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The gold deposits in the Jiaodong Peninsula constitute the largest gold mineralized province in China. The mineralization shows common characteristics in their tectonic setting, ore-forming fluid and metallogenic system. Sulfidation and fluid immiscibility are two important mechanisms controlling gold precipitation, both of which consume sulfur in the ore-forming fluids. The escape of H2S from the main ore-forming fluids and the decrease of total sulfur concentration not only lead to the efficient precipitation of gold, but also result in the crystallization of reducing minerals such as pyrrhotite and oxidizing minerals such as magnetite. Quartz solubility shows strong dependence on temperature, pressure, and CO2content. The dependence of quartz solubility on pressure is weak at low temperatures, and progressively stronger at higher temperatures. Similarly, the temperature dependence of quartz solubility is relatively low at low pressures, but becomes gradually stronger at high pressures. The results of solubility modeling can constrain the dissolution and reprecipitation behavior of quartz in the ore-forming veins and the formation mechanism of different types of quartz veins. The multi-stage mineralization fluid activity resulted in the complex dissolution structure of quartz in the Jiaodong gold veins. Pyrite in the main metallogenic period in the Jiaodong gold deposits shows complex microstructure characteristics at single crystal scale. The trace elements (mainly the coupling of As- and Au-rich belt) and sulfur isotope composition also display a certain regularity. The As-rich fluids might have formed by the initial pulse of ore-forming fluids through As-rich metasedimentary strata, while the As-Au oscillation zone at the margin of pyrite grains is related to the pressure fluctuation caused by fault activity and the local phase separation of fluids. There is a temporal and spatial evolution of gold fineness in the Jiaodong gold deposits. Water/rock reaction (sulfidation) was the main ore-forming mechanism of early gold mineralization, forming relatively high fineness gold, while significant pressure drop in the shallow part accompanied by fluid phase separation promoted the late gold mineralization, forming low fineness gold. Under cratonic destruction setting, dehydration of the amphibolite and granulite facies metamorphic lower-crust resulted in the formation of Au-CO2-rich ore-forming fluids, which rose along the deep fault and secondary structure, and formed the largescale fault-controlled gold deposits in Jiaodong.

Air pollution fluctuations have been found to strongly depend on the weather dynamics. Here we identify the significant atmospheric processes that affect the local daily variability of air pollution. We develop a multilayered network analysis to detect the interlinks between the 500‐hPa geopotential height and surface air pollution in both China and the United States. We find that Rossby waves significantly affect air pollution fluctuations through the development of cyclone and anticyclone systems and further affect the local stability of the air and the winds. Some of these systems are remote (∼3,000 km) and lead to air pollution 1–2 days later. Thus, the impact of Rossby waves on human life is greater than previously believed. The rapid warming of the Arctic could slow down Rossby waves, thus increasing human health risks. Our method can help to determine the risk assessment of such extreme events and can improve potential predictability. Outdoor air pollution plays an important role in a wide range of environmental and health problems. The impact of weather dynamics (at different pressure levels) on the daily fluctuations of air pollution is still not clear. Here we develop a novel multilayer and multivariable network method to delineate the influence of the upper air dynamics on the temporal variability of surface air pollution. We show that the underlying mechanism of our observed relation between weather and air pollution is the dynamics of planetary Rossby waves that not only cause extreme weather events but also lead to strong fluctuations in air pollution. The developed method is applied on data from China and the United States and can help to improve the prediction of extreme pollution events. Surface pollution variations from China and the United States associated with atmospheric upper air conditions are studied by a network approachThe upper air critical regimes are found to significantly influence the surface air pollutionRossby waves significantly affect air pollution fluctuations through low‐ and high‐pressure systems

In this study, computer simulations are performed on three-dimensional granular systems under shear conditions. The system comprises granular particles that are confined between two rigid plates. The top plate is subjected to a normal force and driven by a shearing velocity. A positive shear-rate dependence of granular friction, known as velocity-strengthening, exists between the granular and shearing plate. To understand the origin of the dependence of frictional sliding, we treat the granular system as a complex network, where granular particles are nodes and normal contact forces are weighted edges used to obtain insight into the interiors of granular matter. Community structures within granular property networks are detected under different shearing velocities in the steady state. Community parameters, such as the size of the largest cluster and average size of clusters, show significant monotonous trends in shearing velocity associated with the shear-rate dependence of granular friction. Then, we apply an instantaneous change in shearing velocity. A dramatic increase in friction is observed with a change in shearing velocity in the non-steady state. The community structures in the non-steady state are different from those in the steady state. Results indicate that the largest cluster is a key factor affecting the friction between the granular and shearing plate.

Herein, percolation phase transitions on a two-dimensional lattice were studied using machine learning techniques. Results reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks (NNs), whereas phase transitions of different universality classes require different NNs. Based on this finding, we proposed the universality class of machine learning for critical phenomena. Furthermore, we investigated and discussed the NNs of different universality classes. Our research contributes to machine learning by relating the NNs with the universality class.

