Miracle-dz/UniFAR-FTUs huggingface dataset:
Kalman-Filter-Based Walking Distance Estimation for a Smart-Watch

A novel walking distance estimation algorithm using the inertial sensors of the smart-watch is proposed. Firstly, the peaks of the norm of the accelerometer and gyroscope signals are detected. Due to arm swing, walking step detection using these peaks are not reliable. A Kalman filter is used to combine with the peak detection algorithm applied on the accelerometer and gyroscope norm peaks and robustly detect walking steps even if there is large arm swing. Walking distance is estimated using walking step time and walking length relationship. The proposed algorithm was tested on 25 subjects: each subject walked 50 m six times with different walking speed and different arm swing speed. The standard deviation of walking distance estimation error is 3.9 m (without person dependent calibration) and 1.9 m (with person dependent calibration) for a 50m distance.
Effects of EPG treatment for English consonant contrasts on L2 perception and production

Links between perception and production were investigated for two adult native speakers of Korean who participated in electropalatographic (EPG) treatment designed to teach phonological and articulatory contrasts between English /s/ - /ʃ/, /z/ - /ʤ/, and /l/ - /ɹ/. Participants were successful in learning to produce the English contrasts. Perception of English consonants was tested pre- and post-treatment. Post-treatment perception improved somewhat for treated consonants but not for untreated consonants, although perception was not directly trained.
Anxiety, restraint, and eating behavior.

It was hypothesized that individual differences in eating behavior based on the distinction between obese and normal subjects could be demonstrated within a population of normal subjects classified as to the extent of restraint chronically exercised with respect to eating. Restrained subjects resembled the obese behaviorally, and unrestrained subjects resembled normals. This demonstration was effected in the context of a test . of the psychosomatic hypothesis of obesity. The results indicated that although some individuals may eat more when anxious, there is little empirical support for the notion that eating serves to reduce anxiety. An explanation for this apparent inconsistency was offered. The role of anxiety as a possible causal agent in obesity has recently been subjected to experimental analysis. Schachter, Goldman, and Gordon (1968) hypothesized that although anxiety would decrease eating in normal-weight subjects by inhibiting gastric contractions and releasing sugar into the bloodstream, it would have little if any effect on the obese, who do not eat on the basis of internal physiological state. These predictions were confirmed, with normal-weight subjects eating substantially less (34%) when anxious and the obese eating nonsignificantly more (15%). Schachter et al. (1968) concluded that the psychosomatic hypothesis of obesity —that the obese in effect confuse hunger with negative affect (Bruch, 1961) and thus overeat in response to aversive emotional states (Kaplan & Kaplan, 1957)— had failed to find confirmation. Obese subjects did not eat more when anxious and did not exhibit significant anxiety reduction as a consequence of eating.
Time for Break: Understanding Information Workers' Sedentary Behavior Through a Break Prompting System

Extended periods of uninterrupted sedentary behavior are detrimental to long-term health. While prolonged sitting is prevalent among information workers, it is difficult for them to break prolonged sedentary behavior due to the nature of their work. This work aims to understand information workers' intentions & practices around standing or moving breaks. We developed Time for Break, a break prompting system that enables people to set their desired work duration and prompts them to stand up or move. We conducted an exploratory field study (N = 25) with Time for Break to collect participants' work & break intentions and behaviors for three weeks, followed by semi-structured interviews. We examined rich contexts affecting participants' receptiveness to standing or moving breaks, and identified how their habit strength and self-regulation are related to their break-taking intentions & practices. We discuss design implications for interventions to break up periods of prolonged sedentary behavior in workplaces.
Adaptive vector quantization for picture coding using neural networks

The paper presents applications of neural network algorithms to the design of an adaptive vector quantizer. Vector quantization has been applied to the problem of displaying natural images with a reduced set of colors (colormap) and to the interframe coding of image sequences. The first step was to test classical Linde Buzo Gray (LGB), self organizing feature maps (SOFM) and Competitive Learning (CL) algorithms for the codebook design. The best results for the reconstructed quality image and the computational time are obtained using a CL algorithm with a new initialization strategy that solves the problem of underutilized nodes. An adaptive vector quantization algorithm is proposed and tested in a motion compensated image coder. The results of the simulations are very promising. In fact the coder performance, compared with that using a fixed VQ, is considerably improved and the subjective quality of the coded images is much better than that obtained using standard vector quantization, especially when rapid motion is present in the scene. >
Fine Dissection of Human Mitochondrial DNA Haplogroup HV Lineages Reveals Paleolithic Signatures from European Glacial Refugia

