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Plasticity theory aims at describing the yield loci and work hardening of a material under general deformation states. Most of its complexity arises from the nontrivial dependence of the yield loci on the complete strain history of a material and its microstructure. This motivated 3 ingenious simplifications that underpinned a century of developments in this field: 1) yield criteria describing yield loci location; 2) associative or nonassociative flow rules defining the direction of plastic flow; and 3) effective stress–strain laws consistent with the plastic work equivalence principle. However, 2 key complications arise from these simplifications. First, finding equations that describe these 3 assumptions for materials with complex microstructures is not trivial. Second, yield surface evolution needs to be traced iteratively, i.e., through a return mapping algorithm. Here, we show that these assumptions are not needed in the context of sequence learning when using recurrent neural networks, diverting the above-mentioned complications. This work offers an alternative to currently established plasticity formulations by providing the foundations for finding history- and microstructure-dependent constitutive models through deep learning.

During winter 2013, extremely high concentrations (i.e., 4–20 times higher than the World Health Organization guideline) of PM2.5 (particulate matter with an aerodynamic diameter < 2.5 μm) mass concentrations (24 h samples) were found in four major cities in China including Xi'an, Beijing, Shanghai and Guangzhou. Statistical analysis of a combined data set from elemental carbon (EC), organic carbon (OC), 14C and biomass-burning marker measurements using Latin hypercube sampling allowed a quantitative source apportionment of carbonaceous aerosols. Based on 14C measurements of EC fractions (six samples each city), we found that fossil emissions from coal combustion and vehicle exhaust dominated EC with a mean contribution of 75 ± 8% across all sites. The remaining 25 ± 8% was exclusively attributed to biomass combustion, consistent with the measurements of biomass-burning markers such as anhydrosugars (levoglucosan and mannosan) and water-soluble potassium (K+). With a combination of the levoglucosan-to-mannosan and levoglucosan-to-K+ ratios, the major source of biomass burning in winter in China is suggested to be combustion of crop residues. The contribution of fossil sources to OC was highest in Beijing (58 ± 5%) and decreased from Shanghai (49 ± 2%) to Xi'an (38 ± 3%) and Guangzhou (35 ± 7%). Generally, a larger fraction of fossil OC was from secondary origins than primary sources for all sites. Non-fossil sources accounted on average for 55 ± 10 and 48 ± 9% of OC and total carbon (TC), respectively, which suggests that non-fossil emissions were very important contributors of urban carbonaceous aerosols in China. The primary biomass-burning emissions accounted for 40 ± 8, 48 ± 18, 53 ± 4 and 65 ± 26% of non-fossil OC for Xi'an, Beijing, Shanghai and Guangzhou, respectively. Other non-fossil sources excluding primary biomass burning were mainly attributed to formation of secondary organic carbon (SOC) from non-fossil precursors such as biomass-burning emissions. For each site, we also compared samples from moderately to heavily polluted days according to particulate matter mass. Despite a significant increase of the absolute mass concentrations of primary emissions from both fossil and non-fossil sources during the heavily polluted events, their relative contribution to TC was even decreased, whereas the portion of SOC was consistently increased at all sites. This observation indicates that SOC was an important fraction in the increment of carbonaceous aerosols during the haze episode in China.

An intensive investigation of carbonaceous PM2.5 and TSP (total suspended particles) from Pudong (China) was conducted as part of the MIRAGE-Shanghai (Megacities Impact on Regional and Global Environment) experiment in 2009. Data for organic and elemental carbon (OC and EC), organic species, including C17 to C40 n-alkanes and 17 polycyclic aromatic hydrocarbons (PAHs), and stable carbon isotopes OC (δ13COC) and EC (δ13CEC) were used to evaluate the aerosols' temporal variations and identify presumptive sources. High OC/EC ratios indicated a large fraction of secondary organic aerosol (SOA); high char/soot ratios indicated stronger contributions to EC from motor vehicles and coal combustion than biomass burning. Diagnostic ratios of PAHs indicated that much of the SOA was produced via coal combustion. Isotope abundances (δ13COC = −24.5 ± 0.8‰ and δ13CEC = −25.1 ± 0.6‰) indicated that fossil fuels were the most important source for carbonaceous PM2.5 (particulate matter less than 2.5 micrometers in diameter), with lesser impacts from biomass burning and natural sources. An EC tracer system and isotope mass balance calculations showed that the relative contributions to total carbon from coal combustion, motor vehicle exhaust, and SOA were 41%, 21%, and 31%; other primary sources such as marine, soil and biogenic emissions contributed 7%. Combined analyses of OC and EC, n-alkanes and PAHs, and stable carbon isotopes provide a new way to apportion the sources of carbonaceous particles.

