Exploring Lexical Alignment in a Price Bargain Chatbot

This study investigates the integration of lexical alignment into text-based negotiation chatbots, including its impact on user satisfaction, perceived trustworthiness, and potential influences on negotiation results. Lexical alignment is the phenomenon where participants in a conversation adopt similar words. This study introduces a chatbot architecture for price negotiation, consisting of components such as intent and price/product extractors, dialogue management, and response generation using OpenAI’s API, with a lexical alignment feature. To evaluate the effects of lexical alignment on negotiation outcomes and the user’s perception of the chatbot, a between-subject user experiment was conducted online. A total of 52 individuals participated. While the results do not show statistical significance, they suggest that lexical alignment might positively influence user satisfaction. This finding indicates a potential direction for enhancing user interaction with chatbots in the future

Effects of 1.5 °C global warming on pavement climatic factors and performance

This study compared 11 global climate models (GCMs) in assessing the variability of predicted pavement performance in 24 cities in the U.S. under 1.5 °C global warming and presented equations to estimate the impacts of global warming on pavement performance more simply. The results show a spread among GCMs regarding their predicted pavement deterioration with some models resulting in higher deterioration values than others. Thermal cracking, fatigue cracking, total rutting, and international roughness index (IRI) for the investigated 24 cities in the U.S. are found to increase by 124 ft/mi (23.11 m/km), 24 %, 4.6 %, and 1 % on average under 1.5 °C global warming comparatively to the baseline scenario (1991–2010). Regardless of GCMs, the results reveal southern U.S. cities are expected to suffer from greater changes in IRI and thermal cracking, while global warming induced rutting and fatigue cracking will be of greater concern in northern cities than in southern cities.</p

ONEKANA:Modelling thermal inequalities in African cities

Africa, as a major climate change hotspot, faces severe impacts, including extreme temperatures. Notably, urban areas are unequally affected by these impacts. The urban poor are particularly vulnerable to extreme temperatures, because of the environmental and physical characteristics of their neighbourhoods, and their limited resources to develop coping strategies. Limited knowledge exists of the spatial patterns of thermal inequalities within neighbourhoods. Our overall scientific objective is to explore the potential of Earth Observation (EO) to study how and why urban dwellers in the Global South (focusing on Africa) with different levels of deprivation are divergently exposed to varying temperatures and extreme heat, and to quantify the urban population exposed to such conditions. We make use of several state-of-the-art EO/AI models, and employ innovative in situ data collection methods together with local stakeholders through Citizen Science. We rely as far as possible on open or low-cost satellite imagery (e.g., Sentinel-1/2, Landsat, ECOSTRESS) for scalability and transferability, and we implement Machine Learning (ML) methods, including Deep Learning (DL). Results highlight significant local differences in thermal exposure, emphasizing the need to understand and communicate these spatial patterns to support the development of cost-effective adaptation strategies

Radiotherapy Trends and Variations in Invasive Non-metastatic Breast Cancer Treatment in the Netherlands:A Nationwide Overview From 2008 to 2019

Aims: This nationwide study provides an overview of trends and variations in radiotherapy use as part of multimodal treatment of invasive non-metastatic breast cancer in the Netherlands in 2008–2019. Materials and Methods: Women with invasive non-metastatic breast cancer were selected from the population-based Netherlands Cancer Registry. Treatments trends were presented over time. Factors associated with (1) boost irradiation in breast-conserving therapy and (2) regional radiotherapy instead of axillary lymph node dissection (ALND) in N+ disease were identified using multilevel logistic regression analyses. Results: Radiotherapy use increased from 61% (2008) to 70% (2016), caused by breast-conserving therapy instead of mastectomy, increased post-mastectomy radiotherapy, and increased regional radiotherapy (32% in 2011 to 61% in 2019) instead of ALND in N+ disease. Omission of radiotherapy after breast-conserving surgery (BCS) in 2016–2019 (4–9%, respectively), mainly in elderly, decreased overall radiotherapy use to 67%. Radiotherapy treatment was further de-escalated by decreased boost irradiation in breast-conserving therapy (66% in 2011 to 37% in 2019) and partial (1% in 2011 to 6% in 2019) instead of whole breast irradiation following BCS. Boost irradiation was associated with high-risk features: younger age (OR&gt;75 vs &lt;50:0.04, 95%CI:0.03–0.05), higher grade (OR grade III vs I:11.46, 95%CI:9.90–13.26) and residual disease (OR focal residual vs R0-resection:28.08, 95%CI:23.07–34.17). Variation across the country was found for both boost irradiation use (OR South vs North:0.58, 95%CI:0.49–0.68), and regional radiotherapy instead of ALND (OR Southwest vs North:0.55, 95%CI:0.37–0.80). Conclusion: Overall radiotherapy use increased in 2008–2016, while a decreasing trend was observed after 2016, caused by post-BCS radiotherapy omission. Boost irradiation in breast-conserving therapy became omitted in low-risk patients, and regional radiotherapy use increased as an alternative for ALND in N+ disease.</p

