bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of equity in healthcare financing and benefits distribution in Tanzania: a cross-sectional study protocol
Authors: Binyaruka Peter , Kuwawenaruwa August , Ally Mariam , Piatti Moritz , Mtei Gemini
Published: February 2022

Introduction

Achieving universal health coverage goal by ensuring access to quality health service without financial hardship is a policy target in many countries. Thus, routine assessments of financial risk protection, and equity in financing and service delivery are required in order to track country progress towards realising this universal coverage target. This study aims to undertake a system-wide assessment of equity in health financing and benefits distribution as well as catastrophic and impoverishing health spending by using the recent national survey data in Tanzania. We aim for updated analyses and compare with previous assessments for trend analyses.

Methods and analysis

We will use cross-sectional data from the national Household Budget Survey 2017/2018 covering 9463 households and 45 935 individuals cross all 26 regions of mainland Tanzania. These data include information on service utilisation, healthcare payments and consumption expenditure. To assess the distribution of healthcare benefits (and in relation to healthcare need) across population subgroups, we will employ a benefit incidence analysis across public and private health providers. The distributions of healthcare benefits across population subgroups will be summarised by concentration indices. The distribution of healthcare financing burdens in relation to household ability-to-pay across population subgroups will be assessed through a financing incidence analysis. Financing incidence analysis will focus on domestic sources (tax revenues, insurance contributions and out-of-pocket payments). Kakwani indices will be used to summarise the distributions of financing burdens according to households’ ability to pay. We will further estimate two measures of financial risk protection (ie, catastrophic health expenditure and impoverishing effect of healthcare payments).

Ethics and dissemination

We will involve secondary data analysis that does not require ethical approval. The results of this study will be disseminated through stakeholder meetings, peer-reviewed journal articles, policy briefs, local and international conferences and through social media platforms.
Effect of profit status in facilities on the mortality of patients on long-term haemodialysis: a nationwide cohort study
Authors: Liu Sheng-Yu , Cheng Chung-Yi , Wu Mei-Yi , Zheng Cai-Mei , Hsu Chih-Cheng , Wu Mai-Szu , Lin Yen-Chung
Published: February 2022

Objectives

Over the past two decades, debates on whether the profit status of dialysis facilities influences patient prognosis have been popular in the USA. Taiwan is one of the regions with the highest rate per capita of kidney replacement therapy worldwide, but no similar research has been conducted to date. This is the first study to address this issue.

Design

This was a nationwide retrospective cohort study based on the Taiwan Renal Registry Data System.

Setting

Patients were categorised into two groups based on the profit status (for-profit, not-for-profit (NFP)) of dialysis facilities, with 31 350 patients in each group. The patients were followed up from 2005 to 2012.

Participants

Patients with uraemia who underwent long-term haemodialysis in private dialysis facilities and public facilities were excluded.

Primary and secondary outcome measures

Survival analyses were performed to compare prognosis between the two groups. Adjustments to patients’ basic profile, and facilities’ geographical distribution, level, and length of ownership were carried out to minimise possible confounding effects.

Results

Analysis revealed that NFP dialysis facilities had better outcomes (HR=0.91, 95% CI (0.89 to 0.93)). A favourable effect remains with the adjustment of the facilities’ level, geographical distribution (HR=0.89, 95% CI (0.86 to 0.93)) or length of ownership (HR=0.95, 95% CI (0.89 to 0.95)). Survival analysis based on the geographical distribution and level of facilities was also conducted, which showed better prognosis in medical centres in the six municipalities, whereas worse prognosis was found in local hospitals not located in these municipalities.

Conclusion

Our findings suggest that in contemporary settings in Taiwan, treatment at NFP dialysis facilities was associated with a better prognosis. The results should be interpreted with caution since the possibility of residual confounding effects and uncertainty of casual relations exist due to the nature of observational studies.
Impact of night shifts on sleeping patterns, psychosocial and physical
well-being among healthcare professionals: a cross-sectional study in a
tertiary hospital in Saudi Arabia
Authors: Qanash Sultan , Alwafi Hassan , Barasheed Shaima , Bashnaini Shahad , Andergiri Rahaf , Yaghmour Loujain , Murad Weam , Shabrawishi Mohammed , Naser Abdallah Y , Alsywid Basim
Published: February 2022

Background

Shift work and night shifts are very common in healthcare
organisations worldwide. However, healthcare professionals doing shift
work and night shifts are exposed to several stressors with
psychological, social, physical and sleeping consequences. This study
aimed to evaluate the effect of night shifts on the psychosocial,
physical well-being and sleeping patterns of healthcare professionals in
Saudi Arabia.

Methods

We conducted an observational cross-sectional study from July to
September 2019 at King Abdulaziz Medical City, Jeddah, Saudi Arabia.
Convenience sampling technique was used to recruit healthcare providers
to participate in the study. The outcomes measured included the effect
of working hours of healthcare workers on psychosocial and physical
health, substance use, and sleep quality and patterns. Pearson’s
χ2 test was used to compare proportions, and
Student’s t-test/Analysis of variance (ANOVA) was used to examine the
mean differences among different demographic groups.

