Miracle-dz/UniFAR-FTUs huggingface dataset:
IdleBot: Exploring the Design of Serendipitous Artifacts

We are increasingly surrounded by interactive, connected and engaging "things" that demand attention and convey a sense of continuous pace into our personal spaces. In this work, we explore how things could be designed from this opposite perspective: seemingly aware, but non-engaging. IdleBot is a very furry robotic puppet that is waiting. Unlike many applications in social robotics, IdleBot has neither clear purpose, nor explicit functionality--it merely exists and waits. The subtleness of its interaction, consisting of mostly idle motion, is the starting point to investigate forms of interaction bordering non-interaction situated in a personal context. Using data about human waiting behavior from an observational study, we designed a fully working prototype in two design iterations that embodies different modes of waiting and evaluated this design for its effect and acceptance of idle motions in context.
Neural Disease Named Entity Extraction with Character-based BiLSTM+CRF in Japanese Medical Text

We propose an 'end-to-end' character-based recurrent neural network that extracts disease named entities from a Japanese medical text and simultaneously judges its modality as either positive or negative; i.e., the mentioned disease or symptom is affirmed or negated. The motivation to adopt neural networks is to learn effective lexical and structural representation features for Entity Recognition and also for Positive/Negative classification from an annotated corpora without explicitly providing any rule-based or manual feature sets. We confirmed the superiority of our method over previous char-based CRF or SVM methods in the results.
Size–strain separation in diffraction line profile analysis

Separation of size and strain effects on diffraction line profiles has been studied in a round robin involving laboratory instruments and synchrotron radiation beamlines operating with different radiation, optics, detectors and experimental configurations. The studied sample, an extensively ball milled iron alloy powder, provides an ideal test case, as domain size broadening and strain broadening are of comparable size.
Retrieval on source code: a neural code search

Searching over large code corpora can be a powerful productivity tool for both beginner and experienced developers because it helps them quickly find examples of code related to their intent. Code search becomes even more attractive if developers could express their intent in natural language, similar to the interaction that Stack Overflow supports. In this paper, we investigate the use of natural language processing and information retrieval techniques to carry out natural language search directly over source code, i.e. without having a curated Q&A forum such as Stack Overflow at hand. Our experiments using a benchmark suite derived from Stack Overflow and GitHub repositories show promising results. We find that while a basic word–embedding based search procedure works acceptably, better results can be obtained by adding a layer of supervision, as well as by a customized ranking strategy.
Overload Control for Scaling WeChat Microservices

Effective overload control for large-scale online service system is crucial for protecting the system backend from overload. Conventionally the design of overload control is ad-hoc for individual service. However, service-specific overload control could be detrimental to the overall system due to intricate service dependencies or flawed implementation of service. Service developers usually have difficulty to accurately estimate the dynamics of actual workload during the development of service. Therefore, it is essential to decouple the overload control from service logic. In this paper, we propose DAGOR, an overload control scheme designed for the account-oriented microservice architecture. DAGOR is service agnostic and system-centric. It manages overload at the microservice granule such that each microservice monitors its load status in real time and triggers load shedding in a collaborative manner among its relevant services when overload is detected. DAGOR has been used in the WeChat backend for five years. Experimental results show that DAGOR can benefit high success rate of service even when the system is experiencing overload, while ensuring fairness in the overload control.
Conditional Noise-Contrastive Estimation of Unnormalised Models

Many parametric statistical models are not properly normalised and only specified up to an intractable partition function, which renders parameter estimation difficult. Examples of unnormalised models are Gibbs distributions, Markov random fields, and neural network models in unsupervised deep learning. In previous work, the estimation principle called noise-contrastive estimation (NCE) was introduced where unnormalised models are estimated by learning to distinguish between data and auxiliary noise. An open question is how to best choose the auxiliary noise distribution. We here propose a new method that addresses this issue. The proposed method shares with NCE the idea of formulating density estimation as a supervised learning problem but in contrast to NCE, the proposed method leverages the observed data when generating noise samples. The noise can thus be generated in a semi-automated manner. We first present the underlying theory of the new method, show that score matching emerges as a limiting case, validate the method on continuous and discrete valued synthetic data, and show that we can expect an improved performance compared to NCE when the data lie in a lower-dimensional manifold. Then we demonstrate its applicability in unsupervised deep learning by estimating a four-layer neural image model.
Lecture capture use in engineering education: Influence of students’ social and behavioral factors and teachers’ perceptions

