Miracle-dz/UniFAR-FTUs huggingface dataset:
The decarbonisation of Europe powered by lifestyle changes

Decision makers increasingly recognise the importance of lifestyle changes in reaching low emission targets. How the mitigation potential of changes in mobility, dietary, housing or consumption behaviour compare to those of ambitious technological changes in terms of decarbonisation remains a key question. To evaluate the interplay of behaviour and technological changes, we make use of the European Calculator model and show that changes in behaviour may contribute more than 20% of the overall greenhouse gas (GHG) emission reductions required for net-zero by 2050. Behaviour and technology-oriented scenarios are tested individually and in combination for the EU plus the UK and Switzerland. The impacts of behavioural change vary across sectors, with significant GHG emission reduction potential and broader benefits. Changes in travel behaviour limit the rising demand for electricity, natural resources and infrastructure costs from the electrification of passenger transport. Adopting a healthy diet reduces emissions substantially compared to intensifying agricultural practices, while at the same time making cropland available for conservation or bioenergy crops. The trade-offs between energy and food may be substantially alleviated when deploying technological and behavioural changes simultaneously. The results suggest that without behavioural change, the dependency of Europe on carbon removal technologies for its net-zero ambitions increases. Structural changes will be necessary to achieve full decarbonisation by 2050, yet changes in lifestyles are crucial, contributing to achieving climate targets sooner.
Trust Drivers and Revisit Intention of Foreign Tourists in Bali

Previous studies on the consequences of trust on revisit intention have been carried out both at service companies and modern retailers, but how it affects tourists rvisit intention at traditional market has not been widely carried out. This study aims to explain the factors that influence trust as well as its consequences on revisit intention of tourists at souvenir traditional market in Bali. In addition, it also explained the role of trust to mediate the effect service quality and product quality towards tourist revisit intention. A survey was conducted from foreign tourists who visited and experienced to shop souvenirs at the traditional market in Bali. The data were analyzed using the SEM-PLS approach. This study revealed that service quality had a positive and significant effect on trust and revisit intention, product quality had a positive and significant effect on trust and revisit intention, trust partially mediated the effect of service quality towards revisit intention and the effect of product quality towards revisit intention. The important factors in creating tourists trust and increasing tourist revisit intention are the ability to maintain consistency of service quality and product quality. This research is expected to prove the importance of trust to shape tourists behaviours, especially revisit intention to souvenir traditional market.
Effects of Support-Seekers’ Community Knowledge on Their Expressed Satisfaction with the Received Comments in Mental Health Communities

Online mental health communities (OMHCs) are prominent resources for improving people’s mental wellbeing. An immediate cue of such improvement is support-seekers’ satisfaction expressed in their replies to the received comments. However, the comments that seekers find satisfying may change with their community knowledge, e.g., measured by tenure and posting experience in that community. In this paper, we first model the amount of satisfaction conveyed in the support-seekers’ replies to the received comments. Then we quantitatively examine how seekers’ expressed satisfaction is affected by their community knowledge, sought and received support in an OMHC. Results show that support-seekers with more posting experience generally display less contentment to the received comments. Compared to newcomers, higher tenured members express less satisfaction when receiving informational support. We also found that support matching positively predicts seekers’ satisfaction regardless of their community knowledge. Our findings have implications for OMHCs to satisfy support-seekers through their community knowledge.
What Motivates Students Engaging with Public Universities: A Case in Vietnam

The fierce competition among educational institutions further affirms the role of maintaining student cohesion as an important strategy for each institution's existence and development. Therefore, the need to better understand this topic for both academics and managers is getting more and more interesting. The relationships between student engagement, and motives have been investigated through several studies in developed countries context, but they have not yet been properly considered for developing countries. An appropriate method - MEC- explored the motivations that force students to engage with the educational institutions in this study. The results show that the five main student engagement motivations include career orientation, financial relevance, memorable emotion, meaningful behaviour, and self-enhancement. This result is expected not only to provide more information for education administrators in determining the factors motivating student engagement with a specific institution but to complement knowledge to the literature foundation of student engagement.
Deformation-dependent peak floor acceleration for the performance-based design of nonstructural elements attached to R/C structures

