Degradation pathway is important for the study of carbamazepine (CBZ) removal in advanced oxidation processes (AOPs). Generally, degradation pathways are speculated based on intermediate identification and basic chemical rules. However, this semiempirical strategy is sometimes time-consuming and baseless. To improve the situation, a mini meta-analysis was first conducted for the degradation pathways of CBZ in AOPs. Then, the rationality of the pathways was analyzed by Density Functional Theory (DFT) calculation. Results show that the degradation pathways of CBZ in various AOPs has high similarity, and the reactive sites predicted by Fukui function fitted well with the data retrieved from literatures. In addition, molecule configuration of degradation intermediates was found to play a very important roles on degradation pathway. The study reveals that computational chemistry is a useful tool for degradation pathway speculation in AOPs.
Accurate forecasts are vital for supporting the decisions of modern companies. Forecasters typically select the most appropriate statistical model for each time series. However, statistical models usually presume some data generation process while making strong assumptions about the errors. In this paper, we present a novel data-centric approach — ‘forecasting with cross-similarity’, which tackles model uncertainty in a model-free manner. Existing similarity-based methods focus on identifying similar patterns within the series, i.e., ‘self-similarity’. In contrast, we propose searching for similar patterns from a reference set, i.e., ‘cross-similarity’. Instead of extrapolating, the future paths of the similar series are aggregated to obtain the forecasts of the target series. Building on the cross-learning concept, our approach allows the application of similarity-based forecasting on series with limited lengths. We evaluate the approach using a rich collection of real data and show that it yields competitive accuracy in both points forecasts and prediction intervals.
The spatiotemporal context a ects corporate behavior because any corporate activity is carried out in a speci c time and space. Based on an examination on the research and development (R&D) expenditures of 284 listed biopharmaceutical companies in China, this study nds that the innovation space of the biopharmaceutical industry presents a spa- tial “North–South” pattern. The spatial gravity center of the biopharmaceutical industry’s R&D investment has been shifting to the eastern coastal region. This spatiotemporal con- text will impact the R&D investment of biopharmaceutical companies. Research shows that the distance between biopharmaceutical companies and the gravity center has a direct impact on the R&D expenditures of biopharmaceutical companies. This study supports the context-sensitive thesis and shows how the spatiotemporal context a ects the R&D invest- ment of biopharmaceutical companies while controlling rm-level factors.
Hobart KD, Feygelson TI, Tadjer MJ, Anderson TJ, Koehler AD, Graham Jr S, Goorsky M, Cheng Z, Yates L, Bai T.; 2021. Diamond on nanopatterned substrate. United States of America patent US
Volatile organic compounds (VOCs) emitted from building and furnishing materials represent a major concern of indoor air quality, in particular in new buildings. We carried out multiweek nontargeted VOC measurements in 10 new apartments in Beijing, China, using online chemical ionization mass spectrometry. Dimethyl esters of succinic, glutaric, and adipic acids, which are rarely known for their presence in indoor air, were identified in three apartments. The identification was confirmed using authentic standards and by gas chromatography/mass spectrometry analysis. Despite varying concentrations, the three compounds exhibited largely consistent ratios across the three apartments and throughout the observation periods. The observed ratios resemble chemical composition of dibasic esters (DBE), which are a solvent mixture of the three compounds and have been used in the coating industry. A field “sniffing” experiment further confirms DBE emissions from the coatings of some wooden furniture in at least one apartment. The average airborne DBE concentrations in the three apartments were 41, 5, and 4 $μ$g/m3, respectively, exceeding the screening level of 1 $μ$g/m3 recommended by the Michigan Department of Environmental Quality, United States. In the context of fast-growing DBE usage, the current results suggest that DBE might be emerging indoor air pollutants and merit further investigation.
