bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplemental Material: What drives large-scale glacier detachments? Insights from Flat Creek glacier, St. Elias Mountains, Alaska
Authors: Jacquemart M.
Published: May 2020

Descriptions of datasets, analysis methods, and processing code.
Supplemental Material: Using speleothems to constrain late Cenozoic uplift rates in karst terranes
Authors: Engel John
Published: May 2020

Three supplemental tables providing the specific geochronological data produced in this study.
Supplemental Material: Prominent thermal anomalies in the mantle transition zone beneath the Transantarctic Mountains
Authors: Emry E.L.
Published: May 2020

Additional information about methods and results (Appendices S1 and S2, Figures S1–S8, and Datasets S1 and S2)
Supplemental Material: Modulation of zircon solubility by crystal–melt dynamics
Authors: Szymanowski Dawid
Published: May 2020

Analytical data, descriptions of units in Figure 3, details of MELTS modeling, and additional diagrams.
Supplemental Material: Uplift and exhumation in Haida Gwaii driven by terrane translation and transpression along the southern Queen Charlotte fault, Canada
Authors: Schoettle-Greene Philip
Published: May 2020

Detailed thermal modeling results, themochronometry data, and animations of plate reconstructions.
Supplemental Material: Experimental evidence for crustal control over seismic fault segmentation
Authors: Lefevre Marthe
Published: May 2020

Experimental set-up, model validation, materials properties, experiment results, and seismogenic thickness values.
Supplemental Material: Pleistocene organic matter modified by the Hiawatha impact, northwest Greenland
Authors: Garde Adam
Published: May 2020

Microphotographs, Raman methodology, Raman spectra and SEM-EDS spectrum supporting the close association between shocked quartz, impact glass, and organic matter described in the text.
Supplemental Material: Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data
Authors: Shah A.K.
Published: May 2020

Shapefiles providing locations of faults and folds determined from magnetic and seismic data, or just magnetic data, with projection NAD27-UTM5N.
Supplemental Material: Climate-driven late Quaternary fan surface abandonment in the NW Himalaya
Authors: Orr Elizabeth N.
Published: May 2020

Sample details of local and regional chronological datasets
Effects of a multifactorial ecosustainable isocaloric diet on liver fat in patients with type 2 diabetes: randomized clinical trial
Authors: Della Pepa Giuseppe , Vetrani Claudia , Brancato Valentina , Vitale Marilena , Monti Serena , Annuzzi Giovanni , Lombardi Gianluca , Izzo Anna , Tommasone Marianna , Cipriano Paola , Clemente Gennaro , Mirabelli Peppino , Mancini Marcello , Salvatore Marco , Riccardi Gabriele , Rivellese Angela Albarosa , Bozzetto Lutgarda
Published: May 2020

Introduction

Treatment options for non-alcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes (T2D) are still a matter of debate. We compared the effects of a diet including different components versus a proven beneficial diet rich in monounsaturated fatty acids (MUFAs) on liver fat in T2D.

Research design and methods

According to a parallel design, 49 individuals with T2D, overweight/obese, with high waist circumference, 35–75 years-old, in satisfactory blood glucose control with diet or drugs not affecting liver fat content, were randomly assigned to an 8-week isocaloric intervention with a MUFA diet (n=26) or a multifactorial diet rich in fiber, MUFA, n-6 and n-3 polyunsaturated fatty acids, polyphenols, and vitamins D, E, and C (n=23). Before and after the intervention, liver fat content was evaluated by proton magnetic resonance spectroscopy (1H-MRS).1H-MRS complete data were available for n=21 (MUFA diet) and n=18 (multifactorial diet) participants.

Results

Adherence to dietary interventions was optimal. No significant differences between groups in body weight reduction, plasma glycated hemoglobin, insulin, glucose, lipids and liver enzymes were observed. Liver fat significantly decreased after both the multifactorial diet (9.18%±7.78% vs 5.22%±4.80%, p=0.003) and the MUFA diet (9.47%±8.89% vs 8.07%±8.52%, p=0.027) with a statistically significant difference between changes either in absolute terms (−4.0%±4.5% vs −1.4%±2.7%, p=0.035) or percent (−40%±33% vs −19%±25%, p=0.030).

Conclusions

An isocaloric multifactorial diet including several beneficial dietary components induced a clinically relevant reduction of liver fat in patients with T2D, more pronounced than that induced by simply replacing saturated fat with MUFA. This suggests that the ‘optimal diet’ for NAFLD treatment in T2D should be based on synergic actions of different dietary components on multiple pathophysiological pathways.

Trial registration number

NCT03380416.
Cardiovascular risk profiles and the uptake of the NHS Healthcheck programme in male prisoners in six UK prisons: an observational cross-sectional survey
Authors: Packham Christopher , Butcher Elizabeth , Williams Marie , Miksza Joanne , Morriss Richard , Khunti Kamlesh
Published: May 2020

Introduction

Half of all deaths in custody are due to natural causes, the most common being cardiovascular disease (CVD). National Health Service Healthchecks should be available to all eligible prisoners; it is not clear who receives them. Mental health issues are common in prisoners and may affect how healthcare interventions should be delivered. Current policy is to offer Healthchecks to those serving over 2 years in prison.

