Characterization of alluvial formation by stochastic modelling of paleo-fluvial processes: The concept and method

Modelling fluvial processes is an effective way to reproduce basin evolution and to recreate riverbed morphology. However, due to the complexity of alluvial environments, deterministic modelling of fluvial processes is often impossible. To address the related uncertainties, we derive a stochastic fluvial process model on the basis of the convective Exner equation that uses the statistics (mean and variance) of river velocity as input parameters. These statistics allow for quantifying the uncertainty in riverbed topography, river discharge and position of the river channel. In order to couple the velocity statistics and the fluvial process model, the perturbation method is employed with a non-stationary spectral approach to develop the Exner equation as two separate equations: the first one is the mean equation, which yields the mean sediment thickness, and the second one is the perturbation equation, which yields the variance of sediment thickness. The resulting solutions offer an effective tool to characterize alluvial aquifers resulting from fluvial processes, which allows incorporating the stochasticity of the paleoflow velocity.

Post-quantum key exchange for the TLS protocol from the ring learning with errors problem

Lattice-based cryptographic primitives are believed to offer resilience against attacks by quantum computers. We demonstrate the practicality of post-quantum key exchange by constructing cipher suites for the Transport Layer Security (TLS) protocol that provide key exchange based on the ring learning with errors (R-LWE) problem, we accompany these cipher suites with a rigorous proof of security. Our approach ties lattice-based key exchange together with traditional authentication using RSA or elliptic curve digital signatures: the post-quantum key exchange provides forward secrecy against future quantum attackers, while authentication can be provided using RSA keys that are issued by today's commercial certificate authorities, smoothing the path to adoption. Our cryptographically secure implementation, aimed at the 128-bit security level, reveals that the performance price when switching from non-quantum-safe key exchange is not too high. With our R-LWE cipher suites integrated into the Open SSL library and using the Apache web server on a 2-core desktop computer, we could serve 506 RLWE-ECDSA-AES128-GCM-SHA256 HTTPS connections per second for a 10 KiB payload. Compared to elliptic curve Diffie-Hellman, this means an 8 KiB increased handshake size and a reduction in throughput of only 21%. This demonstrates that provably secure post-quantum key-exchange can already be considered practical.

Enhanced electron lifetime of CdSe/CdS quantum dot (QD) sensitized solar cells using ZnSe core–shell structure with efficient regeneration of quantum Ddots

Research on development of efficient passivation materials for high performance and stable quantum dot sensitized solar cells (QDSCs) is highly important. While ZnS is one of the most widely used passivation material in QDSCs, an alternative material based on ZnSe which was deposited on CdS/CdSe/TiO2 photoanode to form a semi-core/shell structure has been found to be more efficient in terms of reducing electron recombination in QDSCs in this work. It has been found that the solar cell efficiency was improved from 1.86% for ZnSe0 (without coating) to 3.99% using 2 layers of ZnSe coating (ZnSe2) deposited by successive ionic layer adsorption and reaction (SILAR) method. The short circuit current density (Jsc) increased nearly 1-fold (from 7.25 mA/cm2 to13.4 mA/cm2), and the open circuit voltage (Voc) was enhanced by 100 mV using ZnSe2 passivation layer compared to ZnSe0. Studies on the light harvesting efficiency (ηLHE) and the absorbed photon-to-current conversion efficiency (APCE) have revealed that the ZnSe coating layer caused the enhanced ηLHE at wavelength beyond 500 nm and a significant increase of the APCE over the spectrum 400−550 nm. A nearly 100% APCE was obtained with ZnSe2, indicating the excellent charge injection and collection process in the device. The investigation on charge transport and recombination of the device has indicated that the enhanced electron collection efficiency and reduced electron recombination should be responsible for the improved Jsc and Voc of the QDSCs. The effective electron lifetime of the device with ZnSe2 was nearly 6 times higher than ZnSe0 while the electron diffusion coefficient was largely unaffected by the coating. Study on the regeneration of QDs after photoinduced excitation has indicated that the hole transport from QDs to the reduced species (S2−) in electrolyte was very efficient even when the QDs were coated with a thick ZnSe shell (three layers). For comparison, ZnS coated CdS/CdSe sensitized solar cell with optimum shell thickness was also fabricated, which generated a lower energy conversion efficiency (η = 3.43%) than the ZnSe based QDSC counterpart due to a lower Voc and FF. This study suggests that ZnSe may be a more efficient passivation layer than ZnS, which is attributed to the type II energy band alignment of the core (CdS/CdSe quantum dots) and passivation shell (ZnSe) structure, leading to more efficient electron−hole separation and slower electron recombination.

Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes

This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

Group 14 element-based non-centrosymmetric quantum spin hall insulators with large bulk gap

To date, a number of two-dimensional (2D) topological insulators (TIs) have been realized in Group 14 elemental honeycomb lattices, but all are inversionsymmetric. Here, based on first-principles calculations, we predict a new family of 2D inversion-asymmetric TIs with sizeable bulk gaps from 105 meV to 284 meV, in X2–GeSn (X = H, F, Cl, Br, I) monolayers, making them in principle suitable for room-temperature applications. The nontrivial topological characteristics of inverted band orders are identified in pristine X2–GeSn with X = (F, Cl, Br, I), whereas H2–GeSn undergoes a nontrivial band inversion at 8% lattice expansion. Topologically protected edge states are identified in X2–GeSn with X = (F, Cl, Br, I), as well as in strained H2–GeSn. More importantly, the edges of these systems, which exhibit single-Dirac-cone characteristics located exactly in the middle of their bulk band gaps, are ideal for dissipationless transport. Thus, Group 14 elemental honeycomb lattices provide a fascinating playground for the manipulation of quantum states.

Envisaging change: Supporting grassroots efforts in Colombia with agonistic design processes

Design has become increasingly engaged with bringing about social change. Shifting domains and perspectives to conflict stricken contexts yield opportunities to explore emerging forms of design that enable the expression and articulation of difference in productive ways, which can contribute positively to efforts related to civic issues and struggles in urban settings from developing countries. We explore the recently developed notion of Adversarial Design to support the integration of diverging perspectives and grassroots voices in the design process. This paper presents the findings and design insights from our study with two grassroots organisations in Bogota, Colombia. We present three themes that expose ways in which conflict motivates bringing about change, the importance of the social and physical features of the urban landscape, and the way in which social change acts as catalyst for acquiring new knowledge. To finalise, we discuss two design areas and how design could be used to integrate dissimilar worldviews.

Mapping bound plasmon propagation on a nanoscale stripe waveguide using quantum dots: Influence of spacer layer thickness

In this paper we image the highly confined long range plasmons of a nanoscale metal stripe waveguide using quantum emitters. Plasmons were excited using a highly focused 633 nm laser beam and a specially designed grating structure to provide stronger incoupling to the desired mode. A homogeneous thin layer of quantum dots was used to image the near field intensity of the propagating plasmons on the waveguide. We observed that the photoluminescence is quenched when the QD to metal surface distance is less than 10 nm. The optimised spacer layer thickness for the stripe waveguides was found to be around 20 nm. Authors believe that the findings of this paper prove beneficial for the development of plasmonic devices utilising stripe waveguides.

Online hidden Markov model parameter estimation and minimax robust quickest change detection in uncertain stochastic processes

Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.

Characterisation of lignins isolated from sugarcane bagasse pretreated with acidified ethylene glycol and ionic liquids

Sugarcane bagasse pretreatment processes using acidified aqueous ethylene glycol (EG) and ionic liquids (ILs) have been reported recently. In this study, recovery of lignins from these processes was conducted, as well as determination of their physico-chemical properties. The amount of lignins recovered from 1-butyl-3-methylimidazolium chloride ([bmim]Cl) with HCl as a catalyst and [bmim][CH3SO3] was ∼42%, and ∼35%–36% by EG with HCl or H2SO4 as a catalyst, respectively. The isolated lignins were characterised using wet chemistry, spectroscopy and thermogravimetry analysis (TGA), and the results compared to soda lignin from NaOH pretreatment of bagasse. The IL and EG lignins contained no or trace amounts of carbohydrates, slightly lower hydrogen content but slightly higher oxygen contents than soda lignin. The IL and EG lignins contained more C-3 and C-5 reactive sites for Mannich reaction and had more p-hydroxypheny propane unit structures than soda lignin. Two-dimensional heteronuclear single quantum coherence (2D HSQC) nuclear magnetic resonance (NMR) identified the major substructural units in the lignins, and allowed differences among them to be studied. As EG lignins were extracted in very reactive environment, intermediate enol ethers were formed and led to cleavage reactions which were not apparent in the other lignins. 31P NMR and infra-red spectroscopy results showed that IL and EG lignins had lower total hydroxyl content than soda lignin, probably indicating that a higher degree of self-polymerisation occurred during bagasse pretreatment, despite the use of lower temperature and shorter reaction time. On the basis of the salient features of these lignins, potential applications were proposed.