A large change in albedo has a significant effect on glacier ablation. Atmospheric aerosols – e.g. black carbon (BC) and dust – can reduce the albedo of glaciers and thus contribute to their melting. In this study, two main themes were explored: (1) the decrease in albedo of the Zhadang glacier on Mt. Nyainqentanglha between 2001 and 2012, as observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Terra satellite, and the correlation of this albedo with mass balance; and (2) the concentrations of BC and dust in the glacier measured during 2012, and the associated impacts of these impurities on albedo and radiative forcings (RF). The average albedo of the Zhadang glacier from the MODIS increased with the altitude and fluctuated but had a decreasing trend (−0.003 a−1) during the period 2001–2012, with the highest (0.722) in 2003 and the lowest (0.597) in 2009 and 2010. The mass balance of the glacier has a positively significant correlation with its surface albedo derived from MODIS. Snow samples were collected on the Zhadang glacier to measure the BC and dust in the summer of 2012. The impacts of BC and dust on albedo reduction in different melting conditions were identified with the SNow ICe Aerosol Radiative (SNICAR) model initiated by in situ observation data. The sensitivity analysis showed that BC was a major factor in albedo reduction when the glacier was covered by newly fallen snow. Nevertheless, the contribution of dust to albedo reduction can reach as high as 56%, much exceeding that of BC (28%), when the glacier experiences strong surficial melting and its surface is almost bare ice. The average RF caused by dust could increase from 1.1 to 8.6 W m−2, exceeding the RF caused by BC after snow was deposited and surface melting occurred in the Zhadang glacier. This implies that it may be dust that primarily dominates the melting of some glaciers in the inner Tibetan Plateau during melting seasons, rather than BC.

Obesity is traditionally viewed to be beneficial to bone health because of well-established positive effect of mechanical loading conferred by body weight on bone formation, despite being a risk factor for many other chronic health disorders. Although body mass has a positive effect on bone formation, whether the mass derived from an obesity condition or excessive fat accumulation is beneficial to bone remains controversial. The underline pathophysiological relationship between obesity and bone is complex and continues to be an active research area. Recent data from epidemiological and animal studies strongly support that fat accumulation is detrimental to bone mass. To our knowledge, obesity possibly affects bone metabolism through several mechanisms. Because both adipocytes and osteoblasts are derived from a common multipotential mesenchymal stem cell, obesity may increase adipocyte differentiation and fat accumulation while decrease osteoblast differentiation and bone formation. Obesity is associated with chronic inflammation. The increased circulating and tissue proinflammatory cytokines in obesity may promote osteoclast activity and bone resorption through modifying the receptor activator of NF-κB (RANK)/RANK ligand/osteoprotegerin pathway. Furthermore, the excessive secretion of leptin and/or decreased production of adiponectin by adipocytes in obesity may either directly affect bone formation or indirectly affect bone resorption through up-regulated proinflammatory cytokine production. Finally, high-fat intake may interfere with intestinal calcium absorption and therefore decrease calcium availability for bone formation. Unraveling the relationship between fat and bone metabolism at molecular level may help us to develop therapeutic agents to prevent or treat both obesity and osteoporosis. Obesity, defined as having a body mass index ≥ 30 kg/m 2 , is a condition in which excessive body fat accumulates to a degree that adversely affects health [ 1 ]. The rates of obesity rates have doubled since 1980 [ 2 ] and as of 2007, 33% of men and 35% of women in the US are obese [ 3 ]. Obesity is positively associated to many chronic disorders such as hypertension, dyslipidemia, type 2 diabetes mellitus, coronary heart disease, and certain cancers [ 4 – 6 ]. It is estimated that the direct medical cost associated with obesity in the United States is ~$100 billion per year [ 7 ]. Bone mass and strength decrease during adulthood, especially in women after menopause [ 8 ]. These changes can culminate in osteoporosis, a disease characterized by low bone mass and microarchitectural deterioration resulting in increased bone fracture risk. It is estimated that there are about 10 million Americans over the age of 50 who have osteoporosis while another 34 million people are at risk of developing the disease [ 9 ]. In 2001, osteoporosis alone accounted for some $17 billion in direct annual healthcare expenditure. Several lines of evidence suggest that obesity and bone metabolism are interrelated. First, both osteoblasts (bone forming cells) and adipocytes (energy storing cells) are derived from a common mesenchymal stem cell [ 10 ] and agents inhibiting adipogenesis stimulated osteoblast differentiation [ 11 – 13 ] and vice versa, those inhibiting osteoblastogenesis increased adipogenesis [ 14 ]. Second, decreased bone marrow osteoblastogenesis with aging is usually accompanied with increased marrow adipogenesis [ 15 , 16 ]. Third, chronic use of steroid hormone, such as glucocorticoid, results in obesity accompanied by rapid bone loss [ 17 , 18 ]. Fourth, both obesity and osteoporosis are associated with elevated oxidative stress and increased production of proinflammatory cytokines [ 19 , 20 ]. At present, the mechanisms for the effects of obesity on bone metabolism are not well defined and will be the focus of this review.