This study introduces a simple and efficient method to determine the peak floor acceleration (PFA) at different performance levels for three types of plane reinforced concrete (RC) structures: moment-resisting frames (MRFs), infilled–moment-resisting frames (I-MRFs), and wall-frame dual systems (WFDSs). By associating the structural maximum PFA response with the deformation response, the acceleration-sensitive nonstructural components, and the building contents, can be designed to adhere to the performance-based seismic design of the supporting structure. Thus, the proposed method can accompany displacement-based seismic design methods to design acceleration-sensitive nonstructural elements to comply with the deformation target of the supporting structure. The PFA response shape is represented by line segments defined by key points corresponding to certain floor levels. These key points are defined by explicit empirical expressions developed herein. The maximum PFA response is correlated with the maximum interstory drift ratio (IDR) and other vital characteristics of the supporting structure such as the fundamental period. The proposed expressions are established based on extensive nonlinear dynamic analyses of 19 MRFs, 19 WFDSs, and 19 I-MRFs under 100 far-fault ground motions scaled to capture different deformation targets. Realistic examples demonstrate the efficiency of the proposed method to assess the PFA response at a given IDR, making the method suitable in the framework of performance-based design.
Human beings and robots: Are there any differences in the attribution of punishments for the same crimes?

ABSTRACT As collaborative robots and artificial intelligence (AI) systems are being deployed in ever-increasing contexts, we are more and more called upon to make judgements on their moral behaviour. Understanding the factors, affecting our ethical judgements involving these types of agents, would thus seem of the uttermost importance to allow for safer and well-regulated interactions between humans and machines. So far, however, this topic has been rarely investigated. We compared the perception of the seriousness of an action committed by either a person or a robot, causing harm to either some persons or some robots, and the attribution of the appropriated punishment for that action. The results showed a significant effect of the type of victim: the action was considered more a serious offence, and deemed worthy of more severe punishment, if the victims were humans than if they were robots. A significant agent-by-victim interaction was also found in the punishment judgements: for human victims, a human agent was punished more severely than a robot, while for robot victims, a robot agent was attributed a more severe punishment than a human one. The results are discussed in the light of the theories linking moral judgements to mind perception.
Echolocation as a Means for People with Visual Impairment (PVI) to Acquire Spatial Knowledge of Virtual Space

In virtual environments, spatial information is communicated visually. This prevents people with visual impairment (PVI) from accessing such spaces. In this article, we investigate whether echolocation could be used as a tool to convey spatial information by answering the following research questions: What features of virtual space can be perceived by PVI through the use of echolocation? How does active echolocation support PVI in acquiring spatial knowledge of a virtual space? And what are PVI’s opinions regarding the use of echolocation to acquire landmark and survey knowledge of virtual space? To answer these questions, we conducted a two-part within-subjects experiment with 12 people who were blind or had a visual impairment and found that size and materials of rooms and 90-degree turns were detectable through echolocation, participants preferred using echoes derived from footsteps rather than from artificial sound pulses, and echolocation supported the acquisition of mental maps of a virtual space. Ultimately, we propose that appropriately designed echolocation in virtual environments improves understanding of spatial information and access to digital games for PVI.
Task-Specific Pre-Training and Cross Lingual Transfer for Sentiment Analysis in Dravidian Code-Switched Languages

Sentiment analysis in Code-Mixed languages has garnered a lot of attention in recent years. It is an important task for social media monitoring and has many applications, as a large chunk of social media data is Code-Mixed. In this paper, we work on the problem of sentiment analysis for Dravidian Code-Switched languages - Tamil-Engish and Malayalam-English, using three different BERT based models. We leverage task-specific pre-training and cross-lingual transfer to improve on previously reported results, with significant improvement for the Tamil-Engish dataset. We also present a multilingual sentiment classification model that has competitive performance on both Tamil-English and Malayalam-English datasets.
WASSA 2021 Shared Task: Predicting Empathy and Emotion in Reaction to News Stories

This paper presents the results that were obtained from the WASSA 2021 shared task on predicting empathy and emotions. The participants were given access to a dataset comprising empathic reactions to news stories where harm is done to a person, group, or other. These reactions consist of essays, Batson empathic concern, and personal distress scores, and the dataset was further extended with news articles, person-level demographic information (age, gender, ethnicity, income, education level), and personality information. Additionally, emotion labels, namely Ekman’s six basic emotions, were added to the essays at both the document and sentence level. Participation was encouraged in two tracks: predicting empathy and predicting emotion categories. In total five teams participated in the shared task. We summarize the methods and resources used by the participating teams.
Advancing Digital Behavior Change Interventions by Exploring a Calendar-Based Suggestion System

Digital Behavior Change Interventions (DBCI) have a pivotal role in reducing lifestyle-related illness, absenteeism, and healthcare costs. Current challenges in designing DBCI are appropriately tailoring interventions and finding new forms of delivery. In this exploratory work, we present the design and evaluation of Tweak, a cloud-based health promotion system that integrates tailored and context-aware health suggestions into the users digital work calendar. Two four-week field studies (N=21) showed how Tweak adapted to changing user profiles and used personal and contextual data to situate suggestions. User insights showed that integration into the calendar stimulated reflective behavior and curiosity and was perceived as easy to use. However, due to differences in calendar use, suggestions could be overlooked. We conclude by discussing implications on how integrated delivery mechanisms can aid the development of future workplace DBCI.
Working with Machine Learning/Artificial Intelligence systems: workers’ viewpoints and experiences

