The Emerging Regulatory Role of Circular RNAs in Periodontal Tissues and Cells

Periodontitis is a chronic complex inflammatory disease associated with a destructive host immune response to microbial dysbiosis, leading to irreversible loss of tooth-supporting tissues. Regeneration of functional periodontal soft (periodontal ligament and gingiva) and hard tissue components (cementum and alveolar bone) to replace lost tissues is the ultimate goal of periodontal treatment, but clinically predictable treatments are lacking. Similarly, the identification of biomarkers that can be used to accurately diagnose periodontitis activity is lacking. A relatively novel category of molecules found in oral tissue, circular RNAs (circRNAs) are single-stranded endogenous, long, non-coding RNA molecules, with covalently circular-closed structures without a 5’ cap and a 3’ tail via non-classic backsplicing. Emerging research indicates that circRNAs are tissue and disease-specific expressed and have crucial regulatory functions in various diseases. CircRNAs can function as microRNA or RNA binding sites or can regulate mRNA. In this review, we explore the biogenesis and function of circRNAs in the context of the emerging role of circRNAs in periodontitis pathogenesis and the differentiation of periodontal cells. CircMAP3K11, circCDK8, circCDR1as, circ_0062491, and circ_0095812 are associated with pathological periodontitis tissues. Furthermore, circRNAs are expressed in periodontal cells in a cell-specific manner. They can function as microRNA sponges and can form circRNA–miRNA–mRNA networks during osteogenic differentiation for periodontal-tissue (or dental pulp)-derived progenitor cells.     

A Terahertz Video Camera Patch Sheet with an Adjustable Design based on Self-Aligned, 2D,Suspended Sensor Array Patterning

Terahertz (THz) imaging is expected to become powerful tools for non-destructive inspections. To ensure the practical use of THz non-destructive monitoring, versatile THz imagers with adjustable designs that can eliminate the complexities and the bulkiness of the device are urgently required. Herein, a self-aligned filtration process for a 2D, free-standing carbon nanotube film array and its application to a THz video camera patch are reported. The presented techniques enable a) to freely design the camera size, sensor array pattern, and suspended shape according to its applications, b) to cut the camera patch into desired shapes, and c) to attach them to the objects that are intended to be measured. Real-time, non-destructive monitoring of various infrastructures is demonstrated. These results indicate that it can function regardless of restrictions, such as the shapes and locations of the measurement samples, thus providing a strong possibility for use in future non-destructive sensor networks.     

Various density light field image coding based on distortion minimization interpolation

In recent years, the light field (LF) as a new imaging modality has attracted wide interest. The large data volume of LF images poses great challenge to LF image coding, and the LF images captured by different devices show significant differences in angular domain. In this paper we propose a view prediction framework to handle LF image coding with various sampling density. All LF images are represented as view arrays. We first partition the views into reference view (RV) set and intermediate view (IV) set. The RVs are rearranged into a pseudo sequence and directly compressed by a video encoder. Other views are then predicted by the RVs. To exploit the four dimensional signal structure, we propose the linear approximation prior (LAP) to reveal the correlation among LF views and efficiently remove the LF data redundancy. Based on the LAP, a distortion minimization interpolation (DMI) method is used to predict IVs. To robustly handle the LF images with different sampling density, we propose an Iteratively Updating depth image based rendering (IU-DIBR) method to extend our DMI. Some auxiliary views are generated to cover the target region and then the DMI calculates reconstruction coefficients for the IVs. Different view partition patterns are also explored. Extensive experiments on different types LF images also valid the efficiency of the proposed method.     

Environmental impact estimation of ceramic lightweight aggregates production starting from residues

Within a circular economy approach, this study investigates the environmental impact of lightweight aggregates (LWAs) produced starting from different mixes of different clays with brewery sludge and cattle bone flour ash (CBA), used as poring and fertilizing agents, respectively. The environmental impact was evaluated by means of release tests, insulation capacity, carbon footprint (CFP), and particulate matter emission during pellet firing. Release tests representative of LWAs realistic application showed very high release of phosphate and satisfactory release of potassium. The thermal insulation of the LWAs was tested by thermal imaging camera and resulted highly variable depending on the composition, with the mix containing CBA performing best. This latter composition leads also to the smallest CO₂ equivalent emission, due to the calorific power of CBA, allowing lower consumption of fossil fuels during the LWA production. Finally, total particulate emissions during the thermal treatment resulted similar in terms of mass for all mixes, while differences in terms of particle morphology and composition occurred. Samples containing residue resulted with a quite good release behavior, CFP, and insulation properties, but higher emission of particles, particularly when glass is added.     

