Catalyst Selection over an Electrochemical Reductive Coupling Reaction toward Direct Electrosynthesis of Oxime from NOx and Aldehyde.

Aqueous electrochemical coupling reactions, which enable the green synthesis of complex organic compounds, will be a crucial tool in synthetic chemistry. However, a lack of informed approaches for screening suitable catalysts is a major obstacle to its development. Here, we propose a pioneering electrochemical reductive coupling reaction toward direct electrosynthesis of oxime from NOx and aldehyde. Through integrating experimental and theoretical methods, we screen out the optimal catalyst, i.e., metal Fe catalyst, that facilitates the enrichment and C-N coupling of key reaction intermediates, all leading to high yields (e.g., ∼99% yield of benzaldoxime) for the direct electrosynthesis of oxime over Fe. With a divided flow reactor, we achieve a high benzaldoxime production of 22.8 g h-1 gcat-1 in ∼94% isolated yield. This work not only paves the way to the industrial mass production of oxime via electrosynthesis but also offers references for the catalyst selection of other electrochemical coupling reactions.

Sources and transport of CO2 in the karst system of Jiguan Cave, Funiu Mountains, China.

Conveyance and modification of carbon-isotope signals within the karst system remain difficult to constrain, due to the complexity of interactions between multiple components, including precipitation, bedrock, soil, atmosphere, and biota. Cave monitoring is thus critical to understanding both their transport in the karst system and dependence on local hydroclimatic conditions. Jiguan Cave, located in Funiu Mountain in central China, is representative of karst tourist caves with relatively thin epikarst zone. We conducted a comprehensive monitoring program of cave climate from 2018 to 2021 and measured δ13C during 2021 in monthly and heavy-rainfall samples of soil CO2, cave CO2, cave water (drip water and underground river), and underground river outlet. Our results demonstrate synchronous variations between CO2 concentration and δ13CCO2 in both soil and cave air on seasonal time scales. Cave pCO2 and carbon-isotope composition further exhibited a high sensitivity to human respiration with fluctuations of ~2000-3000 ppm within 4 days during the cave closure period in July 2021 without tourists. 13C-depleted isotopic signal of cave air in summer is the mixture of human respiration and soil CO2 which varies as a function of regional hydrological conditions of the summer monsoon during the rainy season with high temperatures and humidity. However, respired CO2 from the overlying soil was expected to be the only principal source of the cave CO2 when the anthropogenic CO2 source was removed. The high seasonal amplitude of cave air δ13CCO2 reflects ventilation dynamics, which leads to a prominent contribution from the external atmosphere during winter. Intriguingly, although the δ13C signal reflects complex vertical processes in the vertical karst profile, a heavy summer rainfall event was related to anomalously high δ13C values of cave water that can be utilized to interpret rainfall intensity and regional hydroclimate.

Altered Gut Microbiota and Short-chain Fatty Acids in Chinese Children with Constipated Autism Spectrum Disorder.

Gastrointestinal symptoms are more prevalent in children with autism spectrum disorder (ASD) than in typically developing (TD) children. Constipation is a significant gastrointestinal comorbidity of ASD, but the associations among constipated autism spectrum disorder (C-ASD), microbiota and short-chain fatty acids (SCFAs) are still debated. We enrolled 80 children, divided into the C-ASD group (n = 40) and the TD group (n = 40). In this study, an integrated 16S rRNA gene sequencing and gas chromatography-mass spectrometry-based metabolomics approach was applied to explore the association of the gut microbiota and SCFAs in C-ASD children in China. The community diversity estimated by the Observe, Chao1, and ACE indices was significantly lower in the C-ASD group than in the TD group. We observed that Ruminococcaceae_UCG_002, Erysipelotrichaceae_UCG_003, Phascolarctobacterium, Megamonas, Ruminiclostridium_5, Parabacteroides, Prevotella_2, Fusobacterium, and Prevotella_9 were enriched in the C-ASD group, and Anaerostipes, Lactobacillus, Ruminococcus_gnavus_group, Lachnospiraceae_NK4A136_group, Ralstonia, Eubacterium_eligens_group, and Ruminococcus_1 were enriched in the TD group. The propionate levels, which were higher in the C-ASD group, were negatively correlated with the abundance of Lactobacillus taxa, but were positively correlated with the severity of ASD symptoms. The random forest model, based on the 16 representative discriminant genera, achieved a high accuracy (AUC = 0.924). In conclusion, we found that C-ASD is related to altered gut microbiota and SCFAs, especially decreased abundance of Lactobacillus and excessive propionate in faeces, which provide new clues to understand C-ASD and biomarkers for the diagnosis and potential strategies for treatment of the disorder. This study was registered in the Chinese Clinical Trial Registry ( www.chictr.org.cn ; trial registration number ChiCTR2100052106; date of registration: October 17, 2021).

