bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictability of Recurrence using Immunohistochemistry to delineate Surgical Margins in mucosal Head and Neck Squamous Cell Carcinoma (PRISM-HNSCC): study protocol for a prospective, observational and bilateral study in Australia and India
Authors: Joseph Sheela , Janakiraman Rajinikanth , Chacko Geeta , Jayaraj Rama , Thomas Mahiban , Thomas Meera , Mukhopadhyay Sramana
Published: June 2019

Objectives

Treatment failure and poor 5-year survival in mucosal head and neck squamous cell carcinoma (HNSCC) has remained unchanged for decades mainly due to advanced stage of presentation and high rates of recurrence. Incomplete surgical removal of the tumour, attributed to lack of reliable methods to delineate the surgical margins, is a major cause of disease recurrence. The predictability of recurrence using immunohistochemistry (IHC) to delineate surgical margins (PRISM) in mucosal HNSCC study aims to redefine margin status by identifying the true extent of the tumour at the molecular level by performing IHC with molecular markers, eukaryotic initiation factor, eIF4Eand tumour suppressor gene, p53, on the surgical margins and test the use of Lugol’s iodine and fluorescence visualisation prior to the wide local excision. This article describes the study protocol at its pre - results stage.

Methods and analysis

PRISM-HNSCC is a bilateral observational research being conducted in Darwin, Australia and Vellore, India. Individuals diagnosed with HNSCC will undergo the routine wide local excision of the tumour followed by histopathological assessment. Tumours with clear surgical margins that satisfy the exclusion criteria will be selected for further staining of the margins with eIF4E and p53 antibodies. Results of IHC staining will be correlated with recurrences in an attempt to predict the risk of disease recurrence. Patients in Darwin will undergo intraoperative staining of the lesion with Lugol’s iodine and fluorescence visualisation to delineate the excision margins while patients in Vellore will not undertake these tests. The outcomes will be analysed.

Ethics and dissemination

The PRISM-HNSCC study was approved by the institutional ethics committees in Darwin (Human Research Ethics Committee 13-2036) and Vellore (Institutional Review Board Min. no. 8967). Outcomes will be disseminated through publications in academic journals and presentations at educational meetings and conferences. It will be presented as dissertation at the Charles Darwin University. We will communicate the study results to both participating sites. Participating sites will communicate results with patients who have indicated an interest in knowing the results.

Trial registration number

Australian New Zealand Clinical Trials Registry (ACTRN12616000715471).
Compliance compromises an interventional study on iron supplementation in female combatants
Authors: Gofrit Shany Guly , Ohayon-Cohen S , Tsur A M , Rabkin V , Michael Shapira M , Finestone A S
Published: June 2019

Introduction

Low iron levels are related to overuse injuries, poor physical performance and cognitive impairments in female recruits. The aim of this study was to evaluate iron supplement compliance in female combatants during basic training, and its effect on haemoglobin (Hgb), ferritin and injuries.

Methods

329 female recruits to light infantry units filled induction questionnaires regarding smoking status, previous overuse injuries and iron deficiency. Blood was drawn for Hgb and ferritin. Subjects with ferritin levels below 20 ng/mL were considered iron depleted and were prescribed a ferrous fumarate supplement. After 4 months of basic training, the subjects completed a follow-up questionnaire regarding overuse injuries, reasons for failure to complete basic training and compliance with iron supplementation. Blood tests were repeated.

Results

Mean ferritin levels declined during training (from 18.1±18.2 to 15.3±9.6, p=0.01). Compliance with iron supplementation was observed in 26 (26.3%) of the subjects. In compliant subjects, Hgb levels remained constant and ferritin levels increased by 2.9±5.4 (p=0.07). The main reasons for reported non-compliance were forgetfulness, 26 (35.6%), and gastrointestinal side effects, 17 (23.3%). Injuries during training were not found to be associated with iron status. Smokers had a significantly higher rate of reported injuries prior to training (p<0.01).

Conclusions

Ferritin levels decline during training. Compliance with iron supplementation is low. Iron supplementation has a significant effect on ferritin levels, even in the non-compliance group. Injuries were not related to iron status in this group. Further research is needed in order to clarify the most appropriate iron supplementation method.
Impacts of human activities on tidal dynamics in a sexta-diurnal tidal resonant bay
Authors: Zhang Jiyun , Song Dehai , Wu Wen , Bao Xianwen
Published: June 2019

Using numerical modelling, we study changes in tidal dynamics in Daya Bay (DYB) between 1989 and 2014. During this period, a total water area of 30 km2 was reclaimed and the average water depth increased by 38 cm. As DYB is a sexta-diurnal tidal resonant bay, the sexta-diurnal tides respond differently to the coastline and bathymetry changes than other tides. Taking K1, M2, M4, and M6 as examples, model results show a decrease in tidal elevation amplitude, tidal current magnitude, and tidal energy flux for K1, M2, and M4 tides. For the M6 tide, however, the model predicted an increase in tidal elevation amplitude, tidal current magnitude in some parts of the bay, and the tidal energy flowing into the bay. Land reclamation leads to the enhancement of sexta-diurnal tidal resonance and thus the magnitude of the M6 tide. Furthermore, due to the magnification of M6, tidal duration asymmetry in DYB changed from ebb-dominance to flood-dominance, and water exchange became much more active. Therefore, owing to the sexta-diurnal tidal resonance, the impact of human activities on tidal dynamics in DYB is different from that in previously reported semi-enclosed bays where large-scale land reclamation has been carried out.
Evaluation of self-penetration potential of a bio-inspired site characterization probe by cavity expansion analysis
Authors: Martinez A. , DeJong J.T. , Jaeger R.A. , Khosravi A.
Published: June 2019

