Protein–protein interactions are central to many biological processes. A considerable challenge consists however in understanding and deciphering when and how proteins interact, and this can be ...particularly difficult when interactions are weak and transient. The site‐specific incorporation of unnatural amino acids (UAAs) that crosslink with nearby molecules in response to light provides a powerful tool for mapping transient protein–protein interactions and for defining the structure and topology of protein complexes both in vitro and in vivo. Complementary strategies consist in site‐specific incorporation of UAAs bearing electrophilic moieties that react with natural nucleophilic amino acids in a proximity‐dependent manner, thereby chemically stabilizing low‐affinity interactions and providing additional constraints on distances and geometries in protein complexes. Herein, we review how UAAs bearing fine‐tuned chemical moieties that react with proteins in their vicinity can be utilized to map, study, and characterize weak and transient protein–protein interactions in living systems.
Trapping transient protein–protein interactions: Site‐specific incorporation of unnatural amino acids bearing chemical groups that allow covalent crosslinking with molecules in their vicinity provides a powerful tool for mapping weak and transient protein–protein interactions and for defining the structure and topology of protein complexes both in vitro and in vivo.
This study investigated the effects of corruption and economic freedom on corporate leverage. We also evaluated how economic freedom shapes the effect of corruption on corporate leverage. Using a ...sample of Vietnamese firms covering a nine‐year period from 2010 to 2018, we find evidence that increased control of corruption has a significant positive impact on firm leverage, whereas the opposite is true for economic freedom. This effect is robust to alternative measures of control of corruption as well as advanced estimation methods, such as firm‐fixed effects and quantile regressions. Our results also reveal that the positive impact of corruption controls on corporate leverage is more pronounced for firms with high economic freedom. Econometrically, our findings indicate that firms with better control over corruption prefer debt financing, as demonstrated by their higher leverage ratio.
•Integrated building design is inherently a multi-objective optimization problem.•Recently, many multi-objective optimization algorithms have been developed.•The performance of seven multi-objective ...evolutionary are tested in solving a nZEB design case.•The performance of studied algorithms is ranked using six comparison criteria (two are novel).•1400–1800 were minimum required number of evaluations to stabilize optimization results.
Integrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently. Many multi-objective optimization algorithms have been developed; however few of them are tested in solving building design problems.
This paper compares performance of seven commonly-used multi-objective evolutionary optimization algorithms in solving the design problem of a nearly zero energy building (nZEB) where more than 1.610 solutions would be possible. The compared algorithms include a controlled non-dominated sorting genetic algorithm with a passive archive (pNSGA-II), a multi-objective particle swarm optimization (MOPSO), a two-phase optimization using the genetic algorithm (PR_GA), an elitist non-dominated sorting evolution strategy (ENSES), a multi-objective evolutionary algorithm based on the concept of epsilon dominance (evMOGA), a multi-objective differential evolution algorithm (spMODE-II), and a multi-objective dragonfly algorithm (MODA). Several criteria was used to compare performance of these algorithms.
In most cases, the quality of the obtained solutions was improved when the number of generations was increased. The optimization results of running each algorithm 20 times with gradually increasing number of evaluations indicated that the PR_GA algorithm had a high repeatability to explore a large area of the solution-space and achieved close-to-optimal solutions with a good diversity, followed by the pNSGA-II, evMOGA and spMODE-II. Uncompetitive results were achieved by the ENSES, MOPSO and MODA in most running cases. The study also found that 1400–1800 were minimum required number of evaluations to stabilize optimization results of the building energy model.
•Building design optimization techniques are described.•Advances and obstacles in building design optimization are outlined.•Bibliographic information related to building design optimization is ...analyzed.•New research directions are introduced.
Recent progress in computer science and stringent requirements of the design of “greener” buildings put forwards the research and applications of simulation-based optimization methods in the building sector. This paper provides an overview on this subject, aiming at clarifying recent advances and outlining potential challenges and obstacles in building design optimization. Key discussions are focused on handling discontinuous multi-modal building optimization problems, the performance and selection of optimization algorithms, multi-objective optimization, the application of surrogate models, optimization under uncertainty and the propagation of optimization techniques into real-world design challenges. This paper also gives bibliographic information on the issues of simulation programs, optimization tools, efficiency of optimization methods, and trends in optimization studies. The review indicates that future researches should be oriented towards improving the efficiency of search techniques and approximation methods (surrogate models) for large-scale building optimization problems; and reducing time and effort for such activities. Further effort is also required to quantify the robustness in optimal solutions so as to improve building performance stability.