The subordinated processes controlled by a family of subordinators and corresponding Fokker-Planck type equations

In this work, we consider subordinated processes controlled by a family of subordinators which consist of a power function of a time variable and a negative power function of an α-stable random variable. The effect of parameters in the subordinators on the subordinated process is discussed. By suitable variable substitutions and the Laplace transform technique, the corresponding fractional Fokker–Planck-type equations are derived. We also compute their mean square displacements in a free force field. By choosing suitable ranges of parameters, the resulting subordinated processes may be subdiffusive, normal diffusive or superdiffusive

A rapid and label-free dual detection of Hg (II) and cysteine with the use of fluorescence switching of graphene quantum dots

A simple and rapid method of analysis for mercury ions (Hg2+) and cysteine (Cys) was developed with the use of graphene quantum dots (GQDs) as a fluorescent probe. In the presence of GQDs, Hg2+ cations are absorbed on their negatively charged surface by means of electrostatic interactions. Thus, the fluorescence (FL) of the GQDs would be significantly quenched as a result of the FL charge transfer, e.g. 92% quenching at 450 nm occurs for a 5 μmol L−1 Hg2+ solution. However, when Cys was added, a significant FL enhancement was observed (510% at 450 nm for a 8.0 μmol L−1 Cys solution), and Hg2+ combined with Cys rather than with the GQDs in an aqueous solution. This occurred because a strong metalsingle bondthiol bond formed, displacing the weak electrostatic interactions, and this resulted in an FL enhancement of the GQDs. The limits of detection (LOD) for Hg2+ and Cys were 0.439 nmol L−1 and 4.5 nmol L−1, respectively. Also, this method was used successfully to analyze Hg2+ and Cys in spiked water samples.

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

Monitoring care processes in the gynecologic oncology department

The care processes of healthcare providers are typically considered as human-centric, flexible, evolving, complex and multi-disciplinary. Consequently, acquiring an insight in the dynamics of these care processes can be an arduous task. A novel event log based approach for extracting valuable medical and organizational information on past executions of the care processes is presented in this study. Care processes are analyzed with the help of a preferential set of process mining techniques in order to discover recurring patterns, analyze and characterize process variants and identify adverse medical events.

Optimizing the quantum dot: Plasmon interaction in a nano gap waveguide

Spontaneous emission (SE) of a Quantum emitter depends mainly on the transmission strength between the upper and lower energy levels as well as the Local Density of States (LDOS)[1]. When a QD is placed in near a plasmon waveguide, LDOS of the QD is increased due to addition of the non-radiative decay and a plasmonic decay channel to free space emission[2-4]. The slow velocity and dramatic concentration of the electric field of the plasmon can capture majority of the SE into guided plasmon mode (Гpl ). This paper focused on studying the effect of waveguide height on the efficiency of coupling QD decay into plasmon mode using a numerical model based on finite elemental method (FEM). Symmetric gap waveguide considered in this paper support single mode and QD as a dipole emitter. 2D simulation models are done to find normalized Гpl and 3D models are used to find probability of SE decaying into plasmon mode ( β) including all three decay channels. It is found out that changing gap height can increase QD-plasmon coupling, by up to a factor of 5 and optimally placed QD up to a factor of 8. To make the paper more realistic we briefly studied the effect of sharpness of the waveguide edge on SE emission into guided plasmon mode. Preliminary nano gap waveguide fabrication and testing are already underway. Authors expect to compare the theoretical results with experimental outcomes in the future

Graphene quantum dots and the resonance light scattering technique for trace analysis of phenol in different water samples

A novel, highly selective resonance light scattering (RLS) method was researched and developed for the analysis of phenol in different types of industrial water. An important aspect of the method involved the use of graphene quantum dots (GQDs), which were initially obtained from the pyrolysis of citric acid dissolved in aqueous solutions. The GQDs in the presence of horseradish peroxidase (HRP) and H2O2 were found to react quantitatively with phenol such that the RLS spectral band (310 nm) was quantitatively enhanced as a consequence of the interaction between the GQDs and the quinone formed in the above reaction. It was demonstrated that the novel analytical method had better selectivity and sensitivity for the determination of phenol in water as compared to other analytical methods found in the literature. Thus, trace amounts of phenol were detected over the linear ranges of 6.00×10−8–2.16×10−6 M and 2.40×10−6–2.88×10−5 M with a detection limit of 2.20×10−8 M. In addition, three different spiked waste water samples and two untreated lake water samples were analysed for phenol. Satisfactory results were obtained with the use of the novel, sensitive and rapid RLS method.