bluuebunny/crossref_metadata_2025 huggingface dataset:
Vacuum births and barriers to its use: An observational study in governmental hospitals in Sierra Leone
Authors: Bakke Eirik , Øseth Eirik Hammer , Fofanah Tairu , Sesay Ibrahim , van Duinen Alex , Bolkan Håkon Angell , Westendorp Josien , Lonnee-Hoffmann Risa
Published: November 2022

Objectives

Assisted vaginal births (AVD) can prevent unnecessary caesarean sections (CS). The number of CS is increasing rapidly in sub-Saharan Africa; these are still associated with high perioperative mortality rates. The aim of this study is to define the proportion of AVD in governmental hospitals in Sierra Leone and examine barriers to its use.

Design

Retrospective observational study of AVD between September 2016 and August 2017.

Setting

A representative selection of Sierra Leonean governmental hospitals (n=11).

Participant and intervention

(a) Data were collected from labour ward records. (b) Health workers involved in labour management were questioned.

Primary and secondary outcome measures

(a) Number of spontaneous, assisted vaginal and caesarean births. (b) Potential barriers to use vacuum-assisted births.

Results

(a) Total annual numbers of registered births, AVD and CS were 16 833, 631 (3.7%) and 4642 (27.6%). The proportion of vacuum births ranged from 0.0% to 5.1% across facilities. The proportion of CS ranged from 6.5% to 33.4%. (b) The most frequently reported reasons for limited vacuum use were lack of equipment (25/72; 35%) and insufficient training (18/72; 25%).

Conclusions

The proportion of AVD was particularly low in district facilities, and according to healthcare workers this was mostly due to lack of equipment and insufficient training. Implementing relevant training programmes on the use of vacuum devices and increasing the availability of working devices may increase the proportion of vacuum births in government hospitals in Sierra Leone. This could reduce the number of unnecessary CS.
Needs and views on healthy lifestyles for the prevention of dementia and the potential role for mobile health (mHealth) interventions in China: a qualitative study
Authors: Zhang Jinxia , Eggink Esmé , Zhang Xiaoyu , Li Xingming , Jiang Bin , Liu Hongmei , Ge Siqi , Zhang Wei , Lyu Jihui , Niu Yixuan , Yu Yueyi , Hou Haifeng , Xu Xizhu , Ye Xiaoyan , Wang Wenzhi , Terlou Ruben , Richard Edo , Wang Wei , Wang Youxin , Moll van Charante Eric P , Song Manshu
Published: November 2022

Objectives

Over the coming decades, China is expected to face the largest worldwide increase in dementia incidence. Mobile health (mHealth) may improve the accessibility of dementia prevention strategies, targeting lifestyle-related risk factors. Our aim is to explore the needs and views of Chinese older adults regarding healthy lifestyles to prevent cardiovascular disease (CVD) and dementia through mHealth, supporting the Prevention of Dementia using Mobile Phone Applications (PRODEMOS) study.

Design

Qualitative semi-structured interview study, using thematic analysis.

Setting

Primary and secondary care in Beijing and Tai’an, China.

Participants

Older adults aged 55 and over without dementia with an increased dementia risk, possessing a smartphone. Participants were recruited through seven hospitals participating in the PRODEMOS study, purposively sampled on age, sex, living area and history of CVD and diabetes.

Results

We performed 26 interviews with participants aged 55–86 years. Three main themes were identified: valuing a healthy lifestyle, sociocultural expectations and need for guidance. First, following a healthy lifestyle was generally deemed important. In addition to generic healthy behaviours, participants regarded certain specific Chinese lifestyle practices as important to prevent disease. Second, the sociocultural context played a crucial role, as an important motive to avoid disease was to limit the care burden put on family members. However, time-consuming family obligations and other social values could also impede healthy behaviours such as regular physical activity. Finally, there seemed to be a need for reliable and personalised lifestyle advice and for guidance from a health professional.

Conclusions

The Chinese older adults included in this study highly value a healthy lifestyle. They express a need for personalised lifestyle support in order to adopt healthy behaviours. Potentially, the PRODEMOS mHealth intervention can meet these needs through blended lifestyle support to improve risk factors for dementia and CVD.

Trial registration number

ISRCTN15986016; Pre-results.
An investigation of cultural influences in survivors of paediatric cancer: a systematic review protocol
Authors: Hou Sharon H J , Schulte Fiona S M
Published: November 2022

Introduction

Paediatric cancer affects children and families from diverse backgrounds. However, there is a limited understanding of how diversity/cultural factors play a role, especially in survivorship. This protocol outlines a systematic review on the cultural influences in survivors of childhood cancer.

Methods and analysis

This protocol is reported based on the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) guidelines checklist and is registered with PROSPERO. EMBASE, MEDLINE and PsycINFO are searched. Eligibility criteria include original research studies published in English, and an assessment of culture on survivors of childhood cancer. Search terms are developed with a medical librarian. Primary objective will be to describe culture (ethnic and population groups, migration status, acculturation, cultural characteristics) in survivors of paediatric cancer and study characteristics and methods. Secondary objective will be to identify the role of culture in outcomes of survivors of paediatric cancer. Data extraction will include participant characteristics such as the number of participants and/or controls, sex, age at diagnosis. Extraction will also include analytical approaches, type of cultural variables (predictor, moderator, mediator, outcome) and effect measures.

