bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the efficacy of low concentration fluoride gel using custom trays to prevent radiation-related dental caries in patients with head and neck cancer: protocol for a randomised controlled phase III trial (FluCar study)
Authors: Sakiko Soutome , Yanamoto Souichi , Murata Maho , Kawashita Yumiko , Yoshimatsu Masako , Funahara Madoka , Umeda Masahiro , Saito Toshiyuki
Published: September 2020

Introduction

The present study is a randomised, multicentre, open-label, phase III study, to evaluate the efficacy of low concentration of fluoride gel, applied using custom trays, in preventing radiation-related dental caries in patients with head and neck cancer who have undergone or are undergoing radiotherapy.

Methods and analysis

Patients will be randomised into fluoride and control groups (1:1 ratio). In the fluoride group, patients will wear custom trays loaded with 0.145% fluoride gel after brushing every night while sleeping. In the control group, patients will receive oral hygiene instructions as usual. Patients in both the groups will be followed up every 3 months for 1 year. The primary endpoint is the incidence of newly developed dental caries. Target accrual is 80 patients with a two-sided type I error rate of 5% and 80% power to detect 80% risk reduction.

Ethics and dissemination

This study was approved by the Clinical Research Review Board in Nagasaki University The protocol of this study was registered at Japan Registry of Clinical Trials (jRCT) and University hospital Medical Information Network Clinical Trials Registry (UMIN). The datasets generated during the current study will be available from the corresponding author on reasonable request.

Trial registration numbers

jRCTs 072190039 and UMIN000041426
Cognitive impairment and psychopathology in out-of-hospital cardiac arrest survivors in Denmark: The REVIVAL cohort study protocol
Authors: Wagner Mette Kirstine , Berg Selina Kikkenborg , Hassager Christian , Armand Sophia , Møller Jacob Eifer , Ekholm Ola , Rasmussen Trine Bernholdt , Fisher Patrick MacDonald , Knudsen Gitte Moos , Stenbæk Dea Siggaard
Published: September 2020

Introduction

Cognitive impairment and psychopathology caused by brain hypoxia and the traumatic impact of critical illness are common in cardiac arrest survivors and can lead to negative consequences of everyday life functioning, and further impact mental health in relatives. Most studies have dealt with the mere survival rate after cardiac arrest and not with long-term consequences to mental health in cardiac arrest survivors. Importantly, we face a gap in our knowledge about suitable screening tools in the early post-arrest phase for long-term risk prediction of mental health problems. This study aims to evaluate the efficacy of a novel screening procedure to predict risk of disabling cognitive impairment and psychopathology 3 months after cardiac arrest. Furthermore, the study aims to evaluate long-term prevalence of psychopathology in relatives.

Methods and analyses

In this multicentre prospective cohort study, out-of-hospital cardiac arrest survivors and their relatives will be recruited. The post-arrest screening includes the Montreal Cognitive Assessment (MoCA), the Hospital Anxiety and Depression Scale (HADS), the Impact of Event Scale-Revised (IES-R) and the Acute Stress Disorder Interview (ASDI) and is conducted during hospitalisation. In a subsample of the patients, functional MRI is done, and cortisol determination collected. At 3-month follow-up, the primary study outcomes for 200 survivors include the Danish Affective Verbal Learning Test-26 (VAMT-26), Delis-Kaplan Executive Function System tests (trail making, colour-word interference, word and design fluency), Rey’s Complex Figure and Letter-number sequencing subtest of Wechsler Adult Intelligence Scale-IV, HADS and IES-R. For the relatives, they include HADS and IES-R.

Ethics and dissemination

The study is approved by the local regional Research Ethics Committee (H-18046155) and the Danish Data Protection Agency (RH-2017-325, j.no.05961) and follows the latest version of the Declaration of Helsinki. The results will be published in peer-reviewed journals and may impact the follow-up of cardiac arrest survivors.
Comparing rates and characteristics of emergency department presentations related to pharmaceutical opioid poisoning in Australia: a study protocol for a retrospective observational study
Authors: Lam Tina , Hayman Jane , Berecki-Gisolf Janneke , Sanfilippo Paul , Lubman Dan I , Nielsen Suzanne
Published: September 2020

Introduction and aims

Pharmaceutical opioids are an important contributor to the global ‘opioid crisis’, and are implicated in 70% of Australia’s opioid-related mortality. However, there have been few studies which consider the relative contribution of different pharmaceutical opioids to harm.

We aim to compare commonly used pharmaceutical opioids in terms of (1) rates of harm, and (2) demographic and clinical characteristics associated with that harm.

Method and analysis

Observational study of emergency department presentations for non-fatal poisoning related to pharmaceutical opioid use. Data from 2009 to 2019 will be extracted from the Victorian Emergency Minimum Dataset which contains data from public hospitals with dedicated emergency departments in Victoria, Australia’s second most populous state. A combination of free-text and International Classification of Diseases 10th Revision codes will be used to identify relevant cases, with manual screening of each case to confirm relevance. We will calculate supply-adjusted rates of presentations using Poisson regression for all pharmaceutical opioid cases identified, separately for nine commonly prescribed pharmaceutical opioids (buprenorphine, codeine, fentanyl, methadone, morphine, oxycodone, oxycodone-naloxone, tapentadol, tramadol), and for a multiple opioid category. We will use multinomial logistic regression to compare demographic and clinical characteristics, such as triage category, across opioid types.

