Miracle-dz/UniFAR-FTUs huggingface dataset:
Negotiating Relation Work with Telehealth Home Care Companionship Technologies that Support Aging in Place

In response to a perceived caregiver shortage and need to support aging in place, telehealth home care systems are being developed to provide remote care and monitoring to older people. Though research has examined the experiences of teleoperators delivering care through these systems, we know less about the experiences of older adults receiving this care. We report findings from a three-month study of a tablet-based telehealth home care system that provides support for aging in place. We find that there is a mismatch between the designer's conception of how care should be delivered and the ways that participants were interested in using the system. This mismatch exists in four areas: participants' interest in getting to know the human teleoperators and rejecting the virtual avatar, interrogating the interface to figure out the inner workings of the platform, pushing for a more symmetrical relationship, and negotiating the relation work that they were willing to perform in the "sacred space" of their homes. We draw on the concept of heteromation to understand the political dimensions of telehealth aging in place technologies. We also provide implications and future directions for technologies requiring relation work as well as the design of avatar-based remote companionship.
Capacity Estimation for Self-Backhaul in mmWave Networks

We consider the performance implications of using self-backhaul in a millimeter wave (mmWave) wireless network. In a self-backhauled network some nonanchored basestations route their traffic through another anchored basestation rather than utilize an expensive wired backhaul. Self-backhaul is particularly attractive in the mmWave context since we can form narrow beams that reduce the interference due to the backhaul links.In this work we study how interference and load affect the overall performance of self-backhauled networks and we examine which network parameters determine whether self-backhaul is beneficial. We demonstrate that highly directional beams and a steep path loss function improve the tradeoffs associated with self-backhaul. We also develop a scaling law that allows us to easily estimate the self-backhaul capacity.
Influence of Individual Differences when Training Public Speaking with Virtual Audiences

Multimodal interaction technologies have enabled new applications for training interpersonal skills such as public speaking. Various training paradigms have been proposed, most of them relying on some form of graphical feedback provided to the trainee in real-time during their training or after training using an after-action review tool. Another paradigm consists of using virtual characters to provide feedback through their behavior during simulated social interactions. Preliminary studies have started to explore the effectiveness of these different training paradigms; however, these have not investigated the impact of individual differences on which interaction paradigm is more efficient or motivating for different populations of users. In this article, we explore the impact of personality, public speaking anxiety, and immersive tendencies on the experiences of users training public speaking with an interactive virtual audience system providing realtime feedback through virtual audience behavior as well as delayed feedback with an after-action review tool. We found that these three factors impacted different output measures of user experience and user ratings of the system's quality.
Metastasis Suppressor NME1 Directly Activates Transcription of the ALDOC Gene in Melanoma Cells

Background/Aim: NME/NM23 nucleoside diphosphate kinase 1 (NME1) is a metastasis suppressor gene, exhibiting reduced expression in metastatic cancers and the ability to suppress metastatic activity of cancer cells. We previously identified NME1-regulated genes with prognostic value in human melanoma. This study was conducted in melanoma cell lines aiming to elucidate the mechanism through which NME regulates one of these genes, aldolase C (ALDOC). Materials and Methods: ALDOC mRNA and protein expression was measured using qRT-PCR and immunoblot analyses. Promoter-luciferase constructs and chromatin immunoprecipitation were employed to measure the impact of NME1 on ALDOC transcription. Results: NME1 enhanced ALDOC transcription, evidenced by increased expression of ALDOC pre-mRNA and activity of an ALDOC promoter-luciferase module. NME1 was detected at the ALDOC promoter, and forced NME1 expression resulted in enhanced occupancy of the promoter by NME1, increased presence of epigenetic activation markers (H3K4me3 and H3K27ac), and recruitment of RNA polymerase II. Conclusion: This is the first study to indicate that NME1 induces transcription through its direct binding to the promoter region of a target gene.
Blockchain-based Privacy-Preserving Charging Coordination Mechanism for Energy Storage Units

Energy storage units (ESUs) enable several attractive features of modern smart grids such as enhanced grid resilience, effective demand response, and reduced bills. However, uncoordinated charging of ESUs stresses the power system and can lead to mass blackout. On the other hand, existing charging coordination mechanisms suffer from several limitations. First, the need for a central charging controller (CC) presents a single point of failure that jeopardizes the effectiveness of the charging coordination. Second, existing mechanisms overlook privacy concerns of the involved customers. To address these limitations, in this paper, we leverage the blockchain and smart contracts to build a decentralized charging coordination mechanism without the need for centralized charging coordinator. After each ESU sends a charging request to the smart contract address on the blockchain, the smart contract will run the charging coordination mechanism in a self-executed manner such that ESUs with the highest priority are charged in the present time slot while charging requests of lower priority ESUs are deferred to future time slots. We have implemented the proposed mechanism on the Ethereum blockchain and our analysis shows that the blockchain enables a decentralized charging coordination with increased transparency, reliability, and privacy preservation.
FELIX: Fast and Energy-Efficient Logic in Memory