Site investigations at limited-access project sites often require mobilization of smaller rigs that may not have the reaction mass required to perform soundings to the desired depth. This study explores the feasibility of a new conceptual bio-inspired solution by adapting functional principles from organisms whose primary mode of locomotion is soil burrowing, including razor clams, caecilians, and earthworms. These organisms radially expand a segment of their body to increase the normal radial pressure acting on it to temporarily form an anchor. This study evaluates the dimensions required for self-penetration of an idealized bio-inspired probe consisting of a radially expanding shaft and a penetrating tip. Cavity expansion analyses, field test data, and theoretical relationships from the literature are used to evaluate the self-penetration potential in different soil types. The results indicate that the resistance to self-penetration is higher in dense sands than in silts and clays. In sands, the resistance to self-penetration is greater for sands that exhibit a more dilative behavior at a given overburden pressure. On the contrary, the resistance to self-penetration in clays decreases slightly as the overconsolidation ratio is increased. The relative dimensions required to initiate self-penetration predicted by cavity expansion analysis are compared with the dimensions of various burrowing organisms.
Optimal design of a hanging truss with shape memory alloy wires
Authors: Zhang Xuan , Hanahara Kazuyuki , Tada Yukio , Pei Zhiyong , Li Zhe , Sun Pengjie
Published: June 2019

In this study, we discuss the dynamic problem of a column-type hanging truss structural system with pseudo-elastic shape memory alloy (SMA) bracing wires. In the case where the sectional area values of the bracing SMA wire members are small enough to be negligible, it is close to the situation where there are no braces. In the case where the sectional area values of the bracing SMA wire members are large enough not to be negligible, the vibration amplitude of the peripheral end apparatus is suppressed from the deformation point of view. In addition, energy attenuation efficiency is improved with larger sectional area values because of the hysteretic characteristic of SMA. Small sectional area values of the bracing SMA wire members near the support ceiling or peripheral end are beneficial to vibration transmission reduction. These findings indicate that the placement and sectional area values of SMA wire members are both significant from the viewpoint of suppression of influence of the support ceiling vibration of the hanging truss. In this study, we obtain the optimal sectional area values of the SMA wire bracing members for the objectives of vibration isolation and attenuation. We discuss influences of different vibration conditions on the optimal solutions.
Optimization in single point incremental forming of Inconel 718 through response surface methodology
Authors: Pratheesh Kumar S. , Elangovan S.
Published: June 2019

Incremental sheet forming is a flexible and versatile process with a promising future in the batch production and prototyping sectors. With decreased design time and negligible production time, incremental sheet forming provides reliability, flexibility, and quality, while being an economical option in contrast to the traditional forming process. In this paper, Inconel 718, a material that has extensive use in aircraft engines, is considered for experimental work to obtain the optimum combination of process parameters. Response surface methodology is used to optimize the process parameters, in particular feed rate, step depth, and lubricant viscosity. The output responses are surface roughness, profile accuracy, and wall thickness. Analysis of variance (ANOVA) is performed using the experimental results to predict the statistical influence of the process parameters. The optimal combination of process parameters is further predicted using a numerical optimization technique to achieve better profile accuracy and surface finish. The results obtained are experimentally validated and are in good agreement with the predicted values.
Azimuthal asymmetries from 𝜃 vacuum
Authors: Yang Weihua
Published: June 2019

We present the complete azimuthal asymmetries at leading twist in terms of fragmentation functions in dihadron production semi-inclusive electron–positron annihilation process. When the nontrivial [Formula: see text] vacuum is taken into consideration, the parity symmetry of quantum chromodynamics is violated. As a consequence of the [Formula: see text] [Formula: see text]-odd effects, [Formula: see text]-odd fragmentation functions would contribute to the azimuthal asymmetries. Azimuthal asymmetry coming from two interference terms with opposite signs vanishes when sum over many events. This symmetry only survives on the event-by-event basis. Azimuthal asymmetry coming from two interference terms with same signs survives and can be measured to extract the [Formula: see text]-odd fragmentation functions. We also present the hadron polarizations.
Structural, magnetic and high frequency (1–6 GHz) parameters of Sr-substituted BaFe2O4 monoferrites synthesized by sol–gel method
Authors: Ahmad Mukhtar , Shaheen Jawaria , Hashmi Waseem Abbas , Akhtar Majid Niaz , Asif Muhammad
Published: June 2019

