El artículo presenta una nueva lectura de CLE 614. El modo de conservación de la placa funeraria correspondiente a CLE 614, hallada en la iglesia de San Gereón en Colonia, ha supuesto variaciones en la lectura de algunas de sus partes y ha generado controversia sobre su posible naturaleza cristiana. Por ello, el presente trabajo tiene como objetivo aportar luz sobre las dudas sobre su naturaleza cristiana, pero también ofrecer una nueva edición crítica de su texto completo a partir de la observación directa de la pieza y las ediciones previas de la misma. Esta nueva lectura ha permitido una mejor interpretación del texto, conformado por seis hexámetros dactílicos, en los que destacan ciertos términos y recursos poéticos propios de la epigrafía latina en verso, y enfocado en presentar una lamentatio por la muerte de Optata, la joven difunta.
Early Christian literature. Fathers of the Church, etc.
Samuel Church, Joshua D. Warner, Danyal Maqbool
et al.
The development of machine learning models for CT imaging depends on the availability of large, high-quality, and diverse annotated datasets. Although large volumes of CT images and reports are readily available in clinical picture archiving and communication systems (PACS), 3D segmentations of critical findings are costly to obtain, typically requiring extensive manual annotation by radiologists. On the other hand, it is common for radiologists to provide limited annotations of findings during routine reads, such as line measurements and arrows, that are often stored in PACS as GSPS objects. We posit that these sparse annotations can be extracted along with CT volumes and converted into 3D segmentations using promptable segmentation models, a paradigm we term Opportunistic Promptable Segmentation. To enable this paradigm, we propose SAM2CT, the first promptable segmentation model designed to convert radiologist annotations into 3D segmentations in CT volumes. SAM2CT builds upon SAM2 by extending the prompt encoder to support arrow and line inputs and by introducing Memory-Conditioned Memories (MCM), a memory encoding strategy tailored to 3D medical volumes. On public lesion segmentation benchmarks, SAM2CT outperforms existing promptable segmentation models and similarly trained baselines, achieving Dice similarity coefficients of 0.649 for arrow prompts and 0.757 for line prompts. Applying the model to pre-existing GSPS annotations from a clinical PACS (N = 60), SAM2CT generates 3D segmentations that are clinically acceptable or require only minor adjustments in 87% of cases, as scored by radiologists. Additionally, SAM2CT demonstrates strong zero-shot performance on select Emergency Department findings. These results suggest that large-scale mining of historical GSPS annotations represents a promising and scalable approach for generating 3D CT segmentation datasets.
Abstract During the Cold War, various political forces sought to shape the mindset of the Chinese diaspora. One understudied cultural influence that played an important role in reaching overseas Chinese was Chinese Christian literature. Focusing on Dengta ( Lighthouse , 1956–1967), the first Chinese Christian magazine aimed at non-Christian communities in the diaspora, this study examines how the magazine developed an evangelical discourse that engaged with the cultural and spiritual identities of the Chinese diaspora amid political and ideological conflicts. Published in Hong Kong, which emerged as a hub for Chinese Christian literature in the post-war period, the magazine reflects a pivotal shift in Chinese Christian publishing: the start of a global movement aimed at evangelizing overseas Chinese. To appeal to the diaspora, Dengta adopted an ethnic and cultural rhetoric of Chineseness and presented Christian ideals in a context that resonated with the experiences of the Chinese diaspora. I argue that the Chineseness promoted by Dengta helped construct a transregional and transnational sense of belonging for overseas Chinese by framing a blend of traditional Chinese culture and modern knowledge within a Christian cosmic worldview. This study foregrounds the evangelical efforts of Christian literary workers to shape the diasporic experience amid the political tensions of the Cold War.
Artykuł podejmuje problematykę józefologiczną w pismach Hieronima ze Strydonu. Mnich z Betlejem w swoich rozważaniach nie poświęca miejsca temu świętemu w sposób bezpośredni. Józef zajmuje ważne miejsce w dyskusjach chrystologicznych oraz w obronie dziewictwa Maryi. Autor Wulgaty posługuje się również przykładem Józefa w dyskusjach dotyczących wyższości życia w dziewictwie nad życiem w małżeństwie. Można wyodrębnić kilka tematów związanych ze św. Józefem, które porusza Hieronim w swoich dziełach: odrzucenie wdowieństwa św. Józefa, podkreślanie jego dziewiczości, walka o prawdziwe a nie legendarne przedstawienie postaci Opiekuna Zbawiciela oraz uzasadnianie jego pozostania w stanie bezżennym spowodowane misją daną od Boga. Należy jednak stwierdzić, że Autor Wulgaty porusza wątki związane z Opiekunem Zbawiciela w celu przedstawienia prawdziwej chrystologii lub obrony dziewictwa Najświętszej Maryi Panny. Wartym podkreślenie jest fakt, że w tekstach Strydończyka możemy zaobserwować początki myśli teologicznej o misji św. Józefa.