Electrocatalytic Synthesis of Nylon-6 Precursor at Almost 100 % Yield.

Synthesis of cyclohexanone oxime via the cyclohexanone-hydroxylamine process is widespread in the caprolactam industry, which is an upstream industry for nylon-6 production. However, there are two shortcomings in this process, harsh reaction conditions and the potential danger posed by explosive hydroxylamine. In this study, we presented a direct electrosynthesis of cyclohexanone oxime using nitrogen oxides and cyclohexanone, which eliminated the usage of hydroxylamine and demonstrated a green production of caprolactam. With the Fe electrocatalysts, a production rate of 55.9 g h-1 gcat -1 can be achieved in a flow cell with almost 100 % yield of cyclohexanone oxime. The high efficiency was attributed to their ability of accumulating adsorbed hydroxylamine and cyclohexanone. This study provides a theoretical basis for electrocatalyst design for C-N coupling reactions and illuminates the tantalizing possibility to upgrade the caprolactam industry towards safety and sustainability.

Monitoring surface dynamics of electrodes during electrocatalysis using in situ synchrotron FTIR spectroscopy.

Monitoring the surface dynamics of catalysts under working conditions is important for a deep understanding of the underlying electrochemical mechanisms towards efficient energy conversion and storage. Fourier transform infrared (FTIR) spectroscopy with high surface sensitivity has been considered as a powerful tool for detecting surface adsorbates, but it faces a great challenge when being adopted in surface dynamics investigations during electrocatalysis due to the complication and influence of aqueous environments. This work reports a well designed FTIR cell with tunable micrometre-scale water film over the surface of working electrodes and dual electrolyte/gas channels for in situ synchrotron FTIR tests. By coupling with a facile single-reflection infrared mode, a general in situ synchrotron radiation FTIR (SR-FTIR) spectroscopic method is developed for tracking the surface dynamics of catalysts during the electrocatalytic process. As an example, in situ formed key *OOH is clearly observed on the surface of commercial benchmark IrO2 catalysts during the electrochemical oxygen evolution process based on the developed in situ SR-FTIR spectroscopic method, which demonstrates its universality and feasibility in surface dynamics studies of electrocatalysts under working conditions.

Coupling CO2-to-Ethylene Reduction with the Chlor-Alkaline Process in Seawater through In Situ-Formed Cu Catalysts.

The overall commercial value of a CO2 electroreduction system is hindered by the valueless product and high energy consumption of the oxygen evolution reaction (OER) at the anode. Herein, with an in situ-formed copper catalyst, we employed the alternative chlorine evolution reaction for OER, and high-speed formation of both C2 products and hypochlorite in seawater can be realized. The EDTA in the sea salt electrolyte can trigger an intense dissolution and deposition of Cu on the surface of the electrode, resulting in the in situ formation of dendrites of Cu with high chemical activity. In this system, a faradaic efficiency of 47% can be realized for C2H4 production at the cathode and a faradaic efficiency of 85% can be realized for hypochlorite production at the anode with an operation current of 100 mA/cm2. This work presents a system for designing a highly efficient coupling system for the CO2 reduction reaction and alternative anodic reactions toward value-added products in a seawater environment.