In this study, manganese ferrite-graphene oxide (MFO-GO) nanocomposites were prepared
via
a co-precipitation reaction of Fe
3+
and Mn
2+
ions in a GO suspension. The effects of graphene oxide on the ...physicochemical characteristics, magnetic properties and adsorption activities of the MFO-GO nanocomposites were studied. Methylene blue (MB) and arsenic(
v
) were used in this study as model water pollutants. With an increase in the GO content in the range of 10 wt% to 50 wt%, the removal efficiency for both MB dye and arsenic(
v
) ions was improved. Our adsorption data revealed that the adsorption behavior of MB dye showed good agreement with the Langmuir isotherm model and pseudo-second-order equation, whereas the Freundlich isotherm model was more suitable for simulating the adsorption process of arsenic(
v
) ions on the MFO-GO nanocomposites. In addition, an important role of the GO content in the adsorption mechanisms of both MB dye and arsenic(
v
) ions was found, in which GO nanosheets play a key role in the mechanisms of electrostatic/ionic interactions, oxygen-containing groups and π-π conjugation in the case of the adsorption of MB dye, whereas the role of the GO content is mainly related to the mechanism of electrostatic/ionic interactions in the case of the adsorption of arsenic(
v
). Graphene oxide has the functions of increasing the number of active binding sites comprising oxygen-containing functional groups, reducing the agglomeration of MFO nanoparticles, increasing the number of adsorption sites, and improving the electrostatic/ionic interactions between adsorbents and adsorbates in order to enhance the adsorption performance of cationic organic dyes and/or heavy metal anions from aqueous solutions.
In this study, manganese ferrite-graphene oxide (MFO-GO) nanocomposites were prepared
via
a co-precipitation reaction of Fe
3+
and Mn
2+
ions in a GO suspension.
► A novel survey of intelligent energy buildings in the theme of activity recognition. ► We define new metrics and ways to compare the various studies. ► We determine the most valued activities for ...each subsystem (HVAC, light, plug loads). ► The most appropriate activity recognition technologies and approaches are discussed. ► We emphasize the principles of energy intelligent buildings based on user activity.
Occupant presence and behaviour in buildings has been shown to have large impact on heating, cooling and ventilation demand, energy consumption of lighting and appliances, and building controls. Energy-unaware behaviour can add one-third to a building's designed energy performance. Consequently, user activity and behaviour is considered as a key element and has long been used for control of various devices such as artificial light, heating, ventilation, and air conditioning. However, how are user activity and behaviour taken into account? What are the most valuable activities or behaviours and what is their impact on energy saving potential? In order to answer these questions, we provide a novel survey of prominent international intelligent buildings research efforts with the theme of energy saving and user activity recognition. We devise new metrics to compare the existing studies. Through the survey, we determine the most valuable activities and behaviours and their impact on energy saving potential for each of the three main subsystems, i.e., HVAC, light, and plug loads. The most promising and appropriate activity recognition technologies and approaches are discussed thus allowing us to conclude with principles and perspectives for energy intelligent buildings based on user activity.
Nanofluids have gained significant popularity in the field of sustainable and renewable energy systems. The heat transfer capacity of the working fluid has a huge impact on the efficiency of the ...renewable energy system. The addition of a small amount of high thermal conductivity solid nanoparticles to a base fluid improves heat transfer. Even though a large amount of research data is available in the literature, some results are contradictory. Many influencing factors, as well as nonlinearity and refutations, make nanofluid research highly challenging and obstruct its potentially valuable uses. On the other hand, data-driven machine learning techniques would be very useful in nanofluid research for forecasting thermophysical features and heat transfer rate, identifying the most influential factors, and assessing the efficiencies of different renewable energy systems. The primary aim of this review study is to look at the features and applications of different machine learning techniques employed in the nanofluid-based renewable energy system, as well as to reveal new developments in machine learning research. A variety of modern machine learning algorithms for nanofluid-based heat transfer studies in renewable and sustainable energy systems are examined, along with their advantages and disadvantages. Artificial neural networks-based model prediction using contemporary commercial software is simple to develop and the most popular. The prognostic capacity may be further improved by combining a marine predator algorithm, genetic algorithm, swarm intelligence optimization, and other intelligent optimization approaches. In addition to the well-known neural networks and fuzzy- and gene-based machine learning techniques, newer ensemble machine learning techniques such as Boosted regression techniques, K-means, K-nearest neighbor (KNN), CatBoost, and XGBoost are gaining popularity due to their improved architectures and adaptabilities to diverse data types. The regularly used neural networks and fuzzy-based algorithms are mostly black-box methods, with the user having little or no understanding of how they function. This is the reason for concern, and ethical artificial intelligence is required.