Results

A total of 352 healthcare providers were involved in the study, of
whom only 272 were night shift workers. The mean level of job
satisfaction was higher among day shift workers than night shift
workers: the mean scores were 3.82 (SD=0.93) and 3.48 (SD=1.04),
respectively, p=0.007. Moreover, social life was more adversely affected
among night shift workers compared with day shift workers: 3.95
(SD=1.11) and 3.61 (SD=1.25), respectively, p<0.030. Likewise, family
life was more adversely affected among night shift workers than day
shift workers, with a mean of 3.92 (SD=1.10) and 3.50 (SD=1.21),
respectively, p<0.006. Around 71% of night shift workers reported
having poor-quality sleep compared with 50% of day shift workers
(p=0.001).

Conclusion

Quality of life is poor among night shift workers than day shift
workers, particularly concerning sleep and social and physical outcomes.
Further research is needed to investigate factors associated with the
quality of sleep and the psychosocial and physical well-being of
healthcare professionals working night shifts.
Remote cognitive assessment of older adults in rural areas by
telemedicine and automatic speech and video analysis: protocol for a
cross-over feasibility study
Authors: König Alexandra , Zeghari Radia , Guerchouche Rachid , Duc Tran Minh , Bremond François , Linz Nicklas , Lindsay Hali , Langel Kai , Ramakers Inez , Lemoine Pascale , Bultingaire Vincent , Robert Philippe
Published: February 2022

Introduction

Early detection of cognitive impairments is crucial for the
successful implementation of preventive strategies. However, in rural
isolated areas or so-called ‘medical deserts’, access to diagnosis and
care is very limited. With the current pandemic crisis, now even more
than ever, remote solutions such as telemedicine platforms represent
great potential and can help to overcome this barrier. Moreover, current
advances made in voice and image analysis can help overcome the barrier
of physical distance by providing additional information on a patients’
emotional and cognitive state. Therefore, the aim of this study is to
evaluate the feasibility and reliability of a videoconference system for
remote cognitive testing empowered by automatic speech and video
analysis.

Methods and analysis

60 participants (aged 55 and older) with and without cognitive
impairment will be recruited. A complete neuropsychological assessment
including a short clinical interview will be administered in two
conditions, once by telemedicine and once by face-to-face. The order of
administration procedure will be counterbalanced so half of the sample
starts with the videoconference condition and the other half with the
face-to-face condition. Acceptability and user experience will be
assessed among participants and clinicians in a qualitative and
quantitative manner. Speech and video features will be extracted and
analysed to obtain additional information on mood and engagement levels.
In a subgroup, measurements of stress indicators such as heart rate and
skin conductance will be compared.

Ethics and dissemination

The procedures are not invasive and there are no expected risks or
burdens to participants. All participants will be informed that this is
an observational study and their consent taken prior to the experiment.
Demonstration of the effectiveness of such technology makes it possible
to diffuse its use across all rural areas (‘medical deserts’) and thus,
to improve the early diagnosis of neurodegenerative pathologies, while
providing data crucial for basic research. Results from this study will
be published in peer-reviewed journals.
Suicide after cancer diagnosis in South Korea: a population-based cohort
study
Authors: Choi Young , Park Eun-Cheol
Published: February 2022

Objective

The present study aimed to determine whether the suicide risk
increased after a cancer diagnosis.

Design

Population-based cohort study.

Setting and participants

This study incorporated the National Health Insurance
Service-National Sample Cohort in South Korea. Of the 975 348 subjects,
39 027 with cancer and 936 321 who were cancer free participated between
2005 and 2013.

Primary outcome measure

Suicide.

Results

A total of 110 suicides (82 men, 28 women) were identified among
these 39 027 subjects with cancer during a total of 127 184
person-years; among the 936 321 cancer-free subjects, 2163 suicides were
reported during a total of 8 222 479 person-years. Cox proportional
hazards models were used to compare all-cause and suicide mortalities
after cancer diagnosis following adjustment for possible confounding
covariates. After adjusting for factors related to suicide, we
identified an elevated relative risk of suicide among patients with
cancer (HR: 1.480, 95% CI: 1.209 to 1.812). Among men, the relative risk
was substantially increased among patients with lip, oral
cavity/pharyngeal, colon and rectal, pancreatic and lung cancers when
compared with cancer-free subjects; whereas among women, the relative
risk was substantially increased among patients with colon and rectal
cancers.

Conclusion

Our study observed an increased risk of suicide among patients with
cancer that varied according to the anatomical cancer site, even after
accounting for clinical comorbidities and psychiatric illness. Our
findings indicate a need for social support and suicide prevention
strategies for patients with cancer.
COVID-19 hinterland: surveilling the self-reported impacts of the pandemic on diabetes management in the USA (cross-sectional results of the iNPHORM study)
Authors: Ratzki-Leewing Alexandria A , Ryan Bridget L , Buchenberger John D , Dickens Joseph W , Black Jason E , Harris Stewart B
Published: February 2022

Main objective

To determine how and to what extent COVID-19 has affected real-world, self-reported glycaemic management in Americans with type 1 or type 2 diabetes taking insulin and/or secretagogues, with or without infection.