Early Christian literature. Fathers of the Church, etc., Philosophy of religion. Psychology of religion. Religion in relation to other subjects
Peter Plantinga, Briac Cordelle, Dominique Louër
et al.
Using speech samples as a biomarker is a promising avenue for detecting and monitoring the progression of Parkinson's disease (PD), but there is considerable disagreement in the literature about how best to collect and analyze such data. Early research in detecting PD from speech used a sustained vowel phonation (SVP) task, while some recent research has explored recordings of more cognitively demanding tasks. To assess the role of language in PD detection, we tested pretrained models with varying data types and pretraining objectives and found that (1) text-only models match the performance of vocal-feature models, (2) multilingual Whisper outperforms self-supervised models whereas monolingual Whisper does worse, and (3) AudioSet pretraining improves performance on SVP but not spontaneous speech. These findings together highlight the critical role of language for the early detection of Parkinson's disease.
Francesco Vitale, Stephen A. Church, Daniel Repp
et al.
Nanowire-based plasmonic lasers are now established as nano-sources of coherent radiation, appearing as suitable candidates for integration into next-generation nanophotonic circuitry. However, compared to their photonic counterparts, their relatively high losses and large lasing thresholds still pose a burdening constraint on their scalability. In this study, the lasing characteristics of ZnO nanowires on Ag and Al substrates, operating as optically-pumped short-wavelength plasmonic nanolasers, are systematically investigated in combination with the size-dependent performance of the hybrid cavity. A hybrid nanomanipulation-assisted single nanowire optical characterization combined with high-throughput PL spectroscopy enables the correlation of the lasing characteristics to the metal substrate and the nanowire diameter. The results evidence that the coupling between excitons and surface plasmons is closely tied to the relationship between substrate dispersive behavior and nanowire diameter. Such coupling dictates the degree to which the lasing character, be it more plasmonic- or photonic-like, can define the stimulated emission features and, as a result, the device performance.
In this paper we discuss the growing need for system behaviour to be validated and verified (V&V'ed) early in model-based systems engineering. Several aspects push companies towards integration of techniques, methods, and processes that promote specific and general V&V activities earlier to support more effective decision-making. As a result, there are incentives to introduce new technologies to remain competitive with the recently drastic changes in system complexity and heterogeneity. Performing V&V early on in development is a means of reducing risk for later error detection while moving key activities earlier in a process. We present a summary of the literature on early V&V and position existing challenges regarding potential solutions and future investigations. In particular, we reason that the software engineering community can act as a source for inspiration as many emerging technologies in the software domain are showing promise in the wider systems domain, and there already exist well formed methods for early V&V of software behaviour in the software modelling community. We conclude the paper with a road-map for future research and development for both researchers and practitioners to further develop the concepts discussed in the paper.
Francisco Bolanos, Angelo Salatino, Francesco Osborne
et al.
This manuscript presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology that assesses and integrates previous research on a given topic. Numerous tools have been developed to assist and partially automate the SLR process. The increasing role of AI in this field shows great potential in providing more effective support for researchers, moving towards the semi-automatic creation of literature reviews. Our study focuses on how AI techniques are applied in the semi-automation of SLRs, specifically in the screening and extraction phases. We examine 21 leading SLR tools using a framework that combines 23 traditional features with 11 AI features. We also analyse 11 recent tools that leverage large language models for searching the literature and assisting academic writing. Finally, the paper discusses current trends in the field, outlines key research challenges, and suggests directions for future research.