The Internet of Things (IoT) has led to the emergence of big data. Processing this amount of data poses a challenge for current computing systems. PIM enables in-place computation which reduces data movement, a major latency bottleneck in conventional systems. In this paper, we propose an in-memory implementation of fast and energy-efficient logic (FELIX) which combines the functionality of PIM with memories. To the best of authors' knowledge, FELIX is the first PIM logic to enable the single cycle NOR, NOT, NAND, minority, and OR directly in crossbar memory. We exploit the voltage threshold-based memristors to enable single cycle operations. It is a purely in-memory execution which neither reads out data nor changes sense amplifiers, while preserving data in-memory. We extend these single cycle operations to implement more complex functions like XOR and addition in memory with 2× lower latency than the fastest published PIM technique. We also increase the amount of in-memory parallelism in our design by segmenting bitlines using switches. To evaluate the efficiency of our design at the system level, we design a FELIX-based HyperDimensional (HD) computing accelerator. Our evaluation shows that for all applications tested using HD, FELIX provides on average 128.8× speedup and 5,589.3× lower energy consumption as compared to AMD GPU. FELIX HD also achieves on average 2.21× higher energy efficiency, 1.86× speedup, and 1.68× less memory as compared to the fastest PIM technique.
Molecular mechanism of depolarization-dependent inactivation in W366F mutant of Kv1.2

Voltage-gated potassium channels play crucial roles in regulating membrane potential. They are activated by membrane depolarization, allowing the selective permeation of potassium ions across the plasma membrane, and enter a nonconducting state after lasting depolarization of membrane potential, a process known as inactivation. Inactivation in voltage-activated potassium channels occurs through two distinct mechanisms, N-type inactivation and C-type inactivation. C-type inactivation is caused by conformational changes in the extracellular mouth of the channel, while N-type inactivation is elicited by changes in the cytoplasmic mouth of the protein. The W434F-mutated Shaker channel is known as a nonconducting mutant and is in a C-type inactivation state at a depolarizing membrane potential. To clarify the structural properties of C-type inactivated protein, we performed molecular dynamics simulations of the wild-type and W366F (corresponding to W434F in Shaker) mutant of the Kv1.2-2.1 chimera channel. The W366F mutant was in a nearly nonconducting state with a depolarizing voltage and recovered from inactivation with a reverse voltage. Our simulations and 3D-RISM analysis suggested that structural changes in the selective filter upon membrane depolarization trap potassium ions around the entrance of the selectivity filter and prevent ion permeation. This pore restriction is involved in the molecular mechanism of C-type inactivation.
The CAT for efficient 2D and 3D interaction as an alternative to mouse adaptations

We present the first usable prototype of the CAT (Control Action Table). The CAT is a 6 degree of freedom freestanding device, mixing isotonic and isometric sensing modes. It allows a group of users to interact with virtual environments by means of 3D and 2D interaction techniques. The innovating design of the CAT unifies the principle advantages of existing input devices while rejecting their main limitations. We present the resulting characteristics and compare the CAT to existing input devices. A 3D docking task experiment and a demo application have shown that the CAT can be used more efficiently than an 3D isometric desktop device and that the users preferred the CAT. The CAT is contributing to the development of real VR applications.
wgd—simple command line tools for the analysis of ancient whole-genome duplications

Abstract Summary Ancient whole-genome duplications (WGDs) have been uncovered in almost all major lineages of life on Earth and the search for traces or remnants of such events has become standard practice in most genome analyses. This is especially true for plants, where ancient WGDs are abundant. Common approaches to find evidence for ancient WGDs include the construction of KS distributions and the analysis of intragenomic colinearity. Despite the increased interest in WGDs and the acknowledgment of their evolutionary importance, user-friendly and comprehensive tools for their analysis are lacking. Here, we present an easy to use command-line tool for KS distribution construction named wgd. The wgd suite provides commonly used KS and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner. Availability and implementation wgd is free and open source software implemented in Python and is available at https://github.com/arzwa/wgd. Supplementary information Supplementary data are available at Bioinformatics online.
Key Factors of Logistic Capacity of a Mining Enterprise, Management of Processes and Their Assessment

