bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical pattern and predictors of stroke treatment outcome among hospitalised patients who had a stroke at Felege Hiwot comprehensive specialised hospital, northwest Ethiopia: a retrospective cross-sectional study
Authors: Kefale Belayneh , Ewunetei Amien , Molla Mulugeta , Tegegne Gobezie Temesgen , Degu Amsalu
Published: December 2020

Objectives

This study aimed to assess the clinical pattern and predictors of stroke treatment outcomes among hospitalised patients in Felege Hiwot comprehensive specialised hospital (FHCSH) in northwest Ethiopia.

Design

A retrospective cross-sectional study.

Setting

The study was conducted medical ward of FHCSH.

Participants

The medical records of 597 adult patients who had a stroke were included in the study. All adult (≥18 years) patients who had a stroke had been admitted to the medical ward of FHSCH during 2015–2019 were included in the study. However, patients with incomplete medical records (ie, incomplete treatment regimen and the status of the patients after treatment) were excluded in the study.

Results

In the present study, 317 (53.1%) were males, and the mean age of the study participants was 61.08±13.76 years. About two-thirds of patients (392, 65.7%) were diagnosed with ischaemic stroke. Regarding clinical pattern, about 203 (34.0%) of patients complained of right-side body weakness and the major comorbid condition identified was hypertension (216, 64.9%). Overall, 276 (46.2%) of them had poor treatment outcomes, and 101 (16.9%) of them died. Patients who cannot read and write (AOR=42.89, 95% CI 13.23 to 111.28, p<0.001), attend primary school (AOR=22.11, 95% CI 6.98 to 55.99, p<0.001) and secondary school (AOR=4.20, 95% CI 1.42 to 12.51, p<0.001), diagnosed with haemorrhagic stroke (AOR=2.68, 95% CI 1.62 to 4.43, p<0.001) and delayed hospital arrival more than 24 hours (AOR=2.92, 95% CI 1.83 to 4.66, p=0.001) were the independent predictors of poor treatment outcome.

Conclusions

Approximately half of the patients who had a stroke had poor treatment outcomes. Ischaemic stroke was the most predominantly diagnosed stroke type. Education status, types of stroke and the median time from onset of symptoms to hospitalisation were the predictors of treatment outcome. Health education should be given to patients regarding clinical symptoms of stroke. In addition, local healthcare providers need to consider the above risk factors while managing stroke.
Cost-effectiveness of prehabilitation prior to elective surgery compared to usual preoperative care: protocol for a systematic review of economic evaluations
Authors: Rombey Tanja , Eckhardt Helene , Quentin Wilm
Published: December 2020

Introduction

Preoperative functional capacity is an important predictor of postoperative outcomes. Prehabilitation aims to optimise patients’ functional capacity before surgery to improve postoperative outcomes. As prolonged hospital stay and postoperative complications present an avoidable use of healthcare resources, prehabilitation might also save costs.

The aim of this systematic review is to investigate the cost-effectiveness of prehabilitation programmes for patients awaiting elective surgery compared with usual preoperative care. The results will be useful to inform decisions about the implementation of prehabilitation programmes and the design of future economic evaluations of prehabilitation programmes.

Methods and analysis

We will search PubMed, Embase, the Centre for Reviews and Dissemination Database, the WHO International Clinical Trials Registry Platform and ClinicalTrials.gov for full or partial economic evaluations of preoperative prehabilitation programmes conducted in any population compared with usual preoperative care. Studies will be included regardless of the type, design and perspective of the economic evaluation, and their publication year, language or status. Initial searches were performed between 30 April and 4 May 2020.

Study selection, data extraction and assessment of the included studies’ risk of bias and methodological quality will initially be performed by two independent reviewers and, if agreement was sufficiently high, by one reviewer. We will extract data regarding the included studies’ basic characteristics, economic evaluation methods and cost-effectiveness results.

A narrative synthesis will be performed. The primary endpoint will be cost-effectiveness based on cost–utility analyses. We will discuss heterogeneity between the studies and assess the risk of publication bias. The certainty of the evidence will be determined using the Grading of Recommendations, Assessment, Development and Evaluation approach.

Ethics and dissemination

Ethics approval is not required as the systematic review will not involve human participants. We plan to present our findings at scientific conferences, pass them on to relevant stakeholder organisations and publish them in a peer-reviewed journal.

PROSPERO registration number

CRD42020182813
Implementation and adherence of routine pertussis vaccination (DTP) in a low-resource urban birth cohort
Authors: Gunning Christian E , Mwananyanda Lawrence , MacLeod William B , Mwale Magdalene , Thea Donald M , Pieciak Rachel C , Rohani Pejman , Gill Christopher J
Published: December 2020

Introduction

Reliable information on rates of up-to-date coverage and timely administration of routine childhood immunisations are critical for guiding public health efforts worldwide, yet prospective observation of vaccination programmes within individual communities is rare. Here, we provide a longitudinal analysis of the directly observed administration of a three-dose primary vaccination series to infants in a low-resource community in Lusaka, Zambia.

