This study investigates how architectural studio environments influence student well-being through the lens of Self-Determination Theory (SDT). According to SDT, the fulfilment of three core psychological needs, autonomy, competence, and relatedness, is essential for motivation and learning. Using a convergent mixed-methods case study, we examined the lived experiences of undergraduate interior architecture design students at Osmaniye Korkut Ata University (Türkiye). Data were collected through an online survey ( n = 114), classroom observations, and a design exercise in which students reimagined their ideal studio space. Survey results revealed consistent concerns about spatial inflexibility, inadequate lighting and insufficient equipment, which students perceived as undermining their autonomy and competence. Observations confirmed these limitations, while design proposals emphasised flexible layouts, individualised workstations, improved lighting, and informal gathering spaces to foster relatedness and collaboration. By triangulating quantitative and qualitative data, the study demonstrates how deficiencies in current studio design hinder learning outcomes while also identifying strategies to create environments that support psychological well-being. The findings provide evidence-based recommendations for aligning architecture studio design with SDT principles, offering practical guidance for institutions seeking to create learning environments that foster student motivation, engagement, and well-being.
History of scholarship and learning. The humanities, Social Sciences
يهدف هذا البحث إلى تكييف العلاقات التعاقدية الناشئة عن نشاط التطبيقات، واستخلاص التزاماتها ومسؤولياتها تجاه المتعاملين معها. إذ تعمل تطبيقات توصيل الأطعمة كحلقة وصل بين المطاعم والمستهلكين والسائقين، وتدار من خلال منظومة إلكترونية معقدة. وتخضع هذه التطبيقات لعدد كبير من الأنظمة واللوائح والقرارات، مما يشكل صعوبة في تحديد الالتزامات القانونية لهذه التطبيقات. وقد اتّبع البحث المنهج الوصفي التحليلي لنصوص الأنظمة واللوائح والقرارات. وتم تقسيم البحث إلى مقدمة وتمهيد وثلاثة مباحث، جاء التمهيد في التعريف بتطبيقات توصيل الأطعمة وآلية عملها. وتطرق المبحث الأول إلى التكييف النظامي لنشاط تطبيقات التوصيل والعقود التي تنشئها، وتناول المبحث الثاني: التزامات تطبيقات التوصيل تجاه أطراف العلاقة، أما المبحث الثالث فتناول المسؤولية النظامية المترتبة على الإخلال بأي من هذه الالتزامات، وتوصل إلى أن العلاقات التي تنشأ بين التطبيقات والمتعاملين معها تكيّف بأنها عقود مركّبة تجمع بين الوساطة والوكالة والنقل والخدمات الإلكترونية، إضافة إلى عقد العمل. وأن تطبيقات توصيل الأطعمة تلتزم بالالتزامات التي تمليها هذه العقود، إضافة إلى الالتزامات التي نصت عليها الأنظمة. وأن مسؤوليات تطبيقات توصيل الأطعمة تجاه المتعاملين معها تتنوع بين المسؤولية العقدية والتقصيرية إضافة إلى المسؤولية الإدارية.
History of scholarship and learning. The humanities
Mochamad Aviandy, Fajar Muhammad Nugraha, Zeffry Alkatiri
et al.
The Tabot Festival has been held for centuries in Bengkulu, a province on the west coast of Sumatra, Indonesia. Recently, in 2023, it was made an official national-level event, representing the cultural heritage of Bengkulu. For years, the Keluarga Kerukunan Tabot (KKT, lit. ‘The Tabot Family Association’) has served as the key initiator and organizer, supported by local and provincial governments to preserve and promote the Tabot tradition. Throughout its existence the tradition has been marked by fluctuating dynamics, shaped by competing narratives around Islamic customs, economic interests, and diverse societal perceptions. Since the start of the Reform era in 1998, following the fall of president Suharto’s regime, new discourses have emerged, contesting cultural, religious, and economic elements of the festival. This article examines how Bengkulu’s Tabot tradition, as constructed to a significant extent by the KKT, encompasses various societal dimensions. Using a cultural studies approach, this study, based on field observations and in-depth interviews, reveals the ‘hidden framing’ around the tradition. Based on these interviews with stakeholders of Bengkulu’s Tabot tradition new insights are offered into how this tradition is a site of negotiation between different interest groups; whether political, economic (through the commodification of culture), tourism-related, or religious.
