Search results for: tunable decoder

Authors: Siva Kumar Reddy, Anwesha Mukherjee, Abha Misra

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Excellent energy absorption capability in carbon nanotubes (CNT) is shown in their bulk structure that behaves like super compressible foam. Furthermore, a tunable mechanical behavior of CNT foam is achieved using several methods like changing the concentration of precursors, polymer impregnation, non covalent functionalization of CNT microstructure etc. Influence of magnetic field on compressive behavior of magnetic CNT demonstrated an enhanced peak stress and energy absorption capability, which does not require any surface and structural modification of the foam. This presentation discusses the mechanical behavior of micro porous CNT foam that is impregnated in magnetic field responsive fluid. Magnetic particles are dispersed in a nonmagnetic fluid so that alignment of both particles and CNT could play a crucial role in controlling the stiffness of the overall structure. It is revealed that the compressive behavior of CNT foam critically depends on the fluid viscosity as well as magnetic field intensity. Both peak Stress and energy absorption in CNT foam followed a power law behavior with the increase in the magnetic field intensity. However, in the absence of magnetic field, both peak stress and energy absorption capability of CNT foam presented a linear dependence on the fluid viscosity. Hence, this work demonstrates the role magnetic filed in controlling the mechanical behavior of the foams prepared at nanoscale.

Keywords: carbon nanotubes, magnetic field, energy absorption capability and viscosity

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Authors: Jiwuer Jilili, Iogann Tolbatov, Mousumi U. Kahaly

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Metal to insulator transition and interfacial magnetism of the LaNiO₃ based superlattice are main interest due to thickness dependent electronic response and tunable magnetic behavior. We investigate the structural, electronic, and magnetic properties of recently experimentally synthesized (LaNiO₃)n/(CaMnO₃)m superlattices with varying LaNiO₃ thickness using density functional theory. The effect of the on-site Coulomb interaction is discussed. In switching from zero to finite U value for Ni atoms, LaNiO₃ shows transitions from half-metallic to metallic character, while spinning ordering changes from paramagnetic to ferromagnetic (FM). For CaMnO₃, U < 3 eV on Mn atoms results in G-type anti-FM spin ordering whereas increasing U value yields FM ordering. In superlattices, metal to insulator transition was achieved with a reduction of LaNiO₃ thickness. The system with one layer of LaNiO₃ yields insulating character. Increasing LaNiO₃ to two layers and above results in the onset of the metallic character with a major contribution from Ni and Mn 3d eg states. Our results for interfacial ferromagnetism, induced Ni magnetic moments and novel antiferromagnetically coupled Ni atoms are consistent with the recent experimental findings. The possible origin of the emergent magnetism is proposed in terms of the exchange interaction and Anderson localization.

Keywords: density functional theory, interfacial magnetism, metal-insulator transition, Ni magnetism.

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Authors: Giovanni Meloni

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Recent results are presented from experiments carried out at the Advanced Light Source (ALS) at the Chemical Dynamics Beamline of Lawrence Berkeley National Laboratory using multiplexed synchrotron photoionization mass spectrometry. The reaction mixture and a buffer gas (He) are introduced through individually calibrated mass flow controllers into a quartz slow flow reactor held at constant pressure and temperature. The gaseous mixture effuses through a 650 μm pinhole into a 1.5 mm skimmer, forming a molecular beam that enters a differentially pumped ionizing chamber. The molecular beam is orthogonally intersected by a tunable synchrotron radiation produced by the ALS in the 8-11 eV energy range. Resultant ions are accelerated, collimated, and focused into an orthogonal time-of-flight mass spectrometer. Reaction species are identified by their mass-to-charge ratios and photoionization (PI) spectra. Comparison of experimental PI spectra with literature and/or simulated curves is routinely done to assure the identity of a given species. With the aid of electronic structure calculations, potential energy surface scans are performed, and Franck-Condon spectral simulations are obtained. Examples of these experiments are discussed, ranging from new intermediates characterization to reaction mechanisms elucidation and biofuels oxidation pathways identification.

Keywords: mass spectrometry, reaction intermediates, synchrotron photoionization, oxidation reactions

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Authors: Ibrahim Abdelfattah, Adel Ismail, Ahmed Helal, Mohamed Faisal

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Advanced oxidation technologies are an environment friendly approach for the remediation of industrial wastewaters. Here, one pot synthesis of mesoporous In₂O₃-TiO₂ nanocomposites at different In₂O₃ contents (0-3 wt%) have been synthesized through a facile sol-gel method to evaluate their photocatalytic performance for the degradation of the imazapyr herbicide and phenol under visible light and UV illumination compared with commercially available either Degussa P-25 or UV-100 Hombikat. The prepared mesoporous In₂O₃-TiO₂ nanocomposites were characterized by TEM, STEM, XRD, Raman FT-IR, Raman spectra and diffuse reflectance UV-visible. The bandgap energy of the prepared photocatalysts was derived from the diffuse reflectance spectra. XRD Raman's spectra confirmed that highly crystalline anatase TiO₂ phase was formed. TEM images show TiO₂ particles are quite uniform with 10±2 nm sizes with mesoporous structure. The mesoporous TiO₂ exhibits large pore volumes of 0.267 cm³g⁻¹ and high surface areas of 178 m²g⁻¹, but they become reduced to 0.211 cm³g⁻¹ and 112 m²g⁻¹, respectively upon In₂O₃ incorporation, with tunable mesopore diameter in the range of 5 - 7 nm. The 0.5% In₂O₃-TiO₂ nanocomposite is considered to be the optimum photocatalyst which is able to degrade 90% of imazapyr herbicide and phenol along 180 min and 60 min respectively. The proposed mechanism of this system and the role of In₂O₃ are explained by details.