Methods

Throughout 2015, we recruited a longitudinal birth cohort of mother/infant pairs (initial enrolment, 1981 pairs; attending, 1497 pairs) from the periurban informal settlement of Chawama compound, located in Lusaka, Zambia. We prospectively monitored the administration of scheduled diphtheria–tetanus–pertussis (DTP) vaccinations across the first 14–18 weeks of life. We analysed study attendance and vaccine coverage, both overall and stratified by age group. We employed Kaplan-Meier analyses to estimate delays in age-appropriate administration of vaccine doses. We also assessed schedule timing violations, including early and compressed dose administration.

Results

At study completion, first dose (DTP1) rates were high (92.9% of attending), whereas third dose completion (DTP3) rates were far lower (61.9%). Missed vaccinations and study dropout both contributed to the low DTP3 completion rates. DTP1 was administered very late (at or after 10 weeks) to 61 infants (4.1%). DTP1 was administered too early to 64 infants (4.3%), and 77 (5.1%) received consecutive doses below the minimum recommended spacing of 28 days.

Conclusions

We observe substantial individual variation in the timing of early childhood DTP doses, though following this birth cohort proved challenging. Our results indicate that timely administration of both DTP1 and DTP3 remains a challenge in this community. These directly-observed, individual-based results provide an important counterpoint to more course-grained, survey-based national and province estimates of up-to-date vaccine coverage. This study also highlights the challenges of vaccine hesitancy and suboptimal utilisation of (no-cost) healthcare services in a low-resource urban setting.
Impact of the COVID-19 pandemic on mental health and well-being of communities: an exploratory qualitative study protocol
Authors: Shahil Feroz Anam , Akber Ali Naureen , Akber Ali Noshaba , Feroz Ridah , Nazim Meghani Salima , Saleem Sarah
Published: December 2020

Introduction

The COVID-19 pandemic has certainly resulted in an increased level of anxiety and fear in communities in terms of disease management and infection spread. Due to fear and social stigma linked with COVID-19, many individuals in the community hide their disease and do not access healthcare facilities in a timely manner. In addition, with the widespread use of social media, rumours, myths and inaccurate information about the virus are spreading rapidly, leading to intensified irritability, fearfulness, insomnia, oppositional behaviours and somatic complaints. Considering the relevance of all these factors, we aim to explore the perceptions and attitudes of community members towards COVID-19 and its impact on their daily lives and mental well-being.

Methods and analysis

This formative research will employ an exploratory qualitative research design using semistructured interviews and a purposive sampling approach. The data collection methods for this formative research will include indepth interviews with community members. The study will be conducted in the Karimabad Federal B Area and in the Garden (East and West) community settings in Karachi, Pakistan. The community members of these areas have been selected purposively for the interview. Study data will be analysed thematically using NVivo V.12 Plus software.

Ethics and dissemination

Ethical approval for this study has been obtained from the Aga Khan University Ethical Review Committee (2020-4825-10599). The results of the study will be disseminated to the scientific community and to the research subjects participating in the study. The findings will help us explore the perceptions and attitudes of different community members towards the COVID-19 pandemic and its impact on their daily lives and mental well-being.
Observational cohort study with internal and external validation of a predictive tool for identification of children in need of hospital admission from the emergency department: the Paediatric Admission Guidance in the Emergency Department (PAGE) score
Authors: Rowland Andrew , Cotterill Sarah , Heal Calvin , Garratt Natalie , Long Tony , Bonnett Laura Jayne , Brown Stephen , Woby Steve , Roland Damian
Published: December 2020

Objectives

To devise an assessment tool to aid discharge and admission decision-making in relation to children and young people in hospital urgent and emergency care facilities, and thereby improve the quality of care that patients receive, using a clinical prediction modelling approach.

Design

Observational cohort study with internal and external validation of a predictive tool.

Setting

Two general emergency departments (EDs) and an urgent care centre in the North of England.

Participants

The eligibility criteria were children and young people 0–16 years of age who attended one of the three hospital sites within one National Health Service (NHS) organisation. Children were excluded if they opted out of the study, were brought to the ED following their death in the community or arrived in cardiac arrest when the heart rate and respiratory rate would be unmeasurable.

Main outcome measures

Admission or discharge. A participant was defined as being admitted to hospital if they left the ED to enter the hospital for further assessment, (including being admitted to an observation and assessment unit or hospital ward), either on first presentation or with the same complaint within 7 days. Those who were not admitted were defined as having been discharged.