Ethics and dissemination

Ethical approval was not required for this systematic review. Results from this systematic review will be disseminated in line with PRISMA guidelines through peer-reviewed publications and conference presentations. Findings will also be shared with our target communities, including survivors of childhood cancer and their families, through the creation of lay summaries and/or educational workshops in the community. Knowledge gathered from this review may help to identify gaps in knowledge and directions for future research. They may also inform the development of clinical recommendations for healthcare providers of survivors of childhood cancer.

PROSPERO registration number

CRD42021234101.
An initiative for a more inclusive working life and its effect on return-to-work after sickness absence: a multistate longitudinal cohort study
Authors: Hoff Rune , Maltzahn Niklas , Hasting Rachel Louise , Merkus Suzanne L , Undem Karina , Kristensen Petter , Mehlum Ingrid Sivesind , Gran Jon Michael
Published: November 2022

Objectives

To reduce sickness absence (SA) and increase work participation, the tripartite Agreement for a More Inclusive Working Life (IA) was established in Norway in 2001. IA companies have had access to several measures to prevent and reduce SA. Our aim in this paper was to estimate the average effect of having access to IA at the time of entering a first SA on later return-to-work (RTW) and on time spent in other work-related states. A secondary objective was to study how effects varied between women and men, and individuals with SA due to either musculoskeletal or psychological diagnoses.

Design

Population-based observational multistate longitudinal cohort study.

Setting

Individual characteristics and detailed longitudinal records of SA, work and education between 1997-2011 were obtained from population-wide registries.

Participants

Each individual born in Norway 1967–1976 who entered full-time SA during 2004–2011, with limited earlier SA, was included (n=187 930).

Primary and secondary outcome measures

Individual multistate histories containing dated periods of work, graded SA, full-time SA, non-employment and education.

Methods

Data were analysed in a multistate model with 500 days of follow-up. The effect of IA was assessed by estimating differences in state probabilities over time, adjusted for confounders, using inverse probability weighting.

Results

IA increased the probability of work after SA, with the largest difference between groups after 29 days (3.4 percentage points higher (95% CI 2.5 to 4.3)). Differences in 1-year expected length of stay were 8.4 additional days (4.9 to 11.9) in work, 7.6 (4.8 to 10.3) fewer days in full-time SA and 1.6 (-0.2 to 3.4) fewer days in non-employment. Similar trends were found within subgroups by sex, musculoskeletal and psychological diagnoses. The robustness of the findings was studied in sensitivity analyses.

Conclusion

Measures to prevent and reduce SA, as given through IA, were found to improve individuals’ RTW after entering SA.
Cohort profile: CareConekta: a pilot study of a smartphone application to improve engagement in postpartum HIV care in South Africa
Authors: Clouse Kate , Noholoza Sandisiwe , Ngcobo Nkosinathi , Madwayi Sindiswa , Mrubata Megan , Camlin Carol S , Myer Landon , Phillips Tamsin K
Published: November 2022

Purpose

Pregnant and postpartum women living with HIV in South Africa are at high risk of dropping out of care, particularly after delivery. Population mobility may contribute to disruptions in HIV care, and postpartum women are known to be especially mobile. To improve engagement in HIV care during the peripartum period, we developed CareConekta, a smartphone application (app) that uses GPS coordinates to characterise mobility and allow for real-time intervention. We conducted a randomised controlled pilot study to assess feasibility, acceptability and initial efficacy of the app intervention to improve engagement in HIV care. This cohort profile describes participant enrolment and follow-up, describes the data collected and provides participant characteristics.

Participants

We enrolled 200 pregnant women living with HIV attending routine antenatal care at the Gugulethu Midwife Obstetric Unit in Cape Town, South Africa. Eligible women must have owned smartphones that met the app’s technical requirements. Seven participants were withdrawn near enrolment, leaving 193 in the cohort.

Findings to date

Data were collected from detailed participant questionnaires at enrolment and follow-up (6 months after delivery), as well as GPS data from the app, and medical records. Follow-up is complete; initial analyses have explored smartphone ownership, preferences and patterns of use among women screened for eligibility and those enrolled in the study.

Future plans

Additional planned analyses will characterise mobility in the population using the phone GPS data and participant self-reported data. We will assess the impact of mobility on engagement in care for the mother and infant. We also will describe the acceptability and feasibility of the study, including operational lessons learnt. By linking this cohort to the National Health Laboratory Service National HIV Cohort in South Africa, we will continue to assess engagement in care and mobility outcomes for years to come. Collaborations are welcome.

