly. Finally, we reproduce the average velocity simulatively, which is highly consistent with real experiments. Importantly, the nearly permanent slip state is probed by our analysis of long-term states rather than observing real experiments. The investigation supports the design and operational strategies of AMT and other microrobots driven by magnetic fields.

Enhanced fault diagnosis via stochastic resonance in a piecewise asymmetric bistable system.

Weak fault signals are often overwhelmed by strong noise or interference. The key issue in fault diagnosis is to accurately extract useful fault characteristics. Stochastic resonance is an important signal processing method that utilizes noise to enhance weak signals. In this paper, to address the issues of output saturation and imperfect optimization of potential structure models in classical bistable stochastic resonance (CBSR), we propose a piecewise asymmetric stochastic resonance system. A two-state model is used to theoretically derive the output signal-to-noise ratio (SNR) of the bistable system under harmonic excitations, which is compared with the SNR of CBSR to demonstrate the superiority of the method. The method is then applied to fault data. The results indicate that it can achieve a higher output SNR and higher spectral peaks at fault characteristic frequencies/orders, regardless of whether the system operates under fixed or time-varying speed conditions. This study provides new ideas and theoretical guidance for improving the accuracy and reliability of fault diagnosis technology.

The occurrence mechanisms of extreme events in a class of nonlinear Duffing-type systems under random excitations.

The occurrence mechanisms of extreme events under random disturbances are relatively complex and not yet clear. In this paper, we take a class of generalized Duffing-type systems as an example to reveal three mechanisms for the occurrence of extreme events. First, it is intuitive that a very large excitation can generate extreme events, such as the Lévy noise. In such a case, extreme excitation works, while it does not require much about the systems. Second, when a system has a bifurcation structure, if the difference of the branches at the bifurcation point is large, a randomly varying bifurcation parameter can lead to extreme events. Finally, when a system has rare attractors, a random impulse excitation, such as Poisson white noise, is able to cause the system to escape from one general attractor into rare attractors. Such a kind of special regime switching behavior can lead to extreme events. These results reveal the possible mechanisms of extreme events in a class of nonlinear Duffing-type systems and provide guidance for further prediction and avoidance of extreme events.

Effects of land use and land cover change on soil organic carbon storage in the Hexi regions, Northwest China.

Soil organic carbon (SOC) storage in arid inland regions is significantly affected by land use and land cover change (LUCC) associated with climate change and agricultural activities. A systematic evaluation to the LUCC effects on SOC storage could enable us to better manage soil carbon pools in arid inland regions. Here, we evaluated the effects of LUCC on SOC storage in the Hexi Regions based on high-resolution SOC and LUCC maps derived from Landsat imagery and digital soil mapping using machine learning algorithm and environmental covariates. The results showed that SOC generally increased from northwest to southeast over the Hexi Regions with an average stock of 7.15 kg C m-2 at a soil depth of 100 cm and a total storage of 2783.05 Tg C. The SOC stock and storage in the Qilian Mountains (mountains) was about 3.90 and 4.55 times higher than that in the Hexi Corridor (plains), respectively. It was estimated that LUCC over the past four decades caused a net increase of 23.41 and 18.19 Tg C in total SOC storage for the Qilian Mountains and Hexi Corridor, respectively. Specifically, the development in grasslands quality as well as the land-use category conversion from the bare land to grassland mainly contributed to the increase in SOC storage of the Qilian Mountains, where the LUCC was mainly driven by climate change. By contrast, the SOC storage change in the Hexi Corridor was mainly associated with the conversion from sandy land and low-cover grassland to cropland as well as sandy land to grassland, being mainly affected by intense cropland expansion and desertification control. Our results highlighted the importance of climate change and cropland expansion in enhancing SOC storage of the Qilian Mountains and Hexi corridor, respectively.

Characterizing stochastic resonance in a triple cavity.

Many biological systems possess confined structures, which produce novel influences on the dynamics. Here, stochastic resonance (SR) in a triple cavity that consists of three units and is subjected to noise, periodic force and vertical constance force is studied, by calculating the spectral amplification η numerically. Meanwhile, SR in the given triple cavity and differences from other structures are explored. First, it is found that the cavity parameters can eliminate or regulate the maximum of η and the noise intensity that induces this maximum. Second, compared to a double cavity with similar maximum/minimum widths and distances between two maximum widths as the triple cavity, η in the triple one shows a larger maximum. Next, the conversion of the natural boundary in the pure potential to the reflection boundary in the triple cavity will create the necessity of a vertical force to induce SR and lead to a decrease in the maximum of η. In addition, η monotonically decreases with the increase of the vertical force and frequency of the periodic force, while it presents several trends when increasing the periodic force's amplitude for different noise intensities. Finally, our studies are extended to the impact of fractional Gaussian noise excitations. This article is part of the theme issue 'Vibrational and stochastic resonance in driven nonlinear systems (part 2)'.