Abstract This study delves into the ways in which corporate social responsibility (CSR) affects cybersecurity behavior among employees. It specifically examines the mediating effects of psychological safety and job stress, as well as the moderating role of organizationally-prescribed perfectionism. Drawing on theories of social identity, social exchange, and the job demands-resources model, we postulate that CSR influences cybersecurity behavior in employees in a positive way, first through psychological safety and then through job stress as a sequential mediator. We also look at how organizationally-prescribed perfectionism moderates the connection between CSR and psychological safety. Our research design was based on collecting survey data from 402 employees in South Korea at four different time points. Our findings support the idea that CSR has a direct and indirect positive effect on cybersecurity behavior among employees through measures such as increased psychological safety and decreased job stress. In addition, the study discovered that when employees have high levels of organizationally-prescribed perfectionism, it reduces the favorable effect of CSR on psychological safety. Our findings further the current literature by illuminating the psychological processes and boundary circumstances that govern the impact of CSR on cybersecurity behavior among employees. CSR programs can promote safe online habits and boost morale, but it’s important for businesses to remember that employees have different levels of perfectionism and to accommodate those variations. In this paper, we discuss the study’s shortcomings and provide suggestions for further research to support a holistic strategy for CSR in the IT age.
History of scholarship and learning. The humanities, Social Sciences
While the huge data repositories of web archives carry big potential for knowledge production in academia, researchers have described significant challenges when trying to access and make use of web archives in research. This article describes the creation of a “Web News Collection” where content from the National Library of Norway’s web archive has been made available for computational text analysis, in a manner that facilitates access for research and beyond – aligning with FAIR principles, while also accounting for copyright restrictions. Developing the warc2corpus pipeline, we detail the processes for extracting natural language from WARC files, curating content, and enhancing metadata for analytical purposes. This structured collection — consisting of 1.5 million news articles accessible via a REST API —enables distant reading of news from the web, with tools for building corpora, word frequencies and collocations. To support usage, both programming interfaces and user-friendly web apps are offered, representing a significant step forward in making web archives usable and valuable for digital scholars.
History of scholarship and learning. The humanities, Language and Literature
This article presents a case study comparing the capabilities of humans and artificial intelligence (AI) for visual storytelling. We developed detailed instructions to recreate a three-panel Nancy cartoon strip by Ernie Bushmiller and provided them to both humans and AI systems. The human participants were 20-something students with basic artistic training but no experience or knowledge of this comic strip. The AI systems used were popular commercial models trained to draw and paint like artists, though their training sets may not necessarily include Bushmiller's work. Results showed that AI systems excel at mimicking professional art but struggle to create coherent visual stories. In contrast, humans proved highly adept at transforming instructions into meaningful visual narratives.
Multi-distribution learning extends agnostic Probably Approximately Correct (PAC) learning to the setting in which a family of $k$ distributions, $\{D_i\}_{i\in[k]}$, is considered and a classifier's performance is measured by its error under the worst distribution. This problem has attracted a lot of recent interests due to its applications in collaborative learning, fairness, and robustness. Despite a rather complete picture of sample complexity of passive multi-distribution learning, research on active multi-distribution learning remains scarce, with algorithms whose optimality remaining unknown. In this paper, we develop new algorithms for active multi-distribution learning and establish improved label complexity upper and lower bounds, in distribution-dependent and distribution-free settings. Specifically, in the near-realizable setting we prove an upper bound of $\widetilde{O}\Bigl(θ_{\max}(d+k)\ln\frac{1}{\varepsilon}\Bigr)$ and $\widetilde{O}\Bigl(θ_{\max}(d+k)\Bigl(\ln\frac{1}{\varepsilon}+\frac{ν^2}{\varepsilon^2}\Bigr)+\frac{kν}{\varepsilon^2}\Bigr)$ in the realizable and agnostic settings respectively, where $θ_{\max}$ is the maximum disagreement coefficient among the $k$ distributions, $d$ is the VC dimension of the hypothesis class, $ν$ is the multi-distribution error of the best hypothesis, and $\varepsilon$ is the target excess error. Moreover, we show that the bound in the realizable setting is information-theoretically optimal and that the $kν/\varepsilon^2$ term in the agnostic setting is fundamental for proper learners. We also establish instance-dependent sample complexity bound for passive multidistribution learning that smoothly interpolates between realizable and agnostic regimes~\citep{blum2017collaborative,zhang2024optimal}, which may be of independent interest.
