Stabilization/solidification (S/S) is commonly applied to treat heavy metal-contaminated soils through the use of lime and ordinary Portland cement (OPC). Recently, reactive magnesia (MgO) has ...emerged as a novel binder for S/S of heavy metal-contaminated soils; however, a comprehensive comparison between MgO, lime (CaO), and OPC for S/S application is still missing. This study compares the S/S efficiency of MgO, CaO, and OPC for soils contaminated by six individual heavy metals (Pb, Cu, Zn, Ni, Cd, and Mn) through unconfined compressive strength (UCS) test, one stage batch leaching test, and microstructural analysis. The addition of binders can transform soluble heavy metal salts to insoluble hydroxides and their complexes, and hence the leachability of heavy metals decreases. However, the level, to which the leachability can be reduced, is highly pH dependent. Contaminated soils treated with MgO have pH of 9–10.5, at which the leachability of Pb and Zn is much lower than that of OPC- or CaO-treated soils with pH of 10.5–13; for example, the leached Pb and Zn from MgO-treated soils are only 0.1%–3.3% and 0.1%–9.4% of those from OPC-treated soils, respectively. On the other hand, the leached Cd and Mn from OPC-treated soils are 0.1%–28.5% and 0.1–10.7% of those from MgO-treated soils, respectively, due to the high pH and the formation of calcium silicate hydrate (CSH) in OPC-treated soils. OPC and CaO are more effective than MgO in decreasing the Ni leachability at high original concentrations, but less effective at low original concentrations. For all soils except those contaminated by Zn, the OPC generally produces a much higher UCS, up to two orders of magnitude, than the CaO and MgO. The results of study indicate that no single binder can treat all types of heavy metal-contaminated soils perfectly, and the selection of binder is a site-specific problem.
Display omitted
•Comparison of MgO, CaO, and cement for treating heavy metal-contaminated soils.•pH of treated heavy metal-contaminated soils: MgO < cement<CaO.•Leachability of treated Pb- and Zn-contaminated soils: MgO < cement<CaO.•Leachability of treated Cd- and Mn-contaminated soils: cement<CaO < MgO.•Strength of treated Pb-, Cu- Cd-, and Mn-contaminated soils: MgO, CaO < cement.
Many statistical applications involve models for which it is difficult to evaluate the likelihood, but from which it is relatively easy to sample. Approximate Bayesian computation is a ...likelihood-free method for implementing Bayesian inference in such cases. We present results on the asymptotic variance of estimators obtained using approximate Bayesian computation in a large data limit. Our key assumption is that the data are summarized by a fixed-dimensional summary statistic that obeys a central limit theorem. We prove asymptotic normality of the mean of the approximate Bayesian computation posterior. This result also shows that, in terms of asymptotic variance, we should use a summary statistic that is of the same dimension as the parameter vector, p, and that any summary statistic of higher dimension can be reduced, through a linear transformation, to dimension p in a way that can only reduce the asymptotic variance of the posterior mean. We look at how the Monte Carlo error of an importance sampling algorithm that samples from the approximate Bayesian computation posterior affects the accuracy of estimators. We give conditions on the importance sampling proposal distribution such that the variance of the estimator will be of the same order as that of the maximum likelihood estimator based on the summary statistics used. This suggests an iterative importance sampling algorithm, which we evaluate empirically on a stochastic volatility model.
Abstract
Our primary objective is to provide the clinical informatics community with an introductory tutorial on calibration measurements and calibration models for predictive models using existing R ...packages and custom implemented code in R on real and simulated data. Clinical predictive model performance is commonly published based on discrimination measures, but use of models for individualized predictions requires adequate model calibration. This tutorial is intended for clinical researchers who want to evaluate predictive models in terms of their applicability to a particular population. It is also for informaticians and for software engineers who want to understand the role that calibration plays in the evaluation of a clinical predictive model, and to provide them with a solid starting point to consider incorporating calibration evaluation and calibration models in their work.