Keywords: In₂O₃-TiO₂ nanocomposites, sol-gel method, visible light illumination, UV illumination, herbicide and phenol wastewater, removal

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Authors: Piotr K. Szewczyk, Arkadiusz Gradys, Sungkyun Kim, Luana Persano, Mateusz M. Marzec, Oleksander Kryshtal, Andrzej Bernasik, Sohini Kar-Narayan, Pawel Sajkiewicz, Urszula Stachewicz

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Piezoelectric polymers have received great attention in smart textiles, wearables, and flexible electronics. Their potential applications range from devices that could operate without traditional power sources, through self-powering sensors, up to implantable biosensors. Semi-crystalline PVDF is often proposed as the main candidate for industrial-scale applications as it exhibits exceptional energy harvesting efficiency compared to other polymers combined with high mechanical strength and thermal stability. Plenty of approaches have been proposed for obtaining PVDF rich in the desired β-phase with electric polling, thermal annealing, and mechanical stretching being the most prevalent. Electrospinning is a highly tunable technique that provides a one-step process of obtaining highly piezoelectric PVDF fibers without the need for post-treatment. In this study, voltage polarity and relative humidity influence on electrospun PVDF, fibers were investigated with the main focus on piezoelectric β-phase contents and piezoelectric performance. Morphology and internal structure of fibers were investigated using scanning (SEM) and transmission electron microscopy techniques (TEM). Fourier Transform Infrared Spectroscopy (FITR), wide-angle X-ray scattering (WAXS) and differential scanning calorimetry (DSC) were used to characterize the phase composition of electrospun PVDF. Additionally, surface chemistry was verified with X-ray photoelectron spectroscopy (XPS). Piezoelectric performance of individual electrospun PVDF fibers was measured using piezoresponse force microscopy (PFM), and the power output from meshes was analyzed via custom-built equipment. To prepare the solution for electrospinning, PVDF pellets were dissolved in dimethylacetamide and acetone solution in a 1:1 ratio to achieve a 24% solution. Fibers were electrospun with a constant voltage of +/-15kV applied to the stainless steel nozzle with the inner diameter of 0.8mm. The flow rate was kept constant at 6mlh⁻¹. The electrospinning of PVDF was performed at T = 25°C and relative humidity of 30 and 60% for PVDF30+/- and PVDF60+/- samples respectively in the environmental chamber. The SEM and TEM analysis of fibers produced at a lower relative humidity of 30% (PVDF30+/-) showed a smooth surface in opposition to fibers obtained at 60% relative humidity (PVDF60+/-), which had wrinkled surface and additionally internal voids. XPS results confirmed lower fluorine content at the surface of PVDF- fibers obtained by electrospinning with negative voltage polarity comparing to the PVDF+ obtained with positive voltage polarity. Changes in surface composition measured with XPS were found to influence the piezoelectric performance of obtained fibers what was further confirmed by PFM as well as by custom-built fiber-based piezoelectric generator. For PVDF60+/- samples humidity led to an increase of β-phase contents in PVDF fibers as confirmed by FTIR, WAXS, and DSC measurements, which showed almost two times higher concentrations of β-phase. A combination of negative voltage polarity with high relative humidity led to fibers with the highest β-phase contents and the best piezoelectric performance of all investigated samples. This study outlines the possibility to produce electrospun PVDF fibers with tunable piezoelectric performance in a one-step electrospinning process by controlling relative humidity and voltage polarity conditions. Acknowledgment: This research was conducted within the funding from m the Sonata Bis 5 project granted by National Science Centre, No 2015/18/E/ST5/00230, and supported by the infrastructure at International Centre of Electron Microscopy for Materials Science (IC-EM) at AGH University of Science and Technology. The PFM measurements were supported by an STSM Grant from COST Action CA17107.

Keywords: crystallinity, electrospinning, PVDF, voltage polarity

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Authors: Ben Hadj Hassen Sameh, Gaillard Corentin, Andrew Parker, Kristine Krug

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Perceptual decisions about sequences of sensory stimuli often show serial dependence. The behavioural choice on one trial is often affected by the choice on previous trials. We investigated whether the neuronal signals in extrastriate visual area V5/MT on preceding trials might influence choice on the current trial and thereby reveal the neuronal mechanisms of sequential choice effects. We analysed data from 30 single neurons recorded from V5/MT in three Rhesus monkeys making sequential choices about the direction of rotation of a three-dimensional cylinder. We focused exclusively on the responses of neurons that showed significant choice-related firing (mean choice probability =0.73) while the monkey viewed perceptually ambiguous stimuli. Application of a wavelet transform to the choice-related firing revealed differences in the frequency band of neuronal activity that depended on whether the previous trial resulted in a correct choice for an unambiguous stimulus that was in the neuron’s preferred direction (low alpha and high beta and gamma) or non-preferred direction (high alpha and low beta and gamma). To probe this in further detail, we applied a regularized linear decoder to predict the choice for an ambiguous trial by referencing the neuronal activity of the preceding unambiguous trial. Neuronal activity on a previous trial provided a significant prediction of the current choice (61% correc, 95%Cl~52%t), even when limiting analysis to preceding trials that were correct and rewarded. These findings provide a potential neuronal signature of sequential choice effects in the primate visual cortex.

