The detection of epileptic seizures by classifying electroencephalography (EEG) signals into ictal and interictal classes is a demanding challenge, because it identifies the seizure and seizure-free states of an epileptic patient. In previous works, several machine learning-based strategies were introduced to investigate and interpret EEG signals for the purpose of their accurate classification. However, non-linear and non-stationary characteristics of EEG signals make it complicated to get complete information about these dynamic biomedical signals. In order to address this issue, this paper focuses on extracting the most discriminating and distinguishing features of seizure EEG recordings to develop an approach that employs both fuzzy-based and traditional machine learning algorithms for epileptic seizure detection. The proposed framework classifies unknown EEG signal segments into ictal and interictal classes. The model is validated using empirical evaluation on two benchmark datasets, namely the Bonn and Children's Hospital of Boston-Massachusetts Institute of Technology (CHB-MIT) datasets. The obtained results show that in both cases, K-Nearest Neighbor (KNN) and Fuzzy Rough Nearest Neighbor (FRNN) give the highest classification accuracy scores, with improved sensitivity and specificity percentages.

Continued improvements on existing reconstruction methods are vital to the success of high-energy physics experiments, such as the IceCube Neutrino Observatory. In IceCube, further challenges arise as the detector is situated at the geographic South Pole where computational resources are limited. However, to perform real-time analyses and to issue alerts to telescopes around the world, powerful and fast reconstruction methods are desired. Deep neural networks can be extremely powerful, and their usage is computationally inexpensive once the networks are trained. These characteristics make a deep learning-based approach an excellent candidate for the application in IceCube. A reconstruction method based on convolutional architectures and hexagonally shaped kernels is presented. The presented method is robust towards systematic uncertainties in the simulation and has been tested on experimental data. In comparison to standard reconstruction methods in IceCube, it can improve upon the reconstruction accuracy, while reducing the time necessary to run the reconstruction by two to three orders of magnitude.

The Surface Enhancement of the IceTop air-shower array will include the addition of radio antennas and scintillator panels, co-located with the existing ice-Cherenkov tanks and covering an area of about 1 km(2). Together, these will increase the sensitivity of the IceCube Neutrino Observatory to the electromagnetic and muonic components of cosmic-ray-induced air showers at the South Pole. The inclusion of the radio technique necessitates an expanded set of simulation and analysis tools to explore the radio-frequency emission from air showers in the 70 MHz to 350 MHz band. In this paper we describe the software modules that have been developed to work with time-and frequency-domain information within IceCube's existing software framework, IceTray, which is used by the entire IceCube collaboration. The software includes a method by which air-shower simulation, generated using CoREAS, can be reused via waveform interpolation, thus overcoming a significant computational hurdle in the field.

Polymer nanocomposite based on polyvinyl alcohol (PVA) and lead sulfide (PbS) in the average radius of (1.88-2.23) nm, have been synthesized using the chemical reduction rote and solution casting technique for different concentrations of PbS. The characterization of the polymer nanocomposite films were carried out using UV-visible spectroscopy, SEM, and XRD. The effect of various concentration of PbS NP on the optical properties of the composite has been studied to understand the optimum conditions for the synthesis process. The nanocomposite film shows high UV and visible light absorptions in the wavelength range of (200-500) nm, which correspond to the characteristics of the PbS NPs. The significant decreasing trend of the direct allowed band gap of the nanocomposite was observed upon increasing the Pb source concentration, from (6.27 eV) for pure PVA to (2.34 eV) for 0.04 M PbS concentration, which is much higher than the energy gap of bulk PbS value (0.41 eV). The calculated values of the static refractive index of Cauchy dispersion model were in the range of (1.09-1.20). X-ray diffraction analysis confirmed the cubic nanocrystalline PbS phase formation.

The aim behind this study was to observe and understand barriers to access the eHealth system equally. The study was conducted in Stockholm based on qualitative data in which semi- structured interviews were conducted among 15 interviewees from different localities of Stockholm. The findings from the collected data revealed that language barriers, lack of knowledge about digital literacy, unawareness of Swedish healthcare services, psychological and social barriers, safety and privacy concerns, and the lack of an e-identification are all major barriers to accessing the eHealth system. From the data, it has also been observed that the main causes of the aforementioned hurdles are based on varied socioeconomic levels, literacy conditions of an individual, cultural background, and age. Another important observation shows that highly qualified people with limited language abilities have a difficult time using eHealth services. 

Keywords 

Ehealth, Covid-19, nudge approach, digital literacy, linguistic skills, Bank ID, 1177.se, Alltid öppet. 

The aim behind this study was to observe and understand barriers to access the eHealth system equally. The study was conducted in Stockholm based on qualitative data in which semi- structured interviews were conducted among 15 interviewees from different localities of Stockholm. The findings from the collected data revealed that language barriers, lack of knowledge about digital literacy, unawareness of Swedish healthcare services, psychological and social barriers, safety and privacy concerns, and the lack of an e-identification are all major barriers to accessing the eHealth system. From the data, it has also been observed that the main causes of the aforementioned hurdles are based on varied socioeconomic levels, literacy conditions of an individual, cultural background, and age. Another important observation shows that highly qualified people with limited language abilities have a difficult time using eHealth services. 

The fluctuation statistics of the observed sea-ice extent during the satellite era are compared with model output from CMIP5 models using a multifractal time series method. The two robust features of the observations are that on annual to biannual time scales the ice extent exhibits white noise structure, and there is a decadal scale trend associated with the decay of the ice cover. It is shown that (i) there is a large inter-model variability in the time scales extracted from the models, (ii) none of the models exhibits the decadal time scales found in the satellite observations, (iii) five of the 21 models examined exhibit the observed white noise structure, and (iv) the multi-model ensemble mean exhibits neither the observed white noise structure nor the observed decadal trend. It is proposed that the observed fluctuation statistics produced by this method serve as an appropriate test bed for modelling studies. This article is part of the theme issue 'Modelling of sea-ice phenomena'.

