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Rationale: Surface enhanced Raman scattering (SERS) is proving to be a useful tool for biomedical imaging. However, this imaging technique can suffer from poor signal-to-noise ratio, as the complexity of biological tissues can lead to overlapping of Raman bands from tissues and the Raman reporter molecule utilized. Methods: Herein we describe the synthesis of triple bond containing Raman reporters that scatter light in the biological silent window, between 1750 cm-1 and 2750 cm-1. Results: Our SERS nanoprobes are comprised of uniquely designed Raman reporters containing either alkyne- or cyano-functional groups, enabling them to be readily distinguished from background biological tissue. Conclusion: We identify promising candidates that eventually can be moved forward as Raman reporters in SERS nanoparticles for highly specific contrast-enhanced Raman-based disease or analyte detection in biological applications.

The massive penetration of Renewables into the energy mix and the existence of IoT-enabled Distributed Energy Resources (DERs) in the emerging smart grid, while a blessing towards de-carbonization, increase considerably the operations and planning functions of the grid. Cloud processing of IoT/DER data facilitates the deployment of various Demand-Response (DR) and other DER asset scenarios, the organization of distribution grids into Local Energy Markets (LEM) and the efficient computation of load forecasting and power flow. Cloud computing enables a plethora of service provisions to the grid including frequency response. The decentralized nature of DERs at the edge of the distribution grid requires nodal approaches for the computation of power grid congestion constraints and power flow solutions. We present here a cloud-edge continuum approach, anchored on the new generation of communications infrastructure, which expedites the computation time of the load and DER forecasting and optimal power flow calculations. The proposed approach allows the LEM operator to respond to Fast Frequency Response service procurement signals issued by the balancing authority requiring even sub-second latency for service settlement. The proposed cloud-edge architecture has been tested on the IEEE European Low Voltage Benchmark model and provides scalability and elasticity for various DR/DER configurations. 1 BACKGROUND T HE massive penetration of Distributed Energy Resources (DERs) and the Internet of Things (IoT) devices in the grid, physically located everywhere, in all shapes and sizes, both in front (FTM) and behind the meter (BTM) are fundamentally changing the operating characteristics of the power grids. It also transforms the current electricity market architectures towards an hierarchical energy market model under which DERs can voluntarily participate simultaneously in multiple markets to maximize their value to the grid. The deployment of low latency 5G network along with the installment of vast amount of IoT devices enable assets at the edge of the distribution grid to participate in the wholesale energy markets by implementing [1]. The successful implementation of such hierarchical market architecture, under which transactions will take place across all levels in the supply chain, namely wholesale, retail, BTM and under the Transactive Energy (TE) paradigm requires the presence of a comprehensive and consistent set of market prices for various products and services such as energy, °). capacity, ancillary and grid network services [2]. In the emerging energy marketplace, cloud computing is expected to act as an enabler to future electricity markets, since it provides the necessary computational resources to process the vast volume of data from the IoT devices, coordinate the operation of DERs and offer scalability to the system. Effective control of the emerging smart grid will be made possible through ICT, intelligent terminal technology, industrial IoT and cloud computing. These technologies will enhance the effectiveness of Demand Response (DR) solutions by enabling electricity prices and control signals to be processed in real-time. DR schemes along with electric storage assets are expected to play a fundamental role in the successful integration of massive penetration of renewable energy assets in organized energy markets. However, the processing of massive amount of data in real-time is expected to increase the computational burden and is prone to communication delays, transmission failures and communication network imbalances. In this environment, single cloud computing might not be able to deal with the additional computational burden. Emerging edge computing combined with cloud computing in a "cloud continuum" is expected to enable IoT devices to unprecedented DER balancing ancillary services including frequency control in hard real-time. Edge computing provides computational resources at the edge of the grid, closer to terminal devices and users, and potentially relieves the pressure on cloud computing and the latency requirements of the communications network. The services that are getting substantial attention in the European Continental Synchronous Area in recent years are related to the standardization of Frequency

Multiplexed imaging of 8 molecular targets with SERS nanoprobes in mice reveals spatially heterogeneous tumor responses to immunotherapy. Multichannel image segmentation enables classification of the tumor regions into responders and naïve.

