Tampere University

This letter proposes a methodology for phase-normalization of the complex-valued I/Q inputs of a real-valued time delay neural network (RVTDNN). The normalization enables modeling of the nonlinear behavior of a radio frequency (RF) power amplifier (PA) in a more efficient way, by complying with the physical characteristics of the distortions at RF. The presented digital predistortion (DPD) linearization experiments with a Doherty GaN PA at 3.5 GHz show a 4-dB improvement in the output linearity compared to state-of-the-art neural network (NN) and polynomial-based DPD models, allowing linearization to below $-$ 50 dBc adjacent channel leakage ratio (ACLR) levels with feasible processing complexity.

Second Harmonic Generation Microscopy (SHG) is widely acknowledged as a valuable non-linear optical imaging tool, its contrast mechanism providing the premises to non-invasively identify, characterize, and monitor changes in the collagen architecture of tissues. However, the interpretation of SHG data can pose difficulties even for experts histopathologists, which represents a bottleneck for the translation of SHG-based diagnostic frameworks to clinical settings. The use of artificial intelligence methods for automated SHG analysis is still in an early stage, with only few studies having been reported to date, none addressing ocular tissues yet. In this work we explore the use of three Deep Learning models, the highly popular InceptionV3 and ResNet50, alongside FLIMBA, a custom developed architecture, requiring no pre-training, to automatically detect corneal edema in SHG images of porcine cornea. We observe that Deep Learning models building on different architectures provide complementary results for the classification of cornea SHG images and demonstrate an AU-ROC = 0.98 for their joint use. These results have potential to be extrapolated to other diagnostics scenarios, such as automated extraction of hydration level of cornea, or identification of corneal edema causes, and thus pave the way for novel methods for precision diagnostics of the cornea with Deep-Learning assisted SHG imaging.

This article presents a direct model predictive con-trol (MPC) scheme for drive systems consisting of a three-phase three-level neutral-point-clamped (3L-NPC) inverter and an induction machine (IM). Even though the discussed MPC algorithm is a direct control strategy, it operates the inverter at a fixed switching frequency, while the output harmonic spectrum of the stator current is discrete, with harmonics at non-triplen, odd integer multiples of the fundamental frequency. As a result, the proposed method achieves similar or superior steady-state behavior than that of modulator-based control schemes. Moreover, thanks to its direct control nature, it exhibits the fast transient responses that characterize direct controllers due to the absence of an explicit modulator. Furthermore, the multiple control objectives of the system, i.e., stator current control and neutral point (NP) potential balancing, are addressed in one computational stage, thus avoiding any additional control loops in a cascaded or parallel structure. This favorable control structure is facilitated by the adopted modeling approach, according to which the system behavior is described by the gradient of the system output. In doing so, not only a simple, versatile system model is derived, but also the direct MPC can be formulated as a constrained quadratic program (QP), which can be easily solved in real time with an in-house solver. The effectiveness of the proposed control scheme is experimentally verified on a 4-kW drive system.

This paper focuses on indirect model predictive control (MPC) for variable speed drives, such as induction and synchronous machine drives. The optimization problem underlying indirect MPC is typically written as a standard constrained quadratic programming (QP) problem, which requires a QP solver to find the optimal solution. Although many mature QP solvers exist, solving the QP problems in industrial real-time embedded systems in a matter of a few tens of microseconds remains challenging. Instead of using the complex general-purpose QP solvers, this paper proposes a geometrical method for isotropic machine drives and an analytical method for anisotropic machine drives to find the optimal output voltage. This is done by examining and subsequently exploiting the geometry of the associated optimization problems. Both methods are simple, and easy to implement on industrial control platforms. The effectiveness of the proposed geometrical and analytical methods is demonstrated by experimental results for an induction machine drive and an interior permanent-magnet synchronous machine drive, respectively. Index Terms-Model predictive control (MPC), quadratic programming (QP), induction machine (IM), interior permanent-magnet synchronous machine (IPMSM).