Solving Fokker-Planck equation using deep learning.

The probability density function of stochastic differential equations is governed by the Fokker-Planck (FP) equation. A novel machine learning method is developed to solve the general FP equations based on deep neural networks. The proposed algorithm does not require any interpolation and coordinate transformation, which is different from the traditional numerical methods. The main novelty of this paper is that penalty factors are introduced to overcome the local optimization for the deep learning approach, and the corresponding setting rules are given. Meanwhile, we consider a normalization condition as a supervision condition to effectively avoid that the trial solution is zero. Several numerical examples are presented to illustrate performances of the proposed algorithm, including one-, two-, and three-dimensional systems. All the results suggest that the deep learning is quite feasible and effective to calculate the FP equation. Furthermore, influences of the number of hidden layers, the penalty factors, and the optimization algorithm are discussed in detail. These results indicate that the performances of the machine learning technique can be improved through constructing the neural networks appropriately.

The influences of correlated spatially random perturbations on first passage time in a linear-cubic potential.

The influences of correlated spatially random perturbations (SRPs) on the first passage problem are studied in a linear-cubic potential with a time-changing external force driven by a Gaussian white noise. First, the escape rate in the absence of SRPs is obtained by Kramers' theory. For the random potential case, we simplify the escape rate by multiplying the escape rate of smooth potentials with a specific coefficient, which is to evaluate the influences of randomness. Based on this assumption, the escape rates are derived in two scenarios, i.e., small/large correlation lengths. Consequently, the first passage time distributions (FPTDs) are generated for both smooth and random potential cases. We find that the position of the maximal FPTD has a very good agreement with that of numerical results, which verifies the validity of the proposed approximations. Besides, with increasing the correlation length, the FPTD shifts to the left gradually and tends to the smooth potential case. Second, we investigate the most probable passage time (MPPT) and mean first passage time (MFPT), which decrease with increasing the correlation length. We also find that the variation ranges of both MPPT and MFPT increase nonlinearly with increasing the intensity. Besides, we briefly give constraint conditions to guarantee the validity of our approximations. This work enables us to approximately evaluate the influences of the correlation length of SRPs in detail, which was always ignored previously.

Predicting noise-induced critical transitions in bistable systems.

Critical transitions from one dynamical state to another contrasting state are observed in many complex systems. To understand the effects of stochastic events on critical transitions and to predict their occurrence as a control parameter varies are of utmost importance in various applications. In this paper, we carry out a prediction of noise-induced critical transitions using a bistable model as a prototype class of real systems. We find that the largest Lyapunov exponent and the Shannon entropy can act as general early warning indicators to predict noise-induced critical transitions, even for an earlier transition due to strong fluctuations. Furthermore, the concept of the parameter dependent basin of the unsafe regime is introduced via incorporating a suitable probabilistic notion. We find that this is an efficient tool to approximately quantify the range of the control parameter where noise-induced critical transitions may occur. Our method may serve as a paradigm to understand and predict noise-induced critical transitions in multistable systems or complex networks and even may be extended to a broad range of disciplines to address the issues of resilience.

Transports in a rough ratchet induced by Lévy noises.

We study the transport of a particle subjected to a Lévy noise in a rough ratchet potential which is constructed by superimposing a fast oscillating trigonometric function on a common ratchet background. Due to the superposition of roughness, the transport process exhibits significantly different properties under the excitation of Lévy noises compared to smooth cases. The influence of the roughness on the directional motion is explored by calculating the mean velocities with respect to the Lévy stable index α and the spatial asymmetry parameter q of the ratchet. Variations in the splitting probability have been analyzed to illustrate how roughness affects the transport. In addition, we have examined the influences of roughness on the mean first passage time to know when it accelerates or slows down the first passage process. We find that the roughness can lead to a fast reduction of the absolute value of the mean velocity for small α, however the influence is small for large α. We have illustrated that the ladder-like roughness on the potential wall increases the possibility for particles to cross the gentle side of the ratchet, which results in an increase of the splitting probability to right for the right-skewed ratchet potential. Although the roughness increases the corresponding probability, it does not accelerate the mean first passage process to the right adjacent well. Our results show that the influences of roughness on the mean first passage time are sensitive to the combination of q and α. Hence, the proper q and α can speed up the passage process, otherwise it will slow down it.