Design

A cross-sectional substudy using data from the Investigating Novel Predictions of Hypoglycemia Occurrence using Real-world Models panel survey.

Setting

USA.

Participants

Americans 18–90 years old with type 1 or 2 diabetes taking insulin and/or secretagogues were conveniently sampled from a probability-based internet panel.

Primary outcome measure

A structured, COVID-19-specific questionnaire was administered to assess the impact of the pandemic (irrespective of infection) on socioeconomic, behavioural/clinical and psychosocial aspects of glycaemic management.

Results

Data from 667 respondents (type 1 diabetes: 18%; type 2 diabetes: 82%) were analysed. Almost 25% reported A1c values ≥8.1%. Rates of severe and non-severe hypoglycaemia were 0.68 (95% CI 0.5 to 0.96) and 2.75 (95% CI 2.4 to 3.1) events per person-month, respectively. Ten respondents reported a confirmed or probable COVID-19 diagnosis. Because of the pandemic, 24% of respondents experienced difficulties affording housing; 28% struggled to maintain sufficient food to avoid hypoglycaemia; and 19% and 17% reported challenges accessing diabetes therapies and testing strips, respectively. Over one-quarter reported issues retrieving antihyperglycaemics from the pharmacy and over one-third reported challenges consulting with diabetes providers. The pandemic contributed to therapeutic non-adherence (14%), drug rationing (17%) and reduced monitoring (16%). Many struggled to keep track, and in control, of hypoglycaemia (12%–15%) and lacked social support to help manage their risk (19%). Nearly half reported decreased physical activity. Few statistically significant differences were observed by diabetes type.

Conclusions

COVID-19 was found to cause substantial self-reported deficiencies in glycaemic management. Study results signal the need for decisive action to restabilise routine diabetes care in the USA.

Trial registration number

NCT04219514.
Systems thinking and complexity science methods and the policy process in non-communicable disease prevention: a systematic scoping review protocol
Authors: Clifford Astbury Chloe , McGill Elizabeth , Egan Matt , Penney Tarra L
Published: February 2022

Introduction

Given the complex causal origins of many non-communicable diseases (NCDs), and the complex landscapes in which policies designed to tackle them are made and unfold, the need for systems thinking and complexity science (STCS) in developing effective policy solutions has been emphasised. While numerous methods informed by STCS have been applied to the policy process in NCD prevention, these applications have not been systematically catalogued. The aim of this scoping review is to identify existing applications of methods informed by STCS to the policy process for NCD prevention, documenting which domains of the policy process they have been applied to.

Methods and analysis

A systematic scoping review methodology will be used. Identification: We will search Medline, SCOPUS, Embase and Web of Science using search terms combining STCS, NCD prevention and the policy process. All records published in English will be eligible for inclusion, regardless of study design. Selection: We will screen titles and abstracts and extract data according to published guidelines for scoping reviews. In order to determine the quality of the included studies, we will use the approach developed by Dixon-Woods et al, excluding studies identified as fatally flawed, and determining the credibility and contribution of included studies. Synthesis: We will identify relevant studies, summarising key data from each study and mapping applications of methods informed by STCS to different parts of the policy process. Review findings will provide a useful reference for policy-makers, outlining which domains of the policy process different methods have been applied to.

Ethics and dissemination

Formal ethical approval is not required, as the study does not involve primary data collection. The findings of this study will be disseminated through a peer-reviewed publication, presentations and summaries for key stakeholders.
Cross-sectional Survey of Medical student Attitudes to Research and
Training pathways (SMART) in the UK: study protocol
Authors: Roche Sophie , Bandyopadhyay Soham , Grassam-Rowe Alexander , Brown Robin Andrew , Iveson Poppy , Mallett Garry , Eggington Holly , Swales Catherine
Published: February 2022

Background

An understanding and appreciation of scientific research is a key
quality of the modern clinician. Yet the Medical Schools Council has
previously reported a reduction in the number of clinicians performing
research. To explore the reasons for this difficulty, this multicentre,
cross-sectional study aims to determine the medical student involvement
and perceptions of research and research-orientated careers. It will
additionally identify perceived barriers and incentives to participating
in research as a student.

Methods and analysis

This cross-sectional study of medical students at UK medical schools
recognised by the General Medical Council will be administered using an
online questionnaire. This will be disseminated nationally over a
2-month period through collaborative university medical school and
student networks. The primary outcome is to determine the extent to
which medical students are currently involved in research. Secondary
outcomes include identifying the personal and demographic factors
involved in incentivising and deterring medical students from becoming
involved in research during medical school. This will be achieved using
a selection of Likert scale, multiple-choice and free text questions.
Ordinal logistic regression analysis will be performed to understand the
association between specific factors and student involvement in
research. This study will also characterise the proportion of medical
students who are currently interested in conducting research in the
future.