Haptic upper limb exoskeletons are robots that assist human operators during task execution while having the ability to render virtual or remote environments. Therefore, ensuring the stability of such robots in physical human-robot-environment interaction (pHREI) is crucial. Having a wide range of Z-width, which indicates the region of passively renderable impedance by a haptic display, is also important for rendering a broad range of virtual environments. To address these issues, this study designs subsystem-based adaptive impedance control to achieve a stable pHREI for 7 degrees of freedom haptic exoskeleton. The presented controller decomposes the entire system into subsystems and designs the controller at the subsystem level. The stability of the controller in the presence of contact with a virtual environment and human arm force is proven by employing the concept of virtual stability. Additionally, the Z-width of the 7-DoF haptic exoskeleton is illustrated using experimental data and improved by exploiting varying virtual mass element. Experimental results are provided to demonstrate the performance of the controller. The control results are also compared to state-of-the-art control methods, highlighting the excellence of the designed controller.

We investigate explainability via short Boolean formulas in the data model based on unary relations. As an explanation of length k , we take a Boolean formula of length k that minimizes the error with respect to the target attribute to be explained. We first provide novel quantitative bounds for the expected error in this scenario. We then also demonstrate how the setting works in practice by studying three concrete data sets. In each case, we calculate explanation formulas of different lengths using an encoding in Answer Set Programming. The most accurate formulas we obtain achieve errors similar to other methods on the same data sets. However, due to overfitting, these formulas are not necessarily ideal explanations, so we use cross validation to identify a suitable length for explanations. By limiting to shorter formulas, we obtain explanations that avoid overfitting but are still reasonably accurate and also, importantly, human interpretable.

Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n = 10) and compared these with similar measurements from matched children who were either positive for a single autoantibody (n = 10) or autoantibody negative (n = 10). Following statistical analysis of the longitudinal data, targeted serum proteomics was used to verify 11 proteins putatively associated with the disease development in a similar yet independent and larger cohort of children who progressed to the disease within 5 years of age (n = 31) and matched autoantibody negative children (n = 31). These data reiterated extensive age-related trends for protein levels in young children. Further, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes, in comparison to autoantibody negative children.

This paper reports findings from a study focusing on user experience of image search tool utilizing content-based image retrieval methods. Previous studies have indicated challenges in textual image search especially in the historical domain. As a part of the project, a prototype tool was created for searching digitized historical images based on their visual contents to provide support for user needs identified in earlier studies. The tool was tested by 15 participants who evaluated their user experience with User Experience Scale and by verbal feedback. Our results indicate that participants derived benefits from the search capabilities provided by the tool, which went beyond relying on textual image descriptions. However, problems occurred, for example, in evaluating the search results and in user skills. Results also emphasize the value of intellectually produced metadata for image searching and use. Therefore, future developments should focus on creating hybrid systems supporting both textual and visual image searching.

Photoisomerization of azobenzenes from their stable E isomer to the metastable Z state is the basis of numerous applications of these molecules. However, this reaction typically requires ultraviolet light, which limits applicability. In this study, we introduce disequilibration by sensitization under confinement (DESC), a supramolecular approach to induce the E -to- Z isomerization by using light of a desired color, including red. DESC relies on a combination of a macrocyclic host and a photosensitizer, which act together to selectively bind and sensitize E -azobenzenes for isomerization. The Z isomer lacks strong affinity for and is expelled from the host, which can then convert additional E- azobenzenes to the Z state. In this way, the host–photosensitizer complex converts photon energy into chemical energy in the form of out-of-equilibrium photostationary states, including ones that cannot be accessed through direct photoexcitation.

Formal ontology as a main branch of metaphysics investigates categories of being. In the formal ontological approach to metaphysics, these ontological categories are analysed by ontological forms. This analysis, which the Element illustrates by some category systems, provides a tool to assess the clarity, exactness and intelligibility of different category systems or formal ontologies. It discusses critically different accounts of ontological form in the literature. Of ontological form, the authors propose a character-neutral relational account. In this metatheory, ontological forms of entities are their standings in internal relations whose holding is neutral on the character of their relata. These relations are 'formal ontological relations'. The Element concludes by showing that our metatheory is useful for understanding categorial fundamentality/non-fundamentality, different formal ontologies, and for unifying metaphysical questions.