Tuning the Selectivity of Liquid Products of CO2RR by Cu-Ag Alloying.

The combination of Cu and Ag presents a promising way to steer the CO2 reduction products through regulating the surface active sites. However, the difficulty in forming the CuAg alloy with a controllable atomic ratio impedes the in-depth understanding of the structure-activity relationship of CuAg catalysts. Herein, we use E-beam evaporation to synthesize a series of CuAg films with uniform distribution and controllable stoichiometry to reveal the real reaction mechanism on CuAg for the electrochemical CO2 reduction process. Compared with Cu, the Cu1-xAgx (x = 0.05-0.2) alloy showed an apparent suppression of HCOOH and the ratio between C2 liquid products (e.g., ethanol and acetate) and C1 liquid product (HCOOH) is also increased. Operando synchrotron radiation Fourier transform infrared spectroscopy results suggest that the introduction of Ag into the Cu phase can significantly strengthen the absorbed *CO and *OCCO intermediates and suppress the O-C-O intermediates. This research provides a reliable way to inhibit the generation of HCOOH and enhance the production of liquid C2 products during CO2RR and presents a guideline for the future manipulation of copper catalysts by alloying.

In Situ Construction of Flexible VNi Redox Centers over Ni-Based MOF Nanosheet Arrays for Electrochemical Water Oxidation.

Atomic-level design and construction of synergistic active centers are central to develop advanced oxygen electrocatalysts toward efficient energy conversion. Herein, an in situ construction strategy to introduce flexible redox sites of VNi centers onto Ni-based metal-organic framework (MOF) nanosheet arrays (NiV-MOF NAs) as a promising oxygen electrocatalyst is developed. The abundant redox VNi centers with flexible metal valence states of V+3/+4/+5 and Ni+3/+2 enable NiV-MOF NAs excellent oxygen evolution reaction (OER) activity and a long-term stability under high current densities, achieving current densities of 10 and 100 mA cm-2 at recorded overpotentials of 189 and 290 mV, respectively, and showing ignorable decay of initial activity at 100 mA cm-2 after 100 h OER operation. Operando synchrotron radiation Fourier transform infrared combined with quasi in situ X-ray absorption fine structure spectroscopies reveal at atomic level that the flexible V sites can continuously accept electrons from adjacent active Ni sites to accelerate OER kinetics for NiV-MOF NAs during the reaction process, accompanied by a self-optimized structural distortion of VO6 octahedron for promoting the electrochemical stability.

In-situ spectroscopic observation of dynamic-coupling oxygen on atomically dispersed iridium electrocatalyst for acidic water oxidation.

Uncovering the dynamics of active sites in the working conditions is crucial to realizing increased activity, enhanced stability and reduced cost of oxygen evolution reaction (OER) electrocatalysts in proton exchange membrane electrolytes. Herein, we identify at the atomic level potential-driven dynamic-coupling oxygen on atomically dispersed hetero-nitrogen-configured Ir sites (AD-HN-Ir) in the OER working conditions to successfully provide the atomically dispersed Ir electrocatalyst with ultrahigh electrochemical acidic OER activity. Using in-situ synchrotron radiation infrared and X-ray absorption spectroscopies, we directly observe that one oxygen atom is formed at the Ir active site with an O-hetero-Ir-N4 structure as a more electrophilic active centre in the experiment, which effectively promotes the generation of key *OOH intermediates under working potentials; this process is favourable for the dissociation of H2O over Ir active sites and resistance to over-oxidation and dissolution of the active sites. The optimal AD-HN-Ir electrocatalyst delivers a large mass activity of 2860 A gmetal-1 and a large turnover frequency of 5110 h-1 at a low overpotential of 216 mV (10 mA cm-2), 480-510 times larger than those of the commercial IrO2. More importantly, the AD-HN-Ir electrocatalyst shows no evident deactivation after continuous 100 h OER operation in an acidic medium.

