The one-pot multi-step conversion of biomass-derived furfural to γ-valerolactone (GVL) with 64.5% yield is achieved via acid–base bifunctional catalysis enabled by HfCl 4 in 2-propanol, and the recovered solid is active for transfer hydrogenation.
Computing-in-memory (CIM) suffers from remarkable area and performance costs from large memory cell and inefficient peripheral circuits for MLP acceleration. In this work, a 2D2R ReRAM CIM accelerator is proposed with circuit improvements for MLP in visual classification applications. The 2D2R ReRAM cell is organized as crossbar array for dense weight storage. The multi-level input circuit is proposed for high precision input with compensation for the nonlinearity of 2D2R cell. The successive-approximation output circuit is employed with all-0 detecting for fast and energy-efficient conversions. Besides, the weight-aware configurable computing is proposed to dynamically configure the input count for partial sum for improved performance. Compared with the traditional 2T2R cell, the area of 2D2R cell can be reduced by >85%. The accuracy of MNIST test set is 97.76% for the accuracy of 3b input, output and weight, and the energy efficiency can reach 174.5TOP/W under the working frequency of 200 MHz, realizing ∼2.6× improvement over previous work.
Understanding the hydrogen content in Venus' primordial atmosphere is crucial for comprehending the hydrodynamic escape process that shaped its atmospheric evolution. The hydrogen originated from two main sources: molecular hydrogen (H_2) from the solar nebula and water vapor (H_2O) from geological degassing. The precise proportions of these sources remain uncertain, leading to different hypotheses about Venus' atmospheric history. However, a systematic exploration of the parameter space regarding the proportions of these sources has not yet been conducted. This study aims to constrain the hydrogen content and its sources in Venus' primordial atmosphere by conducting extensive numerical simulations of early atmospheric escape scenarios. We developed an improved energy-limited hydrodynamic escape model, integrated with a 1D radiative-convective equilibrium atmospheric model, to simulate the early atmospheric escape on Venus. Using isotopic data of Ne and Ar from the current Venusian atmosphere, we constrained the contributions of nebula-derived and degassing-derived hydrogen. Our simulations have explored over 500,000 scenarios, varying the initial H_2 and H_2O compositions and considering different solar extreme ultraviolet (EUV) irradiation conditions. Our results, based on the isotopic ratios of ^20Ne/^22Ne, ^36Ar/^38Ar, and ^20Ne/^36Ar observed in Venus' atmosphere, indicate that the primordial atmospheric water content was limited to less than 0.01 ocean equivalents of H_2 (0.0004 wt$%$) and less than 1.4 ocean equivalents of H_2O. This suggests that if Venus ever had a primary hydrogen-rich atmosphere, it was mostly lost before forming its secondary, H_2O-rich atmosphere. Furthermore, our method can be applied to constrain the primordial atmospheric compositions of other terrestrial planets, providing insights into their evolutionary histories.
As the shared micromobility becomes a part of our daily life and environment, we expect the number of low-speed modes for first-and-last mile trips to grow rapidly. The shared micomobility is expected to serve billions of humans, bringing us considerable advantages. With this growth, shared micromobility simulation such as docked stations based shared bikes, dockless shared bikes and e-scooters, are regarded as promising solutions to deal with a large number of first-and-last mile trips. In this paper, we first provide a comprehensive overview of shared micromobility simulation and its related validation metrics. Next, we classify the research topics of shared micromobility simulation, summarize, and classify the existing works. Finally, challenges and future directions are provided for further research.
In order to assess the pollution levels and health risks of PM2.5-bound metals in Baoding City before and after the heating period, samples were collected in 2016 at Hebei University from September 25th to November 14th during the non-heating period, and November 15th to December 26th during the heating period, respectively. ICP-MS was applied to analyze seven heavy metals (Cr, Zn, Cu, Pb, Ni, Cd and Fe). The statistical analysis, enrichment factor (EF), pollution load index method, and Risk Assessment Method proposed by U.S. EPA were used to evaluate the non-carcinogenic risks of six of these heavy metals (Cr, Zn, Cu, Pb, Ni and Cd) and carcinogenic risks of three of these heavy metals (Cr, Ni and Cd). The results showed three main results. First, the average daily PM2.5 concentrations of the national air monitoring stations was 155.66 μg·m-3 which was 2.08 times as high as that of the second level criterion in China (75 μg·m-3) during the observation period. Compared with the non-heating period, all heavy metals concentrations increased during heating period. The growth rates of Pb and Ni were the highest and the lowest, which were 88.03 and 5.11 percent, respectively. Second, the results of enrichment factor indicated that the EF values of all heavy metals were higher during the heating period in comparison with during the non-heating period, but the degree of enrichment of all heavy metals remained unchanged. Not only those, Cr and Ni were minimally enriched and were affected by both human and natural factors, Pb, Cu and Zn were significantly enriched and were mainly affected by human factors, the enrichment of Cd was much higher than that of the other heavy metals, exhibiting extremely high enrichment, mainly due to human factors during the whole sampling period. The results of the pollution load index indicated that the proportions of the number of highly and very highly polluted PM2.5-bound metals were the highest during the heating period, while the proportion of moderately polluted PM2.5-bound metals was the highest during the non-heating period. The combined pollution degree of heavy metals was more serious during the heating period. Third, according to the health risk assessment model, we concluded that the non-carcinogenic and carcinogenic risks caused by inhalation exposure were the highest and by dermal exposure were the lowest for all kinds of people. The overall non-carcinogenic risk of heavy metals via inhalation and subsequent ingestion exposure caused significant harm to children during the non-heating and the heating periods, and the risk values were 2.64, 4.47, 1.20 and 1.47, respectively. Pb and Cr exhibited the biggest contributions to the non-carcinogenic risk. All the above non-carcinogenic risks exceeded the standard limits suggested by EPA (HI or HQ < 1). The carcinogenic risk via inhalation exposure to children, adult men and women were 2.10 × 10-4, 1.80 × 10-4, and 1.03 × 10-4 during the non-heating period, respectively, and 2.52 × 10-4, 2.16 × 10-4 and 1.23 × 10-4 during the heating period, respectively. All the above carcinogenic risks exceeded the threshold ranges (10-6~10-4), and Cr posed a carcinogenic risk to all people.
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