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Blended cements, where Portland cement clinker is partially replaced by supplementary cementitious materials (SCMs), provide the most feasible route for reducing carbon dioxide emissions associated with concrete production. However, lowering the clinker content can lead to an increasing risk of neutralisation of the concrete pore solution and potential reinforcement corrosion due to carbonation. carbonation of concrete with SCMs differs from carbonation of concrete solely based on Portland cement (PC). This is a consequence of the differences in the hydrate phase assemblage and pore solution chemistry, as well as the pore structure and transport properties, when varying the binder composition, age and curing conditions of the concretes. The carbonation mechanism and kinetics also depend on the saturation degree of the concrete and CO2 partial pressure which in turn depends on exposure conditions (e.g. relative humidity, volume, and duration of water in contact with the concrete surface and temperature conditions). This in turn influence the microstructural changes identified upon carbonation. This literature review, prepared by members of RILEM technical committee 281-CCC carbonation of concrete with supplementary cementitious materials, working groups 1 and 2, elucidates the effect of numerous SCM characteristics, exposure environments and curing conditions on the carbonation mechanism, kinetics and structural alterations in cementitious systems containing SCMs.
Algorithm selection (AS) tasks are dedicated to find the optimal algorithm for an unseen problem instance. With the knowledge of problem instances’ meta-features and algorithms’ landmark performances, Machine Learning (ML) approaches are applied to solve AS problems. However, the standard training process of benchmark ML approaches in AS either needs to train the models specifically for every algorithm or relies on the sparse one-hot encoding as the algorithms’ representation. To escape these intermediate steps and form the mapping function directly, we borrow the learning to rank framework from Recommender System (RS) and embed the bi-linear factorization to model the algorithms’ performances in AS. This Bi-linear Learning to Rank (BLR) has proven to work with competence in some AS scenarios and thus is also proposed as a benchmark approach. Thinking from the evaluation perspective in the modern AS challenges, precisely predicting the performance is usually the measuring goal. Though approaches’ inference time also needs to be counted for the running time cost calculation, it’s always overlooked in the evaluation process. The multi-objective evaluation metric Adjusted Ratio of Root Ratios (A3R) is therefore advocated in this paper to balance the trade-off between the accuracy and inference time in AS. Concerning A3R, BLR outperforms other benchmarks when expanding the candidates range to TOP3. The better effect of this candidates expansion results from the cumulative optimum performance during the AS process. We take the further step in the experimentation to represent the advantage of such TOPK expansion, and illustrate that such expansion can be considered as the supplement for the convention of TOP1 selection during the evaluation process.
Within many real-world networks, the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal graphs requires a proximity measure to compare different temporal graphs. To this end, we propose to study dynamic time warping on temporal graphs. We define the dynamic tem- poral graph warping (dtgw) distance to determine the dissimilarity of two temporal graphs. Our novel measure is flexible and can be applied in various application domains. We show that computing the dtgw-distance is a challenging (in general) NP-hard optimization problem and identify some polynomial-time solvable special cases. Moreover, we develop a quadratic programming formulation and an efficient heuristic. In experiments on real-world data, we show that the heuristic performs very well and that our dtgw-distance performs favorably in de-anonymizing networks compared to other approaches.
The world’s population is aging at an unprecedented pace. Aging society is not only a severe crisis in the developed world, but also a rigorous challenge in emerging economies. Many age-related diseases are fostered by the lack of physical, cognitive, and social activities. Increasing the activity level has many benefits for the elderly and can improve their independence. Based on the analysis of the state-of-the-art and shortcomings of the current smart home solutions, the EU-funded research project REACH aims to develop a service system that will turn clinical and care environments into personalized modular sensing, prevention, and intervention systems that encourage the elderly to become healthy through various activities. To achieve that goal, the research team developed a series of smart furniture (PI2Us) that materialize the research concepts and functionality seamlessly into the various environments. Specifically, the development process and the functionality testing results of the PI2Us are reported in detail. In addition, a simulated smart home solution concept (TRACK) integrating key assistive technologies developed is proposed to create a comprehensive interior living and care environment for elderly users. Due to its modularity and flexibility, the partial or entire solution can be easily adapted and rapidly deployed in different use case settings in Europe, which allows the project consortium to execute different testing activities. In the next phase, the research team will focus on enhancing the usability and performance of the prototypes in order to eventually push them to the market. In conclusion, this research provides an innovative smart home solution for the industry to mitigate the impact of aging society.
