A dopant-free hole transport layer with high mobility and a low-temperature process is desired for optoelectronic devices. Here, we study a metal–organic framework material with high hole mobility and strong hole extraction capability as an ideal hole transport layer for perovskite solar cells. By utilizing lifting-up method, the thickness controllable floating film of Ni 3 (2,3,6,7,10,11-hexaiminotriphenylene) 2 at the gas–liquid interface is transferred onto ITO-coated glass substrate. The Ni 3 (2,3,6,7,10,11-hexaiminotriphenylene) 2 film demonstrates high compactness and uniformity. The root-mean-square roughness of the film is 5.5 nm. The ultraviolet photoelectron spectroscopy and the steady-state photoluminescence spectra exhibit the Ni 3 (HITP) 2 film can effectively transfer holes from perovskite film to anode. The perovskite solar cells based on Ni 3 (HITP) 2 as a dopant-free hole transport layer achieve a champion power conversion efficiency of 10.3%. This work broadens the application of metal–organic frameworks in the field of perovskite solar cells. Graphical Abstract
The goal of classifying shock metamorphic features in meteorites is to estimate the corresponding shock pressure conditions. However, the temperature variability of shock metamorphism is equally important and can result in a diverse and heterogeneous set of shock features in samples with a common overall shock pressure. In particular, high-pressure (HP) minerals, which were previously used as a solid indicator of high shock pressure in meteorites, require complex pressure–temperature–time ( P–T–t ) histories to form and survive. First, parts of the sample must be heated to melting temperatures, at high pressure, to enable rapid formation of HP minerals before pressure release. Second, the HP minerals must be rapidly cooled to below a critical temperature, before the pressure returns to ambient conditions, to avoid retrograde transformation to their low-pressure polymorphs. These two constraints require the sample to contain large temperature heterogeneities, e.g. melt veins in a cooler groundmass, during shock. In this study, we calculated shock temperatures and possible P–T paths of chondritic and differentiated mafic–ultramafic rocks for various shock pressures. These P–T conditions and paths, combined with observations from shocked meteorites, are used to constrain shock conditions and P–T – t histories of HP-mineral bearing samples. The need for rapid thermal quench of HP phases requires a relatively low bulk-shock temperature and therefore moderate shock pressures below ~ 30 GPa, which matches the stabilities of these HP minerals. The low-temperature moderate-pressure host rock generally shows moderate shock-deformation features consistent with S4 and, less commonly, S5 shock stages. Shock pressures in excess of 50 GPa in meteorites result in melt breccias with high overall post-shock temperatures that anneal out HP-mineral signatures. The presence of ringwoodite, which is commonly considered an indicator of the S6 shock stage, is inconsistent with pressures in excess of 30 GPa and does not represent shock conditions different from S4 shock conditions. Indeed, ringwoodite and coexisting HP minerals should be considered as robust evidence for moderate shock pressures (S4) rather than extreme shock (S6) near whole-rock melting.
Long-lived interlayer excitons (IXs) in van der Waals heterostructures (HSs) stacked by monolayer transition metal dichalcogenides (TMDs) carry valley-polarized information and thus could find promising applications in valleytronic devices. Current manipulation approaches for valley polarization of IXs are mainly limited in electrical field/doping, magnetic field or twist-angle engineering. Here, we demonstrate an electrochemical-doping method, which is efficient, in-situ and nonvolatile. We find the emission characteristics of IXs in WS 2 /WSe 2 HSs exhibit a large excitonic/valley-polarized hysteresis upon cyclic-voltage sweeping, which is ascribed to the chemical-doping of O 2 /H 2 O redox couple trapped between WSe 2 and substrate. Taking advantage of the large hysteresis, a nonvolatile valley-addressable memory is successfully demonstrated. The valley-polarized information can be non-volatilely switched by electrical gating with retention time exceeding 60 min. These findings open up an avenue for nonvolatile valley-addressable memory and could stimulate more investigations on valleytronic devices.