Genetic signatures from the Paleolithic inhabitants of Eurasia can be traced from the early divergent mitochondrial DNA lineages still present in contemporary human populations. Previous studies already suggested a pre-Neolithic diffusion of mitochondrial haplogroup HV*(xH,V) lineages, a relatively rare class of mtDNA types that includes parallel branches mainly distributed across Europe and West Asia with a certain degree of structure. Up till now, variation within haplogroup HV was addressed mainly by analyzing sequence data from the mtDNA control region, except for specific sub-branches, such as HV4 or the widely distributed haplogroups H and V. In this study, we present a revised HV topology based on full mtDNA genome data, and we include a comprehensive dataset consisting of 316 complete mtDNA sequences including 60 new samples from the Italian peninsula, a previously underrepresented geographic area. We highlight points of instability in the particular topology of this haplogroup, reconstructed with BEAST-generated trees and networks. We also confirm a major lineage expansion that probably followed the Late Glacial Maximum and preceded Neolithic population movements. We finally observe that Italy harbors a reservoir of mtDNA diversity, with deep-rooting HV lineages often related to sequences present in the Caucasus and the Middle East. The resulting hypothesis of a glacial refugium in Southern Italy has implications for the understanding of late Paleolithic population movements and is discussed within the archaeological cultural shifts occurred over the entire continent.
The UV-B Photoreceptor UVR8: From Structure to Physiology

Low doses of UV-B light (280 to 315 nm) elicit photomorphogenic responses in plants that modify biochemical composition, photosynthetic competence, morphogenesis, and defense. UV RESISTANCE LOCUS8 (UVR8) mediates photomorphogenic responses to UV-B by regulating transcription of a set of target genes. UVR8 differs from other known photoreceptors in that it uses specific Trp amino acids instead of a prosthetic chromophore for light absorption during UV-B photoreception. Absorption of UV-B dissociates the UVR8 dimer into monomers, initiating signal transduction through interaction with CONSTITUTIVELY PHOTOMORPHOGENIC1. However, much remains to be learned about the physiological role of UVR8 and its interaction with other signaling pathways, the molecular mechanism of UVR8 photoreception, how the UVR8 protein initiates signaling, how it is regulated, and how UVR8 regulates transcription of its target genes.
Effects of Viewing Multiple Viewpoint Videos on Metacognition of Collaborative Experiences

This paper discusses the effects of multiple viewpoint videos for metacognition of experiences. We present a system for recording multiple users' collaborative experiences by wearable and environmental sensors, and another system for viewing multiple viewpoint videos automatically identified and extracted to associate to individual users. We designed an experiment to compare the metacognition of one's own experience between those based on memory and those supported by video viewing. The experimental results show that metacognitive descriptions related to one's own mind, such as feelings and preferences, are possible regardless whether a person is viewing videos, but such episodic descriptions as the content of someone's utterance and what s/he felt associated with it are strongly promoted by video viewing. We conducted another experiment where the same participants did identical metacognitive description tasks about half a year after the previous experiment. Through the experiments, we found the first-person view video is mostly used for confirming the episodic facts immediately after the experience, whereas after half a year, even one's own experience is often felt like the experiences of others therefore the videos capturing themselves from the conversation partners and environment become important for thinking back to the situations where they were placed.
ShadowGC: Cooperative garbage collection with multi-level buffer for performance improvement in NAND flash-based SSDs

Garbage collection, an essential background activity in NAND flash based SSDs, often introduces large runtime overhead. Recent studies showed that it is beneficial to separate the flash pages that have dirty copies in the write buffers from those that do not. However, the existing schemes exploring this observation have limitations, which prevent them from maximizing the performance improvement. In this paper, we address the above challenge through ShadowGC, a novel GC design that exploits the pages in both host-side and device-side write buffers and adopts different read and write strategies to minimize the GC overhead. When garbage collecting flash pages that have dirty copies in the device-side write buffer, ShadowGC reads data from the write buffer. When garbage collecting flash pages that have dirty copies in the host-side write buffer, ShadowGC moves them to dedicated blocks and speeds up the movement with fast-write operations. Our experimental results show that, on average, ShadowGC reduces the write amplification by 16.2% and the GC latency by 20.5% over the state-of-the-art.
Interaction Restraint: Enforcing Adaptive Cognitive Tasks to Restrain Problematic User Interaction

We propose an interaction restraint that aims to degrade interactivity of a device, for example, by asking users to perform a mandatory cognitive task whenever they start an interaction. This mechanism is designed to help users to self-reflect upon their interaction intent with the devices, and thus they can break the habit of unconscious frequent access to their smartphones. We perform a preliminary study to understand the design requirements of the cognitive tasks and develop a high-fidelity prototype. Our field trial clearly documents that a positive influence of interaction restraints on deterring habitual frequent use of smartphones.
A self-sufficient solar powered SRM driven irrigation pump utilizing modified Zeta converter

