Recent publications
Dynamic sparsity is intrinsic to biological computing and is key to its extreme power efficiency. Edge computing systems can improve their energy efficiency and reduce response latency by exploiting this neuromorphic principle. The neuromorphic approach for the extraction of acoustic features replaces conventional ADC and DSP with biological cochlea-inspired filters and event generators implemented in mixed-signal circuits. The resulting sparse feature events drive inference in dynamic-sparsity-aware neural network accelerators to reduce computational load and memory access. The demonstration of edge keyword spotting shows the dynamic savings in power. Exploiting dynamic sparsity at all levels will be the next step toward the design of intelligent devices for the edge.
Wood-based construction (WBC) has gained prominence as a sustainable alternative to traditional construction, offering significant environmental benefits such as carbon storage and reduced greenhouse gas emissions. Its importance lies in its potential to contribute to climate change mitigation while supporting economic growth and innovation in the construction industry. Therefore, understanding the drivers and challenges of WBC is essential for its future development. This study, at the first stage, conducted a literature review to identify the key drivers and challenges associated with WBC, categorizing them into environmental, technical, economic, and perception and policy aspects. Then, based on these findings, we conducted 20 semi-structured interviews with WBC experts from Finland in the construction industry, public administration and academia to compare theoretical perspectives with practical insights. Results revealed that literature often focuses on matters such as life-cycle assessments, policy development, and renewable resource management. On the other hand, interviewees emphasize practical concerns like technical feasibility, economic viability, and client perceptions. Climate considerations are acknowledged by interview participants as important but are often viewed as external expectations rather than core business drivers. This study highlights the gap between academic research and industry practice.
The yeast prion protein Sup35 is aggregation-prone at high concentrations. De novo Sup35 prion formation occurs at a significantly increased rate after transient overexpression of Sup35 in the presence of another prion, [ PIN ⁺ ], but it is still a rare event. Recent studies uncovered an additional and seemingly more prevalent role of Sup35: at its physiological level, it undergoes phase separation to form reversible condensates in response to transient stress. Stress-induced reversible Sup35 condensation in the [ psi ⁻ ] strain enhances cellular fitness after stress ceases, whereas irreversible Sup35 aggregates in the [ PSI ⁺ ] strain do not confer this advantage. However, how Sup35 overexpression, which could potentially lead to irreversible aggregation, affects its condensation under stress conditions remains unclear. In this study, we used a combinatorial method to examine how different levels of Sup35 overproduction and cellular conditions affect the nature, formation, and physical properties of Sup35 assemblies in yeast cells, as well as their impacts on cellular growth. We observed notable morphological distinctions between irreversible Sup35 aggregates and reversible Sup35 condensates, possibly indicating different formation mechanisms. In addition, Sup35 aggregation caused by a very high overexpression level can strongly inhibit cell growth, diminish the formation of stress-induced condensates when Sup35 is completely aggregated, and impair cellular recovery from stress. Together, this study advances our fundamental understanding of the physical properties and formation mechanism of different Sup35 assemblies and their impacts on cellular growth. We conclude that in vivo studies are sensitive to overexpression and can lead to assembly routes that strongly affect functions.
IMPORTANCE
The role of condensates in living cells is often studied by overexpression. For understanding their physiological role, this can be problematic. Overexpression can shift cellular functions, thereby changing the system under study, and overexpression can also affect the phase behavior of condensates by shifting the position of the system in the underlying phase diagram. Our detailed study of overexpression of Sup35 in S. cerevisiae shows the interplay between these factors and highlights basic features of intracellular condensation such as the balance between condensation and aggregation as well as how cellular localization and responsiveness depend on protein levels. We also apply super-resolution microscopy to highlight details within the cells.
Configurational research has great promise in entrepreneurship. There are few universal laws or relationships that hold under all circumstances. More often, optimal entrepreneurial outcomes are contingent on many factors. Consequently, configurational analysis using qualitative comparative analysis (QCA) has become increasingly popular. However, methodological research in sociology and political science has raised concerns about possible false positive findings produced by this method. In this editorial, we explore the potential and the common pitfalls of QCA in entrepreneurship research, as well as guidelines for its use.
