Miracle-dz/UniFAR-FTUs huggingface dataset:
The British Press

EVERY day some ten million copies of the nine London morning newspapers leave the presses, so that London f alone supplies one newspaper for every fourth man, woman and child in the country. The aggregate circulation of the three afternoon papers is about 1,750,000; but their coverage is pretty well confined to the actual metropolitan area. There are about a dozen provincial newspapers which are leaders in their respective fields; but when these have duly been taken into consideration, the fact remains that for our present purpose London is not only England, but to a very large extent Scotland and Wales as well. To say this is in no way to deprecate the high standard of journalism to be found in British provincial cities; it is merely to recognize the centralization of the interests of a comparatively small and densely populated country about an urban agglomeration which contains one-fourth of its entire population, and which is at the same time its political, social, intellectual, financial and industrial capital. The geography of the country serves further to confirm Lon don's supremacy. Three-fourths of England's population live within five hours' train journey from the metropolis. Eight hours takes one to Glasgow or Edinburgh. Even those newspapers which are printed only in London, therefore, can be laid on the breakfast tables of the greater part of England upon the morning of their publication; while those which print duplicate editions in Manchester or Glasgow can virtually blanket the British Isles. The assumption would be pardonable that such concentration would tend to confer upon the London press a position of unique authority. The equation, however, is not so simple as that. In the last resort the authority of any influence upon public opin ion must depend upon the factors by which the public has been conditioned to react to such influences. In Great Britain these factors are both complex and subtle, so that while the press is in no sense a subservient one, its power over the public mind is subject to modifications and limitations which do not directly correspond to anything in our journalistic experience. We in the United States have had newspapers ever since we became a nation ? indeed, for an even longer time. The freedom
Nested 1D-2D approach for urban surface flood modeling

Floods in urban areas as a consequence of sewer capacity exceedance receive increased attention because of trends in urbanization (increased population density and impermeability of the surface) and climate change. Despite the strong recent developments in numerical modeling of water systems, urban surface flood modeling is still a major challenge. Whereas very advanced and accurate flood modeling systems are in place and operation by many river authorities in support of flood management along rivers, this is not yet the case in urban water management. Reasons include the small scale of the urban inundation processes, the need to have very high resolution topographical information available, and the huge computational demands.
The Hellenic School of Ottawa and Cultural Maintenance: The Perceptions of the Administrators

In multicultural societies like Canada where cultural diversity always exist, ethnic groups strive to preserve their cultural heritage and not become assimilated by the mainstream culture. Today, ethnic groups such as the Hellenic Community of Ottawa seek innovative means to sustain cultural elements such as ethnic language, religious beliefs, and social, cultural and leisure pursuits. This phenomenological study presents the perspectives of recent administrators of the Hellenic School of Ottawa toward language and cultural maintenance. The results of this study indicate that the Hellenic School of Ottawa is vital and effective for maintaining the Hellenic culture and language beyond the 3 rd and 4 th generation, as it includes the instruction of Greek language and familiarization with Greek culture. The results also indicate that students of the language school: (1) Are provided with an opportunity to learn Greek which may not be received at home, (2) learn to appreciate their ethnic heritage through language oriented leisure activities, (3) make friendships with those of same ethnic cultural heritage, (4) learn to have a deeper appreciation of multiculturalism and its place in Canadian society, and (5) develop confidence to speak their ethnic language. This study also provides suggestions for the enhancement of the operation of the HSO, such as addition of more Greek-content leisure activities, organization of trips to Greece, and expansion of the instructional time.
Enhanced or hindered research benefits? A realist review of community engagement and participatory research practices for non-communicable disease prevention in low- and middle-income countries

Introduction Community engagement and participatory research are widely used and considered important for ethical health research and interventions. Based on calls to unpack their complexity and observed biases in their favour, we conducted a realist review with a focus on non-communicable disease prevention. The aim was to generate an understanding of how and why engagement or participatory practices enhance or hinder the benefits of non-communicable disease research and interventions in low- and middle-income countries. Methods We retroductively formulated theories based on existing literature and realist interviews. After initial searches, preliminary theories and a search strategy were developed. We searched three databases and screened records with a focus on theoretical and empirical relevance. Insights about contexts, strategies, mechanisms and outcomes were extracted and synthesised into six theories. Five realist interviews were conducted to complement literature-based theorising. The final synthesis included 17 quality-appraised articles describing 15 studies. Results We developed six theories explaining how community engagement or participatory research practices either enhance or hinder the benefits of non-communicable disease research or interventions. Benefit-enhancing mechanisms include community members’ agency being realised, a shared understanding of the benefits of health promotion, communities feeling empowered, and community members feeling solidarity and unity. Benefit-hindering mechanisms include community members’ agency remaining unrealised and participation being driven by financial motives or reputational expectations. Conclusion Our review challenges assumptions about community engagement and participatory research being solely beneficial in the context of non-communicable disease prevention in low- and middle-income countries. We present both helpful and harmful pathways through which health and research outcomes are affected. Our practical recommendations relate to maximising benefits and minimising harm by addressing institutional inflexibility and researcher capabilities, managing expectations on research, promoting solidarity in solving public health challenges and sharing decision-making power.
Isótopos estáveis (C, O, S) e geoquímica de rocha total de carbonatitos da Província Ígnea Alto Paranaíba - SE Brasil

