Deep quantum neural networks on a superconducting processor.

Deep learning and quantum computing have achieved dramatic progresses in recent years. The interplay between these two fast-growing fields gives rise to a new research frontier of quantum machine learning. In this work, we report an experimental demonstration of training deep quantum neural networks via the backpropagation algorithm with a six-qubit programmable superconducting processor. We experimentally perform the forward process of the backpropagation algorithm and classically simulate the backward process. In particular, we show that three-layer deep quantum neural networks can be trained efficiently to learn two-qubit quantum channels with a mean fidelity up to 96.0% and the ground state energy of molecular hydrogen with an accuracy up to 93.3% compared to the theoretical value. In addition, six-layer deep quantum neural networks can be trained in a similar fashion to achieve a mean fidelity up to 94.8% for learning single-qubit quantum channels. Our experimental results indicate that the number of coherent qubits required to maintain does not scale with the depth of the deep quantum neural network, thus providing a valuable guide for quantum machine learning applications with both near-term and future quantum devices.

Size-fractionated nonpolar organic compounds of traffic aerosol emissions in a highway tunnel.

Size-fractionated aerosol samples (PM0.25, PM0.25-1, PM1-2.5, and PM2.5-10) were collected in a highway tunnel in Shanghai, China. The concentrations of nonpolar organic compounds (NPOCs), i.e., n-alkanes, polycyclic aromatic hydrocarbons (PAHs) and hopanes in the aerosol samples at the tunnel inlet and outlet, emission factors (EFs) of individual NPOCs in PM10, and EFs of size-fractionated individual NPOCs were analyzed comprehensively. NPOC concentrations in this tunnel were lower than the earlier tunnel results, which might be attributed to the tunnel configuration effect on the pollution dilution along the tunnel, in addition to the improvement of engine technology and fuel quality during past decades. n-Alkane homologs for C14-C35 exhibited a smooth hump-like distribution pattern with the most abundance at C22 and 1-2 carbon number shifts of Cmax in comparison to those in other tunnels due to different fleet and fuel compositions. The most abundant PAHs from diesel (e.g., Nap, Phe, Flu and Pyr) and gasoline (e.g., BghiF, BbkF, BeP, DBA and BghiP) vehicle emissions presented concentration increases of 1.8-5.8 times from the tunnel inlet to outlet. The individual n-alkane and PAH distributions exhibited obvious size dependence, while it was expected that the relative abundances and homolog distributions of hopanes were very similar for different size stages. Several diagnostic ratios, e.g., fossil/plant n-alkanes and LMW/HMW PAHs, were evidently size dependent, indicating different sources of size-fractionated n-alkanes and PAHs.

CUDC-907 enhances TRAIL-induced apoptosis through upregulation of DR5 in breast cancer cells.

CUDC-907 is a novel dual-acting inhibitor of phosphoinositide 3-kinase (PI3K) and histone deacetylase (HDAC). In this study, we aimed to explore the anticancer effects of CUDC-907 on human breast cancer cells. Our results showed that CUDC-907 effectively inhibited breast cancer cell proliferation. Flow cytometry analysis revealed that CUDC-907 induced cell cycle arrest and apoptosis in breast cancer cells. The combined treatment of CUDC-907 and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) resulted in a marked increase in apoptosis and cleavage of caspase-8, -9 and poly (ADP-ribose) polymerase (PARP) in breast cancer cells. CUDC-907 enhanced expressions of death receptor 5 (DR5), reduced the levels of anti-apoptotic molecules XIAP, Bcl-2 and Bcl-xL. Knockdown of DR5 abrogated apoptosis induced by the combination of CUDC-907 and TRAIL in breast cancer cells. CUDC-907 increased the phosphorylation of JNK and p38 MAPK. JNK inhibitor pretreatment attenuated CUDC-907-induced upregulation of DR5. In summary, CUDC-907 shows potent cytotoxicity against breast cancer cells and facilitates TRAIL-mediated apoptosis through DR5 upregulation. The combination of CUDC-907 and TRAIL may be a promising therapeutic approach in the treatment of breast cancer.

Identification of Fungal Communities Associated with the Biodeterioration of Waterlogged Archeological Wood in a Han Dynasty Tomb in China.

The Mausoleum of the Dingtao King (termed 'M2') is a large-scale huangchang ticou tomb that dates to the Western Han Dynasty (206 B.C.-25 A.D.). It is the highest-ranking Han Dynasty tomb discovered to date. However, biodeterioration on the surface of the tomb M2 is causing severe damage to its wooden materials. The aim of the present study was to give insight into the fungal communities colonized the wooden tomb. For this purpose, seven samples were collected from different sections of the tomb M2 which exhibited obvious biodeterioration in the form of white spots. Microbial structures associated with the white spots were observed with scanning electron microscopy. Fungal community structures were assessed for seven samples via a combination of high-throughput sequencing and culture-dependent techniques. Sequencing analyses identified 114 total genera that belonged to five fungal phyla. Hypochnicium was the most abundant genus across all samples and accounted for 98.61-99.45% of the total community composition. Further, Hypochnicium sp. and Mortierella sp. cultures were successfully isolated from the tomb samples, and were distinguished as Hypochnicium sp. WY-DT1 and Mortierella sp. NK-DT1, respectively. Cultivation-dependent experiments indicated that the dominant member, Hypochnicium sp. WY- DT1, could grow at low temperatures and significantly degraded cellulose and lignin. Thus, our results taken together suggest that this fungal strain must be regarded as a serious threat to the preservation of the wooden tomb M2. The results reported here are useful for informing future contamination mitigation efforts for the tomb M2 as well as other similar cultural artifacts.

[Damage to ancient mural paintings and petroglyphs caused by Pseudonocardia sp. - A review].

The historical relics exposed to the natural environment during the long-term were vulnerable to microbial invasion. According to some new studies, microorganism of Pseudonocardia may is one of the main groups on the surface of mural paintings and petroglyphs, causing damage to the paints. Based on recent research progress, we reviewed the phenomenon according to the relationship between the ancient paintings and the growth conditions of Pseudonocardia, which could provide a new theory basis for the protection of cultural relics especially mural paintings and petroglyphs.

Microbial abundance and community composition influence production performance in a low-temperature petroleum reservoir.

Enhanced oil recovery using indigenous microorganisms has been successfully applied in the petroleum industry, but the role of microorganisms remains poorly understood. Here, we investigated the relationship between microbial population dynamics and oil production performance during a water flooding process coupled with nutrient injection in a low-temperature petroleum reservoir. Samples were collected monthly over a two-year period. The microbial composition of samples was determined using 16S rRNA gene pyrosequencing and real-time quantitative polymerase chain reaction analyses. Our results indicated that the microbial community structure in each production well microhabitat was dramatically altered during flooding with eutrophic water. As well as an increase in the density of microorganisms, biosurfactant producers, such as Pseudomonas, Alcaligenes, Rhodococcus, and Rhizobium, were detected in abundance. Furthermore, the density of these microorganisms was closely related to the incremental oil production. Oil emulsification and changes in the fluid-production profile were also observed. In addition, we found that microbial community structure was strongly correlated with environmental factors, such as water content and total nitrogen. These results suggest that injected nutrients increase the abundance of microorganisms, particularly biosurfactant producers. These bacteria and their metabolic products subsequently emulsify oil and alter fluid-production profiles to enhance oil recovery.