Dynamic CoRu Bond Shrinkage at Atomically Dispersed Ru Sites for Alkaline Hydrogen Evolution Reaction.

Accurately manipulating the electronic structure of metal active sites under working conditions is central to developing efficient and stable electrocatalysts in industrial water-alkali electrolyzers. However, the lack of an intuitive means to capture the evolution of metal sites during the reaction state inhibits the manipulation of its electronic structure. Here, atomically dispersed Ru single-sites on cobalt nanoparticles confined onto macro-microporous frameworks (M-Co NPs@Ru SAs/NC) with tunable electron coupling effect for efficient catalysis of alkaline hydrogen evolution reaction (HER) are constructed. Using operando X-ray absorption and infrared spectroscopies, a dynamic CoRu bond shrinkage with strong electron coupling effect under working conditions is identified, which significantly promotes the adsorption of water molecules and then accelerates its dissociation to form the key H* over Ru sites for high HER activity. The well-designed M-Co NPs@Ru SAs/NC delivers efficient HER performance with a small overpotential of 34 mV at 10 mA cm-2 and a high turnover frequency of ≈4284 H2  h-1 at -0.05 V, 40 times higher than that of the benchmark Pt/C. This work provides a new point of view to manipulate the electronic structure of the metal active sites for highly effective electrocatalysis processes.

Self-Nanocavity-Confined Halogen Anions Boosting the High Selectivity of the Two-Electron Oxygen Reduction Pathway over Ni-Based MOFs.

We present a strategy of self-nanocavity confinement for substantially boosting the superior electrochemical hydrogen peroxide (H2O2) selectivity for conductive metal-organic framework (MOF) materials. By using operando synchrotron radiation X-ray adsorption fine structure and Fourier transform infrared spectroscopy analyses, the dissociation of key *OOH intermediates during the oxygen reduction reaction (ORR) is effectively suppressed over the self-nanocavity-confined X-Ni MOF (X = F, Cl, Br, or I) catalysts, contributing to a favorable two-electron ORR pathway for highly efficient H2O2 production. As a result, the as-prepared Br-confined Ni MOF catalyst significantly promotes H2O2 selectivity up to 90% in an alkaline solution, evidently outperforming the pristine Ni MOF catalyst (40%). Moreover, a maximal faradic efficiency of 86% with a high cumulative H2O2 yield rate of 596 mmol gcatalyst-1 h-1 for electrochemical H2O2 generation is achieved by the Br-confined Ni MOF catalyst.

Down-regulation of lncRNA HCG11 promotes cell proliferation of oral squamous cell carcinoma through sponging miR-455-5p.

BACKGROUND: As a type of head and neck squamous cell carcinoma (HNSCC), oral squamous cell carcinoma (OSCC) has a high incidence and low survival rate. Frequent deletion of protein tyrosine phosphatase receptor type sigma (PTPRS) has been found in HNSCC. Long non-coding RNA (lncRNA) HCG11 and miR-455-5p have been reported to be involved in several cancers, in which miR-455-5p was found to be up-regulated in the OSCC. However, the role of HCG11 in OSCC development is still unclear. METHODS: Several co-transfection systems were established to explore the regulation of HCG11 on OSCC cells. Cell proliferation was evaluated by the MTT assay, flow cytometry of cell cycle distribution, immunofluorescence of Ki67 and western blotting. A dual luciferase reporter assay was performed to verify the binding effects of miR-455-5p on HCG11 and PTPRS. The role of HCG11 knockdown in OSCC cell growth was also confirmed by nude mouse tumorigenicity assay in vivo. RESULTS: Knockdown of HCG11 increased OSCC cell proliferation, as indicated by enhanced cell vitalities over time, increased G1/S transition and Ki67 levels. Furthermore, lncRNA HCG11 was shown to negatively regulate miR-455-5p and miR-455-5p targeted PTPRS directly to affect its downstream indicators, which can further modulate OSCC cell proliferation and growth. The results obtained in vivo confirmed that HCG11 knockdown promoted OSCC cell growth. CONCLUSIONS: The lncRNA HCG11/miR-R-455-5p axis can be considered as an upstream signalling circuit of PTPRS with respect to regulating its activity and downstream pathways to further influence the progression of OSCC. This finding may provide a novel RNA-based therapeutic target for OSCC treatment.

