Application of Natural Clinoptilolite for Ammonium Removal from Sludge Water

Sludge water (SW) arising from the dewatering of anaerobic digested sludge causes high back loads of ammonium, leading to high stress (inhibition of the activity of microorganisms by an oversupply of nitrogen compounds (substrate inhibition)) for wastewater treatment plants (WWTP). On the other hand, ammonium is a valuable resource to substitute ammonia from the energy intensive Haber-Bosch process for fertilizer production. Within this work, it was investigated to what extent and under which conditions Carpathian clinoptilolite powder (CCP 20) can be used to remove ammonium from SW and to recover it. Two different SW, originating from municipal WWTPs were investigated (SW1: c₀ = 967 mg/L NH₄-N, municipal wastewater; SW2: c₀ = 718–927 mg/L NH₄-N, large industrial wastewater share). The highest loading was achieved at 307 K with 16.1 mg/g (SW1) and 15.3 mg/g (SW2) at 295 K. Kinetic studies with different specific dosages (0.05 g_CLI/mg_NH4-N), temperatures (283–307 K) and pre-loaded CCP 20 (0–11.4 mg/g) were conducted. At a higher temperature a higher load was achieved. Already after 30 min contact time, regardless of the sludge water, a high load up to 7.15 mg/g at 307 K was reached, achieving equilibrium after 120 min. Pre-loaded sorbent could be further loaded with ammonium when it was recontacted with the SW.     

Scale-space point spread function based framework to boost infrared target detection algorithms

Small target detection is one of the major concern in the development of infrared surveillance systems. Detection algorithms based on Gaussian target modeling have attracted most attention from researchers in this field. However, the lack of accurate target modeling limits the performance of this type of infrared small target detection algorithms. In this paper, signal to clutter ratio (SCR) improvement mechanism based on the matched filter is described in detail and effect of Point Spread Function (PSF) on the intensity and spatial distribution of the target pixels is clarified comprehensively. In the following, a new parametric model for small infrared targets is developed based on the PSF of imaging system which can be considered as a matched filter. Based on this model, a new framework to boost model-based infrared target detection algorithms is presented. In order to show the performance of this new framework, the proposed model is adopted in Laplacian scale-space algorithms which is a well-known algorithm in the small infrared target detection field. Simulation results show that the proposed framework has better detection performance in comparison with the Gaussian one and improves the overall performance of IRST system. By analyzing the performance of the proposed algorithm based on this new framework in a quantitative manner, this new framework shows at least 20% improvement in the output SCR values in comparison with Laplacian of Gaussian (LoG) algorithm.     

WSANs中基于蜂巢结构的移动容错恢复算法

旨在研究无线传感器与执行器网络(WSANs)中节点失效情况下恢复执行器(actor)节点服务的算法. 首先说明了WSANs中的实时覆盖模型, 证明WSANs覆盖恢复问题是NP难问题, 给出了近似求解方案. 在此基础上, 提出了一种基于六边形蜂巢结构的移动容错算法HMFR用于恢复失效actor节点, HMFR 算法在限制网络初始部署的条件下拥有很好的性能. 通过实验与现有的恢复算法进行比较, 发现HMFR算法在actor覆盖sensor节点数和移动距离方面有更好的性能.     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

Evaluating the accuracy of ESR dose determination of pseudo-Early Pleistocene fossil tooth enamel samples using dose recovery tests

In ESR dating of Early Pleistocene fossil tooth enamel samples, the fitting function used for the evaluation of the D_E value is undoubtedly among the major sources of uncertainty. Dose recovery tests performed on fossil tooth enamel showing D_E values >1,000 Gy demonstrate: (i) that high precision ESR measurements (<0.5%) and high D_E reproducibility (<5%) may be achieved; (ii) the appropriateness of the Double Saturating Exponential (DSE) fitting function for ESR dose reconstruction. In contrast, the SSE function, which has been almost exclusively used so far, does simply not correctly describe the behavior of the radiation induced ESR signal of tooth enamel with the dose.Several fitting functions and data weighting options were tested and the combination of a DSE with data weighted by the inverse of the squared intensities is the procedure providing the most accurate D_E results. However, the SSE may nevertheless sometimes produce consistent results if D_max does not exceed 6*D_E. Further work is required in that direction in order to determine more precisely in which conditions the SSE could be used as a fair approximation of the DSE function for these samples.     