Results are presented of a systematic experimental investigation aiming to eliminate refractory organics from industrial effluents, of high and non-biodegradable organic load, by two Advanced Oxidation Processes (AOPs). Bench scale experiments were performed with real wastewater samples collected from a pesticides manufacturing plant, of varying TOC content (800-1820 mg/L), to investigate the effectiveness of boron-doped diamond (BDD) anodic oxidation (AO), of H2O2 photolysis with UV-C irradiation (H2O2/UV-C), and their combination (i.e. AO/H2O2/UV-C) on the total organic carbon (TOC) removal. The effect of main operating conditions was investigated for both processes, separately and in combination. In the case of AO, TOC and COD were removed at a rate of 36.4 mgC/h and 89.5 mgO2/L, by applying a current density of 100 mA/cm2 and a recirculation flow rate of 1400 mL/min. The H2O2/UV-C process achieved a TOC removal rate of 369 mgC/h and over 98% color removal after 4 h of treatment, when a single dose of 6 g/L H2O2 and 11.8 W/L of UVC irradiation dose were applied. Finally, the combined process (AO/H2O2/UV-C) led to a faster TOC abatement (534 mgC/h) and a higher color removal, after treating the wastewater with 77 mA/cm2 current density, 5.9 W/L UVC irradiation dose and ‘on-line’ dosing 15.7 g/L H2O2.

Results are presented from an ongoing R&D project, aiming at full utilization of dairy-industry effluents. Development of a membrane-based method is pursued, for treatment of digestate (after fermentation yielding bio-gas) to recover nutrients (N-NH4, P-PO4) and water for reuse/recycling or safe disposal. The performance is investigated herein of four commercial nanofiltration/ultra-low-pressure reverse osmosis membranes, employed in dead-end filtration mode, for nutrients recovery from solutions simulating the liquid digestate/effluent of an anaerobic membrane-bioreactor (AnMBR). Best-performing membranes, regarding nutrients’ rejection, were assessed within a sufficiently broad range of all key process parameters, including trans-membrane pressure and feed-composition. Further testing took place in a cross-flow set-up, simulating real operating conditions. For ~80% permeate recovery, the concentrate was significantly enriched in nutrients; i.e. compared to feed-solution, N-NH4 was concentrated twice, whereas P-PO4 was concentrated by 3- to 4-times. Research with real AnMBR effluent is on-going, for process improvements/optimization, mainly focusing on composition of concentrate/nutrients (for use in liquid fertilizers), membrane-fouling mitigation and quality of permeate/water for possible reuse.

Treated municipal wastewater is considered a valuable non-conventional water resource. However, a substantial number of wastewater treatment plants installed in the Mediterranean region have proven to be unsuccessful copies of systems operating in technolo-gically advanced countries. In addition to high operating and maintenance cost, these systems are often unsuited to address the local challenges of wastewater treatment. Therefore, treated municipal water is commonly under-exploited throughout the region. To address these challenges, the AQUACYCLE project aims to develop an eco-innovative wastewater treatment process scheme, comprised of anaerobic digestion, constructed wetlands and a solar photocatalytic reactor, for cost-effective treatment of urban wastewater and maximum environ-mental benefits. This paper presents the distinct features of the novel process scheme and the characteristics of three such demonstration units to be installed in Tunisia, Lebanon and Spain to test and validate the efficiency and cost-effectiveness of the hybrid system.

The fundamental changes in power systems have led to an increased complexity in their operation and control. Wide area monitoring systems (WAMS) are considered as a key solution in order to deal with these challenges. In this paper, a general description of WAMS is presented along with a literature review on the topic. Emphasis is given on documenting real up to date applications of WAMS in the European power network. Moreover, wide area damping control systems for power system oscillations are also presented. A description is provided of two innovative WAMS combined with damping control using FACTS devices and Battery Energy Energy Storage Systems (BESS) that are currently implemented in the European network.

As installed wind generation capacities increase, there is a need to model variability in wind generation in detail to analyse its impacts on power systems. Utilization of meteorological reanalysis data and stochastic simulation are possible approaches for modelling this variability. In this paper, a combination of these two approaches is used to model wind generation variability. Parameters for the model are determined based on measured wind speed data. The model is used to simulate wind generation from the level of a single offshore wind power plant to the aggregate onshore wind generation of western Denmark. The simulations are compared to two years of generation measurements on 15 min resolution. The results indicate that the model, combining reanalysis data and stochastic simulation, can successfully model wind generation variability on different geographical aggregation levels on sub-hourly resolution. It is shown that the addition of stochastic simulation to reanalysis data is required when modelling offshore wind generation and when analysing onshore wind in small geographical regions.