This article develops a framework, based on recognition theory, for examining youth work services that target young Finnish adults who are not in education or employment. It complements previous research by examining targeted youth work (TYW) as an institutional context with specific ways of recognising young adults. Drawing upon Axel Honneth’s recognition theory and Randall Collins’ interaction ritual theory, it explores how the context can provide access to different kinds of recognition-based situations. Thus, the analysis addresses how the three different forms of recognition (care, respect, and esteem) are activated and experienced by young adults in targeted youth work. Examining data drawn from 35 interviews with young adults who have been or are currently outside of education or employment, the findings highlight the potential of targeted youth work to offer social interactions that can help clients to encounter care, respect, and esteem. Findings also reveal the potential challenges of providing recognition in targeted youth work, such as the lack of meaningful opportunities for self-determination and autonomy. This study contributes to research on how recognition theory can be understood and applied in social and youth work services.

This article contributes to the debate concerning pension financialization and how countries are adapting their pension systems to respond to demographic ageing. We do so by examining the statutory pension systems of Canada and Finland, which diverge interestingly from current international trends. The Canadian and Finnish public pension schemes reflect two tendencies often associated with pension financialization: an increasing reliance on financial markets and an investment policy with a diversified asset allocation. However, unlike in many other countries, this has not resulted in heightened individual risks in old‐age income security caused by a shift from defined benefit to defined contribution pensions – an otherwise common trend internationally.

p>Failures of structures occur in all parts of the world as the result of design errors, construction defects, abuse or misuse, ageing and deterioration of the structure, lack of maintenance, as well as environmental effects such as wind, flood, snow, earthquake and, of course, human errors. They can result in catastrophic human costs as well as heavy financial losses to all involved, including local economic growth deceleration, expensive delays and repairs, as well as other repercussions, such as legal actions to responsible parties. ‘Welcome’ effects of these unfortunate events include a better understanding of the origins and causes of structural failures, their corresponding lessons learnt, and a more effective mitigation of their occurrence through changes in codes, standards, guidelines, and practice. In several countries the investigation process of the causes of failures, responsibilities, and resolution of the consequent claims have created an active, demanding, and specialised field of professional practice – often referred to as Forensic Structural Engineering – with well-defined technical and legal procedures. This bulletin is the result of the work lead by the Task Group 5.1 ‘Forensic Structural Engineering’. It provides understanding of the origins, causes, and consequences of failures, their forensic investigations, and the lessons learnt from them. The aim of the bulletin is not only to describe different examples but, mainly, to use emblematic case studies to show procedures that can be used when dealing with structural failures. In addition to obtaining a deeper insight into the technical causes for structural failure, the reader would be duly informed about the different countries’ legal issues related to the investigation process. The bulletin is aimed at young, mid-career and experienced structural engineers who want to acquire a better understanding of failure mechanisms towards improving their design, inspection, construction, administrative, and other project-related practices to avoid pitfalls that may lead to failures. It also aims at those wanting to acquire a working knowledge of the challenging professional practice of forensic structural engineering.</p

Introduction Previous studies have shown that manual workers use less psychotherapy than non-manual workers. However, little is known about the match between the use and the need of psychotherapy in different occupational grades. Our study investigates how the prevalence of mental distress corresponds to psychotherapy use rate in different occupational grades by gender. Methods The data were collected from the Rise of Mental Vulnerability Study (use of psychotherapy) and the FinHealth 2017 Study (prevalence of mental distress). Adjusting for age, we calculated General Health Questionnaire (GHQ-12) caseness (a measure for mental distress), a 3-year psychotherapy use rate, and the ratio between GHQ caseness and the psychotherapy use rate in 3 occupational grades (upper non-manual employees, lower non-manual employees, and manual workers) for men and women separately. Results In men, for 1 person having used psychotherapy there were 10 persons experiencing mental distress in upper non-manual workers, 14 in lower non-manual workers, and 31 in manual workers. In women, for 1 person having used psychotherapy, there were 6 persons experiencing mental distress in upper non-manual workers, 9 in lower non-manual workers, and 18 in manual workers. Conclusions At the population level, manual employees use considerably less long-term psychotherapy than upper non-manual workers although their level of mental distress is high. This indicates a mismatch between symptoms and therapy, which was higher for men in all occupational grades.