MegaWika: Millions of reports and their sources across 50 diverse languages

To foster the development of new models for collaborative AI-assisted report generation, we introduce MegaWika, consisting of 13 million Wikipedia articles in 50 diverse languages, along with their 71 million referenced source materials. We process this dataset for a myriad of applications, going beyond the initial Wikipedia citation extraction and web scraping of content, including translating non-English articles for cross-lingual applications and providing FrameNet parses for automated semantic analysis. MegaWika is the largest resource for sentence-level report generation and the only report generation dataset that is multilingual. We manually analyze the quality of this resource through a semantically stratified sample. Finally, we provide baseline results and trained models for crucial steps in automated report generation: cross-lingual question answering and citation retrieval.Comment: Submitted to ACL, 202

Mineralogy and geochemistry of atypical reduction spheroids from the Tumblagooda Sandstone, Western Australia

Funding Information: This research was supported by a CSIRO Mineral Resources studentship, a Curtin University student scholarship and a Minerals Research Institute of Western Australia scholarship. The editors of Sedimentology and three anonymous reviewers are acknowledged for their assistance in improving the manuscript. We would also like to thank Mike Paxman and the Parks and Wildlife Service for permission to sample in Kalbarri National Park. Finally, the authors would like to pay tribute to the memory of Professor Nigel Trewin, whose work laid much of the foundation for this study and many others on the Tumblagooda Sandstone.Peer reviewedPostprin

Dual roles for potassium hydride in haloarene reduction : CSNAr and SET reduction via organic electron donors formed in benzene

Potassium hydride behaves uniquely and differently than sodium hydride towards aryl halides. Its reactions with a range of haloarenes, including designed 2,6-dialkylhaloarenes, were studied in THF and in benzene. In THF, evidence supports concerted nucleophilic aromatic substitution, CSNAr, and the mechanism originally proposed by Pierre et al. is now validated through DFT studies. In benzene, besides this pathway, strong evidence for single electron transfer chemistry is reported. Experimental observations and DFT studies lead us to propose organic super electron donor generation to initiate BHAS (base-promoted homolytic aromatic substitution) cycles. Organic donor formation originates from deprotonation of benzene by KH; attack on benzene by the resulting phenylpotassium generates phenylcyclohexadienylpotassium that can undergo (i) deprotonation to form an organic super electron donor or (ii) hydride loss to afford biphenyl. Until now, BHAS reactions have been triggered by reaction of a base, MOtBu (M = K, Na), with many different types of organic additive, all containing heteroatoms (N or O or S) that enhance their acidity and place them within range of MOtBu as a base. This paper shows that with the stronger base, KH, even a hydrocarbon (benzene) can be converted into an electron-donating initiator

Topiramate-Induced Modulation of Hepatic Molecular Mechanisms: An Aspect for Its Anti-Insulin Resistant Effect

Topiramate is an antiepileptic drug known to ameliorate insulin resistance besides reducing body weight. Albeit liver plays a fundamental role in regulation of overall insulin resistance, yet the effect of topiramate on this organ is controversial and is not fully investigated. The current work aimed to study the potential hepatic molecular mechanistic cassette of the anti-insulin resistance effect of topiramate. To this end, male Wistar rats were fed high fat/high fructose diet (HFFD) for 10 weeks to induce obese, insulin resistant, hyperglycemic animals, but with no overt diabetes. Two HFFD-groups received oral topiramate, 40 or 100 mg/kg, for two weeks. Topiramate, on the hepatic molecular level, has opposed the high fat/high fructose diet effect, where it significantly increased adiponectin receptors, GLUT2, and tyrosine kinase activity, while decreased insulin receptor isoforms. Besides, it improved the altered glucose homeostasis and lipid profile, lowered the ALT level, caused subtle, yet significant decrease in TNF-α, and boosted adiponectin in a dose dependent manner. Moreover, topiramate decreased liver weight/, visceral fat weight/, and epididymal fat weight/body weight ratios. The study proved that insulin-resistance has an effect on hepatic molecular level and that the topiramate-mediated insulin sensitivity is ensued partly by modulation of hepatic insulin receptor isoforms, activation of tyrosine kinase, induction of GLUT2 and elevation of adiponectin receptors, as well as their ligand, adiponectin, besides its known improving effect on glucose tolerance and lipid homeostasis

PaLM 2 Technical Report

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of objectives. Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more efficient inference compared to PaLM. This improved efficiency enables broader deployment while also allowing the model to respond faster, for a more natural pace of interaction. PaLM 2 demonstrates robust reasoning capabilities exemplified by large improvements over PaLM on BIG-Bench and other reasoning tasks. PaLM 2 exhibits stable performance on a suite of responsible AI evaluations, and enables inference-time control over toxicity without additional overhead or impact on other capabilities. Overall, PaLM 2 achieves state-of-the-art performance across a diverse set of tasks and capabilities. When discussing the PaLM 2 family, it is important to distinguish between pre-trained models (of various sizes), fine-tuned variants of these models, and the user-facing products that use these models. In particular, user-facing products typically include additional pre- and post-processing steps. Additionally, the underlying models may evolve over time. Therefore, one should not expect the performance of user-facing products to exactly match the results reported in this report

Copper Isotope Fractionation in Archean Hydrothermal Systems: Evidence From the Mesoarchean Carlow Castle Cu‐Co‐Au Deposit

Abstract Copper isotope analysis has emerged as a promising tool for understanding genetic processes in Cu ore deposits. However, applications of this analytical technique to Archean Cu deposits have been extremely limited, even though Archean terranes are among the most economically endowed on Earth. As such, this study presents the first Cu isotope analysis of an Archean Cu deposit, the Mesoarchean Carlow Castle hydrothermal Cu‐Co‐Au deposit. Archean primary Cu sulfide ore samples and Cenozoic supergene Cu ore samples were analyzed. Primary ore samples are isotopically light, with δ65Cu values ranging between −0.80 ± 0.02‰ and 0.00 ± 0.007‰, whilst supergene samples are isotopically heavier and range between −0.50 ± 0.01‰ and 0.62 ± 0.005‰. In primary ore samples, a relationship is observed between the Cu isotope signature, ore grade, and alteration assemblage that records the isotopic and physicochemical evolution of the Carlow Castle deposit's hydrothermal ore‐forming system. A mafic igneous source is suggested as a metal source in the Carlow Castle Cu‐Co‐Au deposit. The limited heavy isotopic fractionation of supergene Cu ore samples in this study is interpreted to reflect limited redox cycling of Cu due to in situ oxidative weathering of vein‐hosted Cu sulfides in the overlying Cenozoic supergene system. This differs from previously studied deposits where significant Cu transport and multiple stages of isotopic enrichment are often evident in supergene Cu enrichment layers. The results of this study suggest that Cu isotope analysis could be valuable in understanding genetic processes in hydrothermal Cu deposits, including Archean ore deposits and terranes