Objectives, methods, setting and design

An observational cross-sectional survey in six male prisons in England between September 2017 and January 2019 in prisoners aged 35–74 to identify who was eligible for a Healthcheck and compare CVD risk data with those that were not, and factors associated with uptake.

Outcome measures

Characteristics of those accepting a Healthcheck were compared with those declining. Assessments of anxiety and depression were compared with CVD risk factors.

Results

1207 prisoners completed a Healthcheck. 21.8% of prisoners were ineligible due to existing comorbidities. 76.4% of those invited took up a Healthcheck, and of those, 12.1% were found to have new significant CVD comorbidity. CVD risk was similar to community levels but this population was 10 years younger. Definite case-level depression or anxiety was present in 20.7% and 18.0%, respectively, of participants. An association was found between ethnicity and those invited (p=0.023, φ=0.1) and accepting (p=0.008, φ=0.1) a Healthcheck. 9.7% of prisoners serving less than 2 years had CVD risk scores of 10% or more, and had similar CVD risk profiles but much higher levels of anxiety (p<0.001, φ=0.2) or depression (p=0.009, φ=0.2) than those serving 2 years or more.

Conclusion

Cardiovascular risk was comparable with community rates and in some prisons, much higher. Rates of anxiety and depression were high. The national policy for selecting prisoners for Healthchecks may leave many high-risk prisoners without appropriate cardiovascular preventative assessments.
Clinical factors associated with progression to dementia in people with late-life depression: a cohort study of patients in secondary care
Authors: Peakman Georgia , Karunatilake Nishshanka , Seynaeve Mathieu , Perera Gayan , Aarsland Dag , Stewart Robert , Mueller Christoph
Published: May 2020

Objectives

Depression can be a prodromal feature or a risk factor for dementia. We aimed to investigate which clinical factors in patients with late-life depression are associated with a higher risk of developing dementia and a more rapid conversion.

Design

Retrospective cohort study.

Setting

South London and Maudsley NHS Foundation Trust (SLaM) secondary mental healthcare services.

Participants

The SLaM Clinical Record Interactive Search was used to retrieve anonymised data on 3659 patients aged 65 years or older who had received a diagnosis of depression in mental health services and had been followed up for at least 3 months.

Outcome measures

Predictors of development of incident dementia were investigated, including demographic factors, health status rated on the Health of the National Outcome scale for older people (HoNOS65+), depression recurrence and treatments including psychotropic drugs and cognitive behavioural therapy (CBT).

Results

In total, 806 (22.0%) patients developed dementia over a mean follow-up time of 2.7 years. Significant predictors of receiving a dementia diagnosis in fully adjusted models and after accounting for multiple comparisons were older age (adjusted HR=1.04, 95% CI 1.03 to 1.06 per year difference from sample mean) and the HoNOS65+ subscale measuring cognitive problems (HR=4.72, 95% CI 3.67 to 6.06 for scores in the problematic range). Recurrent depressive disorder or past depression (HR=0.65, 95% CI 0.55 to 0.77) and the receipt of CBT (HR=0.73 95% CI 0.61 to 0.87) were associated with a lower dementia risk. Over time, hazards related to age increased and hazards related to cognitive problems decreased.

Conclusions

In older adults with depression, a higher risk of being subsequently diagnosed with dementia was predicted by higher age, new onset depression, severity of cognitive symptoms and not receiving CBT. Further exploration is needed to determine whether the latter risk factors are responsive to interventions.
A Qualitative study assessing organisational readiness to implement caregiver support programmes in Ontario, Canada
Authors: Tseung Victrine , Jaglal Susan , Salbach Nancy Margaret , Cameron Jill I
Published: May 2020

Objective

To qualitatively explore factors affecting implementation of caregiver support programmes in healthcare institutions in a regional stroke system.

Design

A qualitative descriptive study with the Ontario Stroke System (OSS) was conducted. Data were collected through focus groups and in-depth interviews. Transcripts were coded and analysed using inductive thematic analysis.

Setting

Regional Stroke System, Ontario, Canada.

Participants

OSS stakeholders including medical directors, executives, programme directors, education coordinators, rehabilitation and community and long-term care specialists, primary care leaders and healthcare professionals.

Intervention

Not applicable.

Main outcome measures

Data collection explored perceptions of the need for caregiver support programmes and factors that may affect their implementation.

Results

Four focus groups (n=43) and 29 interviews were completed. Analyses identified themes related to (1) evidence that a caregiver programme will improve health and health system outcomes, (2) personnel requirements, (3) barriers associated with current billing and referral processes and (4) integration with current practice and existing workflow processes.

Conclusions

Implementation strategies to adopt caregiver programmes into clinical practice should incorporate evidence and consider personnel and existing workflow processes.
Predictors of non-fatal violence or assault among adolescents in rural Bangladesh: cross-sectional study
Authors: Osaghae Ikponmwosa , Bhuiyan Md Al-Amin , Alonge Olakunle
Published: May 2020

Objective

To determine the predictors of non-fatal violence or assault among adolescents in rural Bangladesh to inform evidence-based interventions.