Addressing complexity in transportation in cases such as disruptive trends or disaggregated management strategies has become increasingly important. This in turn is resulting in the rising adoption of Agent-Based and Activity-Based modeling. Still, a broad adoption is hindered by the high complexity and computational needs. For example, hundreds of parameters are involved in the calibration of Activity-Based models focused on behavioral theory, to properly frame the required detailed socio-economical characteristics. To address this challenge, this paper presents a novel Bayesian Optimization approach that incorporates a surrogate model defined as an improved Random Forest to automate the calibration process of the behavioral parameters. The presented solution calibrates the largest set of parameters yet, according to the literature, by combining state-of-the-art methods. To the best of the authors' knowledge, this is the first work in which such a high dimensionality is tackled in sequential model-based algorithm configuration theory. The proposed method is tested in the city of Tallinn, Estonia, for which the calibration of 477 behavioral parameters is carried out. The calibration process results in a satisfactory performance for all the major indicators, the OD matrix average mismatch is equal to 15.92 vehicles per day while the error for the overall number of trips is equal to 4%.

As global average temperatures rise, so does the frequency and intensity of El Niño-induced droughts, which in turn threaten the reliability of hydropower. 1.4 billion people live in countries where hydropower constitutes more than a quarter of the electricity production and which have experienced El Niño droughts, meaning many more power outages can be expected around the world. Little research has been conducted on the impact of power outages on mental health. This study takes Zambia as its case study to examine the impact that El Niño droughts have had on the lives of householders connected to a highly hydropower-dependant electricity grid, and includes the impact it has had on their physical and self-reported mental health. Using 54 online responses to a survey, we found that the greatest impacts of outages spoiled food, compromised entertainment, compromised ability to work and limitation in cooking options. More than a fifth of respondents reported experiencing self-reported depression to a major degree or all of the time due to power outages, with individuals writing their own responses that they felt debilitated, experienced reduced communication and reduced activities, and stress. Using Bayesian inference, we found that changes in sleeping patterns arising from power outages was a statistically significant predictor of self-reported depression. 63% of surveyed households were willing to pay approximately USD 0.10/kWh as of the end of 2019, about double the tariff that they did, to ensure reliable electricity supply. Household income was a statistically significant predictor of willingness to pay more.

Many aquatic animals swim by undulatory body movements and understanding the diversity of these movements could unlock the potential for designing better underwater robots. Here, we analyzed the steady swimming kinematics of a diverse group of fish species to investigate whether their undulatory movements can be represented using a series of interconnected multi-segment models, and if so, to identify the key factors driving the segment configuration of the models. Our results show that the steady swimming kinematics of fishes can be described successfully using parsimonious models, 83% of which had fewer than five segments. In these models, the anterior segments were significantly longer than the posterior segments, and there was a direct link between segment configuration and swimming kinematics, body shape, and Reynolds number. The models representing eel-like fishes with elongated bodies and fishes swimming at high Reynolds numbers had more segments and less segment length variability along the body than the models representing other fishes. These fishes recruited their anterior bodies to a greater extent, initiating the undulatory wave more anteriorly. Two shape parameters, related to axial and overall body thickness, predicted segment configuration with moderate to high success rate. We found that head morphology was a good predictor of its segment length. While there was a large variation in head segments, the length of tail segments was similar across all models. Given that fishes exhibited variable caudal fin shapes, the consistency of tail segments could be a result of an evolutionary constraint tuned for high propulsive efficiency. The bio-inspired multi-segment models presented in this study highlight the key bending points along the body and can be used to decide on the placement of actuators in fish-inspired robots, to model hydrodynamic forces in theoretical and computational studies, or for predicting muscle activation patterns during swimming.

This thesis examines the cybersecurity incident response problem using a socio-technical approach. The motivation of this work is the need to bridge the knowledge and practise gap that exists because of the increasing complexity of cybersecurity threats and our limited capability of applying cybersecurity controls necessary to adequately respond to these threats. Throughout this thesis, knowledge from Systems Theory, Soft Systems Methodology and Socio-Technical Systems is applied to examine and document the socio-technical properties of cybersecurity incident response process. The holistic modelling of cybersecurity incident response process developed concepts and methods tested to improve the socio-technical security controls and minimise the existing gap in security controls.

The scientific enquiry of this thesis is based on pragmatism as the underpinning research philosophy.  The thesis uses a design science research approach and embeds multiple research methods to develop five artefacts (concept, model, method, framework and instantiation) outlined in nine peer-reviewed publications. The instantiated artefact embraces the knowledge developed during this research to provide a prototype for a socio-technical security information and event management system (ST-SIEM) integrated with an open source SIEM tool. The artefact relevance was validated through a panel of cybersecurity experts using a Delphi method. The Delphi method indicated the artefact can improve the efficacy of handling cybersecurity incidents.

