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Being able to describe any user interface (UI) screenshot in natural language can promote understanding of the main purpose of the UI, yet currently it cannot be accomplished with state-of-the-art captioning systems. We introduce XUI, a novel method inspired by the global precedence effect to create informative descriptions of UIs, starting with an overview and then providing fine-grained descriptions about the most salient elements. XUI builds upon computational models for topic classification, visual saliency prediction, and natural language generation (NLG). XUI provides descriptions with up to three different granularity levels that, together, describe what is in the interface and what the user can do with it. We found that XUI descriptions are highly readable, are perceived to accurately describe the UI, and score similarly to human-generated UI descriptions. XUI is available as open-source software. Funding Information: We acknowledge the computational resources provided by the Aalto Science-IT project. We thank Homayun Afrabandpey, Daniel Buschek, Jussi Jokinen, and Jörg Tiedemann for reviewing an earlier draft of this article. This work has been supported by the Horizon 2020 FET program of the European Union through the ERA-NET Cofund funding (grant CHIST-ERA-20-BCI-001), the European Innovation Council Pathfinder program (SYMBIOTIK project), and the Academy of Finland (grants 291556, 318559, 310947). Publisher Copyright: © 2022 Copyright held by the owner/author(s). Publication rights licensed to ACM. Peer reviewed

In our submission to the SIGMORPHON 2022 Shared Task on Morpheme Segmentation, we study whether an unsupervised morphological segmentation method, Morfessor, can help in a supervised setting. Previous research has shown the effectiveness of the approach in semisupervised settings with small amounts of labeled data. The current tasks vary in data size: the amount of word-level annotated training data is much larger, but the amount of sentencelevel annotated training data remains small. Our approach is to pre-segment the input data for a neural sequence-to-sequence model with the unsupervised method. As the unsupervised method can be trained with raw text data, we use Wikipedia to increase the amount of training data. In addition, we train multilingual models for the sentence-level task. The results for the Morfessor-enriched features are mixed, showing benefit for all three sentencelevel tasks but only some of the word-level tasks. The multilingual training yields considerable improvements over the monolingual sentence-level models, but it negates the effect of the enriched features. Peer reviewed

Dynamic properties of civil structures such as natural frequencies, damping ratios, and mode shapes are essential parameters for evaluating the health condition of structures. However, dynamic properties are prone to be biased by environmental effects which may lead to fault structural health assessment. To investigate the environmental effect on the dynamic parameters of ballasted bridge, in this paper, a series of vibration experiments were performed on a multi-span pre-stressed concrete beam railway bridge. The dynamic properties of the bridge were identified and analyzed. In total, 9 experiments were conducted in 2 years. In the first 8 experiments, only sleepers and tracks had been removed. For the last experiment, the bridge was under destruction. The subsidiary components of the structure were destructed, and some holes were drilled on the slab for hoisting. The results show a clear seasonal variation in natural frequencies that in winters the natural frequencies reach local maximum values. Damping ratios show no clear variation regularity, indicating the complex correlation between the damping ratios and the environmental variation. Additionally, compression tests of concrete pieces of the slab were also conducted to investigate the degradation of material properties. The result of the compression tests indicates that there is approximately no degradation of compression strength of the concrete slab after the bridge was in service for several over 4 decades. Funding Information: This research was financially supported by Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Research(C) Grant Number 15K06176, Japanese Government Scholarship (MEXT), and the Academy of Finland (decision number: 339493). The contributions of Mr. Yuta Shirakawa, Ms. Sanae Suzuki, Mr. Kaneyoshi Okada, Dr. Tomoyuki Yamazaki, Dr. Shunzo Kawajiri, and the Kitami City Government were greatly acknowledged. Publisher Copyright: © 2023 The Author(s) Peer reviewed

Rechargeable lithium-oxygen (Li-O2) batteries have been regarded as a promising energy storage device, but its practical use is impeded by its low energy efficiency. Herein, a bi-functional catalytic perovskite LaNi0.5Co0.5O3 (LNCO) is employed as the cathode of an efficient Li-O2 battery with a molten nitrate salt electrolyte at 160 °C. It displays a stable low charge–discharge overpotential 50 mV with a high energy efficiency (EE) 98.2 % at 0.1 mA cm−2 for over 100 cycles. The excellent performance is attributed to the extremely fast oxygen reduction and evolution kinetics on the surface of LNCO. The discharge product is Li2O with a porous and fluffy morphology which facilitates the transfer of oxygen and other intermediate species. It is noted that Li2O as a discharge product enables a theoretical specific energy density of 5200 Wh kg−1, which is superior to the Li2O2 as product giving 3500 Wh kg−1 for those ambient temperature Li-O2 batteries. Funding Information: This work was supported with the start-up package of T10108 professorship offered by Aalto University. Q. Qiu, P. Yao and J. Yuan acknowledge the financial support from the China Scholarship Council (Grant No. 201906150134, 202006120046 and 201906250030). Z.-Z. Pan acknowledges the financial support of the Academy of Finland (Grant No. 324414). The authors acknowledge the technical support of SEM from OtaNano Nanomicroscopy Center and computational resources from CSC-IT center for science, Finland. Publisher Copyright: © 2022 The Author(s) Peer reviewed

