Miracle-dz/UniFAR-FTUs huggingface dataset:
User Expectations of Conversational Chatbots Based on Online Reviews

Open-domain chatbots that can engage in a conversation on any topic received significant attention in the last several years, which opened opportunities for studying user interaction with them. Drawing from reviews of chatbots posted on Google Play, we explore user experience and expectations of these agents in a mixed-method study. Results of statistical analysis reveal which social qualities of chatbots are the most significant for user satisfaction. Further, we employ natural language processing and qualitative methods to identify how users wish their chatbots to evolve in the future. While currently users mostly value the entertaining component of their experience, their expectations call for more human-like behavior of chatbots. The most prominent expectations include chatbots’ abilities to treat and express emotions and be more attentive to the user. Based on these findings, we conclude with design implications, discussing the directions for developing social skills of open-domain chatbots.
Shöwn: Adaptive Conceptual Guidance Aids Example Use in Creative Tasks

Examples are powerful tools for creativity and can provide inspiration and structure. However, novices often don’t know when to seek examples or how to apply them. Showing real-time examples targeted to the current task (adaptive conceptual guidance) may help novices consider inspiration more often and better implement the ideas that examples illustrate. We explore this in a Wizard-of-Oz system, Shöwn, that presents examples based on the user’s current activity while drawing a comic strip. Shöwn’s design is informed by interviews with novice and expert comic artists (n=18). A between-subjects experiment (n=24) found that adaptive conceptual guidance improved the clarity and uniqueness of drawings and stories compared to non-adaptive examples. Users also found the examples more useful and inspirational than those without adaptive guidance. Our results present an initial exploration of the challenges and benefits of contextually showing examples in interactive creativity tools.
Early Address Prediction

Achieving low load-to-use latency with low energy and storage overheads is critical for performance. Existing techniques either prefetch into the pipeline (via address prediction and validation) or provide data reuse in the pipeline (via register sharing or L0 caches). These techniques provide a range of tradeoffs between latency, reuse, and overhead. In this work, we present a pipeline prefetching technique that achieves state-of-the-art performance and data reuse without additional data storage, data movement, or validation overheads by adding address tags to the register file. Our addition of register file tags allows us to forward (reuse) load data from the register file with no additional data movement, keep the data alive in the register file beyond the instruction’s lifetime to increase temporal reuse, and coalesce prefetch requests to achieve spatial reuse. Further, we show that we can use the existing memory order violation detection hardware to validate prefetches and data forwards without additional overhead. Our design achieves the performance of existing pipeline prefetching while also forwarding 32% of the loads from the register file (compared to 15% in state-of-the-art register sharing), delivering a 16% reduction in L1 dynamic energy (1.6% total processor energy), with an area overhead of less than 0.5%.
VXSlate: Exploring Combination of Head Movements and Mobile Touch for Large Virtual Display Interaction

Virtual Reality (VR) headsets can open opportunities for users to accomplish complex tasks on large virtual displays using compact and portable devices. However, interacting with such large virtual displays using existing interaction techniques might cause fatigue, especially for precise manipulation tasks, due to the lack of physical surfaces. To deal with this issue, we explored the design of VXSlate, an interaction technique that uses a large virtual display as an expansion of a tablet. We combined a user’s head movements as tracked by the VR headset, and touch interaction on the tablet. Using VXSlate, a user head movements positions a virtual representation of the tablet together with the user’s hand, on the large virtual display. This allows the user to perform fine-tuned multi-touch content manipulations. In a user study with seventeen participants, we investigated the effects of VXSlate on users in problem-solving tasks involving content manipulations at different levels of difficulty, such as translation, rotation, scaling, and sketching. As a baseline for comparison, off-the-shelf touch-controller interactions were used. Overall, VXSlate allowed participants to complete the task with completion times and accuracy that are comparable to touch-controller interactions. After an interval of use, VXSlate significantly reduced users’ time to perform scaling tasks in content manipulations, as well as reducing perceived effort. We reflected on the advantages and disadvantages of VXSlate in content manipulation on large virtual displays and explored further applications within the VXSlate design space.
Neuro-DCF: Design of Wireless MAC via Multi-Agent Reinforcement Learning Approach