Trial registration number

NCT03836625.
Factors affecting contraceptive choice in women over 40: a qualitative study
Authors: Burgin Jo , Bailey Julia V
Published: November 2022

Objective

To explore the views of women over 40 years in choosing and using contraception, and to inform how contraceptive counselling for this age group could be improved.

Design, setting and participants

Fourteen women aged 40–52 years were recruited through social media platforms to take part in online, semistructured, in-depth interviews. Transcripts were analysed using a qualitative thematic approach.

Results

(1) Participants were anxious about unplanned pregnancy, and still highly motivated to avoid this. (2) Changes of contraceptive method over the lifecourse were occasionally precipitated by emergent health conditions, but healthcare providers often recommended a change in method on the basis of age alone. (3) Participants were experiencing perimenopausal symptoms but were largely unaware of how hormonal contraception could be used to treat these symptoms. (4) Prior negative experiences with contraceptive methods, coercive experiences with healthcare providers, and traumatic life events all contributed to a narrowing of contraceptive preference in later life.

Conclusion

Women over 40 years may be highly motivated to avoid pregnancy. This age group may have complex contraceptive histories with emerging perimenopausal symptoms. Women over 40 years may have accumulated adverse experiences which impact their contraceptive choices. These factors need to be explored by clinicians, to facilitate shared decision-making.
Automated digital technologies for supporting sepsis prediction in children: a scoping review protocol
Authors: Tennant Ryan , Graham Jennifer , Mercer Kate , Ansermino J Mark , Burns Catherine M
Published: November 2022

Introduction

While there have been several literature reviews on the performance of digital sepsis prediction technologies and clinical decision-support algorithms for adults, there remains a knowledge gap in examining the development of automated technologies for sepsis prediction in children. This scoping review will critically analyse the current evidence on the design and performance of automated digital technologies to predict paediatric sepsis, to advance their development and integration within clinical settings.

Methods and analysis

This scoping review will follow Arksey and O’Malley’s framework, conducted between February and December 2022. We will further develop the protocol using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. We plan to search the following databases: Association of Computing Machinery (ACM) Digital Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, Google Scholar, Institute of Electric and Electronic Engineers (IEEE), PubMed, Scopus and Web of Science. Studies will be included on children >90 days postnatal to <21 years old, predicted to have or be at risk of developing sepsis by a digitalised model or algorithm designed for a clinical setting. Two independent reviewers will complete the abstract and full-text screening and the data extraction. Thematic analysis will be used to develop overarching concepts and present the narrative findings with quantitative results and descriptive statistics displayed in data tables.

Ethics and dissemination

Ethics approval for this scoping review study of the available literature is not required. We anticipate that the scoping review will identify the current evidence and design characteristics of digital prediction technologies for the timely and accurate prediction of paediatric sepsis and factors influencing clinical integration. We plan to disseminate the preliminary findings from this review at national and international research conferences in global and digital health, gathering critical feedback from multidisciplinary stakeholders.

Scoping review registration

https://osf.io/veqha/?view_only=f560d4892d7c459ea4cff6dcdfacb086
Prevalence of stroke and associated risk factors: a population-based cross-sectional study from the Qinghai-Tibet Plateau of China
Authors: Li ZhenHua , Hu QuanZhong , Ji WeiZhong , Fan QingLi
Published: November 2022

Background and objectives

The epidemiology of stroke at high altitudes has not been extensively studied, especially at heights of 4000 m and above. Thus, stroke prevention and treatment at high altitudes are challenging. We conducted a cross-sectional study to estimate the prevalence of stroke, the detection rate of individuals at high risk of stroke and the risk factors for stroke in the Qinghai-Tibet Plateau in China, a high altitude plateau that inhabits approximately 15 million people.

Design

A population-based cross-sectional study in the Qinghai-Tibet Plateau.

Setting

Data were collected from participants through face-to-face screening using a primary screening table. The table relied on the China National Stroke Screening and Prevention Project.

Participants

A total of 10 700 residents aged ≥40 years and living on the Qinghai-Tibet Plateau for more than 6 months participated from January 2019 to December 2021.

Main outcome measures

The primary screening table included basic demographic information, medical history information, personal lifestyle habits and physical examination information.

Results

A total of 10 056 people were included in the analysis. The prevalence of stroke was 2.3% (95% CI 2.0% to 2.6%), and the detection rate of individuals at high risk of stroke was 26.2% (95% CI 25.3% to 27.0%). The prevalence of stroke and the detection rate of individuals at high risk of stroke increased with altitude (p<0.01), and the prevalence of stroke at high altitudes was almost 2.2 times that at mid-altitudes (p<0.01). After full adjustments, age, residence, hypertension, family history of stroke and smoking were significantly associated with stroke (p<0.05).