Keywords: perception, decision making, attention, decoding, visual system

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Authors: Hyunuk Kim, Yang No Yun, Muhammad Sohail, Jong-Ho Moon, Young Cheol Park

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Metal-organic frameworks (MOFs), which are emerging absorbents assembled from metal ions and organic ligands, have attracted attention for their permanent porosity and design of tunable pore size. These microporous materials showed interesting properties for CO₂ storage and separation. In particular, MOFs with high surface area and open metal sites showed the remarkable adsorption capacity and selectivity for CO₂. [Mg₂ (DOBDC)] (DOBDC = 2,5-dioxidobenzene-1,4-dicarboxylate) (MOF-74 or CPO-27) is a well-known absorbent showing an exceptionally high CO₂ sorption capacity at low partial pressure and room temperature. In this work, we synthesized [M₂(DOBDC)(DMF)₂] (M = Mg, Co, Ni) and determined their single-crystal structures by X-ray crystallography. The removal of coordinated guest molecules generates Lewis acidic sites and showed high CO₂ adsorption affinity. Both CO₂ adsorption capacity and surface area are much higher than reported values in literature. To fabricate MMMs, microcrystalline [M₂ (DOBDC)(DMF)₂] was synthesized by microwave reaction and dispersed in PDMS solution. The MMMs with a various amount of [M₂ (DOBDC)(DMF) ₂] in PDMS were fabricated by a solution casting method. [M₂ (DOBDC)(DMF)₂]@PDMS membrane showed higher CO2 permeability and CO₂/N₂ selectivity than those of PDMS. Therefore, we believe that MMMs combining polymer and MOFs provide new materials for CO₂ separation technology.

Keywords: metal-organic frameworks, mixed matrix membrane, CO2/N2 separation, polydimethylsiloxane (PDMS)

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Authors: Ahmed Raza Khan

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Local-strain engineering is an exciting approach to tune the optoelectronic properties of materials and enhance the performance of devices. Two dimensional (2D) materials such as 2D transition metal dichalcogenides (TMDCs) are particularly well-suited for this purpose because they have high flexibility and can withstand high deformations before rupture. Wrinkles on thick TMDC layers have been reported to show the interesting photoluminescence enhancement due to bandgap modulation and funneling effect. However, the wrinkles in ultrathin TMDCs have not been investigated, because the wrinkles can easily fall down to form folds in these ultrathin layers of TMDCs. Here, we have achieved both wrinkle and fold nano-structures simultaneously on 1-3L WS₂ using a new fabrication technique. The comparable layer dependent reduction in surface potential is observed for both folded layers and corresponding perfect pack layers due to the dominant interlayer screening effect. The strains produced from the wrinkle nanostructures considerably vary semi conductive junction properties. Thermo-ionic modelling suggests that the strained (1.6%) wrinkles can lower the Schottky barrier height (SBH) by 20%. The photo-generated carriers would further significantly lower the SBH. These results present an important advance towards controlling the optoelectronic properties of atomically thin WS₂ using strain engineering, with important implications for practical device applications.

Keywords: strain engineering, folding, WS₂, Kelvin probe force microscopy, KPFM, surface potential, photo current, layer dependence

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Authors: Lingling Shui, Shuting Xie

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As alternatives to electronic devices, optically active structures from responsive nanomaterials offer great opportunity buildup smart functional sensors. Hereby, we report on droplet microfluidics enabled construction and application of photonic microcapsules (PMCs) for colorimetric temperature microsensors, enabling miniaturization for injectable local micro-area sensing and integration for large-area sensing. Monodispersed PMCs are produced by in-situ photopolymerization of hydrogel shells of cholesteric liquid crystal (CLC)-in-water-in-oil double emulsion droplets prepared using microfluidic devices, with controllable physical structures and chemical compositions. Constructed PMCs exhibit thermal responsive structural color according to the selective Bragg reflection of CLC’s periodical helical structures within the microdroplet’s spherical confinement. Constructed PMCs with tunable size and composition have been successfully applied for monitoring the living cell extracellular temperature via co-incubation with cell suspension, and for detecting human body temperature via a flexible device from assembled PMCs. These PMCs could be flexibly applied in either micro-environment or large-area surface, enabling wide applications for precision temperature monitoring biological activities (e.g. cells or organs), optoelectronic devices working conditions (e.g. temperature indicators under extreme conditions), and etc.