The carrier sense multiple access (CSMA) algorithm has been used in the wireless medium access control (MAC) under standard 802.11 implementation due to its simplicity and generality. An extensive body of research on CSMA has long been made not only in the context of practical protocols, but also in a distributed way of optimal MAC scheduling. However, the current state-of-the-art CSMA (or its extensions) still suffers from poor performance, especially in multi-hop scenarios, and often requires patch-based solutions rather than a universal solution. In this paper, we propose an algorithm which adopts an experience-driven approach and train CSMA-based wireless MAC by using deep reinforcement learning. We name our protocol, Neuro-DCF. Two key challenges are: (i) a stable training method for distributed execution and (ii) a unified training method for embracing various interference patterns and configurations. For (i), we adopt a multi-agent reinforcement learning framework, and for (ii) we introduce a novel graph neural network (GNN) based training structure. We provide extensive simulation results which demonstrate that our protocol, Neuro-DCF, significantly outperforms 802.11 DCF and O-DCF, a recent theory-based MAC protocol, especially in terms of improving delay performance while preserving optimal utility. We believe our multi-agent reinforcement learning based approach would get broad interest from other learning-based network controllers in different layers that require distributed operation.
”Why are they all obsessed with Gender?” — (Non)binary Navigations through Technological Infrastructures

Gender is encoded in multiple technological infrastructures, most prominently in digital forms across educational, commercial, medical and governmental contexts. To illustrate the pervasiveness of (binary) gender ideologies and the impact this can have on non-binary individuals – like me – encountering them, I conducted an autoethnography. For more than a year, starting with me receiving a legal non-binary status, I documented systems that did not allow me to register my gender correctly. The findings indicate how technological infrastructures predominantly encode gender as a fixed, immutable and static binary variable with limited options for non-binary people to adequately register self-determined choices for gender and/or (gendered) titles. I further analyse the range of reactions that I received when pro-actively asking for workarounds, fixes and updates, indicating how pointing towards those issues can trouble the status quo, identities and power hierarchies in unintended ways. I close on suggestions for the refactoring of existing and design of new technological infrastructures around gender and reflect on the value of lived experience in knowledge production – as well as the cost it comes with for those doing this research.
Flynn’s Reconciliation

A large portion of the recent performance increase in the High Performance Computing (HPC) and Machine Learning (ML) domains is fueled by accelerator cards. Many popular ML frameworks support accelerators by organizing computations as a computational graph over a set of highly optimized, batched general-purpose kernels. While this approach simplifies the kernels’ implementation for each individual accelerator, the increasing heterogeneity among accelerator architectures for HPC complicates the creation of portable and extensible libraries of such kernels. Therefore, using a generalization of the CUDA community’s warp register cache programming idiom, we propose a new programming idiom (CoRe) and a virtual architecture model (PIRCH), abstracting over SIMD and SIMT paradigms. We define and automate the mapping process from a single source to PIRCH’s intermediate representation and develop backends that issue code for three different architectures: Intel AVX512, NVIDIA GPUs, and NEC SX-Aurora. Code generated by our source-to-source compiler for batched kernels, borG, competes favorably with vendor-tuned libraries and is up to 2× faster than hand-tuned kernels across architectures.
Understanding Cache Compression

Hardware cache compression derives from software-compression research; yet, its implementation is not a straightforward translation, since it must abide by multiple restrictions to comply with area, power, and latency constraints. This study sheds light on the challenges of adopting compression in cache design—from the shrinking of the data until its physical placement. The goal of this article is not to summarize proposals but to put in evidence the solutions they employ to handle those challenges. An in-depth description of the main characteristics of multiple methods is provided, as well as criteria that can be used as a basis for the assessment of such schemes. It is expected that this article will ease the understanding of decisions to be taken for the design of compressed systems and provide directions for future work.
The CoCe Design Space: Exploring the Design Space for Co-Located Collaborative Games that Use Multi-Display Composition

In this paper, we map out the CoCe design space - a design space for co-located collaborative games that use multi-display composition. The design space grew out of the analysis of game instances based on the 4in1 concept. First, we did a horizontal analysis of 16 game instances with 31 corresponding gameplay design patterns (GDP), followed by a vertical analysis of 89 GDPs occurring in the description of the GDP Cooperation. Through inductive analysis, we have identified four perspectives with corresponding dimensions that span the CoCe design space. By applying the CoCe design space with game instances, we illustrate how it can be used both as an analytic tool for analysis of games and also as a generative tool in the design or re-design of cooperative games that use multi-display composition.
Troubling Care: Four Orientations for Wickedness in Design

Tensions in designing for care are often positioned as conflicts to be resolved. We draw upon queer theories to investigate caring for loved ones as not ”in-line” with normative expectations of care as positive and fulfilling. Through the critique of two autobiographical design projects designed for informal, everyday care of our families, we describe four troubling orientations of care: willful detours, selfish shortcuts, naughty invasions, and unhappy departures. From these, we argue that tensions in care may not always be designed against, but can also be desired and generative. We conclude by discussing a ”wickedness” in caring for loved ones that problematizes in-home technologies as attractively naughty and potentially violent, and the four orientations as resources for interaction designers to spatially navigate tensions of domestic care.
Data-based polyhedron model for optimization of engineering structures involving uncertainties

