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 paper presents a novel smoothing gradient damage model, which goes beyond certain limitations of conventional methods, for accurate prediction of localized failure in quasi-brittle materials. ...The proposed method is particularly tailored to low-order finite elements such as 4-node quadrilateral or 3-node triangular elements. The low-order elements are preferable in practice as they can automatically be generated for problems even with complex geometries at low computational cost. In order to eliminate spurious damage growth and correct wrong prediction of shear band induced by using the constant gradient parameter in terms of conventional models, we thus introduce a novel modified evolving anisotropic nonlocal gradient parameter, which aims to control the behavior of nonlocal interactions of damage microprocess during the entire loading history in a more appropriate manner. Unlike conventional approaches, the novel modified evolving gradient parameter heavily depends on the principal stress and equivalent strain states, which serves to reduce the impact of localized deformation. The stress fields thus play a crucial role in the present formulation as they greatly affect the orientation and intensity of nonlocal interactions. The quality of raw stresses becomes critical (e.g., stress oscillation) once two unknowns (i.e., displacements and nonlocal equivalent strain) are approximated simultaneously using the same orders of interpolation functions (e.g., linear-linear). A smoothing technique is thus adopted to smooth out the raw stresses. The stresses after smoothing are shown adequately in the estimation of the new gradient parameter, providing much better solutions. In addition, to precisely capture the softening in quasi-brittle materials, the original energy norm is decomposed into tensile and compressive parts to form a new bi-energy norm. The scalar equivalent strain is thus estimated through this new bi-energy norm, which is obviously able to distinguish tensile and compressive conditions. To further enhance the capability of the present damage model, the material softening process is also determined through fracture energy in terms of fracture mechanics. Comparison of the present results with reference solutions derived from experimental data and other numerical methods for benchmark applications, regarding the nonlocal equivalent strain, damage profile, structural force-displacement curves, etc., confirms the accuracy and superior performance of the proposed approach for characterizing localized failure in quasi-brittle materials.
The escalating burden of diabetes is increasing the risk of contracting tuberculosis (TB) and has a pervasive impact on TB treatment outcomes. Therefore, we conducted this systematic review and ...meta-analysis to examine the burden of diabetes among TB patients and assess its impact on TB treatment in South Asia (Afghanistan, Bangladesh, Bhutan, Maldives, Nepal, India, Pakistan, and Sri Lanka). PubMed, Excerpta Medica Database (EMBASE), and CINAHL databases were systematically searched for observational (cross-sectional, case-control and cohort) studies that reported prevalence of diabetes in TB patients and published between 1 January 1980 and 30 July 2020. A random-effect model for computing the pooled prevalence of diabetes and a fixed-effect model for assessing its impact on TB treatment were used. The review was registered with PROSPERO number CRD42020167896. Of the 3463 identified studies, a total of 74 studies (47 studies from India, 10 from Pakistan, four from Nepal and two from both Bangladesh and Sri-Lanka) were included in this systematic review: 65 studies for the prevalence of diabetes among TB patients and nine studies for the impact of diabetes on TB treatment outcomes. The pooled prevalence of diabetes in TB patients was 21% (95% CI 18.0, 23.0; I2 98.3%), varying from 11% in Bangladesh to 24% in Sri-Lanka. The prevalence was higher in studies having a sample size less than 300 (23%, 95% CI 18.0, 27.0), studies conducted in adults (21%, 95% CI 18.0, 23.0) and countries with high TB burden (21%, 95% CI 19.0, 24.0). Publication bias was detected based on the graphic asymmetry of the funnel plot and Egger's test (p < 0.001). Compared with non-diabetic TB patients, patients with TB and diabetes were associated with higher odds of mortality (Odds Ratio (OR) 1.7; 95% CI 1.2, 2.51; I2 19.4%) and treatment failure (OR 1.7; 95% CI 1.1, 2.4; I2 49.6%), but not associated with Multi-drug resistant TB (OR 1.0; 95% CI 0.6, 1.7; I2 40.7%). This study found a high burden of diabetes among TB patients in South Asia. Patients with TB-diabetes were at higher risk of treatment failure and mortality compared to TB alone. Screening for diabetes among TB patients along with planning and implementation of preventive and curative strategies for both TB and diabetes are urgently needed.
► 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.