Results

The study collected data on 36 365 participants. 15 328 participants were included in the final analysis cohort (21 045 observations) and 17 710 participants were included in the validation cohort (23 262 observations). There were 14 variables entered into the regression analysis. Of the 13 that remained in the final model, 10 were present in all 500 bootstraps. The resulting Paediatric Admission Guidance in the Emergency Department (PAGE) score demonstrated good internal validity. The C-index (area under the ROC) was 0.779 (95% CI 0.772 to 0.786).

Conclusions

For units without the immediate availability of paediatricians the PAGE score can assist staff to determine risk of admission. Cut-off values will need to be adjusted to local circumstance.

Study protocol

The study protocol has been published in an open access journal: Riazet alRefining and testing the diagnostic accuracy of an assessment tool (Pennine Acute Hospitals NHS Trust-Paediatric Observation Priority Score) to predict admission and discharge of children and young people who attend an ED: protocol for an observational study. BMC Pediatr 18, 303 (2018).https://doi.org/10.1186/s12887-018-1268-7.

Trial registration number

The protocol has been published and the study registered (NIHR RfPB Grant: PB-PG-0815–20034; ClinicalTrials.gov:213469).
Higher serum vitamin D levels are associated with decreased odds of obstructive lung disease in the general population: an NHANES analysis (2007–2008 to 2009–2010)
Authors: Seedahmed Mohamed Ismail , Baugh Aaron D , Kempker Jordan A
Published: December 2020

Background

Obstructive lung disease is a significant cause of morbidity and healthcare burden within the USA. A growing body of evidence has suggested that vitamin D levels can influence the course or incidence of obstructive lung disease. However, there is an insufficient previous investigation of this association.

Study design and methods

We used the National Health and Nutrition Examination Survey (NHANES) cycles 2007–2008 and 2009–2010 spirometry results of individuals aged 40 years and older to assess the association between serum 25-hydroxyvitamin D levels and obstructive lung disease, as defined by the American Thoracic Society using the lower limit of normal. We used stage multivariate survey-logistic regression.

Results

The final model included age, gender, body mass index, pack-years smoking history, season, income-to-poverty ratio and race/ethnicity. In the primary analysis using vitamin D as a continuous variable, there was no association between vitamin D levels and obstructive lung disease. We noted a trend between ‘other Hispanic’ self-identified race and serum vitamin D levels wherein higher levels were associated with higher odds of obstructive lung disease in this ethnicity, but not among other racial or ethnic groups (OR (95% CI)=1.40 (0.98 to 1.99), p=0.06). In a secondary analysis, when vitamin D was measured as a categorical variable, there was a significant association between the highest levels of serum vitamin D levels and lesser odds of obstructive lung disease (OR (95% CI)=0.77 [0.61 to 0.98], p=0.04).

Conclusions

Higher serum vitamin D levels among adults are associated with decreased odds of obstructive lung disease in the general population. Results among non-Mexican Hispanic participants highlight the need for further research in minority populations. More work is needed to address the course and incidence of lung disease in the USA.
Niche-specific functional heterogeneity of intestinal resident macrophages
Authors: Viola Maria Francesca , Boeckxstaens Guy
Published: December 2020

Intestinal resident macrophages are at the front line of host defence at the mucosal barrier within the gastrointestinal tract and have long been known to play a crucial role in the response to food antigens and bacteria that are able to penetrate the mucosal barrier. However, recent advances in single-cell RNA sequencing technology have revealed that resident macrophages throughout the gut are functionally specialised to carry out specific roles in the niche they occupy, leading to an unprecedented understanding of the heterogeneity and potential biological functions of these cells. This review aims to integrate these novel findings with long-standing knowledge, to provide an updated overview on our understanding of macrophage function in the gastrointestinal tract and to speculate on the role of specialised subsets in the context of homoeostasis and disease.
A Practical Approach to Verification of Floating-Point C/C++ Programs with math.h/cmath Functions
Authors: Bagnara Roberto , Chiari Michele , Gori Roberta , Bagnara Abramo
Published: December 2020

Verification of C/C++ programs has seen considerable progress in several areas, but not for programs that use these languages’ mathematical libraries. The reason is that all libraries in widespread use come with no guarantees about the computed results. This would seem to prevent any attempt at formal verification of programs that use them: without a specification for the functions, no conclusion can be drawn statically about the behavior of the program. We propose an alternative to surrender. We introduce a pragmatic approach that leverages the fact that most math.h/cmath functions are
almost
piecewise monotonic: as we discovered through exhaustive testing, they may have
glitches
, often of very small size and in small numbers. We develop interval refinement techniques for such functions based on a modified dichotomic search, which enable verification via symbolic execution based model checking, abstract interpretation, and test data generation. To the best of our knowledge, our refinement algorithms are the first in the literature to be able to handle non-correctly rounded function implementations, enabling verification in the presence of the most common implementations. We experimentally evaluate our approach on real-world code, showing its ability to detect or rule out anomalous behaviors.
Global-local Metamodel-assisted Stochastic Programming via Simulation
Authors: Xie Wei , Yi Yuan , Zheng Hua
Published: December 2020