The present work investigates the relationship between whole-rock geochemistry and stable isotope composition from carbonatites belonging to the Tapira, Araxa, Salitre, Serra Negra, Catalao I, and Catalao II alkaline-carbonatite complexes of the Alto Paranaiba Igneous Province (APIP), central Brazil and from the Jacupiranga Complex, of the Ponta Grossa Province, southeast Brazil. The APIP complexes are ultrapotassic, comprising bebedourites, phoscorites, nelsonites, and carbonatites, whereas Jacupiranga is a sodic complex composed of ijolite-series rocks, syenites, carbonatites, and alkaline gabbros. The geochemistry data allied to mineralogical constraints allowed us to classify the carbonatites into five groups, and to devise a chemical index (BaO/(BaO+SrO)) to gauge the magmatic evolution of the studied carbonatites.The APIP carbonatites evolve from apatite-rich calciocarbonatites toward Ba-, Sr-, and rare earth element (REE)-rich magnesiocarbonatites. This evolution is mostly driven by apatite, phlogopite, dolomite, and calcite fractionation and consequent enrichment in monazite, norsethite, and strontianite. Stable isotope data show a wide diversity of petrogenetic processes in play at the APIP, relatively to the Jacupiranga Complex, which is interpreted as a result of the shallower intrusion levels of the APIP complexes. Such shallower emplacement, at low lithostatic pressure, allowed for a complex interplay of fractional crystallization, liquid immiscibility, degassing, and interaction with hydrothermal and carbohydrothermal systems.
Evaluating ambient fine particulate matter source regions in the Ohio River Valley Region

Source types or source regions contributing to the concentration of atmospheric fine particles measured in the Ohio New River Valley were identified using cluster back trajectories chemical component analysis. Cluster analysis of backward air trajectories on fine particulate matter (FPM) with high and low concentrations was used to link factors to potential source regions. There is a high density of power plants along the Ohio River Valley. Some evidence suggests that secondary organic aerosol formation is an important contributor to high PM days for regional aerosols. Using analysis of chemical component, it is verified that sulfate is the dominant component in the Ohio River Valley Region. The chemical components included: Li, Na, NH4, K, Mg, Ca, F, Cl, NO3, PO4, SO4, Si, S, Cl, Ca, Ti, V, Mn, Fe, Cu, Zn. Approved: Kevin Crist Associate Professor of Health Sciences
Effect of a Zinc Phosphate Shell on the Uptake and Translocation of Foliarly Applied ZnO Nanoparticles in Pepper Plants (Capsicum annuum)

Here, isotopically labeled 68ZnO NPs (ZnO NPs) and 68ZnO NPs with a thin 68Zn3(PO4)2 shell (ZnO_Ph NPs) were foliarly applied (40 μg Zn) to pepper plants (Capsicum annuum) to determine the effect of surface chemistry of ZnO NPs on the Zn uptake and systemic translocation to plant organs over 6 weeks. Despite similar dissolution of both Zn-based NPs after 3 weeks, the Zn3(PO4)2 shell on ZnO_Ph NPs (48 ± 12 nm; −18.1 ± 0.6 mV) enabled a leaf uptake of 2.31 ± 0.34 μg of Zn, which is 2.7 times higher than the 0.86 ± 0.18 μg of Zn observed for ZnO NPs (26 ± 8 nm; 14.6 ± 0.4 mV). Further, ZnO_Ph NPs led to higher Zn mobility and phloem loading, while Zn from ZnO NPs was stored in the epidermal tissues, possibly through cell wall immobilization as a storage strategy. These differences led to higher translocation of Zn from the ZnO_Ph NPs within all plant compartments. ZnO_Ph NPs were also more persistent as NPs in the exposed leaf and in the plant stem over time. As a result, the treatment of ZnO_Ph NPs induced significantly higher Zn transport to the fruit than ZnO NPs. As determined by spICP-TOFMS, Zn in the fruit was not in the NP form. These results suggest that the Zn3(PO4)2 shell on ZnO NPs can help promote the transport of Zn to pepper fruits when foliarly applied. This work provides insight into the role of Zn3(PO4)2 on the surface of ZnO NPs in foliar uptake and in planta biodistribution for improving Zn delivery to edible plant parts and ultimately improving the Zn content in food for human consumption.
3D WAVE PROPAGATION AND SITE EFFECTS IN THE HUMBOLDT BAY AREA USING STRONG GROUND MOTION RECORDS FROM THE M6.5 2010 FERNDALE EARTHQUAKE