Driver fatigue is a contributing factor in about 20% of all fatal road crashes worldwide. Countermeasures are urgently needed and one of the most promising and currently available approaches for that are in-vehicle systems for driver fatigue detection. The main objective of this paper is to present a video-based driver sleepiness detection system set up as a two-stage model with (1) a generic deep feature extraction module combined with (2) a personalised sleepiness detection module. The approach was designed and evaluated using data from 13 drivers, collected during naturalistic driving conditions on a motorway in Sweden. Each driver performed one 90-minute driving session during daytime (low sleepiness condition) and one session during night-time (high sleepiness condition). The sleepiness detection model outputs a continuous output representing the Karolinska Sleepiness Scale (KSS) scale from 1-9 or a binary decision as alert (defined as KSS 1-6) or sleepy (defined as KSS 7-9). Continuous output modelling resulted in a mean absolute error (MAE) of 0.54 KSS units. Binary classification of alert or sleepy showed an accuracy of 92% (sensitivity = 91.7%, specificity = 92.3%, F1 score = 90.4%). Without personalisation, the corresponding accuracy was 72%, while a standard fatigue detection PERCLOS-based baseline method reached an accuracy of 68% on the same dataset. The developed real-time sleepiness detection model can be used in the management of sleepiness/fatigue by detecting precursors of severe fatigue, and ultimately reduce sleepiness-related road crashes by alerting drivers before high levels of fatigue are reached.

A model based on a specific phantom, called QuAArC, has been designed for the evaluation of planning and verification systems of complex radiotherapy treatments, such as volumetric modulated arc therapy (VMAT). This model uses the high accuracy provided by the Monte Carlo (MC) simulation of log files and allows the experimental feedback from the high spatial resolution of films hosted in QuAArC. This cylindrical phantom was specifically designed to host films rolled at different radial distances able to take into account the entrance fluence and the 3D dose distribution. Ionization chamber measurements are also included in the feedback process for absolute dose considerations. In this way, automated MC simulation of treatment log files is implemented to calculate the actual delivery geometries, while the monitor units are experimentally adjusted to reconstruct the dose-volume histogram (DVH) on the patient CT. Prostate and head and neck clinical cases, previously planned with Monaco and Pinnacle treatment planning systems and verified with two different commercial systems (Delta4 and COMPASS), were selected in order to test operational feasibility of the proposed model. The proper operation of the feedback procedure was proved through the achieved high agreement between reconstructed dose distributions and the film measurements (global gamma passing rates > 90% for the 2%/2 mm criteria). The necessary discretization level of the log file for dose calculation and the potential mismatching between calculated control points and detection grid in the verification process were discussed. Besides the effect of dose calculation accuracy of the analytic algorithm implemented in treatment planning systems for a dynamic technique, it was discussed the importance of the detection density level and its location in VMAT specific phantom to obtain a more reliable DVH in the patient CT. The proposed model also showed enough robustness and efficiency to be considered as a pre-treatment VMAT verification system.

We propose a novel method for achieving the average consensus in a distributed manner while dealing with communication compression. While it is widely recognized that distributed consensus algorithms with compression can falter due to compression-error-induced divergences, our approach integrates an error correction step to guarantee convergence towards an approximate average consensus across any bounded compression function. Significantly, with our error correction mechanism, we can achieve convergence to a solution of arbitrarily high accuracy, irrespective of how crude the compression is in a fully distributed setting. Additionally, we quantify the convergence rate and provide upper bounds for the estimation error based on the spectral properties of the underlying communication network. Simulation results validate the scalability and efficacy of our proposed algorithm.

Large-scale neural simulations encompass challenges in simulator design, data handling and understanding of simulation output. As the computational power of supercomputers and the size of network models increase, these challenges become even more pronounced. Here we introduce the experimental scalable neural simulator Nexa, for parallel simulation of large-scale neural network models at a high level of biological abstraction and for exploration of the simulation methods involved. It includes firing-rate models and capabilities to build networks using machine learning inspired methods for e.g. self-organization of network architecture and for structural plasticity. We show scalability up to the size of the largest machines currently available for a number of model scenarios. We further demonstrate simulator integration with online analysis and real-time visualization as scalable solutions for the data handling challenges.

One of the main advantages of second-order methods in a centralized setting is that they are insensitive to the condition number of the objective function's Hessian. For applications such as regression analysis, this means that less pre-processing of the data is required for the algorithm to work well, as the ill-conditioning caused by highly correlated variables will not be as problematic. Similar condition number independence has not yet been established for distributed methods. In this paper, we analyze the performance of a simple distributed second-order algorithm on quadratic problems and show that its convergence depends only logarithmically on the condition number. Our empirical results indicate that the use of second-order information can yield large efficiency improvements over first-order methods, both in terms of iterations and communications, when the condition number is of the same order of magnitude as the problem dimension.

Maintenance planning of trucks at Scania have previously been done using static cyclic plans with fixed sets of maintenance tasks, determined by mileage, calendar time, and some data driven physical models. Flexible maintenance have improved the maintenance program with the addition of general data driven expert rules and the ability to move sub-sets of maintenance tasks between maintenance occasions. Meanwhile, successful modelling with machine learning on big data, automatic planning using constraint programming, and route optimization are hinting on the ability to achieve even higher fleet utilization by further improvements of the flexible maintenance. The maintenance program have therefore been partitioned into its smallest parts and formulated as individual constraint rules. The overall goal is to maximize the utilization of a fleet, i.e. maximize the ability to perform transport assignments, with respect to maintenance. A sub-goal is to minimize costs for vehicle break downs and the costs for maintenance actions. The maintenance planner takes as input customer preferences and maintenance task deadlines where the existing expert rule for the component has been replaced by a predictive model. Using machine learning, operational data have been used to train a predictive random forest model that can estimate the probability that a vehicle will have a breakdown given its operational data as input. The route optimization takes predicted vehicle health into consideration when optimizing routes and assignment allocations. The random forest model satisfactory predicts failures, the maintenance planner successfully computes consistent and good maintenance plans, and the route optimizer give optimal routes within tens of seconds of operation time. The model, the maintenance planner, and the route optimizer have been integrated into a demonstrator able to highlight the usability and feasibility of the suggested approach.