Ethics and dissemination

This work is conducted under approval 21427 from the Monash University Human Research Ethics Committee for ongoing injury surveillance. As per conditions of approval, cells of <5 will not be reported, though zeroes will be preserved. We will present project findings in a peer-reviewed journal article as well as at relevant scientific conferences.
Prospective cohort protocol examining the perioperative indicators for complications and early mortality following hip fracture surgery in the frail patient
Authors: de Jong Louis , van Rijckevorsel Veronique , Klem Taco M A L , Kuijper Martijn , Roukema Gert R
Published: September 2020

Introduction

The primary aim is to validate earlier suggested risk factors and to find new associated risk factors for (30-day) mortality after a hip fracture in the frail population. The secondary aim is to determine the factors associated with perioperative complications. At last we want to develop and validate a more specific 30-day mortality prediction tool compared with the Nottingham Hip Fracture Score. The 30-day mortality prediction can help inform surgical risk and guide shared decision-making among patients, family and physicians.

Methods and analysis

The study is designed as a prospective multicentre cohort study within the area of Rotterdam, the Netherlands starting from January 2018. All patients over 65 years of age, with an acute proximal hip fracture, are included. Treatment of patients will be by standard practice of care using the latest national and international guidelines. Inclusion will be continued at least until January 2021 and including at least 2500 patients. In this large cohort we hope to have sufficient strength and quality to identify risk factors of 30-day mortality and to compare them to known risk factors in literature. Moreover, we plan to develop and validate a 30-day mortality prediction tool, which identifies patients with a high probability of 30-day mortality.

Ethics and dissemination

Ethical approval for this protocol was given by the Ethics Committee of the Maasstad Hospital (TWOR). Patient data are stored anonymously using the Castor data management system. No external funding is used for this study. Results will be published in peer-reviewed publications and at international conferences.

Trial registration number

NL8313.
Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability
Authors: Nicodemo Catia , Barzin Samira , Cavalli Nicolo' , Lasserson Daniel , Moscone Francesco , Redding Stuart , Shaikh Mujaheed
Published: September 2020

Objectives

The growth of COVID-19 infections in England raises questions about system vulnerability. Several factors that vary across geographies, such as age, existing disease prevalence, medical resource availability and deprivation, can trigger adverse effects on the National Health System during a pandemic. In this paper, we present data on these factors and combine them to create an index to show which areas are more exposed. This technique can help policy makers to moderate the impact of similar pandemics.

Design

We combine several sources of data, which describe specific risk factors linked with the outbreak of a respiratory pathogen, that could leave local areas vulnerable to the harmful consequences of large-scale outbreaks of contagious diseases. We combine these measures to generate an index of community-level vulnerability.

Setting

91 Clinical Commissioning Groups (CCGs) in England.

Main outcome measures

We merge 15 measures spatially to generate an index of community-level vulnerability. These measures cover prevalence rates of high-risk diseases; proxies for the at-risk population density; availability of staff and quality of healthcare facilities.

Results

We find that 80% of CCGs that score in the highest quartile of vulnerability are located in the North of England (24 out of 30). Here, vulnerability stems from a faster rate of population ageing and from the widespread presence of underlying at-risk diseases. These same areas, especially the North-East Coast areas of Lancashire, also appear vulnerable to adverse shocks to healthcare supply due to tighter labour markets for healthcare personnel. Importantly, our index correlates with a measure of social deprivation, indicating that these communities suffer from long-standing lack of economic opportunities and are characterised by low public and private resource endowments.

Conclusions

Evidence-based policy is crucial to mitigate the health impact of pandemics such as COVID-19. While current attention focuses on curbing rates of contagion, we introduce a vulnerability index combining data that can help policy makers identify the most vulnerable communities. We find that this index is positively correlated with COVID-19 deaths and it can thus be used to guide targeted capacity building. These results suggest that a stronger focus on deprived and vulnerable communities is needed to tackle future threats from emerging and re-emerging infectious disease.
Contamination and washing of cloth masks and risk of infection among hospital health workers in Vietnam: a post hoc analysis of a randomised controlled trial
Authors: MacIntyre Chandini Raina , Dung Tham Chi , Chughtai Abrar Ahmad , Seale Holly , Rahman Bayzidur
Published: September 2020

Background

In a previous randomised controlled trial (RCT) in hospital healthcare workers (HCWs), cloth masks resulted in a higher risk of respiratory infections compared with medical masks. This was the only published RCT of cloth masks at the time of the COVID-19 pandemic.

Objective

To do a post hoc analysis of unpublished data on mask washing and mask contamination from the original RCT to further understand poor performance of the two-layered cotton cloth mask used by HCWs in that RCT.

Setting

14 secondary-level/tertiary-level hospitals in Hanoi, Vietnam.

Participants

A subgroup of 607 HCWs aged ≥18 years working full time in selected high-risk wards, who used a two-layered cloth mask and were part of a randomised controlled clinical trial comparing medical masks and cloth masks.

Intervention

Washing method for cloth masks (self-washing or hospital laundry). A substudy of contamination of a sample of 15 cloth and medical masks was also conducted.