Design

Cross-sectional study.

Setting

Household survey and national census in 51 unions of rural Bangladesh.

Participants, methods and main outcome

213 782 adolescents aged 11–19 years who reported violence during a population-based survey in 2013. We used logistic regression to determine the prevalence of factors that predict non-fatal forms of violence or assaults among adolescents. Assault or violence was defined as all injuries inflicted directly by another person or resulting from collateral impact over a 6-month recall period.

Results

457 (0.21%) cases of violence or assault were reported. The adjusted prevalence ratio (PR) of violence was lower among female adolescents compared with males (PR: 0.60, 95% CI 0.47 to 0.78, p<0.001). Compared with the lowest socioeconomic quintile, being in a higher quintile was associated with lower prevalence of violence, with a 39% decrease in the adjusted prevalence of violence among adolescents in highest compared with lowest socioeconomic index (PR: 0.61, 95% CI 0.44 to 0.84). The adjusted prevalence of violence in Chandpur and Comilla districts was 7.30 times and 7.27 times higher respectively than the prevalence of violence in Sirajganj (PR: 7.30, 95% CI 4.07 to 13.10 and PR: 7.27, 95% CI 3.56 to 14.84, respectively). There was no significant difference in the adjusted prevalence of violence occurring in school compared with home (PR: 1.19, 95% CI 0.85 to 1.69).

Conclusion

Male adolescents may be at an increased risk of suffering violence, and socioeconomic factors and place (districts) are strong predictors of adolescent violence among a selected population in rural Bangladesh. These findings are important in guiding interventions to address the burden of violence among adolescents in communities with similar demographics as our study population. Further research is needed to identify the actual burden of violence among adolescents at national level and to establish an effective violence prevention programme across Bangladesh.
Work effort, readability and quality of pharmacy transcription of patient directions from electronic prescriptions: a retrospective observational cohort analysis
Authors: Zheng Yifan , Jiang Yun , Dorsch Michael P , Ding Yuting , Vydiswaran V G Vinod , Lester Corey A
Published: May 2020

Background

Free-text directions generated by prescribers in electronic prescriptions can be difficult for patients to understand due to their variability, complexity and ambiguity. Pharmacy staff are responsible for transcribing these directions so that patients can take their medication as prescribed. However, little is known about the quality of these transcribed directions received by patients.

Methods

A retrospective observational analysis of 529 990 e-prescription directions processed at a mail-order pharmacy in the USA. We measured pharmacy staff editing of directions using string edit distance and execution time using the Keystroke-Level Model. Using the New Dale-Chall (NDC) readability formula, we calculated NDC cloze scores of the patient directions before and after transcription. We also evaluated the quality of directions (eg, included a dose, dose unit, frequency of administration) before and after transcription with a random sample of 966 patient directions.

Results

Pharmacy staff edited 83.8% of all e-prescription directions received with a median edit distance of 18 per e-prescription. We estimated a median of 6.64 s of transcribing each e-prescription. The median NDC score increased by 68.6% after transcription (26.12 vs 44.03, p<0.001), which indicated a significant readability improvement. In our sample, 51.4% of patient directions on e-prescriptions contained at least one pre-defined direction quality issue. Pharmacy staff corrected 79.5% of the quality issues.

Conclusion

Pharmacy staff put significant effort into transcribing e-prescription directions. Manual transcription removed the majority of quality issues; however, pharmacy staff still miss or introduce following their manual transcription processes. The development of tools and techniques such as a comprehensive set of structured direction components or machine learning–based natural language processing techniques may help produce clear directions.
Usability assessment of Versius, a new robot-assisted surgical device for use in minimal access surgery
Authors: Haig Fiona , Medeiros Ana Cristina Barbosa , Chitty Karen , Slack Mark
Published: May 2020

Objectives

Versius is a teleoperated surgical robotic system intended for use in minimal access surgery. This study aimed to validate the safety and effectiveness of the Versius user interface in the hands of trained users and identify and address the causes of any user errors.

Design

Surgical teams completed a commercially representative training program over 3.5 days. After training was completed, the usability-related aspects of the system were assessed.

Setting

A simulated operating room using a cadaveric model.

Participants

Surgical teams consisting of a lead surgeon, assistant surgeon, scrub nurse and circulating nurse.

Main outcome measures

Usability-related aspects of the system were assessed through the completion of critical and non-critical tasks. A critical task was defined according to the Food and Drug Administration’s definition, as a user task which, if performed incorrectly or not performed at all, would or could cause serious harm to the patient or user, where harm is defined to include compromised medical care.

Results

In total, 17 surgical teams participated in the study and all were experienced in laparoscopic surgery. The number of robotic surgeries performed by the participants per month ranged from 0 to 100. Surgical specialties were similarly represented from obstetrics and gynecology, colorectal, urology and upper gastrointestinal. No critical task failures were observed. Of all the tasks completed, 98% were recorded as a pass or a pass with difficulty.