Ethics and dissemination

Ethics approval has been obtained from the Medical Sciences
Interdivisional Research Ethics Committee, Oxford, England. The results
will be disseminated via publication in a peer-reviewed medical journal
and may be presented at local, regional, national and international
conferences by medical student collaborators.
Performance of a novel ECG criterion for improving detection of left ventricular hypertrophy: a cross-sectional study in a general Chinese population
Authors: Chen Yanli , Sun Guozhe , Guo Xiaofan , Li Zhao , Li Guangxiao , Zhou Ying , Yang Hongmei , Yu Shasha , Zheng Liqiang , Sun Yingxian
Published: February 2022

Objectives

The sensitivity of ECG for detecting left ventricular hypertrophy (LVH) is low. The aim of this study was to explore a better ECG criterion for screening LVH in a large general Chinese population.

Design

Case–control study.

Setting

China Medical University in Shenyang, China.

Participants

All permanent residents in Dawa, Zhangwu and Liaoyang aged 35 years or older were invited. Participants with unqualified data, pacemaker rhythm, frequent premature ventricular beats, Wolff-Parkinson-White syndrome, complete bundle branch block, myocardial infarction or hypertrophic cardiomyopathy were excluded. A total of 10 360 subjects (4630 males) were recruited.

Interventions

A novel ECG criterion (Northeast China Rural Cardiovascular Health Study (NCRCHS)) composed of different ratios of maximum R wave in lead V5 or V6 (RV5/V6), S wave in lead V3 (SV3) and R wave in lead aVL (RaVL) was proposed and validated using multiple linear regression. Receiver-operating characteristic curves were used to compare the NCRCHS criterion with traditional criteria for LVH detection.

Results

An optimised model (15*RaVL+8*SV3+7*RV5/V6) was constructed (R2 0.192, p<0.001) with the cut-off values of 36.8 mV for males and 26.1 mV for females. The maximum area under the curve was obtained using the NCRCHS criterion (male 0.74, 95% CI 0.73 to 0.75; female 0.73, 95% CI 0.72 to 0.75), followed by Cornell voltage criterion, Sokolow-Lyon criterion, Peguero-Lo Presti criterion, multi-ethnic study of atherosclerosis (MESA)-specific criterion and Syst-Eur voltage criterion. Compared with the Cornell voltage criterion, the NCRCHS criterion had a significantly higher sensitivity for detecting LVH at the same level of specificity (p<0.05).

Conclusions

The NCRCHS criterion significantly improved sensitivity for LVH detection in a general Chinese population, with cut-off values of 36.8 and 26.1 mV for males and females, respectively. This criterion can detect LVH earlier and better and may prevent subsequent cardiovascular diseases.
Perceptions on undertaking regular asymptomatic self-testing for COVID-19 using lateral flow tests: a qualitative study of university students and staff
Authors: Wanat Marta , Logan Mary , Hirst Jennifer A , Vicary Charles , Lee Joseph J , Perera Rafael , Tracey Irene , Duff Gordon , Tufano Peter , Fanshawe Thomas , Mwandigha Lazaro , Nicholson Brian D , Tonkin-Crine Sarah , Hobbs Richard
Published: February 2022

Objectives

Successful implementation of asymptomatic testing programmes using lateral flow tests (LFTs) depends on several factors, including feasibility, acceptability and how people act on test results. We aimed to examine experiences of university students and staff of regular asymptomatic self-testing using LFTs, and their subsequent behaviours.

Design and setting

A qualitative study using semistructured remote interviews and qualitative survey responses, which were analysed thematically.

Participants

People who were participating in weekly testing feasibility study, between October 2020 and January 2021, at the University of Oxford.

Results

We interviewed 18 and surveyed 214 participants. Participants were motivated to regularly self-test as they wanted to know whether or not they were infected with SARS-CoV-2. Most reported that a negative test result did not change their behaviour, but it did provide them with reassurance to engage with permitted activities. In contrast, some participants reported making decisions about visiting other people because they felt reassured by a negative test result. Participants valued the training but some still doubted their ability to carry out the test. Participants were concerned about safety of attending test sites with lots of people and reported home testing was most convenient.

Conclusions

Clear messages highlighting the benefits of regular testing for family, friends and society in identifying asymptomatic cases are needed. This should be coupled with transparent communication about the accuracy of LFTs and how to act on either a positive or negative result. Concerns about safety, convenience of testing and ability to do tests need to be addressed to ensure successful scaling up of asymptomatic testing.
Field investigation into the performance of pipe pile in soft clay under static and cyclic axial loads
Authors: Peng Chun-Yin , Chen Ren-Peng , Wang Jian-Fu , Wang Han-Lin
Published: February 2022

We performed a field investigation into the effective stress, the shaft friction at the pile–soil interface, and the pile-end base resistance of a 29.5 m long prestressed concrete pipe pile in soft clay under static and cyclic loadings (50 000 cycles). Our results indicate that under low-level cyclic loading (CLR ≤ 0.2, where CLR is the ratio of cyclic load amplitude to the ultimate capacity), the pore water pressure at the pile–soil interface initially accumulates with the number of cycles, followed by gradual dissipation after reaching its maximum value. The effective stress also initially decreases and then increases. The shaft friction increases after cyclic loading. Owing to axial load redistribution, the base resistance decreases with the number of cycles. When the pile is subjected to high-level cyclic loading (CLR ≥ 0.5), the pore water pressure at the pile–soil interface keeps accumulating while the effective stress continues to decrease, leading to the degradation of shaft friction. The base resistance increases as a result of axial load redistribution. In particular, we analyzed the effects of the static load level and the cyclic load level on the changes shaft friction.
Tackling racial bias in automated online hate detection: Towards fair and accurate detection of hateful users with geometric deep learning
Authors: Ahmed Zo , Vidgen Bertie , Hale Scott A.
Published: February 2022