Conclusions

The prevalence of stroke, the related risk factors and the detection rate of high-risk individuals were clarified. The prevalence rates of hypertension, overweight or obesity and diabetes in the Qinghai-Tibet Plateau were all higher than the Chinese average. Higher-altitude exposure may be an independent risk factor for stroke.
Study protocol for an integrative theory review of the concept of unidentified pain
Authors: Monroe Todd B , Anderson Alison , Failla Michelle , Carter MIchael
Published: November 2022

Introduction

Most definitions of pain require individuals experiencing pain to report their pain. There are three groups who may not always report pain including those who: (1) lack the cognitive ability to verbally communicate their pain and also lack a proxy/surrogate to report pain for them; (2) lack the cognitive ability to verbally communicate their pain but have a proxy to report the pain; and (3) have the cognitive ability to verbally report pain but are unable or unwilling to do so. Clinicians may not be able to determine which patients are at risk for unidentified pain. Therefore, in this study, we present a protocol for an integrative review with the aim of identifying existing theoretical approaches to understanding unidentified pain.

Methods and analysis

We propose a systematic overview of the existing theoretical approaches to understanding ‘unidentified pain’. We will use Campbell and colleagues’ criteria for systematic reviews of theory and the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. Our search will be broad to cover theoretical approaches to ‘unidentified pain’ using MEDLINE, CINAHL, Embase and Google Scholar. Covidence systematic review software will be used for data extraction and analysis. Then, qualitative content analysis will take place. The content analysis will be presented as a narrative.

Ethics and dissemination

No human or animal subjects will be involved. The results are to be published in peer-reviewed journals and presented at conferences in the USA and internationally.
Notes for the general paediatrician: managing thyrotoxicosis in children and young people
Authors: Vidouris Marianna , Worth Christopher , Patel Leena , Date Anjali , Jasser Anas , Hird Beverly , Tetlow Lesley , Banerjee Indraneel
Published: November 2022

Thyrotoxicosis due to hyperthyroidism is a serious disorder in childhood often presenting to general paediatricians with a range of clinical manifestations. The commonest cause is Graves’ disease, an autoimmune disorder resulting from thyrotropin receptor stimulation by autoantibodies. Early recognition and accurate interpretation of investigations are essential to achieve and maintain a euthyroid state. This will not only optimise growth, development and transition from childhood to young adult life but also avoid the potentially severe and life-threatening complications of acute thyrotoxicosis. In this review, we have focussed on the general paediatrician’s perspective of the presentation and management of thyrotoxicosis and the need to network with specialist paediatric endocrine centres to optimise patient care. We have discussed nuances of therapy, side effects and long-term outcomes, while recognising that limited remission rates in this age group often necessitate more definitive management. While carbimazole is usually used as first-line medical therapy, we have provided useful information to guide paediatricians in the discussion of individualised safe and effective treatment plans for both short-term and long-term management.
SOFAR and Auto-link: software tools that bridge the gap between multirotor drone design optimization and CAD
Authors: May Morgan J.S. , Braga Mateus A.R. , Ferguson Philip A.
Published: November 2022

Several types of tools are used to develop drones. Computer-aided design (CAD) is used for developing the drone geometry, and software such as ComQuest Venture’s Typhon UDX is used for aerodynamic analysis. Presently, both are used independently, and a user then manually bridges the gap between the analysis and the CAD to create a final aerostructure. This manual process can lead to long design times and information transfer errors. An automated design process that automatically selects parts from a database optimizes drone parts cost, while meeting key performance requirements could shorten the design time. This paper presents the Sensible Optimization for Aerial Robots tool for automatically minimizing drone systems’ cost using a commercial component database and linking it directly to CAD software. As drones become increasingly popular, this streamlining of the drone development process will reduce both the time and cost required to develop an optimal structure.
WPEviRC: A Multi-rules-based Classifier for Evidential Databases Without Class Label Ambiguities
Authors: Bahri Nassim , Tobji Mohamed Anis Bach , Yaghlane Boutheina Ben
Published: November 2022

Rule-based classifiers use a collection of high-quality rules to classify new data instances. They can be categorized according to the adopted classification strategy: Classifiers based on a single rule, and classifiers based on multiple rules. Many works were proposed in this field. However, most of them do not handle imperfect data. In this study, we focus on the issue of multi-rules-based classification for evidential data, i.e., data where imperfection is modeled via the belief functions theory. In this respect, we introduce a new algorithm called PWEviRC. This latter involves a two-level pruning technique to remove redundant and noisy rules. Finally, it applies the Dempster rule of combination to fuse the selected rules and make the final decision. To evaluate the proposed method, we carried out extensive experiments on several benchmark data sets. The performance study showed interesting results in comparison to existing methods.
An Efficient Iterative Method for Nonlinear Boundary Value Problems with Existence and Uniqueness
Authors: Chang Shih-Hsiang
Published: November 2022

A simple and efficient iterative method involving Green’s function is presented for solving the general [Formula: see text]th-order nonlinear boundary value problems. Existence and uniqueness results for such problems are established using the fixed-point theorems. This guarantees the uniform convergence of the proposed iterative algorithm. The resulting iterative solutions does not contain any unknown constants and automatically satisfy the given boundary conditions. This gives the iterative method much wider applicability in obtaining the analytical or numerical solution of the problem. The performance of the proposed approach is assessed and tested on four examples.
Red Sea rifting in central Egypt: constraints from the offshore Quseir province
Authors: Ali Moamen , Decarlis Alessandro , Ligi Marco , Ball Philip , Bosworth William , Ceriani Andrea
Published: November 2022