This study reports the different degradation mechanisms of carbamazepine (CBZ) and diclofenac (DCF) by single-atom Barium (Ba) embedded g-C3N4. Single-atom Ba is anchored onto g-C3N4 by forming ionic bond with triazine ring, thus greatly enhances the photocatalytic activity with an atom ratio of 1.78%. CBZ undergoes a typical photocatalysis mechanism, while DCF is degraded via a photosensitization-like process, which does not need band gap excitation of photocatalyst. By means of Density Functional Theory (DFT) calculation, the selectivity is found to be related with the different valence excitation modes of CBZ and DCF. Specifically, CBZ undergoes a local excitation, which does not obviously affect molecular configuration. In contrast, DCF undergoes a charge transfer excitation, which significantly changes the reactive sites distribution and facilitates photosensitization-like degradation. Due to the different degradation mechanism, the effects of pH, co-existed anions, and water matrix are also different. Since photosensitization-like mechanism does not rely on photo-generated holes mediated oxidation, the degradation efficient of DCF shows higher anti-interference capacity in real water.
Abstract In this paper, a difluoro-monobromo end group is designed and synthesized, which is then used to construct a novel polymer acceptor (named PY2F-T) yielding high-performance all-polymer solar cells with 15.22% efficiency. The fluorination strategy can increase the intramolecular charge transfer and interchain packing of the previous PY-T based acceptor, and significantly improve photon harvesting and charge mobility of the resulting polymer acceptor. In addition, detailed morphology investigations reveal that the PY2F-T-based blend shows smaller domain spacing and higher domain purity, which significantly suppress charge recombination as supported by time-resolved techniques. These polymer properties enable simultaneously enhanced JSC and FF of the PY2F-T-based devices, eventually delivering device efficiencies of over 15%, significantly outperforming that of the devices based on the non-fluorinated PY-T polymer (13%). More importantly, the PY2F-T-based active layers can be processed under ambient conditions and still achieve a 14.37% efficiency. They can also be processed using non-halogenated solvent o-xylene (no additive) and yield a decent performance of 13.05%. This work demonstrates the success of the fluorination strategy in the design of high-performance polymer acceptors, which provide guidelines for developing new all-PSCs with better efficiencies and stabilities for commercial applications.
Finding out the physical structure of neuronal circuits that governs neuronal responses is an important goal for brain research. With fast advances for large-scale recording techniques, identification of a neuronal circuit with multiple neurons and stages or layers becomes possible and highly demanding. Although methods for mapping the connection structure of circuits have been greatly developed in recent years, they are mostly limited to simple scenarios of a few neurons in a pairwise fashion; and dissecting dynamical circuits, particularly mapping out a complete functional circuit that converges to a single neuron, is still a challenging question. Here, we show that a recent method, termed spike-triggered non-negative matrix factorization (STNMF), can address these issues. By simulating different scenarios of spiking neural networks with various connections between neurons and stages, we demonstrate that STNMF is a persuasive method to dissect functional connections within a circuit. Using spiking activities recorded at neurons of the output layer, STNMF can obtain a complete circuit consisting of all cascade computational components of presynaptic neurons, as well as their spiking activities. For simulated simple and complex cells of the primary visual cortex, STNMF allows us to dissect the pathway of visual computation. Taken together, these results suggest that STNMF could provide a useful approach for investigating neuronal systems leveraging recorded functional neuronal activity.
Lake waters often act as important methane sources for global greenhouse gas emission, but it would be more complex as lakes are regulated by rivers. In this study, seasonal variations of dissolved and emitted methane in the Poyang Lake, the largest freshwater lake in China, are investigated based on a specially designed monitoring. As a typical subtropical linking-to-river lake, the Poyang shows characteristics of the "lake" in wet season and the "river" in dry season alternatively over a year. Consequently, CH(4)flux from the Poyang Lake to the Yangtze River closes to the highest in January due to concentrated dissolved CH(4)and "river" effects in dry season, while CH(4)flux to the atmosphere falls to the lowest in July because of intensified CH(4)oxidization and diluted dissolved CH(4)as well as "lake" effects in wet season. Overall, CH(4)fluxes from Poyang Lake to the atmosphere and to the Yangtze River were 19 and 0.35 Gg CH(4)yr(-1), respectively. The Three Gorges Dam, the world's largest dam in the Yangtze River, would further intensify this pattern, enhancing the transformation between "lake phase" and "river phase". This study also provides the paradigm for CH(4)budget from other large lakes in similar situations around the world.