The demand for Lithium-ion batteries (LIB) is expected to increase exponentially due to the electrification of society. Thus, recycling LIBs will be essential to support this activity and ensure the availability of the limited raw material. End-of-life batteries entering the recycling process may still contain energy, representing a safety risk for processing. The energy can be drained in an electrochemical discharge before mechanical crushing, and it has been proposed that an aqueous NaCl solution would be suitable media. The field has lacked an accurate tool to evaluate the suitability of an electrolyte for LIB discharge. In this work, we intoduce two methods: external and internal electrochemical discharge. We also validate the methodology selection with ammonia-based electrolytes and provide a corrosion-free evaluation of the role of NaCl as an electrochemical discharge medium. The new methodology results confirmed that the batteries could be discharged to low voltage levels in NaCl electrolytes. Still, this electrolyte is highly corrosive, preventing the recovery of active materials in high purity. Thus, with the new methodology, finding alternative salt solutions that provide an efficient and non-corrosive discharge environment will be fast. Funding Information: The author would like to acknowledge the work of Aurelia Aminoff for conducting ammonia-based experiments with a potentiostat and Arpad Toldy for language editing. The work was funded by the Academy of Finland with two separated project: Hyper-sphere ( 341629 ) and Profiling funding 5 for Energy Storage ( 326346) . Publisher Copyright: © 2022 The Authors Peer reviewed

Structural health monitoring (SHM) systems provide opportunities to understand the structural behaviors remotely in real-time. However, anomalous measurement data are frequently collected from structures, which greatly affect the results of further analyses. Hence, detecting anomalous data is crucial for SHM systems. In this article, we present a simple yet efficient approach that incorporates complementary information obtained from multi-view local binary patterns (LBP) and random forests (RF) to distinguish data anomalies. Acceleration data are first converted into gray-scale image data. The LBP texture features are extracted in three different views from the converted images, which are further aggregated as the anomaly representation for the final RF prediction. Consequently, multiple types of data anomalies can be accurately identified. Extensive experiments validated on an acceleration dataset acquired on a long-span cable-stayed bridge highlight the advantages of the proposed method. State-of-the-art performances are achieved by the proposed method, demonstrating its effectiveness and generalization ability. Funding Information: The authors greatly appreciate the financial support from the Academy of Finland (Decision number: 339493). The authors also appreciate the kind support from Prof. Hui Li from Lab of Intelligent Civil Infrastructure (LiCi) for sharing the dataset and Prof. Yuequan Bao for the valuable comments. We also acknowledge the computational resources provided by the Aalto Science-IT project. Publisher Copyright: © 2022 The Author(s) Peer reviewed

Funding Information: This research has been partly funded by the Finnish Cultural Foundation, Fulbright Finland and the Intimacy in Data-Driven Culture (IDA) project, which was funded by the Strategic Research Council of the Academy of Finland (funding decision no. 327391). Härkönen worked in the IDA consortium as a senior researcher in 2021–2022 and Särmäkari since 2019. We are grateful to Dr Tuomas Mattila and Dr Mikko Antikainen for their valuable comments on the early draft of this article. We thank the audience of the European Policy for Intellectual Property (EPIP) 2022 conference for their feedback on this research. Peer reviewed

The effects of two deposit ageing mechanisms were identified by analysing superheater ash deposits from a kraft recovery boiler. Local differences in deposit morphology and chemical composition were identified under the electron microscope. Temperature-gradient-induced diffusion of alkali chloride vapours toward the steel was evident. Two deposit types were identified, based on local chemical compositions: “Type 1” deposits had an innermost porous layer of fine, sintered fume particles enriched in K and Cl, that deposited after homogeneous condensation in the gas phase. “Type 2” deposits formed via sulfation of initially deposited fume particles rich in K and Cl. Thus the innermost layer was enriched in K and S, while concurrently depleted in Cl. Differences in the local first melting temperature (T0) within the innermost regions of the two deposit types were identified. T0 reached a minimum within the innermost region of Type 1 deposits, implying an increased risk for melt formation and corrosion. Whereas for Type 2 deposits, T0 was increased closest to the steel, reducing the risk for melt formation and superheater corrosion. The presented results provide a better understanding of intra-depositional changes taking place after initial deposition, helping assess risks of deposit-related operational problems in the boiler. Funding Information: The financing through a research grant awarded by the Fortum Foundation [Application number 20190123] is highly acknowledged. This work has been partly carried out within the Åbo Akademi CLUE2 Research Consortium (2017–2022). Support from ANDRITZ Oy, Valmet Technologies Oy, UPM-Kymmene Oyj, Metsä Fibre Oy, and International Paper Inc. is gratefully acknowledged. Additional support from the Academy of Finland projects “Understanding the dynamics of intradeposit chemistry and morphology for control of corrosion in high temperature processes“ [Decision number 310266] and “New insights on the effects of temperature gradients on high temperature corrosion” [Decision number 338322] is highly appreciated. We want to thank Linus Silvander for carrying out SEM/EDX analyses. Publisher Copyright: © 2023 The Authors Peer reviewed