Outcome measure

Infection rate over 4 weeks of follow up and viral contamination of masks tested by multiplex PCR.

Results

Viral contamination with rhinovirus was identified on both used medical and cloth masks. Most HCW (77% of daily washing) self-washed their masks by hand. The risk of infection was more than double among HCW self-washing their masks compared with the hospital laundry (HR 2.04 (95% CI 1.03 to 4.00); p=0.04). There was no significant difference in infection between HCW who wore cloth masks washed in the hospital laundry compared with medical masks (p=0.5).

Conclusions

Using self-reported method of washing, we showed double the risk of infection with seasonal respiratory viruses if masks were self-washed by hand by HCWs. The majority of HCWs in the study reported hand-washing their mask themselves. This could explain the poor performance of two layered cloth masks, if the self-washing was inadequate. Cloth masks washed in the hospital laundry were as protective as medical masks. Both cloth and medical masks were contaminated, but only cloth masks were reused in the study, reiterating the importance of daily washing of reusable cloth masks using proper method. A well-washed cloth mask can be as protective as a medical mask.

Trial resgistration number

ACTRN12610000887077.
Validation of the Sexual Knowledge Picture Instrument as a diagnostic instrument for child sexual abuse: study protocol
Authors: van Ham Kirsten , Brilleslijper-Kater Sonja , van der Lee Hanneke , van Rijn Rick , van Goudoever Hans , Teeuw Rian
Published: September 2020

Background

The consequences of child sexual abuse (CSA) can be significant and can affect short-term and long-term mental, sexual and physical health. In order to offer timely and appropriate care for the child, early recognition of CSA is necessary. The lack of specific physical and psychological signs and barriers to abuse disclosure that these young victims face makes it difficult for medical and psychological professionals to recognise and confirm CSA signs. We aimed to validate the Sexual Knowledge Picture Instrument (SKPI) as a diagnostic instrument for CSA.

Methods and analysis

An observational study to quantify the intraobserver and interobserver reliability and diagnostic accuracy of the SKPI will be performed. A total of 250 subjects from three groups will be included in the study: (1) a group of suspected CSA victims, recruited from three academic paediatric hospitals; (2) a case group of (proven) victims of CSA, recruited in cooperation with the Dutch Police Vice Squad; and (3) a control group of children, recruited from preschools and primary schools. All children will be interviewed using the SKPI, and to investigate reliability, video recordings will be assessed and reassessed by the same and a different blinded rater, respectively. Within 1 year, the results of the SKPI will be compared with the conclusions from the independent child protective services or police reports. If necessary, the SKPI will be modified to improve its reliability and accuracy.

Ethics and dissemination

This validation study of the SKPI is necessary for obtaining a reliable diagnostic tool, which will enable medical and psychological professionals to detect CSA in young victims at an early age and start intervention/treatment.

Trial registration number

NL 50903.018.15.
Evaluating the impact of a multidisciplinary master programme in palliative care on professional learning outcomes: a cross-sectional study after 20 years of experience
Authors: Lasmarías Cristina , Guanter Lourdes , Turrillas Pamela , Peñafiel Judith , Gómez-Batiste Xavier
Published: September 2020

Objective

To assess the impact after 20 years of a Master’s degree in palliative care (MsPC) on the participants’ educational outcomes in terms of educational needs satisfaction, motivation, applicability and professional development (PD) in the palliative care (PC) field.

Methods

A cross-sectional study was conducted between October 2016 and February 2017. Participants were students of the MsPC from 13 editions. An ad hoc survey comprising closed-end questions was provided. Variables such as sociodemographic and learning outcomes, based on Kirkpatrick’s model, were included.

Results

Respondents were 76.6% women, and 60% were between 30 and 50 years of age. Over half of participants were physicians (57.4%), with >15 years of experience (52%). 77% (n=152) reported previous work experience (PWE) in PC, and 23% (n=45) had no PWE. After completing the MsPC, 49% of those without PWE were hired to work in a PC unit, while 84,2% with PWE continued work in a PC-related position. 51.6% professionals with PWE were currently working in other PC areas, such as training or research. High scores were observed on expectations, training needs, motivation in professional practice, PD, applicability and satisfaction, in both groups. Data have shown statistically significant differences on the perceived value of the MsPC to obtain work in the PC field (p=0.006).

Conclusions

This MsPC training programme improves educational outcomes, and promotes PD, regardless of PWE in PC. Interdisciplinary training for all professionals who care for PC individuals is required. To ensure the quality of education in PC programmes, a systematic process of continuous evaluation is needed.
Recent advances in clinical practice: colorectal cancer chemoprevention in the average-risk population
Authors: Chapelle Nicolas , Martel Myriam , Toes-Zoutendijk Esther , Barkun Alan N , Bardou Marc
Published: September 2020