Online hate is a growing concern on many social media platforms, making them unwelcoming and unsafe. To combat this, technology companies are increasingly developing techniques to automatically identify and sanction hateful users. However, accurate detection of such users remains a challenge due to the contextual nature of speech, whose meaning depends on the social setting in which it is used. This contextual nature of speech has also led to minoritized users, especially African–Americans, to be unfairly detected as ‘hateful’ by the very algorithms designed to protect them. To resolve this problem of inaccurate and unfair hate detection, research has focused on developing machine learning (ML) systems that better understand textual context. Incorporating social networks of hateful users has not received as much attention, despite social science research suggesting it provides rich contextual information. We present a system for more accurately and fairly detecting hateful users by incorporating social network information through geometric deep learning. Geometric deep learning is a ML technique that dynamically learns information-rich network representations. We make two main contributions: first, we demonstrate that adding network information with geometric deep learning produces a more accurate classifier compared with other techniques that either exclude network information entirely or incorporate it through manual feature engineering. Our best performing model achieves an AUC score of 90.8% on a previously released hateful user dataset. Second, we show that such information also leads to fairer outcomes: using the ‘predictive equality’ fairness criteria, we compare the false positive rates of our geometric learning algorithm to other ML techniques and find that our best-performing classifier has no false positives among a subset of African–American users. A neural network without network information has the largest number of false positives at 26, while a neural network incorporating manual network features has 13 false positives among African–American users. The system we present highlights the importance of effectively incorporating social network features in automated hateful user detection, raising new opportunities to improve how online hate is tackled.
Salient Regions and Hierarchical Indexing for Crop Disease Images
Authors: Gao Ronghua , Li Qifeng , Wu Huarui , Lu Feng
Published: February 2022

With the development of modern agricultural facilities, crop diseases recognition, nutritional status and morphology achieved rapid growth. To avoid yield loss caused by the delay of disease detection, digital images that contain information with respect to crop growth, disease type and nutrition deficiency have been studied by some researchers. However, traditional image processing methods fail to extract typical disease features of crop images with ambiguous disease information. In this paper, a crop disease image recognition technique based on the salient region and hierarchical indexing was proposed. Improved Harris algorithm and maximum radius were used to calculate the widest salient region. In order to eliminate the effect of different salience distribution ranges between different features, a group of images in the cucumber disease image library were normalized. Experiment results indicate that the time complexity of each algorithm will go up as the size of the dataset increase. Especially when testing large datasets, nonhierarchical and nonclustering, hierarchical and nonclustering and hierarchical based on points all tend to raise the algorithm’s time complexity. Plant Village dataset and AI Challenger 2018 dataset were utilized to compare the recognition performances among the models based on machine learning, neural network, deep learning and our methods. The experiment results show that the method proposed in this paper is capable of recognizing local similar images effectively rather than global similar images, therefore, it has better recognition performance than the model learning methods in the early detection stage of crop disease.
A Framework for Solving the Source Localization of the EEG Measurements with the Application of Particle Filtering with Branching Resampling
Authors: Veeramalla Santhosh Kumar , Hindumathi V.
Published: February 2022

Inverse algorithms are used to assess EEG source parameters. This involves identifying unknown voxels in hundreds of different regions, giving an incomplete picture of the brain. There are no uniform solutions since the same sensor output may come from many source configurations. To overcome the lack of uniqueness, one must consider previous information and parameters inherent in the source. Our goal is to predict the location of brain sources from the recorded EEG signal without any prior knowledge of sources. We applied a particle filter to locate the brain sources in this article. The degeneracy of particle weights limits the particle filter’s performance. Various resampling techniques are suggested to address this problem. The performance of the branching resampling approach is compared to a systematic resampling method for brain source localization. To perform assessment and comparison studies, both simulated and real EEG data are used.
THE RISE OF BOROPHENE AND BOROPHENE NANORIBBONS: A POTENTIAL QUANTUM ELECTRONICS MATERIAL
Authors: KHARWAR SAURABH , SINGH SANGEETA
Published: February 2022