Keywords: droplet, microfluidics, assembly, soft materials, microsensor

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Authors: Erhan Zor, Funda Copur, Asli I. Dogan, Haluk Bingol

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Current trends in the wide-scale sensing technologies rely on the development of miniaturized, rapid and easy-to-use sensing platforms. Quantum dots (QDs) with strong and easily tunable luminescence and high emission quantum yields have become a well-established photoluminescent nanomaterials for sensor applications. Although the majority of the reports focused on the cadmium-based QDs which have toxic effect on biological systems and eventually would cause serious environmental problems, carbon-based quantum dots (CQDs) that do not contain any toxic class elements have attracted substantial research interest in recent years. CQDs are small carbon nanostructures (less than 10 nm in size) with various unique properties and are widely-used in different fields during the last few years. In this respect, chiral nanostructures have become a promising class of materials in various areas such as pharmacology, catalysis, bioanalysis and (bio)sensor technology due to the vital importance of chirality in living systems. We herein report the synthesis of chiral CQDs with D- or L-tartaric acid as precursor materials. The optimum experimental conditions were examined and the purification procedure was performed using ethanol/water by column chromatography. The purified chiral CQDs were characterized by UV-Vis, FT-IR, XPS, PL and TEM techniques. The resultants display different photoluminescent characteristics due to the size and conformational difference. Considering the results, it can be concluded that chiral CQDs is expected to be used as optical chiral sensor in different platforms.

Keywords: carbon quantum dots, chirality, sensor, tartaric acid

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Authors: Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen

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Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable.

Keywords: natural language inference, explanation generation, variational auto-encoder, generative model

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the customer support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions -dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter- in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Cody Stolle, Mojdeh Asadollahipajouh, Khaleb Pafford, Jada Iwuoha, Samantha White, Becky Mueller

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Battery-electric vehicles (BEVs) are growing in sales and popularity in the United States as an alternative to traditional internal combustion engine vehicles (ICEVs). BEVs are generally heavier than corresponding models of ICEVs, with large battery packs located beneath the vehicle floorpan, a “skateboard” chassis, and have front and rear crush space available in the trunk and “frunk” or front trunk. The geometrical and frame differences between the vehicles may lead to incompatibilities with gasoline vehicles during vehicle-to-vehicle crashes as well as run-off-road crashes with roadside barriers, which were designed to handle lighter ICEVs with higher centers-of-mass and with dedicated structural chasses. Crash data were collected from 10 states spanning a five-year period between 2017 and 2021. Vehicle Identification Number (VIN) codes were processed with the National Highway Traffic Safety Administration (NHTSA) VIN decoder to extract BEV models from ICEV models. Crashes were filtered to isolate only vehicles produced between 2010 and 2021, and the crash circumstances (weather, time of day, maximum injury) were compared between BEVs and ICEVs. In Washington, 436,613 crashes were identified, which satisfied the selection criteria, and 3,371 of these crashes (0.77%) involved a BEV. The number of crashes which noted a fire were comparable between BEVs and ICEVs of similar model years (0.3% and 0.33%, respectively), and no differences were discernable for the time of day, weather conditions, road geometry, or other prevailing factors (e.g., run-off-road). However, crashes involving BEVs rose rapidly; 31% of all BEV crashes occurred in just 2021. Results indicate that BEVs are performing comparably to ICEVs, and events surrounding BEV crashes are statistically indistinguishable from ICEV crashes.

Keywords: battery-electric vehicles, transportation safety, infrastructure crashworthiness, run-off-road crashes, ev crash data analysis

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Authors: N.Revathy, C.Gomathi

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This work aims for a tunable capacitor as a sensor which can vary the control voltage of a voltage control oscillator in a ultra wide band (UWB) transmitter. In this paper power consumption is concentrated. The reason for choosing a capacitive sensing is it give slow temperature drift, high sensitivity and robustness. Previous works report a resistive sensing in a voltage control oscillator (VCO) not aiming at power consumption. But this work aims for power consumption of a capacitive sensing in ultra wide band transmitter. The ultra wide band transmitter to be used is a direct modulation of pulses. The VCO which is the heart of pulse generator of UWB transmitter works on the principle of voltage to frequency conversion. The VCO has and odd number of inverter stages which works on the control voltage input this input is now from a variable capacitor and the buffer stages is reduced from the previous work to maintain the oscillating frequency. The VCO is also aimed to consume low power. Then the concentration in choosing a variable capacitor is aimed. A compact model of a capacitor with the transient characteristics is to be designed with a movable dielectric and multi metal membranes. Previous modeling of the capacitor transient characteristics is with a movable membrane and a fixed membrane. This work aims at a membrane with a wide tuning suitable for ultra wide band transmitter.This is used in this work because a capacitive in a ultra wide transmitter need to be tuned in such a way that all satisfies FCC regulations.

Keywords: capacitive sensing, ultra wide band transmitter, voltage control oscillator, FCC regulation

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Authors: S. M. Giripunje, Shikha Jindal