Mesenchymal stem cells (MSCs), a non-hematopoietic stem cell population first discovered in bone marrow, are multipotent cells capable of differentiating into mature cells of several mesenchymal tissues, such as fat and bone. As common progenitor cells of adipocytes and osteoblasts, MSCs are delicately balanced for their differentiation commitment. Numerous in vitro investigations have demonstrated that fat-induction factors inhibit osteogenesis, and, conversely, bone-induction factors hinder adipogenesis. In fact, a variety of external cues contribute to the delicate balance of adipo-osteogenic differentiation of MSCs, including chemical, physical, and biological factors. These factors trigger different signaling pathways and activate various transcription factors that guide MSCs to commit to either lineage. The dysregulation of the adipo-osteogenic balance has been linked to several pathophysiologic processes, such as aging, obesity, osteopenia, osteopetrosis, and osteoporosis. Thus, the regulation of MSC differentiation has increasingly attracted great attention in recent years. Here, we review external factors and their signaling processes dictating the reciprocal regulation between adipocytes and osteoblasts during MSC differentiation and the ultimate control of the adipo-osteogenic balance.

Although significant advances have recently been made in the diagnosis and treatment of cervical carcinoma, the long-term survival rate for advanced cervical cancer remains low. Therefore, an urgent need exists to both uncover the molecular mechanisms and identify potential therapeutic targets for the treatment of cervical cancer. MicroRNAs (miRNAs) have important roles in cancer progression and could be used as either potential therapeutic agents or targets. miR-506 is a component of an X chromosome-linked miRNA cluster. The biological functions of miR-506 have not been well established. In this study, we found that miR-506 expression was downregulated in approximately 80% of the cervical cancer samples examined and inversely correlated with the expression of Ki-67, a marker of cell proliferation. Gain-of-function and loss-of-function studies in human cervical cancer, Caski and SiHa cells, demonstrated that miR-506 acts as a tumor suppressor by inhibiting cervical cancer growth in vitro and in vivo . Further studies showed that miR-506 induced cell cycle arrest at the G1/S transition, and enhanced apoptosis and chemosensitivity of cervical cancer cell. We subsequently identified Gli3, a hedgehog pathway transcription factor, as a direct target of miR-506 in cervical cancer. Furthermore, Gli3 silencing recapitulated the effects of miR-506, and reintroduction of Gli3 abrogated miR-506-induced cell growth arrest and apoptosis. Taken together, we conclude that miR-506 exerts its anti-proliferative function by directly targeting Gli3. This newly identified miR-506/Gli3 axis provides further insight into the pathogenesis of cervical cancer and indicates a potential novel therapeutic agent for the treatment of cervical cancer.

Composition and size distribution of atmospheric aerosols from Xi'an city (~400 m, altitude) in inland China during the spring of 2009 including a massive dust event on 24 April were measured and compared with a parallel measurement at the summit (2060 m, altitude) of Mt. Hua, an alpine site nearby Xi'an. EC (elemental carbon), OC (organic carbon) and major ions in the city were 2–22 times higher than those on the mountaintop during the whole sampling period. Compared to that in the non-dust period a sharp increase in OC was observed at both sites during the dust period, which was mainly caused by an input of biogenic organics from the Gobi desert. However, adsorption/heterogeneous reaction of gaseous organics with dust was another important source of OC in the urban, contributing 22% of OC in the dust event. In contrast to the mountain atmosphere where fine particles were less acidic when dust was present, the urban fine particles became more acidic in the dust event than in the non-dust event, mainly due to enhanced heterogeneous formation of nitrate and diluted NH3. Cl− and NO3− in the urban air during the dust event significantly shifted toward coarse particles. Such redistributions were further pronounced on the mountaintop when dust was present, resulting in both ions almost entirely staying in coarse particles. On the contrary, no significant spatial difference in size distribution of SO42− was found between the urban ground surface and the mountain atmosphere, which dominated in the fine mode (<2.1 μm) during the nonevent and comparably distributed in the fine (<2.1 μm) and coarse (>2.1 μm) modes during the dust event.

The environmental conditions of Earth, including the climate, are determined by physical, chemical, biological, and human interactions that transform and transport materials and energy. This is the \"Earth system\": a highly complex entity characterized by multiple nonlinear responses and thresholds, with linkages between disparate components. One important part of this system is the iron cycle, in which iron-containing soil dust is transported from land through the atmosphere to the oceans, affecting ocean biogeochemistry and hence having feedback effects on climate and dust production. Here we review the key components of this cycle, identifying critical uncertainties and priorities for future research.