Este documento es una reseña del libro: Basail Rodríguez, A., Köhler, A., & De La Garza Chávez, M. L. (2023). Figuraciones transculturales. Estudios críticos sobre geoculturas y agencias (Primera Edición). Universidad de Ciencias y Artes de Chiapas. https://doi.org/10.29043/CESMECA.rep.1090
History of scholarship and learning. The humanities, Social sciences (General)
The study's primary focus is to gather profound insights into user perceptions and preferences related to living in smart environments prioritizing thermal comfort and energy efficiency. This objective is pursued through meticulous surveys designed to capture the nuanced experiences of residents, unravelling the intricate relationship between smart technologies and their impact on daily life within these intelligent living spaces. The findings from these quantitative surveys become a valuable repository of information that sheds light on the intricate dynamics of user satisfaction and experience, providing a holistic understanding of the role played by smart technologies in shaping thermal comfort in the built environment. Additionally, the research sets out to assess the specific influence of smart technologies on thermal comfort within the urban settings of Turkey. By narrowing the focus to this geographical context, the study aims to draw region-specific insights that can be instrumental in tailoring smart living solutions to the unique needs and nuances of the Turkish urban landscape. This contextual analysis allows for a nuanced understanding of how smart technologies operate in diverse urban environments, providing a foundation for targeted interventions and improvements. A core objective of the study is to distil actionable recommendations for architects, designers, and urban planners. These recommendations are crafted with the intention of guiding the creation of user-centric spaces within the built environment that not only meet but exceed expectations in optimizing thermal comfort. By translating survey findings and regional assessments into practical suggestions, this research aims to empower professionals in the field to integrate smart technologies seamlessly into their designs, ultimately contributing to the development of intelligent, sustainable, and people-focused spaces. In summary, the study positions itself as a comprehensive exploration of the symbiotic relationship between smart technologies and thermal comfort. Through a meticulous examination of user perceptions, regional influences, and actionable recommendations, the research seeks to chart a course for a future where the built environment actively supports and enhances thermal comfort, thereby improving the overall quality of life for its residents.
History of scholarship and learning. The humanities, Social sciences (General)
Sequential learning with Gaussian processes (GPs) is challenging when access to past data is limited, for example, in continual and active learning. In such cases, errors can accumulate over time due to inaccuracies in the posterior, hyperparameters, and inducing points, making accurate learning challenging. Here, we present a method to keep all such errors in check using the recently proposed dual sparse variational GP. Our method enables accurate inference for generic likelihoods and improves learning by actively building and updating a memory of past data. We demonstrate its effectiveness in several applications involving Bayesian optimization, active learning, and continual learning.
Although supervised learning has been highly successful in improving the state-of-the-art in the domain of image-based computer vision in the past, the margin of improvement has diminished significantly in recent years, indicating that a plateau is in sight. Meanwhile, the use of self-supervised learning (SSL) for the purpose of natural language processing (NLP) has seen tremendous successes during the past couple of years, with this new learning paradigm yielding powerful language models. Inspired by the excellent results obtained in the field of NLP, self-supervised methods that rely on clustering, contrastive learning, distillation, and information-maximization, which all fall under the banner of discriminative SSL, have experienced a swift uptake in the area of computer vision. Shortly afterwards, generative SSL frameworks that are mostly based on masked image modeling, complemented and surpassed the results obtained with discriminative SSL. Consequently, within a span of three years, over $100$ unique general-purpose frameworks for generative and discriminative SSL, with a focus on imaging, were proposed. In this survey, we review a plethora of research efforts conducted on image-oriented SSL, providing a historic view and paying attention to best practices as well as useful software packages. While doing so, we discuss pretext tasks for image-based SSL, as well as techniques that are commonly used in image-based SSL. Lastly, to aid researchers who aim at contributing to image-focused SSL, we outline a number of promising research directions.