Conclusions

These results demonstrate that in a simulated clinical setting, Versius can be safely used by both laparoscopically and robotically trained healthcare professionals. These results support the progression to assessment of Versius in preclinical studies.
Analytical validation of the Immunoscore and its associated prognostic value in patients with colon cancer
Authors: Marliot Florence , Chen Xiaoyi , Kirilovsky Amos , Sbarrato Thomas , El Sissy Carine , Batista Luciana , Van den Eynde Marc , Haicheur-Adjouri Nacilla , Anitei Maria-Gabriela , Musina Ana-Maria , Scripcariu Viorel , Lagorce-Pagès Christine , Hermitte Fabienne , Galon Jérôme , Fieschi Jacques , Pagès Franck
Published: May 2020

Background

New and fully validated tests need to be brought into clinical practice to improve the estimation of recurrence risk in patients with colon cancer. The aim of this study was to assess the analytical performances of the Immunoscore (IS) and show its contribution to prognosis prediction.

Methods

Immunohistochemical staining of CD3+ and CD8+ T cells on adjacent sections of colon cancer tissues were quantified in the core of the tumor and its invasive margin with dedicated IS modules integrated into digital pathology software. Staining intensity across samples collected between 1989 and 2016 (n=595) was measured. The accuracy of the IS workflow was established by comparing optical and automatic counts. Analytical precision of the IS was evaluated within individual tumor block on distant sections and between eligible blocks. The IS interlaboratory reproducibility (n=100) and overall assay precision were assessed (n=3). Contribution of the IS to prediction of recurrence based on clinical and molecular parameters was determined (n=538).

Results

Optical and automatic counts for CD3+ or CD8+ were strongly correlated (r=0.94, p<0.001 and r=0.92, p<0.001, respectively). CD3 and CD8 staining intensities were not altered by the age of the tumor block over a period of 30 years. Neither the position of tested tissue sections within a tumor block nor the selection of the tissue blocks affected the IS. Reproducibility of the IS was not affected by multiple variables (eg, antibody lots, DAB revelation kits, immunohistochemistry automates and operators). Interassay repeatability of the IS was 100% and interlaboratory reproducibility between two testing centers was 93%. Finally, in a case series of patients with stage II–III colon cancer, the relative proportion of variance for time to recurrence was greatest for the IS (53% of prognostic variability) in a model that included IS, T-stage, microsatellite instability status and total number of lymph nodes.

Conclusion

IS is a robust and validated clinical assay leveraging immune scoring to predict recurrence risk of patient with localized colon cancer. The strong and independent prognostic value of IS should pave the way for it use in clinical practice.
Efficacy and safety of camrelizumab combined with apatinib in advanced triple-negative breast cancer: an open-label phase II trial
Authors: Liu Jieqiong , Liu Qiang , Li Ying , Li Qian , Su Fengxi , Yao Herui , Su Shicheng , Wang Quanren , Jin Liang , Wang Ying , Lau Wan Yee , Jiang Zefei , Song Erwei
Published: May 2020

Background

Previous trials showed that antiangiogenesis or anti-programmed death protein 1/programmed death ligand 1 (PD-1/PD-L1) monotherapy only showed marginal effect in triple-negative breast cancer (TNBC). Preclinical studies demonstrated that antiangiogenic therapy could sensitize breast cancer to PD-1/PD-L1 blockade via reprogramming tumor microenvironment. Combinational treatment of checkpoint blockade and antiangiogenesis for TNBC has not been reported.

Methods

Patients with advanced TNBC with less than three lines of systemic therapy were enrolled in an open-label, non-comparative, two-arm, phase II trial at Sun Yat-sen Memorial Hospital. Camrelizumab (intravenously every 2 weeks) with apatinib orally at either continuous dosing (d1–d14) or intermittent dosing (d1–d7) was given until disease progression or unacceptable toxicities. Primary endpoint was objective response rate (ORR).

Results

From January 2018 to April 2019, 40 patients were enrolled, including 10 in the apatinib intermittent dosing cohort and 30 in the apatinib continuous dosing cohort. The ORR was 43.3% (13 of 30) in the continuous dosing cohort, while no objective response was observed in the intermittent dosing cohort. The disease control rate was 63.3% (19 of 30) in the apatinib continuous dosing cohort, and 40.0% (4 of 10) in the apatinib intermittent dosing cohort, respectively. The median progression-free survival (PFS) was 3.7 (95% CI 2.0 to 6.4) months and 1.9 (95% CI 1.8 to 3.7) months in the continuous dosing and intermittent dosing cohort, respectively. In the continuous dosing cohort, the median PFS of patients with partial response (8.3 months, 95% CI 5.9 to not reached) was significantly longer than that of patients with stable disease/progressive disease/not evaluable (2.0 months, 95% CI 1.7 to 3.0). The most common adverse events (AEs) included elevated aspartate aminotransferase/alanine aminotransferase and hand-foot syndrome. Overall, 26.7% and 20.0% of patients experienced grade ≥3 AEs in the continuous dosing and intermittent dosing cohort, respectively. In the continuous dosing cohort, a high percentage of baseline tumor-infiltrating lymphocytes (>10%) was associated with higher ORR and favorable PFS (p=0.029, 0.054, respectively).

