Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the development of scientific data repositories, as well as data mining and machine learning tools to investigate the vast materials space. The goal of using these tools is to establish a deeper understanding of the relations between materials properties and activity, selectivity and stability – the important figures of merit in catalysis. Based on these insights, catalyst design principles can be established, which hopefully lead us to discover highly efficient catalysts to solve pressing issues for a sustainable future and the synthesis of highly functional materials, chemicals and pharmaceuticals. The inherent complexity of catalytic reactions quests for machine learning methods to efficiently navigate through the high‐dimensional hyper‐surfaces in structure optimization problems to determine relevant chemical structures and transition states. In this review, we show how cutting edge data infrastructures and machine learning methods are being used to address problems in computational heterogeneous catalysis.

BackgroundOxaliplatin, a platinum-based chemotherapeutic agent, causes an unusual acute peripheral neuropathy. Oxaliplatin-induced acute peripheral neuropathy appears in almost all patients rapidly after infusion, and is triggered or exacerbated by cold, while its mechanisms are poorly understood. In this study, the involvement of thermosensitive transient receptor potential channels (TRPA1, TRPM8 and TRPV1) in oxaliplatin-induced acute hypersensitivity was investigated in mice.ResultsA single intraperitoneal administration of oxaliplatin (1–10 mg/kg) induced cold but not mechanical hypersensitivity within 2 h in a dose-dependent manner. Infusion of the oxaliplatin metabolite, oxalate (1.7 mg/kg), also induced acute cold hypersensitivity, while another platinum-based chemotherapeutic agent, cisplatin (5 mg/kg), or the non-platinum-containing chemotherapeutic agent, paclitaxel (6 mg/kg) failed to induce mechanical or cold hypersensitivity. The oxaliplatin-induced acute cold hypersensitivity was abolished by the TRPA1 antagonist HC-030031 (100 mg/kg) and by TRPA1 deficiency. The nocifensive behaviors evoked by intraplantar injections of allyl-isothiocyanate (AITC; TRPA1 agonist) were significantly enhanced in mice treated for 2 h with oxaliplatin (1–10 mg/kg) in a dose-dependent manner, while capsaicin (TRPV1 agonist)-evoked nocifensive behaviors were not affected. Menthol (TRPM8/TRPA1 agonist)-evoked nocifensive-like behaviors were also enhanced by oxaliplatin pretreatment, which were inhibited by TRPA1 deficiency. Similarly, oxalate enhanced, but neither cisplatin nor paclitaxel affected AITC-evoked nocifensive behaviors. Pretreatment of cultured mouse dorsal root ganglia (DRG) neurons with oxaliplatin (30–300 μM) for 1, 2, or 4 h significantly increased the number of AITC-sensitive neurons in a concentration-dependent manner whereas there was no change in the number of menthol- or capsaicin-sensitive neurons.ConclusionsTaken together, these results suggest that a brief treatment with oxaliplatin or its metabolite oxalate is sufficient to enhance the responsiveness of TRPA1 but not that of TRPM8 and TRPV1 expressed by DRG neurons, which may contribute to the characteristic acute peripheral neuropathy induced by oxaliplatin.

A new monthly global drought severity index (DSI) dataset developed from satellite-observed time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE) is presented. The GRACE-DSI record spans from 2002 to 2014 and will be extended with the ongoing GRACE and scheduled GRACE Follow-On missions. The GRACE-DSI captures major global drought events during the past decade and shows overall favorable spatiotemporal agreement with other commonly used drought metrics, including the Palmer drought severity index (PDSI) and the standardized precipitation evapotranspiration index (SPEI). The assets of the GRACE-DSI are 1) that it is based solely on satellite gravimetric observations and thus provides globally consistent drought monitoring, particularly where sparse ground observations (especially precipitation) constrain the use of traditional model-based monitoring methods; 2) that it has a large footprint (~350 km), so it is suitable for assessing regional- and global-scale drought; and 3) that it is sensitive to the overall terrestrial water storage component of the hydrologic cycle and therefore complements existing drought monitoring datasets by providing information about groundwater storage changes, which affect soil moisture recharge and drought recovery. In Australia, it is demonstrated that combining GRACE-DSI with other satellite environmental datasets improves the characterization of the 2000s “Millennium Drought” at shallow surface and subsurface soil layers. Contrasting vegetation greenness response to surface and underground water supply changes between western and eastern Australia is found, which might indicate that these regions have different relative plant rooting depths.

The early rift sedimentation history of the South China Sea is still not well understood due to restricted borehole coverage of the Paleogene strata and lack of reliable stratigraphic dating. We use detrital zircon U‐Pb geochronology to explore the source‐to‐sink characteristics of syn‐rift sequences in the northern South China Sea. The results reveal significant intrabasinal provenances in addition to the well‐perceived terrigenous supply from the north. The Dongsha Uplift is considered to account for the dominance of the Early Cretaceous zircons in the Eocene samples. The Lower Oligocene sediments in the Qiongdongnan Basin could have been sourced from Hainan Island and local uplifts, but their distinction cannot be confirmed by the U‐Pb age spectra. Contemporary sediments in the northern Pearl River Mouth Basin were most likely transported from southeastern South China with well‐rounded zircon grains showing U‐Pb age similarity to those from the northeastern tributaries of the Pearl River. By contrast, intrabasinal sources from the west and east are suggested to have contributed the infill of the southern part of the Pearl River Mouth Basin based on generally euhedral zircon shapes. These sedimentary source patterns appear to change very little in the Oligocene northern South China Sea. However, the newly detected Neoproterozoic zircons in the Upper Oligocene sediments from borehole L21 tend to indicate a southern source. The episodic and diachronic nature of rifting and erosion processes in the early South China Sea is the cause of complex patterns in the Paleogene provenance history.