Understanding the role of major components of electric waste during smelting of these materials to recover valuable trace metals is poorly constrained by experimental data. In this study, phase equilibria and trace element deportments were studied at 1473 K (1200°C) in conditions of combined sulfide concentrate and electric and electronic equipment waste processing in batchwise submerged lance smelting. In this system, liquid slag domain is limited by silica and magnetite saturation boundaries or primary phase fields at all alumina concentrations from alumina-free slags to silica-spinel double saturation. The impact of alumina concentration in slag at fixed oxygen and sulfur dioxide partial pressures on the distributions of Ag, Cu, In, Pb, and Sn was studied. Elemental concentrations in slag, matte, and solid magnetite (a Fe-Al spinel solid solution) were measured using electron probe microanalysis and laser ablation-ICP-mass spectrometry techniques. The observed impact of alumina on the distribution coefficient of silver, copper, and indium favored the matte phase at silica and magnetite saturation but lead and tin behaved differently within different primary phase fields as a function of alumina concentration.
Decarbonizing the power mix will require investments in storage and flexibility options to replace the current carbon-intensive supply of reserves. This paper questions whether reserve-capacity markets can serve as a capacity mechanism for flexible technologies. A fundamental model of the day-ahead and reserve markets is used to investigate the evolution of reserve prices with large shares of renewable energy and storage. The model represents the current market design in Continental Europe with a centralized supply and platforms for the exchange of reserves. By becoming the main suppliers of reserve capacity, batteries have a noticeable impact on reserve prices. Their flexibility implies zero opportunity cost most of the time, meaning that the flexibility is not rewarded by the market. These results suggest that reserve-capacity markets cannot provide additional remuneration for flexible technologies and, thus, do not solve the missing-money problem in the context of the energy transition.
JEL Classification: Q41, Q47
Ultrafast fibre lasers, characterized by ultrashort pulse duration and broad spectral bandwidth, have drawn significant attention due to their vast potential across a wide range of applications, from fundamental scientific to industrial processing and beyond. As dissipative nonlinear systems, ultrafast fibre lasers not only generate single solitons, but also exhibit various forms of spatiotemporal soliton bunching. Analogous to molecules composed of multiple atoms in chemistry, soliton molecules (SMs) – alias bound states – in ultrafast fibre lasers are a key concept for gaining a deeper understanding of nonlinear interaction and hold a promise for advancing high-capacity fibre-optic communications. SMs are particularly notable for their high degree of controllability, including their internal temporal separation, and relative phase differences, thereby suggesting new possibilities for manipulating multi-pulse systems. In this review, we provide a comprehensive overview of recent advancements in the studies of SMs with the multidimensional parameter space in ultrafast fibre lasers. Owing to the flexibility afforded by mode-locking techniques and dispersion management, various types of SMs – with diverse values of the soliton number, relative phase, pulse separation, carrier frequencies, and even modal dispersion – have been experimentally demonstrated. We also discuss other basic nonlinear optical phenomena observed in fibre lasers, including the formation, spatiotemporal pulsations, and interaction dynamics of SMs. Furthermore, we explore the multidimensional control of SMs through approaches such as gain modulation, polarization control, dispersion management, and photomechanical effects, along with their applications to optical data encoding. Finally, we discuss challenges and future development of multidimensional technologies for the manipulation of SMs.
Spatially separated palladium nanocubes (Pd NCs) terminated by {100} facets are synthesized using direct micelles approach. The stepwise seed‐mediated growth of Pd NCs is applied for the first time. The resulting Pd NCs are thoroughly characterized by HR‐TEM, XPS, Raman, ATR‐FTIR, TGA, and STEM‐EDX spectroscopies. Some traces of residual stabilizer (polyvinylpyrrolidone, PVP) attached to the vertices of Pd NCs are identified after the necessary separation‐washing procedure, however, it is vital to avoid aggregation of the NCs. Pd NCs are subsequently and uniformly loaded on Vulcan carbon (≈20 wt.%) for the electrochemical hydrogen cycling. By post‐mortem characterizations, it is revealed that their shape and size remained very stable after all electrochemical experiments. However, a strong effect of the NCs size on their hydrogen interaction is revealed. Hydrogen absorption capacity, measured as the H:Pd ratio, ranges from 0.28 to 0.48, while hydrogen evolution and oxidation reactions (HER and HOR) kinetics decrease from 15.5 to 4.6 mA.mg Pd⁻¹ between ≈15 and 34 nm of Pd NCs, respectively. Theoretical calculations further reveal that adsorption of H atoms and their penetration into the Pd lattice tailors the NCs electronic structure, which in turn controls the kinetics of HER, experimentally observed by the electrochemical tests. This work may pave the way to the design of highly active electrocatalysts for efficient HER stable for a long reactive time. In particular, obtained results might be transferred to active Pd‐alloy‐based NCs terminated by {100} facets.