Abstract This paper studies the data-based polyhedron model and its application in uncertain linear optimization of engineering structures, especially in the absence of information either on probabilistic properties or about membership functions in the fussy sets-based approach, in which situation it is more appropriate to quantify the uncertainties by convex polyhedra. Firstly, we introduce the uncertainty quantification method of the convex polyhedron approach and the model modification method by Chebyshev inequality. Secondly, the characteristics of the optimal solution of convex polyhedron linear programming are investigated. Then the vertex solution of convex polyhedron linear programming is presented and proven. Next, the application of convex polyhedron linear programming in the static load-bearing capacity problem is introduced. Finally, the effectiveness of the vertex solution is verified by an example of the plane truss bearing problem, and the efficiency is verified by a load-bearing problem of stiffened composite plates.
New intranasal and injectable gene therapy for healthy life extension

As the global elderly population grows, it is socioeconomically and medically critical to have diverse and effective means of mitigating the impact of aging on human health. Previous studies showed that adenovirus-associated virus (AAV) vector induced overexpression of certain proteins can suppress or reverse the effects of aging in animal models. Here, we sought to determine whether the high-capacity cytomegalovirus vector can be an effective and safe gene delivery method for two such-protective factors: telomerase reverse transcriptase (TERT) and follistatin (FST). We found that the mouse cytomegalovirus (MCMV) carrying exogenous TERT or FST (MCMVTERT or MCMVFST) extended median lifespan by 41.4% and 32.5%, respectively. This is the first report of CMV being used successfully as both an intranasal and injectable gene therapy system to extend longevity. Treatment significantly improved glucose tolerance, physical performance, and prevented loss of body mass and alopecia. Telomere shortening seen with aging was ameliorated by TERT, and mitochondrial structure deterioration was halted in both treatments. Intranasal and injectable preparations performed equally well in safely and efficiently delivering gene therapy to multiple organs, with long-lasting benefits and without carcinogenicity or unwanted side effects. Translating this research to humans could have significant benefits associated with increased health span.
On the neuronal dynamics of aesthetic experience: Evidence from electroencephalographic oscillatory dynamics

Aesthetic experiences have an influence on many aspects of life. Interest in the neural basis of aesthetic experiences has grown rapidly in the past decade, and fMRI studies have identified several brain systems supporting aesthetic experiences. Work on the rapid neuronal dynamics of aesthetic experience, however, is relatively scarce. The present study adds to this field by investigating the experience of being aesthetically moved by means of ERP and time-frequency analysis. Participants’ EEG was recorded while they viewed a diverse set of artworks and evaluated the extent to which these artworks moved them. Results show that being aesthetically moved is associated with a sustained increase in gamma activity over centroparietal regions. Also, alpha power over right frontocentral regions was reduced in high and low moving images, compared to artworks given intermediate ratings. We interpret the gamma effect as an indication for sustained savoring processes for aesthetically moving artworks compared to aesthetically less moving artworks. The alpha effect is interpreted as an indication of increased attention for aesthetically salient images. In contrast to previous works, we observed no significant effects in any of the established ERP components, but we did observe effects at latencies longer than 1 s. We conclude that EEG time-frequency analysis provides useful information on the neuronal dynamics of aesthetic experience.
Gymnasts’ ability to modulate bioelectric sensorimotor rhythms during kinesthetic motor imagery of sports non-specific movements

