Abstract In the digital education era, artificial intelligence has developed rapidly in education in China, and hybrid teaching models have become popular. This study aims to explore whether college students’ enjoyment in online classes influences their learning interest and achievement of learning goals, and to examine the moderating role of teacher-student interaction in the realization of learning goals. We conducted an online questionnaire survey of 1736 college students in China to explore the relationships among enjoyment, learning interest, teacher-student interaction, and the achievement of learning goals of online classes. All statistical analyses were performed using SPSS 25.0 and Mplus 8.0. These findings show that college students’ enjoyment influences the achievement of learning goals through the mediating role of learning interest in online classes. The high level of teacher–student interaction is conducive to the transformation of students’ enjoyment into learning interest and the achievement of learning goals. Our study is expected to serve as an important reference for increasing students’ learning interest and achieving their learning goals in online classes.
History of scholarship and learning. The humanities, Social Sciences
Effective clinical history taking is a foundational yet underexplored component of clinical reasoning. While large language models (LLMs) have shown promise on static benchmarks, they often fall short in dynamic, multi-turn diagnostic settings that require iterative questioning and hypothesis refinement. To address this gap, we propose \method{}, a note-driven framework that trains LLMs to conduct structured history taking and diagnosis by learning from widely available medical notes. Instead of relying on scarce and sensitive dialogue data, we convert real-world medical notes into high-quality doctor-patient dialogues using a decision tree-guided generation and refinement pipeline. We then propose a three-stage fine-tuning strategy combining supervised learning, simulated data augmentation, and preference learning. Furthermore, we propose a novel single-turn reasoning paradigm that reframes history taking as a sequence of single-turn reasoning problems. This design enhances interpretability and enables local supervision, dynamic adaptation, and greater sample efficiency. Experimental results show that our method substantially improves clinical reasoning, achieving gains of +16.9 F1 and +21.0 Top-1 diagnostic accuracy over GPT-4o. Our code and dataset can be found at https://github.com/zhentingsheng/Note2Chat.
19. yüzyılda Osmanlı Devleti, toplumsal ve siyasal düzenin istikrarını temin etmek amacıyla Ehl-i Sünnet inancı dışındaki çeşitli dini ve mezhebi gruplara yönelik politikalar geliştirmiştir. Bu çerçevede, Kızılbaş topluluklarına da belirli düzenlemeler ve tedbirler uygulanmıştır. Kızılbaş gruplar, dinî ayrışma ve İran etkisine bağlı bir siyasi tehdit olarak değerlendirilmiş ve özellikle II. Abdülhamid döneminde (1876-1909), Kızılbaşların inanç pratiklerini Ehl-i Sünnet inançlarına uygun hale getirmek amacıyla “tashih-i itikad” politikaları uygulanmıştır. Ancak bu politikalar, yerel direnişler ve devletin uygulama yetersizlikleri nedeniyle beklenen sonuçları verememiştir. Osmanlının mezhepsel farklılıklarla baş etme çabaları, dinî birlikteliği sağlama ve merkezi otoriteyi güçlendirme hedefleri çerçevesinde şekillense de sahadaki uygulamalar bu hedeflerle uyumlu sonuçlar doğurmamıştır. Bu araştırma, II. Abdülhamid döneminde Kızılbaşlara yönelik tashih-i itikad politikalarının ideolojik gerekçelerini, tarihsel arka planını ve toplumsal yansımalarını incelemeyi amaçlamaktadır. Bu bağlamda, dönemin dinî ve siyasal kaygıları ile mezhepsel farklılıklar arasındaki ilişki, tarihî belgeler üzerinden analiz edilmiştir. Osmanlı Devleti’nin farklı inanç gruplarına yönelik din-siyaset politikalarının uygulanış biçimleri ve bu politikaların toplumsal etkileri ele alınarak, mezhepsel farklılıkların yönetimi konusundaki tarihsel deneyimler ortaya konmuştur. Osmanlı Devleti’nin farklı inanç gruplarıyla ilişkilerini anlamak açısından özgün bir katkı sunulmuştur. Kızılbaş gruplara yönelik politikaların mezhepsel ayrışmayı nasıl etkilediği ve dönemin toplumsal yapısı üzerindeki yansımaları, arşiv belgeleri ve tarihsel veriler ışığında değerlendirilmiştir. Osmanlı tarih yazımı İslam Mezhepleri Tarihi perspektifinden ele alınarak, bu döneme dair dinî ve siyasal politikalara vurgu yapılmıştır. Osmanlı arşiv belgeleri, resmî yazışmalar ve İslam