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Zinc sulphide (ZnS) quantum dots (QDs) were synthesized successfully via simple sonochemical method. X-ray diffraction (XRD), scanning electron microscopy (SEM) and high resolution transmission electron microscopy (HRTEM) analysis revealed the average size of QDs of the order of 3.7 nm. The band gap of the QDs was tuned to 5.2 eV by optimizing the synthesis parameters. UV-Vis absorption spectra of ZnS QD confirm the quantum confinement effect. Fourier transform infrared (FTIR) analysis confirmed the formation of single phase ZnS QDs. To fabricate the diode, blend of ZnS QDs and P3HT was prepared and the heterojunction of PEDOT:PSS and the blend was formed by spin coating on indium tin oxide (ITO) coated glass substrate. The diode behaviour of the heterojunction was analysed, wherein the ideality factor was found to be 2.53 with turn on voltage 0.75 V and the barrier height was found to be 1.429 eV. ZnS-Graphene QDs nanocomposite was characterised for the surface morphological study. It was found that the synthesized ZnS QDs appear as quasi spherical particles on the graphene sheets. The average particle size of ZnS-graphene nanocomposite QDs was found to be 8.4 nm. From voltage-current characteristics of ZnS-graphene nanocomposites, it is observed that the conductivity of the composite increases by 10⁴ times the conductivity of ZnS QDs. Thus the addition of graphene QDs in ZnS QDs enhances the mobility of the charge carriers in the composite material. Thus, the graphene QDs, with high specific area for a large interface, high mobility and tunable band gap, show a great potential as an electron-acceptors in photovoltaic devices.

Keywords: graphene, heterojunction, quantum confinement effect, quantum dots(QDs), zinc sulphide(ZnS)

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Authors: Latha Nataraj, Todd Henry, Micheal Wallock, Asha Hall, Christine Hatter, Babak Anasori, Yury Gogotsi

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Multifunctional composites with enhanced strength and toughness for superior damage tolerance are essential for advanced aerospace and military applications. Detection of structural changes prior to visible damage may be achieved by incorporating fillers with tunable properties such as two-dimensional (2D) nanomaterials with high aspect ratios and more surface-active sites. While 2D graphene with large surface areas, good mechanical properties, and high electrical conductivity seems ideal as a filler, the single-atomic thickness can lead to bending and rolling during processing, requiring post-processing to bond to polymer matrices. Lately, an emerging family of 2D transition metal carbides and nitrides, MXenes, has attracted much attention since their discovery in 2011. Metallic electronic conductivity and good mechanical properties, even with increased polymer content, coupled with hydrophilicity make MXenes a good candidate as a filler material in polymer composites and exceptional as multifunctional damage indicators in composites. Here, we systematically study MXene-based (Ti₃C₂) coated on glass fibers for fiber reinforced polymer composite for self-sensing using microscopy and micromechanical testing. Further testing is in progress through the investigation of local variations in optical, acoustic, and thermal properties within the damage sites in response to strain caused by mechanical loading.

Keywords: damage sensing, fiber composites, MXene, self-sensing

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Authors: Nouf Alharbi, James O'shea

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For decades, renewable energy sources have received considerable global interest due to the increase in fossil fuel consumption. The abundant energy produced by sunlight makes dye-sensitised solar cells (DSSCs) a promising alternative compared to conventional silicon and thin film solar cells due to their transparency and tunable colours, which make them suitable for applications such as windows and glass facades. The transfer of an excited electron onto the surface is an important procedure in the DSSC system, so different groups of dye molecules were studied on the rutile TiO2 (110) surface. Currently, the study of organic dyes has become an interest of researchers due to ruthenium being a rare and expensive metal, and metal-free organic dyes have many features, such as high molar extinction coefficients, low manufacturing costs, and ease of structural modification and synthesis. There are, of course, some groups that have developed organic dyes and exhibited lower light-harvesting efficiency ranging between 4% and 8%. Since most dye molecules are complicated or fragile to be deposited by thermal evaporation or sublimation in the ultra-high vacuum (UHV), all dyes (i.e, D5, SC4, and R6) in this study were deposited in situ using the electrospray deposition technique combined with X-ray photoelectron spectroscopy (XPS) as an alternative method to obtain high-quality monolayers of titanium dioxide. These organic molecules adsorbed onto rutile TiO2 (110) are explored by XPS, which can be used to obtain element-specific information on the chemical structure and study bonding and interaction sites on the surface.

Keywords: dyes, deposition, electrospray, molecules, organic, rutile, sensitised, XPS

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Authors: Kusum Kumari, Ramesh Banoth, V. S. Reddy Channu

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Organic-inorganic perovskite solar cells (PrSCs) have emerged as a promising solar photovoltaic technology in terms of realizing high power conversion efficiency (PCE). However, their limited lifetime and poor device stability limits their commercialization in future. In this regard, interface engineering of the electron transport layer (ETL) using 2D materials have been currently used owing to their high carrier mobility, high thermal stability and tunable work function, which in turn enormously impact the charge carrier dynamics. In this work, we report an easy and effective way of simultaneously enhancing the efficiency of PrSCs along with the long-term stability through interface engineering via the incorporation of 2D-Molybdenum disulfide (2D-MoS₂, few layered nanoflakes) in mesoporous-Titanium dioxide (mp-TiO₂)scaffold electron transport buffer layer, and using poly 3-hexytheophene (P3HT) as hole transport layers. The PSCs were fabricated in ambient air conditions in device configuration, FTO/c-TiO₂/mp-TiO₂:2D-MoS₂/CH3NH3PbI3/P3HT/Au, with an active area of 0.16 cm². The best device using c-TiO₂/mp-TiO₂:2D-MoS₂ (0.5wt.%) ETL exhibited a substantial increase in PCE ~13.04% as compared to PCE ~8.75% realized in reference device fabricated without incorporating MoS₂ in mp-TiO₂ buffer layer. The incorporation of MoS₂ nanoflakes in mp-TiO₂ ETL not only enhances the PCE to ~49% but also leads to better device stability in ambient air conditions without encapsulation (retaining PCE ~86% of its initial value up to 500 hrs), as compared to ETLs without MoS₂.