This paper aims at developing an inexpensive autonomous photovoltaic (PV) array fed irrigation pump utilizing the switched reluctance motor (SRM) drive. A modified Zeta converter is utilized between PV array and motor-pump to incorporate power conditioning. Its continuous conduction mode (CCM) operation helps to reduce the stress on its devices and also the size of PV capacitor. A Perturb and observe (P &O) maximum power point tracking (MPPT) control algorithm is used to maximize the power output of the PV array. DC link voltage is kept variable which allows reduction of sensors. The fundamental switching of mid-point converter improves the efficiency of the system. The suggested system is premeditated in MATLB and further confirmed with hardware implementation. The simulated and hardware results under varying environmental conditions testify the utility and worthiness of proposed system for irrigation pumps.
Privacy and personalization

I N T E R A C T I O N S . A C M . O R G I HOW IT ALL STARTED December 2016, 10 months before the field trip Our identities are complemented by a virtual counterpart, consisting of diverse social network profiles and a data footprint most of us leave when we are online. This accumulation of personal information is used to tailor the content or functionality of Web pages to our preferences, interests, knowledge, and other personal traits. The concept behind this adaptation, or personalization, is simple: Messages, objects, and experiences that we attribute to our self affirm our identity and differentiate us from others. As a In September 2017, we had the chance to conduct a two-day field trip in Mumbai, India. This field trip provided us with a fresh perspective, inspiration, and great human encounters. With this article, we aim to provide insights and motivation, as well as details on planning and conducting an intercultural field trip for researchers considering a similar endeavor. We recount our experiences from the perspectives of both German and Indian participants, from the initial idea to planning and conducting the field trip in collaboration with locals. We also share our lessons and recommendations. Insights → In collaborative field research, very different perspectives might meet and challenge each other. → It takes close listening, open-mindedness, good preparation, and improvisation to set up a field trip in an unfamiliar context. Close collaboration with locals is invaluable. → Despite all preparation, be ready for surprises— and welcome them. PRIVACY AND PERSONALIZATION: THE STORY OF A CROSS-CULTURAL FIELD STUDY
Classification of text documents through distance measurement: An experiment with multi-domain Bangla text documents

This paper explores the use of two similarity measures for categorizing Bangla text documents into their respective domains. Cosine Similarity and Euclidean Distance have been usedasthe similarity measures on the vector space model based on TF-IDF feature. The domains of interest are Business, State, Medical, Sports, and Science texts which are used as inputs for analysis. The recognition accuracy of 95.80% for Cosine Similarity and 95.20% for Euclidean Distanceare achieved on 1000 text documents. This confirms that unsupervised feature extraction technique may be treated as one of the useful methods for automatic text classification in Bangla (and for other Indian language documents), if input texts are not pre-classified based on certain predefined linguistic or statistical parameters. Comparative experiments on the dataset using several classification algorithm show that the distance measures perform better compare to other classifiers.
Paragon: An Online Gallery for Enhancing Design Feedback with Visual Examples

Examples provide a source of inspiration for creating designs, but can they help improve the feedback process? Supplementing design feedback with examples could help recipients see issues clearly, identify concrete steps for improvement, and integrate novel ideas. Two online studies investigated how to support novices providing feedback on visual poster designs in an online context. Study One found that feedback providers select poster examples that complement their feedback and align with a provided rubric. Study Two shows that feedback providers give more specific, actionable, and novel input when using an example-centric approach, as opposed to text alone. To support this, we designed Paragon, an interface to efficiently browse examples using metadata. Finally, we discuss implications for collecting examples from the Web and structuring the design feedback process.
Deciphering hepatocellular carcinoma through metabolomics: from biomarker discovery to therapy evaluation

Hepatocellular carcinoma (HCC) is the third most common cause of death from cancer, with increasing prevalence worldwide. The mortality rate of HCC is similar to its incidence rate, which reflects its poor prognosis. At present, the diagnosis of HCC is still mostly dependent on invasive biopsy, imaging methods, and serum α-fetoprotein (AFP) testing. Because of the asymptomatic nature of early HCC, biopsy and imaging methods usually detect HCC at the middle–late stages. AFP has limited sensitivity and specificity, as many other nonmalignant liver diseases can also result in a very high serum level of AFP. Therefore, better biomarkers with higher sensitivity and specificity at earlier stages are greatly needed. Since metabolic reprogramming is an essential hallmark of cancer and the liver is the metabolic hub of living systems, it is useful to investigate HCC from a metabolic perspective. As a noninvasive and nondestructive approach, metabolomics provides holistic information on dynamically metabolic responses of living systems to both endogenous and exogenous factors. Therefore, it would be conducive to apply metabolomics in investigating HCC. In this review, we summarize recent metabolomic studies on HCC cellular, animal, and clinicopathologic models with attention to metabolomics as a biomarker in cancer diagnosis. Recent applications of metabolomics with respect to therapeutic and prognostic evaluation of HCC are also covered, with emphasis on the potential of treatment by drugs from natural products. In the last section, the current challenges and trends of future development of metabolomics on HCC are discussed. Overall, metabolomics provides us with novel insight into the diagnosis, prognosis, and therapeutic evaluation of HCC.
The influence of biogeographic history on the functional and phylogenetic diversity of passerine birds in savannas and forests of the Brazilian Amazon