Mezhepleri Tarihi ve diğer ilim dallarına ait araştırmalar temel alınarak değerlendirmeler yapılmıştır. Tarihî belge analizi ve nitel yöntemlerin bir araya getirilmesiyle, Kızılbaş gruplara yönelik tashih-i itikad politikaları, tarihî ve sosyolojik bağlamda değerlendirilmiştir. İslam Mezhepleri Tarihi yazıcılığının ilkeleri doğrultusunda, Kızılbaşların inanç yapıları, toplumsal konumları ve Osmanlı bürokrasisinin bu gruplara yaklaşımı analiz edilmiştir. Osmanlı Devleti, Kızılbaşlara yönelik politikalarında Ehl-i Sünnet inancını tahkim etmeyi amaçlamıştır. Eğitim reformları, cami-mescit inşası, din görevlilerinin istihdamı ve dinî risalelerin hazırlanması gibi adımlar bu hedeflerin gerçekleştirilmesi için temel araçlar olarak öne çıkmıştır. Ancak, dedelerin toplumsal etkisi, yerel direnç ve devletin uygulama yetersizlikleri bu politikaların başarısını sınırlamıştır. Eğitim kurumlarının yetersizliği, imam ve müderris eksikliği gibi yapısal sorunlar, tashih-i itikad çabalarının etkisini azaltmıştır. Ayrıca, Kızılbaş grupların tarihî, kültürel ve coğrafi farklılıklarının dikkate alınmaması, bu politikaların toplumsal kabul görmesini zorlaştırmıştır. Elde edilen bulgular, tashih-i itikad politikalarının yalnızca dinî bir çaba değil, aynı zamanda İran etkisi, misyoner faaliyetler ve mezhepsel ayrışma gibi siyasi tehditlere karşı bir strateji olarak uygulandığını göstermektedir. Bu politikaların sert müdahalelerle şekillendirilmesi, mezhep gerilimlerini azaltmak yerine artırmış, Kızılbaşların devlete karşı daha dirençli bir duruş sergilemesine yol açmıştır. Eğitimsizlik ve dinî bilgi eksikliği gibi nedenlerle şekillenen toplumsal sorunlar, mezhepsel ayrışmanın derinleşmesine katkı sağlamıştır. Sonuç olarak, Osmanlı Devleti’nin 19. yüzyıldaki tashih-i itikad politikaları, mezhepsel farklılıkları kontrol altına almayı ve toplumsal düzeni korumayı amaçlamış; ancak yerel dinamiklerin ve toplumsal gerçekliklerin göz ardı edilmesi, bu çabaların başarısını sınırlamıştır.
This article aims to demonstrate the essential role of compassion in the puritan practice of spiritual healing, as it developed in England from the end of the reign of Elizabeth I to the end of the 1630s. While the pastoral care established by puritan divines to address the spiritual crises caused by soteriological anxiety has received some scholarly attention, the question of the emotional resources mobilised by spiritual consolers remains a neglected theme in existing scholarship. Yet, if spiritual comfort is a discursive exchange, the interaction it involves is not solely verbal but also encompasses a significant emotional dimension. In particular, the guides to the practice of spiritual comfort consistently identify compassion as an indispensable quality for the exercise of spiritual comfort: it allows the consoler to find the right balance between gentleness and firmness in their interaction with the afflicted; more generally, it contributes to creating a protective therapeutic environment, based on a relationship of trust and benevolence, within which the afflicted benefits from constant spiritual and emotional support.
History (General) and history of Europe, French literature - Italian literature - Spanish literature - Portuguese literature
Multi-role pedagogical agents can create engaging and immersive learning experiences, helping learners better understand knowledge in history learning. However, existing pedagogical agents often struggle with multi-role interactions due to complex controls, limited feedback forms, and difficulty dynamically adapting to user inputs. In this study, we developed a VR prototype with LLM-powered adaptive role-switching and action-switching pedagogical agents to help users learn about the history of the Pavilion of Prince Teng. A 2 x 2 between-subjects study was conducted with 84 participants to assess how adaptive role-switching and action-switching affect participants' learning outcomes and experiences. The results suggest that adaptive role-switching enhances participants' perception of the pedagogical agent's trustworthiness and expertise but may lead to inconsistent learning experiences. Adaptive action-switching increases participants' perceived social presence, expertise, and humanness. The study did not uncover any effects of role-switching and action-switching on usability, learning motivation, and cognitive load. Based on the findings, we proposed five design implications for incorporating adaptive role-switching and action-switching into future VR history education tools.