Borophene, a boron analogue of graphene, has been considered as an innovative two-dimensional (2D) material for the scientific and research community. First 2D boron sheet was reported in 2015 by growing it on Ag substrate. Attributable to its exceptional structural, electronic, and spin properties, it has earned enormous exploration interests in the multifaceted fields of material science, nanotechnology and computational physics. Borophene is the newest rising 2D material, which demonstrates various diversified configurations that can be marked by anisotropic and polymorphism. These configurations enabled enhanced tailoring properties of borophene for various applications. This review provides brief discussion on various experimentally synthesized borophene and borophene nanoribbon (BNR), their structural, electronic, and magnetic properties variations along with the width effect. Based upon the type of edges, BNRs are categorized as line edge-BNR (LE-BNR) and zigzag-BNR (ZZ-BNR). Electronic properties of LE-BNR with vacancy defect show semiconductor behavior and ZZ-BNR indicates metallic property. It covers all the structural allotropes, their synthesis, stability and other crucial intrinsic properties, characterization and tailoring of physical properties. Hence, this comprehensive review reported here incorporates the crucial recent experimental and theoretical advances on borophene and BNRs till date. This work also covers recent modifications reported in borophene and BNR to alter their properties as per the demands of various application areas such as nanoelectronic devices, interconnects, biosensors, metal detectors and gas sensors.
CALIBRATING LOCAL VOLATILITY MODELS WITH STOCHASTIC DRIFT AND DIFFUSION
Authors: ÖGETBIL ORCAN , GANESAN NARAYAN , HIENTZSCH BERNHARD
Published: February 2022

We propose Monte Carlo calibration algorithms for three models: local volatility with stochastic interest rates, stochastic local volatility with deterministic interest rates and finally stochastic local volatility with stochastic interest rates. For each model, we include detailed derivations of the corresponding SDE systems and list the required input data and steps for calibration. We give conditions under which a local volatility can exist given European option prices, stochastic interest rate model parameters, and correlations. The models are posed in a foreign exchange setting. The drift term for the exchange rate is given as a difference of two stochastic short rates, domestic and foreign; each modeled by a Gaussian one-factor model with deterministic shift (G1[Formula: see text]) process. For stochastic volatility, we model the variance for the exchange rate by a Cox–Ingersoll–Ross (CIR) process. We include tests to show the convergence and the accuracy of the proposed algorithms.
Poro-Thermoelastic Waves in a Homogeneous Anisotropic Plate Plunged in the Inviscid Fluid
Authors: Pathania Vijayata , Dhiman Pankaj
Published: February 2022

This paper inspects the behavior of thermoelastic waves in the homogeneous, transversely isotropic plate containing voids immersed in the inviscid fluid in reference to the one-temperature generalized model of thermoelasticity. The basic governing equations for the solid plate have been developed in the context of the linear theory of poro-thermoelasticity. Helmholtz decomposition principle has been employed to solve the equations of motion for liquid. For the stress-free solid-liquid interfaces, the isothermal and thermally insulated boundary conditions have been applied simultaneously on the obtained solutions. The solutions of governing equations reveal that there exists a coupled system of waves namely thermal waves, void wave motion, and elastic waves, and a decoupled purely transverse wave. Apart from that, one mechanical wave in each liquid layer also exists. The secular equation for anti-symmetric and symmetric modes of vibration has been derived which better explains wave motion. To unveil the wave characteristics, the numerical–functional iteration technique has been employed for generating numerical data and results have been validated by tracing out the various graphs. The effects of temperature change, as well as voids in the solid plate and inviscid liquid in the neighborhood of the plate, have been noticed on phase velocity, attenuation coefficient, etc
Adaptive Trading Strategies Across Liquidity Pools
Authors: Baldacci Bastien , Manziuk Iuliia
Published: February 2022

In this paper, we provide a flexible framework for optimal trading in an asset listed on different venues. We take into account the dependencies between the imbalance and spread of the venues, and allow for partial execution of limit orders at different limits as well as market orders. We present a Bayesian update of the model parameters to take into account possibly changing market conditions and propose extensions to include short/long trading signals, market impact or hidden liquidity. To solve the stochastic control problem of the trader we apply the finite difference method and also develop a deep reinforcement learning algorithm allowing to consider more complex settings.
The impact of clay fraction on the strength and stress ratio (
K
0
) in Gulf of Mexico mudrocks and quartz silt mixtures: implications for borehole stability and fracture gradient
Authors: Zablocki Mark , Germaine John T. , Plumb Richard , Flemings Peter B.
Published: February 2022

Mudrock strength parameters are required to improve the prediction of fracture gradient during drilling in poorly consolidated formations. Understanding the influence that mineral composition and consolidation stress have on the mechanical properties of mudrocks aids safe well design. Small changes in the mudrock clay content are shown to have significant effects on two important engineering parameters: the lateral stress ratio at rest,
K
0
, and the critical state effective friction angle,

ϕ

′
cs
. A laboratory-testing programme using quartz silt and a Gulf of Mexico clay mixture investigates the effects of mudrock clay content on
K
0
and

ϕ

′
cs
at two stress levels: 1 and 10 MPa. Values of
K
0
and

ϕ

′
cs
were obtained by subjecting composition-controlled clay–silt specimens to a drained uniaxial vertical strain (
K
0
consolidation) phase, followed by an undrained compression triaxial shear phase. Triaxial tests illustrate consistent and systematic increases in
K
0
and decreases in

ϕ

′
cs
, with increases in clay content at both stress levels. Stress dependence is observed through increases in
K
0
and decreases in

ϕ

′
cs
with increases in stress level. Stress-dependent behaviour is shown to be more pronounced in mudrocks of high clay content. A predictive model is presented for
K
0
in normally consolidated mudrocks, as a function of clay content and effective stress. The model is used to calculate the fracture gradient (least horizontal stress) profile at the International Ocean Drilling Program (IODP) Expedition 308 Site 1324. The estimated fracture gradient illustrates the effects of clay content and consolidation stress on safe mud weight design.