In this work, Sr-substituted samples of single-phase spinel monoferrites with chemical formula [Formula: see text] (x = 0.00, 0.33, 0.67, 1.00) were synthesized using sol–gel auto-combustion method. In order to confirm the single-phase formation of these samples, a sample (x = 0.00) was chosen for heat treatment at different temperatures (100, 300, 400, 600 and [Formula: see text]) for 4 h. The heat treated sample was then investigated by X-ray diffraction (XRD) analysis and results showed that a single-phase sample can be successfully synthesized at a temperature of [Formula: see text], which is much lower than that reported in earlier literature for synthesis of same structured samples. All the synthesized samples were then sintered at [Formula: see text] for 4 h to achieve better crystallinity. From XRD patterns, lattice parameters, cell volume and XRD density as a function of Sr-substitution were calculated. Scanning electron microscopy (SEM) results showed that the grain size increased as the temperature was increased. Fourier transform infrared spectroscopy (FTIR) results confirmed the single-phase spinel monoferrites at [Formula: see text]. From M–H loops (x = 0.0, 0.33, 0.67 and 1.00), different magnetic parameters such as saturation magnetization [Formula: see text], remanance [Formula: see text], coercivity [Formula: see text] and magnetic moment [Formula: see text] were calculated. Magnetocrystalline anisotropy constant and Y–K angles of Sr-doped Ba monoferrites were also calculated. In addition, the variation of different dielectric parameters (real permittivity, imaginary permittivity, real permeability, imaginary permeability, ac conductivity and loss tangent) as a function of frequency (1–6 GHz) has been discussed in this work. The results suggest that the synthesized materials have many advantages over previously reported single-phase spinel monoferrites.
Parallel Spine Design and CPG Motion Test of Quadruped Robot
Authors: Wang Binrui , Liu Yixuan , Li Zhongwen , Chen Dijian , Ma Ruizi , Wang Ling
Published: June 2019

The spine of mammals aids in the stability of locomotion. Central Pattern Generators (CPGs) located in spinal cord can rapidly provide a rhythmic output signal during loss of sensory feedback on the basis of a simulated quadruped agent. In this paper, active spine of quadruped robot is shown to be extremely effective in motion. An active spine model based on the Parallel Kinematic Mechanism (PKM) system and biological phenomena is described. The general principles involved in constructing a neural network coupled with limbs and spine to solve specific problems are discussed. A CPG mathematical model based on Hopf nonlinear oscillators produces rhythmic signal during locomotion is described, where many parameters to be solved must be formulated in terms of desired stability, often subject to vertical stability analysis. Our simulations demonstrate that active spine with setting reasonable CPG parameters can reduce unnecessary lateral displacement during trot gait, improving the stability of quadruped robot. In addition, we demonstrate that physical prototype mechanism provides a framework which shows correctness of simulation, and stability can thus be easily embodied within locomotion.
The Einstein–Infeld–Hoffmann legacy in mathematical relativity I: The classical motion of charged point particles
Authors: Kiessling Michael K.-H. , Tahvildar-Zadeh A. Shadi
Published: June 2019

Einstein, Infeld and Hoffmann (EIH) claimed that the field equations of general relativity theory alone imply the equations of motion of neutral matter particles, viewed as point singularities in space-like slices of spacetime; they also claimed that they had generalized their results to charged point singularities. While their analysis falls apart upon closer scrutiny, the key idea merits our attention. This report identifies necessary conditions for a well-defined general-relativistic joint initial value problem of [Formula: see text] classical point charges and their electromagnetic and gravitational fields. Among them, in particular, is the requirement that the electromagnetic vacuum law guarantees a finite field energy–momentum of a point charge. This disqualifies the Maxwell(–Lorentz) law used by EIH. On the positive side, if the electromagnetic vacuum law of Bopp, Landé–Thomas and Podolsky (BLTP) is used, and the singularities equipped with a nonzero bare rest mass, then a joint initial value problem can be formulated in the spirit of the EIH proposal, and shown to be locally well-posed — in the special-relativistic zero-[Formula: see text] limit. With gravitational coupling (i.e. [Formula: see text]), though, changing Maxwell’s into the BLTP law and assigning a bare rest mass to the singularities is by itself not sufficient to obtain even a merely well-defined joint initial value problem: the gravitational coupling also needs to be changed, conceivably in the manner of Jordan and Brans–Dicke.
Scaling Crowdsourcing with Mobile Workforce
Authors: Acer Utku Günay , Broeck Marc van den , Forlivesi Claudio , Heller Florian , Kawsar Fahim
Published: June 2019