Long non-coding RNA IGF2-AS represses breast cancer tumorigenesis by epigenetically regulating IGF2.

Long non-coding RNAs are a kind of endogenous ncRNAs with a length of more than 200 bp. Accumulating evidence suggests that long non-coding RNAs function as pivotal regulators in tumorigenesis and progression. However, their biological roles in breast cancer remain largely unknown. Here, we found that IGF2 antisense RNA (IGF2-AS) was significantly decreased in breast cancer tissues, cell lines, and plasma. Patients with low IGF2-AS were more likely to develop larger tumor size and later clinical stage. Overexpression of IGF2-AS evidently inhibited the proliferation and induced apoptosis of MCF-7 and T47D cells in vitro, as well as retarded tumor growth in vivo. Further investigation revealed that IGF2-AS inhibited the expression of its sense-cognate gene IGF2 in an epigenetic DNMT1-dependent manner, resulting in the inactivation of downstream oncogenic PI3K/AKT/mTOR signaling pathway. Enforced expression of IGF2 could significantly block the tumor inhibitory effect of IGF2-AS. Importantly, we found that IGF2-AS could be used as an effective biomarker for breast cancer diagnosis and prognosis. Taken together, our study indicates that IGF2-AS is a tumor suppressor in breast cancer, restoration of IGF2-AS may be a promising treatment for this fatal disease.

MOVES-Matrix for high-performance on-road energy and running emission rate modeling applications.

The MOVES model was developed by the U.S. Environmental Protection Agency (U.S. EPA) to estimate emissions from on-road mobile sources and nonroad sources in the United States. Coupling high-resolution on-road vehicle activity data with appropriate MOVES emission rates further advances research efforts designed to assess the environmental impacts of transportation design and operation strategies. However, the complicated MOVES interface and slow performance makes it difficult to assess large, regional scale transportation networks and to undertake analyses of large-scale systems that are dynamic in nature. The MOVES-Matrix system develops an initial Large Matrix of MOVES outputs by running MOVES 146,853 times on the PACE high performance computing cluster to generate more than 90 billion emission rates to populate the matrix for a single area with one fuel regime and one inspection and maintenance program. A total of 117 such Large Matrices would be needed for the entire United States. The MOVES-Matrix system developed can be used to conduct the emissions modeling 200-times faster than using MOVES. The hypothetical case study shows that MOVES-Matrix is able to generate the exact same emission results as the MOVES model to ensure the validity for regulatory analysis. The resulting matrix allows users to link emission rates to big data projects and to evaluate changes in emissions for dynamic transportation systems in near-real-time. MOVES-Matrix does not currently estimate emissions from starts, hoteling or evaporative emissions, and the research team is working on MOVES-Matrix version 2 that supports incorporating off-network modeling.Implications: MOVES-Matrix should be of interest to a broad readership including those interested in vehicle emission modeling, near-road air quality modeling, transportation conformity analysis. The paper should also interest engineers who are involved in transportation regulatory and conformity analysis, state implementation plan, and who are seeking an efficient way of conducting regulatory emission modeling and air quality analysis in the United States.

Auditory temporal perceptual learning and transfer in Chinese-speaking children with developmental dyslexia.