This paper discusses the influence of students’ social and behavioral features on lecture capture use in the learning of engineering courses, as well as teachers’ perceptions of pedagogical changes and students’ performance. Results show that the students’ perceptions about lecture capture are highly positive in terms of improving learning and academic performance. With respect to behavioral factors like attention deficit, the study suggests that a significant number of students having difficulties in maintaining attention during lectures and rely on lecture capture for further understanding. With respect to social factors, variation in the use of lecture capture has also been observed between native and non‐native English speaking students, and in students with different levels of past experience in using lecture capture. Lecturers of these engineering courses have expressed optimism about using lecture capture, and have raised concerns about restrictive teaching styles, and the requirement for technological improvements and adequate training.
Enhancing computation-to-core assignment with physical location information

Going beyond a certain number of cores in modern architectures requires an on-chip network more scalable than conventional buses. However, employing an on-chip network in a manycore system (to improve scalability) makes the latencies of the data accesses issued by a core non-uniform. This non-uniformity can play a significant role in shaping the overall application performance. This work presents a novel compiler strategy which involves exposing architecture information to the compiler to enable an optimized computation-to-core mapping. Specifically, we propose a compiler-guided scheme that takes into account the relative positions of (and distances between) cores, last-level caches (LLCs) and memory controllers (MCs) in a manycore system, and generates a mapping of computations to cores with the goal of minimizing the on-chip network traffic. The experimental data collected using a set of 21 multi-threaded applications reveal that, on an average, our approach reduces the on-chip network latency in a 6×6 manycore system by 38.4% in the case of private LLCs, and 43.8% in the case of shared LLCs. These improvements translate to the corresponding execution time improvements of 10.9% and 12.7% for the private LLC and shared LLC based systems, respectively.
Syntactic word embedding based on dependency syntax and polysemous analysis

Most word embedding models have the following problems: (1) In the models based on bag-of-words contexts, the structural relations of sentences are completely neglected; (2) Each word uses a single embedding, which makes the model indiscriminative for polysemous words; (3) Word embedding easily tends to contextual structure similarity of sentences. To solve these problems, we propose an easy-to-use representation algorithm of syntactic word embedding (SWE). The main procedures are: (1) A polysemous tagging algorithm is used for polysemous representation by the latent Dirichlet allocation (LDA) algorithm; (2) Symbols ‘+’ and ‘−’ are adopted to indicate the directions of the dependency syntax; (3) Stopwords and their dependencies are deleted; (4) Dependency skip is applied to connect indirect dependencies; (5) Dependency-based contexts are inputted to a word2vec model. Experimental results show that our model generates desirable word embedding in similarity evaluation tasks. Besides, semantic and syntactic features can be captured from dependency-based syntactic contexts, exhibiting less topical and more syntactic similarity. We conclude that SWE outperforms single embedding learning models.
Part-of-Speech Tagging on an Endangered Language: a Parallel Griko-Italian Resource

Most work on part-of-speech (POS) tagging is focused on high resource languages, or examines low-resource and active learning settings through simulated studies. We evaluate POS tagging techniques on an actual endangered language, Griko. We present a resource that contains 114 narratives in Griko, along with sentence-level translations in Italian, and provides gold annotations for the test set. Based on a previously collected small corpus, we investigate several traditional methods, as well as methods that take advantage of monolingual data or project cross-lingual POS tags. We show that the combination of a semi-supervised method with cross-lingual transfer is more appropriate for this extremely challenging setting, with the best tagger achieving an accuracy of 72.9%. With an applied active learning scheme, which we use to collect sentence-level annotations over the test set, we achieve improvements of more than 21 percentage points.
Musical trends and predictability of success in contemporary songs in and out of the top charts

We analyse more than 500 000 songs released in the UK between 1985 and 2015 to understand the dynamics of success (defined as ‘making it’ into the top charts), correlate success with acoustic features and explore the predictability of success. Several multi-decadal trends have been uncovered. For example, there is a clear downward trend in ‘happiness’ and ‘brightness’, as well as a slight upward trend in ‘sadness’. Furthermore, songs are becoming less ‘male’. Interestingly, successful songs exhibit their own distinct dynamics. In particular, they tend to be ‘happier’, more ‘party-like’, less ‘relaxed’ and more ‘female’ than most. The difference between successful and average songs is not straightforward. In the context of some features, successful songs pre-empt the dynamics of all songs, and in others they tend to reflect the past. We used random forests to predict the success of songs, first based on their acoustic features, and then adding the ‘superstar’ variable (informing us whether the song’s artist had appeared in the top charts in the near past). This allowed quantification of the contribution of purely musical characteristics in the songs’ success, and suggested the time scale of fashion dynamics in popular music.
Deleting Death and Dialysis: Conservative Care of Cardio-Vascular Risk and Kidney Function Loss in Chronic Kidney Disease (CKD)