Structural head MRIs are a crucial ingredient in MEG/EEG source imaging; they are used to define a realistically shaped volume conductor model, constrain the source space, and visualize the source estimates. However, individual MRIs are not always available, or they may be of insufficient quality for segmentation, leading to the use of a generic template MRI, matched MRI, or the application of a spherical conductor model. Such approaches deviate the model geometry from the true head structure and limit the accuracy of the forward solution. Here, we implemented an easy‐to‐use tool, pseudo‐MRI engine, which utilizes the head‐shape digitization acquired during a MEG/EEG measurement for warping an MRI template to fit the subject's head. To this end, the algorithm first removes outlier digitization points, densifies the point cloud by interpolation if needed, and finally warps the template MRI and its segmented surfaces to the individual head shape using the thin‐plate‐spline method. To validate the approach, we compared the geometry of segmented head surfaces, cortical surfaces, and canonical brain regions in the real and pseudo‐MRIs of 25 subjects. We also tested the MEG source reconstruction accuracy with pseudo‐MRIs against that obtained with the real MRIs from individual subjects with simulated and real MEG data. We found that the pseudo‐MRI enables comparable source localization accuracy to the one obtained with the subject's real MRI. The study indicates that pseudo‐MRI can replace the need for individual MRI scans in MEG/EEG source imaging for applications that do not require subcentimeter spatial accuracy.
We introduce a collective experimentation problem where a continuum of agents choose the timing of irreversible actions under uncertainty and where public feedback from the actions arrives gradually over time. The leading application is the adoption of new technologies. The socially optimal expansion path entails an informational trade‐off where acting today speeds up learning but postponing capitalizes on the option value of waiting. We contrast the social optimum to the decentralized equilibrium where agents ignore the social value of information they generate. We show that the equilibrium can be obtained by assuming that agents ignore the future actions of other agents, which lets us recast the complicated two‐dimensional problem as a series of one‐dimensional problems.
The emergence of multi‐agent systems and significant integration of distributed energy sources (DESs) are transforming distribution networks. This necessitates a decentralized management strategy for unbalanced operation in multi‐agent distribution systems (MADSs) due to the autonomous nature and potential for unbalanced injection of single‐phase DESs. Accordingly, this paper proposes a novel approach for decentralized management of unbalanced operation in MADSs. The approach leverages a customized alternating direction method of multipliers to facilitate decentralized decision‐making, while incorporating transactive energy signals aligned with the alternating direction method of multiplier framework to enable independent agent operation. In this scheme, independent agents would optimize their operating costs considering the announced transactive signals, which model the power prices and power loss in the grid. The decentralized structure enables agents to apply stochastic and condition value at risk methods to address the uncertainty and associated risk in scheduling resources. Furthermore, without violating the privacy concerns of agents, the developed transactive‐based scheme facilitates minimizing the asymmetrical condition, caused by the unbalanced integration of DESs, in the power request at the connection point of MADSs and transmission networks. Finally, the proposed methodology is simulated on 37‐bus and 123‐bus test‐systems to study its effectiveness in managing the MADSs with unbalanced integration of DESs.