In this study we simulated and analyzed strong ground motion data recorded in the Humboldt Bay and Eureka areas during the M6.5 Ferndale area earthquake of January 2010. The scope of the presented work was two-fold. First, we investigated the main aspects of seismic wave generation and propagation, including kinematic rupture process and 3D wave propagation scattering. Our goal is to analyze their potential effects on seismic motion recorded at free field stations across Humboldt Bay and Eureka, and test the performance of a standard broadband strong ground motion simulation technique. Second, using non-linear site response analysis, we investigated the effects of shallow sedimentary layers on strong ground motion recorded by the Humboldt Bay geotechnical array. Our study provides insight into the composition of the wave field during the earthquake and an improved understanding of how the wave field is affected by the local 3D structure and the non-linear response of the shallow sediments of the Humboldt Bay.
Nucleotide-level distance metrics to quantify alternative splicing implemented in TranD

Abstract Advances in affordable transcriptome sequencing combined with better exon and gene prediction has motivated many to compare transcription across the tree of life. We develop a mathematical framework to calculate complexity and compare transcript models. Structural features, i.e. intron retention (IR), donor/acceptor site variation, alternative exon cassettes, alternative 5′/3′ UTRs, are compared and the distance between transcript models is calculated with nucleotide level precision. All metrics are implemented in a PyPi package, TranD and output can be used to summarize splicing patterns for a transcriptome (1GTF) and between transcriptomes (2GTF). TranD output enables quantitative comparisons between: annotations augmented by empirical RNA-seq data and the original transcript models; transcript model prediction tools for longread RNA-seq (e.g. FLAIR versus Isoseq3); alternate annotations for a species (e.g. RefSeq vs Ensembl); and between closely related species. In C. elegans, Z. mays, D. melanogaster, D. simulans and H. sapiens, alternative exons were observed more frequently in combination with an alternative donor/acceptor than alone. Transcript models in RefSeq and Ensembl are linked and both have unique transcript models with empirical support. D. melanogaster and D. simulans, share many transcript models and long-read RNAseq data suggests that both species are under-annotated. We recommend combined references.
Scalable Interactive Machine Learning for Future Command and Control

Future warfare will require Command and Control (C2) personnel to make decisions at shrinking timescales in complex and potentially ill-defined situations. Given the need for robust decision-making processes and decision-support tools, integration of artificial and human intelligence holds the potential to revolutionize the C2 operations process to ensure adaptability and efficiency in rapidly changing operational environments. We propose to leverage recent promising breakthroughs in interactive machine learning, in which humans can cooperate with machine learning algorithms to guide machine learning algorithm behavior. This paper identifies several gaps in state-of-the-art science and technology that future work should address to extend these approaches to function in complex C2 contexts. In particular, we describe three research focus areas that together, aim to enable scalable interactive machine learning (SIML): 1) developing human-AI interaction algorithms to enable planning in complex, dynamic situations; 2) fostering resilient human-AI teams through optimizing roles, configurations, and trust; and 3) scaling algorithms and human-AI teams for flexibility across a range of potential contexts and situations.
Sequential Flow Straightening for Generative Modeling

Straightening the probability flow of the continuous-time generative models, such as diffusion models or flow-based models, is the key to fast sampling through the numerical solvers, existing methods learn a linear path by directly generating the probability path the joint distribution between the noise and data distribution. One key reason for the slow sampling speed of the ODE-based solvers that simulate these generative models is the global truncation error of the ODE solver, caused by the high curvature of the ODE trajectory, which explodes the truncation error of the numerical solvers in the low-NFE regime. To address this challenge, We propose a novel method called SeqRF, a learning technique that straightens the probability flow to reduce the global truncation error and hence enable acceleration of sampling and improve the synthesis quality. In both theoretical and empirical studies, we first observe the straightening property of our SeqRF. Through empirical evaluations via SeqRF over flow-based generative models, We achieve surpassing results on CIFAR-10, CelebA-$64 \times 64$, and LSUN-Church datasets.
Towards full control of molecular exciton energy transfer via FRET in DNA origami assemblies