Perceptual learning refers to the improvement of perceptual performance as a function of training. Recent studies found that auditory perceptual learning may improve phonological skills in individuals with developmental dyslexia in alphabetic writing system. However, whether auditory perceptual learning could also benefit the reading skills of those learning the Chinese logographic writing system is, as yet, unknown. The current study aimed to investigate the remediation effect of auditory temporal perceptual learning on Mandarin-speaking school children with developmental dyslexia. Thirty children with dyslexia were screened from a large pool of students in 3th-5th grades. They completed a series of pretests and then were assigned to either a non-training control group or a training group. The training group worked on a pure tone duration discrimination task for 7 sessions over 2 weeks with thirty minutes per session. Post-tests immediately after training and a follow-up test 2 months later were conducted. Analyses revealed a significant training effect in the training group relative to non-training group, as well as near transfer to the temporal interval discrimination task and far transfer to phonological awareness, character recognition and reading fluency. Importantly, the training effect and all the transfer effects were stable at the 2-month follow-up session. Further analyses found that a significant correlation between character recognition performance and learning rate mainly existed in the slow learning phase, the consolidation stage of perceptual learning, and this effect was modulated by an individuals' executive function. These findings indicate that adaptive auditory temporal perceptual learning can lead to learning and transfer effects on reading performance, and shed further light on the potential role of basic perceptual learning in the remediation and prevention of developmental dyslexia.

Safety impacts of bicycle infrastructure: A critical review.

PROBLEM AND METHOD: This paper takes a critical look at the present state of bicycle infrastructure treatment safety research, highlighting data needs. Safety literature relating to 22 bicycle treatments is examined, including findings, study methodologies, and data sources used in the studies. Some preliminary conclusions related to research efficacy are drawn from the available data and findings in the research. RESULTS AND DISCUSSION: While the current body of bicycle safety literature points toward some defensible conclusions regarding the safety and effectiveness of certain bicycle treatments, such as bike lanes and removal of on-street parking, the vast majority treatments are still in need of rigorous research. Fundamental questions arise regarding appropriate exposure measures, crash measures, and crash data sources. PRACTICAL APPLICATIONS: This research will aid transportation departments with regard to decisions about bicycle infrastructure and guide future research efforts toward understanding safety impacts of bicycle infrastructure.

Understanding the emission impacts of high-occupancy vehicle (HOV) to high-occupancy toll (HOT) lane conversions: Experience from Atlanta, Georgia.

Converting a congested high-occupancy vehicle (HOV) lane into a high-occupancy toll (HOT) lane is a viable option for improving travel time reliability for carpools and buses that use the managed lane. However, the emission impacts of HOV-to-HOT conversions are not well understood. The lack of emission impact quantification for HOT conversions creates a policy challenge for agencies making transportation funding choices. The goal of this paper is to evaluate the case study of before-and-after changes in vehicle emissions for the Atlanta, Georgia, I-85 HOV/HOT lane conversion project, implemented in October 2011. The analyses employed the Motor Vehicle Emission Simulator (MOVES) for project-level analysis with monitored changes in vehicle activity data collected by Georgia Tech researchers for the Georgia Department of Transportation (GDOT). During the quarterly field data collection from 2010 to 2012, more than 1.5 million license plates were observed and matched to vehicle class and age information using the vehicle registration database. The study also utilized the 20-sec, lane-specific traffic operations data from the Georgia NaviGAtor intelligent transportation system, as well as a direct feed of HOT lane usage data from the State Road and Tollway Authority (SRTA) managed lane system. As such, the analyses in this paper simultaneously assessed the impacts associated with changes in traffic volumes, on-road operating conditions, and fleet composition before and after the conversion. Both greenhouse gases and criteria pollutants were examined. IMPLICATIONS: A straight before-after analysis showed about 5% decrease in air pollutants and carbon dioxide (CO2). However, when the before-after calendar year of analysis was held constant (to account for the effect of 1 yr of fleet turnover), mass emissions at the analysis site during peak hours increased by as much as 17%, with little change in CO2. Further investigation revealed that a large percentage decrease in criteria pollutants in the straight before-after analysis was associated with a single calendar year change in MOVES. Hence, the Atlanta, Georgia, results suggest that an HOV-to-HOT conversion project may have increased mass emissions on the corridor. The results also showcase the importance of obtaining on-road data for emission impact assessment of HOV-to-HOT conversion projects.

MOVES-Matrix and distributed computing for microscale line source dispersion analysis.