Covered topics include (1) an introduction to the importance of calibration in the clinical setting, (2) an illustration of the distinct roles that discrimination and calibration play in the assessment of clinical predictive models, (3) a tutorial and demonstration of selected calibration measurements, (4) a tutorial and demonstration of selected calibration models, and (5) a brief discussion of limitations of these methods and practical suggestions on how to use them in practice.
Conspectus Molecular self-assembly (MSA) refers to spontaneous arrangement of molecular building blocks into ordered structures governed by weak interactions. Due to its high versatility and ...reversibility, MSA has been widely employed as a robust bottom-up approach to fabricating low-dimensional functional nanostructures, which are used in various applications in nanoscience and technology. To date, tremendous effort has been devoted to constructing various MSAs at surfaces, ranging from self-assembled monolayers and two-dimensional (2D) nanoporous networks to complex 2D quasicrystals and Sierpiński triangle fractals. However, precise control of the assembled structures and efficient achievement of their full applicability remain two major challenges in the MSA field. As another widely employed bottom-up approach to fabricating nanostructures, on-surface reaction (OSR) refers to a reaction that occurs on the surface and is two-dimensionally confined. OSR offers the possibility to synthesize compounds that may not be feasibly achieved in solution chemistry. Compared with MSA based on weak intermolecular interactions, OSR-based structures possess high thermal and chemical stabilities due to internal strong covalent bonds. In this Account, we briefly overview recent achievements of MSAs on single crystal metal surfaces with a focus on their controllability and applicability in tweaking the properties of the molecular building blocks involved. Emphasis will be particularly placed upon mediation of OSRs with the MSA strategy. To explore surface MSAs, on the one hand, scanning tunneling microscopy and spectroscopy have been routinely employed as the experimental tools to probe the intermolecular interactions as well as geometric and electronic structures of the assemblies at the atomic and molecular levels. On the other hand, density functional theory and molecular dynamics have been theoretically applied to model and calculate the assembling systems, furthering our understanding of the experimental results. In principle, MSA is primarily balanced by molecule–molecule and molecule–substrate interactions under vacuum conditions. In terms of the assembling methodologies, people have been attempting to achieve rational design, accurate prediction, and controllable construction of assembled molecular nanostructures, namely, tentative design of specific backbones and functional groups of the molecular building blocks, and careful control of the assembling parameters including substrate lattice, temperature, coverage, and external environment as well. An obvious goal for the development of these methodologies lies in the ultimate applications of these MSAs. MSA can retrospectively affect the properties of the assembling molecules. For instance, self-assembled structures not only can serve as secondary templates to host guest molecules but also can stabilize surface metal adatoms. In fact, the electronics, magnetism, and optics of MSAs have been successfully explored. In surface chemistry, the MSA strategy can be further applied to mediate OSRs in at least three aspects: tweaking reaction selectivity, changing reaction pathway, and restricting reaction site. The governing principle lies in that the self-assembled molecules are confined in the assemblies so that the pre-exponential factors and the energy barriers in the Arrhenius equation of the involved reactions could be substantially varied because the subtle reaction mechanisms may change upon assembling. In this sense, the MSA strategy can be efficiently exploited to tune the properties of the assembling molecules and mediate OSRs in surface chemistry.
Abstract
The purpose of this study was to collect evidence of the relationship between retirement and depression through meta-analysis and further analyze the heterogeneity of results. The quality of ...the studies was rated based on 10 predefined criteria. We searched for articles published between 1980 and 2020, and a total of 25 longitudinal studies were included in the meta-analysis. The meta-analysis results showed that retirement was associated with more depressive symptoms (d = 0.044, 95% confidence interval (CI): 0.008, 0.080). The association of more depressive symptoms with involuntary retirement (d = 0.180, 95% CI: 0.061, 0.299) was stronger than with voluntary retirement (d = 0.086, 95% CI: −0.018, 0.190) and regulatory retirement (d = 0.009, 95% CI: −0.079, 0.097). Retirement was significantly associated with more depressive symptoms in Eastern developed countries (d = 0.126, 95% CI: 0.041, 0.210), and the association was stronger than that in Western developed countries (d = 0.016, 95% CI: −0.023, 0.055). We found that the transition to retirement was associated with higher risk of depression, and this association varied by the type of retirement and country. Further empirical studies are needed to explore the mechanism of retirement and depression and whether such an association is linked with socioeconomic position.