Anomalous diffusion, non-Gaussianity, nonergodicity, and confinement in stochastic-scaled Brownian motion with diffusing diffusivity dynamics.

Scaled Brownian motions (SBMs) with power-law time-dependent diffusivity have been used to describe various types of anomalous diffusion yet Gaussian observed in granular gases kinetics, turbulent diffusion, and molecules mobility in cells, to name a few. However, some of these systems may exhibit non-Gaussian behavior which can be described by SBM with diffusing diffusivity (DD-SBM). Here, we numerically investigate both free and confined DD-SBM models characterized by fixed or stochastic scaling exponent of time-dependent diffusivity. The effects of distributed scaling exponent, random diffusivity, and confinement are considered. Different regimes of ultraslow diffusion, subdiffusion, normal diffusion, and superdiffusion are observed. In addition, weak ergodic and non-Gaussian behaviors are also detected. These results provide insights into diffusion in time-fluctuating diffusivity landscapes with potential applications to time-dependent temperature systems spreading in heterogeneous environments.

The role of land use change in affecting ecosystem services and the ecological security pattern of the Hexi Regions, Northwest China.

The land use and land cover change (LUCC) associated with climate change and human activities is supposed to exert a significant effect on ecosystem functions in arid inland regions. However, the role of LUCC in shaping the spatio-temporal patterns of ecosystem services and ecological security remain unclear, especially under different future LUCC scenarios. Here, we evaluated dynamic changes of ecosystem services and ecological security pattern (ESP) in the Hexi Regions based on LUCC and other environment variables by integrating morphological spatial pattern analysis (MSPA), entropy weight method and circuit theory. Our result showed that the LUCC was generally stable from 1980 to 2050. Compare to 2020, the land conversion under natural growth (NG), ecological protection (EP) and urban development (UD) scenarios in 2050 has changed by 10.30 %, 10.10 %, and 10.31 %, respectively. The forest, medium-cover grassland and water increased in the EP scenario, and construction land and cropland greatly expanded in the other two scenarios. Ecosystem services grew larger in the EP scenario by 2050 in comparison with the NG and UD scenarios. The ESP in the Hexi Regions has obvious spatial differences during 1980-2050. The larger ecological sources and less resistance corridors were mainly distributed in the central and eastern of the Hexi Regions with high ecosystem services. Conversely, fragmented ecological sources and larger resistance corridors were mostly located in the western regions blocked by sandy land, bare land or mountains. Compared to 2020, the area of ecological sources and pinch points under the EP scenario in 2050 increased by 4.10 × 103 km2 and 0.31 × 103 km2, respectively. The number of ecological corridors reduced while the length and resistance increased apart from the EP scenario. Our results highlighted the importance of ecological protection in shaping the LUCC, which further enhances the integrity of ecosystem and ecological security.

CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms.

Linking cis-regulatory sequences to target genes has been a long-standing challenge. In this study, we introduce CREaTor, an attention-based deep neural network designed to model cis-regulatory patterns for genomic elements up to 2 Mb from target genes. Coupled with a training strategy that predicts gene expression from flanking candidate cis-regulatory elements (cCREs), CREaTor can model cell type-specific cis-regulatory patterns in new cell types without prior knowledge of cCRE-gene interactions or additional training. The zero-shot modeling capability, combined with the use of only RNA-seq and ChIP-seq data, allows for the ready generalization of CREaTor to a broad range of cell types.

Synchronization in the network-frustrated coupled oscillator with attractive-repulsive frequencies.