Wonji Shoa Sugar Estate (WSSE) is one of the large-scale irrigation schemes in Ethiopia which was established in 1951. The aim of this study was to evaluate the performance of current furrow irrigation water management practices of WSSE. Performance evaluation of the current furrow irrigation was evaluated based on field experiment and the WinSRFR model. For this purpose, ten fields were selected from commonly used furrow lengths (32, 48, and 64 m). Application efficiency, distribution uniformity, and deep percolation performance indicators were used for evaluation. The performance of furrow irrigation showed poor performance, and as an improvement option, inflow rate and cutoff time were altered keeping furrow geometry constant. Advance and recession times for all furrow lengths were recorded and simulated using the WinSRFR model to obtain an accurate cutoff time of irrigation. The result obtained showed that the time allocated for all furrow lengths was not accurately determined. As an improvement option, both inflow rate and cutoff time changed and the performance of furrow irrigation significantly improved. By changing those decision variables, application efficacy and deep percolation performance indicators were significantly improved but distribution uniformity was not changed. In almost all statistical indices used, predicted performances by model were better than computed values in the existing situation. From the current result, it can be concluded that the inflow rate and cutoff time should be changed to attain good performance and increase furrow irrigation efficiency.
Objective Arterial stiffness is a strong predictor of cardiovascular mortality, and often precedes elevations in blood pressure. This cross-sectional pilot study examined differences in arterial stiffness, blood pressure, cardiometabolic markers, anthropometric outcomes, and inflammation in vegetarians and matched omnivores. Participants were healthy, non-smoking adults (18–65 years old) adhering to either a vegetarian/vegan or omnivore diet. Omnivores were matched to vegetarians using broad body mass index (BMI) categories. Results Arterial stiffness trended higher in omnivores versus vegetarians (7.0 ± 1.5 and 6.8 ± 1.1 m/s, respectively; p = 0.073). This trend was mainly driven by the male omnivores (p = 0.006 for gender effect and p = 0.294 for eating pattern effect). Omnivores displayed higher HDL concentrations compared to vegetarians, 63.8 ± 18.5 and 55.2 ± 16.9 mg/dL; however, total cholesterol/HDL ratio did not vary significantly between groups; p = 0.310. In men, a vegetarian eating pattern may reduce arterial stiffness; however, this benefit may be limited in women, particularly those who are premenopausal. Future research should examine arterial stiffness and cardiometabolic health outcomes in younger versus older female vegetarians, as these data can provide valuable insights on the role of plant-based eating patterns on arterial stiffness and cardiometabolic health.
Neutral evolution is a fundamental concept in evolutionary biology but teaching this and other non-adaptive concepts is especially challenging. Here we present Genie, a browser-based educational tool that demonstrates population-genetic concepts such as genetic drift, population isolation, gene flow, and genetic mutation. Because it does not need to be downloaded and installed, Genie can scale to large groups of students and is useful for both in-person and online instruction. Genie was used to teach genetic drift to Evolution students at Arizona State University during Spring 2016 and Spring 2017. The effectiveness of Genie to teach key genetic drift concepts and misconceptions was assessed with the Genetic Drift Inventory developed by Price et al. (CBE Life Sci Educ 13(1):65–75, 2014). Overall, Genie performed comparably to that of traditional static methods across all evaluated classes. We have empirically demonstrated that Genie can be successfully integrated with traditional instruction to reduce misconceptions about genetic drift.
Background Cannabis legalization has resulted in the proliferation of cannabis products. Participants’ familiarity with terms for these products may have implications for assessment, as unfamiliarity with particular terms may result in under-reports of use. Methods A convenience sample of 861 college students from one U.S. university completed a survey in the spring of 2020 about their familiarity with a variety of cannabis product terms and use of a variety of cannabis products. Results Participants varied in their familiarity with cannabis product terms. For example, with regard to terms for cannabis concentrates with very high concentrations of THC, 85% of participants reported being familiar with the term “wax pen or THC oil,” but only 27% reported being familiar with the term “butane hash oil (BHO)” (i.e., the oil that composes most concentrates). Moreover, of participants who reported use of concentrates based on selecting pictures of the products they had used ( n = 324, 40%), 99% ( n = 322) reported having seen a “wax pen or THC oil” based on a written list of product terms, whereas only 20% ( n = 65) reported having seen “butane hash oil (BHO).” This suggests that asking about use of “butane hash oil” use may result in lower rates of cannabis concentrate use than asking about use of “wax pen/THC oil.” With regard to terms for marijuana flower, 29% of participants ( n = 248) reported being unfamiliar with the term marijuana “buds or flowers.” Of participants who reported use of marijuana flower based on selecting pictures of the products they had used (38% of the sample, n = 329), only 86% ( n = 282) reported having seen marijuana “buds or flowers” based on a written list of product terms. This suggests that asking about use of marijuana “buds or flowers” use could result in under-reporting due to lack of familiarity with that term. Finally, when asked to select pictures of the cannabis product(s) that participants thought constituted “marijuana,” participants most commonly selected pictures of marijuana flower (93%), followed by wax pen/THC oil (57%) and edibles (49%). Conclusions Young adults vary in their familiarity with cannabis product terms, and some may under-report cannabis use in surveys that rely on written cannabis product terms. Young adults also differ in terms of which cannabis products they think constitute “marijuana.” Although participants’ familiarity with specific cannabis product terms in this sample may not generalize to other populations, results highlight the need for standardized surveys of cannabis use that incorporate pictures of cannabis products to overcome issues related to variability in familiarity with cannabis product terms.