Traditional urban-scale crowdsourcing approaches suffer from three caveats - lack of complete spatiotemporal coverage, lack of accurate information and lack of sustained engagement of crowd workers. In this paper, we argue that these caveats can be addressed by embedding crowdsourcing tasks into the daily routine of mobile workforces that roam around an urban area. As a use case, we take the bpost who deliver the letters and parcels to the citizens across entire Belgium. We present a study that explores the behavioural attributes of these mobile postal workers both quantitatively (6.3K) and qualitatively (6) to assess the opportunity of leveraging them for crowdsourcing tasks. We report their mobility pattern, workflow, and behavioural traits which collectively inform the design of a purpose-built crowdsourcing solution. In particular, our solution operates on two key techniques - route augmentation, and on-wearable interruptibility management. Together, these mechanisms enhance the spatial coverage, response accuracy and increase workers' engagement with crowdsourcing tasks. We describe these principal components in a wearable smartwatch application supported by a data management infrastructure. Finally, we report a first-of-its-kind real-world trial with ten postal workers for two weeks to assess the quality of road signs at the city centre of Antwerp. Our findings suggest that our solution was effective in achieving 89% spatial coverage and increasing response rate (83.6%) and accuracy (100%) of the crowdsourcing tasks. Although limited in scale, these and the rest of our findings highlight the way of building an efficient and purposeful crowdsourcing solution of the future.
An Optimized Recurrent Unit for Ultra-Low-Power Keyword Spotting
Authors: Amoh Justice , Odame Kofi M.
Published: June 2019

There is growing interest in being able to run neural networks on sensors, wearables and internet-of-things (IoT) devices. However, the computational demands of neural networks make them difficult to deploy on resource-constrained edge devices.

To meet this need, our work introduces a new recurrent unit architecture that is specifically adapted for on-device low power acoustic event detection (AED). The proposed architecture is based on the gated recurrent unit ('GRU' -- introduced by Cho et al. [9]) but features optimizations that make it implementable on ultra-low power micro-controllers such as the Arm Cortex M0+.

Our new architecture, the Embedded Gated Recurrent Unit (eGRU) is demonstrated to be highly efficient and suitable for short-duration AED and keyword spotting tasks. A single eGRU cell is 60× faster and 10× smaller than a GRU cell. Despite its optimizations, eGRU compares well with GRU across tasks of varying complexities.

The practicality of eGRU is investigated in a wearable acoustic event detection application. An eGRU model is implemented and tested on the Arm Cortex M0-based Atmel ATSAMD21E18 processor. The Arm M0+ implementation of the eGRU model compares favorably with a full precision GRU that is running on a workstation. The embedded eGRU model achieves a classification accuracy 95.3%, which is only 2% less than the full precision GRU.
RAMT
Authors: Bi Chongguang , Xing Guoliang
Published: June 2019

Recently a class of new in-vehicle technologies based on off-the-shelf mobile devices have been developed to improve driving safety and experience. For instance, wearables like the smartwatches are utilized to monitor the action of the driver and detect possible secondary tasks. Moreover, wearables can allow a driver to use gesture for in-vehicle controls, reducing distractions to driving. The accuracy of these systems can be significantly improved by tracking the real-time attitude of mobile devices. This paper proposes a novel system called Real-time Attitude and Motion Tracking (RAMT) that can enable a mobile device to accurately learn the coordinate system of a moving vehicle, and hence track its attitude and motion in real time. RAMT consists of a series of lightweight algorithms to sense the vehicle's movement and calculate the device's attitude. It provides a solution for trajectory-based gesture recognition. We have implemented RAMT on a smartphone and a smartwatch and evaluated the performance in 10 real driving trips. Our results show that the overall error of the coordinate system alignment is around 5° for the smartphone and 10° for the smartwatch, and over 84% of customized hand gestures can be accurately recognized with the result of RAMT. A video demo of RAMT is available at https://youtu.be/9rZp7HxyRts.
Multi-Stage Receptivity Model for Mobile Just-In-Time Health Intervention
Authors: Choi Woohyeok , Park Sangkeun , Kim Duyeon , Lim Youn-kyung , Lee Uichin
Published: June 2019

A critical aspect of mobile just-in-time (JIT) health intervention is proper delivery timing, which correlates with successfully promoting target behaviors. Despite extensive prior studies on interruptibility, however, our understanding of the receptivity of mobile JIT health intervention is limited. This work extends prior interruptibility models to capture the JIT intervention process by including multiple stages of conscious and subconscious decisions. We built BeActive, a mobile intervention system for preventing prolonged sedentary behaviors, and we collected users' responses to a given JIT support and relevant contextual factors and cognitive/physical states for three weeks. Using a multi-stage model, we systematically analyzed the responses to deepen our understanding of receptivity using a mixed methodology. Herein, we identify the key factors relevant to each stage outcome and show that the receptivity of JIT intervention is nuanced and context-dependent. We propose several practical design implications for mobile JIT health intervention and context-aware computing.
MAC
Authors: Fang Zhihan , Yang Yu , Wang Shuai , Fu Boyang , Song Zixing , Zhang Fan , Zhang Desheng
Published: June 2019