To integrate strategic, tactical, and operational decisions, stochastic programming has been widely used to guide dynamic decision-making. In this article, we consider complex systems and introduce the global-local metamodel-assisted stochastic programming via simulation that can efficiently employ the simulation resource to iteratively solve for the optimal first- and second-stage decisions. Specifically, at each visited first-stage decision, we develop a local metamodel to simultaneously solve a set of scenario-based second-stage optimization problems, which also allows us to estimate the optimality gap. Then, we construct a global metamodel accounting for the errors induced by: (1) using a finite number of scenarios to approximate the expected future cost occurring in the planning horizon, (2) second-stage optimality gap, and (3) finite visited first-stage decisions. Assisted by the global-local metamodel, we propose a new simulation optimization approach that can efficiently and iteratively search for the optimal first- and second-stage decisions. Our framework can guarantee the convergence of optimal solution for the discrete two-stage optimization with unknown objective, and the empirical study indicates that it achieves substantial efficiency and accuracy.
RegionTrack
Authors: Ma Xiaoxue , Wu Shangru , Pobee Ernest , Mei Xiupei , Zhang Hao , Jiang Bo , Chan Wing-Kwong
Published: December 2020

Atomicity is a correctness criterion to reason about isolated code regions in a multithreaded program when they are executed concurrently. However, dynamic instances of these code regions, called
transactions
, may fail to behave atomically, resulting in transactional atomicity violations. Existing dynamic online atomicity checkers incur either false positives or false negatives in detecting transactions experiencing transactional atomicity violations. This article proposes RegionTrack. RegionTrack tracks cross-thread dependences at the event, dynamic subregion, and transaction levels. It maintains both dynamic subregions within selected transactions and transactional happens-before relations through its novel timestamp propagation approach. We prove that RegionTrack is sound and complete in detecting both transactional atomicity violations and non-serializable traces. To the best of our knowledge, it is the first online technique that precisely captures the transitively closed set of happens-before relations over all conflicting events with respect to every running transaction for the above two kinds of issues. We have evaluated RegionTrack on 19 subjects of the DaCapo and the Java Grande Forum benchmarks. The empirical results confirm that RegionTrack precisely detected all those transactions which experienced transactional atomicity violations and identified all non-serializable traces. The overall results also show that RegionTrack incurred 1.10x and 1.08x lower memory and runtime overheads than Velodrome and 2.10x and 1.21x lower than Aerodrome, respectively. Moreover, it incurred 2.89x lower memory overhead than DoubleChecker. On average, Velodrome detected about 55% fewer violations than RegionTrack, which in turn reported about 3%–70% fewer violations than DoubleChecker.
Privacy-preserving IoT Framework for Activity Recognition in Personal Healthcare Monitoring
Authors: Jourdan Theo , Boutet Antoine , Bahi Amine , Frindel Carole
Published: December 2020

The increasing popularity of wearable consumer products can play a significant role in the healthcare sector. The recognition of human activities from IoT is an important building block in this context. While the analysis of the generated datastream can have many benefits from a health point of view, it can also lead to privacy threats by exposing highly sensitive information. In this article, we propose a framework that relies on machine learning to efficiently recognise the user activity, useful for personal healthcare monitoring, while limiting the risk of users re-identification from biometric patterns characterizing each individual. To achieve that, we show that features in temporal domain are useful to discriminate user activity while features in frequency domain lead to distinguish the user identity. We then design a novel protection mechanism processing the raw signal on the user’s smartphone to select relevant features for activity recognition and normalise features sensitive to re-identification. These unlinkable features are then transferred to the application server. We extensively evaluate our framework with reference datasets: Results show an accurate activity recognition (87%) while limiting the re-identification rate (33%). This represents a slight decrease of utility (9%) against a large privacy improvement (53%) compared to state-of-the-art baselines.
Assessing Visual Perception in Heritage Sites with Visual Acuity
Authors: Polig Martina , Papacharalambous Despina G. , Bakirtzis Nikolas , Hermon Sorin
Published: December 2020

A challenging aspect of visibility studies is visual acuity, which concerns the clarity of vision within a given space in relation to variables such as spatial geometry, lighting conditions, the physical properties of the viewed object, or the familiarity of viewers with the target. Our research proposes a novel approach to visibility studies, based on visual acuity and its related pipeline, which integrates qualitative and quantitative aspects such as the cultural background of viewers, the illumination values of space, contrast, and size of objects of interest as well as their meaning and context. The proposed pipeline relies on 3D documentation of the investigated space, light measurements, research in optics, trigonometry calculations, and 3D GIS set against images and architectural space. The method's effectiveness is demonstrated in the study of the iconography of the Cathedral of St. John the Theologian in Nicosia, Cyprus, the work hypothesis being that the church's spatial organization, choice of scenes, and level of detail were carefully planned to establish visual narratives with strong political and religious connotations and to overall dictate the ways the building was accessed and experienced. The method can be broadly applied for visibility analyses in a variety of case-studies in closed spaces.
From Point Cloud to HBIM to FEA, the Case of a Vernacular Architecture
Authors: Zouaoui Mohamed Amine , Djebri Boualem , Capsoni Antonio
Published: December 2020

The preservation of architectural heritage represents a major asset for economic development in several countries. Nevertheless, its protection remains a complex task due to its high vulnerability, especially in seismic zones.