MOVES and AERMOD are the U.S. Environmental Protection Agency's recommended models for use in project-level transportation conformity and hot-spot analysis. However, the structure and algorithms involved in running MOVES make analyses cumbersome and time-consuming. Likewise, the modeling setup process, including extensive data requirements and required input formats, in AERMOD lead to a high potential for analysis error in dispersion modeling. This study presents a distributed computing method for line source dispersion modeling that integrates MOVES-Matrix, a high-performance emission modeling tool, with the microscale dispersion models CALINE4 and AERMOD. MOVES-Matrix was prepared by iteratively running MOVES across all possible iterations of vehicle source-type, fuel, operating conditions, and environmental parameters to create a huge multi-dimensional emission rate lookup matrix. AERMOD and CALINE4 are connected with MOVES-Matrix in a distributed computing cluster using a series of Python scripts. This streamlined system built on MOVES-Matrix generates exactly the same emission rates and concentration results as using MOVES with AERMOD and CALINE4, but the approach is more than 200 times faster than using the MOVES graphical user interface. Because AERMOD requires detailed meteorological input, which is difficult to obtain, this study also recommends using CALINE4 as a screening tool for identifying the potential area that may exceed air quality standards before using AERMOD (and identifying areas that are exceedingly unlikely to exceed air quality standards). CALINE4 worst case method yields consistently higher concentration results than AERMOD for all comparisons in this paper, as expected given the nature of the meteorological data employed. IMPLICATIONS: The paper demonstrates a distributed computing method for line source dispersion modeling that integrates MOVES-Matrix with the CALINE4 and AERMOD. This streamlined system generates exactly the same emission rates and concentration results as traditional way to use MOVES with AERMOD and CALINE4, which are regulatory models approved by the U.S. EPA for conformity analysis, but the approach is more than 200 times faster than implementing the MOVES model. We highlighted the potentially significant benefit of using CALINE4 as screening tool for identifying potential area that may exceeds air quality standards before using AERMOD, which requires much more meteorology input than CALINE4.

Water-soluble thermoresponsive α-helical polypeptide with an upper critical solution temperature: synthesis, characterization, and thermoresponsive phase transition behaviors.

Water-soluble polypeptides bearing 1-alkylimidazolium (methyl or n-butyl) and various counter-anions (i.e., Cl(-), I(-) or BF4 (-)) are prepared by ring-opening polymerization of γ-4-chloromethylbenzyl-l-glutamate-based N-carboxyanhydride (3), post-polymerization of poly(γ-4-chloromethylbenzyl-l-glutamate) (4), and ion-exchange reaction. Circular dichroism (CD) analysis reveals that the resulting polypeptides adopt an α-helical conformation in water with a fractional helicity in the range of 30%-56% at 20 °C and exhibit good conformational stability against temperature variations. The polypeptides exhibit lower critical solution temperature (LCST)-type or upper critical solution temperature (UCST)-type transitions in organic solvents or in water. The UCST-type transition temperature (Tpt ) in water is independent on the molecular weight, yet it decreases upon addition of NaCl and increases upon addition of NaI or NaBF4, suggesting a mainly electrostatic interaction mechanism.

The behavioral economics of drunk driving.

This study investigates whether drinker-drivers attributes are associated with imperfect rationality or irrationality. Using data from eight U.S. cities, we determine whether drinker-drivers differ from other drinkers in cognitive ability, ignorance of driving while intoxicated (DWI) laws, have higher rates of time preference, are time inconsistent, and lack self-control on other measures. We find that drinker-drivers are relatively knowledgeable about DWI laws and do not differ on two of three study measures of cognitive ability from other drinkers. Drinker-drivers are less prone to plan events involving drinking, e.g., selecting a designated driver in advance of drinking, and are more impulsive. Furthermore, we find evidence in support of hyperbolic discounting. In particular, relative to non-drinker-drivers, the difference between short- and long-term discount rates is much higher for drinker-drivers than for other drinkers. Implications of our findings for public policy, including incapacitation, treatment, and educational interventions, are discussed.