We investigate the synchronization behavior of a generalized useful mode of the emergent collective behavior in sets of interacting dynamic elements. The network-frustrated Kuramoto model with interaction-repulsion frequency characteristics is presented, and its structural features are crucial to capture the correct physical behavior, such as describing steady states and phase transitions. Quantifying the effect of small-world phenomena on the global synchronization of the given network, the impact of the random phase-shift and their mutual behavior shows particular challenges. In this paper, we derive the phase-locked states and identify the significant synchronization transition points analytically with exact boundary conditions for the correlated and uncorrelated degree-frequency distributions and their full stability analysis. We find that a supercritical to subcritical bifurcation transition occurs depending on the synchronic transition points, characterized by the power scale of the network for the correlated degree frequency and the largest eigenvalue of the network in the uncorrelated case. Furthermore, our frustrated degree-frequency distribution brings us to the classical Kuramoto model with all-to-all coupling, with ß=1/2 for the correlated case and λ_{N}=1 for the uncorrelated distribution. In addition, the interplay between the network topology and the frustration forms a powerful alliance, where they control the synchronization ability of the generalized model without affecting its stability.

[Expression Level of SOCS3 in Acute Lymphoblastic Leukemia Cells Affects the Cytotoxicity of NK Cells].

OBJECTIVE: To detect the expression level of suppressors of cytokine signaling 3 （SOCS3） in acute lymphoblastic leukemia (ALL), and to observe the effect of over-expresson of SOCS3 in Jurkat cells on the cytotoxicity of NK cells. METHODS: The expression levels of SOCS3 mRNA in peripheral blood mononuclear cells of 20 children with ALL and 20 healthy children (normal control group) were detected by RT-PCR. The peripheral blood NK cells from healthy subjects were selected by immunomagnetic technique, and the purity was detected by flow cytometry. SOCS3 was overexpressed in Jurkat cells infected with lentivirus vector, and SOCS3 mRNA expression was detected by RT-PCR after lentivirus infection. The NK cells were co-cultured with the infected Jurkat, and LDH release method was used to detect the cytotoxicity of NK cells on the infected Jurkat cells. The concentrations of TNF-α and IFN-γ were determined by ELISA. The expression of NKG2D ligands MICA and MICB on the surface of Jurkat cells were detected by flow cytometry. Western blot was used to detect the effect of SOCS3 overexpression on STAT3 phosphorylation in Jurkat cells. RESULTS: Compared with the control group, the mRNA expression of SOCS3 in the peripheral blood mononucleated cells of ALL children was significantly decreased. The purity of NK cells isolated by flow cytometry could reach more than 70%. The expression of SOCS3 mRNA in Jurkat cells increased significantly after lentivirus infection. Overexpression of SOCS3 in Jurkat cells significantly promoted the killing ability of NK cells and up-regulated the secretion of TNF-α and IFN-γ from NK cells. The results of flow cytometry showed that the expression of NKG2D ligands MICA and MICB on Jurkat cells increased significantly after SOCS3 overexpression. Western blot results showed that overexpression of SOCS3 significantly reduced the phosphorylation level of STAT3 protein in Jurkat cells. CONCLUSION: SOCS3 mRNA expression was significantly decreased in ALL patients, and overexpression of SOCS3 may up-regulate the expression of MICA and MICB of NKG2D ligands on Jurkat cell surface through negative regulation of JAK/STAT signaling pathway, thereby promoting the cytotoxic function of NK cells.

[The effects of vagus nerve stimulation on hippocampal neuro-inflammatory and α7nAChR expression in rats with intractable epilepsy].