Colorectal cancer (CRC) is one of the most common and lethal malignancies in Western countries. Its development is a multistep process that spans more than 15 years, thereby providing an opportunity for prevention and early detection. The high incidence and mortality rates emphasise the need for prevention and screening. Many countries have therefore introduced CRC screening programmes. It is expected, and preliminary evidence in some countries suggests, that this screening effort will decrease CRC-related mortality rates. CRC prevention involves a healthy lifestyle and chemoprevention—more specifically, oral chemoprevention that can interfere with progression from a normal colonic mucosa to adenocarcinoma. This preventive effect is important for individuals with a genetic predisposition, but also in the general population. The ideal chemopreventive agent, or combination of agents, remains unknown, especially when considering safety during long-term use. This review evaluates the evidence across 80 meta-analyses of interventional and observational studies of CRC prevention using medications, vitamins, supplements and dietary factors. This review suggests that the following factors are associated with a decreased incidence of CRC: aspirin, non-steroidal anti-inflammatory drugs, magnesium, folate, a high consumption of fruits and vegetables, fibre and dairy products. An increased incidence of CRC was observed with frequent alcohol or meat consumption. No evidence of a protective effect for tea, coffee, garlic, fish and soy products was found. The level of evidence is moderate for aspirin, β-carotene and selenium, but is low or very low for all other exposures or interventions.
Small intestinal metabolism is central to whole-body insulin resistance
Authors: Angelini Giulia , Salinari Serenella , Castagneto-Gissey Lidia , Bertuzzi Alessandro , Casella-Mariolo James , Ahlin Sofie , Boskoski Ivo , Gaggini Melania , Raffaelli Marco , Costamagna Guido , Casella Giovanni , Marini Pier Luigi , Gastaldelli Amalia , Bornstein Stefan , Mingrone Geltrude
Published: September 2020

Objective

To assess the role of jejunum in insulin resistance in humans and in experimental animals.

Design

Twenty-four subjects undergoing biliopancreatic diversion (BPD) or Roux-en-Y gastric bypass (RYGB) were enrolled. Insulin sensitivity was measured at baseline and at 1 week after surgery using oral glucose minimal model.

We excluded the jejunum from intestinal continuity in pigs and created a jejunal loop with its vascular and nerve supply intact accessible from two cutaneous stomas, and reconnected the bowel with an end-to-end anastomosis. Glucose stable isotopes were given in the stomach or in the jejunal loop.

In vitro studies using primary porcine and human hepatocytes or myoblasts tested the effects of plasma on gluconeogenesis or glucose uptake and insulin signalling.

Results

Whole-body insulin sensitivity (SI∙104: 0.54±0.12 before vs 0.82±0.11 after BPD, p=0.024 and 0.41±0.09 before vs 0.65±0.09/pM/min after RYGB, p=not significant) and Glucose Disposition Index increased only after BPD. In pigs, insulin sensitivity was significantly lower when glucose was administered in the jejunal loop than in the stomach (glucose rate of disappearance (Rd) area under the curve (AUC)/insulin AUC∙10: 1.82±0.31 vs 2.96±0.33 mmol/pM/min, p=0.0017).

Metabolomics showed a similar pattern before surgery and during jejunal-loop stimulation, pointing to a higher expression of gluconeogenetic substrates, a metabolic signature of impaired insulin sensitivity.

A greater hepatocyte phosphoenolpyruvate-carboxykinase and glucose-6-phosphatase gene expression was elicited with plasma from porcine jejunal loop or before surgery compared with plasma from jejunectomy in pigs or jejunal bypass in humans.

Stimulation of myoblasts with plasma from porcine jejunal loop or before surgery reduced glucose uptake, Ser473-Akt phosphorylation and GLUT4 expression compared with plasma obtained during gastric glucose administration after jejunectomy in pigs or after jejunal bypass in humans.

Conclusion

Proximal gut plays a crucial role in controlling insulin sensitivity through a distinctive metabolic signature involving hepatic gluconeogenesis and muscle insulin resistance. Bypassing the jejunum is beneficial in terms of insulin-mediated glucose disposal in obesity.

Trial registration number

NCT03111953.
Regular use of proton pump inhibitors and risk of type 2 diabetes: results from three prospective cohort studies
Authors: Yuan Jinqiu , He Qiangsheng , Nguyen Long H , Wong Martin C S , Huang Junjie , Yu Yuanyuan , Xia Bin , Tang Yan , He Yulong , Zhang Changhua
Published: September 2020

Objective

The association between the regular use of proton pump inhibitors (PPIs) and the risk of type 2 diabetes remains unclear, although a recent randomised controlled trial showed a trend towards increased risk. This study was undertaken to evaluate the regular use of PPIs and risk of type 2 diabetes.

Method

This is a prospective analysis of 204 689 participants free of diabetes in the Nurses' Health Study (NHS), NHS II and Health Professionals Follow-up Study (HPFS). Type 2 diabetes was confirmed using American Diabetes Association (ADA) diagnostic criteria. We evaluated hazard ratios (HRs) adjusting for demographic factors, lifestyle habits, the presence of comorbidities, use of other medications and clinical indications.

Results

We documented 10 105 incident cases of diabetes over 2 127 471 person-years of follow-up. Regular PPI users had a 24% higher risk of diabetes than non-users (HR 1.24, 95% CI 1.17 to 1.31). The risk of diabetes increased with duration of PPI use. Fully adjusted HRs were 1.05 (95% CI 0.93 to 1.19) for participants who used PPIs for >0–2 years and 1.26 (95% CI 1.18 to 1.35) for participants who used PPIs for >2 years compared with non-users.

