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A Formal Description of an Algorithm Suitable for Parsing the Language of Mathematics
No full textKofler’s DynGenPar (DGP) generalized dynamic parsing algorithm [6, 7] is aimed at parsing the language of mathematics. Notably, DGP uses a notion of initial graph instead of parsing tables in the style of GLR and LR parsers. We distinguish the two previously existing definitions of DGP: (1) The high-level “Abstract DGP” (ADGP) is a non-deterministic algorithm which reaches any particular parse tree via a sequence of non-deterministic choices. It is not obvious just from reading ADGP how to implement it well. (2) Kofler’s C++ implementation (KDGP) implements its own concurrency engine for finding all possible parse trees simultaneously while synchronizing on each input token. It is challenging to comprehend how ADGP corresponds to KDGP, and it would be hard to formally prove properties of either ADGP or KDGP. We present a new mathematical definition of Core DGP (CDGP), the context-free grammar (CFG) core of DGP, that is both declarative and deterministic. We formalize the concurrency with a notion of continuation, and define a way to match continuations to parse trees in proving that our algorithm is sound and complete, i.e., it terminates and returns all valid parse trees excluding trees with superfluous recursion. We also make available a Python implementation which corresponds quite directly to the mathematical definition of CDGP.</p
A qualitative study of the impact of the COVID-19 pandemic on equality, diversity and inclusion in the UK’s research and innovation ecosystem:Structural inequality, lived experience and recommendations for change
No full textQuantum information processing with spatially structured light
No full textQudits have proven to be a powerful resource for quantum information processing, offering enhanced channel capacities, improved robustness to noise, and highly efficient implementations of quantum algorithms. The encoding of photonic qudits in transverse-spatial degrees of freedom has emerged as a versatile tool for quantum information processing, allowing access to a vast information capacity within a single photon. We examine recent advances in quantum optical circuits with spatially structured light, focusing particularly on top-down approaches that employ complex mode-mixing transformations in free space and fibers. We highlight circuits based on platforms such as multi-plane light conversion, complex scattering media, multi-mode, and multi-core fibers. We discuss their applications for the manipulation and measurement of multi-dimensional and multi-mode quantum states. Furthermore, we discuss how these circuits have been employed to perform multi-party operations and multi-outcome measurements, thereby opening new avenues for scalable photonic quantum information processing
Reviews and syntheses:Carbon vs. cation based MRV of Enhanced Rock Weathering and the issue of soil organic carbon
No full textWe discuss the “monitoring, reporting and verification” (MRV) strategy of Enhanced Weathering (EW) based on carbon accounting and argue that in open systems such as arable land, this approach is ill-suited to close the balance of all carbon fluxes. We argue for total alkalinity (TA) as the central parameter for the carbon based MRV of EW. However, we also stress that tracking alkalinity fluxes using a systems-level approach is best done by focusing on charge balance maintenance through time. We start by explaining the concept and history of alkalinity conceptualization for the oceans. The same analytical method first proposed for the oceans-titration with a strong acid-is now commonly used for porewaters in agricultural soils. We explain why this is an accurate analysis for ocean water and why it is unsuitable to record TA for porewaters in agricultural soils. We then introduce an alternative MRV based on cation accounting and finally discuss the fate of cations released from the weathering of basalt, soil cation dynamics and close by suggesting open research questions.</p
Social media influencer marketing: the role of influencer type, brand popularity, and consumers’ need for uniqueness
No full textThe present study investigates how the type of social media influencer based on follower count (i.e. macro or micro-influencer) and the popularity of a brand that the influencer endorses affect consumers’ purchase intentions for the endorsed brand. Results of four experimental studies demonstrate that consumers are more likely to purchase a more (less) popular brand when it is endorsed by a macro(micro)-influencer, because a macro(micro)-influencer is perceived as more congruent with the endorsement of a more (less) popular brand. Results further show that the higher effectiveness of a macro(micro)-influencer for a more (less) popular brand endorsement only holds for consumers who have a low need for uniqueness. Theoretical contributions and managerial relevance of the results are discussed
Role of artificial intelligence in data-centric additive manufacturing processes for biomedical applications