In this paper, using the shrinkage-based approach for portfolio weights and modern results from random matrix theory we construct an effective procedure for testing the efficiency of the expected utility (EU) portfolio and discuss the asymptotic behavior of the proposed test statistic under the high-dimensional asymptotic regime, namely when the number of assets p increases at the same rate as the sample size n such that their ratio p/n approaches a positive constant c is an element of (0, 1) as n -> infinity. We provide an extensive simulation study where the power function and receiver operating characteristic curves of the test are analyzed. In the empirical study, the methodology is applied to the returns of S&P 500 constituents.

In this paper, we construct two tests for the weights of the global minimum variance portfolio (GMVP) in a high-dimensional setting, namely, when the number of assets p depends on the sample size n such that p/n -> c is an element of (0, 1) as n tends to infinity. In the case of a singular covariance matrix with rank equal to q we assume that q/n -> <(c)over tilde is an element of (0,1) as n -> infinity. The considered tests are based on the sample estimator and on the shrinkage estimator of the GMVP weights. We derive the asymptotic distributions of the test statistics under the null and alternative hypotheses. Moreover, we provide a simulation study where the power functions and the receiver operating characteristic curves of the proposed tests are compared with other existing approaches. We observe that the test based on the shrinkage estimator performs well even for values of c close to one.

We consider the game-theoretic approach to time-inconsistent stopping of a onedimensional diffusion where the time-inconsistency is due to the presence of a nonexponential (weighted) discount function. In particular, we study (weak) equilibria for this problem in a novel class of mixed (i.e., randomized) stopping times based on a local time construction of the stopping intensity. For a general formulation of the problem we provide a verification theorem giving sufficient conditions for mixed (and pure) equilibria in terms of a set of variational inequalities, including a smooth fit condition. We apply the theory to prove the existence of (mixed) equilibria in a recently studied real options problem in which no pure equilibria exist.

We consider a continuous time stochastic dynamic game between a stopper (the owner of an asset) and a controller (the manager ) who is either effective or non -effective. An effective manager can exert high or low effort which corresponds to a high or a low positive drift for the accumulated income of the owner with random noise in terms of Brownian motion. The manager earns a salary until the owner stops the game. A non -effective manager cannot act but receives a salary. We find a threshold (Nash) equilibrium using stochastic filtering methods in a weak formulation.

Until the day comes when all vehicles are fully autonomous, self-driving cars must be more than safe and efficient, they must also understand and interact naturally with human drivers. The web extras include videos demonstrating "rude" behavior by Tesla's Autopilot system, www.youtube.com/watch?v=el4OdwtgzNk; a human driver confused by self-driving technology, www.youtube.com/watch?v=Uj-rK8V-rik; and aggressive driving prompted by self-driving technology, www.youtube.com/watch?v=FbSQm3YaAzA.

This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6%.

Y1-xGdxBa2Cu3O7-BaHfO3 (YGBCO-BHO) nanocomposite films containing 12 mol% BHO nanoparticles and different amounts of Gd,x, were grown by Chemical Solution Deposition (CSD) on Ni5W substrates in order to investigate the impact of the rare-earth stoichiometry on the structure and superconducting properties of these films. For Gd contentsx>0.5, epitaxial YGBCO-BHO films with an approximate thickness of 270 nm self-field critical current density Jc at 77 K∼1,5 MA/cm² were obtained. The field dependence of the critical current density Jc (B) shows a much larger accommodation field and lower exponents α in Jc∼B−α values compared to pristine YBCO films. This is both due to the high amount of individual nanoparticles in the matrix as observed in TEM images and thehigher critical temperatures Tc. The results show that the CSD is a potential candidate for the preparation of REBCO films in long-length coated conductors.

The stability of payment system is of vital importance to the credit market as well as the economic development. Most researches focus on the effect of system connectivity on systemic risk and demonstrate that connectivity provides both risk-spread channel and risk-sharing mechanism. But the management of systemic risk is quite different in real-time gross settlement system and net settlement system. We provide an integrated analysis of the effect of connectivity and netting on systemic risk in payment systems by considering more detailed network structures of pure creditors and pure debtors. We show that the effect of netting is partly due to the change of network connectivity, which severs the contagion channel of shocks. Moreover, netting can lower the actual magnitude of the shock from the beginning by reducing source bank's debt.

Thesis supervision is one of the most complex and problematic pedagogical methods(Connell, 1985). Hansson and others discuss this complexity and show that the core activities of supervision require (an estimated) four to five times more effort per individual student than the payment/time allocated (Hansson, Larsson, & Wettergren, 2009). These authors also discuss the nature of thesis supervision and argue that a large part of the process is dependent on communication. Communication is time-consuming and hence may be one of the reasons for this problematic state of affairs; maintaining the quality of communication is a challenge. The Department of Computer and Systems Sciences (DSV) faced this challenge when several theses were reviewed by the Swedish Authority of Higher Education (Bider & Jalali, 2016). The DSV initiated a project to implement an ICT-supported system for the thesis supervision process in 2011 in order to address the issue of quality. Sci-Pro, the thesis supervision support system, was launched in 2011 and has grown into a mature system during the last six years. There is a lack of comprehensive studies of ICT support systems; the aim of the current study is to conduct a literature review of the published articles about the DSV thesis supervision system to explore how ICT can support the thesis supervision process. The results of this study therefore offer benefits to individuals who intend to develop or use ICT support for the thesis process.

Text matching tools employed to detect plagiarism are widely used in universities, but their availability may have pushed students to find ways to evade detection. One such method is the use of automatic paraphrasing software, where assignments can be rewritten with little effort required by students. This paper uses the search engine analytics methodology with data from SEMrush and Google Trends to estimate the level of interest in online automatic paraphrasing tools, focusing on the period 2016 to 2020 and the four countries: the USA, UK, Canada and Australia. The results show a concerning trend, with the number of searches for such tools growing during the period, especially during COVID-19, and notable increases observed during the months where assessment periods take place in universities. The method employed in this study opens up a new avenue of analysis to enrich and supplement the existing knowledge in the field of academic integrity research. The data obtained demonstrates that faculty should be alert for student use of automatic paraphrasing tools and that academic integrity interventions need to be in place across the sector to address this problem.