Conclusions

Regular use of PPIs was associated with a higher risk of type 2 diabetes and the risk increased with longer duration of use. Physicians should therefore exercise caution when prescribing PPIs, particularly for long-term use.
Molecular landscape of CAPN3 mutations in limb-girdle muscular dystrophy type R1: from a Chinese multicentre analysis to a worldwide perspective
Authors: Zhong Huahua , Zheng Yiming , Zhao Zhe , Lin Pengfei , Xi Jianying , Zhu Wenhua , Lin Jie , Lu Jun , Yu Meng , Zhang Wei , Lv He , Yan Chuanzhu , Hu Jing , Wang Zhaoxia , Lu Jiahong , Zhao Chongbo , Yuan Yun , Luo Sushan
Published: September 2020

Background

Limb-girdle muscular dystrophy type R1 (LGMDR1) can be caused by recessive CAPN3 mutations accounting for the majority of LGMD. To date, no systemic evaluation has been performed to analyse the detrimental and normal mutations on CAPN3 and its hotspots.

Methods

CAPN3 variants (n=112) from a total of 124 patients with LGMDR1 recruited in four centres in China were retrospectively analysed. Then external CAPN3 variants (n=2031) from online databases were integrated with our Chinese cohort data to achieve a worldwide perspective on CAPN3 mutations. According to their related phenotypes (LGMDR1 or normal), we analysed consequence, distribution, ethnicity and severity scores of CAPN3 mutations.

Results

Two hotspot mutations were identified including c.2120A>G in Chinese population and c.550del in Europe. According to the integrated dataset, 521 mutations were classified as LGMDR1-related and converged on exons 1, 10, 5, 22 and 13 of CAPN3. The remaining 1585 variants were classified as normal-population related. The deleterious ratio of LGMDR1-relevant variants to total variants in each population was 0.26 on average with a maximum of 0.35 in Finns and a minimum of 0.21 in South Asians. Severity evaluation showed that Chinese LGMDR1-related variants exhibited a higher risk (Combined Annotation Dependent Depletion score +1.10) than that from database patients (p<0.001).

Conclusions

This study confirmed two hotspots and LGMDR1-related CAPN3 variants, highlighting the advantages in using a data-based comprehensive analysis to achieve a genetic landscape for patients with LGMDR1.
Big data, machine learning and artificial intelligence: a neurologist’s guide
Authors: Auger Stephen D , Jacobs Benjamin M , Dobson Ruth , Marshall Charles R , Noyce Alastair J
Published: September 2020

Modern clinical practice requires the integration and interpretation of ever-expanding volumes of clinical data. There is, therefore, an imperative to develop efficient ways to process and understand these large amounts of data. Neurologists work to understand the function of biological neural networks, butartificialneural networks and other forms of machine learning algorithm are likely to be increasingly encountered in clinical practice. As their use increases, clinicians will need to understand the basic principles and common types of algorithm. We aim to provide a coherent introduction to this jargon-heavy subject and equip neurologists with the tools to understand, critically appraise and apply insights from this burgeoning field.
Evaluation of lamb colostrum supplements
Authors: Bond Cherry
Published: September 2020

Introduction

Half of UK lamb mortality occurs within the first 24 hours of life, with newborn lambs requiring adequate intake of colostrum as soon as possible after birth to combat disease and optimise health. Approximately 22 percent of ewes produce colostrum of inadequate quality; consequently, colostrum replacers and supplements can be offered. Colostrum replacers should fully replace maternal colostrum, whereas colostrum supplements have been developed to provide exogenous immunoglobulins to neonates when natural concentrations are low and should contain a minimum of 3 g IgG/feed.

Methods

Fifteen different colostrum supplements were evaluated. For each product, two different batches were analysed for IgG content.

Results

Levels of IgG/feed ranged from 0.4 to 3.5 g. Products with the highest IgG levels were Lamaid (VetPlus), Colostro+ Lamb (Greencoat), Ovicol (Farmsense) and Shepherdess Lamb Colostrum (Provimi) averaging ≥3.0 g/feed. The remaining 11 products had IgG levels below 3 g IgG/feed, hence could be providing inadequate levels of IgG and potentially impacting on neonatal health.

Conclusion

This study has shown great variability between the quality of commercially available colostrum supplements, so care must be taken when selecting products.
Modeling and predicting evacuation flows during hurricane Irma
Authors: Hong Lingzi , Frias-Martinez Vanessa
Published: September 2020

Evacuations are a common practice to mitigate the potential risks and damages made by natural disasters. However, without proper coordination and management, evacuations can be inefficient and cause negative impact. Local governments and organizations need to have a better understanding of how the population responds to disasters and evacuation recommendations so as to enhance their disaster management processes. Previous studies mostly examine responses to evacuations at the individual or household level by using survey methods. However, population flows during disasters are not just the aggregation of individuals’ decisions, but a result of complex interactions with other individuals and the environment. We propose a method to model evacuation flows and reveal the patterns of evacuation flows at different spatial scales. Specifically, we gathered large-scale geotagged tweets during Hurricane Irma to conduct an empirical study. First, we present a method to characterize evacuation flows at different geographic scales: the state level, considering evacuation flows across southern states affected by Irma; the urban/rural area level, and the county level. Then we demonstrate results on the predictability of evacuation flows in the most affected state, Florida, by using the following environmental factors: the destructive force of the hurricane, the socioeconomic context, and the evacuation policy issued for counties. Feature analyses show that distance is a dominant predictive factor with counties that are geographically closer generally having larger evacuation flows. Socioeconomic levels are positively related to evacuation flows, with popular destinations associated to higher socioeconomic levels. The results presented in this paper can help decision makers to better understand population evacuation behaviors given certain environmental features, which in turn will aid in the design of efficient and informed preparedness and response strategies.
Crosscap number of knots and volume bounds
Authors: Ito Noboru , Takimura Yusuke
Published: September 2020