Design Implications for Next Generation Chatbots with Education 5.0

Prior research indicates that chatbots have the capacity to significantly enhance learning performance, student satisfaction, and engagement. Chatbots are employed in various educational contexts, serving as content delivery platforms, facilitating student interaction, fostering collaborative learning, and promoting question-and-answer practice, among other applications. Moreover, integrating chatbots into teaching practices empowers educators to analyze and assess students’ learning abilities and comprehension levels. However, much of the existing research on educational instruments, including chatbots, lacks both theoretical support from recent advancements in the learning sciences and an evidence-informed foundation for selecting appropriate data and information models. As a consequence, educational chatbots run the risk of yielding unintended negative consequences instead of delivering the intended benefits. This study seeks to address this gap by grounding the design of educational chatbots in the principles of learning sciences. We argue that effective communication through educational chatbots necessitates formulating information in the form of feedback dialogues to enhance learners’ comprehension. Additionally, we align the design of educational chatbots with learner-centric and mindful technology concepts, inline with Industry 5.0 digitization strategies.</p

Development of an IALF Overarching Learning Module for Circular Economy

The increasing importance of sustainable business models due to the scarcity of resources and resulting political regulations leads many companies and research institutions towards the concept of Circular Economy. Subsequently, the learning factory community is facing the challenge of expanding existing concepts to include Circular Economy in their learning factories. Therefore, a learning factory- and competency-based module for Circular Economy is developed by eight members of the International Association of Learning Factories to define a common ground. The module covers the basics of Circular Economy in the production environment and make it tangible through concrete use cases. To achieve these goals, extensive research on existing concepts has been conducted by IALF experts to analyze learning objectives and requirements in detail and derive required competencies. Based on that, the learning module is developed.</p

Survey of Simulators for Aerial Robots

Uncrewed Aerial Vehicle (UAV) research faces challenges with safety, scalability, costs, and ecological impact when conducting hardware testing. High-fidelity simulators offer a vital solution by replicating real-world conditions to enable the development and evaluation of novel perception and control algorithms. However, the large number of available simulators poses a significant challenge for researchers to determine which simulator best suits their specific use-case, based on each simulator's limitations and customization readiness. In this paper we present an overview of 44 UAV simulators, including in-depth, systematic comparisons for 14 of the simulators. Additionally, we present a set of decision factors for selection of simulators, aiming to enhance the efficiency and safety of research endeavors

Querying Fault and Attack Trees:Property Specification on a Water Network

We provide an overview of three different query languages whose objective is to specify properties on the highly popular formalisms of fault trees (FTs) and attack trees (ATs). These are BFL, a Boolean Logic for FTs, PFL, a probabilistic extension of BFL and ATM, a logic for security metrics on ATs. We validate the framework composed by these three logics by applying them to the case study of a water distribution network. We extend the FT for this network - found in the literature - and we propose to model the system under analysis with the Fault Trees/Attack Trees (FT/ATs) formalism, combining both FTs and ATs in a unique model. Furthermore, we propose a novel combination of the showcased logics to account for queries that jointly consider both the FT and the AT of the model, integrating influences of attacks on failure probabilities of different components. Finally, we extend the domain specific language for PFL with novel constructs to capture the interplay between metrics of attacks - e.g., 'cost', success probabilities - and failure probabilities in the system.</p