Reinforcement learning from human feedback (RLHF) has emerged as a powerful technique to make large language models (LLMs) easier to use and more effective. A core piece of the RLHF process is the training and utilization of a model of human preferences that acts as a reward function for optimization. This approach, which operates at the intersection of many stakeholders and academic disciplines, remains poorly understood. RLHF reward models are often cited as being central to achieving performance, yet very few descriptors of capabilities, evaluations, training methods, or open-source models exist. Given this lack of information, further study and transparency is needed for learned RLHF reward models. In this paper, we illustrate the complex history of optimizing preferences, and articulate lines of inquiry to understand the sociotechnical context of reward models. In particular, we highlight the ontological differences between costs, rewards, and preferences at stake in RLHF's foundations, related methodological tensions, and possible research directions to improve general understanding of how reward models function.
I många samhälleliga sammanhang återkommer en uppmaning att lyssna på barn, inte sällan med hänvisning till FN:s barnkonvention och kanske särskilt artikel 12 om rätten att bli hörd. Men vad innebär det att lyssna på barn? Mängder av böcker om lyssnande till barn som riktar sig till yrkespraktiker och andra som möter barn i sitt vardagsliv publiceras kontinuerligt. Vi saknar emellertid en kritisk diskussion som sätter frågor om lyssnande, lyssnande på barn och det goda lyssnandet i en större teoretisk kontext. Mot den bakgrunden har föreliggande artikel tillkommit. Lyssnandets problematik diskuteras här primärt i relation till monologiska och dialogiska perspektiv på kommunikation samt i relation till olika synsätt på barn (barnsyn) som lika eller olika vuxna. Avslutningsvis pekar vi på etiska implikationer som följer i kölvattnet av olika teoretiska perspektiv på lyssnande och lyssnande på barn.
History of scholarship and learning. The humanities, Social sciences (General)
The environment of uncertainty created by the COVID-19 pandemic period has caused difficulties especially for healthcare professionals in their work activities. The purpose of this research is to find out which variables might affect the commitment of healthcare professionals to their works during this COVID-19 period. Based on the data announced by the Ministry of Health during the pandemic in the first quarter of 2021, it was decided to conduct a research on doctors, nurses, caregivers, and medical secretaries working in hospitals in the cities of the Eastern Black Sea Region of Turkey which generally show high risk. In the developed research model, satisfactory conditions (SC), emotional commitment to change (ECC), and psychological ownership (PO) as variables that may directly or indirectly affect the commitment of healthcare professionals to their works (CW) were used. The Smart PLS program was used in the analysis of the research model and hypothesis. It was seen that the ECC of healthcare professionals has a positive and significant (.694; p < .000) effect on SC. It was understood that the PO of healthcare professionals has positive and significant effects on their CW (.394; p < .000). It was also observed that the presence of SC has positive and significant effects on the PO of the healthcare professionals in the current situation (.796; p < .000). It was observed that only the effect of ECC of healthcare professionals on their CW is insignificant (.097; p > .086). Looking at the indirect (intermediary) effects obtained as a result of the research, it was seen that all of the hypotheses consist of positive coefficients. This situation reveals that the mediating variables have complementary effects on the obtained results.
History of scholarship and learning. The humanities, Social Sciences
Este texto explora en la historia de las compañías nacional de teatro y sus contextos para buscar considerar su pertinencia en este momento. La investigación se desarrolló a partir de la revisión de libros, documentos, artículos académicos, artículos periodísticos y entrevistas con los responsables de algunas de las iniciativas. El resultado fue la identificación de cuatro hitos: el nacimiento en 1946 con Santiago Ontañón, el paso a la INSAD y a La Cabaña con Armando Robles Godoy y el Teatro Ambulante en 1957, el Teatro Nacional Popular con Alonso Alegría en 1971 y el Teatro Nacional en 1995 con Ruth Escudero. Tras la revisión, se concluyó que, en este momento, no es pertinente ni necesaria una compañía nacional, ya que competiría con la producción local.