Urban anomalies have a large impact on passengers' travel behavior and city infrastructures, which can cause uncertainty on travel time estimation. Understanding the impact of urban anomalies on travel time is of great value for various applications such as urban planning, human mobility studies and navigation systems. Most existing studies on travel time have been focused on the total riding time between two locations on an individual transportation modality. However, passengers often take different modes of transportation, e.g., taxis, subways, buses or private vehicles, and a significant portion of the travel time is spent in the uncertain waiting. In this paper, we study the fine-grained travel time patterns in multiple transportation systems under the impact of urban anomalies. Specifically, (i) we investigate implicit components, including waiting and riding time, in multiple transportation systems; (ii) we measure the impact of real-world anomalies on travel time components; (iii) we design a learning-based model for travel time component prediction with anomalies. Different from existing studies, we implement and evaluate our measurement framework on multiple data sources including four city-scale transportation systems, which are (i) a 14-thousand taxicab network, (ii) a 13-thousand bus network, (iii) a 10-thousand private vehicle network, and (iv) an automatic fare collection system for a public transit network (i.e., subway and bus) with 5 million smart cards.
Viewport Prediction for Live 360-Degree Mobile Video Streaming Using User-Content Hybrid Motion Tracking
Authors: Feng Xianglong , Swaminathan Viswanathan , Wei Sheng
Published: June 2019

360-degree video streaming has been gaining popularities recently with the rapid growth of adopting mobile head mounted display (HMD) devices in the consumer video market, especially for live broadcasts. The 360-degree video streaming introduces brand new bandwidth and latency challenges in live streaming due to the significantly increased video data. However, most of the existing bandwidth saving approaches based on viewport prediction have only focused on the video-on-demand (VOD) use cases leveraging historical user behavior data, which is not available in live broadcasts. We develop a new viewport prediction scheme for live 360-degree video streaming using video content-based motion tracking and dynamic user interest modeling. To obtain real-time performance, we implement the Gaussian mixture model (GMM) and optical flow algorithms for motion detection and feature tracking. Then, the user's future viewport of interest is generated by leveraging a dynamic user interest model that weighs all the features and motion information abstracted from the live video frames. Furthermore, we develop two enhancement techniques that take into consideration of user feedback for fast error recovery and view updates. Consequently, our predicted viewports are irregular and dynamically adjusted to cover the maximum portions of the actual user viewports and thus ensure a high prediction accuracy. We evaluate our viewport prediction approach using a public user head movement dataset, which contains the data of 48 users watching 6 360-degree videos. The experimental results show that the proposed approach supports sophisticated user head movement patterns and outperforms the existing velocity-based approach in terms of prediction accuracy. In addition, the motion tracking scheme introduces minimum latency overhead to ensure the quality of live streaming experience.
On-body Sensing of Cocaine Craving, Euphoria and Drug-Seeking Behavior Using Cardiac and Respiratory Signals
Authors: Gullapalli Bhanu Teja , Natarajan Annamalai , Angarita Gustavo A. , Malison Robert T. , Ganesan Deepak , Rahman Tauhidur
Published: June 2019

Drug addiction is a chronic brain-based disorder that affects a person's behavior and leads to an inability to control drug usage. Ubiquitous physiological sensing technologies to detect illicit drug use have been well studied and understood for different types of drugs. However, we currently lack the ability to continuously and passively measure the user state in ways that might shed light on the complex relationships between cocaine-induced subjective states (e.g., craving and euphoria) and compulsive drug-seeking behavior. More specifically, the applicability of wearable sensors to detect drug-related states is underexplored. In the current work, we take an initial step in the modeling of cocaine craving, euphoria and drug-seeking behavior using electrocardiographic (ECG) and respiratory signals unobtrusively collected from a wearable chest band. Ten experienced cocaine users were studied using a human laboratory paradigm of self-regulated (i.e., "binge") cocaine administration, during which self-reported visual analog scale (VAS) ratings of cocaine-induced subjective effects (i.e., craving and euphoria) and behavioral measures of drug-seeking behavior (i.e., button clicks for drug infusions) are collected. Our results are encouraging and show that self-reported VAS Craving scores are predicted with a normalized root-mean-squared error (NRMSE) of 17.6% and a Pearson correlation coefficient of 0.49. Similarly, for VAS Euphoria prediction, an NRMSE of 16.7% and a Pearson correlation coefficient of 0.73 were achieved. We further analyze the relative importance of different morphology-related ECG and respiratory features for craving and euphoria prediction. Demographic factor analysis reveals how one single factor (i.e., average dollar ($) per cocaine use) can help to further boost the performance of our craving and euphoria models. Lastly, we model drug-seeking behavior using cardiac and respiratory signals. Specifically, we demonstrate that the latter signals can predict participant button clicks with an F1 score of 0.80 and estimate different levels of click density with a correlation coefficient of 0.85 and an NRMSE of 17.9%.
The PARK Framework for Automated Analysis of Parkinson's Disease Characteristics
Authors: Langevin Raina , Ali Mohammad Rafayet , Sen Taylan , Snyder Christopher , Myers Taylor , Dorsey E. Ray , Hoque Mohammed Ehsan
Published: June 2019