Structural color printings have broad applications due to their advantages of long-term sustainability, eco-friendly manufacturing, and ultra-high resolution. However, most of them require costly and time-consuming fabrication processes from nanolithography to vacuum deposition and etching. Here, we demonstrate a new color printing technology based on polymer-assisted photochemical metal deposition (PPD), a room temperature, ambient, and additive manufacturing process without requiring heating, vacuum deposition or etching. The PPD-printed silver films comprise densely aggregated silver nanoparticles filled with a small amount (estimated <20% volume) of polymers, producing a smooth surface (roughness 2.5 nm) even better than vacuum-deposited silver films (roughness 2.8 nm) at ~4 nm thickness. Further, the printed composite films have a much larger effective refractive index n (~1.90) and a smaller extinction coefficient k (~0.92) than PVD ones in the visible wavelength range (400 to 800 nm), therefore modulating the surface reflection and the phase accumulation. The capability of PPD in printing both ultra-thin (~5 nm) composite films and highly reflective thicker film greatly benefit the design and construction of multilayered Fabry–Perot (FP) cavity structures to exhibit vivid and saturated colors. We demonstrated programmed printing of complex pictures of different color schemes at a high spatial resolution of ~6.5 μm by three-dimensionally modulating the top composite film geometries and dielectric spacer thicknesses (75 to 200 nm). Finally, PPD-based color picture printing is demonstrated on a wide range of substrates, including glass, PDMS, and plastic, proving its broad potential in future applications from security labeling to color displays.
Detecting outliers in gene–protein mapping that reveal the presence of neuro-degenerative disorders or distinguishes between two different neuro-degenerations is an unexplored research area. This research work proposes a new methodology based on graphs for detecting outliers that relate the gene–protein mapping anchored on their physicochemical properties. The results of this study have revealed the exact protein physicochemical properties and the corresponding gene that is mapped to that protein. This research work makes the following contributions: (i) Proposes a simple graphical approach to visualize the gene–protein mapping for neuro-degenerative disorders based on their structural and physicochemical properties (ii) Generation of a pre-processed database by feature extraction from multiple web servers (iii) Proposed methodology of extracting outliers from tabulated (supervised/unsupervised) data can be extended to detect outliers from any dataset. The outliers that have been detected by this methodology were further studied using the REVIGO server that reveals the genetic functionality of the genes in maintaining healthy human activity. The outliers have reported no significant contribution and hence it is believed that this method can be extended to detect noisy outlier data from other biological and clinical datasets.
We demonstrate an all optical approach that can surprisingly offer the possibility of yielding much more information than one would expect, pertinent to the carrier recombination dynamics via both radiative and nonradiative processes when only one dominant deep defect level is present in a semiconductor material. By applying a band-defect state coupling model that explicitly treats the inter-band radiative recombination and Shockley–Read–Hall (SRH) recombination via the deep defect states on an equal footing for any defect center occupation fraction, and analyzing photoluminescence (PL) as a function of excitation density over a wide range of the excitation density (e.g., 5–6 orders in magnitude), in conjunction with Raman measurements of the LO-phonon plasmon (LOPP) coupled mode, nearly all of the key parameters relevant to the recombination processes can be obtained. They include internal quantum efficiency (IQE), minority and majority carrier density, inter-band radiative recombination rate ( W r ), minority carrier nonradiative recombination rate ( W nr ), defect center occupation fraction ( f ), defect center density ( N t ), and minority and majority carrier capture cross-sections ( σ t and σ tM ). While some of this information is thought to be obtainable optically, such as IQE and the W r / W nr ratio, most of the other parameters are generally considered to be attainable only through electrical techniques, such as current-voltage (I-V) characteristics and deep level transient spectroscopy (DLTS). Following a procedure developed herein, this approach has been successfully applied to three GaAs double-heterostructures that exhibit two distinctly different nonradiative recombination characteristics. The method greatly enhances the usefulness of the simple PL technique to an unprecedented level, facilitating comprehensive material and device characterization without the need for any device processing.