The problem of assessment of logistic providing of the mining industry and production management with maximum efficiency is considered. The technique of integrated assessment of logistic capacity of the enterprise in the form of the sum of all product weight coefficient and ball values of components of system. It is proposed to be achieved through contour-integrated control of the logistical processes of the mining enterprise. The production logistics tasks included in the integrated system are formulated. A methodology for the operational management of the loading and transport complex has been developed. The local contour of capacity is proposed to evaluate the ratings of participants included in the matrix structure. The possibilities of the contour-integrated control of management with calculation of rating estimates of participants of organizational and logistic subsystems allow increasing reliability of material support due to streamlining of material, information and financial flows, system control of conducting organizational and logistic works at the enterprise. Use of the recommended technique allows estimating the conditions of logistic providing mining enterprise, to compare him with the existing standards.
Author retrospective improving data cache performance by pre-executing instructions under a cache miss

The paper introduces and evaluates a technique, referred to as runahead, that prefetches instructions and data into the L1 caches on cache misses. The results of the experiments reported in the paper show that the CPI of a simple in-order pipeline could be reduced by 30%. The principle advantage of runahead over many other prefetching strategies, is twofold: 1) it prefetches both instructions and date; and 2) it is able to create non-sequential data prefetches. Original Paper: http://dx.doi. org/10.1145/263580.263597.
Experience with Grapevine: The Growth of a Distributed System (Summary)

Grapevine is a distributed, replicated system that provides message delivery, naming, authentication, resource location, and access control services in an internet of computers. The system, described in a previous paper [1], was designed and implemented several years ago. We now have had operational experience with the system under substantial load. This experience has proved the original design sound in most aspects, but there also have been some surprises. In this paper we report what we have learned from using Grapevine. Our experience may offer some help to designers of new systems. Grapevine is implemented as a program that is run on a set of dedicated server computers. Client programs o f Grapevine run on various workstation and server computers attached to an internet. The services provided by Grapevine are divided into the message service and the registration service. The message service accepts messages prepared by clients for delivery to individual recipients and distribution lists. Messages are buffered in inboxes on message servers until the recipient requests them. Any message server can accept any message for delivery, thus providing a replicated submission service. A computer system mall user has inboxes on at least two message servers, thus replicating the delivery path for the user.
The freezing threshold for k-colourings of a random graph

We rigorously determine the exact freezing threshold, rkf, for k-colourings of a random graph. We prove that for random graphs with density above rkf, almost every colouring is such that a linear number of variables are frozen, meaning that their colours cannot be changed by a sequence of alterations whereby we change the colours of o(n) vertices at a time, always obtaining another proper colouring. When the density is below rkf, then almost every colouring has at most o(n) frozen variables. This confirms hypotheses made using the non-rigorous cavity method. It has been hypothesized that the freezing threshold is the cause of the "algorithmic barrier", the long observed phenomenon that when the edge-density of a random graph exceeds hf k ln k(1+ok(1)), no algorithms are known to find k-colourings, despite the fact that this density is only half the k-colourability threshold. We also show that rkf is the threshold of a strong form of reconstruction for k-colourings of the Galton-Watson tree, and of the graphical model.
Enhancing Loosely Schema-aware Entity Resolution with User Interaction

Entity Resolution (ER) is a fundamental task of data integration: it identifies different representations (i.e., profiles) of the same real-world entity in databases. To compare all possible profile pairs through an ER algorithm has a quadratic complexity. Blocking is commonly employed to avoid that: profiles are grouped into blocks according to some features, and ER is performed only for entities of the same block. Yet, devising blocking criteria and ER algorithms for data with highly schema heterogeneity is a difficult and error-prone task calling for automatic methods and debugging tools. In our previous work, we presented Blast, an ER system that can scale practitioners' favorite Entity Resolution algorithms. In current version, Blast has been devised to take full advantage of parallel and distributed computation as well (running on top of Apache Spark). It implements the state-of-the-art unsupervised blocking method based on automatically extracted loose schema information. We build on top of blast a GUI (Graphic User Interface), which allows: (i) to visualize, understand, and (optionally) manually modify the loose schema information automatically extracted (i.e., injecting user's knowledge in the system); (ii) to retrieve resolved entities through a free-text search box, and to visualize the process that lead to that result (i.e., the provenance). Experimental results on real-world datasets show that these two functionalities can significantly enhance Entity Resolution results.
From Deletion to Re-Registration in Zero Seconds: Domain Registrar Behaviour During the Drop