Stigma poses considerable challenges to the mental health of people living with HIV who use drugs (PLHWUD). In this study, we explored factors related to different types of stigma (perceived and ...internalized) attached to layered stigmatizing characters (HIV and drug use) and their mental health influences on PLHWUD. The study used baseline data of an ongoing randomized controlled trial among 241 PLHWUD recruited between March and December 2018 in Vietnam. A structural equation model was used to assess the relationships among different types and layers of stigma and mental health status. Both perceived and internalized drug-related stigma measures were significantly higher than their corresponding HIV-related stigma. HIV-related stigma was negatively associated with mental health status; however, we did not find a significant relationship between drug-related stigma and mental health. Tailored intervention strategies in consideration of types and layers of stigma are needed to address stigma-related challenges faced by PLHWUD.
This study aimed to measure the exposure of residents to health education messages about non-communicable diseases (NCD)-related risk factors, and activities of village health workers (VHWs) in NCDs ...prevention and control in the mountainous setting of Vietnam. A cross-sectional study was performed in Dap Thanh commune (Ba Che, Quang Ninh province, Vietnam), a mountainous area. There were 151 residents aged 18 years or above recruited for this study. Information regarding exposure to messages about risk factors of NCDs, and activities of VHWs was collected via face-to-face interviews using a structured questionnaire. Multivariate logistic regression was employed to identify associated factors with exposing messages about NCD-related risk factors. The majority of participants heard about messages related to risk factors of NCDs in the last 30 days, from 56.3% (physical inactivity message), 59.6% (diet message), 75.5% (alcohol use message) to 79.5% (smoking message). Radio/television was the most common source of the messages (from 91.8% to 95.8%) and the majority of participants heard these messages from one source (from 77.1% to 80.9%). Most of sample reported the unavailability of VHWs in their locals (53.6%). Among locals having VHWs, health communication and education was the most common service provided (54.3%); however, only 30% received NCD management services. Participants who had other jobs were less likely to hear about diet-related messages (OR = 0.32; 95%CI = 0.11-0.92), and those ever smoking were more likely to hear these messages in the last 30 days (OR = 6.86; 95%CI = 1.06-44.51). People who had diabetes mellitus were more likely to hear physical activity-related messages in the last 30 days (OR = 2.55; 95%CI = 1.20-5.41). Our findings indicated that health communication regarding risk factors of NCDs in mountainous areas in Vietnam was insufficient, and the role of health workers as formal information source was not recognized. Efforts should be made to increase the capacity and involvement of VHWs in health education and NCD prevention in mountainous regions.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In this work, a series of unsaturated polyester resin (UPRs)/electrochemically exfoliated graphene oxide (e-GO) polymer nanocomposites with different ratios of e-GO (0.05, 0.1, 0.15, and 0.2 wt%) ...were prepared
via
an
in situ
polymerization method. The surface morphology and structural and chemical properties of the original UPR and UPR/e-GO nanocomposites were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and fourier transform infrared spectroscopy (FTIR). The positive influence of e-GO nanosheets on the mechanical properties, thermal stability, and anti-UV aging performance of UPR/e-GO nanocomposites was demonstrated by thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA). The obtained results showed that the incorporation of e-GO nanosheets within the UPR matrix, despite the addition of e-GO at as low as 0.2 wt% comprehensively improves the advanced functional properties of UPR/e-GO nanocomposites as compared to the original UPR. In addition, artificial weathering testing of quartz-based artificial stone using UPR/e-GO 0.2 wt% showed excellent UV-resistant efficiency, supporting the use of e-GO nanosheets as an additive in manufacturing the industrial-scale UPRs-based artificial quartz stone samples for real outdoor applications.
Preparation of UPR/e-GO polymer nanocomposites for anti-UV aging application in quartz-based artificial stone.
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