Objective: To investigate the effects of vagus nerve stimulation(VNS) on hippocampal neuro-inflammatory and α7 nicotinic acetylcholine receptor (α7nAChR) expression in rats with intractable epilepsy (IE). Methods: Eighty adult male SD rats (SPF) were randomly divided into control group, model group, VNS group and MLA+VNS group. There were respectively 20 rats in the control group and MLA+VNS group, and because of model failure and animal death, 15 rats and 14 rats in the model group and VNS group were left respectively . Except the control group, the IE model was established in other groups. Only the vagus nerve was isolated in the control group without electrical stimulation; the model group did not take any intervention measures; the VNS group was treated for 4 weeks with VNS after the model was successful; the MLA(3.4 µg/µl, 5 µl) was given to the lateral ventricle in the MLA+VNS group, and then VNS for 4 weeks. Seizure frequency and duration in each group were observed and recorded. And then the rats were decapitated, the hippocampus were quickly separated and 10% tissue homogenate was prepared. The homogenate was centrifuged and the supernatant was extracted. The activities of AChE and ChAT in the supernatant were measured by spectrophotometry, and the levels of TNF-ɑ, IL-6 and IL-1ß were detected by ELISA. The expression of α7nAChR in rat hippocampals was detected by Western blot. The expression of α7nAChR on microglias in rat hippocampals was assesed by double-labeled immunofluorescence. Results: ①After VNS for 4 weeks, the frequency and duration of seizures in rats were decreased significantly, which were lower than those of the model group (P<0.01); After treated with MLA +VNS, the frequency and duration of seizures in rats were also reduced significantly, which were lower than those of the model group, but higher than those of the VNS group (P<0.01).②Compared with the control group, the expression of ChAT in the hippocampus of rats in the model group was decreased significantly and the expression of AChE was increased significantly (P<0.01); Compared with the model group, the expressions of ChAT in the hippocampus of rats in the VNS group and MLA+VNS group were increased significantly and the expressions of AChE were decreased significantly (P<0.01); Compared with the VNS group, in the hippocampus of rats in the MLA+VNS group, the expressions of ChAT and AChE had no significant changes (P>0.05). ③Compared with the control group, the expressions of TNF-ɑ, IL-6 and IL-1ß in the hippocampus of rats in the model group were increased significantly (P<0.01). Compared with the model group, the expressions of TNF-ɑ, IL-6 and IL-1ß in the hippocampus of rats in the VNS group were decreased significantly (P<0.01). Compared with the VNS group, the expressions of TNF-ɑ, IL-6 and IL-1ß in the hippocampus of rats in the MLA+VNS group were increased significantly(P<0.01). ④Compared with the control group, the expression of α7nAChR in hippocampus and microglia of rats in the model group was decreased significantly(P<0.01); Compared with the model group, the expression of α7nAChR in hippocampus and microglia of rats in the VNS group was up-regulated significantly (P<0.01); Compared with the VNS group, coexpression of α7nAChR on microglia wasreduced significantly in the MLA+VNS group (P<0.01). Conclusion: VNS has obvious therapeutic effect on IE rats, and its mechanism may be related to activating hippocampal microglia cholinergic anti-inflammatory pathway directly and inhibiting hippocampal neuro-inflammatory response.

Heterogeneous diffusion processes and nonergodicity with Gaussian colored noise in layered diffusivity landscapes.

Heterogeneous diffusion processes (HDPs) with space-dependent diffusion coefficients D(x) are found in a number of real-world systems, such as for diffusion of macromolecules or submicron tracers in biological cells. Here, we examine HDPs in quenched-disorder systems with Gaussian colored noise (GCN) characterized by a diffusion coefficient with a power-law dependence on the particle position and with a spatially random scaling exponent. Typically, D(x) is considered to be centerd at the origin and the entire x axis is characterized by a single scaling exponent α. In this work we consider a spatially random scenario: in periodic intervals ("layers") in space D(x) is centerd to the midpoint of each interval. In each interval the scaling exponent α is randomly chosen from a Gaussian distribution. The effects of the variation of the scaling exponents, the periodicity of the domains ("layer thickness") of the diffusion coefficient in this stratified system, and the correlation time of the GCN are analyzed numerically in detail. We discuss the regimes of superdiffusion, subdiffusion, and normal diffusion realisable in this system. We observe and quantify the domains where nonergodic and non-Gaussian behaviors emerge in this system. Our results provide new insights into the understanding of weak ergodicity breaking for HDPs driven by colored noise, with potential applications in quenched layered systems, typical model systems for diffusion in biological cells and tissues, as well as for diffusion in geophysical systems.

First-passage-time distribution in a moving parabolic potential with spatial roughness.

In this paper, we investigate the first-passage-time distribution (FPTD) within a time-dependent parabolic potential in the presence of roughness with two methods: the Kramers theory and a nonsingular integral equation. By spatially averaging, the rough potential is equivalent to the combination of an effective smooth potential and an effective diffusion coefficient. Based on the Kramers theory, we first obtain Kramers approximations (KAs) of FPTD for both smooth and rough potentials. As expected, KA is valid only for high barriers and small external forces, and generally applicable for high barriers in rough potentials. To overcome the shortcoming of KA, a probability asymptotic approximation (PAA) based on an integral equation is proposed, which uses the transient probability density function (PDF) of the natural boundary conditions instead of the absorbing boundary conditions. We find that PAA fits very well even for large external forces. This enables us to analytically solve the FPTD for large external forces and low barriers as a strong extension to KA. In addition, we show that in the presence of a rough potential, the PAA of FPTD is in good agreement with numerical simulations for low barrier potentials. The PAA makes it possible to investigate the first-passage problem with ultrafast varying potentials and short exiting time. Thus, KA and PAA are complementary in determining the FPTD both for various barriers and external forces. Finally, the mean first-passage time (MFPT) is studied, which illustrates that the PAA of MFPT is effective almost in the whole range of external forces, while the KA of MFPT is valid only for small external forces.