A novel terminal modification agent to endow hyperbranched polyamidoamine (HPAMAM) with thermo‐/pH‐responsive properties is reported. HPAMAM with terminal vinyl groups is first synthesized and then end‐capped by 1‐adamantylamine (ADA). The resulting hyperbranched polymer (HPAMAM‐ADA) shows interesting thermo‐responsive properties in aqueous solution, which have been investigated by UV‐vis spectroscopy, optical microscopy, and 1H NMR spectroscopy. The lower critical solution temperature can be controlled by adjusting the end‐capping ratio of ADA. In addition, HPAMAM‐ADA exhibits a pH‐dependent water solubility. This pH‐responsive behavior is also studied.

This study provided a facile and green method to prepare stable colloid silver nanoparticles in aqueous solution by utilizing the amine-terminated hyperbranched poly(amidoamine) (HPAMAM-NH2) as both stabilizer and reductant. The formation of silver nanoparticles was verified by FTIR, UV−vis, TEM, EDS, and XRD measurements. Monodispersed colloid silver nanoparticles with small particle sizes were obtained, and the average particle size could be effectively controlled from ca. 15 to 4 nm by simply adjusting the molar ratio of N/Ag in feed. The antibacterial activity of the HPAMAM-NH2/Ag nanocomposites was also investigated against Gram-positive and Gram-negative bacteria. They were able to efficiently inhibit the growth and multiplication of several bacteria, including Staphylococcus aureus, Bacillus subtilis, Escherichia coli, and Klebsiella mobilis, and the bacterial inhibition ratio reached up to 95% at a low silver concentration of 2.7 g/mL.

Here we focus on a basic statistical measure of earthquake catalogs that has not been studied before, the asymmetry of interevent time series (e.g., reflecting the tendency to have more aftershocks than spontaneous earthquakes). We define the asymmetry metric as the ratio between the number of positive interevent time increments minus negative increments and the total (positive plus negative) number of increments. Such asymmetry commonly exists in time series data for nonlinear geophysical systems like river flow which decays slowly and increases rapidly. We find that earthquake interevent time series are significantly asymmetric, where the asymmetry function exhibits a significant crossover to weak asymmetry at large lag index. We suggest that the Omori law can be associated with the large asymmetry at short time intervals below the crossover whereas overlapping aftershock sequences and the spontaneous events can be associated with a fast decay of asymmetry above the crossover. We show that the asymmetry is better reproduced by a recently modified Epidemic‐Type Aftershock Sequence (ETAS) model with two triggering processes in comparison to the standard ETAS model which only has one. Earthquakes are often associated with non‐equilibrium and nonlinear underlying processes which can lead to asymmetric behavior in metrics derived from earthquake records. By asymmetry we are referring to “the tendency of more events to occur after a previous one than before the next one” or vice versa. In earthquake sequences the main source of asymmetry is the occurrence of large numbers of aftershocks due to the earthquake triggering. We find here that the distributions of interevent time increments in real seismic catalogs are asymmetric and that the degree of asymmetry is characterized by a scaling function that exhibits a crossover, from a high asymmetry at short times to low asymmetry at long times. We suggest that different earthquake triggering processes are associated with these two distinct regimes of asymmetry. We apply the asymmetry analysis to an earthquake forecasting model–the Epidemic‐Type Aftershock Sequence (ETAS) model and find that the new generalized ETAS model that includes both short‐ and long‐term triggering mechanisms better reproduces the observed asymmetry than the standard ETAS model. We study the asymmetry of earthquake interevent time intervals which exhibits a crossoverWe suggest that the mechanism of the observed asymmetry is related to the earthquake triggering processesThe observed asymmetry is better reproduced by an improved Epidemic‐Type Aftershock Sequence model developed recently We study the asymmetry of earthquake interevent time intervals which exhibits a crossover We suggest that the mechanism of the observed asymmetry is related to the earthquake triggering processes The observed asymmetry is better reproduced by an improved Epidemic‐Type Aftershock Sequence model developed recently