The uremic syndrome, which is the clinical expression of chronic kidney disease (CKD), is a complex amalgam of accelerated aging and organ dysfunctions, whereby cardio-vascular disease plays a capital role. In this narrative review, we offer a summary of the current conservative (medical) treatment options for cardio-vascular and overall morbidity and mortality risk in CKD. Since the progression of CKD is also associated with a higher cardio-vascular risk, we summarize the interventions that may prevent the progression of CKD as well. We pay attention to established therapies, as well as to novel promising options. Approaches that have been considered are not limited to pharmacological approaches but take into account lifestyle measures and diet as well. We took as many randomized controlled hard endpoint outcome trials as possible into account, although observational studies and post hoc analyses were included where appropriate. We also considered health economic aspects. Based on this information, we constructed comprehensive tables summarizing the available therapeutic options and the number and kind of studies (controlled or not, contradictory outcomes or not) with regard to each approach. Our review underscores the scarcity of well-designed large controlled trials in CKD. Nevertheless, based on the controlled and observational data, a therapeutic algorithm can be developed for this complex and multifactorial condition. It is likely that interventions should be aimed at targeting several modifiable factors simultaneously.
Sheep identity recognition, age and weight estimation datasets

Increased interest of scientists, producers and consumers in sheep identification has been stimulated by the dramatic increase in population and the urge to increase productivity. The world population is expected to exceed 9.6 million in 2050. For this reason, awareness is raised towards the necessity of effective livestock production. Sheep is considered as one of the main of food resources. Most of the research now is directed towards developing real time applications that facilitate sheep identification for breed management and gathering related information like weight and age. Weight and age are key matrices in assessing the effectiveness of production. For this reason, visual analysis proved recently its significant success over other approaches. Visual analysis techniques need enough images for testing and study completion. For this reason, collecting sheep images database is a vital step to fulfill such objective. We provide here datasets for testing and comparing such algorithms which are under development. Our collected dataset consists of 416 color images for different features of sheep in different postures. Images were collected fifty two sheep at a range of year from three months to six years. For each sheep, two images were captured for both sides of the body, two images for both sides of the face, one image from the top view, one image for the hip and one image for the teeth. The collected images cover different illumination, quality levels and angle of rotation. The allocated data set can be used to test sheep identification, weigh estimation, and age detection algorithms. Such algorithms are crucial for disease management, animal assessment and ownership.
Aging male symptoms: the relationship between physical activity and quality of life

Objective To examine the relationship between physical activity (PA) and the aging male symptoms of middle-aged men in the quality of life (QOL). Methodology: Cross-sectional study with a probabilistic samples of 416 men (40-59 years old), all residents in two cities in southern of Brazil. A questionnaire was used. The studied population was divided into two groups: with and without symptoms. The analyses were carried out in a descriptive and inferential approaches. Results: Aging male symptoms were related to QOL. Men who perceive their overall QOL as good presented a13% lower probability of (95%CI = 0.77-0.98) being insufficiently active. For those with symptoms, QOL scores were higher in social and environmental domain in PA between 30-60 min/day, and the physical domain for more than 60min/day. Conclusion: Our findings show the importance of PA to achieve significant benefits in QOL and health of men in middle age with aging male symptoms.
Textile-Based Flexible Coils for Wireless Inductive Power Transmission

This data set includes the data used for following plots in paper Smart Textile Based Flexible Coils for Wireless Inductive Power Transmission.Fig. 3. Unloaded Q factor versus the turns of spiral coil for a coil design that has 138 mm external diameter, 53 mm inner diameter, and is printed with a conductive paste which has 24 m? /? sheet resistance.Fig. 6. Normalized DC resistance versus curing time for conductive tracks with different number of sub-layers printed on interface-coated textile. The conductive paste is cured after 40 minutes 130 °C thermal curing.Fig. 7. Thickness and practical DC resistance of printed conductive layer as designed coil compared with theoretical DC resistance in different number of sub-layers and thickness.Fig. 9. Impedance phase angle of different type of coils on frequency range from 300 kHz to 50 MHz. The self-resonant frequency can be located from this measurement as 10.3 MHz and 17.6 MHz for wound copper coil and flexible coils, respectively.Fig. 10. Coupling factor k of different type of coupled coils against distance between them compared with the theoretical calculations.Fig. 11. Output powers of wireless power transfer system deployed with different type of coupled coils against output DC current at 5 mm and 10 mm separation between transmitter and receiver coils. An approximate 1.51 W output power can be achieved for all types of coils at 5 mm separation, and 9 % less output power, 1.37 W, can be achieved at 10 mm separation.Fig. 12. DC to DC efficiency at optimal output current against separation distance between different types of paired coils. The same trends of the effect of separation on DC to DC efficiency are shown on all types of coils.Fig. 13. Maximum output power and DC to DC efficiency of WPT employed flexible coils with varying curvature of receiver coil at 5 mm center separation distance from transmitter coil. The maximum output power drops 33 % as a result of the deformation of the receiver coil.Fig. 14. DC to DC efficiency of the WPT system employing a deformed receiver coil under different curvature against the separation distance from the flat transmitter coil.Assigned DOI: 10.5258/SOTON/376588
On the Effects of Ethical Climate(s) on Employees’ Behavior: A Social Identity Approach