The intervention on the historical buildings requires the creation of a numerical and digital support shared by the different building specialists (architects, conservators, engineers, designers), which can contain all of the data relating to the construction. This will allow to ensure not only a better interchangeability between the different disciplines but also a correct and coherent conception and execution of the interventions.

The introduction of 3D digitization tools, particularly the 3D laser scanner, plays a major role during the realization of the architectural survey. Indeed, the use of the architectural modeling software based on Building Information Modeling and Non-Uniform Rational Basis Spline allows first of all to move from the point cloud to an accurate 3D numerical model exploitable for various types of analysis, such as structural analysis, building archeology analysis, and thermal analysis.

We propose through this article an unprecedented application of the 3D laser scanner on an example of vernacular architecture, constituting a truly unique type of “Medina.” The object of the study is an aggregate composed of five houses, falling inside the Kasbah of Algiers, which since 1992 has been classified as “universal heritage” by UNESCO.

The architectural survey is followed by a demonstration of numerical modelling based on 10 grades of generation using two categories of software founded mainly on Building Information Modeling and Non-Uniform Rational Basis Spline. Two kinds of numerical models are obtained: a first architectural model will be exploited during the building archaeology principally based on the 3D scanning results and a second structural model that will be used for structural analysis through a Finite Element Analysis software.
Zeros of Holant Problems
Authors: Guo Heng , Liao Chao , Lu Pinyan , Zhang Chihao
Published: December 2020

We present fully polynomial-time (deterministic or randomised) approximation schemes for Holant problems, defined by a non-negative constraint function satisfying a generalised second-order recurrence modulo in a couple of exceptional cases. As a consequence, any non-negative Holant problem on cubic graphs has an efficient approximation algorithm unless the problem is equivalent to approximately counting perfect matchings, a central open problem in the area. This is in sharp contrast to the computational phase transition shown by two-state spin systems on cubic graphs. Our main technique is the recently established connection between zeros of graph polynomials and approximate counting.
Tight Bounds for Online TSP on the Line
Authors: Bjelde Antje , Hackfeld Jan , Disser Yann , Hansknecht Christoph , Lipmann Maarten , Meißner Julie , SchlÖter Miriam , Schewior Kevin , Stougie Leen
Published: December 2020

We consider the online traveling salesperson problem (TSP), where requests appear online over time on the real line and need to be visited by a server initially located at the origin. We distinguish between closed and open online TSP, depending on whether the server eventually needs to return to the origin or not. While online TSP on the line is a very natural online problem that was introduced more than two decades ago, no tight competitive analysis was known to date. We settle this problem by providing tight bounds on the competitive ratios for both the closed and the open variant of the problem. In particular, for closed online TSP, we provide a 1.64-competitive algorithm, thus matching a known lower bound. For open online TSP, we give a new upper bound as well as a matching lower bound that establish the remarkable competitive ratio of 2.04.

Additionally, we consider the online D
IAL
-A-R
IDE
problem on the line, where each request needs to be transported to a specified destination. We provide an improved non-preemptive lower bound of 1.75 for this setting, as well as an improved preemptive algorithm with competitive ratio 2.41.

Finally, we generalize known and give new complexity results for the underlying offline problems. In particular, we give an algorithm with running time 
O
(
n
2
) for closed offline TSP on the line with release dates and show that both variants of offline D
IAL
-A-R
IDE
on the line are NP-hard for any capacity 
c
≥ 2 of the server.
Perception Clusters
Authors: Khan Aftab , Zenonos Alexandros , Kalogridis Georgios , Wang Yaowei , Vatsikas Stefanos , Sooriyabandara Mahesh
Published: December 2020

Automated mood recognition has been studied in recent times with great emphasis on stress in particular. Other affective states are also of great importance, as studying them can help in understanding human behaviours in more detail. Most of the studies conducted in the realisation of an automated system that is capable of recognising human moods have established that mood is personal—that is, mood perception differs amongst individuals. Previous machine learning--based frameworks confirm this hypothesis, with personalised models almost always outperforming the generalised methods. In this article, we propose a novel system for grouping individuals in what we refer to as “perception clusters” based on their physiological signals. We evaluate perception clusters with a trial of nine users in a work environment, recording physiological and activity data for at least 10 days. Our results reveal no significant difference in performance with respect to a personalised approach and that our method performs equally better against traditional generalised methods. Such an approach significantly reduces computational requirements that are otherwise necessary for personalised approaches requiring individual models developed separately for each user. Further, perception clusters manifest a direction towards semi-supervised affective modelling in which individual perceptions are inferred from the data.
Museum Mobile Guide Preferences of Different Visitor Personas
Authors: Almeshari Moneerah , Dowell John , Nyhan Julianne
Published: December 2020