Supramolecular Zn(II)-Dipicolylamine-Azobenzene-Aminocyclodextrin-ATP Complex: Design and ATP Recognition in Water

Cyclodextrins (CyDs) are water-soluble host molecules possessing a nanosized hydrophobic cavity. In the realm of molecular recognition, this cavity is used not only as a recognition site but also as a reaction medium, where a hydrophobic sensor recognizes a guest molecule. Based on the latter concept, we have designed a novel supramolecular sensing system composed of Zn(II)-dipicolylamine metal complex-based azobenzene (1-Zn) and 3A-amino-3A-deoxy-(2AS,3AS)-γ-cyclodextrin (3-NH₂-γ-CyD) for sensing adenosine-5′-triphosphate (ATP). 1-Zn showed redshifts in the UV-Vis spectra and induced circular dichroism (ICD) only when both ATP and 3-NH₂-γ-CyD were present. Calculations of equilibrium constants indicated that the amino group of 3-NH₂-γ-CyD was involved in the formation of supramolecular 1-Zn/3-NH₂-γ-CyD/ATP. The Job plot of the ICD spectral response revealed that the stoichiometry of 1-Zn/3-NH₂-γ-CyD/ATP was 2:1:1. The pH effect was examined and 1-Zn/3-NH₂-γ-CyD/ATP was most stable in the neutral condition. The NOESY spectrum suggested the localization of 1-Zn in the 3-NH₂-γ-CyD cavity. Based on the obtained results, the metal coordination interaction of 1-Zn and the electrostatic interaction of 3-NH₂-γ-CyD were found to take place for ATP recognition. The “reaction medium approach” enabled us to develop a supramolecular sensing system that undergoes multi-point interactions in water. This study is the first step in the design of a selective sensing system based on a good understanding of supramolecular structures.     

Electrical and optical characteristics of atmospheric helium jet array plasma

In this paper, a honeycomb structure jet array with seven jet units was adopted to generate plasmas. Both the average discharge power and the emission intensity of the main excited species increase with increasing applied voltage. There are three stages of discharge evolution at different applied voltages: initial discharge, uniform discharge and strong coupling discharge.The spatial distribution of the emission intensity of the excited species can be divided into three categories: growth class, weakening class and variation class. The gas temperature along the whole plasma plume at different applied voltages is maintained at around 320K and can be widely used in heat-labile applications.     

Challenges in supply chain redesign for the Circular Economy: a literature review and a multiple case study

Despite companies face several challenges when redesigning their supply chain for the Circular Economy, the literature lacks a systematisation of such challenges and of the ways to overcome them. Through a systematic literature review, this paper identifies and systematises 24 challenges that may hamper a supply chain redesign for the Circular Economy. Sixteen among these challenges are well known from research in related topics. On the contrary, the remaining eight are relatively new or take a different relevance within the Circular Economy context. A multiple case study in the household appliance supply chain is carried out, to explore how these challenges appear in practice and how companies may tackle them. The cases analysed involve actors at different supply chain levels, and findings suggest that a great degree of vertical integration by one actor in the supply chain is not a necessary condition for Circular Economy implementation. The empirical study, in conjunction with the literature analysis, leads to the development of a framework linking the challenges to specific levers that companies may pursue to overcome them. The framework can be seen as a reference for managers undertaking the path towards Circular Economy.     

Nonuniform linear array DOA estimation using EM criterion

In this letter, we address the problem of Direction of Arrival (DOA) estimation with nonuniform linear array in the context of sparse Bayesian learning (SBL) framework. The nonuniform array output is deemed as an incomplete-data observation, and a hypothetical uniform linear array output is treated as an unavailable complete-data observation. Then the Expectation-Maximization (EM) criterion is directly utilized to iteratively maximize the expected value of the complete-data log likelihood under the posterior distribution of the latent variable. The novelties of the proposed method lie in its capability of interpolating the actual received data to a virtual uniform linear array, therefore extending the achievable array aperture. Simulation results manifests the superiority of the proposed method over off-the-shelf algorithms, specially on circumstances such as low SNR, insufficient snapshots, and spatially adjacent sources.     

Channel estimation and tracking with nested sampling for fast-moving users in millimeter-wave communication

Channel estimation is very challenging in millimeter-wave (mmWave) communications since the receiver is usually equipped with a limited number of radio-frequency (RF) chains and a large number of antennas. The receiver can only observe a low-dimensional projection of the received signals due to the huge gap between the numbers of RF chains and antennas. Instead of using the phase-shifter which is not a simple circuit at mmWave, we employ a switch network for analog design, which is equivalent to an antenna selection process. To increase the resolution and accuracy, a nested sampling strategy is used to formulate a virtual array with a larger aperture, aiming to reduce the complexity and power consumption of the system. We also consider the Doppler effect caused by the fast-moving user which may seriously deteriorate the channel estimation accuracy. Based on the covariance fitting criterion, a joint Doppler and channel estimation method is proposed without need of discretizing the angle space, and thus the model mismatch effect can be totally eliminated. Finally, we excavate the temporal variation law of the user to estimate the line-of-sight (LoS) channel in the current time slot by using the estimates from the previous two time slots. Numerical simulation results are provided to demonstrate the effectiveness and superiority of our proposed method.