Images taken with time-of-flight (TOF) positron emission tomography (PET) scanners are of improved quality compared to equivalent non-TOF images. This improvement is dependent on the scanner time resolution. The present generation of commercial TOF scanners has a time resolution in the range of 500-600 ps full width half maximum. In this work we investigate how the image characteristics will improve for future generations of TOF PET. We performed a Geant4 simulation of a 30-cm uniform cylinder containing hot spheres, with time resolution ranging from 600 to 200 ps. Data were reconstructed using TOF filtered back projection (FBP) and TOF ordered subsets expectation maximization (OSEM), with nonTOF reconstruction as a reference. Images were compared in terms of contrast recovery and variance in the image. The TOF gain was evaluated for both reconstruction methods. The TOF gain was also evaluated vs. counts in the scan, in order to understand the behavior of such gain at very low statistics. Using TOF FBP, it was shown that the TOF gain can be used as a sensitivity amplifier, reducing (according to the expected TOF gain) the number of counts necessary to produce an image of the same characteristics. Some limitations in the TOF gain were observed at very low counts, particularly if using iterative methods.

Research and development (R&D) in the pharmaceutical sector traditionally operated with in closed, siloed institutional settings, driven by intellectual property rights concerns that viewed data sharing as a threat. However, the evolving scientific landscape demands a more collaborative approach involving external engagement and dynamic partnerships. To address this, a hybrid contractual framework combining smart contracts, non-fungible tokens (NFTs), and traditional licensing schemes is introduced. This framework was developed through an experimental pilot platform that adhered to FAIR data principles, allowing participants to store, find, and reuse data related to drug discovery. The platform utilizes blockchain technology to document real-world assets in an immutable digital ledger. Smart contracts and NFTs offer an open and global collaborative platform for advancing drug research assets, overcoming hurdles related to standardization, interoperability, and disclosure. This framework aims to reconcile the conflict between the demand for greater data sharing and the protection of rightsholder interests in pharmaceutical R&D. By providing mechanisms for resolving practical challenges, it facilitates further cooperation and innovation in the field. 

This article discusses some of the findings of a study that bridges an existing knowledge gap by focusing on identifying influences on the wider adoption and uptake of TEL techniques by HEIs in Nairobi. In this context, TEL techniques can encompass e-learning, blended learning, using massive open online courses (MOOCs), or an entirely online course delivery. This study examines why HEIs are using TEL, perceived benefits and challenges of using TEL from an institutional and instructor perspective, and the impact of policies. The findings have important research, practical, societal, and policy making implications for educational delivery on a continent with a rapidly growing population. Findings will assist decision making, inform policy creation, and provide useful foundational reference material for further comparative research in Africa. The lessons learned will also assist tertiary level institutions across the African continent that wish to plan for wider TEL adoption, or to implement TEL in a more effective manner, by considering common challenges that could limit adoption.

Hamiltonian Monte Carlo (HMC) samples efficiently from high-dimensional posterior distributions with proposed parameter draws obtained by iterating on a discretized version of the Hamiltonian dynamics. The iterations make HMC computationally costly, especially in problems with large data sets, since it is necessary to compute posterior densities and their derivatives with respect to the parameters. Naively computing the Hamiltonian dynamics on a subset of the data causes HMC to lose its key ability to generate distant parameter proposals with high acceptance probability. The key insight in our article is that efficient subsampling HMC for the parameters is possible if both the dynamics and the acceptance probability are computed from the same data subsample in each complete HMC iteration. We show that this is possible to do in a principled way in a HMC-within-Gibbs framework where the subsample is updated using a pseudo marginal MH step and the parameters are then updated using an HMC step, based on the current subsample. We show that our subsampling methods are fast and compare favorably to two popular sampling algorithms that use gradient estimates from data subsampling. We also explore the current limitations of subsampling HMC algorithms by varying the quality of the variance reducing control variates used in the estimators of the posterior density and its gradients.

The paper presents group decision assessment for the Internet services in the context of development (ISCD). The assessment is achieved through the use of a decision model whose fundamental goal is to provide a systematic approach for addressing the problem of misalignments among the Internet stakeholders’ objectives. The modelling of the problem is approached from the perspectives of delivering/receiving the Internet services that maximizes the respective stakeholders’ objectives. Based on the AHP theory, it structures the problem into four hierarchies with three aspects of consideration as (a) services relevance in context of development, (b) services delivery mechanism convergence to IP Infrastructure and (c) services commensurability to traffic classes’ requirements. An assessment of the aggregated individually derived final priorities (AIP) reveals that for aligning the stakeholders’ objectives at local level, end users should first strive to implement the Internet components/applications that can cause high impact to their transactions/business, followed by those services/applications that can “empower” them to fulfil their goals. While at global level, the affordability of recurring subscriptions for Internet access, end user terminal equipment cost, and coverage rage/penetration are the key issues that the policy makers should address in view of achieving the ISCD objectives. Finally the paper includes strategic options for the best course of action in aligning the stakeholders’ objectives.

The distribution-free chain ladder of Mack justified the use of the chain ladder predictor and enabled Mack to derive an estimator of conditional mean squared error of prediction for the chain ladder predictor. Classical insurance loss models, that is of compound Poisson type, are not consistent with Mack’s distribution-free chain ladder. However, for a sequence of compound Poisson loss models indexed by exposure (e.g., number of contracts), we show that the chain ladder predictor and Mack’s estimator of conditional mean squared error of prediction can be derived by considering large exposure asymptotics. Hence, quantifying chain ladder prediction uncertainty can be done with Mack’s estimator without relying on the validity of the model assumptions of the distribution-free chain ladder.