The electronics industry is expected to adopt more sustainable and circular product concepts and operations. Since the electronics value chains are complex, digital product passports (DPPs) that provide value chain transparency and traceability can be seen as one key enabler for shifting towards circular economy. Data carriers that are physical identifiers attached to products provide access to product data stored in the cloud and databases. Smart tags that combine item-level identification with condition monitoring are proposed to enable access also to dynamic lifecycle data of products to improve decision-making at end-of-life based on conditions that the product has been exposed to during its lifecycle. This dynamic information could be effectively used together with product data to decide on which circular economy strategy to adopt: reuse, remanufacture, repair, recycle etc. This paper analyses the data requirements of electronics value chain for DPPs, specifically focusing on which conditions to monitor with the help of smart tags. The data for this analysis was collected from ten developmental value chains aiming for sustainability and circularity with a questionnaire related to data needs, data access, data gaps, and data availability. The responses highlighted the need for data exchange and tools to monitor performance of components during storage and use. A printed visual humidity sensor is developed and analyzed as an experimental case study to help the value chains to dynamically monitor lifecycle conditions of products. This smart tag principal was functional with a visible colour change over time at different humidities between 33–72%RH, while not reacting at 0%RH. The relevance of different smart tag concepts is discussed and other important aspects, such as sustainability and durability of the smart tags, are included in the discussion.
During the past decades, experiments with scale models have been widely conducted to study the flooding process and motions of damaged ships, both in calm water and in waves. Survivability tests in irregular beam seas have been well-established and widely used, also commercially, to verify the compliance with the so-called Stockholm Agreement regulatory requirements. However, model tests for both transient and progressive flooding modes have mainly targeted at obtaining experimental data for validation of numerical simulation methods. This is becoming more important as increased computing capacity has enabled practical use of first principle tools for assessing damages stability. In this review, the different model test types and typical experimental setups are analyzed. In addition, the applied scales factors are studied and some research gaps are pointed out. Despite notable achievements in the past, further model tests are still considered essential for obtaining reliable experimental data on certain flooding mechanisms. Consequently, some recommendations for future experiments are also given.
Solid‐state photosynthetic cell factories (SSPCFs) are a new production concept that leverages the innate photosynthetic abilities of microbes to drive the production of valuable chemicals. It addresses practical challenges such as high energy and water demand and improper light distribution associated with suspension‐based culturing; however, these systems often face significant challenges related to mass transfer. The approach focuses on overcoming these limitations by carefully engineering the microstructure of the immobilization matrix through freeze‐induced assembly of nanochitin building blocks. The use of nanochitins with optimized size distribution enabled the formation of macropores with lamellar spatial organization, which significantly improves light transmittance and distribution, crucial for maximizing the efficiency of photosynthetic reactions. The biomimetic crosslinking strategy, leveraging specific interactions between polyphosphate anions and primary amine groups featured on chitin fibers, produced mechanically robust and wet‐resilient cryogels that maintained their functionality under operational conditions. Various model biotransformation reactions leading to value‐added chemicals are performed in chitin‐based matrix. It demonstrates superior or comparable performance to existing state‐of‐the‐art matrices and suspension‐based systems. The findings suggest that chitin‐based cryogel approach holds significant promise for advancing the development of solid‐state photosynthetic cell factories, offering a scalable solution to improve the efficiency and productivity of light‐driven biotransformation.
Promising intrinsic electronic properties, such as narrow bandgap and high charge carrier mobilities, make germanium (Ge) a good replacement for silicon in optoelectronic applications (e.g., photodetectors). However, successful fabrication of efficient Ge devices requires minimization of both reflectance and surface recombination losses. This work begins with an observation that metal‐assisted chemical etching (MACE) of Ge surfaces, used for optics improvement, reduces surface recombination without application of any intentional passivation. We proceed with investigation of the effect of MACE solution components and their mixtures on Ge surface passivation. The results demonstrate that HF:H 2 O 2 aqueous solution leads to efficient and stable passivation. The film formed in this solution secures surface recombination velocity ( S eff ) of 14 cm s ⁻¹ . Morphological and chemical characterization of the structure reveals porous germanium (PGe) layer with some GeO x included. Finally, we propose several hypotheses on a mechanism behind this passivation, among which are the presence of GeO 2 at the film‐bulk Ge interface and appearance of a potential barrier due to the heterojunction formation. The presented Ge passivation with PGe layer provides a simple and cost‐efficient alternative to existing state‐of‐the‐art passivation schemes.