There are about 900,000 people with Parkinson's disease (PD) in the United States. Even though there are benefits of early treatment, unfortunately, over 40% of individuals with PD over 65 years old do not see a neurologist. It is often very difficult for these individuals to get to a physician's office for diagnosis and subsequent monitoring. To address this problem, we present PARK, Parkinson's Analysis with Remote Kinetic-tasks. PARK instructs and guides users through six motor tasks and one audio task selected from the standardized MDS-UPDRS rating scale and records their performance via webcam. An initial experiment was conducted with 127 participants with PD and 127 age-matched controls, in which a total of 1,778 video recordings were collected. 90.6% of the PD participants agreed that PARK was easy to use, and 93.7% mentioned that they would use the system in the future. We explored objective differences between those with and without PD. A novel motion feature based on the Fast Fourier Transform (FFT) of optical flow in a region of interest was designed to quantify these differences in the collected video recordings. Additionally, we found that facial action unit AU4 (brow lowerer) was expressed significantly more often, while AU12 (lip corner puller) was expressed less often in various tasks for participants with PD.
How Does a Nation Walk?
Authors: Lim Brian Y. , Kay Judy , Liu Weilong
Published: June 2019

Activity trackers are being deployed in large-scale physical activity intervention programs, but analyzing their data is difficult due to the large data size and complexity. As such large datasets of steps become more available, it is paramount to develop analysis methods to deeply interpret them to understand the variety and changing nature of human steps behavior. In this work, we explored ways to analyze the heterogeneous steps activity data and propose a framework of dimensions and time aggregations to interpret how providing a city-wide population with activity trackers, and monetary incentives influences their wearing and steps behavior. We analyzed the daily step counts of 140,000 individuals, walking a combined 74 billion steps in 305 days of a city-wide public health campaign. We performed data mining clustering to identify 16 user segments, each with distinctive weekly streaks in patterns of device wear and recorded steps. We demonstrate that these clusters enable us to interpret how some users increased their steps level. Our key contributions are: a new analytic method to scalably interpret large steps data; the insights of our analysis about key user segments in our large intervention; demonstrating the power to predictive user outcomes from their first few days of tracking.
MenstruLoss
Authors: Mukherjee Manideepa , Naqvi Sana Ali , Verma Anushika , Sengupta Debarka , Parnami Aman
Published: June 2019

Self-monitoring of menstrual blood loss volume could lead to early detection of multiple gynecological diseases. In this paper, we describe the development of a textile-based blood volume sensor which can be integrated into the sanitary napkin to quantify the menstrual blood loss during menstruation. It is based on sensing the resistance change detected as the output voltage change, with the added volume of fluid. Benchtop characterization tests with 5 mL of fluid determined the effect of spacing, orientation and weight, and location of fluid drop on the sensor. The sensor has been evaluated by intravenous blood samples collected from 18 participants and menstrual blood samples collected from 10 participants for four months. The collected intravenous blood samples and menstrual blood samples were used to create two regression model that can predict the blood volume and menstrual blood volume from the voltage input with Mean Absolute Percentage Error (MAPE) of 11-15% and 15-30% respectively.
Drinks & Crowds
Authors: Phan Thanh-Trung , Muralidhar Skanda , Gatica-Perez Daniel
Published: June 2019

The design of computational methods to recognize alcohol intake is a relevant problem in ubiquitous computing. While mobile crowdsensing and social media analytics are two current approaches to characterize alcohol consumption in everyday life, the question of how they can be integrated, to examine their relative value as informative of the drinking phenomenon and to exploit their complementarity towards the classification of drinking-related attributes, remains as an open issue. In this paper, we present a comparative study based on five years of Instagram data about alcohol consumption and a 200+ person crowdsensing campaign collected in the same country (Switzerland). Our contributions are two-fold. First, we conduct data analyses that uncover temporal, spatial, and social contextual patterns of alcohol consumption on weekend nights as represented by both crowdsensing and social media. This comparative analysis provides a contextual snapshot of the alcohol drinking practices of urban youth dwellers. Second, we use a machine learning framework to classify individual drinking events according to alcohol and non-alcohol categories, using images features and contextual cues from individual and joint data sources. Our best performing models give an accuracy of 82.3% on alcohol category classification (against a baseline of 48.5%) and 90% on alcohol/non-alcohol classification (against a baseline of 65.9%) using a fusion of image features and contextual cues in this task. Our work uncovers important patterns in drinking behaviour across these two datasets and the results of study are promising towards developing systems that use machine learning for self-monitoring of alcohol consumption.
Input, Output and Construction Methods for Custom Fabrication of Room-Scale Deployable Pneumatic Structures
Authors: Swaminathan Saiganesh , Rivera Michael , Kang Runchang , Luo Zheng , Ozutemiz Kadri Bugra , Hudson Scott E.
Published: June 2019

In this paper, we examine the future of designing room-scale deployable pneumatic structures that can be fabricated with interactive capabilities and thus be responsive to human input and environments. While there have been recent advances in fabrication methods for creating large-scale structures, they have mainly focused around creating passive structures. Hence in this work, we collectively tackle three main challenges that need to be solved for designing room-scale interactive deployable structures namely -- the input, output (actuation) and construction methods. First, we explore three types of sensing methods --- acoustic, capacitive and pressure --- in order to embed input into these structures. These sensing methods enable users to perform gestures such as knock, squeeze and swipe with specific parts of our fabricated structure such as doors, windows, etc. and make them interactive. Second, we explore three types of actuation mechanisms -- inflatable tendon drive, twisted tendon drive and roll bending actuator -- that are implemented at structural scale and can be embedded into our structures to enable a variety of responsive actuation. Finally, we provide a construction method to custom fabricate and assemble inter-connected pneumatic trusses with embedded sensing and actuation capability to prototype interactions with room-scale deployable structures. To further illustrate the collective (input, output and construction) usage of the system, we fabricated three exemplar interactive deployable structures -- a responsive canopy, an interactive geodesic dome and a portable table (Figures 1 and 2). These can be deployed from a compact deflated state to a much larger inflated state which takes on a desired form while offering interactivity.
ScratchThat
Authors: Wu Jason , Ahuja Karan , Li Richard , Chen Victor , Bigham Jeffrey
Published: June 2019