The ongoing deployment of Distributed Energy Resources, while bringing benefits, introduces significant challenges to the electric utility industry, especially in the distribution grid. These challenges call for closer monitoring through state estimation, where real-time topology recovery is the basis for accurate modeling. Previous methods either ignore geographical information, which is important in connectivity identification or are based on an ideal assumption of an isolated sub-network for topology recovery, e.g., within one transformer. This requires field engineers to identify the association, which is costly and may contain errors. To solve these problems, we propose a density-based topology clustering method that leverages both voltage domain data and the geographical space information to segment datasets from a large utility customer pool, after which other topology reconstruction methods can carry over. Specifically, we show how to use voltage and GPS information to infer associations within one transformer area, i.e., to identify the meter-transformer connectivity. To give a guarantee, we show a theoretic bound for our clustering method, providing the ability to explain the performance of the machine learning method. The proposed algorithm has been validated by IEEE test systems and Duquesne Light Company in Pittsburgh, showing outstanding performance. A utility implementation is also demonstrated.
This paper considers the model discrimination problem among a finite number of models in safety–critical systems that are subjected to constraints that can be disjunctive and where state and input constraints can be coupled with each other. In particular, we consider both the optimal input design problem for active model discrimination that is solved offline as well as the online passive model discrimination problem via a model invalidation framework. To overcome the issues associated with non-convex and generalized semi-infinite constraints due to the disjunctive and coupled constraints, we propose some techniques for reformulating these constraints in a computationally tractable manner by leveraging the Karush–Kuhn–Tucker (KKT) conditions and introducing binary variables, thus recasting the active and passive model discrimination problems into tractable mixed-integer linear/quadratic programming (MILP/MIQP) problems. When compared with existing approaches, our method is able to obtain the optimal solution and is observed in simulations to also result in less computation time. Finally, we demonstrate the effectiveness of the proposed active model discrimination approach for estimating driver intention with disjunctive safety constraints and state–input coupled curvature constraints, as well as for fault identification.
Researchers have launched a new era of studies exploring relationships between legal services regulation and access to justice. These scholarly developments respond to recent changes in how Anglo-American jurisdictions regulate the practice of law, changing who can make money from the practice of law, who can engage in it, and who can direct and control it. Often described as projects of deregulation, most are actually acts of reregulation. This article reviews empirical evidence of the relationship between these changes and access to justice. While evidence suggests some promise for increasing access, particularly through lawyerless legal services, most of these projects are in early stages and their impacts on access to justice will take some time to understand. Because much remains to explore, we also offer a research agenda for this emerging subfield. Expected final online publication date for the Annual Review of Law and Social Science, Volume 18 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Food value chains (FVCs) in developing countries are transforming rapidly, with some regions in the modern stage (led by supermarkets and large processors) and other regions in a transitional stage (led by midstream small and medium enterprises). With transformation, however, come market-performance issues related to monopoly and monopsony power, vertical bargaining, contracting, and other issues addressed by empirical industrial organization (EIO) researchers. Although the concepts and methods of EIO are evolving rapidly, the two bodies of literature on EIO and FVC transformation as part of the food markets and food industries branches of development economics have not sufficiently cross-pollinated. Applying tools of modern EIO to FVCs in developing countries is now relevant because of the transformation that has occurred and possibly due to the increasing availability of data from surveys of farms, processors, and wholesalers, and for some retailers, from scanner data. We review the transformation trends, the EIO themes and tools relevant to them, and the emerging data sources. Expected final online publication date for the Annual Review of Resource Economics, Volume 14 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