The formation of oceanic crust in the southern and central Red Sea is generally accepted to have started at
c.
5 Ma. However, the nature of the crust in the northern Red Sea is still debated. This paper describes the rift architecture, dynamics and evolution of the northern Red Sea and identifies domains that relate to first-order geodynamic processes. The proximal margin domain is located onshore and is characterized by latest Oligocene–Miocene half-graben basins. New seismic interpretations show that the offshore region is a necking domain dominated by low-angle, high-offset extensional faults, which led to the exhumation of lower crustal gabbros at Brothers Islands. Two-dimensional forward models suggest that the necking domain passes into a distal margin domain, where the continental crust thins to <10 km at 120 km from the coast. Sensitivity testing of interpretations for the distal domain indicates a probable scenario where exhumed lower continental crust or serpentinized mantle is present. A comprehensive rift model for the northern Red Sea in the Quseir province accounts for magmatic underplating accompanied by half-graben development at
c.
25 Ma, followed by Early Miocene crustal thinning accommodated by an east-dipping detachment fault. A Late Miocene phase with a flip of the detachment geometry led to the present day configuration.
Building a new economy
Authors: Pentland Alex
Published: November 2022

How distributed technologies could return more control to users.
Automated Generation of Security Assertions for RTL Models
Authors: Witharana Hasini , Jayasena Aruna , Whigham Andrew , Mishra Prabhat
Published: November 2022

System-on-Chip (SoC) security is vital in designing trustworthy systems. Detecting and fixing a vulnerability in the early stages is easier and cost-effective. Assertion-based verification is widely used for functional validation of Register-Transfer Level (RTL) designs. Assertions can improve the controllability and observability that can lead to faster error detection and localization. Although assertions are widely used for functional validation of RTL models, there is limited effort in applying assertions to detect SoC security vulnerabilities. Specifically, a fundamental challenge in SoC security and trust validation is how to develop high-quality security assertions. In this article, we perform automated vulnerability analysis of RTL models to generate security assertions for six classes of vulnerabilities. Experimental results show that the generated security assertions can detect a wide variety of vulnerabilities. Our automated framework can drastically reduce the overall security validation effort compared to the manual development of security assertions. Automated generation of security assertions will enable assertion-based verification to be one of the most promising pre-silicon security sign-off solutions.
Is having AI generate text cheating?
Authors: Baquero Carlos
Published: November 2022

The
Communications
website, https://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of
Communications
, we'll publish selected posts or excerpts.

twitter

Follow us on Twitter at http://twitter.com/blogCACM

https://cacm.acm.org/blogs/blog-cacm

Carlos Baquero on whether using artificial intelligence provides an unfair advantage to writers.
The four horsemen of an ailing software project
Authors: Neville-Neil George
Published: November 2022

Don't let the pale rider catch you with an exception.
No More “Solutionism” or “Saviourism” in Futuring African HCI: A Manyfesto
Authors: Adamu Muhammad Sadi
Published: November 2022

Research in HCI4D has continuously advanced a narrative of “lacks” and “gaps” of the African perspective in technoscience. In response to such misguided assumptions, this article attempts to reformulate the common and perhaps unfortunate thinking about African practices of design in HCI4D – i.e., largely as a function of African societal predicaments and Western technocratic resolutions. Through critical reflection on a range of issues associated with post-colonialism and post-development, I examine the possibilities that various historical tropes might offer to the reinvention of the African perspective on innovation. This leads to the consideration of how engaging in critical discussions about the future dimensions of African HCI can allow for grappling with the effect of the coloniality of being, power, and knowledge. Developing on the ideas of futuring as a way of dealing with the complexities of the present—in this case, the coloniality of the imagination—the article ends by discussing three tactical propositions for “remembering” future identities of African innovation where the values of autonomy are known and acted upon.
PEDM: A Multi-task Learning Model for Persona-aware Emoji-embedded Dialogue Generation
Authors: Zhao Sirui , Jiang Hongyu , Tao Hanqing , Zha Rui , Zhang Kun , Xu Tong , Chen Enhong
Published: November 2022