The recent developments of Artificial Intelligence (AI) have raised several social issues, especially about the consequences of the deployment of AI systems on work. This paper aims to discuss those issues in light of literature and an ongoing empirical study. Drawing on a qualitative method, this study explores workers’ viewpoints on and/or experiences of AI systems in different work situations. We organize our findings according to five dimensions: place and usage of Machine Learning/Artificial Intelligence (ML/AI) systems in work settings; “relationship” between ML/AI systems and workers; explainability; trust; and transformations of work. For each dimension, we examine workers’ viewpoints and experiences, in the light of recent “gray” literature and on previous ergonomics literature on automation and AI.
ELITR Multilingual Live Subtitling: Demo and Strategy

This paper presents an automatic speech translation system aimed at live subtitling of conference presentations. We describe the overall architecture and key processing components. More importantly, we explain our strategy for building a complex system for end-users from numerous individual components, each of which has been tested only in laboratory conditions. The system is a working prototype that is routinely tested in recognizing English, Czech, and German speech and presenting it translated simultaneously into 42 target languages.
Understanding Social Support Expressed in a COVID-19 Online Forum

In online forums focused on health and wellbeing, individuals tend to seek and give the following social support: emotional and informational support. Understanding the expressions of these social supports in an online COVID- 19 forum is important for: (a) the forum and its members to provide the right type of support to individuals and (b) determining the long term effects of the COVID-19 pandemic on the well-being of the public, thereby informing interventions. In this work, we build four machine learning models to measure the extent of the following social supports expressed in each post in a COVID-19 online forum: (a) emotional support given (b) emotional support sought (c) informational support given, and (d) informational support sought. Using these models, we aim to: (i) determine if there is a correlation between the different social supports expressed in posts e.g. when members of the forum give emotional support in posts, do they also tend to give or seek informational support in the same post? (ii) determine how these social supports sought and given changes over time in published posts. We find that (i) there is a positive correlation between the informational support given in posts and the emotional support given and emotional support sought, respectively, in these posts and (ii) over time, users tended to seek more emotional support and give less emotional support.
Human Likeness in robots: Differences between industrial and non-industrial robots

This study aims to provide an original investigation of the morphological features and the anthropomorphic characteristics of industrial robots. In the introduction, we summarise some empirical findings on the topic, drawing to the Uncanny Valley hypothesis and other theoretical frameworks. Subsequently, we conduct an argumentative literature review to elicit the connection between industrial use and morphological features of robots, particularly in the European and Italian robotic context. We hypothesise that non-industrial robots are distinguishable from the other types of robots basing on their degree of Human Likeness and that facial features are crucial in determining such difference, whilst hands and fingers would report a higher level of HL in industrial robots. We tested our hypothesis using the open-source ABOT database, which aggregates descriptions of robots for industrial and non-industrial use. We found support for our hypothesis (p=.04, F=2.88). Ultimately, we offer some considerations about the physical features associated with the use of robots in the industrial context and their functionality.
miRNA-193a-3p Regulates the AKT2 Pathway to Inhibit the Growth and Promote the Apoptosis of Glioma Cells by Targeting ALKBH5

Emerging evidence indicates that microRNA (miR)-193a-3p is involved in the tumor progression of various cancers. However, the biological functions and precise molecular mechanisms of miR-193a-3p in gliomas have not been well documented. Accordingly, this study focused on the tumor suppressor role and molecular mechanisms of miR-193a-3p in glioma cells. miR-193a-3p expression was determined by qRT-PCR in glioma tissues and cell lines. U251 and U87 glioma cells were transfected with a miR-193a-3p mimic. The effects of miR-193a-3p on cell growth and apoptosis were investigated using MTT, colony-forming, and flow cytometry assays. Overexpression of miR-193a-3p in U87 cells also significantly suppressed tumorigenicity and induced apoptosis in the xenograft mouse model. Luciferase assays were conducted to determine if ALKBH5 is a direct target of miR-193a-3p in glioma cells. Immunoprecipitation was used to explore the interaction between ALKBH5 and RAC-serine/threonine-protein kinase 2 (AKT2) in glioma cells. miR-193a-3p was downregulated in glioma tissues and cell lines. miR-193a-3p treatment suppressed proliferation and promoted apoptosis in both U251 and U87 cells. Bioinformatics analysis and luciferase reporter assay identified a novel miR-193a-3p target, ALKBH5. Notably, the antitumor effect of miR-193a-3p transfection in glioma cells may be due to the miR-193a-3p–induced inhibition of AKT2 expression caused by the suppression of ALKBH5 expression. Furthermore, immunoprecipitation indicated that ALKBH5 physically interacted with AKT2 through an RNA-independent mechanism in glioma cells. miR-193a-3p directly targets ALKBH5 to inhibit the growth and promote the apoptosis of glioma cells by suppressing the AKT2 pathway both in vitro and in vivo, and the physical interaction between ALKBH5 and AKT2 is essential for suppressing cell apoptosis by upregulating miR-193a-3p in glioma cells. Our study revealed that the antitumor effects of miR-193a-3p on glioma cells is due to ALKBH5 mediation of the AKT2-induced intrinsic apoptosis signaling pathway.
Creative Capabilities of Machine Learning: Evaluating music created by algorithms