[Characteristics of Stable Isotopes and Analysis of Water Vapor Sources of Precipitation at the Northern Slope of the Qilian Mountains].

This study is based on precipitation samples from eight sites at the northern slope of the Qilian Mountains, combined with meteorological factors over the same period. Precipitation isotope characteristics, influence factors and the vapor sources of precipitation were analyzed, and the results show that:① The stable isotopes of precipitation in the study area show obvious seasonal changes, which are characterized by enrichment in the summer half-year and depletion in the winter half-year. The spatial precipitation δ18O value shows a significant downward trend with increasing altitude, and the altitude effect of the annual precipitation δ18O is -0.19‰/100 m, respectively;② At all stations, the slope and intercept of local meteoric water lines show an increasing trend from low altitude to high altitude. The high-altitude mountains above 2000 m are affected by local water vapor recirculation;③ The temperature effect is more significant and the temperature effect of δ18O is 0.64‰, and there is only a weak precipitation effect in summer;④ The results indicate that sub-cloud evaporation has a great influence on the δ18O of precipitation; the average raindrop evaporation rate of δ18O is 23%, 11%, 12%, and 16%,and the δ18O composition has been enriched by 46%, 27%, 38%, and 32% in May, June, July, and August from cloud base to ground, respectively.⑤ Under the condition of continuous rainfall in summer, the vapor sources of precipitation mainly come from the west and are affected by local evaporation of water vapor. The study enhances knowledge of isotopic evolution of precipitation and provides a basis for further study of isotopic hydrology in arid regions.

[Space-Time Characteristics and Environmental Significance of the Stable Isotopes in Precipitation in the Gulang River Basin].

Based on the precipitation samples and meteorological data simultaneously collected during individual precipitation events at the Gulang (2085 m a.s.l.) and Anyuan stations (2700 m a.s.l.) in Gulang, this article analyzes the temporal variation and local meteroic water lines and discusses the relationship between precipitation stable isotopes and temperature and precipitation and relative humidity. The results show that:① Gulang and Anyuan have higher δ18O values in summer and autumn and lower δ18O values in spring and winter, respectively; ② The vaule of δ18O decreases with increasing altitude, while the value of the d-excess increases, reflecting the gradual depletion of stable isotopes of precipitation when the air mass is rising along the slope; ③ The slope and intercept of the local meteroic water lines deviate from that of the global meteroic water lines, showing that they may also be affected by local water vapor recirculation, except for the dry environment and strong evaporation effect; and ④ The temperature effect of Gulang in the low-altitude area is more significant than that of the Anyuan station and the Gulang River Basin does not show a precipitation effect. It has been proven that precipitation is not the fundamental factor determining the δ18O of the precipitation in arid areas. The results of this study are helpful to further understand the water circulation mechanism in the Gulang River Basin.

Climate background, relative rate, and runoff effect of multiphase water transformation in Qilian Mountains, the third pole region.

Multiphase water transformation has great effects on alpine hydrology, but these effects remain unclear in the third pole region. Taking the Qilian Mountains as an example, the climate background and relative rates of multiphase water transformation were analyzed, and the runoff effect was evaluated based on long-term field observations. There are three climatic aspects driving multiphase water transformation, including lengthening ablation period, accelerative warming after 1990, and larger warming in the cryosphere belt than in the vegetation belt. The accelerative multiphase water transformation was quantified by three facts: the glacier area retreat rate accelerated by 50% after 1990, the percentage of snowfall in precipitation decreased by 7% after 1990, and the contribution from recycling moisture to precipitation increased by 60% from 1961-1990 to 1991-2016. Under the multiphase water transformation, the outlet runoff for three inland rivers increased by 5 × 108 m3/10 a after 1990. This runoff increase was concentrated mainly in the ablation period. For the seasonal runoff pattern, maximum runoff lagged maximum precipitation by one month under increasing glacier snow meltwater and thickening permafrost active layer. Meltwater from the cryosphere is a crucial runoff component in the Qilian Mountains. At present, these multiphase water transformations are accelerating, along with the yearly runoff increase, which will obviously have a profound impact on water resources management and flood control in the third pole region.