Personalising museum mobile guides is widely acknowledged as being important for enhancing the visitor experience. Due to the lack of information about an individual visitor and the relatively limited time of his or her visit, adapting the user interface based on a museum visitor's type is a promising approach to personalisation. This approach first requires a mechanism to identify the visitor type (‘persona’) and, second, knowledge of the preferences and needs of different types to apply personalisation. In this article, we report a face-to-face questionnaire study carried out with 105 visitors to Scitech, a science and technology visitor centre. The study aims to investigate the main facts required to identify a visitor persona and to explore the preferences of different visitor personas for particular mobile guide features. We limited our concern to the user interface features of the guide (e.g., whether it provides recommendations for related items to view) rather than what content and services the guide provides (e.g., what related items are recommended). We found that we can reliably identify the visitor persona using two multiple choice questions about visit motivation and perceived success criteria. In addition, we found that visitors have significant preferences for particular features such as presentation media, venue navigation tool, object suggestions, details level, accessing external links, exhibit information retrieval method and social interaction features such as voice communication, instant messaging, group games and challenges. Some features were found to be preferred differently by different personas such as the challenges feature, some were found to be preferred by personas differently to the overall preference such as in presentation media, and some were found to be preferred by some personas with no particular preference for others such as a venue navigation tool. Instant messaging was found to be significantly not preferred by all personas. The results provide a basis for personalisation of museum guides and services using a personas approach, which is a solution where data about individual users may be limited and where the individual configuration of a user interface may not be practical or warranted.
Replication of Computational Results Report for “
Green Simulation with Database Monte Carlo
”
Authors: Pellegrini Alessandro
Published: December 2020

This article presents the reproducibility results associated with the article “
Green Simulation with Database Monte Carlo
,” by Mingbin Feng and Jeremy Staum. The authors have uploaded their artifact to Zenodo, which ensures a long-term retention of the artifact. The artifact, which is based on a set of R scripts, allows to easily regenerate data for the figures and the tables, it completes successfully, and allows to reproduce all the experimental results in the article.

The article can thus receive the
Artifacts Available
, the
Artifacts Evaluated—Functional
, and the
Results Reproduced
badges.
Optimal Substring Equality Queries with Applications to Sparse Text Indexing
Authors: Prezza Nicola
Published: December 2020

We consider the problem of encoding a string of length
n
from an integer alphabet of size σ so
access
,
substring equality
, and
Longest Common Extension
(LCE) queries can be answered efficiently. We describe a new space-optimal data structure supporting logarithmic-time queries. Access and substring equality query times can furthermore be improved to the optimal
O
(1) if
O
(log
n
) additional precomputed words are allowed in the total space. Additionally, we provide in-place algorithms for converting between the string and our data structure.

Using this new string representation, we obtain the first in-place subquadratic algorithms for several string-processing problems in the
restore
model: The input string is rewritable and must be restored before the computation terminates. In particular, we describe the first in-place subquadratic Monte Carlo solutions to the sparse suffix sorting, sparse LCP array construction, and suffix selection problems. With the sole exception of suffix selection, our algorithms are also the first running in
sublinear
time for small enough sets of input suffixes. Combining these solutions, we obtain the first sublinear-time Monte Carlo algorithm for building the sparse suffix tree in compact space. We also show how to build a correct version of our data structure using small working space. This leads to the first Las Vegas in-place algorithm computing the full LCP array in
O
(
n
log
n
) time w.h.p. and to the first Las Vegas in-place algorithms solving the sparse suffix sorting and sparse LCP array construction problems in
O
(
n
1.5
√ log σ) time w.h.p.
Application of Simulation in Healthcare Service Operations
Authors: Roy Sudipendra Nath , Shah Bhavin J. , Gajjar Hasmukh
Published: December 2020

The health system is intricate due to its dynamic nature and critical service requirements. The involvement of multiple layers of health service providers quadrupled this complexity and results in a complicated operating environment. Simulation is often considered an apt technique to model and study complex systems in the literature. The popularity of simulation in the healthcare domain had only accelerated with time and resulted in a large number of articles intended to solve myriad healthcare problems. This article analyzes healthcare simulation literature of the past decade (2007--2016) that addresses operations management issues in various healthcare service delivery levels and categorizes the literature accordingly. In the next step, we attempt to assimilate the entire literature to capture specific health issues addressed, operations management concepts applied, and simulation methods used, and identify major research gaps. Finally, we develop the research agenda from dividing these gaps into the contextual, conceptual, and methodological genre that is consistent with the previous state-of-the-art literature reviews in operations management. Furthermore, this article demonstrates other minute aspects such as “sources of funding” and “tools used for the research” to maintain coherence with the previous reviews in the healthcare simulation. The objective of this work is twofold: to connect the knowledge continuum to the present, and to provide potential research directions for future academicians.
Ensemble Deep Learning on Wearables Using Small Datasets
Authors: Mauldin Taylor , Ngu Anne H. , Metsis Vangelis , Canby Marc E.
Published: December 2020