As a vivid and linguistic symbol, Emojis have become a prevailing medium interspersed in text-based communication (e.g., social media and chit-chat) to express emotions, attitudes, and situations. Generally speaking, a social-oriented chatbot that can generate appropriate Emoji-embedded responses would be much more competitive, making communications more fun, engaging, and human-like. However, the current Emoji-related research is still in its infancy, leading to an awkward situation of data deficiency. How to develop an Emoji-embedded dialogue system while addressing the lack of data will be interesting and meaningful for the application of future AI. To bridge this gap, we propose a multi-task learning method for persona-aware Emoji-embedded dialogue generation in this article. Specifically, as the benchmark of model training and evaluation, which includes 1.2 million Emoji-embedded tweets and 1.1 million post-response pairs, we first construct a dataset named
EmojiTweet
to handle the data deficiency problem. Then, a Seq2Seq-based model with multi-task learning is designed to simultaneously learn response generation and Emoji embedding from the constructed non-Emoji dialogue and Emoji-embedded monologue data. Afterward, we incorporate persona factors into our model by adopting persona fusion and personalized bias methods to deliver personalized dialogues with more accurately selected Emojis. Finally, we conduct extensive experiments, where the experimental results and evaluations demonstrate that our model has three key benefits: improved dialogue quality, higher user engagement, and not relying on large-scale Emoji-embedded dialogue data representing specific personas.
EmojiTweet
will be published publicly via
https://mea-lab-421.github.io/EmojiTweet/
.
A Theory of Scrum Team Effectiveness
Authors: Verwijs Christiaan , Russo Daniel
Published: November 2022

Scrum teams are at the heart of the Scrum framework. Nevertheless, an integrated and systemic theory that can explain what makes some Scrum teams more effective than others is still missing. To address this gap, we performed a 7-year-long mixed-methods investigation composed of two main phases. First, we induced a theoretical model from 13 exploratory field studies. Our model proposes that the effectiveness of Scrum teams depends on five high-level factors (responsiveness, stakeholder concern, continuous improvement, team autonomy, and management support) and 13 lower-level factors. In the second phase of our study, we validated our model with a covariance-based structural equation modeling analysis using data from about 5,000 developers and 2,000 Scrum teams that we gathered with a custom-built survey. Results suggest a very good fit of the empirical data in our theoretical model (
CFI
= 0.959,
RMSEA
= 0.038,
SRMR
= 0.035). Accordingly, this research allowed us to (1) propose and validate a generalizable theory for effective Scrum teams and (2) formulate clear recommendations for how organizations can better support Scrum teams.
An In-depth Comparative Analysis of Cloud Block Storage Workloads: Findings and Implications
Authors: Li Jinhong , Wang Qiuping , Lee Patrick P. C. , Shi Chao
Published: November 2022

Cloud block storage systems support diverse types of applications in modern cloud services. Characterizing their input/output (I/O) activities is critical for guiding better system designs and optimizations. In this article, we present an in-depth comparative analysis of production cloud block storage workloads through the block-level I/O traces of billions of I/O requests collected from two production systems, Alibaba Cloud and Tencent Cloud Block Storage. We study their characteristics of load intensities, spatial patterns, and temporal patterns. We also compare the cloud block storage workloads with the notable public block-level I/O workloads from the enterprise data centers at Microsoft Research Cambridge, and we identify the commonalities and differences of the three sources of traces. To this end, we provide 6 findings through the high-level analysis and 16 findings through the detailed analysis on load intensity, spatial patterns, and temporal patterns. We discuss the implications of our findings on load balancing, cache efficiency, and storage cluster management in cloud block storage systems.
Concerning Trends in Likert Scale Usage in Human-robot Interaction: Towards Improving Best Practices
Authors: Schrum Mariah , Ghuy Muyleng , Hedlund-botti Erin , Natarajan Manisha , Johnson Michael , Gombolay Matthew
Published: November 2022

As robots become more prevalent, the importance of the field of human-robot interaction (HRI) grows accordingly. As such, we should endeavor to employ the best statistical practices in HRI research. Likert scales are commonly used metrics in HRI to measure perceptions and attitudes. Due to misinformation or honest mistakes, many HRI researchers do not adopt best practices when analyzing Likert data. We conduct a review of psychometric literature to determine the current standard for Likert scale design and analysis. Next, we conduct a survey of five years of the International Conference on Human-Robot Interaction (HRIc) (2016 through 2020) and report on incorrect statistical practices and design of Likert scales [1,2,3,5,7]. During these years, only 4 of the 144 papers applied proper statistical testing to correctly designed Likert scales. We additionally conduct a survey of best practices across several venues and provide a comparative analysis to determine how Likert practices differ across the field of Human-robot Interaction. We find that a venue’s impact score negatively correlates with number of Likert-related errors and acceptance rate, and total number of papers accepted per venue positively correlates with the number of errors. We also find statistically significant differences between venues for the frequency of misnomer and design errors. Our analysis suggests there are areas for meaningful improvement in the design and testing of Likert scales. Based on our findings, we provide guidelines and a tutorial for researchers for developing and analyzing Likert scales and associated data. We also detail a list of recommendations to improve the accuracy of conclusions drawn from Likert data.
The Power and Perils of De Novo Domestication Using Genome Editing
Authors: Bartlett Madelaine E. , Moyers Brook T. , Man Jarrett , Subramaniam Banu , Makunga Nokwanda P.
Published: November 2022