Functionalized particles ranging from nanoscale to microscale and their assemblies have facilitated a wide variety of sensing concepts, from molecular‐scale chemical and biological detection to large‐scale engineering defect testing. Related to macroscopic object shape sensing, visual recognition is generally the most versatile approach whenever possible. However, under certain conditions where visual perception is hindered, for example, dark space or underwater, electrosensing can serve as an alternative sensation manner. Inspired by this concept, the sensing of rudimentary object shapes using electrically conductive, soft ferromagnetic Ni particles is demonstrated, herein denoted as colloidal magnetoelectric shape recognition. By confining the target and sensory particles between two planar electrodes and using a magnetic field to drive the particles toward object edges, changes in electrical conductivity are monitored. Machine learning is then used to resolve the exact object shapes with high fidelity. This study introduces a colloidal magnetoelectric shape recognition strategy for short‐range shape sensing, with potential applications suggested for the fields such as soft robotics, drug delivery, and biomedical diagnostics.
Cubic silicon-carbide crystals (3C-SiC), known for their high thermal conductivity and in-plane stress, hold significant promise for the development of high-quality (Q) mechanical oscillators. We reveal degeneracy-breaking phenomena in 3C-phase crystalline silicon-carbide membrane and present high-Q mechanical modes in pairs or clusters. The 3C-SiC material demonstrates excellent microwave compatibility with superconducting circuits. Thus, we can establish a coherent electromechanical interface, enabling precise control over 21 high-Q mechanical modes from a single 3C-SiC square membrane. Benefiting from extremely high mechanical frequency stability, this interface enables tunable light slowing with group delays extending up to an impressive duration of an hour. Coherent energy transfer between distinct mechanical modes are also presented. In this work, the studied 3C-SiC membrane crystal with their significant properties of multiple acoustic modes and high-quality factors, provide unique opportunities for the encoding, storage, and transmission of quantum information via bosonic phonon channels.
Methanosarcinales are versatile methanogens, capable of regulating most types of methanogenic pathways. Despite the versatile metabolic flexibility of Methanosarcinales, no member of this order has been shown to use formate for methanogenesis. In the present study, we identified a cytosolic formate dehydrogenase (FdhAB) present in several Methanosarcinales, likely acquired by independent horizontal gene transfers after an early evolutionary loss, encouraging re‐evaluation of our understanding of formate utilization in Methanosarcinales. To explore whether formate‐dependent (methyl‐reducing or CO2‐reducing) methanogenesis can occur in Methanosarcinales, we engineered two different strains of Methanosarcina acetivorans by functionally expressing FdhAB from Methanosarcina barkeri in M. acetivorans. In the first strain, fdhAB was integrated into the N⁵‐methyl‐ tetrahydrosarcinapterin:coenzyme M methyltransferase (mtr) operon, making it capable of growing by reducing methanol with electrons from formate. In the second strain, fdhAB was integrated into the F420‐reducing hydrogenase (frh) operon, instead of the mtr operon, enabling its growth with formate as the only source of carbon and energy after adaptive laboratory evolution. In this strain, one CO2 is reduced to one methane with electrons from oxidizing four formate to four CO2, a metabolism reported only in methanogens without cytochromes. Although methanogens without cytochromes typically utilize flavin‐based electron bifurcation to generate the ferredoxins needed for CO2 activation, we hypothesize that, in our engineered strains, reduced ferredoxins are obtained via the Rhodobacter nitrogen fixation complex complex running in reverse. Our work demonstrates formate‐dependent methyl‐reducing and CO2‐reducing methanogenesis in M. acetivorans that is enabled by the flexible nature of the microbe working in tandem with the nurturing provided.
Ultrafast plasmonics represents a cutting‐edge frontier in light‐matter interactions, providing a unique platform to study electronic interactions and collective motions across femtosecond to picosecond timescales. In the infrared regime, where energy aligns with the rearrangements of low‐energy electrons, molecular vibrations, and thermal fluctuations, ultrafast plasmonics can be a powerful tool for revealing ultrafast electronic phase transitions, controlling molecular reactions, and driving subwavelength thermal processes. Here, the evolution of ultrafast infrared plasmonics, discussing the recent progress in their manipulation, detection, and applications is reviewed. The future opportunities, including their potential to probe electronic correlations, investigate intrinsic ultrafast plasmonic interactions, and enable advanced applications in quantum information are highlighted, which may be promoted by multi‐physical field integrated ultrafast techniques.
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