This study presents an integrated model to shed light on the factors influencing individuals’ likelihood and frequency of usage of bus transit in Bengaluru, India, with a focus on the role of individuals’ subjective perceptions of service quality. Typically, subjective perceptions of transit service characteristics such as comfort, cleanliness, reliability, and safety are measured using Likert rating scale questions in travel surveys. A shortcoming with many such surveys is that the Likert rating scale questions do not include a “don’t know” response category for the respondents to express their unfamiliarity and lack of opinion on the transit service. For this reason, some respondents who are not familiar with and do not have an opinion about the transit system are likely to choose the neutral response to Likert scale questions. At the same time, travelers who are familiar with and/or informed about the transit system may also choose the neutral response to state their opinion neutrality. As a result, some travelers’ unfamiliarity with (and lack of opinion about) transit services may be confounded with the informed perceptions of those who are familiar with transit. This is because those who are unfamiliar with the transit system are less likely to use it and more likely to state neutral responses than those who are familiar with the system. Ignoring such influence of travelers’ unfamiliarity can potentially distort the ordinal scale of Likert variables, result in biased parameter estimates and distorted implications about the influence of perceptions on transit usage. To address this concern, this study uses a generalized heterogeneous data model (GHDM) that allows a joint econometric analysis of the influence of individuals’ perceptions of transit service quality on their likelihood of transit use and frequency of use and at the same time disentangle unfamiliarity from informed perceptions. The empirical results shed light on: (a) the role of individuals’ demographic variables and subjective perceptions on their use and frequency of use of the bus transit system in Bengaluru, (b) the importance of separating unfamiliarity from informed opinions on transit service quality, (c) the need to include an option for respondents to reveal their unfamiliarity in Likert rating scale survey questions on perceptions, and (d) demographic segment-specific strategies for attracting new riders and enhancing ridership of current users of the bus transit system in Bengaluru.
Improving the positive emotions of urban populations is essential for meeting the United Nations Sustainable Development Goals (SDGs) of “good health and well-being” and “sustainable cities and communities”. Urban parks generally may enhance people's positive sentiments, but little is known about explicitly linking the landscape composition and configuration of urban parks directly with visitors' sentiments based on social media data. The main objective of this study, therefore, was to identify key landscape attributes that influence this relationship in the Beijing metropolitan region. We first crawled 55,441 valid text data items from Sina Weibo for 99 urban parks within the fifth ring road of Beijing. Then, we quantified the positive emotions of visitors to urban parks using social media data and sentiment analysis. Finally, we evaluated the differences in visitors' positive emotions among different types of parks and used Random Forest to identify urban park attributes that were correlated with positive emotions. We found that visitors to different types of urban parks had different levels of positive emotions. Specifically, visitors to comprehensive parks and cultural relics parks were significantly happier than visitors to community parks. Visitors to parks between the third and fourth ring roads in Beijing had the lowest levels of positive emotions. Positive emotions were found to be positively correlated with park size and the mean size of water bodies but negatively correlated with large areas of impervious surfaces. This study sheds new light on the relationship between park landscape patterns and visitors' positive emotions through a new approach based on social media data. The research methods and findings may inspire similar studies in other cities and countries, which are needed to improve park planning and management and thus enhance urban sustainability.
Informed by attachment theory and self-determination theory, the goal of this study was to test the hypothesis that behavioral engagement mediates the longitudinal associations between teacher–child relationship quality and academic achievement. In addition, in an exploratory manner, we expected to identify some additional transactional relations among these variables. Participants were 301 children (Mage = 65.72 months, SD = 4.18 months; 49% boys) and their teachers. In each spring semester from kindergarten to second grade, teachers reported on the closeness and conflict in the teacher–child relationship and on children's academic skills. Each year, trained observers rated children's behavioral engagement in the classroom, and a different group of research assistants assessed children's academic skills using subscales from the Woodcock–Johnson III Tests of Achievement. Cross–lagged panel models indicated that teacher–child conflict in kindergarten was indirectly related to teacher–reported academic skills in second grade through behavioral engagement in first grade. There was also evidence of transactional, negative relations between teacher–child conflict and behavioral engagement from kindergarten to first grade. These findings highlight behavioral engagement as a mechanism linking early teacher–child conflict and children's later academic skills.
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