There is intense interest in using genome editing technologies to domesticate wild plants, or accelerate the improvement of weakly domesticated crops, in de novo domestication. Here, we discuss promising genetic strategies, with a focus on plant development. Importantly, genome editing releases us from dependence on random mutagenesis or intraspecific diversity, allowing us to draw solutions more broadly from diversity. However, sparse understanding of the complex genetics of diversity limits innovation. Beyond genetics, we urge the ethical use of indigenous knowledge, indigenous plants, and ethnobotany. De novo domestication still requires conventional breeding by phenotypic selection, especially in the development of crops for diverse environments and cultures. Indeed, uniting genome editing with selective breeding could facilitate faster and better outcomes than either technology alone. Domestication is complex and incompletely understood, involving changes to many aspects of plant biology and human culture. Success in de novo domestication requires careful attention to history and collaboration across traditional boundaries.
Statistical Methods for Exoplanet Detection with Radial Velocities
Authors: Hara Nathan C. , Ford Eric B.
Published: November 2022

Exoplanets can be detected with various observational techniques. Among them, radial velocity (RV) has the key advantages of revealing the architecture of planetary systems and measuring planetary mass and orbital eccentricities. RV observations are poised to play a key role in the detection and characterization of Earth twins. However, the detection of such small planets is not yet possible due to very complex, temporally correlated instrumental and astrophysical stochastic signals. Furthermore, exploring the large parameter space of RV models exhaustively and efficiently presents difficulties. In this review, we frame RV data analysis as a problem of detection and parameter estimation in unevenly sampled, multivariate time series. The objective of this review is two-fold: to introduce the motivation, methodological challenges, and numerical challenges of RV data analysis to nonspecialists, and to unify the existing advanced approaches in order to identify areas for improvement.
Teaching Reform of Ancient Literature Based on Credible BP Neural Network Technology in New Media Environment
Authors: Dai Huiting
Published: November 2022

Recent years have seen a progressive integration of the new media environment into people’s lives, studies, and employment, which has had a profound impact on China’s social economy. It is unavoidable to conduct the educational reform of classical literature in the age of new media. Data mining (DM) is a method for analysing and learning from data in databases and data warehouses using artificial intelligence. They work better together to create a solid foundation for decision-making analysis of businesses or pertinent departments in many fields. The BP algorithm can cause the weight to converge to a specific number, but it cannot ensure that that value is the error plane’s overall minimum. In order to correct the flaw that the BP neural network is prone to falling into local minima, the improved credible BP neural network used in this paper adopts the momentum factor. The findings demonstrate that there is little variation between the predicted value and the actual value achieved by applying the BP algorithm in the experimental group with order of magnitude standardised operation, and that this algorithm’s error has been decreased by 7.38%. It demonstrates that by examining students’ test scores in a data warehouse with a neural network algorithm in DM, we may discover potential patterns among the data.
Experimental Study on the Dynamic Mechanical Properties of a Jointed Rock Mass under Impact Loading
Authors: Wang Feng , Wang Mengxiang , Wang Haibo , Wang Hao , Zong Qi
Published: November 2022

The propagation law of blast stress waves in jointed rock masses is closely related to the characteristics of the joint filling medium. The water content and thickness of the filling medium affect the propagation characteristics of the blast stress wave in the joint surface. Based on similarity theory, mortar-red clay-mortar composite specimens with different moisture contents (36%, 39%, 42%, and 45%) and medium thicknesses (3 mm, 6 mm, and 9 mm) were prepared with red clay as the filling medium. The dynamic uniaxial compression test of the specimen under different strain rates was carried out by using a variable cross-section split Hopkinson compression bar with a diameter of 50 mm. The effects of strain rate, moisture content, and medium thickness on the stress wave propagation characteristics, dynamic stress-strain curve, peak stress, crushing energy consumption density, and crushing characteristics of mortar-red clay-mortar composite specimens were analyzed. The results show that the blocking effect of joints on stress waves increases significantly with increasing filling medium thickness and water content. With increasing strain rate, the peak stress and energy of the composite specimen increase and there is an obvious strain rate effect. With the increase in the thickness and moisture content of the filling medium, the peak stress, dynamic elastic modulus, energy consumption density per unit volume, and crushing degree of the specimen gradually decrease and the nonlinear deformation is more obvious. There is a good linear relationship between the peak stress and the thickness and moisture content of the filling medium. The existence of joints greatly weakens the damage effect of stress waves on the specimens behind the joints, and with the increase in the thickness and water content of the filling medium, the degree of damage to the specimens behind the joint surface decreases under the same impact pressure and the weakening effect becomes increasingly significant.
Sparsity-Preserving Two-Sided Iterative Algorithm for Riccati-Based Boundary Feedback Stabilization of the Incompressible Navier–Stokes Flow
Authors: Islam Md. Toriqul , Uddin Mahtab , Uddin M. Monir , Khan Md. Abdul Hakim , Hossain Md. Tanzim
Published: November 2022