Thematic collection:
This article is part of the Geopressure collection available at:
https://www.lyellcollection.org/cc/geopressure
SocNavBench: A Grounded Simulation Testing Framework for Evaluating Social Navigation
Authors: Biswas Abhijat , Wang Allan , Silvera Gustavo , Steinfeld Aaron , Admoni Henny
Published: February 2022

The human-robot interaction community has developed many methods for robots to navigate safely and socially alongside humans. However, experimental procedures to evaluate these works are usually constructed on a per-method basis. Such disparate evaluations make it difficult to compare the performance of such methods across the literature. To bridge this gap, we introduce
SocNavBench
, a simulation framework for evaluating social navigation algorithms.
SocNavBench
comprises a simulator with photo-realistic capabilities and curated social navigation scenarios grounded in real-world pedestrian data. We also provide an implementation of a suite of metrics to quantify the performance of navigation algorithms on these scenarios. Altogether,
SocNavBench
provides a test framework for evaluating disparate social navigation methods in a consistent and interpretable manner. To illustrate its use, we demonstrate testing three existing social navigation methods and a baseline method on
SocNavBench
, showing how the suite of metrics helps infer their performance trade-offs. Our code is open-source, allowing the addition of new scenarios and metrics by the community to help evolve
SocNavBench
to reflect advancements in our understanding of social navigation.
Hierarchical Sliding Inference Generator for Question-driven Abstractive Answer Summarization
Authors: Li Bing , Yang Peng , Zhao Hanlin , Zhang Penghui , Liu Zijian
Published: February 2022

Text summarization on non-factoid question answering (NQA) aims at identifying the core information of redundant answer guidance using questions, which can dramatically improve answer readability and comprehensibility. Most existing approaches focus on extracting query-related sentences to construct a summary, where the logical connection of natural language and the hierarchical interpretable semantic association are often neglected, thus degrading performance. To address these issues, we propose a novel question-driven abstractive answer summarization model, called the
H
ierarchical
S
liding
I
nference
G
enerator (HSIG), to form inferable and interpretable summaries by explicitly introducing hierarchical information reasoning between questions and corresponding answers. Specifically, we first apply an elaborately designed hierarchical sliding fusion inference model to determine the most relevant question sentence-level representation that provides a deeper interpretable basis for sentence selection in summarization, which further increases computational performance on the premise of following the semantic inheritance structure. Additionally, to improve summary fluency, we construct a double-driven selective generator to integrate various semantic information from two mutual question-and-answer perspectives. Experimental results illustrate that compared with state-of-the-art baselines, our model achieves remarkable improvement on two benchmark datasets and specifically improves the 2.46 ROUGE-1 points on PubMedQA, which demonstrates the superiority of our model on abstractive summarization with hierarchical sequential reasoning.
Communication—Hollow MnO
x
@Nanoparticles Electrospun Fibers with High Porosity for Formaldehyde Removal at Room Temperature
Authors: Zhou Shicheng , Wang Chenxi , Fang Hui , Li Daoyuan , Du Yu , Qi Xiaoyun
Published: February 2022

MnO
x
nanomaterials are regarded as promising catalysts for degrading formaldehyde (HCHO). However, the catalytic nanoparticles (NPs) suffer from the catalysis performance and stability loss due to their weak combination with the substrates and easy-aggregation nature. Herein, we develop a facile method to synthesize hollow porous MnO
x
@NPs fibers via electrospinning and two-step oxidation. The NPs, e.g., TiO2 and SnO2, can be efficiently loaded into MnO
x
fibers’ inner frame through a simple dispersion process. The hollow porous structures obtained through two-step oxidation increase the HCHO removal efficiency by 8 times, while MnO
x
@SnO2 fibers exhibit the enhanced catalytic performance by 23.0% more.
Ionic Liquid Gating Control of Oxygen Vacancies in the La0.8Ba0.2MnO3 Ultrathin Films
Authors: Lin Guankai , Wang Haoru , Cai Xuhui , Tong Wei , Zhu Hong
Published: February 2022

In this work, we show ionic liquid field-effect of La0.8Ba0.2MnO3 (LBMO) untrathin films prepared by the sol-gel method. When applying a positive gate voltage (V
g) in vacuum, it is found that the film resistivity continuously increases tenfold within hours or minutes depending on the magnitude of V
g, accompanied with disappearance of the low-temperature metallic transport behavior. In contrast, the film resistivity changes little in air or under a negative applied V
g. Such a difference reveals that the increased resistivity is related to the oxygen depletion in the films under the positive V
g, especially at the grain boundaries. After removing the positive V
g in vacuum, the room-temperature resistivity begins to fall off and the low-temperature metallic state is partially restored in several tens hours, suggesting oxygen diffusion from the relatively oxygen-rich grains to the seriously oxygen-deficient grain boundaries. Furthermore, the oxygen content in the oxygen-deficient films can be almost fully restored in ten minutes by external annealing (200 °C) or Joule self-heating (21 mA) the films in air. These experimental findings provide an additional method in tuning oxygen vacancies in transition-metal oxide films.
Evaluation of Bone Mineral Density, Serum Osteocalcin, and Osteopontin Levels in Postmenopausal Women with Type 2 Diabetes Mellitus, with/without Osteoporosis
Authors: Roomi Ali B. , Mahdi Salih Abdul-Hassan , Noori Sarmad D. , Nori Wassan , Tariq Saba
Published: February 2022