Modernist propositions long have been understood as atemporal—somehow outside of time—or insistently hailing the future. This temporal framework suppresses the contributions of those excluded from modernist canons, particularly Black women. In this article, visual and material analysis of sculptural works produced in the 1970s and 1980s by U.S. Black women artists Beverly Buchanan, Senga Nengudi, and Betye Saar reveal how Black feminists have engaged with modernist protocols in order to redress cultural erasures of Black women. These practices exemplify <i>Black feminist modernisms</i>, or creative practices that unsettle the racist and sexist logics of dominant cultural institutions. Each of these artists utilizes haptic surfaces as a method for defying institutional modernism’s obfuscation of the past. The analysis focuses on Buchanan’s defiance of memorial erasures, Nengudi’s reenactment of labor, including in its historical forms, and Saar’s adaptation of generational memory-making processes. Ultimately, these artists’ rejection of a “timeless” modernism demands that viewers understand the present moment in relationship to a still-evolving past. In this way, Buchanan, Nengudi, and Saar position the present as an accumulation, rather than transcendence, of historical occurrences.
Hassan Asadigandomani, Nader Mohammadi, Hamid Riazi-Esfahani
et al.
A girl of 8 years old was referred to our clinic with a history of penetrating injury to her left eye 6 years ago with light perception vision and a large traumatic macular hole in her right eye. Her right eye’s vision was 4/10 when she first visited our clinic. Considering the patient’s one-eye status, her parents’ reluctance to undergo surgery, and the possibility of spontaneous closure of traumatic macular holes, it was determined to observe the patient and evaluate her visual acuity and macular hole condition. In 2 years, the final best corrected visual acuity was 8/10 in the right eye, with infratemporal eccentric fixation in visuoscopy. In addition to evaluating and reporting this case as a traumatic macular hole, we will discuss the role of nonsurgical treatment and the possibility of good visual acuity with eccentric fixation in a child with large traumatic macular hole.
Offline reinforcement learning (RL) can in principle synthesize more optimal behavior from a dataset consisting only of suboptimal trials. One way that this can happen is by "stitching" together the best parts of otherwise suboptimal trajectories that overlap on similar states, to create new behaviors where each individual state is in-distribution, but the overall returns are higher. However, in many interesting and complex applications, such as autonomous navigation and dialogue systems, the state is partially observed. Even worse, the state representation is unknown or not easy to define. In such cases, policies and value functions are often conditioned on observation histories instead of states. In these cases, it is not clear if the same kind of "stitching" is feasible at the level of observation histories, since two different trajectories would always have different histories, and thus "similar states" that might lead to effective stitching cannot be leveraged. Theoretically, we show that standard offline RL algorithms conditioned on observation histories suffer from poor sample complexity, in accordance with the above intuition. We then identify sufficient conditions under which offline RL can still be efficient -- intuitively, it needs to learn a compact representation of history comprising only features relevant for action selection. We introduce a bisimulation loss that captures the extent to which this happens, and propose that offline RL can explicitly optimize this loss to aid worst-case sample complexity. Empirically, we show that across a variety of tasks either our proposed loss improves performance, or the value of this loss is already minimized as a consequence of standard offline RL, indicating that it correlates well with good performance.