When desirable Internet domain names expire, they are often re-registered in the very moment the old registration is deleted, in a highly competitive and resource-intensive practice called domain drop-catching. To date, there has been little insight into the daily time period when expired domain names are deleted, and the race to re-registration that takes place. In this paper, we show that . com domains are deleted in a predictable order, and propose a model to infer the earliest possible time a domain could have been re-registered. We leverage this model to characterise at a precision of seconds how fast certain types of domain names are re-registered. We show that 9.5 % of deleted domains are re-registered with a delay of zero seconds. Domains not taken immediately by the drop-catch services are often re-registered later, with different behaviours over the following seconds, minutes and hours. Since these behaviours imply different effort and price points, our methodology can be useful for future work to explain the uses of re-registered domains.
A comprehensive study on sign languages recognition systems using (SVM, KNN, CNN and ANN)

The needs of communities and the new emerging technologies aspire researchers to come up with new and innovative ways to fulfil these needs. Sign languages are said to be a visual language that is used by the deaf community. Undoubtedly, there is a communication difficulty between the hearing-impaired people and the hearing community. To overcome this impediment between the two communities, various approaches were conducted to develop sign language recognition systems. An evaluation between some of these recent technologies is crucial to compare their methodologies and accuracy of their results. Therefore, this paper provides a comprehensive study on the different approaches and techniques used to develop a sign language study. On systems that were developed based on support vector machine (SVM), K-nearest neighbours (KNN) classifier, deep convolutional neural networks (CNN) and artificial neural networks (ANN).
A Versatile Flexible UHF RFID Tag for Glass Bottle Labelling in Self-Service Stores

Low-cost and versatile radio frequency identification (RFID) tag for bottle labeling is in great demand with the rise of self-service stores. Especially, robust performance is of great importance when the tag is needed to be attached on different liquid products. This paper proposed a versatile and flexible ultra-high frequency RFID tag for liquid products with glass bottles. The tag antenna is based on a simple loop structure, which has a strong concentrated magnetic field. As opposed to conventional dipole-based RFID tags, the loop-based antenna is less affected by liquid. Simulations and measurements of the tag have been carried out in different application scenarios. Significant factors, such as installation position, liquid amount and type, bottle shape, and thickness, have been investigated to find out their influences on the proposed tag. According to the simulation and experimental verification, the performance of the tag is robust despite changes of the significant factors, and specifically, the tag antenna keeps well matched around the FCC band and the reading ranges remain 1.6–2.5 m in multiply application scenarios. This makes the proposed tag versatile and feasible for a variety of liquid products with glass bottles in self-service stores.
An extension of nonstationary fuzzy sets to heteroskedastic fuzzy time series

Most applications deal with unconditional variance of the time series. Fuzzy time series allow an inexpensive computation to forecasting dynamic processes and uncertainties. In this paper we have extended the concept of nonstationary fuzzy sets to Fuzzy Time Series, termed Non-stationary Fuzzy Time Series (NSFTS). While some models require new data before adapting, the NSFTS is capable of adapting to heteroskedastic time series. In the experiments, NSFTS outperformed other known FTS methods with box-cox transformations available. Statistical tests in three diﬀerent datasets indicate that the results achieved by the proposed model are either superior or non-inferior to other FTS models.
Profiling the Spatial Structure of London: From Individual Tweets to Aggregated Functional Zones

Knowledge discovery about people and cities from emerging location data has been an active research field but is still relatively unexplored. In recent years, a considerable amount of work has been developed around the use of social media data, most of which focusses on mining the content, with comparatively less attention given to the location information. Furthermore, what aggregated scale spatial patterns show still needs extensive discussion. This paper proposes a tweet-topic-function-structure framework to reveal spatial patterns from individual tweets at aggregated spatial levels, combining an unsupervised learning algorithm with spatial measures. Two-year geo-tweets collected in Greater London were analyzed as a demonstrator of the framework and as a case study. The results indicate, at a disaggregated level, that the distribution of topics possess a fair degree of spatial randomness related to tweeting behavior. When aggregating tweets by zones, the areas with the same topics form spatial clusters but of entangled urban functions. Furthermore, hierarchical clustering generates a clear spatial structure with orders of centers. Our work demonstrates that although uncertainties exist, geo-tweets should still be a useful resource for informing spatial planning, especially for the strategic planning of economic clusters.