In order to improve patient survival and reduce the amount of unnecessary and traumatic biopsies, non-invasive detection of cancerous tumours is of imperative and urgent need. Multicellular tumour spheroids (MTS) can be used as an ex vivo cancer tumour model, to model in vivo nanoparticle (NP) uptake by the enhanced permeability and retention (EPR) effect. Surface enhanced spatially offset Raman spectroscopy (SESORS) combines both surface enhanced Raman spectroscopy (SERS) and spatially offset Raman spectroscopy (SORS) to yield enhanced Raman signals at much greater sub-surface levels. By utilizing a reporter that has an electronic transition in resonance with the laser frequency, surface enhanced resonance Raman scattering (SERRS) yields even greater enhancement in Raman signal. Using a handheld SORS spectrometer with back scattering optics, we demonstrate the detection of live breast cancer 3D multicellular tumour spheroids (MTS) containing SERRS active NPs through 15 mm of porcine tissue. False color 2D heat intensity maps were used to determine tumour model location. In addition, we demonstrate the tracking of SERRS-active NPs through porcine tissue to depths of up to 25 mm. This unprecedented performance is due to the use of red-shifted chalcogenpyrylium-based Raman reporters to demonstrate the novel technique of surface enhanced spatially offset resonance Raman spectroscopy (SESORRS) for the first time. Our results demonstrate a significant step forward in the ability to detect vibrational fingerprints from a tumour model at depth through tissue. Such an approach offers significant promise for the translation of NPs into clinical applications for non-invasive disease diagnostics based on this new chemical principle of measurement.

With increasing wind installations, there is a need to analyse wind generation variability in detail. This paper applies the reanalysis approach for modelling the variability; however, with two important additions. Firstly, high-resolution microscale data is combined with mesoscale reanalysis time series to model local variability in wind. Secondly, as there are often missing technical parameters in large-scale wind power plant datasets, machine learning is used to estimate the missing values. It is shown that such detailed modelling leads to more accurate simulations than a baseline model when compared to historical data from multiple European countries. In addition, applicability of the methodology for analysing future scenarios with changing wind installations is demonstrated.

This paper reports on the fabrication, characterization and testing of iron oxide nanoparticles – powdered activated carbon (PAC) composites for water treatment and PAC regeneration by Fenton reactions. Different wet impregnation procedures and iron loadings were assessed in terms of organic micropollutant adsorption, by using the pharmaceutical diclofenac (DCF) as model compound. The preparation of a ferrihydrite-impregnated PAC with low iron content (~40.7 mgFe/gPAC) and high BET surface area (1037 m2 g-1) was found to be the optimum, exhibiting excellent DCF adsorption capacity, similar to that of the original PAC (203 mgDCF/gPAC/Fe), with the adsorption isotherm satisfactorily fitted by both the Freundlich and Langmuir models. The regeneration of the ferrihydrite-PAC (Fe/PAC) indicated that the presence of iron-oxide nanoparticles is important for achieving a high regeneration efficiency by hydrogen peroxide, even at neutral pH. However, the solution pH had a significant effect on DCF uptake, being greater at acidic pH after the regeneration of the composite. Ongoing R&D is aimed at material optimization and testing in a novel hybrid process scheme developed in author’s laboratory, involving a continuous Fe/PAC – Fenton process in conjunction with a low pressure membrane separation process.&nbsp

Resonant chalcogenpyrylium nanotags demonstrate an exceptional surface enhanced Raman scattering (SERS) performance for use in SORS applications. Using surface enhanced spatially offset Raman spectroscopy (SESORS), nanotags modified with a chalcogenpyrylium dye were observed at concentrations as low as 1 pM through 5 mm of tissue. Calculated limits of detection suggest that these SERS nanotags can be detected at 104 fM using surface enhanced spatially offset resonance Raman scattering (SESORRS) demonstrating their potential for in vivo applications.

Through utilizing the depth penetration capabilities of SESORS, multiplexed imaging and classification of three singleplex nanotags and a triplex of nanotags within breast cancer tumour models is reported for the first time through depths of 10 mm using a handheld SORS instrument.

Jurgen Popp opened a general discussion of the paper by Roy Goodacre: What is the advantage of using SERS instead of ordinary Raman spectroscopy?

A Finite Element Model (FEM) of middle ear was used to simulate the pathology of otosclerosis (OS) and tympanosclerosis (TS). Several aspects regarding the two diseases were examined, the results of which are hereby presented, connecting OS and TS with significant hearing loss, depending on the position of the OS and TS plaque accordingly.