Previous psychological studies using questionnaires have consistently reported that athletes have superior motor imagery ability, both for sports-specific and sports non-specific movements. However, regarding motor imagery of sports non-specific movements, no physiological studies have demonstrated differences in neural activity between athletes and non-athletes. The purpose of the present study was to examine differences in bioelectric sensorimotor rhythms during kinesthetic motor imagery (KMI) of sports non-specific movements between gymnasts and non-gymnasts. We selected gymnasts as an example population because they are likely to have particularly superior motor imagery ability due to frequent usage of motor imagery including KMI as part of daily practice. Healthy young participants (16 gymnasts and 16 non-gymnasts) performed repeated motor execution and KMI of sports non-specific movements (wrist dorsiflexion and shoulder abduction of the dominant hand). Scalp electroencephalogram (EEG) was recorded over the contralateral sensorimotor cortex. During motor execution and KMI, sensorimotor EEG power is known to decrease in the α- (8–15 Hz) and β-bands (16–35 Hz), referred to as event-related desynchronization (ERD). We calculated the maximal peak of ERD both in the α- (αERDmax) and β-bands (βERDmax) as a measure of changes in corticospinal excitability. αERDmax was significantly greater in gymnasts, who subjectively evaluated their KMI as being more vivid, for both KMI tasks. On the other hand, βERDmax was greater in gymnasts only for shoulder abduction KMI. These findings suggest gymnasts’ signature of flexibly modulating sensorimotor rhythm with no movements, which may be the basis of their superior ability of KMI for sports non-specific movements. New & Noteworthy Kinesthetic motor imagery of sports non-specific movements was compared between gymnasts and non-gymnasts (i.e., healthy controls) from both physiological and psychological approaches. The EEG sensorimotor rhythms during kinesthetic motor imagery were more desynchronized in gymnasts who subjectively imaged their own movements as being more vivid. The work reveals novel ability in gymnasts to flexibly control their sensorimotor rhythms with no actual movements, which would be the basis of their superior ability of motor imagery.
The Embodiment of Power as Forward/Backward Movement in Chinese and English Speakers

ABSTRACT In two experiments, we examined whether POWER is embodied in terms of horizontal forward and backward movement using an action compatibility task. Participants were asked to categorize power-related words (e.g., “boss”, “intern”) aseither “powerful” or “powerless” as quickly and accurately as possible. In the compatible condition, the response to indicate that the word was “powerful” involved a forward movement and the response to indicate “powerless” involved a backward movement. Under incompatible conditions, these responses were reversed (“powerful”-backward/“powerless”-forward). In both experiments, participants were faster to categorize the words when the response actions were compatible than incompatible. Furthermore, this compatibility effect was observed for both Chinese (Mandarin) speakers categorizing Chinese words and English speakers categorizing English words. These data suggest that the psychological reality of a “POWER IS MOVING FORWARD” conceptual metaphor in both language groups, which we argue is based on an extension of the “SOURCE-PATH-GOAL” schema.
Thin-Film Deposition and Characterization of a Sn-Deficient Perovskite Derivative Cs2SnI6

In this work, we describe details of a two-step deposition approach that enables the preparation of continuous and well-structured thin films of Cs2SnI6, which is a one-half Sn-deficient 0-D perovskite derivative (i.e., the compound can also be written as CsSn0.5I3, with a structure consisting of isolated SnI64– octahedra). The films were characterized using powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), UV–vis spectroscopy, photoluminescence (PL), photoelectron spectroscopy (UPS, IPES, XPS), and Hall effect measurements. UV–vis and PL measurements indicate that the obtained Cs2SnI6 film is a semiconductor with a band gap of 1.6 eV. This band gap was further confirmed by the UPS and IPES spectra, which were well reproduced by the calculated density of states with the HSE hybrid functional. The Cs2SnI6 films exhibited n-type conduction with a carrier density of 6(1) × 1016 cm–3 and mobility of 2.9(3) cm2/V·s. While the computationally derived band str.
Identifying Sources of Faecal Contamination in a Small Urban Stream Catchment: A Multiparametric Approach

Small urban streams discharging in the proximity of bathing waters may significantly contribute to the deterioration of water quality, yet their impact may be overlooked. This study focuses on the Elm Park stream in the city of Dublin that is subject to faecal contamination by unidentified sources. The aim of the study was to identify a minimum number of “sentinel” sampling stations in an urban catchment that would provide the maximum amount of information regarding faecal pollution in the catchment. Thus, high-resolution sampling within the catchment was carried out over the course of 1 year at 11 stations. Faecal indicator bacteria were enumerated and microbial source tracking (MST) was employed to evaluate human pollution. In addition, ammonium, total oxidised nitrogen, and phosphorus levels were monitored to determine if these correlated with faecal indicator and the HF183 MST marker. In addition, the effect of severe weather events on water quality was assessed using automated sampling at one of the identified “sentinel” stations during baseflow and high flow conditions over a 24-h period. Our results show that this urban stream is at times highly contaminated by point source faecal pollution and that human faecal pollution is pervasive in the catchment. Correlations between ammonium concentrations and faecal indicator bacteria (FIB) as well as the human MST marker were observed during the study. Cluster analysis identified four “sentinel” stations that provide sufficient information on faecal pollution in the stream, thus reducing the geographical complexity of the catchment. Furthermore, ammonium levels strongly correlated with FIB and the human HF183 MST marker under high flow conditions at key “sentinel” stations. This work demonstrates the effectiveness of pairing MST, faecal indicators, and ammonium monitoring to identify “sentinel” stations that could be more rapidly assessed using real-time ammonium readouts to assess remediation efforts.