Controlling the flow of excitons between organic molecules holds immense promise for various applications, including energy conversion, spectroscopy, photocatalysis, sensing, and microscopy. DNA nanotechnology has shown promise in achieving this control by using synthetic DNA as a platform for positioning and, very recently, for also orienting organic dyes. In this study, the orientation of doubly-linked dyes in DNA origami structures was manipulated to control energy transfer. By controlling independently the orientation of single donor and acceptor molecules, the average energy transfer efficiency was doubled. This work demonstrates the potential of DNA nanotechnology for precise control of the excitonic energy transfer with implications for artificial light-harvesting antennas.
Categorical-Symmetry Resolved Entanglement in CFT

We propose a symmetry-resolved entanglement for categorical non-invertible generalized symmetries (CaT-SREE) in (1+1)-dimensional CFTs. The definition parallels that of group-like invertible symmetries employing the concept of symmetric boundary states with respect to a categorical symmetry. Our examination extends to rational CFTs, where the behavior of CaT-SREE mirrors that of group-like invertible symmetries. This includes instances of the breakdown of entanglement equipartition at the next-to-leading order in the cutoff expansion. The findings shed light on the interplay between categorical symmetries, entanglement, and boundary conditions in (1 + 1)-dimensional CFTs.
Reactor neutrino background in third-generation dark matter detectors

Third-generation dark matter detectors will be fully sensitive to the boron-8 solar neutrino flux. Because of this, the characterization of such a background has been the subject of extensive analyses over the last few years. In contrast, little is known about the impact of reactor neutrinos. In this letter we report on the implications of such a flux for dark matter direct detection searches. We consider five potential detector deployment sites envisioned by the recently established XLZD consortium: SURF, SNOLAB, Kamioka, LNGS and Boulby. By using public reactor data we construct five reactor clusters -- involving about 100 currently operating commercial nuclear reactors each -- and determine the net neutrino flux at each detector site. Assuming a xenon-based detector and a 50 tonne-year exposure, we show that in all cases the neutrino event rate may be sizable, depending on energy recoil thresholds. Of all possible detector sites, SURF and LNGS are those with the smallest reactor neutrino background. On the contrary, SNOLAB and Boulby are subject to the strongest reactor neutrino fluxes, with Kamioka being subject to a more moderate background. Our findings demonstrate that reactor neutrino fluxes should be taken into account in the next round of dark matter searches. We argue that this background may be particularly relevant for directional detectors, provided they meet the requirements we have employed in this analysis.
Promoting Target Data in Context-aware Neural Machine Translation

Standard context-aware neural machine translation (NMT) typically relies on parallel document-level data, exploiting both source and target contexts. Concatenation-based approaches in particular, still a strong baseline for document-level NMT, prepend source and/or target context sentences to the sentences to be translated, with model variants that exploit equal amounts of source and target data on each side achieving state-of-the-art results. In this work, we investigate whether target data should be further promoted within standard concatenation-based approaches, as most document-level phenomena rely on information that is present on the target language side. We evaluate novel concatenation-based variants where the target context is prepended to the source language, either in isolation or in combination with the source context. Experimental results in English-Russian and Basque-Spanish show that including target context in the source leads to large improvements on target language phenomena. On source-dependent phenomena, using only target language context in the source achieves parity with state-of-the-art concatenation approaches, or slightly underperforms, whereas combining source and target context on the source side leads to significant gains across the board.
Jointly Learning Representations for Map Entities via Heterogeneous Graph Contrastive Learning

The electronic map plays a crucial role in geographic information systems, serving various urban managerial scenarios and daily life services. Developing effective Map Entity Representation Learning (MERL) methods is crucial to extracting embedding information from electronic maps and converting map entities into representation vectors for downstream applications. However, existing MERL methods typically focus on one specific category of map entities, such as POIs, road segments, or land parcels, which is insufficient for real-world diverse map-based applications and might lose latent structural and semantic information interacting between entities of different types. Moreover, using representations generated by separate models for different map entities can introduce inconsistencies. Motivated by this, we propose a novel method named HOME-GCL for learning representations of multiple categories of map entities. Our approach utilizes a heterogeneous map entity graph (HOME graph) that integrates both road segments and land parcels into a unified framework. A HOME encoder with parcel-segment joint feature encoding and heterogeneous graph transformer is then deliberately designed to convert segments and parcels into representation vectors. Moreover, we introduce two types of contrastive learning tasks, namely intra-entity and inter-entity tasks, to train the encoder in a self-supervised manner. Extensive experiments on three large-scale datasets covering road segment-based, land parcel-based, and trajectory-based tasks demonstrate the superiority of our approach. To the best of our knowledge, HOME-GCL is the first attempt to jointly learn representations for road segments and land parcels using a unified model.