A crude polysaccharide fraction (DAP-1) was prepared from roots of DIPSACUS ASPEROIDES by hot water extraction and EtOH precipitation, and tested for anti-complementary activity, mitogenic activity of lymphocytes, and effects on acid phosphatase and phagocytic activities of macrophages. DAP-1 showed not only anti-complementary activity but also a stimulating effect on the mitogenic activity of lymphocytes. DAP-1 also significantly suppressed the phagocytic activity of macrophages. Although DAP-1 directly stimulated the mitogenecity of lymphocytes, it had no effect on lipopolysaccharide- or concanavalin A-induced mitogenic activity of lymphocytes. Periodate oxidation and pronase digestion suggested that the polysaccharide moiety in DAP-1 contributed to the expression of its anti-complementary and mitogenic activities and that the protein moiety in DAP-1 was responsible for its effect on phagocytosis. DAP-1 gave three polysaccharide fractions (DAP-2, 3, and 4) by fractionation using cetyltrimethylammonium bromide. All the fractions had potent anti-complementary activity, but showed different stimulating or suppressive effects on the proliferation of lymphocytes, phagocytosis, or acid phosphatase activity. Three potent anti-complementary polysaccharides (DAP-4I-1a, DAP-4I-1b, and DAP-4IIa-1) were purified from DAP-4 by anion-exchange chromatography, gel filtration, and HPLC. DAP-4I-1a, I-1b, and IIa-1 consisted of Ara, Rha, Xyl, Gal, Glc and GlcA in a molar ratio of 1.0:0.7:1.0:18.6:22.2: nil; 1.0:0.1:0.3:19.3 : 26.8: nil; and 3.7: trace: 0.6:26.3:5.5 :1.0; respectively. Among the polysaccharides, only DAP-4IIa-1 reacted with ?-glucosyl-Yariv antigen. Methylation analysis indicated that DAP-4I-1a mainly comprised 4-linked Gal and 3-, 4-, and 6-linked Glc, whereas DAP-4IIa-1 consisted mainly of terminal Araf, 3-linked Glc, and 3,6-branched Gal.

A complement activating pectic arabinogalactan (AGIIb-1) has been isolated from roots of Angelica acutiloba Kitagawa, and a neutral arabinogalactan (N-I) unit, which was liberated from a side chain in AGIIb-1 by mild acid hydrolysis, has found to show the most potent complement activating activity among the arabinogalactan side chains of AGIIb-1. In order to clarify the essential carbohydrate side chains in N-I for the activity, neutral arabinogalactan (AF-N-I) unit, which was obtained from exo-α-L-arabinofuranosidase-digested AGIIb-1, was digested with exo-β-d-(1 → 3)-galactanase from Irpex lacteus. The galactanase digestion of the AF-N-I unit completely stopped its reactivity with β-d-glucosyl-Yariv antigen, and significantly reduced its complement activating activity. The digestion products gave high molecular weight fragments (GN-1A and -1B) and intermediate size fragments in addition to β-d-(1 → 6)-galactosyl mono to pentasaccharides as the side chains of the AF-N-I unit. Among the fragments, GN-1A, GN-1B and intermediate size fragments showed relatively potent complement activating activity, suggesting that these side chains in the N-I unit might be responsible for expression of the activity of the N-I unit.

The impact of climate change on extreme weather is one of the most concerning problems. Climate change could cause more frequent and unexpected extreme weather. Still, synchronization features of extreme weather under climate change are not fully understood. Here, we develop a climate network approach to study global synchronization patterns of extreme events based on the 500‐hPa geopotential field. We find that a positive event synchronization (PES) network is associated with the tropical circulations in the tropics; a negative event synchronization network is associated with the large‐scale atmospheric Rossby waves in mid‐latitudes. By studying temporal evolution of the PES network, we find that the synchronization strengths in the tropics are weakening under climate change in relation to the slowing down of tropical circulations. Furthermore, our results show that the strength of synchronization in Africa and the Atlantic Ocean decrease faster than other regions. Climate change could result in the changes of the large‐scale atmospheric and oceanic circulations, which could change the correlations between different regions. Currently, understanding of synchronization features of extreme weather is very limited. During the last two decades, complex network theory has been demonstrated as a useful tool for studying real‐world systems. Here, we perform a climate network‐synchronization approach to study global synchronization patterns based on extreme events of 500‐hpa geopotential height. Different features of extreme event synchronization can be detected by positive‐synchronization and negative‐synchronization networks. Furthermore, we investigate the impacts of climate change on the synchronization patterns from region to region in the tropics. All the regions show a weakening tendency with years, especially in Africa and the Atlantic Ocean. We associate this phenomenon to the weakening of tropical circulations. Showing global synchronization network patterns of extreme 500‐hPa geopotential fieldUncovering two synchronization networks associated with tropical circulations and Rossby waves respectivelyDemonstrating significant weakening synchronization patterns in the topics under climate change Showing global synchronization network patterns of extreme 500‐hPa geopotential field Uncovering two synchronization networks associated with tropical circulations and Rossby waves respectively Demonstrating significant weakening synchronization patterns in the topics under climate change

This study aimed to systematically review neuropsychiatric lupus erythematosus (NPSLE) and establish a simplified diagnostic criterion for NPSLE.

We propose the finite-size scaling of correlation functions in finite systems near their critical points. At a distance rin a d-dimensional finite system of size L, the correlation function can be written as the product of |r|−(d−2+η)and a finite-size scaling function of the variables r/Land tL1/v, where t= (T− Tc)=Tc, ηis the critical exponent of correlation function, and vis the critical exponent of correlation length. The correlation function only has a sigificant directional dependence when |r| is compariable to L. We then confirm this finite-size scaling by calculating the correlation functions of the two-dimensional Ising model and the bond percolation in two-dimensional lattices using Monte Carlo simulations. We can use the finite-size scaling of the correlation function to determine the critical point and the critical exponent η.