Abstract Passeriformes is the largest and most diverse avian order in the world and comprises the Passeri and Tyranni suborders. These suborders constitute a monophyletic group, but differ in their ecology and history of occupation of South America. We investigated the influence of biogeographic history on functional and phylogenetic diversities of Passeri and Tyranni in forest and savanna habitats in the Brazilian Amazon. We compiled species composition data for 34 Passeriformes assemblages, 12 in savannas and 22 in forests. We calculated the functional (Rao's quadratic entropy, FDQ) and phylogenetic diversities (mean pairwise distance, MPD, and mean nearest taxon distance, MNTD), and the functional beta diversity to investigate the potential role of biogeographic history in shaping ecological traits and species lineages of both suborders. The functional diversity of Passeri was higher than for Tyranni in both habitats. The MPD for Tyranni was higher than for Passeri in forests; however, there was no difference between the suborders in savannas. In savannas, Passeri presented higher MNTD than Tyranni, while in forest areas, Tyranni assemblages showed higher MNTD than Passeri. We found a high functional turnover (~75%) between Passeri and Tyranni in both habitats. The high functional diversity of Passeri in both habitats is due to the high diversity of ecological traits exhibited by species of this group, which enables the exploitation of a wide variety of resources and foraging strategies. The higher Tyranni MPD and MNTD in forests is likely due to Tyranni being older settlers in this habitat, resulting in the emergence and persistence of more lineages. The higher Passeri MNTD in savannas can be explained by the existence of a larger number of different Passeri lineages adapted to this severe habitat. The high functional turnover between the suborders in both habitats suggests an ecological strategy to avoid niche overlap.
Current Management of Atherosclerotic Renovascular Disease – What Have We Learned from ASTRAL?

With an increasingly ageing and atherosclerotic-prone population, clinical encounters with patients with atheromatous renovascular disease (ARVD) are commonplace. ARVD is frequently associated with chronic kidney disease (CKD) and hypertension, but evidence suggests that causality only occurs in the minority and it is likely that many atherosclerotic renal artery stenosis (RAS) lesions are incidental. Its association with extensive cardiovascular co-morbidity predisposes to a high patient mortality. The availability of renal angioplasty and stenting, which are generally safe techniques for dilating RAS lesions, has led to widespread use of these endovascular therapies in ARVD, but the outcomes after treatment have been inconsistent, with no clear evidence of benefit in many patients. There has been a great need for a large and appropriately powered randomised control trial to help guide clinical practice. In this review, we present an interpretation of the results of the recently reported Angioplasty and Stenting for Renal Artery Lesions (ASTRAL) trial as well as a brief review of the latest literature, so as to provide the latest guidance regarding the management of this common condition.
Improved UGRNN for short-term traffic flow prediction with multi-feature sequence inputs

As we all know, an Intelligent Transportation System (ITS) will be built more and more perfect in the future. In order to achieve this goal, it is essential to predict short-term traffic flow accurately. Because of the nonlinearity of traffic flow, classic linear models including auto regressive integrated moving average (ARIMA) can not fit it well. With the development of deep learning, some advanced models have been used for traffic flow prediction. The accuracy of prediction has improved, but none of these models can handle multi-feature sequence inputs problem. In this paper, we propose a improved structure called Combined-UGRNN based on Update Gate Recurrent Neural Network (UGRNN) in order to solve this problem. Compared with other widely used algorithms, the Combined-UGRNN achieves highest accuracy.
Producing accessible multimedia music

It is axiomatic that accessibility should be an integral component of any system, and this component is only now beginning to receive the attention it merits. Where such a component is considered integral to the design process, the resulting system benefits on many different levels. For music production and consumption systems, the 'workaround' nature of traditional accessibility enhancements could be replaced by a naturally available transformation and representation feature. However, given the ever-changing requirements of music representation, the interfacing with accessibility tools is constantly set back. With every modification of the models that are used for music analysis, representation and synthesis, additional effort has to be invested to synchronise the consumption and production opportunities for print impaired users with those of the average end-user. If we were able to incorporate the 'changing' nature of music representations in the model itself, we would have a means to integrate the volatile nature of music representation. By doing so, we could also incorporate the modification of these representations for specialised use, such as Braille music, Talking music and enhanced print music. Capturing these aspects in one music representation model that can be used simultaneously for music production and consumption has one particular advantage: it allows all interest groups to cater for their own needs.