Abstract
Motivation
Predicting new drug–target interactions is an important step in new drug development, understanding of its side effects and drug repositioning. Heterogeneous data sources can ...provide comprehensive information and different perspectives for drug–target interaction prediction. Thus, there have been many calculation methods relying on heterogeneous networks. Most of them use graph-related algorithms to characterize nodes in heterogeneous networks for predicting new drug–target interactions (DTI). However, these methods can only make predictions in known heterogeneous network datasets, and cannot support the prediction of new chemical entities outside the heterogeneous network, which hinder further drug discovery and development.
Results
To solve this problem, we proposed a multi-modal DTI prediction model named ‘MultiDTI’ which uses our proposed joint learning framework based on heterogeneous networks. It combines the interaction or association information of the heterogeneous network and the drug/target sequence information, and maps the drugs, targets, side effects and disease nodes in the heterogeneous network into a common space. In this way, ‘MultiDTI’ can map the new chemical entity to this learned common space based on the chemical structure of the new entity. That is, bridging the gap between new chemical entities and known heterogeneous network. Our model has strong predictive performance, and the area under the receiver operating characteristic curve of the model is 0.961 and the area under the precision recall curve is 0.947 with 10-fold cross validation. In addition, some predicted new DTIs have been confirmed by ChEMBL database. Our results indicate that ‘MultiDTI’ is a powerful and practical tool for predicting new DTI, which can promote the development of drug discovery or drug repositioning.
Availability and implementation
Python codes and dataset are available at https://github.com/Deshan-Zhou/MultiDTI/.
Supplementary information
Supplementary data are available at Bioinformatics online.
The emergence of the novel human coronavirus SARS-CoV-2 in Wuhan, China has caused a worldwide epidemic of respiratory disease (COVID-19). Vaccines and targeted therapeutics for treatment of this ...disease are currently lacking. Here we report a human monoclonal antibody that neutralizes SARS-CoV-2 (and SARS-CoV) in cell culture. This cross-neutralizing antibody targets a communal epitope on these viruses and may offer potential for prevention and treatment of COVID-19.
Three structurally identical polymers, except for the number of fluorine substitutions (0, 1, or 2) on the repeat unit (BnDT-DTBT), are investigated in detail, to further understand the impact of ...these fluorine atoms on open circuit voltage (V oc), short circuit current (J sc), and fill factor (FF) of related solar cells. While the enhanced V oc can be ascribed to a lower HOMO level of the polymer by adding more fluorine substituents, the improvement in J sc and FF are likely due to suppressed charge recombination. While the reduced bimolecular recombination with raising fluorine concentration is confirmed by variable light intensity studies, a plausibly suppressed geminate recombination is implied by the significantly increased change of dipole moment between the ground and excited states (Δμge) for these polymers as the number of fluorine substituents increases. Moreover, the 2F polymer (PBnDT-DTffBT) exhibits significantly more scattering in the in-plane lamellar stacking and out-of-plane π–π stacking directions, observed with GIWAXS. This indicates that the addition of fluorine leads to a more face-on polymer crystallite orientation with respect to the substrate, which could contribute to the suppressed charge recombination. R-SoXS also reveals that PBnDT-DTffBT has larger and purer polymer/fullerene domains. The higher domain purity is correlated with an observed decrease in PCBM miscibility in polymer, which drops from 21% (PBnDT-DTBT) to 12% (PBnDT-DTffBT). The disclosed “fluorine” impact not only explains the efficiency increase from 4% of PBnDT-DTBT (0F) to 7% with PBnDT-DTffBT (2F) but also suggests fluorine substitution should be generally considered in the future design of new polymers.
PDF