In this paper, we obtain the crosscap number of any alternating knots by using our recently-introduced diagrammatic knot invariant (Theorem 1). The proof is given by properties of chord diagrams (Kindred proved Theorem 1 independently via other techniques). For non-alternating knots, we give Theorem 2 that generalizes Theorem 1. We also improve known formulas to obtain upper bounds of the crosscap number of knots (alternating or non-alternating) (Theorem 3). As a corollary, this paper connects crosscap numbers and our invariant with other knot invariants such as the Jones polynomial, twist number, crossing number, and hyperbolic volume (Corollaries 1–7). In Appendix A, using Theorem 1, we complete giving the crosscap numbers of the alternating knots with up to 11 crossings including those of the previously unknown values for [Formula: see text] knots (Tables A.1).
A predictive deep-learning approach for homogenization of auxetic kirigami metamaterials with randomly oriented cuts
Authors: Liu Tongwei , Sun Shanwen , Liu Hang , An Ning , Zhou Jinxiong
Published: September 2020

This paper describes a data-driven approach to predict mechanical properties of auxetic kirigami metamaterials with randomly oriented cuts. The finite element method (FEM) was used to generate datasets, the convolutional neural network (CNN) was introduced to train these data, and an implicit mapping between the input orientations of cuts and the output Young’s modulus and Poisson’s ratio of the kirigami sheets was established. With this input–output relationship in hand, a quick estimation of auxetic behavior of kirigami metamaterials is straightforward. Our examples indicate that if the distributions of training and test datasets are close to each other, a good prediction is achievable. Our efforts provide a fast and reliable way to evaluate the homogenized properties of mechanical metamaterials with various microstructures, and thus accelerate the design of mechanical metamaterials for diverse applications.
Underwater metastructure with broadband sound absorption capability in low-frequency range above 20 Hz
Authors: Zhang Ruihao , Song Yifan , Hou Hong , Gao Nansha
Published: September 2020

We present an underwater metastructure with excellent sound absorption effect below 50 Hz. The periodic metastructure unit consists of a conical cavity, rubber matrix, and two metal disks. FEM results show that, in the range of 20–300 Hz, the proposed metastructure demonstrates the excellent sound absorption within 279 Hz bandwidth when the reference absorption coefficient is considered to be 0.5. Displacement vibration diagrams illustrate the addition of two layers of metal disks break the propagation law of acoustic wave in rubber matrix. An anti-phase motion of the rubber matrix emerges due to the presence of the metal disks, then consumes the energy of incident acoustic waves. The geometric parameters of lattice constant [Formula: see text], the thickness [Formula: see text], and the height [Formula: see text] of the upper metal disk are positively correlated with the sound absorption coefficient, while the upper radius [Formula: see text] and the height [Formula: see text] of the conical cavity are negatively correlated with the sound absorption coefficient. The novel design presented in this study could have the potential applications in the realization of an acoustic underwater anechoic layer.
EXPLORING SUCCESSFUL CAMPAIGN PROFILES ON CROWDFUNDING-BASED PROJECT FINANCING: A TREE-BASED COMPARATIVE ANALYSIS
Authors: HARTONO BUDI , TANTINA INDIRA , WIBOWO BUDHI SHOLEH
Published: September 2020

Crowdfunding platforms have become a popular alternative for financing projects. However, campaigners in the platform witness several challenges that affect their success. This study aims to: (a) generate and explore profiles among the non-successful, successful, and very successful campaigns; (b) to interpret investment behaviour of the backers from the profiles. We employed a fresh approach of tree-based comparative analysis (TBCA) as an exploratory tool that augments qualitative comparative analysis (QCA) with data mining evaluation. Campaign profiles were drawn from four groups of 17 predictors, namely: “campaign strategy,” “presentation strategy,” “campaigners” track records, and “temporal data.” We analyzed 647 campaigns in Kickstarter and the analysis was divided into two timelines: before and on the first day of campaigns. The emerging profiles offer practical insights for campaigners to develop a coherent set of campaign decisions and to anticipate the possible outcome. The profiles also indicate that prior to the campaign, investment behaviour is mainly explained by “signal theory.” Interestingly, for the first day of a campaign, the funding ratio performance has the most significant impact on very successful projects — that is, consistent with “herding behaviour.”
Enhanced CNN Models for Binary and Multiclass Student Classification on Temporal Educational Data at the Program Level
Authors: Chau Vo Thi Ngoc , Phung Nguyen Hua
Published: September 2020