This article presents an in-depth experimental study of Ensemble Deep Learning techniques on small datasets for the analysis of time-series data generated by wearable devices. Deep Learning networks generally require large datasets for training. In some health care applications, such as the real-time smartwatch-based fall detection, there are no publicly available, large, annotated datasets that can be used for training, due to the nature of the problem (i.e., a fall is not a common event). We conducted a series of offline experiments using two different datasets of simulated falls for training various ensemble models. Our offline experimental results show that an ensemble of Recurrent Neural Network (RNN) models, combined by the stacking ensemble technique, outperforms a single RNN model trained on the same data samples. Nonetheless, fall detection models trained on simulated falls and activities of daily living performed by test subjects in a controlled environment, suffer from low precision due to high false-positive rates. In this work, through a set of real-world experiments, we demonstrate that the low precision can be mitigated via the collection of false-positive feedback by the end-users. The final Ensemble RNN model, after re-training with real-world user archived data and feedback, achieved a significantly higher precision without reducing much of the recall in a real-world setting.
Toward Dynamic User Intention
Authors: Wang Chenyang , Ma Weizhi , Zhang Min , Chen Chong , Liu Yiqun , Ma Shaoping
Published: December 2020

User intention is an important factor to be considered for recommender systems, which always changes dynamically in different contexts. Recent studies (represented by sequential recommendation) begin to focus on predicting what users want beyond what users like, which are better at capturing user intention and have attracted a surge of interest. However, user intention modeling is non-trivial, because it is generally influenced by various factors, among which item relations and their temporal evolutionary effects are of great importance. For example, consumption of a cellphone will have varying impacts on the demands for its relational items: For complements, the demands are likely to be promoted in the short term; while for substitutes, the long-term effect may take advantage, because users do not need another cellphone immediately. Moreover, the temporal evolutions of different relational effects vary across different domains, which makes it challenging to adaptively take them into consideration. As a result, most existing studies only loosely incorporate item relations by encoding their semantics into embeddings, neglecting fine-grained time-aware effects.

In this work, we propose Knowledge-aware Dynamic Attention (KDA) to take both relational effects and their temporal evolutions into consideration. Specifically, to model dynamic impacts of historical relational interactions on user intention, we aggregate the history sequence into relation-specific embeddings, where the attention weight consists of two parts. First, we measure the relational intensity between historical items and the target item to model the absolute degree of influence in terms of each relation. Second, to model how the relational effects drift with time, we innovatively introduce Fourier transform with learnable frequency-domain embeddings to estimate temporal decay functions of different relations adaptively. Subsequently, the self-attention mechanism is leveraged to derive the final representation of the whole history sequence, which reflects the dynamic user intention and will be applied to generate the recommendation list. Extensive experiments in three real-world datasets indicate the proposed KDA model significantly outperforms the state-of-the-art methods on the Top-
K
recommendation task. Moreover, the proposed Fourier-based method opens up a new avenue to adaptively integrate temporal dynamics into general neural models.
Does autonomic nervous system dysfunction influence cardiovascular disease risk in young adults with intellectual disability?
Authors: Zwack Clara C. , McDonald Rachael , Tursunalieva Ainura , Cooray Amali , Lambert Gavin W. , Lambert Elisabeth A.
Published: December 2020

Adults with intellectual disability experience higher risk of premature death than the general population. Our investigation highlights increased cardiovascular risk markers and autonomic dysfunction in young adults with intellectual disability compared with control adults. Autonomic dysfunction was more marked in those with a more severe disability but independent of cardiovascular parameters. Assessment of autonomic nervous system (ANS) function may provide insight into the mechanisms of cardiometabolic disease development and progression in young adults with intellectual disability.
Psychometric Properties of the Abdominal Pain Index (API) in the Iranian Adolescent Population
Authors: Hoseini Sepideh , Jafari Mahdi , Asl Soleimani Zahra , Qaderi Bagajan Kaveh , Sadeghi Meysam , Zolfaghari Shadi
Published: December 2020