Speech interfaces have become an increasingly popular input method for smartphone-based virtual assistants, smart speakers, and Internet of Things (IoT) devices. While they facilitate rapid and natural interaction in the form of voice commands, current speech interfaces lack natural methods for command correction. We present ScratchThat, a method for supporting command-agnostic speech repair in voice-driven assistants, suitable for enabling corrective functionality within third-party commands. Unlike existing speech repair methods, ScratchThat is able to automatically infer query parameters and intelligently select entities in a correction clause for editing. We conducted three evaluations to (1) elicit natural forms of speech repair in voice commands, (2) compare the interaction speed and NASA TLX score of the system to existing voice-based correction methods, and (3) assess the accuracy of the ScratchThat algorithm. Our results show that (1) speech repair for voice commands differ from previous models for conversational speech repair, (2) methods for command correction based on speech repair are significantly faster than other voice-based methods, and (3) the ScratchThat algorithm facilitates accurate command repair as rated by humans (77% accuracy) and machines (0.94 BLEU score). Finally, we present several ScratchThat use cases, which collectively demonstrate its utility across many applications.
MegaLight
Authors: Zhan Tong , Li Wenzhong , Chen Xu , Lu Sanglu
Published: June 2019

Screen-camera communication using dynamic barcode streaming has emerged as a convenient and secure method for short-range, impromptu device-to-device communication. Conventional dynamic barcode systems adopt a rule-based approach to recognize the color barcode stream in the receiver, which is empirical, inflexible, and lacks self-adaptiveness. In this paper, we propose a novel solution framework for color barcode stream recognition basing on machine learning techniques. By including a number of training frames into the barcode stream to build a classification model, the proposed framework can achieve high accuracy in color barcode recognition and is adaptive to different ambient lighting conditions (without sudden changes during transmission). A semi-supervised learning approach basing on the Mixture of Experts (MoE) model is further proposed to reduce the start-up time. We implement MegaLight on both black-white and color barcode systems. Extensive experiments demonstrate that MegaLight can significantly reduce the frame demodulation error and reach up to 3x improvement in system goodput comparing to conventional barcode stream recognition approaches.
Understanding Mobile Tourism Shopping in Pakistan: An Integrating Framework of Innovation Diffusion Theory and Technology Acceptance Model
Authors: Gu Dongxiao , Khan Salman , Khan Ikram Ullah , Khan Safeer Ullah
Published: June 2019

Consumer adoption of mobile-based tourism shopping is an emerging but overlooked area in tourism research. Given the paybacks and potential scope of this new channel, this study attempts to bridge the gap by proposing a multimediation model investigating mobile tourism shopping (MTS) in a developing country, Pakistan. In particular, we applied structural equation modeling through partial-least-squares structural equation modeling (PLS-SEM) on 396 responses collected from mobile respondents who recently purchased tourism products using a mobile device(s). It was discovered that social presence, directly and indirectly, influences tourist intentions towards MTS. The results further show that the tourists’ perception of compatibility and relative advantages of MTS have insignificant influence on their intention to accept a mobile device(s) for tourism shopping. The findings and implications of the study furnish new vistas to research discourse and managerial significance. Economically, this research contributes to knowledge that could increase income and create jobs in the host country.
Frequency of Hypoglycaemia after Different Bariatric Surgical Procedures
Authors: Brix Johanna Maria , Kopp Hans-Peter , Höllerl Florian , Schernthaner Gerit Holger , Ludvik Bernhard , Schernthaner Guntram
Published: June 2019

Objectives: The frequency of postprandial hypoglycaemia after different operative procedures of bariatric surgery (BS) is unknown, although this complication is potentially dangerous. Predictors and severity of hypoglycaemia after Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy, and gastric banding were investigated in a large prospective study. Methods: This study was performed at an excellence centre for BS at a tertiary care institution. Data of 333 patients (mean BMI: 44.9 ± 9.6 kg/m2; mean age: 40 ± 10 years; 80.7% women) were analysed in a prospective study with a 2-year observation period after BS. All patients underwent a 2-hour oral glucose tolerance test (OGTT) with measurements of blood glucose (BG) and insulin. For the purpose of this study, hypoglycaemia was defined as a post-challenge BG <2.8 mmol/L during the OGTT. Results: 72 (25.6%) of 281 patients showed post-challenge hypoglycaemia after surgery. Hypoglycaemia was different after various procedures: 32.6% of patients after RYGB, 22.6% after sleeve gastrectomy, but only 2.3% after gastric banding had hypoglycaemia. In the whole group, patients with hypoglycaemia had lost more weight (p = 0.013), had a slightly greater decrease in BMI (p = 0.037), a greater change in 2-hour post-challenge BG (p = 0.001), and a smaller change in 1-hour post-challenge insulin (p = 0.004) compared to patients without hypoglycaemia. Conclusion: This prospective study shows a higher prevalence of severe hypoglycaemia (25.6%) after BS than anticipated from retrospective registers. A systematic evaluation of glucose and insulin levels by OGTT 2 years post-surgery may help to identify patients at increased risk for symptomatic and asymptomatic hypoglycaemia.
The Contribution of Food Consumption to Well-Being
Authors: Holder Mark D.
Published: June 2019