Conclusions

The ORR by this chemo-free regimen was dramatically higher than previously reported ORR by anti-PD-1/PD-L1 antibody or apatinib monotherapy. Camrelizumab combined with apatinib demonstrated favorable therapeutic effects and a manageable safety profile in patients with advanced TNBC.

Trial registration number

NCT03394287.
Grass as a linear gastrointestinal foreign body obstruction in four dogs
Authors: McCagherty Joanna , Yool Donald , Earley Naomi F , Woods Sam
Published: May 2020

Four dogs presented with linear gastrointestinal foreign body (FB) obstruction caused by impacted grass fibres. The material had become anchored within the pylorus in three dogs, causing necrosis and perforation of the mesenteric border of the affected intestinal segment. Gastrotomy and intestinal resection and anastomosis were performed. The fourth case presented acutely with no intestinal necrosis or perforation, with the fibres removed via enterotomy. One dog suffered severe postoperative ileus that failed to respond to medical management. Continued deterioration prompted euthanasia 12 days postoperatively. The other three dogs survived and were discharged without complication. Grass has not previously been reported as a cause of linear gastrointestinal obstruction in dogs. It has, however, the potential to cause severe necrosis and perforation of the intestine and should be recognised as a potential linear FB in dogs.
Business as usual: macrolichen community response to the resilience of spruce–fir forests to beetle disturbance in northwestern Colorado
Authors: Freundlich Anna E. , Holt Emily A.
Published: May 2020

Over the past few decades, spruce beetles (Dendroctonus rufipennis Kirby) have drastically altered spruce–fir forests in western North America. Past research has shown that forest conditions (i.e., canopy openings, amounts of coarse woody material) change after spruce beetle disturbance, but little work has studied the impacts of these changes on the resident biotic communities. Even less research has investigated how spruce beetle disturbance affects lichen communities, which we anticipated as benefiting them due to canopy opening and increased woody material availability. We studied macrolichen community structure, including abundance and community composition, and habitat characteristics in areas with significant spruce beetle damage, as first detected between 1996 and 2017 in northwestern Colorado. We found few habitat differences among beetle disturbance classes that reflected varying time since infestation, and only the most recently affected plots (2012–2017) had significantly different lichen community structure relative to other sampled areas. We observed that the spruce–fir forests within our study exhibited ecological resilience to beetle outbreaks, and we did not measure differences in the amount of canopy openings or amounts of coarse woody material. Subsequently, the lack of differential lichen community response was not surprising.
PepMusic: motivational qualities of songs for daily activities
Authors: Kim Yongsung , Aiello Luca Maria , Quercia Daniele
Published: May 2020

Music can motivate many daily activities as it can regulate mood, increase productivity and sports performance, and raise spirits. However, we know little about how to recommend songs that are motivational for people given their contexts and activities. As a first step towards dealing with this issue, we adopt a theory-driven approach and operationalize the Brunel Music Rating Inventory (BMRI) to identify motivational qualities of music from the audio signal. When we look at frequently listened songs for 14 common daily activities through the lens of motivational music qualities, we find that they are clustered into three high-level latent activity groups: calm, vibrant, and intense. We show that our BMRI features can accurately classify songs in the three classes, thus enabling tools to select and recommend activity-specific songs from existing music libraries without any input required from user. We present the results of a preliminary user evaluation of our song recommender (called PepMusic) and discuss the implications for recommending songs for daily activities.
Towards Better Crowdsourced Software Testing Process
Authors: Alyahya Sultan , Alsayyari Manar
Published: May 2020

Crowdsourced software testing (CST) is an emerging trend in software testing. Companies and developers assign testing tasks through CST platforms to thousands of online testers. Currently, CST platform managers are trying to find and resolve challenges in order to reach the best CST practice. Many features have been applied by CST platforms to improve CST activities, including notification emails, online chat rooms, forums and, most importantly, a CST platform dashboard to view all testing projects and tasks; these features have enabled CST to operate efficiently. Still, CST users find it difficult to stay abreast of test project updates, maintain their motivation, and avoid frustration. This aligns with the increasing studies in the literature that call for more efficient solutions to support CST process. This research aims to support CST by searching for potential process limitations and overcoming them. In order to do so, a five-stage approach is used: first, the current process of CST is investigated through reviewing 15 CST platforms. Second, the review has resulted in identifying eight possible activities to improve CST; among them six have been selected after a survey distributed to 30 domain experts in Stage 3. In Stage 4, we have designed and implemented five process models in a web-based system that can fulfill the requirements of the six activities identified earlier. In Stage 5, we have evaluated these process models through interviews with representatives of two CST platforms and an expert tester, and through making scenario-based evaluation with 20 domain experts who used the system and rated the value of the processes. The results show that the new improvements are sound and can strengthen the CST practice.
Symbolic Disintegration with a Variety of Base Measures
Authors: Narayanan Praveen , Shan Chung-chieh
Published: May 2020