Introduction: Backchannels, i.e., short interjections by an interlocutor to indicate attention, understanding or agreement regarding utterances by another conversation participant, are fundamental in human-human interaction. Lack of backchannels or if they have unexpected timing or formulation may influence the conversation negatively, as misinterpretations regarding attention, understanding or agreement may occur. However, several studies over the years have shown that there may be cultural differences in how backchannels are provided and perceived and that these differences may affect intercultural conversations. Culturally aware robots must hence be endowed with the capability to detect and adapt to the way these conversational markers are used across different cultures. Traditionally, culture has been defined in terms of nationality, but this is more and more considered to be a stereotypic simplification. We therefore investigate several socio-cultural factors, such as the participants’ gender, age, first language, extroversion and familiarity with robots, that may be relevant for the perception of backchannels.

Methods: We first cover existing research on cultural influence on backchannel formulation and perception in human-human interaction and on backchannel implementation in Human-Robot Interaction. We then present an experiment on second language spoken practice, in which we investigate how backchannels from the social robot Furhat influence interaction (investigated through speaking time ratios and ethnomethodology and multimodal conversation analysis) and impression of the robot (measured by post-session ratings). The experiment, made in a triad word game setting, is focused on if activity-adaptive robot backchannels may redistribute the participants’ speaking time ratio, and/or if the participants’ assessment of the robot is influenced by the backchannel strategy. The goal is to explore how robot backchannels should be adapted to different language learners to encourage their participation while being perceived as socio-culturally appropriate.

Results: We find that a strategy that displays more backchannels towards a less active speaker may substantially decrease the difference in speaking time between the two speakers, that different socio-cultural groups respond differently to the robot’s backchannel strategy and that they also perceive the robot differently after the session.

Discussion: We conclude that the robot may need different backchanneling strategies towards speakers from different socio-cultural groups in order to encourage them to speak and have a positive perception of the robot.

Organic electrochemical transistors (OECTs) are promising devices for bioelectronics, such as biosensors. However, current cleanroom-based microfabrication of OECTs hinders fast prototyping and widespread adoption of this technology for low-volume, low-cost applications. To address this limitation, a versatile and scalable approach for ultrafast laser microfabrication of OECTs is herein reported, where a femtosecond laser to pattern insulating polymers (such as parylene C or polyimide) is first used, exposing the underlying metal electrodes serving as transistor terminals (source, drain, or gate). After the first patterning step, conducting polymers, such as poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), or semiconducting polymers, are spin-coated on the device surface. Another femtosecond laser patterning step subsequently defines the active polymer area contributing to the OECT performance by disconnecting the channel and gate from the surrounding spin-coated film. The effective OECT width can be defined with high resolution (down to 2 µm) in less than a second of exposure. Micropatterning the OECT channel area significantly improved the transistor switching performance in the case of PEDOT:PSS-based transistors, speeding up the devices by two orders of magnitude. The utility of this OECT manufacturing approach is demonstrated by fabricating complementary logic (inverters) and glucose biosensors, thereby showing its potential to accelerate OECT research. 

Upgrade plans for the ATLAS hadronic tile calorimeter (TileCal) at the LHC include full granularity readout to the 1st level trigger. R&D activities at different laboratories target different parts of the upgraded system. We are developing a possible implementation of the future readout electronics to be included in a full functional demonstrator. This must be capable of adapting to each of the three different front-end alternatives being considered. Prototypes of the two PCBs that will be in charge of digitization, control and communication have been developed. The design is redundant and uses FPGAs with fault tolerant firmware for control and protocol conversion. Communication and clock synchronization between on and offdetector electronics is implemented via high speed optical links using the GBT protocol.

The spatial resolution in positron emission tomography (PET) can be improved by the addition of depth-of-interaction (DOI) information. This can be achieved by using the phoswich approach in which depth identification relies on differences in scintillation decay time and pulse shape discrimination techniques. In this paper we have looked at a special phoswich combination LuAP/LSO or LuYAP/LSO. This combination of scintillators is especially interesting since LuAP and LuYAP have emission in the excitation band of LSO, which may have an impact on the timing resolution of the detector. As will be shown in this paper, the phoswich concept based on these two scintillators can be utilized, however, with some limitations. This paper is an extension of our previous phoswich investigation [3].

In this work, we introduce a lightweight discourse connective detection system. Employing gradient boosting trained on straightforward, low-complexity features, this proposed approach sidesteps the computational demands of the current approaches that rely on deep neural networks. Considering its simplicity, our approach achieves competitive results while offering significant gains in terms of time even on CPU. Furthermore, the stable performance across two unrelated languages suggests the robustness of our system in the multilingual scenario. The model is designed to support the annotation of discourse relations, particularly in scenarios with limited resources, while minimizing performance loss.

Function optimisation is a major challenge in computer science. The No Free Lunch theorems state that if all functions with the same histogram are assumed to be equally probable then no algorithm outperforms any other in expectation. We argue against the uniform assumption and suggest a universal prior exists for which there is a free lunch, but where no particular class of functions is favoured over another. We also prove upper and lower boundson the size of the free lunch.

Samverkan mellan vårdgivare inom och mellan Region Stockholm och Stockholms stad är en stor utmaning för både hälso- och sjukvård samt omsorg (förkortat vård och omsorg). Brister i informationsöverföring kan få negativa konsekvenser som sämre kvalitet och minskad effektivitet. Det gäller särskilt för de äldre personer som ofta slussas mellan öppen och sluten vård samt omsorg. 