REACH stands for “Responsive Engagement of the Elderly Promoting Activity and Customized Healthcare”. Sustained physical activity matters greatly to the health and well-being of older people and significantly improves their chance of maintaining independent living. It can make a difference across the whole care continuum as well as in almost every setting. Therefore, REACH solutions focus on the systematic, target-oriented increase of physical activity of older people, and tackle the whole prevention spectrum (primary, secondary, and tertiary). It seeks to empower older people and their formal and informal caregivers, and works towards viable solutions for both the formal and in-formal care sector. Technology-based personalization of prevention, activation, and care services provided in various living and care settings is at the center of the developed solutions. Ideally toolkit approach would allow for the tailoring of solutions that create value for end-users, care providers and health care payers alike through the combination, integration and adaptation/re-design elements towards the different contexts of different countries, different payment and reimbursement structures. This Special Issue sheds light on such solutions, their conception, their development, and their testing.
Shotcrete is a material frequently used in underground constructions such as tunnels, where Ca leaching and sulfate attack are important durability issues. In this study, two test methods were employed to investigate the sulfate resistance and leaching behaviour of dry- and wet-mix shotcretes in sulfate solutions on a time-resolved basis. Tests on powdered samples showed the dissolution of AFm, portlandite and C-A-S-H, subsequently followed by the precipitation of calcite and ettringite. The extent of sulfate expansion of drill cores corresponded to the chemical response of the powder materials, particularly on the reactivity of Ca- and Al-containing hydrated cement phases. The use of high-purity metakaolin (7-10 wt%) in the shotcrete binder significantly decreased the sulfate durability, while high amounts of other SCMs such as blast-furnace slag and silica fume (> 20 wt%) had a positive effect on the durability of shotcrete.
Resting motor threshold and magnetic field output of the figure-of-8 and the double-cone coil
(2020)
The use of the double-cone (DC) coil in transcranial magnetic stimulation (TMS) is promoted with the notion that the DC coil enables stimulation of deeper brain areas in contrast to conventional figure-of-8 (Fo8) coils. However, systematic comparisons of these two coil types with respect to the spatial distribution of the magnetic field output and also to the induced activity in superficial and deeper brain areas are limited. Resting motor thresholds of the left and right first dorsal interosseous (FDI) and tibialis anterior (TA) were determined with the DC and the Fo8 coil in 17 healthy subjects. Coils were orientated over the corresponding motor area in an angle of 45 degrees for the hand area with the handle pointing in posterior direction and in medio-lateral direction for the leg area. Physical measurements were done with an automatic gantry table using a Gaussmeter. Resting motor threshold was higher for the leg area in contrast to the hand area and for the Fo8 in contrast to the DC coil. Muscle by coil interaction was also significant providing higher differences between leg and hand area for the Fo8 (about 27%) in contrast to the DC coil (about 15%). Magnetic field strength was higher for the DC coil in contrast to the Fo8 coil. The DC coil produces a higher magnetic field with higher depth of penetration than the figure of eight coil.
This work concerns an area of magnetoactive polymer (MAP) research seldom considered. Traditionally only MAP with high concentrations of magnetic filler (typically between 10 and 90 wt%) have been investigated. This article deals with a hitherto neglected aspect of research, namely MAP containing lower magnetic filler concentrations (1 to 3 wt%). This article utilizes a range of spectroscopic analysis methods (Raman and FTIR) and their applicability to MAP characterization at wavelengths ranging from 2.5 to 25 mu m. Particular attention is paid to low carbonyl iron particle (CIP) concentrations in MAP for which the emergence of capillary doublets at a critical 2 wt% concentration is revealed. This results in measurable magnetic field-dependent changes in IR absorption at a wavelength of 4.255 mu m together with a detectable CO2 susceptibility. (c) 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 48366.
The electrical properties of rheopectic magnetoactive composites comprising boron-organo-silicon oxide dielectric matrices containing carbonyl iron microparticles are presented for the first time. The increase in interfacial magnetocapacitance is seen to greatly exceed that experienced when using conventional elastomeric matrices such as polydimethylsiloxane. In addition to the increase in capacitance, a simultaneous and sharp decrease in the parallel electrical resistance over several orders of magnitude is also observed. The effects are time dependent but repeatable. Potential applications include magnetically controlled frequency dependent devices, magnetic sensor systems, weighting elements for neural networks, etc.