Disintegration is a relation on measures and a transformation on probabilistic programs that generalizes density calculation and conditioning, two operations widely used for exact and approximate inference. Existing program transformations that find a disintegration or density automatically are limited to a fixed base measure that is an independent product of Lebesgue and counting measures, so they are of no help in practical cases that require tricky reasoning about other base measures. We present the first disintegrator that handles variable base measures, including
discrete-continuous mixtures
,
dependent products
, and
disjoint sums
. By analogy with type inference, our disintegrator can check a given base measure as well as infer an unknown one that is principal. We derive the disintegrator and prove it sound by equational reasoning from semantic specifications. It succeeds in a variety of applications where disintegration and density calculation had not been previously mechanized.
SCeVE
Authors: Vellingiri Shanthi , McMahan Ryan P. , Prabhakaran Balakrishnan
Published: May 2020

Authoring a collaborative, interactive Mixed Reality (MR) tour requires flexible design and development of various software modules for tasks such as managing geographically distributed participants, adaptable travel and virtual camera techniques, data logging for assessment of the incorporated techniques, as well as for evaluating the Quality of Experiences (QoE). In most cases, authors might have to develop all these software modules, instead of focusing only on the virtual environment design. In this article, we propose SCeVE, a component-based framework that supports flexible design and authoring of interactive MR tours by offering ease of access to four major design choices: (i)
S
ynchronization, (ii)
C
ollaborative
e
xploration, (iii)
V
isualization, and (iv)
E
valuation. Based on tour requirements, an author can access one or more
components (or software libraries)
of design choices via
SCeVE’s API (Application Programming Interface) services
, as demonstrated by the two case studies on group travel in a plant walk MR tour.

SCeVE framework is innovative in the sense that it facilitates group travel in virtual environments involving “live” models of participants from geographically distributed sites. SCeVE empowers authors to focus only on the design of the required virtual environments. They can quickly build a diverse set of collaborative MR tours by utilizing the flexibility of SCeVE in terms of the various available options for traveling, rendering on multiple devices, and virtual camera viewpoint computation strategies. By providing data logs of various components, SCeVE facilitates performance evaluation of the various strategies used as well as the user experience in collaborative MR tours. SCeVE is designed in an extensible manner, allowing authors to add devices and software services as additional components.
EGroupNet
Authors: Duan Mingxing , Li Kenli , Ouyang Aijia , Win Khin Nandar , Li Keqin , Tian Qi
Published: May 2020

Although age estimation is easily affected by smiling, race, gender, and other age-related attributes, most of the researchers did not pay attention to the correlations among these attributes. Moreover, many researchers perform age estimation from a wide range of age; however, conducting an age prediction over a narrow age range may achieve better results. This article proposes a hierarchic approach referred to as EGroupNet for age prediction. The method includes two main stages, i.e., feature enhancement via excavating the correlations among age-related attributes and age estimation based on different age group schemes. First, we apply the multi-task learning model to learn multiple face attributes simultaneously to obtain discriminative features of different attributes. Second, we project the outputs of fully connected layers of several subnetworks into a highly correlated matrix space via the correlation learning process. Third, we classify these enhanced features into narrow age groups using two Extreme Learning Machine models. Finally, we make predictions based on the results of the age groups mergence. We conduct a large number of experiments on MORPH-II, LAP-2016 dataset, and Adience benchmark. The mean absolute errors of the two different settings on MORPH-II are 2.48 and 2.13 years, respectively; the normal score (ε) on the LAP-2016 dataset is 0.3578; and the accuracy of age prediction on Adience benchmark is 0.6978.
Listen, Look, and Find the One
Authors: Wang Xiao , Liu Wu , Chen Jun , Wang Xiaobo , Yan Chenggang , Mei Tao
Published: May 2020

Person search with one portrait, which attempts to search the targets in arbitrary scenes using one portrait image at a time, is an essential yet unexplored problem in the multimedia field. Existing approaches, which predominantly depend on the visual information of persons, cannot solve problems when there are variations in the person’s appearance caused by complex environments and changes in pose, makeup, and clothing. In contrast to existing methods, in this article, we propose an associative multimodality index for person search with face, body, and voice information. In the offline stage, an associative network is proposed to learn the relationships among face, body, and voice information. It can adaptively estimate the weights of each embedding to construct an appropriate representation. The multimodality index can be built by using these representations, which exploit the face and voice as long-term keys and the body appearance as a short-term connection. In the online stage, through the multimodality association in the index, we can retrieve all targets depending only on the facial features of the query portrait. Furthermore, to evaluate our multimodality search framework and facilitate related research, we construct the Cast Search in Movies with Voice (CSM-V) dataset, a large-scale benchmark that contains 127K annotated voices corresponding to tracklets from 192 movies. According to extensive experiments on the CSM-V dataset, the proposed multimodality person search framework outperforms the state-of-the-art methods.
Write Back Energy Optimization for STT-MRAM-based Last-level Cache with Data Pattern Characterization
Authors: Ni Jiacheng , Liu Keren , Wu Bi , Zhao Weisheng , Cheng Yuanqing , Zhang Xiaolong , Wang Ying
Published: May 2020