Keywords: perovskite solar cells, MoS₂, nanoflakes, electron transport layer

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Authors: Sharda Nara, Bansi Dhar Malhotra

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Investigation of the vitamins as an electron transfer mediator could significantly assist in merging the area of tissue engineering and electronics required for the implantable therapeutic devices. The present study report that the molecules of folic acid released by Providencia rettgeri via fermentation route under the anoxic condition of the microbial fuel cell (MFC) exhibit characteristic electrochemical and optical properties, as indicated by absorption spectroscopy, photoluminescence (PL), and cyclic voltammetry studies. The absorption spectroscopy has depicted an absorption peak at 263 nm with a small bulge around 293 nm on day two of bacterial culture, whereas an additional peak was observed at 365 nm on the twentieth day. Furthermore, the PL spectra has indicated that the maximum emission occurred at various wavelengths 420, 425, 440, and 445 nm when excited by 310, 325, 350, and 365 nm. The change of emission spectra with varying excitation wavelength might be indicating the presence of tunable optical bands in the folic acid molecules co-related with the redox activity of the molecules. The results of cyclic voltammetry studies revealed that the oxidation and reduction occurred at 0.25V and 0.12V, respectively, indicating the electrochemical behavior of the folic acid. This could be inferred that the released folic acid molecules in a MFC might undergo inter as well as intra molecular electron transfer forming different intermediate states while transferring electrons to the electrode surface. Synchronization of electrochemical and optical properties of folic acid molecules could be potentially promising for the designing of electroactive scaffold and biocompatible conductive surface for the applications of tissue engineering and biofuel cells, respectively.

Keywords: biofuel cell, electroactivity, folic acid, tissue engineering

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Authors: Erwan Negre, Ewan J. O'Connor, Juha Toivonen

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The need for CO2 monitoring technologies grows simultaneously with the worldwide concerns regarding environmental challenges. To that purpose, we developed a compact coherent all-fiber ranged-resolved Differential Absorption Lidar (RR-DIAL). It has been designed along a tunable 2x1fiber optic switch set to a frequency of 1 Hz between two Distributed FeedBack (DFB) lasers emitting in the continuous-wave mode at 1571.41 nm (absorption line of CO2) and 1571.25 nm (CO2 absorption-free line), with linewidth and tuning range of respectively 1 MHz and 3 nm over operating wavelength. A three stages amplification through Erbium and Erbium-Ytterbium doped fibers coupled to a Radio Frequency (RF) driven Acousto-Optic Modulator (AOM) generates 100 ns pulses at a repetition rate from 10 to 30 kHz with a peak power up to 2.5 kW and a spatial resolution of 15 m, allowing fast and highly resolved CO2 profiles. The same afocal collection system is used for the output of the laser source and the backscattered light which is then directed to a circulator before being mixed with the local oscillator for heterodyne detection. Packaged in an easily transportable box which also includes a server and a Field Programmable Gate Array (FPGA) card for on-line data processing and storing, our setup allows an effective and quick deployment for versatile in-situ analysis, whether it be vertical atmospheric monitoring, large field mapping or sequestration site continuous oversight. Setup operation and results from initial field measurements will be discussed.

Keywords: CO2 profiles, coherent DIAL, in-situ atmospheric sensing, near infrared fiber source

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Authors: Filipa Vasconcelos

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The administration of endoplasmic reticulum amino peptidases (ERAP1 or ERAP2) inhibitors can be used for therapeutic approaches against cancer and auto-immune diseases. However, one of the main shortcomings of drug delivery systems (DDS) is associated with the drug off-target distribution, which can lead to an increase in its side effects on the patient’s body. To overcome such limitations, the encapsulation of four representative compounds of ERAP inhibitors into Polycaprolactone (PCL), Polyvinyl-alcohol (PVA), crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes is proposed as a safe and controlled drug release system. The use of electrospun fibrous meshes as a DDS allows efficient solvent evaporation giving limited time to the encapsulated drug to recrystallize, continuous delivery of the drug while the fibers degrade, prevention of initial burst release (sustained release), tunable dosages, and the encapsulation of other agents. This is possible due to the fibers' small diameters and resemblance to the extracellular matrix (confirmed by scanning electron microscopy results), high specific surface area, and good mechanical strength/stability. Furthermore, release studies conducted on PCL, PVA, crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes with each of the ERAP compounds encapsulated demonstrated that they were capable of releasing >60%, 50%, 40%, and 45% of the total ERAP concentration, respectively. Fibrous meshes with ERAP_E compound encapsulated achieved higher released concentrations (75.65%, 62.41%, 56.05%, and 65.39%, respectively). Toxicity studies of fibrous meshes with encapsulated compounds are currently being accessed in vitro, as well as pharmacokinetics and dynamics studies. The last step includes the implantation of the drug-loaded fibrous meshes in vivo.

