Unusual Two-Step Assembly of a Minimalistic Dipeptide-Based Functional Hypergelator

Self-assembled peptide hydrogels represent the realization of peptide nanotechnology into biomedical products. There is a continuous quest to identify the simplest building blocks and optimize their critical gelation concentration (CGC). Herein, a minimalistic, de novo dipeptide, Fmoc-Lys(Fmoc)-Asp, as an hydrogelator with the lowest CGC ever reported, almost fourfold lower as compared to that of a large hexadecapeptide previously described, is reported. The dipeptide self-assembles through an unusual and unprecedented two-step process as elucidated by solid-state NMR and molecular dynamics simulation. The hydrogel is cytocompatible and supports 2D/3D cell growth. Conductive composite gels composed of Fmoc-Lys(Fmoc)-Asp and a conductive polymer exhibit excellent DNA binding. Fmoc-Lys(Fmoc)-Asp exhibits the lowest CGC and highest mechanical properties when compared to a library of dipeptide analogues, thus validating the uniqueness of the molecular design which confers useful properties for various potential applications.     

A smart process controller framework for Industry 4.0 settings

This paper presents a smart supervisory framework for a single process controller, designed for Industry 4.0 shop floors. This digitization of a full supervisory suite for a single process controller enables self-awareness, self-diagnosis, self-prognosis, and self-healing (by definition, these "self" elements are missing from other supervisory frameworks diagnosing numerous controllers in parallel). The proposed framework is aligned with the concept of a Cyber Physical System (CPS), since its implementation generates a rich cyber physical entity of the controlled process. This CPS entity can either be considered as the process digital twin, or can provide a solid basis for generating it. Finally, the framework includes the main characteristics of Industry 4.0, such as advanced use of Artificial Intelligence (AI) and big data analysis. The framework is based on four modules: (1) Control and Awareness module—performing both continuous process control and adjustments, as well as machine learning (ML) and statistical process control (SPC) for identifying abnormalities that require further diagnosis; (2) Process -diagnosis module—performing continual (recurrent) analysis of the process state and trends; (3) Prognosis and Healing module—performing prognosis and automated intervention via parameter changes, re-configurations, and automated maintenance; (4) External Interaction Platform—an interactive module for interfacing with experts, presenting them with the process analysis information and obtaining feedback from them as part of a learning process. Using an implementation showcase to illustrate the methodological framework’s applicability, we demonstrate its real-world potential. The proposed framework could serve as a guide for implementing smart process control and maintenance systems in Industry 4.0 shop floors. It could also provide a firm basis for comparison with future suggested frameworks. Future research directions could include pursuing improvements to the proposed process control framework and validating the framework by case studies of its implementation.

     

长江重要堤防隐蔽工程建设投资对扩大内需、拉动经济的作用和影响

长江重要堤防隐蔽工程是党中央、国务院实施积极财政政策进行长江堤防建设的重要组成部分，隐蔽工程既是重要的基础设施，也是重要的环境保护工程，隐蔽工程与其他行业的关联性很强，对众多行业具有巨大的带动作用，有效地扩大了内需，拉动了经济增长。     

Dominant inheritance in two families with familial Mediterranean fever (FMF)

Familial Mediterranean fever (FMF) is an autosomal-recessive disease which affects almost exclusively people of Mediterranean and Middle Eastern origin. We examined the possibility of a dominant inheritance of FMF among our 3,000 patients in Israel. Two hundred forty FMF patients were members of 77 families in which the disease affected more than one generation. In 75 of these families the occurrence of FMF in more than one generation was found to be consistent with a recessive mode of inheritance due to a high gene frequency (q) and consanguinity among parents of the patients. In 2 families, one of Ashkenazi and the other of Georgian Iraqi origin, in which FMF occurred in 4 consecutive generations, the mode of inheritance could be explained only by autosomal-dominant inheritance.     

The Prominin-1-Derived Peptide Improves Cardiac Function Following Ischemia

Myocardial infarction (MI) remains the leading cause of death in the western world. Despite advancements in interventional revascularization technologies, many patients are not candidates for them due to comorbidities or lack of local resources. Non-invasive approaches to accelerate revascularization within ischemic tissues through angiogenesis by providing Vascular Endothelial Growth Factor (VEGF) in protein or gene form has been effective in animal models but not in humans likely due to its short half-life and systemic toxicity. Here, we tested the hypothesis that PR1P, a small VEGF binding peptide that we developed, which stabilizes and upregulates endogenous VEGF, could be used to improve outcome from MI in rodents. To test this hypothesis, we induced MI in mice and rats via left coronary artery ligation and then treated animals with every other day intraperitoneal PR1P or scrambled peptide for 14 days. Hemodynamic monitoring and echocardiography in mice and echocardiography in rats at 14 days showed PR1P significantly improved multiple functional markers of heart function, including stroke volume and cardiac output. Furthermore, molecular biology and histological analyses of tissue samples showed that systemic PR1P targeted, stabilized and upregulated endogenous VEGF within ischemic myocardium. We conclude that PR1P is a potential non-invasive candidate therapeutic for MI.     

Displaying a boundary in graphic and symbolic “wait” displays: Duration estimates and users’ preferences

Two experiments assessed the effect of displaying a boundary on duration estimates and preference ratings for dynamic displays that were shown while users waited for the system's response. Displays were either symbolic (changing numbers) or graphic (increasing rectangles) and could contain a boundary that indicated when the interval was expected to be over. Duration estimates were similar for symbolic and graphic displays and for displays with and without a boundary. However, when the displays were encountered successively, participants assessed the graphic displays as having shorter durations than the symbolic displays. Faster rates of change in both types of displays led to increased duration estimates. Although displaying a boundary did not affect duration estimates, participants preferred displays in which a boundary was shown and preferred the graphic displays over the symbolic displays. Hence, bounded graphic displays are recommended as “wait” displays for computerized applications.     

Over-Parameterized Variational Optical Flow

A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to the best results published so far.     

Incremental application of knowledge to continuously arriving time-oriented data

In our previous work, we introduced a computational architecture that effectively supports the tasks of continuous monitoring and of aggregation querying of complex domain meaningful time-oriented concepts and patterns (temporal abstractions), in environments featuring large volumes of continuously arriving and accumulating time-oriented raw data. Examples include provision of decision support in clinical medicine, making financial decisions, detecting anomalies and potential threats in communication networks, integrating intelligence information from multiple sources, etc. In this paper, we describe the general, domain-independent but task-specific problem-solving method underling our computational architecture, which we refer to as incremental knowledge-based temporal abstraction (IKBTA). The IKBTA method incrementally computes temporal abstractions by maintaining persistence and validity of continuously computed temporal abstractions from arriving time-stamped data. We focus on the computational framework underlying our reasoning method, provide well-defined semantic and knowledge requirements for incremental inference, which utilizes a logical model of time, data, and high-level abstract concepts, and provide a detailed analysis of the computational complexity of our approach.