Traditional memory technologies face severe challenges in meeting the ever-increasing power and memory bandwidth requirements for high-performance computing and big-data analyses. Several emerging memory technologies are promising as the replacements of SRAM or DRAM. Among them, STT-MRAM can be used to replace SRAM as the last-level cache (LLC). However, it suffers from high write energy and latency. In this article, we investigate data patterns written from SRAM-based upper-level cache to STT-MRAM-based LLC to explore the write energy reduction potential. Depending on the data layout within a cache line, redundant bits can be identified and eliminated from write back operations to save STT-MRAM write energy. We also propose a dynamic profiling method to accommodate different application characteristics. The extensive simulation results show that write energy can be saved by 37.05% ∼ 38.89% for static profiling and 19.76% ∼ 34.29% for dynamic profiling.
Meta-path Augmented Sequential Recommendation with Contextual Co-attention Network
Authors: Huang Xiaowen , Qian Shengsheng , Fang Quan , Sang Jitao , Xu Changsheng
Published: May 2020

It is critical to comprehensively and efficiently learn user preferences for an effective sequential recommender system. Existing sequential recommendation methods mainly focus on modeling local preference from users’ historical behaviors, which largely ignore the global context information from the heterogeneous information network. This prevents a comprehensive user preference representation. To address these issues, we propose a joint learning approach to incorporate global context with local preferences efficiently. The proposed approach introduces meta-paths from a heterogeneous information network to capture the global context information, and the position-based self-attention mechanism is adopted to model the local preference representation efficiently. Compared with the methods that only consider the local preference, our proposed method takes the advantages of incorporating global context information, which extracts structural features that captures relevant semantics to construct users’ global preference representation for the sequential recommendation. We further adopt a co-attention mechanism to model complex interactions between global context and users’ historical behaviors for better user representations. Quantitative and qualitative experimental evaluations are conducted on nine large-scale Amazon datasets and a multi-modal Zhihu dataset. The promising results demonstrate the effectiveness of the proposed model.
Dual-path Convolutional Image-Text Embeddings with Instance Loss
Authors: Zheng Zhedong , Zheng Liang , Garrett Michael , Yang Yi , Xu Mingliang , Shen Yi-Dong
Published: May 2020

Matching images and sentences demands a fine understanding of both modalities. In this article, we propose a new system to discriminatively embed the image and text to a shared visual-textual space. In this field, most existing works apply the ranking loss to pull the positive image/text pairs close and push the negative pairs apart from each other. However, directly deploying the ranking loss on heterogeneous features (i.e., text and image features) is less effective, because it is hard to find appropriate triplets at the beginning. So the naive way of using the ranking loss may compromise the network from learning inter-modal relationship. To address this problem, we propose the instance loss, which explicitly considers the intra-modal data distribution. It is based on an unsupervised assumption that each image/text group can be viewed as a class. So the network can learn the fine granularity from every image/text group. The experiment shows that the instance loss offers better weight initialization for the ranking loss, so that more discriminative embeddings can be learned. Besides, existing works usually apply the off-the-shelf features, i.e., word2vec and fixed visual feature. So in a minor contribution, this article constructs an end-to-end dual-path convolutional network to learn the image and text representations. End-to-end learning allows the system to directly learn from the data and fully utilize the supervision. On two generic retrieval datasets (Flickr30k and MSCOCO), experiments demonstrate that our method yields competitive accuracy compared to state-of-the-art methods. Moreover, in language-based person retrieval, we improve the state of the art by a large margin. The code has been made publicly available.
Learning Visual Elements of Images for Discovery of Brand Posts
Authors: Gelli Francesco , Uricchio Tiberio , He Xiangnan , Bimbo Alberto Del , Chua Tat-Seng
Published: May 2020

Online Social Network Sites have become a primary platform for brands and organizations to engage their audience by sharing image and video posts on their timelines. Different from traditional advertising, these posts are not restricted to the products or logo but include visual elements that express more in general the values and attributes of the brand, called brand associations. Since marketers are increasingly spending time in discovering and re-posting user generated posts that reflect the brand attributes, there is an increasing demand for such discovery systems. The goal of these systems is to assist brand experts in filtering through online collections of new user media to discover actionable posts, which match the brand value and have the potential to engage the consumers. Driven by this real-life application, we define and formulate a new task of
content discovery for brands
and propose a framework that learns to rank posts for brands from their historical timeline. We design a Personalized Content Discovery (PCD) framework to address the three challenges of high inter-brand similarity, sparsity of brand--post interactions, and diversification of timeline. To learn fine-grained brand representation and to generate explanations for the ranking, we automatically learn visual elements of posts from the timeline of brands and from a set of brand attributes in the domain of marketing. To test our framework we use two large-scale Instagram datasets that contain a total of more than 1.5 million image and video posts from the historical timeline of hundreds of brands from multiple verticals such as food and fashion. Extensive experiments indicate that our model can effectively learn fine-grained brand representations and outperform the closest state-of-the-art solutions.
Montgomery Multiplication for Public Key Cryptography on MSP430X
Authors: Seo Hwajeong , An Kyuhwang , Kwon Hyeokdong , Hu Zhi
Published: May 2020

For traditional public key cryptography and post-quantum cryptography, such as elliptic curve cryptography and supersingular isogeny key encapsulation, modular multiplication is the most performance-critical operation among basic arithmetic of these cryptographic schemes. For this reason, the execution timing of such cryptographic schemes, which may highly determine that the service availability for low-end microprocessors (e.g., 8-bit AVR, 16-bit MSP430X, and 32-bit ARM Cortex-M), mainly relies on the efficiency of modular multiplication on target embedded processors.