The rapid global aging trend has led to an increase in dementia cases, including Alzheimer's disease, underscoring the urgent need for early and accurate diagnostic methods. Traditional diagnostic techniques, such as cognitive tests, neuroimaging, and biomarker analysis, face significant limitations in sensitivity, accessibility, and cost, particularly in the early stages. This study explores the potential of machine learning (ML) as a transformative approach to enhance early dementia detection by leveraging ML models to analyze and integrate complex multimodal datasets, including cognitive assessments, neuroimaging, and genetic information. A comprehensive review of existing literature was conducted to evaluate various ML models, including supervised learning, deep learning, and advanced techniques such as ensemble learning and transformer models, assessing their accuracy, interpretability, and potential for clinical integration. The findings indicate that while ML models show significant promise in improving diagnostic precision and enabling earlier interventions, challenges remain in their generalizability, interpretability, and ethical deployment. This research concludes by outlining future directions aimed at enhancing the clinical utility of ML models in dementia detection, emphasizing interdisciplinary collaboration and ethically sound frameworks to improve early detection and intervention strategies for Alzheimer's disease and other forms of dementia.
Often pieces of information are received sequentially over time. When did one collect enough such pieces to classify? Trading wait time for decision certainty leads to early classification problems that have recently gained attention as a means of adapting classification to more dynamic environments. However, so far results have been limited to unimodal sequences. In this pilot study, we expand into early classifying multimodal sequences by combining existing methods. We show our new method yields experimental AUC advantages of up to 8.7%.
Stephen A. Church, Hoyeon Choi, Nawal Al-Amairi
et al.
Optoelectronic micro- and nanostructures have a vast parameter space to explore for modification and optimisation of their functional performance. This paper reports on a data-led approach using high-throughput single nanostructure spectroscopy to probe > 8,000 structures, allowing for holistic analysis of multiple material and optoelectronic parameters with statistical confidence. The methodology is applied to surface-guided CsPbBr$_3$ nanowires, which have complex and interrelated geometric, structural and electronic properties. Photoluminescence-based measurements, studying both the surface and embedded interfaces, exploits the natural inter-nanowire geometric variation to show that increasing the nanowire width reduces the optical bandgap, increases the recombination rate in the nanowire bulk and reduces the rate at the surface interface. A model of carrier recombination and diffusion is developed which ascribes these trends to carrier density and strain effects at the interfaces and self-consistently retrieves values for carrier mobility, trap densities, bandgap, diffusion length and internal quantum efficiency. The model predicts parameter trends, such as the variation of internal quantum efficiency with width, which is confirmed by experimental verification. As this approach requires minimal a-priori information, it is widely applicable to nano- and micro-scale materials.
Pre-training with self-supervised models, such as Hidden-unit BERT (HuBERT) and wav2vec 2.0, has brought significant improvements in automatic speech recognition (ASR). However, these models usually require an expensive computational cost to achieve outstanding performance, slowing down the inference speed. To improve the model efficiency, we introduce an early exit scheme for ASR, namely HuBERT-EE, that allows the model to stop the inference dynamically. In HuBERT-EE, multiple early exit branches are added at the intermediate layers. When the intermediate prediction of the early exit branch is confident, the model stops the inference, and the corresponding result can be returned early. We investigate the proper early exiting criterion and fine-tuning strategy to effectively perform early exiting. Experimental results on the LibriSpeech show that HuBERT-EE can accelerate the inference of the HuBERT while simultaneously balancing the trade-off between the performance and the latency.
Purpose: The early identification of maximum tolerated dose (MTD) in phase I trial leads to faster progression to a phase II trial or an expansion cohort to confirm efficacy. Methods: We propose a novel adaptive design for identifying MTD early to accelerate dose-finding trials. The early identification of MTD is determined adaptively by dose-retainment probability using a trial data via Bayesian analysis. We applied the early identification design to an actual trial. A simulation study evaluates the performance of the early identification design. Results: In the actual study, we confirmed the MTD could be early identified and the study period was shortened. In the simulation study, the percentage of the correct MTD selection in the early identification Keyboard and early identification Bayesian optimal interval (BOIN) designs was almost same from the non-early identification version. The early identification Keyboard and BOIN designs reduced the study duration by about 50% from the model-assisted designs. In addition, the early identification Keyboard and BOIN designs reduced the study duration by about 20% from time-to-event model-assisted designs. Conclusion: We proposed the early identification of MTD maintaining the accuracy to be able to short the study period.
The turn of the twentieth century represents an incisive moment in religious thought and theological education. Scholars across Europe and North America were wrestling with the twin influences of Protestant Liberalism and Roman Catholic Modernism, the questions they raised for how to conceive of the origins of Christianity, and how to make them palatable to a rapidly changing world. In her most recent monograph, The Fathers Refounded: Protestant Liberalism, Roman Catholic Modernism, and the Teaching of Ancient Christianity in Early Twentieth-Century America, Elizabeth A. Clark explores these questions in the lives and work of three of the era's most influential figures. Her work stands at the center of this forum, with four distinguished scholars considering its implications.