I denna rapport redogörs för resultatet av projektet Digitalisering av vård- och omsorg, DISVO-projektet. Projektet är inriktat på samverkan mellan Region Stockholm och Stockholms stad, med fokus på de IT-mässiga och legala förutsättningar som finns för samverkan inom vård och omsorg. Studien bygger på en beskrivning av ett scenario för samverkan, samt genom en inventering av de regleringar i form av lagar och förordningar m.m. som styr vård och omsorg samt en inventering av de IT-system som används för samverkan i regionen och staden. 

Projektets resultat utgörs av en beskrivning och analys av juridiska och tekniska förutsättningar, hinder och möjligheter kring informationsöverföring för vård och omsorg. 

En granskning av de tekniska förutsättningarna för samverkan i form av systemanvändning visar på ett antal identifierade brister. Vad gäller de system som används så finns det, inte oväntat, ett behov av att i högre grad integrera systemen. Det som även framkom är att en ökad grad av användning av befintliga systemlösningar, som exempelvis den nationella patientöversikten (NPÖ), kan råda bot på brist på information. Ytterligare problem är att vissa system upplevs som komplexa, där det bland annat är svårt att ge behörighet till vissa grupper av användare. Behov av direkt kommunikation mellan användare har idag bristfälligt stöd i systemen, vilket leder till användning av telefon och fax. Framöver är det lämpligt att ett fokus läggs på användningen av lösningar som ger bättre möjlighet till integration. 

Granskningen av de juridiska aspekterna visar att lagstiftningen skulle kunna ändras mot ett tydligare individperspektiv med beaktande av behovet av information för såväl en god vård och omsorg som forskningssamhället. Det innebär t.ex. att nya sekretessbrytande bestämmelser behövs, men också att befintliga sådana skulle behöva reformeras för att anpassas till den digitaliserade vården och omsorgen. Sådana reformer får emellertid inte innebära att skyddet för den personliga integriteten vid behandling personuppgifter inskränks på ett oproportionerligt sätt. Det bör i första hand krävas samtycke från de enskilda för att bryta sekretessen, men lagstiftningen 2 

måste också kunna tillämpas i de situationer då en enskild har nedsatt eller saknar beslutsförmåga. 

I vissa situationer tillämpas inte lagen fullt ut, t.ex. vid användningen av samordnad individuell planering. Ett annat problem är att de möjligheter till digitalisering som regelverken öppnar upp för inte utnyttjas fullt ut, såsom sammanhållen journalföring. Integration av system är vidare centralt för att befintliga bestämmelser ska tillämpas på ett effektivt sätt och få fullt genomslag. Ett exempel är patientdatalagen (2008:355), vilken möjliggör sammanhållen journalföring. Sammanhållen journalföring hindras dock delvis av att system är svåra att integrera. Det finns även exempel där både tekniska och rättsliga rekvisit finns på plats, men där brister finns i själva systemanvändningen, t.ex. vid tillämpningen av lagen (2017:612) om samverkan vid utskrivning från sluten hälso- och sjukvård vilken stöds av systemet WebCare. De brister som finns idag uppvägs av att personalen vidtar andra åtgärder för att säkerställa att rätt information förmedlas, såsom användning av telefon eller fax. 

The performance of the uplink of single and multiuser multiple input multiple output (MIMO) systems depends crucially on the receiver architecture and the quality of channel state information at the receiver. Therefore, several previous works have developed minimum mean squared error (MMSE) receivers and proposed balancing the resources spent on acquiring channel state information and transmitting the payload of data packets. Somewhat surprisingly, the most popular MIMO linear MMSE receivers do not exploit the correlation structure that is present in autoregressive Rayleigh fading environments. Therefore, in this article we first develop a new linear receiver that not only takes channel state information errors into account in minimizing the MSE of the received data symbols, but it also utilizes that the subsequent noisy channel coefficients are correlated. For this new linear MMSE receiver, we derive the achieved MSE as a function of the number of receive antennas and the pilot-to-data power ratio. Interestingly, we find that the pilot power that minimizes the MSE of the data symbols does not depend on the number of antennas and that the new linear MMSE receiver outperforms previously proposed MIMO receivers when the autocorrelation coefficient of the channel is high.

Minimizing the symbol error in the uplink of multi-user multiple input multiple output systems is important, because the symbol error affects the achieved signal-to-interference-plus-noise ratio (SINR) and thereby the spectral efficiency of the system. Despite the vast literature available on minimum mean squared error (MMSE) receivers, previously proposed receivers for block fading channels do not minimize the symbol error in time-varying Rayleigh fading channels. Specifically, we show that the true MMSE receiver structure does not only depend on the statistics of the CSI error, but also on the autocorrelation coefficient of the time-variant channel. It turns out that calculating the average SINR when using the proposed receiver is highly non-trivial. In this paper, we employ a random matrix theoretical approach, which allows us to derive a quasi-closed form for the average SINR, which allows to obtain analytical exact results that give valuable insights into how the SINR depends on the number of antennas, employed pilot and data power and the covariance of the time-varying channel. We benchmark the performance of the proposed receiver against recently proposed receivers and find that the proposed MMSE receiver achieves higher SINR than the previously proposed ones, and this benefit increases with increasing autoregressive coefficient.