Keywords: drug delivery, electrospinning, ERAP inhibitors, liposomes

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Authors: Hassan Bohra, Mingfeng Wang

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Conjugated porous polymers (CPPs) are amorphous, insoluble and highly robust organic semiconductors that have been largely synthesized by traditional transition-metal catalyzed reactions. The distinguishing feature of CPP materials is that they combine microporosity and high surface areas with extended conjugation, making them ideal for versatile applications such as separation, catalysis and energy storage. By applying a modular approach to synthesis, chemical and electronic properties of CPPs can be tailored for specific applications making these materials economical alternatives to inorganic semiconductors. Direct arylation - an environmentally benign alternative to traditional polymerization reactions – is one such reaction that extensively over the last decade for the synthesis of linear p-conjugated polymers. In this report, we present the synthesis and characterization of a new series of robust conjugated porous polymers synthesized by facile direct arylation polymerization of thiophene-flanked acceptor building blocks with multi-brominated aryls with different geometries. We observed that the porosities and morphologies of the polymers are determined by the chemical structure of the aryl bromide used. Moreover, good control of the optical bandgap in the range 2.53 - 1.3 eV could be obtained by using different building blocks. Structure-property relationships demonstrated in this study suggest that direct arylation polymerization is an attractive synthetic tool for the rational design of porous organic materials with tunable photo-physical properties for applications in photocatalysis, energy storage and conversion.

Keywords: direct arylation, conjugated porous polymers, triazine, photocatalysis

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Authors: Deepanjali Gurav, Kun Qian

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In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

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Authors: Faraz Zarghami, Elham Anari, Nosratollah Zarghami, Yones Pilehvar-Soltanahmadi, Abolfazl Akbarzadeh, Sepideh Jalilzadeh-Tabrizi

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The development of nanotherapy has presented a new method of drug delivery targeted directly to the neoplasmic tissues, to maximize the action with fewer dose requirements. In the past two decades, poly(lactic-co-glycolic acid) (PLGA) has frequently been investigated by many researchers and is a popular polymeric candidate, due to its biocompatibility and biodegradability, exhibition of a wide range of erosion times, tunable mechanical properties, and most notably, because it is a FDA-approved polymer. Chrysin is a natural flavonoid which has been reported to have some significant biological effects on the processes of chemical defense, nitrogen fixation, inflammation, and oxidation. However, the low solubility in water decreases its bioavailability and consequently disrupts the biomedical benefits. Being loaded with PLGA-PEG increases chrysin solubility and drug tolerance, and decreases the discordant effects of the drug. The well-structured chrysin efficiently accumulates in the breast cancer cell line (T47D). In the present study, the structure and chrysin loading were delineated using proton nuclear magnetic resonance (HNMR), Fourier-transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM), and the in vitro cytotoxicity of pure and nanochrysin was studied by the MTT assay. Next, the RNA was exploited and the cytotoxic effects of chrysin were studied by real-time PCR. In conclusion, the nanochrysin therapy developed is a novel method that could increase cytotoxicity to cancer cells without damaging the normal cells, and would be promising in breast cancer therapy.

Keywords: MTT assay, chrysin, flavonoids, nanotherapy

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Authors: Miroslava Rysová, Zdena Syrová, Tomáš Zajíc, Petr Exnar

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Currently, attention of tissue engineers has been attracted to novel nanofibrous materials having advanced properties and ability to mimic extracellular matrix (ECM) by structure which makes them interesting candidates for application in regenerative medicine as scaffolding and/or drug delivering material. Throughout the last decade, more than 200 synthetic and natural polymers have been successfully electrospun leading to the formation of nanofibres with a wide range of chemical, mechanical and degradation properties. In this family, inorganic nanofibres represent very specific group offering an opportunity to manufacture inert to body, well degradable and in properties tunable material. Aim of this work, was to reveal unique properties of silica (SiO2, CAS 7631-86-9) nanofibres and their potential in field of regenerative medicine. Silica nanofibres were prepared by sol-gel method from tetraethyl orthosilicate (TEOS, CAS 78-10-4) as a precursor and subsequently manufactured by needleless electrospinning on NanospiderTM device. Silica nanofibres thermally stabilized under 200°C were confirmed to be fully biodegradable and soluble in several simulated body fluids. In vitro cytotoxicity tests of eluate (ES ISO 10993-5:1999) and in direct contact (ES ISO 10993-5:2009) showed no toxicity - e.g. cell viabilities reached values exceeding 80%. Those results were obtained equally from two different cell lines (Vero, 3T3). Non-toxicity of silaca nanofibres´ eluate was additionally confirmed in real time by testing on xCelligence (ACEA Biosciences, Inc.) device. Both cell types also showed good adhesion to material. To conclude, all mentioned results lead to resumption that silica nanofibres have a potential as material for regenerative medicine which opens door to further research.