No full textThe role of additive manufacturing (AM) for healthcare applications is growing, particularly in the aspiration to meet subject-specific requirements. This article reviews the application of artificial intelligence (AI) to enhance pre-, during-, and post-AM processes to meet a wider range of subject-specific requirements of healthcare interventions. This article introduces common AM processes and AI tools, such as supervised learning, unsupervised learning, deep learning, and reinforcement learning. The role of AI in pre-processing is described in the core dimensions like structural design and image reconstruction, material design and formulations, and processing parameters. The role of AI in a printing process is described based on hardware specifications, printing configurations, and core operational parameters such as temperature. Likewise, the post-processing describes the role of AI for surface finishing, dimensional accuracy, curing processes, and a relationship between AM processes and bioactivity. The later sections provide detailed scientometric studies, thematic evaluation of the subject topic, and also reflect on AI ethics in AM for biomedical applications. This review article perceives AI as a robust and powerful tool for AM of biomedical products. From tissue engineering (TE) to prosthesis, lab-on-chip to organs-on-a-chip, and additive biofabrication for range of products; AI holds a high potential to screen desired process-property-performance relationships for resource-efficient pre- to post-AM cycle to develop high-quality healthcare products with enhanced subject-specific compliance specification
Atmospheric carbon dioxide removal using layers of lime
No full textMetal oxides such as lime (CaO and Ca(OH)2) or magnesium oxide (MgO) react spontaneously with CO2 in the air, under ambient conditions, to form stable carbonate minerals. They are therefore, being used as reactive materials to remove carbon dioxide from the atmosphere to help prevent climate change. In these technologies ‘thin’ layers of calcium or magnesium oxides/hydroxides are spread over an area of land or inside tiered structures to contact the material with CO2 in the air. The proposed thickness of these layers varies by orders of magnitude between theoretical studies, from 3 to 100 mm, however, there is no published data describing the rates of carbonation as a function of layer thickness for lime. This study monitored the carbonation reaction of 2.5, 5, 10, 25 and 50 mm layers of CaO and Ca(OH)2 in ambient temperatures and concentrations of CO2. The results show that repeated spreading of thin layers (<10 mm every 5–10 days) resulted in the largest removal rate per spatial area (>2 t CO2 ha−1 day−1). However, given that the production costs of zero carbon lime may be substantially greater than the cost of land, it may be more economical to maximise conversion through extended periods between applications
A Novel Spatio-Temporal Rate-Splitting-based Power Allocation Optimization Strategy for RIS-assisted 6G MU-MISO Communication Systems
No full textReconfigurable intelligent surfaces (RISs) can dynamically adjust phase shifts to achieve scalability in networks, while rate-splitting multiple access (RSMA) can dynamically allocate spectrum and power resources according to the communication needs of IoT devices and reduce the energy consumption of the system. Therefore, the integration of RIS and RSMA can not only enhance the performance of IoT communication systems, but also reduces wastage of limited resources. This paper proposes a novel spatio-temporal rate-splitting-based power allocation optimization strategy for RIS-assisted multi-user (MU) systems to maximize channel capacity and energy efficiency gains. Leveraging the proposed spatio-temporal minimum mean squared error (STMMSE) principle and the rate splitting-based optimal power consumption (RS-OPC) method, the approach considers the Cramér-Rao bound for channel errors and derives expressions for maximizing channel capacity and obtaining the optimal solution. The proposed method selectively adjusts power values for different users and transmission types of symbols to achieve optimal power allocation objectives, thereby ensuring communication quality while optimizing channel capacity. This offers communication systems a higher configurability and resource optimization. Extensive simulation results including channel capacity, energy efficiency (EE) and spectral efficiency (SE) validate the effectiveness of the proposed method
Shining a Light on Benzo[c][1,2,5]thiadiazole Photocatalysts
No full textThe benzo[c][1,2,5]thiadiazole (BTZ) group is a strongly electron accepting unit that has primarily been investigated for application in photovoltaic systems or as fluorescent bioimaging agents or sensors. The strongly electron accepting nature of the BTZ group, in combination with its excellent photostability and options for chemical derivatisation, has kindled interest within the photochemistry community with regards to using this unit as a prospective building block in π-conjugated electron donor-acceptor photocatalysts. The aim of this review is to highlight the research surrounding the development of photocatalytic systems based on the BTZ group. This will include discussing chemical reactions that can be used to synthesise or derivatise the BTZ motif, as well as highlighting methods that have been used to alter the structural, photophysical or optoelectronic properties of electron donor-BTZ electron acceptor systems. Subsequent discussion of the photocatalytic applications will span both homogeneous photocatalysts (molecules, molecular cages and linear polymers) and heterogeneous materials (such as crosslinked organic polymers, covalent organic frameworks, and metal-organic frameworks) containing the BTZ group and structurally related groups
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