In this study, we investigate the intial value problem (IVP) for a time-fractional fourth-order equation with nonlinear source terms. More specifically, we consider the time-fractional biharmonic ...with exponential nonlinearity and the time-fractional Cahn–Hilliard equation. By using the Fourier transform concept, the generalized formula for the mild solution as well as the smoothing effects of resolvent operators are proved. For the IVP associated with the first one, by using the Orlicz space with the function $\Xi (z)={\textrm {e}}^{|z|^{p}}-1$ and some embeddings between it and the usual Lebesgue spaces, we prove that the solution is a global-in-time solution or it shall blow up in a finite time if the initial value is regular. In the case of singular initial data, the local-in-time/global-in-time existence and uniqueness are derived. Also, the regularity of the mild solution is investigated. For the IVP associated with the second one, some modifications to the generalized formula are made to deal with the nonlinear term. We also establish some important estimates for the derivatives of resolvent operators, they are the basis for using the Picard sequence to prove the local-in-time existence of the solution.
•A novel method for text-independent writer identification.•Organization of training samples for Convolutional Neural Network.•Feature aggregation to form global features from local features.•99.97% ...accuracy to classify 100 writers by 200 characters for handwritten Japanese.•91.81% accuracy to classify 900 writers by one text page for handwritten English.
The text-independent approach to writer identification does not require the writer to write some predetermined text. Previous research on text-independent writer identification has been based on identifying writer-specific features designed by experts. However, in the last decade, deep learning methods have been successfully applied to learn features from data automatically. We propose here an end-to-end deep-learning method for text-independent writer identification that does not require prior identification of features. A Convolutional Neural Network (CNN) is trained initially to extract local features, which represent characteristics of individual handwriting in the whole character images and their sub-regions. Randomly sampled tuples of images from the training set are used to train the CNN and aggregate the extracted local features of images from the tuples to form global features. For every training epoch, the process of randomly sampling tuples is repeated, which is equivalent to a large number of training patterns being prepared for training the CNN for text-independent writer identification. We conducted experiments on the JEITA-HP database of offline handwritten Japanese character patterns. With 200 characters, our method achieved an accuracy of 99.97% to classify 100 writers. Even when using 50 characters for 100 writers or 100 characters for 400 writers, our method achieved accuracy levels of 92.80% or 93.82%, respectively. We conducted further experiments on the Firemaker and IAM databases of offline handwritten English text. Using only one page per writer to train, our method achieved over 91.81% accuracy to classify 900 writers. Overall, we achieved a better performance than the previously published best result based on handcrafted features and clustering algorithms, which demonstrates the effectiveness of our method for handwritten English text also.
Many high-throughput experiments compare two phenotypes such as disease vs. healthy, with the goal of understanding the underlying biological phenomena characterizing the given phenotype. Because of ...the importance of this type of analysis, more than 70 pathway analysis methods have been proposed so far. These can be categorized into two main categories: non-topology-based (non-TB) and topology-based (TB). Although some review papers discuss this topic from different aspects, there is no systematic, large-scale assessment of such methods. Furthermore, the majority of the pathway analysis approaches rely on the assumption of uniformity of p values under the null hypothesis, which is often not true.
This article presents the most comprehensive comparative study on pathway analysis methods available to date. We compare the actual performance of 13 widely used pathway analysis methods in over 1085 analyses. These comparisons were performed using 2601 samples from 75 human disease data sets and 121 samples from 11 knockout mouse data sets. In addition, we investigate the extent to which each method is biased under the null hypothesis. Together, these data and results constitute a reliable benchmark against which future pathway analysis methods could and should be tested.
Overall, the result shows that no method is perfect. In general, TB methods appear to perform better than non-TB methods. This is somewhat expected since the TB methods take into consideration the structure of the pathway which is meant to describe the underlying phenomena. We also discover that most, if not all, listed approaches are biased and can produce skewed results under the null.
In this paper, an efficient computational approach based on refined plate theory (RPT) including the thickness stretching effect, namely quasi-3D theory, in conjunction with isogeometric formulation ...(IGA) is proposed for the size-dependent bending, free vibration and buckling analysis of functionally graded nanoplate structures. The present novel quasi-3D theory not only possesses 4 variables as refined plate theory but also accounts for both shear deformation and stretching effect without any requirement of shear correction factors (SCFs). The size-dependent effect is taken into account by nonlocal elasticity theory. Isogeometric analysis shows a great advantage in dealing with the high continuity and high order derivative requirements of the displacement fields used in quasi-3D and nonlocal theory. The reliability and accuracy of the present method are ascertained by comparing the obtained results with other published ones. Numerical examples are also performed to show the significance of nonlocal effect, material distribution profile, aspect ratios and boundary conditions on the behaviour of FGM nanoplates.
•We present an efficient computational approach for size-dependent behaviour of FGM nanoplates.•Both shear deformation and thickness stretching effect are taken into account by a novel quasi-3D theory with only 4 variables.•Nonlocal theory that requires third order derivatives of displacement variables is used to capture the size-dependent effect.•NURBS-based isogeometric analysis can handle properly the high-order derivative requirements.•The numerical results show reliability and effectiveness of the present method.
•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.
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