Keywords: cytotoxicity, electrospinning, nanofibres, silica, tissue engineering

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Authors: Saurabh Basu, Sudin Ganguly

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Conductance in graphene nanoribbons (GNR) in presence of magnetic (for example, Iron) and non-magnetic (for example, Gold) adatoms are explored theoretically within a Kane-Mele model for their possible spintronic applications and topologically non-trivial properties. In our work, we have considered the magnetic adatoms to induce a Rashba spin-orbit coupling (RSOC) and an exchange bias field, while the non-magnetic ones induce an RSOC and an intrinsic spin-orbit (SO) coupling. Even though RSOC is present in both, they, however, represent very different physical situations, where the magnetic adatoms do not preserve the time reversal symmetry, while the non-magnetic case does. This has important implications on the topological properties. For example, the non-magnetic adatoms, for moderately strong values of SO, the GNR denotes a quantum spin Hall insulator as evident from a 2e²/h plateau in the longitudinal conductance and presence of distinct conducting edge states with an insulating bulk. Since the edge states are protected by time reversal symmetry, the magnetic adatoms in GNR yield trivial insulators and do not possess any non-trivial topological property. However, they have greater utility than the non-magnetic adatoms from the point of view of spintronic applications. Owing to the broken spatial symmetry induced by the presence of adatoms of either type, all the x, y and z components of the spin-polarized conductance become non-zero (only the y-component survives in pristine Graphene owing to a mirror symmetry present there) and hence become suitable for spintronic applications. However, the values of the spin polarized conductances are at least two orders of magnitude larger in the case of magnetic adatoms than their non-magnetic counterpart, thereby ensuring more efficient spintronic applications. Further the applications are tunable by altering the adatom densities.

Keywords: magnetic and non-magnetic adatoms, quantum spin hall phase, spintronic applications, spin polarized conductance, time reversal symmetry

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Authors: Mohd Ayyub Khan, Nadeem Akhtar

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Due to recent advances in wireless communication technologies and hand-held devices, there is a huge demand for video-based applications such as video surveillance, video conferencing, remote surgery, Digital Video Broadcast (DVB), IPTV, online learning courses, YouTube, WhatsApp, Instagram, Facebook, Interactive Video Games. However, the raw videos posses very high bandwidth which makes the compression a must before its transmission over the wireless channels. The High Efficiency Video Codec (HEVC) (also called H.265) is latest state-of-the-art video coding standard developed by the Joint effort of ITU-T and ISO/IEC teams. HEVC is targeted for high resolution videos such as 4K or 8K resolutions that can fulfil the recent demands for video services. The compression ratio achieved by the HEVC is twice as compared to its predecessor H.264/AVC for same quality level. The compression efficiency is generally increased by removing more correlation between the frames/pixels using complex techniques such as extensive intra and inter prediction techniques. As more correlation is removed, the chances of interdependency among coded bits increases. Thus, bit errors may have large effect on the reconstructed video. Sometimes even single bit error can lead to catastrophic failure of the reconstructed video. In this paper, we study the performance of HEVC bitstream over additive white Gaussian noise (AWGN) channel. Moreover, HEVC over Quadrature Amplitude Modulation (QAM) combined with forward error correction (FEC) schemes are also explored over the noisy channel. The video will be encoded using HEVC, and the coded bitstream is channel coded to provide some redundancies. The channel coded bitstream is then modulated using QAM and transmitted over AWGN channel. At the receiver, the symbols are demodulated and channel decoded to obtain the video bitstream. The bitstream is then used to reconstruct the video using HEVC decoder. It is observed that as the signal to noise ratio of channel is decreased the quality of the reconstructed video decreases drastically. Using proper FEC codes, the quality of the video can be restored up to certain extent. Thus, the performance analysis of HEVC presented in this paper may assist in designing the optimized code rate of FEC such that the quality of the reconstructed video is maximized over wireless channels.

Keywords: AWGN, forward error correction, HEVC, video coding, QAM

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Authors: Snezana Lazic, Zarko Gacevic, Mark Holmes, Ekaterina Chernysheva, Marcus Müller, Peter Veit, Frank Bertram, Juergen Christen, Yasuhiko Arakawa, Enrique Calleja

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The study reports how the pencil-like morphology of a homoepitaxially grown GaN nanowire can be exploited for the fabrication of a thin conformal InGaN nanoshell, hosting nonpolar, semipolar and polar single photon sources (SPSs). All three SPS types exhibit narrow emission lines (FWHM~0.35 - 2 meV) and high degrees of linear optical polarization (P > 70%) in the low-temperature micro-photoluminescence (µ-PL) experiments and are characterized by a pronounced antibunching in the photon correlation measurements (gcorrected(2)(0) < 0.3). The quantum-dot-like exciton localization centers induced by compositional fluctuations within the InGaN nanoshell are identified as the driving mechanism for the single photon emission. As confirmed by the low-temperature transmission electron microscopy combined with cathodoluminescence (TEM-CL) study, the crystal region (i.e. non-polar m-, semi-polar r- and polar c-facets) hosting the single photon emitters strongly affects their emission wavelength, which ranges from ultra-violet for the non-polar to visible for the polar SPSs. The photon emission lifetime is also found to be facet-dependent and varies from sub-nanosecond time scales for the non- and semi-polar SPSs to a few nanoseconds for the polar ones. These differences are mainly attributed to facet-dependent indium content and electric field distribution across the hosting InGaN nanoshell. The hereby reported pencil-like InGaN nanoshell is the first single nanostructure able to host all three types of single photon emitters and is thus a promising building block for tunable quantum light devices integrated into future photonic and optoelectronic circuits.

Keywords: GaN nanowire, InGaN nanoshell, linear polarization, nonpolar, semipolar, polar quantum dots, single-photon sources

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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