The newly emerging field of positive psychology focuses on the positive facets of life, including happiness, life satisfaction, personal strengths, and flourishing. Research in this field has empirically identified many important benefits of enhanced well-being, including improvements in blood pressure, immune competence, longevity, career success, and satisfaction with personal relationships. Recognizing these benefits has motivated researchers to identify the correlates and causes of well-being to inform them in the development and testing of strategies and interventions to elevate well-being. As positive psychology researchers throughout the world have turned their attention toward facets of food intake, a consensus is developing that the consumption of healthy foods can enhance well-being in a dose-response fashion. The link between unhealthy foods and well-being is less clear. Some studies suggest that under certain conditions, fast food may increase happiness, though other studies demonstrate that fast food can indirectly undermine happiness. The positive impact of food consumption on well-being is not limited to what people consume but extends to how they consume it and social factors related to eating. Though the research suggests that our food intake, particularly fruits and vegetables, increases our well-being, this research is in its infancy. Research specifically focused on subpopulations, including infants and pregnant mothers, is mostly lacking, and the mechanisms that underlie the relationship between food consumption and well-being remain to be elucidated.
Ubiquitous Promoters Direct the Expression of Fatty Acid Delta-6 Desaturase from Nile Tilapia (Oreochromis niloticus) in Saccharomyces cerevisiae
Authors: Jangprai Araya , Boonanuntanasarn Surintorn
Published: June 2019

In general, promoters have significant influence on recombinant protein production. Herein, we compared the performance of actin (pACT), phosphoglycerate kinase (pPGK), and translational elongation factor (pTEF) promoters for driving the expression of fatty acid delta-6 (Δ6) desaturase from Nile tilapia (Oreochromis niloticus; Oni-fads2) in Saccharomyces cerevisiae. Our results showed that by applying real-time RT-PCR, the highest level of Oni-fads2 mRNA was observed in S. cerevisiae carrying the expression vector driven by pTEF promoters. Exogenous substrate C18:2n-6 was used to determine Δ6 activity by quantitatively determining the C18:3n-6 product. The results showed that highest Δ6 desaturation was observed when using pTEF as a promoter. Recombinant S. cerevisiae cells expressing Oni-fads2 driven by pTEF were tested with the substrate C18:3n-3, and Δ6 desaturation efficiently converted C18:3n-3 to C18:4n-3. Furthermore, crude extract of recombinant yeast also exhibited Δ6 activity. Thus, recombinant S. cerevisiae cells expressing Oni-fads2 driven by the pTEF promoter have potential as a yeast factory for the sustainable production of long-chain polyunsaturated fatty acids.
Characterizing the Effect of Automated Cell Sorting Solutions on Cytomorphological Changes
Authors: Ikeda Katsuhide , Sato Shouichi , Chigira Hiroshi , Shibuki Yasuo , Hiraoka Nobuyoshi
Published: June 2019

Introduction: Liquid-based cytology has become a widely adopted, automated screening system for gynecologic and nongynecologic cytology. Automated screening systems function by distinguishing atypical cells based on their cytoplasmic and nuclear areas, densitometric measurement, and so on. However, the morphological influence of the washing solution has not been fully considered. Here, we examined the morphological effect and temporal change resulting from saving the cytologic samples in various solutions. Methods: Cytologic specimens were obtained from the ascites (AS) of patients with peritoneal cancer. Various solutions of a physiological saline, a Ringer’s solution, a low-molecular dextran L injection, VOLUVEN 6% solution, MIXID L injection (ML), RPMI-1640 medium, and horse serum (HS) were added to aliquot sediments. All samples were refrigerated at 4°C, and aliquots were subsequently processed at specific time points (0, 1, 2, 4, 7, and 14 days). For all samples, cytoplasmic and nuclear size of the Papanicolaou-stained specimens were measured. Results: In terms of cytoplasmic and nuclear areas, samples stored in ML and HS showed no significant difference compared to the AS sample; in contrast, the other samples were significantly larger in both cytoplasmic and nuclear areas than the AS sample. In examining the temporal change among the solutions, we found that the cytoplasms and nuclei became small over the time course for all of the tested solutions. Conclusion: We showed that cells swell in the solution after 1 h of storage and contract as time progresses. Together, our findings have important implications for how mathematical analysis is applied during the automated screening process.