In this article, we present new optimal modular multiplication techniques based on the interleaved Montgomery multiplication on 16-bit MSP430X microprocessors, where the multiplication part is performed in a hardware multiplier and the reduction part is performed in a basic arithmetic logic unit (ALU) with the optimal modular multiplication routine, respectively. This two-step approach is effective for the special modulus of NIST curves, SM2 curves, and supersingular isogeny key encapsulation. We further optimized the Montgomery reduction by using techniques for “Montgomery-friendly” prime. This technique significantly reduces the number of partial products. To demonstrate the superiority of the proposed implementation of Montgomery multiplication, we applied the proposed method to the NIST P-256 curve, of which the implementation improves the previous modular multiplication operation by 23.6% on 16-bit MSP430X microprocessors and to the SM2 curve as well (first implementation on 16-bit MSP430X microcontrollers).

Moreover, secure countermeasures against timing attack and simple power analysis are also applied to the scalar multiplication of NIST P-256 and SM2 curves, which achieve the 8,582,338 clock cycles (0.53 seconds@16 MHz) and 10,027,086 clock cycles (0.62 seconds@16 MHz), respectively. The proposed Montgomery multiplication is a generic method that can be applied to other cryptographic schemes and microprocessors with minor modifications.
Kode vicious plays in traffic
Authors: Neville-Neil George V.
Published: May 2020

With increasing complexity comes increasing risk.
Technology adoption
Authors: Denning Peter J. , Lewis Ted G.
Published: May 2020

The S-shaped curve of technology adoption is a welcome recurrence in an otherwise chaotic adoption world.
Learning to Listen... On-Device
Authors: Vipperla Ravichander , Ishtiaq Samin , Li Rui , Bhattacharya Sourav , Leontiadis Ilias , Lane Nicholas D.
Published: May 2020

We have reached an important milestone in Automatic Speech Recognition (ASR) technology, with major industrial AI companies, such as Samsung, Google, Apple, and Amazon releasing high-quality ASR models that run completely on-device, e.g., on consumer smartphones. This is the consequence of giant strides in technological advancements: from making commercial grade ASR systems feasible; to large scale cloud deployments; to the present day state-of-the-art models that run on resource constrained devices.
2019 ACM SIGMOBILE Outstanding Contributions Award: Roy Want
Authors: Helal Sumi
Published: May 2020

Dr. Roy Want has been named the recipient of the 2019 SIGMOBILE Outstanding Contributions Award. For three decades, Roy has been the central figure in context-awareness, which enables mobile systems to adapt their behavior to dynamic variables such as device location and nearby users. Among his earliest contributions was the first mechanism known for context-awareness - the Active Badge system that identified individual mobile users to the infrastructure.
Software-Defined Cooking Using a Microwave Oven
Authors: Jin Haojian , Wang Jingxian , Kumar Swarun , Hong Jason I-An
Published: May 2020

Since their introduction to the consumer market in the 1970s, microwaves have seen widespread adoption and, today, they are the third most popular domestic food heating method (after baking and grilling). Indeed, the original patents for the microwave by Raytheon Inc. in the late 1940s envisioned a universal food cooking instrument for all kinds of food ranging from meat to fish [2]. While microwaves have revolutionized the kitchen since their inception, today's consumer microwaves are mainly used as a blunt heating instrument (e.g., reheating pizzas) rather than a precise cooking equipment (e.g. cooking steak). The potential of microwave cooking is limited by the fact that today's microwaves heat food blindly, resulting in a non-uniform and unpredictable heating distribution [3].
Fluid: Flexible User Interface Distribution for Ubiquitous Multi-Device Interaction
Authors: Oh Sangeun , Kim Ahyeon , Lee Sunjae , Lee Kilho , Jeong Dae R. , Shin Insik , Ko Steven Y.
Published: May 2020

A recent trend in the global mobile/IoT industry is the emergence of next-generation smart devices with various screens, thus mobile/IoT market leaders are highly focused on building a new multi-device computing ecosystem based on such new smart devices. Market leaders are not only simply varying their screen sizes, but also competitively launching new devices equipped with innovative screens like foldable and dual-screen phones. However, the current mobile computing ecosystem is restricted by the single device paradigm that allows a user to interact with only one screen tethered to a single device, limiting the potential that the emerging multi-device computing trend provides.
An interview with Darrell Whitley 2019 ACM fellow
Authors: SIGEVO executive board
Published: May 2020

Professor Darrell Whitley has become one of the 2019 ACM Fellows "Recognized for Far-Reaching Accomplishments that Define the Digital Age".

Members of the SIGEVO executive board sent Darrell a set of questions.