The spread and publicity given to questionable practices in the corporate world during the last two decades have fostered an increasing interest about the importance of ethical work for organizations, practitioners, scholars and, last but not least, the wider public. Relying on the Social Identity Approach, we suggest that the effects of different ethical climates on employee behaviors are driven by affective identification with the organization and, in parallel, by cognitive moral (dis)engagement. We compared the effects of two particular ethical climates derived from the literature: An ethical organizational climate of self-interest, and an ethical organizational climate of friendship. Three hundred seventy-six workers completed measures of Ethical Climate, Organizational Identification, Moral Disengagement, Organizational Citizenship Behaviors (OCBs), and Counterproductive Work Behaviors (CWBs). Structural equation modeling confirmed that the two ethical climates considered were independently related to organizational identification and moral disengagement. These, in turn, mediated the effects of ethical climates on OCBs and CWBs. We discuss results in light of the social identity approach, and present some practical implications of our findings.
The 3’UTRs of Myelin Basic Protein mRNAs Regulate Transport, Local Translation and Sensitivity to Neuronal Activity in Zebrafish

Formation of functional myelin sheaths within the central nervous system depends on expression of myelin basic protein (MBP). Following process extension and wrapping around axonal segments, this highly basic protein is required for compaction of the multi-layered membrane sheath produced by oligodendrocytes. MBP is hypothesized to be targeted to the membrane sheath by mRNA transport and local translation, which ensures that its expression is temporally and spatially restricted. The mechanistic details of how this might be regulated are still largely unknown, in particular because a model system that allows this process to be studied in vivo is lacking. We here show that the expression of the zebrafish MBP orthologs, mbpa and mbpb, is developmentally regulated, and that expression of specific mbpa isoforms is restricted to the peripheral nervous system. By analysis of transgenic zebrafish, which express a fluorescent reporter protein specifically in myelinating oligodendrocytes, we demonstrate that both mbpa and mbpb include a 3’UTR sequence, by which mRNA transport and translation is regulated in vivo. Further functional analysis suggests that: (1) the 3’UTRs delay the onset of protein expression; and that (2) several regulatory elements contribute to targeting of the mbp mRNA to the myelin sheath. Finally, we show that a pharmacological compound known to enhance neuronal activity stimulates the translation of Mbp in zebrafish in a 3’UTR-dependent manner. A similar effect was obtained following stimulation with a TrkB receptor agonist, and cell-based assays further confirmed that the receptor ligand, BDNF, in combination with other signals reversed the inhibitory effect of the 3’UTR on translation.
Specifying system requirements for memory consistency models

The memory consistency model of a shared-memory system determines the order in which memory accesses can be executed by the system, and greatly a ects the implementation and performance of the system. To aid system designers, memory models either directly specify, or are accompanied by, a set of low-level system conditions that can be easily translated into a correct implementation. These su cient conditions play a key role in helping the designer determine the architecture and compiler optimizations that may be safely exploited under a speci c model. Therefore, these conditions should obey three important properties. First, they should be unambiguous. Second, they should be feasibly aggressive; i.e., they should not prohibit practical optimizations that do not violate the semantics of the model. Third, it should be relatively straightforward to convert the conditions into e cient implementations, and conversely, to verify if an implementation obeys the conditions. Most previous approaches in specifying system requirements for a model are lacking in at least one of the above aspects. This paper presents a methodology for specifying the system conditions for a memory model that satis es the above goals. A key attribute of our methodology is the exclusion of ordering constraints among memory operations to di erent locations by observing that such constraints are unnecessary for maintaining the semantics of a model. To demonstrate the exibility of our approach, we specify the conditions for several proposed memory models within this framework. Compared to the original speci cation for each model, the new speci cation allows more optimizations without violating the original semantics and, in many cases, is more precise. The Stanford University authors are supported by DARPA contract N00039-91-C-0138. Anoop Gupta is partly supported by a NSF Presidential Young Investigator Award. The University of Wisconsin authors are supported in part by a National Science Foundation Presidential Young Investigator Award (MIPS-8957278) with matching funds from A.T. & T. Bell Laboratories, Cray Research Foundation and Digital Equipment Corporation. Sarita Adve is also supported by an IBM graduate fellowship.