The concept of creativity is an important part of human society and the continuous evolution of artificial minds has raised questions on creativity among machines. This aim of the this study is to explore machine learning algorithms’ ability to be creative. The study reported in this paper uses short samples of music generated by IBM Watson beats that are evaluated using expert assessment of 51 music teachers together with samples generated by humans as control samples. The results show that one of the machine learning generated samples showed the same level of creativity as the human generated samples. Hence, there are indications that today machine learning algorithms can create music that is hard to distinguish from human created music and can be considered creative.
Effect of Day 3 and Day 5/6 Embryo Quality on the Reproductive Outcomes in the Single Vitrified Embryo Transfer Cycles

Objective To explore the live birth rate and neonatal outcome after single vitrified blastocyst transfer versus single vitrified cleavage-stage embryo transfer at different grades of embryo quality. Methods A retrospective cohort study including 6077 single vitrified-thawed embryo transfer cycles was performed in the time-period from January 2013 to December 2018. Results After controlling for potential confounding variables, there are 161% increased odds of a live birth after transfer of single good quality embryo at day 5, 152% increased odds of a live birth after transfer of single poor quality embryo at day 5, 60% increased odds of a live birth after transfer of single good quality embryo at day 6 compared with transfer of single good quality embryo at day 3. Results from the generalized estimated equation regression showed significant relationship of unadjusted birth weight with development stage of embryo and embryo quality (good quality embryo on day 5 vs. Good quality embryo on day 3:β=108.55, SE=34.89, P=0.002; good quality embryo on day 6 vs. Good quality embryo on day 3:β=68.80, SE=33.75, P=0.041). However, no significant differences were seen in birth weight between transfer single poor quality embryo on day 5, 6 and transfer single good quality embryo on day 3. Conclusion A significant increase in live birth rate and birth weight after transfer of single good quality embryo on day 5 and day 6 compared with transfer of single good quality embryo on day 3 in the vitrified embryo transfer cycles.
Construction and Validation of Novel Nomograms for Predicting Prognosis of Pancreatic Ductal Adenocarcinoma After Surgery According to Different Primary Cancer Locations

Background/Aims Pancreatic ductal adenocarcinoma (PDAC) can occur in different parts of the pancreas. This study aimed to identify clinicopathological characteristics independently correlated with the prognosis of PDAC of the pancreatic head/uncinate (PHC) or body-tail (PBTC), and to develop novel nomograms for predicting cancer-specific survival (CSS) according to different primary cancer locations. Methods 1160 PDAC patients were retrospectively enrolled and assigned to training and test sets with each set divided into PHC and PBTC groups. Comparative analysis of clinicopathologic characteristics, survival analysis, and multivariate analysis were performed. Independent factors were identified and used for constructing nomograms. The performance of the nomograms was validated in the test set. Results Primary tumor location was an independent risk factor for prognosis of PDAC after surgery. Specially, gender, fasting blood glucose, and preoperative cancer antigen 19-9 were significantly associated with prognosis of PHC, whereas age, body mass index, and lymph nodes were significantly correlated with the prognosis of PBTC. A significant difference in prognosis was found between PHC and PBTC in stage Ia and stage III. Three nomograms were established for predicting the prognosis for PDAC, PHC, and PBTC. Notably, these nomograms were calibrated modestly (c-indexes of 0.690 for PDAC, 0.669 for PHC, and 0.704 for PBTC), presented better accuracy and reliability than the 8th AJCC staging system, and achieved clinical validity. Conclusions PHC and PBTC share the differential clinical-pathological characteristics and survival. The nomograms show good performance for predicting prognosis in PHC and PBTC. Therefore, these nomograms hold potential as novel approaches for predicting survival of PHC and PBTC patients after surgery.