In educational data mining, student classification is an important and popular task by predicting final study status of each student. In the existing works, this task has been considered in many various contexts at both course and program levels with different learning approaches. However, its real-world characteristics such as temporal aspects, data imbalance, data overlapping, and data shortage with sparseness have not yet been fully investigated. Making the most of deep learning, our work is the first one addressing those challenges for the program-level student classification task. In a simple but effective manner, convolutional neural networks (CNNs) are proposed to exploit their well-known advantages on images for temporal educational data. As a result, the task is resolved by our enhanced CNN models with more effectiveness and practicability on real datasets. Our CNN models outperform other traditional models and their various variants on a consistent basis for program-level student classification.
Timing of slip across the South Tibetan detachment system and Yadong–Gulu graben, Eastern Himalaya
Authors: Dong Hanwen , Larson Kyle P. , Kellett Dawn A. , Xu Zhiqin , Li Guangwei , Cao Hui , Yi Zhiyu , Zeng Lingsen
Published: September 2020

The Yadong–Gulu graben preserves the kinematic and temporal relationships between east–west-directed extension in southern Tibet and north–south extensional strain in the Himalaya. In the Yadong region, distinct outer and inner top-down-to-the-north segments of the South Tibetan detachment system (STDS) are recognized. Herein, we combine high- to medium-
T
(U–Pb,
40
Ar/
39
Ar) and low-
T
(apatite fission-track, apatite (U–Th)/He and zircon (U–Th)/He) thermochronometry to investigate the timing of slip across the STDS and Yadong–Gulu structures. These data demonstrate that the cessation of the Yadong shear zone, the structurally outer ductile segment of the STDS, occurred
c.
20 Ma and that motion along the inner brittle–ductile Zherger La detachment continued after
c.
16.6 Ma, ending by 11 Ma. The cooling history in the immediate STDS footwall is characterized by two main episodes of relatively rapid cooling and exhumation. The first occurred in the middle Miocene (
c.
15–11 Ma), and is common along-strike of the innermost STDS footwall, related to cooling of the STDS. The second occurred in the late Miocene–Pliocene (
c.
7–3 Ma), and is local to the Yadong–Gulu graben footwall in NW Bhutan, indicating that late Miocene–Pliocene slip along the graben system contributed to exhumation of the STDS east of the graben rift.

Supplementary material:
Tables of analytical data, dating results, and input data and model parameters of HeFTy are available at
https://doi.org/10.6084/m9.figshare.c.5132941
Heterogeneous Univariate Outlier Ensembles in Multidimensional Data
Authors: Pang Guansong , Cao Longbing
Published: September 2020

In outlier detection, recent major research has shifted from developing univariate methods to multivariate methods due to the rapid growth of multidimensional data. However, one typical issue of this paradigm shift is that many multidimensional data often mainly contains
univariate outliers
, in which many features are actually irrelevant. In such cases, multivariate methods are ineffective in identifying such outliers due to the potential biases and the curse of dimensionality brought by irrelevant features. Those univariate outliers might be well detected by applying univariate outlier detectors in individually relevant features. However, it is very challenging to choose a right univariate detector for each individual feature since different features may take very different probability distributions. To address this challenge, we introduce a novel Heterogeneous Univariate Outlier Ensembles (HUOE) framework and its instance ZDD to synthesize a set of heterogeneous univariate outlier detectors as base learners to build heterogeneous ensembles that are optimized for each individual feature. Extensive results on 19 real-world datasets and a collection of synthetic datasets show that ZDD obtains 5%–14% average AUC improvement over four state-of-the-art multivariate ensembles and performs substantially more robustly w.r.t. irrelevant features.
Boosting Item-based Collaborative Filtering via Nearly Uncoupled Random Walks
Authors: Nikolakopoulos Athanasios N. , Karypis George
Published: September 2020

Item-based models
are among the most popular collaborative filtering approaches for building recommender systems.
Random walks
can provide a powerful tool for harvesting the rich network of interactions captured within these models. They can exploit indirect relations between the items, mitigate the effects of sparsity, ensure wider itemspace coverage, as well as increase the diversity of recommendation lists. Their potential however, can be hindered by the tendency of the walks to rapidly concentrate towards the central nodes of the graph, thereby significantly restricting the range of
K
-step distributions that can be exploited for personalized recommendations. In this work, we introduce
RecWalk
; a novel random walk-based method that leverages the spectral properties of
nearly uncoupled Markov chains
to provably lift this limitation and prolong the influence of users’ past preferences on the successive steps of the walk—thereby allowing the walker to explore the underlying network more fruitfully. A comprehensive set of experiments on real-world datasets verify the theoretically predicted properties of the proposed approach and indicate that they are directly linked to significant improvements in top-
n
recommendation accuracy. They also highlight RecWalk’s potential in providing a framework for boosting the performance of item-based models. RecWalk achieves state-of-the-art top-
n
recommendation quality outperforming several competing approaches, including recently proposed methods that rely on deep neural networks.
Exploiting User Preference and Mobile Peer Influence for Human Mobility Annotation
Authors: Hu Renjun , Liu Yanchi , Li Yanyan , Zhou Jingbo , Ma Shuai , Xiong Hui
Published: September 2020