Objective. Osteoporosis (OP) is a worldwide ailment; we aim to establish new biomarkers in diagnosis by determining the levels of serum osteocalcin and osteopontin along with bone mineral density (BMD) and lumbar T-score, in postmenopausal women with type 2 diabetes mellitus (T2DM) with or without OP. Methods. This observational study included 160 postmenopausal women who were an attendee at outpatient clinics in Al-Hussein Hospital, Thi-Qar province; subdivided into 3 groups based on their T-score testing: Group I (n = 40) comprised postmenopausal women without T2DM as controls, Group II (n = 60) comprised postmenopausal women with T2DM but without OP, and Group III (n = 60) comprised postmenopausal women with T2DM with OP. The dual-energy X-ray absorptiometry was used to measure the BMD (total body, lumbar spine, and femoral) and T-score for lumbar spine and femoral. Glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), osteocalcin, and osteopontin levels were assessed in all three groups. Results. Compared with controls, Group III demonstrated significantly lower BMD (total body, lumbar spine, and femoral), T-score for lumbar spine and femoral, serum osteocalcin, and osteopontin levels than Group II and Group I (

P
<
0.001

). FBG and HbA1c levels were significantly higher in Group III than in Groups I and II (

P
<
0.001

). A negative correlation was proved between HbA1c levels with BMD, osteocalcin levels, and osteopontin levels in the three groups. Conclusions. Iraqi postmenopausal women with T2DM had a significantly lower bone mineral density, serum osteocalcin, and osteopontin levels. These results may serve as adjuvants in screening for OP, particularly among diabetic patients.
Optimised Implant Selection Using Digital Volume Tomography (DVT) Osteodensitometry
Authors: Nilius Manfred , Winterhoff Jörg
Published: February 2022

Purpose. The density of the jaw bone has an inhomogeneous distribution and, even within partial volumes, varies more or less strongly from the size of typical implants. Consequently, the primary stability of implants using conventional techniques can only ever be determined postimplantation. The aim of the present case report is to present digital volume tomography (DVT) osteodensitometry as a procedure for assessing the primary stability preimplantation and to evaluate its benefits. Methods. An orthopantomogram (OPT) and vertical sections, including bone density measurement, were obtained from a DVT in the course of preimplantological diagnosis. Conventional implant planning and densitometric simulation were performed on this basis. Results. Densitometric simulation enabled assessment of the bone density at the interface to the implant body preimplantation. This procedure provides not only an overall value (averaged density) but also allocation of bone areas with different densities to the adjacent areas on the implant surface. This then allows the implant with the best possible macroscopic geometry and optimum position to be selected, with the aim of maximising primary stability. In the present case, the maximum torques during insertion confirmed the densitometric values recorded in advance. Conclusion. DVT osteodensitometry enables selection of an implant optimised to bone density distribution. At the same time, the point at which loading occurs can already be defined at the planning stage, thanks to the predictable primary stability. A standard integration of DVT osteodensitometry in the algorithms of implant planning software thus seems desirable.
Ultrasound Image under Artificial Intelligence Algorithm in Thoracoscopic Surgery for Papillary Thyroid Carcinoma
Authors: Shen Xin , Yuan Aolin , Zhang Kaili
Published: February 2022

This study aimed to investigate the therapeutic effect of thoracoscopic thyroidectomy guided by an ultrasound image based on an artificial intelligence algorithm on papillary thyroid carcinoma. Patients diagnosed with papillary thyroid carcinoma by imaging examination or needle biopsy in hospital were selected. The subjects were randomly divided into the experimental group and the control group. In the experimental group, 94 patients underwent conventional thoracoscopic thyroid tumor resection. In the control group, 119 patients underwent thoracoscopic thyroidectomy under ultrasonic guidance based on an intelligent algorithm. The adoption effect of ultrasound imaging based on the least variance algorithm in thoracoscopic papillary thyroid carcinoma surgery was evaluated by comparing the differences between the two groups of patients after laparoscopic thyroidectomy. The results showed that the ultrasonic imaging resolution and sound-absorbing spot imaging effect based on an artificial intelligence algorithm were superior to those of conventional ultrasonic imaging. Compared with the control group, the average duration of surgery in the experimental group was reduced and the intraoperative blood loss, postoperative cumulative drainage volume, postoperative drainage tube duration, hospital stay, and pain evaluation were dramatically better (

P
<
0.05

). It was confirmed that ultrasound-guided endoscopic thyroid surgery based on the least variance algorithm had better results than conventional surgery and showed the same safety as traditional surgery, which was of clinical promotion value. However, some evaluations were influenced by subjective judgment, and the accuracy of data conclusions needed to be further studied.