Background: To investigate the correlation between genomic variation and certain diseases or phenotypes, the fundamental task is to screen out the concerning publications from massive literature, which is called literature triage. Some knowledge bases, including UniProtKB/Swiss-Prot and NHGRI-EBI GWAS Catalog are created for collecting concerning publications. These publications are manually curated by experts, which is time-consuming. Moreover, the manual curation of information from literature is not scalable due to the rapidly increasing amount of publications. In order to cut down the cost of literature triage, machine-learning models were adopted to automatically identify biomedical publications. Methods: Comparing to previous studies utilizing machine-learning models for literature triage, we adopt a multi-channel convolutional network to utilize rich textual information and meanwhile bridge the semantic gaps from different corpora. In addition, knowledge embeddings learned from UMLS is also used to provide extra medical knowledge beyond textual features in the process of triage. Results: We demonstrate that our model outperforms the state-of-the-art models over 5 datasets with the help of knowledge embedding and multiple channels. Our model improves the accuracy of biomedical literature triage results. Conclusions: Multiple channels and knowledge embeddings enhance the performance of the CNN model in the task of biomedical literature triage. Keywords: Literature Triage; Knowledge Embedding; Multi-channel Convolutional Network
Chociaż Toksaris Lukiana jest formalnie dialogiem, jego zawartość stanowi zbiór fantastycznych i sentymentalnych historii o przyjaźni, przedstawianych przez Greka Mnesipposa i Scytę Toksarisa w formie retorycznego agonu, mającego dowieść wyższości jednej z nacji. Interpretacja dialogu stanowi problem: może być on odczytywany jako utwór, który w rozrywkowej formie przekazuje pochwałę tradycyjnej przyjaźni, lub też jako typowa dla Lukiana parodia, skierowana przeciwko sentymentalnym poglądom na męską przyjaźń, przedstawianym w romantycznych powieściach, legendach i mitach. W artykule tym sugeruję, że w Toksarisie Lukian posługuje się humorem przede wszystkim po to, aby podważyć powszechne stereotypy na temat Greków i „barbarzyńców”, a także pokazać nową formę przyjaźni – przyjaźń pomiędzy ludźmi dzielącymi podobne wartości, opartą na wspólnej paidei.
Early Christian literature. Fathers of the Church, etc., Philosophy of religion. Psychology of religion. Religion in relation to other subjects
W przedstawionym artykule został omówiony proces chrystianizacji Afryki Północnej. Podstawę opracowania stanowią przede wszystkim dzieła autorów starochrześcijańskich (Tertulian, Cyprian, Lakancjusz, Augustyn) oraz uchwały synodów afrykańskich. Na podstawie dostępnych danych, trudno jest opisać początki chrześcijaństwa w Afryce. Wydaje się, że przybyło ono z Jerozolimy i rozprzestrzeniło się wśród wspólnot żydowskich, a z biegiem czasu także wśród rdzennych mieszkańców Afryki. Ewangelizacja nie miała charakteru instytucjonalnego, a była owocem świadectwa życia chrześcijan, postawy męczenników, a także gorliwej pracy duchownych. Starano się przede wszystkim o przeprowadzenie rzetelnej i pogłębionej katechezy związanej z przyjęciem sakramentu chrztu, a także przygotowaniem do obchodów najważniejszych uroczystości liturgicznych. Niemałą rolą w kształtowaniu społeczeństwa chrześcijańskiego odegrała także żywa działalność synodalna Kościoła. Niestety wspólnotę chrześcijan osłabiły toczące ją rozłamy, a także najazd ariańskich Wandalów.
Early Christian literature. Fathers of the Church, etc., Philosophy of religion. Psychology of religion. Religion in relation to other subjects
Sina Loriani, Alexander Friedrich, Christian Ufrecht
et al.
The phase of matter waves depends on proper time and is therefore susceptible to special-relativistic (kinematic) and gravitational (redshift) time dilation. Hence, it is conceivable that atom interferometers measure general-relativistic time-dilation effects. In contrast to this intuition, we show: (i.) Closed light-pulse interferometers without clock transitions during the pulse sequence are not sensitive to gravitational time dilation in a linear potential. (ii.) They can constitute a quantum version of the special-relativistic twin paradox. (iii.) Our proposed experimental geometry for a quantum-clock interferometer isolates this effect.