Considering the high prevalence of abdominal pain in children and adolescents in Iran, it is essential to use appropriate screening tools. One of the most comprehensive, yet concise, tools for this purpose is the Abdominal Pain Index (API). This study aimed to investigate the psychometric properties of the Persian version of the self-report API in adolescents. In this descriptive study, A total of 162 Iranian adolescents in the age range of 12 to 18 years were considered as the sample group, which included two groups of school students (n = 125) and adolescent patients with abdominal pain (n = 37). Clinical sample was selected by the available sampling method, and nonclinical sample was selected by the cluster sampling method. Adolescents in the sample group were selected from both clinical and nonclinical groups in order to evaluate differential validity. Instruments, including API, somatic symptoms subscale of the General Health Questionnaire (GHQ), and McGill Pain Questionnaire (MPQ), were also completed for the participants. Also, to evaluate the construct validity of API, exploratory and confirmatory factor analysis methods were applied. The exploratory factor analysis identified one general factor, and the confirmatory factor analysis results show the model’s satisfactory fitting. Also, the researchers’ hypothesis, i.e., API is a single-factor model (with five items), was approved. The reliability coefficient of the questionnaire was satisfactory for the total scale (α < 0.7). This study showed that API could be used with considerable confidence for Iranian children and adolescents with chronic pain.
Melatonin Protects Goat Spermatogonial Stem Cells against Oxidative Damage during Cryopreservation by Improving Antioxidant Capacity and Inhibiting Mitochondrial Apoptosis Pathway
Authors: Feng Tian-Yu , Li Qian , Ren Fa , Xi Hua-Ming , Lv Dong-Liang , Li Yu , Hu Jian-Hong
Published: December 2020

Spermatogonial stem cells (SSCs) are the only adult stem cells that pass genes to the next generation and can be used in assisted reproductive technology and stem cell therapy. SSC cryopreservation is an important method for the preservation of immature male fertility. However, freezing increases the production of intracellular reactive oxygen species (ROS) and causes oxidative damage to SSCs. The aim of this study was to investigate the effect of melatonin on goat SSCs during cryopreservation and to explore its protective mechanism. We obtained SSCs from dairy goat testes by two-step enzymatic digestion and differential plating. The SSCs were cryopreserved with freezing media containing different melatonin concentrations. The results showed that 10-6 M of melatonin increased significantly the viability, total antioxidant capacity (T-AOC), and mitochondrial membrane potential of frozen-thawed SSCs, while it reduced significantly the ROS level and malondialdehyde (MDA) content (

P
<
0.05

). Further analysis was performed by western blotting, flow cytometry, and transmission electron microscopy (TEM). Melatonin improved significantly the enzyme activity and protein expression of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px) (

P
<
0.05

), thereby activating the antioxidant defense system of SSCs. Furthermore, melatonin inhibited significantly the expression of proapoptotic protein (Bax) and increased the expression of antiapoptotic proteins (Bcl-2 and Bcl-XL) (

P
<
0.05

). The mitochondrial apoptosis pathway analysis showed that the addition of melatonin reduced significantly the mitochondrial swelling and vacuolation, and inhibited the release of cytochrome C from mitochondria into the cytoplasm, thereby preventing the activation of caspase-3 (

P
<
0.05

) and inhibiting SSC apoptosis. In addition, melatonin reduced significantly the autophagosome formation and regulated the expression of autophagy-related proteins (LC3-I, LC3-II, P62, Beclin1, and ATG7) (

P
<
0.05

), thereby reversing the freeze-induced excessive autophagy. In summary, melatonin protected goat SSCs during cryopreservation via antioxidant, antiapoptotic, and autophagic regulation.
China’s Spatial Economic Network and Its Influencing Factors
Authors: Yu Guihai , He Deyan , Lin Wenlong , Wu Qiuhua , Xiao Jianxiong , Lei Xiaofang , Xie Zhongqun , Wu Renjie
Published: December 2020

With the deepening of reform and opening-up, China’s economy has been further developed, but there is still a problem of uneven development. It is of great significance to completely construct China’s economic spatial correlation network, to clarify the role and status of each province in the whole network, and to study the influencing factors of the national spatial economic network. In this paper, we employ the network analysis method to analyze China’s economic development in the past 20 years. Based on the modified gravity model, we construct China’s spatial economic network and explore the network structure from three aspects: the whole network structure feature, characteristics of individual provinces in the network, and block model analysis. The results show that (1) China’s spatial economic network has strong internal cohesion, and the hierarchy of the network is becoming less and less obvious. However, the network density is low, and the overall network relationship still needs to be strengthened. (2) The different levels in economic development illustrate the obvious economic unbalance among provinces. (3) The block model analysis results demonstrated that coastal areas are more attractive to other provinces and are playing an important role in driving China’s economy. Finally, we employ Quadratic Assignment Procedure (QAP) regression analysis to analyze the influential factors on spatial economic network. Numerical results show that the geographic proximity and the differences in six factors (industrial structure, level of economic development, degree of opening to the outside world, medical level, size of labor market, and infrastructure) have significant impact on the spatial economic network. Moreover, the influence of these factors on the economic relation among provinces has been gradually strengthened in recent years.