History of scholarship and learning. The humanities, Literature (General)
Mikhail G. Katz, Karl Kuhlemann, David Sherry
et al.
We examine some recent scholarship on Leibniz's philosophy of the infinitesimal calculus. We indicate difficulties that arise in articles by Bassler, Knobloch, and Arthur, due to a denial to Leibniz's infinitesimals of the status of mathematical entities violating Euclid V Definition 4.
Khaled Koutini, Shahed Masoudian, Florian Schmid
et al.
The success of supervised deep learning methods is largely due to their ability to learn relevant features from raw data. Deep Neural Networks (DNNs) trained on large-scale datasets are capable of capturing a diverse set of features, and learning a representation that can generalize onto unseen tasks and datasets that are from the same domain. Hence, these models can be used as powerful feature extractors, in combination with shallower models as classifiers, for smaller tasks and datasets where the amount of training data is insufficient for learning an end-to-end model from scratch. During the past years, Convolutional Neural Networks (CNNs) have largely been the method of choice for audio processing. However, recently attention-based transformer models have demonstrated great potential in supervised settings, outperforming CNNs. In this work, we investigate the use of audio transformers trained on large-scale datasets to learn general-purpose representations. We study how the different setups in these audio transformers affect the quality of their embeddings. We experiment with the models' time resolution, extracted embedding level, and receptive fields in order to see how they affect performance on a variety of tasks and datasets, following the HEAR 2021 NeurIPS challenge evaluation setup. Our results show that representations extracted by audio transformers outperform CNN representations. Furthermore, we will show that transformers trained on Audioset can be extremely effective representation extractors for a wide range of downstream tasks.
In human-robot collaboration domains, augmented reality (AR) technologies have enabled people to visualize the state of robots. Current AR-based visualization policies are designed manually, which requires a lot of human efforts and domain knowledge. When too little information is visualized, human users find the AR interface not useful; when too much information is visualized, they find it difficult to process the visualized information. In this paper, we develop a framework, called VARIL, that enables AR agents to learn visualization policies (what to visualize, when, and how) from demonstrations. We created a Unity-based platform for simulating warehouse environments where human-robot teammates collaborate on delivery tasks. We have collected a dataset that includes demonstrations of visualizing robots' current and planned behaviors. Results from experiments with real human participants show that, compared with competitive baselines from the literature, our learned visualization strategies significantly increase the efficiency of human-robot teams, while reducing the distraction level of human users. VARIL has been demonstrated in a built-in-lab mock warehouse.
Prior political turmoil in the United States constituted a precarious foundation for living and teaching through a pandemic. In this essay, I contend that pandemic separation and ideological distortion have exacerbated polarization and distrust. I also consider the pedagogical implications of rising extremist discourses and conspiratorial thinking for both students and faculty. Educators must pay attention to the rising threat of extremism and consider that our students may be susceptible to radical antidemocratic ideologies as well. To conclude, I provide examples from some of my classes in the communication discipline to illustrate my approach to teaching the complicated intersections of rhetoric and reality in today’s polarized political climate.
This study aims to build and examine a model of sustainable supply management (SSM) practices and sustainability performance (SP) from a dynamic capability perspective. More precisely, this article examines whether SSM practices have an affect on SP, and this relation is mediated by supply chain risk management (SCRM) and network capability (NC), and moderated by firm size. We collected data from 436 supply management professionals through a survey instrument from six manufacturing and logistics companies in China. The hypothesized direct and indirect linkages were tested through structural equation modeling. Our findings highlight that SSM practices positively affect SCRM, NC, and SP. The link between SSM practices and SP is mediated by SCRM and NC. The results indicate that firm size moderate the hypothesized relationships differentially based on small and medium-sized enterprises (SMEs) versus large enterprises. Our study is novel in establishing empirically how SSM practices influence SP as an integrative model bringing together firm size, SCRM, and NC. Our empirical results have critical implications for both supply chain management literature and supply management professionals.
History of scholarship and learning. The humanities, Social Sciences