Human mobility annotation aims to assign mobility records the corresponding visiting Point-of-Interests (POIs). It is one of the most fundamental problems for understanding human mobile behaviors. In literature, many efforts have been devoted to annotating mobility records in a pointwise or trajectory-wise manner. However, the user preference factor is not fully explored and, worse still, the mobile peer influence factor has never been integrated. To this end, in this article, we propose a novel framework, named JEPPI, to jointly exploit user preference and mobile peer influence to tackle the problem. In our JEPPI, we first unify the two distinct factors in a behavior-driven user-POI graph. This graph enables us to model user preference with user-POI visiting relationships, and model two types of mobile peer influence with co-location and co-visiting peer relationships, respectively. Moreover, we devise an equivalence-emphasizing metric to reduce redundancy in the second-order co-visiting peer influence. In addition, a mutual augmentation learning approach is proposed to preserve the latent structures of various factors exploited. Notably, our learning approach preserves all factors in a shared representation space such that user preference is learned with mobile peer influence being considered at the same time, and vice versa. In this way, the different factors are mutually augmented and semantically integrated to enhance human mobility annotation. Finally, using two large-scale real-world datasets, we conduct extensive experiments to demonstrate the superiority of our approach compared with the state-of-the-art annotation methods.
PTOPO
Authors: Katsamaki Christina , Rouillier Fabrice , Tsigaridas Elias , Zafeirakopoulos Zafeirakis
Published: September 2020

PTOPO is a MAPLE package computing the topology and describing the geometry of a parametric plane curve. The algorithm behind PTOPO constructs an abstract graph that is isotopic to the curve. PTOPO exploits the benefits of the parametric representation and performs all computations in the parameter space using exact computing. PTOPO computes the topology and visualizes the curve in less than a second for most examples in the literature.
The Curious Strategy of Multipartite Viruses
Authors: Michalakis Yannis , Blanc Stéphane
Published: September 2020

Multipartite virus genomes are composed of several segments, each packaged in a distinct viral particle. Although this puzzling genome architecture is found in ∼17% of known viral species, its distribution among hosts or among distinct types of genome-composing nucleic acid remains poorly understood. No convincing advantage of multipartitism has been identified, yet the maintenance of genomic integrity appears problematic. Here we review recent studies shedding light on these issues. Multipartite viruses rapidly modify the copy number of each segment/gene from one host species to another, a putative benefit if host switches are common. One multipartite virus functions in a multicellular way: The segments do not all need to be present in the same cell and can functionally complement across cells, maintaining genome integrity within hosts. The genomic integrity maintenance during host-to-host transmission needs further elucidation. These features challenge several virology foundations and could apply to other multicomponent viral systems.
Vaccines to Emerging Viruses: Nipah and Hendra
Authors: Amaya Moushimi , Broder Christopher C.
Published: September 2020

Hendra virus (HeV) and Nipah virus (NiV) are bat-borne zoonotic para-myxoviruses identified in the mid- to late 1990s in outbreaks of severe disease in livestock and people in Australia and Malaysia, respectively. HeV repeatedly re-emerges in Australia while NiV continues to cause outbreaks in South Asia (Bangladesh and India), and these viruses have remained transboundary threats. In people and several mammalian species, HeV and NiV infections present as a severe systemic and often fatal neurologic and/or respiratory disease. NiV stands out as a potential pandemic threat because of its associated high case-fatality rates and capacity for human-to-human transmission. The development of effective vaccines, suitable for people and livestock, against HeV and NiV has been a research focus. Here, we review the progress made in NiV and HeV vaccine development, with an emphasis on those approaches that have been tested in established animal challenge models of NiV and HeV infection and disease.
Actinobacteriophages: Genomics, Dynamics, and Applications
Authors: Hatfull Graham F.
Published: September 2020

Actinobacteriophages are viruses that infect bacterial hosts in the phylum Actinobacteria. More than 17,000 actinobacteriophages have been described and over 3,000 complete genome sequences reported, resulting from large-scale, high-impact, integrated research-education initiatives such as the Science Education Alliance Phage Hunters Advancing Genomics and Evolutionary Sciences (SEA-PHAGES) program. Their genomic diversity is enormous; actinobacteriophages comprise many architecturally mosaic genomes with distinct DNA sequences. Their genome diversity is driven by the highly dynamic interactions between phages and their hosts, and prophages can confer a variety of systems that defend against attack by genetically distinct phages; phages can neutralize these defense systems by coding for counter-defense proteins. These phages not only provide insights into diverse and dynamic phage populations but also have provided numerous tools for mycobacterial genetics. A case study using a three-phage cocktail to treat a patient with a drug-resistant Mycobacterium abscessus suggests that phages may have considerable potential for the therapeutic treatment of mycobacterial infections.
Review—Advancements of Nanoscale Structures and Materials in Impedimetric Biosensing Technologies
Authors: Xie Qiu-Zhe , Lin Ming-Wen , Hsu Wei-En , Lin Chih-Ting
Published: September 2020

Nanotechnologies have become one of the primary directions in the development of biosensing technologies. These nano-enhanced biosensors can achieve a lower limit of detection and better sensing characteristics than traditional sensors can. Within these biosensing technologies, impedimetric biosensors, which have been developed for decades in sensing technologies, have obtained great progress with the momentums of nanotechnologies. To address these advancements of nano-enhanced impedimetric biosensing technologies, in this work, we mainly focus on reviews of nanomaterial-based and nanostructure-based impedimetric biosensors. At the same time, several promising new assays based on nanotechnology are also summarized. And the relationship between the limit of detection to nanoscale techniques is presented to promote the following developments of nanoscale biosensing technologies.