Role of nickel and manganese in recovery of resistivity in iron-based alloys after low-temperature proton irradiation

This study investigates the recovery of electric resistivity in pure iron, Fe–0.6Ni and Fe–1.5Mn as related to isochronal annealing following 1 MeV proton irradiation at lower temperature than 70 K, focusing on the relationship between solute atoms and irradiation defects. Both nickel and manganese prevent stage I_D recovery, which corresponds to correlated recombination. Stage II recovery is also changed by the addition of a solute, which corresponds to the migration of small interstitial clusters. In both pure iron and Fe–0.6Ni, no evident difference was observed in the stage III region, which corresponds to the migration of vacancies. In contrast, two substages appeared in the Fe–1.5Mn at a higher temperature than stage III_B appeared in pure iron. These substages are considered to represent the release of irradiation-induced defects, which was trapped by manganese.     

Poly‐ε‐Lysine Modified Nanocarbon Film Electrodes for LPS Detection

We developed an electrochemical system for detecting lipopolysaccharide (LPS) that uses an ultraflat nanocarbon film electrode modified with poly‐ε‐lysine with a high affinity to LPS. LPS was captured on the modified electrode, and then ferrocene labeled polymyxin B (FcPMB) was captured on the LPS adsorbed electrode via the LPS‐PMB affinity interaction. The adsorbed FcPMB provided an amplified response with Fe²⁺ ions, and the current response was dependent on the amount of captured LPS (LOD=2.0 ng/mL). This was due to the efficient accumulation of the obtained current for LPS and the very low noise made possible by the ultraflat surface.     

Fluorescence Signal Amplification Strategies Based on DNA Nanotechnology for miRNA Detection

In this review,the most recent progresses in the field of fluorescence signal amplification strategies based on DNA nanotechnology for miRNA are summarized.The types of signal amplification are given and the principles of amplification strategies are explained,including rolling circle amplification(RCA),catalytic hairpin assembly(CHA),hybridization chain reaction(HCR)and DNA walker.Subsequently,the application of these signal amplification methods in biosensing and bioimaging are covered and described.Finally,the challenges and the outlook of fluorescence signal amplification methods for miRNA detection are briefly commented.     

Demystifying terms for understanding bioelectrochemical systems towards sustainable wastewater treatment

Bioelectrochemical systems (BESs) have been intensively studied in the past decade, but precise understanding of BESs performance is hindered by unclear definition of several key parameters. Herein, we analyze and discuss three sets of terms about conversion efficiency, energy performance, and pilot scale. It is suggested that ‘Coulombic recovery’ can avoid the misleading results because of different organic removals, compared with ‘Coulombic efficiency.’ Power density is not a suitable term to describe energy performance of BESs, and energy production/consumption should be reported in the energy unit such as kWh. Pilot-scale BESs should meet several criteria, including hydraulic capacity, use of actual wastewater, non-laboratory condition, and long-term operation. Proper use of those terms is strongly encouraged and will be critically important to BESs research and development.     

Nanostructures of noble metals as functional materials in biosensors

Recent advancement in nanoscience and nanotechnologies inspired a wide spectrum of uses of nanodimensional materials ranging from industrial sector to biomedical applications. Inorganic nanomaterials made of noble metals, which are corrosion-resistant, are often included as electrode modifiers in designing electrochemical chemosensors and biosensors because of their unique catalytic, electric, and surface-related properties. This review summarizes the developments in electrochemical biosensors with integrated in their architecture metal nanostructures reported mainly during the last two years with a summary on some of the commonly used methods for the synthesis of metallic nanostructures. Nanodimensional noble metal structures might be considered as multipurpose electrode modifiers because of their abilities to act at the same time as electrocatalysts, signal amplifiers, and tools for immobilization and spatial orientation of redox proteins/enzymes or other type of bioreceptors.