In this paper, we explore the Riccati-based boundary feedback stabilization of the incompressible Navier–Stokes flow via the Krylov subspace techniques. Since the volume of data derived from the original models is gigantic, the feedback stabilization process through the Riccati equation is always infeasible. We apply aℋ2optimal model-order reduction scheme for reduced-order modeling, preserving the sparsity of the system. An extended form of the Krylov subspace-based two-sided iterative algorithm (TSIA) is implemented, where the computation of an equivalent Sylvester equation is included for minimizing the computation time and enhancing the stability of the reduced-order models with satisfying the Wilson conditions. Inverse projection approaches are applied to get the optimal feedback matrix from the reduced-order models. To validate the efficiency of the proposed techniques, transient behaviors of the target systems are observed incorporating the tabular and figurative comparisons with MATLAB simulations. Finally, to reveal the advancement of the proposed techniques, we compare our work with some existing works.
Screen Media Exposure in Early Childhood and Its Relation to Children’s Self-Regulation
Authors: Uzundağ Berna A. , Altundal Merve Nur , Keşşafoğlu Dilara
Published: November 2022

Self-regulation, the ability to control thoughts, emotions, and behavior for goal-directed activities, shows rapid development in infancy, toddlerhood, and preschool periods. Early self-regulatory skills predict later academic achievement and socioemotional adjustment. An increasing number of studies suggest that screen media use may have negative effects on children’s developing self-regulatory skills. In this systematic review, we summarized and integrated the findings of the studies investigating the relationship between young children’s screen media use and their self-regulation. We searched the ERIC, PsycINFO, PubMed, and Web of Science databases and identified 39 relevant articles with 45 studies. We found that screen time in infancy is negatively associated with self-regulation, but findings were more inconsistent for later ages suggesting that screen time does not adequately capture the extent of children’s screen media use. The findings further indicated that background TV is negatively related to children’s self-regulation, and watching fantastical content seems to have immediate negative effects on children’s self-regulatory skills. We suggest that future studies should take the content and context of children’s screen media use into account and also focus on parent- and home-related factors such as parental behaviors that foster the development of self-regulatory skills.
Performance Prediction of Building Integrated Photovoltaic System Using Hybrid Deep Learning Algorithm
Authors: Ragupathi Manivannan , Ramasubbu Rengaraj
Published: November 2022

In a grid-connected photovoltaic system, forecasting is a necessary and critical step. Solar Power is very nonlinear; this article develops and analyses building integrated photovoltaic (BIPV) forecasting algorithms for different timeframes, such as an hour, a day, and a week ahead, to manage grid operation effectively. However, a model built for a certain time scale may improve performance at that time scale but cannot be utilized to make predictions at other time scales. Here, we demonstrate how to use the multitask learning algorithm to create a multitime scale model for solar BIPV forecasting. Effective resource distribution across several tasks is shown. The suggested multitask learning approach is implemented using LSTM neural networks and evaluated over a range of horizons. We employed a modified version of the Chicken Swarm Optimizer (CSO) that takes the best features of the CSO and the GWO algorithms and merges them into one efficient approach to estimate the hyperparameters of the proposed LSTM model. The proposed approach consistently outperformed state-of-the-art single-timescale forecasting algorithms across all time scales.
Improved Double‐Layer Structure Multilabel Classification Model via Optimal Sequence and Attention Mechanism
Authors: Liu Geqiao , Tan Mingjie
Published: November 2022

Multilabel classification is a key research topic in the machine learning field. In this study, the author put forward a two/two‐layer chain classification algorithm with optimal sequence based on the attention mechanism. This algorithm is a classification model with a two‐layer structure. By introducing an attention mechanism, this study analyzes the key attributes to achieve the goal of classification. To solve the problem of algorithm accuracy degradation caused by the order of classifiers, we adopt the OSS (optimal sequence selection) algorithm to find the optimal sequence of tags. The test results based on the actual dataset show that the ATDCC‐OS algorithm has good performance on all performance evaluation metrics. The average accuracy of this algorithm is over 80%. The microaverage AUC performance reaches 0.96. In terms of coverage performance, its coverage performance is below 10%. The comprehensive result of single error performance is the best. The loss performance is about 0.03. The purpose of the ATDCC‐OS algorithm proposed in the study is to help improve the accuracy of multilabel classification so as to obtain more effective data information.
Dual Input Single Phase Quasi Z Source Inverter for Integrated Photovoltaic Systems
Authors: Rampradesh T. , Christober Asir Rajan C. , Fante Kinde Anlay
Published: November 2022

Globally, climate change has increased various environmental concerns, and there is a very high and still ever greater penetration of renewable energy power into energy grids. The intermittent nature of these energy sources has demanded a strong power electronic interface to maintain an uninterrupted power flow to the external load. This paper deals with a novel dual input quasi Z source inverter (qZSI) that can operate with two intermittent sources and perform a single stage power conversion. The novelty of the proposed methodology is the implementation of qZSI with a reduced number of switches, increased voltage gain, and a high boosting factor which results in increased efficiency. A simple boost control-based pulse width modulation (PWM) technique has been adopted, which has been observed after analysis, to have reduced the stress on the switches and simultaneously increased system efficiency. Perturb and observe method-based maximum power point tracking (MPPT) was integrated into the study with the control technique, and its performance was observed using MATLAB/Simulink and further validated with a scale down model.