Field measurements and numerical modelling were used to study the acoustic performance of a low screen in an urban road setting. The results show the usefulness of low screens as well as suggests improvements in screen design. For the measurements, an acoustic screen built up from concrete modules was temporarily installed beside a small park on the reservation between a two-lane road and a track for walking and cycling. A larger traffic system, of which the two-lane road is a part, determines the daytime equivalent noise level within the urban area. The screen height was about 1.4m as measured from the level of the road surface and the width of the screen top was 0.3 m. Measurements were carried out both at 20 m distance from the road (within the park) and at 5 m distance from the road (at the cycle track). Insertion loss in maximum level, using controlled light-vehicle pass-by at 50 km/h, was measured to 10 dB at 5 m distance and to 6 dB at 20 m distance, at 1.5 m height. Insertion loss in equivalent level was measured within the park to 4 dB at 1.5 m height. A listening experiment confirmed a perceived improvement from installing the screen. The measured results were also compared with predicted results using a boundary element method (BEM) and a noise mapping software, the latter showing good agreement, overestimating the equivalent level insertion loss by 1 dB in the park. The BEM comparison showed reasonable agreement in maximum level insertion loss considering that facade reflections were excluded, with an overestimation of 5 dB at the cycle track, and good agreement in the park, overestimating by up to 1 dB the equivalent and maximum level insertion losses. BEM predictions were used to also investigate other screen designs, showing a positive effect of an acoustically soft screen top, significant for a screen width of 0.2 m and increasing for wider screens.

Vocal sound imitations provide a new challenge for understanding the coupling between articulatory mechanisms and the resulting audio. In this study, the classification of three articulatory categories, phonation, supraglottal myoelastic vibrations, and turbulence, have been modeled from audio recordings. Two data sets were assembled, consisting of different vocal imitations by four professional imitators and four non-professional speakers in two different experiments. The audio data were manually annotated by two experienced phoneticians using a detailed articulatory description scheme. A separate set of audio features was developed specifically for each category using both time-domain and spectral methods. For all time-frequency transformations, and for some secondary processing, the recently developed Auditory Receptive Fields Toolbox was used. Three different machine learning methods were applied for predicting the final articulatory categories. The result with the best generalization was found using an ensemble of multilayer perceptrons. The cross-validated classification accuracy was 96.8% for phonation, 90.8% for supraglottal myoelastic vibrations, and 89.0% for turbulence using all the 84 developed features. A final feature reduction to 22 features yielded similar results.

The paper examines the Internet usage and itsmarket environment in developing countries under theperceived assumption that the Internet is one of the mostimportant drivers for development. It gives an insight onprocesses’ (both unintended and intended) implications andtheir effects on achieving real Internet benefits in theenvironments where network infrastructures are limited suchas the ones found in the developing regions. A welfare basedapproach is proposed in which the Internet providers and endusersidentify a set of objective that leads them in achievingincreased benefits. Analytical model of the maincharacteristics in the approach is presented and eventuallyshown how the end user bit rate could be regulated based onthe utility bounds that lead general satisfaction to all users.User satisfaction signifies delivery of expected QoS and aswell as willing to pay for such services.

Information and communication technology and development (ICTD) is a research area that has broadly captured the attention of the public and the academics in the last two decades. It deals with the interaction and the relations between the humans and the society in general on one side and the technology on the other side. The focus in this thesis is on the computing and communication technology, herein referred to as the “Internet – the IP based technology”, which is seen as one of the enablers for economic and social growth.

The benefit of the Internet connectivity and usage in inducing and enhancing positive social changes in basic dimensions of human life is generally accepted as one of the most important drivers for development. The success and the inevitability of the Internet in the developed world underline its proliferation and diffusion essential in less developed countries. However, sometimes these processes are being impaired by unintended and intended consequences created by the social dynamics that drives the current information technological innovations and evolutions, stakeholders’ desire of fulfilling one’s utility egos, all coupled with market environments.

This thesis takes an insight in both unintended and intended implications and their effects on enabling development in the environments where the Internet Protocol (IP) based infrastructures are limited like in Least Developing regions/countries.  The results of this insight study have led in;

a)      Establishing the basic Internet services that would trigger the exploitation of one’s potential for development.

This has been achieved through the use of analytical scientific methods to classify Internet traffic characteristics and derive the relevance levels of their corresponding Internet services groups in fostering development.

b)      Developing a framework that lays down structure guidelines to facilitate Decision Makers especially in least developed countries to make scientifically informed subjective judgements for Internet services in the context of development.

c)      Designing and developing of the Internet Services in the Context of Developing (ISCD) model that enables the alignment of the apparent divergent/misalignment objectives of Internet stakeholders in the present Internet structure to have their respective maximised intended benefits.

Empirical testing of the model led in setting strategic options for aligning stakeholders goals in view of the ISCD along two main domains (i) network management policies – that focuses on provisions of services, and (ii) Internet consumption/usage – that focus on services relevance, commensurability to specific requirements as pertains LDCs, and services delivery mechanism convergence to all-IP.

The notion of fairness with respect to resource sharing among the competing flows is one of the important considerations in network design. This is true in particular for IP networks (which are the foundation of the Internet), where the service model is based on best effort and any possible distortion of it may lead to flow starvation and eventually system imbalances. In fact, fairness should be one of the major objectives both on a network layer and transport layer. This is evident in the case of elastic flows such as TCP, where fairness may have a major impact on congestion resolution. On a network layer, fairness mechanisms combined with scheduling and queuing policies lead to equitable service, which may also induce higher router utilization and hence better network performance. The paper investigates the current trends in understanding and applying the fairness concept on the Internet and hence in heterogeneous networks. Then it studies and examines the extension of the fairness concept in the context of development and developing regions, where both the traditional lack of infrastructure and costly communication services have also affected the penetration of the Internet and more even distribution of its benefits. The key question is whether or not it is plausible to identify a framework for the evaluation of efficiently-fairness tradeoffs that may provide a sound basis for a model of a more equitable access to the Internet to a diversity of users with different needs and financial possibilities representing mainly developing regions and emerging economies.