Drought monitoring is important for characterizing the timing, extent, and severity of drought for effective mitigation and water management. Presented here is a novel satellite-based drought severity index (DSI) for regional monitoring derived using time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE). The GRACE-DSI enables drought feature comparison across regions and periods, it is unaffected by uncertainties associated with soil water balance models and meteorological forcing data, and it incorporates water storage changes from human impacts including groundwater withdrawals that modify land surface processes and impact water management. Here, the underlying algorithm is described, and the GRACE-DSI performance in the continental United States during 2002–14 is evaluated. It is found that the GRACE-DSI captures documented regional drought events and shows favorable spatial and temporal agreement with the monthly Palmer Drought Severity Index (PDSI) and the U.S. Drought Monitor (USDM). The GRACE-DSI also correlates well with a satellite-based normalized difference vegetation index (NDVI), indicating sensitivity to plant-available water supply changes affecting vegetation growth. Because the GRACE-DSI captures changes in total terrestrial water storage, it complements more traditional drought monitoring tools such as the PDSI by providing information about deeper water storage changes that affect soil moisture recharge and drought recovery. The GRACE-DSI shows potential for globally consistent and effective drought monitoring, particularly where sparse ground observations (especially precipitation) limit the use of traditional drought monitoring methods.

Single-atom catalysts (SACs) with magnetic elements as the active center have been widely exploited for efficient electrochemical conversions. Understanding the catalytic role of spin, and thus modulating the spin density of a single-atom center, is of profound fundamental interest and technological impact. Here, we synthesized ferromagnetic single Co atom catalysts on TaS2 monolayers (Co1/TaS2) as a model system to explore the spin–activity correlation for the oxygen evolution reaction (OER). A single Co atom adsorbed at the hollow site (CoHS) with spin-polarized electronic states serves as the active site for OER, whose spin density can be regulated by its neighboring single Co site via tuning the Co loading. Both experimental and theoretical results reveal the spin density-dependent OER activity that an optimal spin density of CoHS can be achieved with a neighboring hetero-single CoTa site (substitution of Ta by Co) for a superior OER performance, in contrast to a homo-single CoHS site, which creates an excessive spin density over vicinal CoHS. An optimized spin density of CoHS results in an optimal binding energy of oxygen species for the OER. Establishing the spin–activity correlation in SACs may create a descriptor for designing efficient magnetic SACs for renewable energy conversions.

BackgroundAntigen-antibody interactions are key events in immune system, which provide important clues to the immune processes and responses. In Antigen-antibody interactions, the specific sites on the antigens that are directly bound by the B-cell produced antibodies are well known as B-cell epitopes. The identification of epitopes is a hot topic in bioinformatics because of their potential use in the epitope-based drug design. Although most B-cell epitopes are discontinuous (or conformational), insufficient effort has been put into the conformational epitope prediction, and the performance of existing methods is far from satisfaction.ResultsIn order to develop the high-accuracy model, we focus on some possible aspects concerning the prediction performance, including the impact of interior residues, different contributions of adjacent residues, and the imbalanced data which contain much more non-epitope residues than epitope residues. In order to address above issues, we take following strategies. Firstly, a concept of 'thick surface patch' instead of 'surface patch' is introduced to describe the local spatial context of each surface residue, which considers the impact of interior residue. The comparison between the thick surface patch and the surface patch shows that interior residues contribute to the recognition of epitopes. Secondly, statistical significance of the distance distribution difference between non-epitope patches and epitope patches is observed, thus an adjacent residue distance feature is presented, which reflects the unequal contributions of adjacent residues to the location of binding sites. Thirdly, a bootstrapping and voting procedure is adopted to deal with the imbalanced dataset. Based on the above ideas, we propose a new method to identify the B-cell conformational epitopes from 3D structures by combining conventional features and the proposed feature, and the random forest (RF) algorithm is used as the classification engine. The experiments show that our method can predict conformational B-cell epitopes with high accuracy. Evaluated by leave-one-out cross validation (LOOCV), our method achieves the mean AUC value of 0.633 for the benchmark bound dataset, and the mean AUC value of 0.654 for the benchmark unbound dataset. When compared with the state-of-the-art prediction models in the independent test, our method demonstrates comparable or better performance.ConclusionsOur method is demonstrated to be effective for the prediction of conformational epitopes. Based on the study, we develop a tool to predict the conformational epitopes from 3D structures, available at http://code.google.com/p/my-project-bpredictor/downloads/list.

Industrial forest plantations are expanding rapidly across Monsoon Asia and monitoring extent is critical for understanding environmental and socioeconomic impacts. In this study, new, multisensor imagery were evaluated and integrated to extract the strengths of each sensor for mapping plantation extent at regional scales. Two distinctly different landscapes with multiple plantation types were chosen to consider scalability and transferability. These were Tanintharyi, Myanmar and West Kalimantan, Indonesia. Landsat-8 Operational Land Imager (OLI), Phased Array L-band Synthetic Aperture Radar-2 (PALSAR-2), and Sentinel-1A images were fused within a Classification and Regression Tree (CART) framework using random forest and high-resolution surveys. Multi-criteria evaluations showed both L-and C-band gamma nought γ˝backscatter decibel (dB), Landsat reflectance ρ λ , and texture indices were useful for distinguishing oil palm and rubber plantations from other land types. The classification approach identified 750,822 ha or 23% of the Taninathryi, Myanmar, and 216,086 ha or 25% of western West Kalimantan as plantation with very high cross validation accuracy. The mapping approach was scalable and transferred well across the different geographies and plantation types. As archives for Sentinel-1, Landsat-8, and PALSAR-2 continue to grow, mapping plantation extent and dynamics at moderate resolution over large regions should be feasible.