HNCO and SiO are well known shock tracers and have been observed in nearby galaxies, including the nearby (D=3.5 Mpc) starburst galaxy NGC 253. The simultaneous detection of these two species in regions where the star formation rate is high may be used to study the shock history of the gas. We perform a multi-line molecular study using these two shock tracers (SiO and HNCO) with the aim of characterizing the gas properties. We also explore the possibility of reconstructing the shock history in NGC 253's Central Molecular Zone (CMZ). Six SiO transitions and eleven HNCO transitions were imaged at high resolution $1''.6$ (28 pc) with the Atacama Large Millimeter/submillimeter Array (ALMA) as part of the ALCHEMI Large Programme. Both non-LTE radiative transfer analysis and chemical modelling were performed in order to characterize the gas properties, and to investigate the chemical origin of the emission. The non-LTE radiative transfer analysis coupled with Bayesian inference shows clear evidence that the gas traced by SiO has different densities and temperatures than that traced by HNCO, with an indication that shocks are needed to produce both species. Chemical modelling further confirms such a scenario and suggests that fast and slow shocks are responsible for SiO and HNCO production, respectively, in most GMCs. We are also able to infer the physical characteristics of the shocks traced by SiO and HNCO for each GMC. Radiative transfer and chemical analysis of the SiO and HNCO in the CMZ of NGC 253 reveal a complex picture whereby most of the GMCs are subjected to shocks. We speculate on the possible shock scenarios responsible for the observed emission and provide potential history and timescales for each shock scenario. Higher spatial resolution observations of these two species are required in order to quantitatively differentiate between scenarios.
The use of the Monte Carlo technique in a reliable and inexpensive way without the need for a standard radioactive source in determining the detector efficiency is becoming widespread every passing day. It is important to model the detector with the real dimensions for an accurate and precise results for the method. Another parameter as important as detector modeling is the number of histories in the simulation code examined in this study. In this study, the effect of the number of histories on the efficiency was examined in detail using different simulation codes. The results obtained in this work, at least 107 particle numbers should be used in all three programs where the uncertainty is below 1%. If the existing facilities are sufficient, it can be increased to 108s in case of having a more equipped and fast computer. However, going higher than this value does not make any sense as seen from the study.
We introduce the partially observable history process (POHP) formalism for reinforcement learning. POHP centers around the actions and observations of a single agent and abstracts away the presence of other players without reducing them to stochastic processes. Our formalism provides a streamlined interface for designing algorithms that defy categorization as exclusively single or multi-agent, and for developing theory that applies across these domains. We show how the POHP formalism unifies traditional models including the Markov decision process, the Markov game, the extensive-form game, and their partially observable extensions, without introducing burdensome technical machinery or violating the philosophical underpinnings of reinforcement learning. We illustrate the utility of our formalism by concisely exploring observable sequential rationality, examining some theoretical properties of general immediate regret minimization, and generalizing the extensive-form regret minimization (EFR) algorithm.
The spin distribution of massive black holes (MBHs) contains rich information on their assembly history. However, only limited information can be extracted from currently available spin measurements of MBHs owing to the small sample size and large measurement uncertainties. Upcoming X-ray telescopes with improved spectral resolution and larger effective area are expected to provide new insights into the growth history of MBHs. Here we investigate, at a proof of concept level, how stringent constraints can be placed on the accretion history of MBHs by the spin measurements from future X-ray missions. We assume a toy model consisting of a two-phase accretion history composed of an initial coherent phase with a constant disk orientation, followed by a chaotic phase with random disk orientations in each accretion episode. By utilizing mock spin data generated from such models and performing Bayesian Markov Chain Monte Carlo simulations, we find that most accretion models of MBHs can be reconstructed provided that $\gtrsim100$ MBH spins are measured with an accuracy of $\lesssim0.1$. We also quantify the precision of the reconstructed parameters by adopting various combinations of sample sizes and spin accuracies, and find that the sample size is more crucial to model reconstruction once the spin accuracy reaches $\sim 0.1$. To some extent, a better spin accuracy will compensate for a small sample size and vice versa. Future X-ray missions such as the Advanced Telescope for High Energy Astrophysics and the enhanced X-ray Timing and Polarimetry mission, may provide spin measurements of $\gtrsim100$ MBHs with an uncertainty of $\sim0.04-0.1$ and will thus put strong constraints on the MBH growth history.
Kathryn Garside, Aida Gjoka, Robin Henderson
et al.
Persistent homology is used to track the appearance and disappearance of features as we move through a nested sequence of topological spaces. Equating the nested sequence to a filtration and the appearance and disappearance of features to events, we show that simple event history methods can be used for the analysis of topological data. We propose a version of the well known Nelson-Aalen cumulative hazard estimator for the comparison of topological features of random fields and for testing parametric assumptions. We suggest a Cox proportional hazards approach for the analysis of embedded metric trees. The Nelson-Aalen method is illustrated on globally distributed climate data and on neutral hydrogen distribution in the Milky Way. The Cox method is use to compare vascular patterns in fundus images of the eyes of healthy and diabetic retinopathy patients.