bluuebunny/crossref_metadata_2025 huggingface dataset:
A novel, multidomain, primary care nurse-led and mHealth-assisted intervention for dementia risk reduction in middle-aged adults (HAPPI MIND): study protocol for a cluster randomised controlled trial
Authors: Cross Amanda J , Geethadevi Gopisankar Mohanannair , Magin Parker , Baker Amanda L , Bonevski Billie , Godbee Kali , Ward Stephanie A , Mahal Ajay , Versace Vincent , Bell J Simon , Mc Namara Kevin , O'Reilly Sharleen L , Thomas Dennis , Manias Elizabeth , Anstey Kaarin J , Varnfield Marlien , Jayasena Rajiv , Elliott Rohan A , Lee Cik Y , Walker Christine , van den Bosch Denise , Tullipan Mary , Ferreira Catherine , George Johnson
Published: December 2023

Introduction

Middle-aged multidomain risk reduction interventions targeting modifiable risk factors for dementia may delay or prevent a third of dementia cases in later life. We describe the protocol of a cluster randomised controlled trial (cRCT), HAPPI MIND (Holistic Approach in Primary care for PreventIng Memory Impairment aNd Dementia). HAPPI MIND will evaluate the efficacy of a multidomain, nurse-led, mHealth supported intervention for assessing dementia risk and reducing associated risk factors in middle-aged adults in the Australian primary care setting.

Methods and analysis

General practice clinics (n≥26) across Victoria and New South Wales, Australia, will be recruited and randomised. Practice nurses will be trained to implement the HAPPI MIND intervention or a brief intervention. Patients of participating practices aged 45–65 years with ≥2 potential dementia risk factors will be identified and recruited (approximately 15 patients/clinic). Brief intervention participants receive a personalised report outlining their risk factors for dementia based on Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI) scores, education booklet and referral to their general practitioner as appropriate. HAPPI MIND participants receive the brief intervention as well as six individualised dementia risk reduction sessions with a nurse trained in motivational interviewing and principles of behaviour change, a personalised risk reduction action plan and access to the purpose-built HAPPI MIND smartphone app for risk factor self-management. Follow-up data collection will occur at 12, 24 and 36 months. Primary outcome is ANU-ADRI score change at 12 months from baseline. Secondary outcomes include change in cognition, quality of life and individual risk factors of dementia.

Ethics and dissemination

Project approved by Monash University Human Research Ethics Committee (ID: 28273). Results will be disseminated in peer-reviewed journals and at healthcare conferences. If effective in reducing dementia risk, the HAPPI MIND intervention could be integrated into primary care, scaled up nationally and sustained over time.

Trial registration number

ACTRN12621001168842.
Understanding the uptake of virtual care for first and return outpatient appointments in child and adolescent mental health services: a mixed-methods study
Authors: Campbell Leslie Anne , Clark Sharon E , Chorney Jill , Emberly Debbie , Carrey NJ , Bagnell Alexa , Blenus Jaime , Daneff Miriam , Campbell John Charles
Published: December 2023

Objective

To describe patterns of virtual and in-person outpatient mental health service use and factors that may influence the choice of modality in a child and adolescent service.

Design

A pragmatic mixed-methods approach using routinely collected administrative data between 1 April 2020 and 31 March 2022 and semi-structured interviews with clients, caregivers, clinicians and staff. Interview data were coded according to the Consolidated Framework for Implementation Research (CFIR) and examined for patterns of similarity or divergence across data sources, respondents or other relevant characteristics.

Setting

Child and adolescent outpatient mental health service, Nova Scotia, Canada.

Participants

IWK Health clinicians and staff who had participated in virtual mental healthcare following its implementation in March 2020 and clients (aged 12–18 years) and caregivers of clients (aged 3–18 years) who had received treatment from an IWK outpatient clinic between 1 April 2020 and 31 March 2022 (n=1300). Participants (n=48) in semi-structured interviews included nine clients aged 13–18 years (mean 15.7 years), 10 caregivers of clients aged 5–17 years (mean 12.7 years), eight Community Mental Health and Addictions booking and registration or administrative staff and 21 clinicians.

Results

During peak pandemic activity, upwards of 90% of visits (first or return) were conducted virtually. Between waves, return appointments were more likely to be virtual than first appointments. Interview participants (n=48) reported facilitators and barriers to virtual care within the CFIR domains of ‘outer setting’ (eg, external policies, client needs and resources), ‘inner setting’ (eg, communications within the service), ‘individual characteristics’ (eg, personal attributes, knowledge and beliefs about virtual care) and ‘intervention characteristics’ (eg, relative advantage of virtual or in-person care).

Conclusions

Shared decision-making regarding treatment modality (virtual vs in-person) requires consideration of client, caregiver, clinician, appointment, health system and public health factors across episodes of care to ensure accessible, safe and high-quality mental healthcare.
Associations of academic environment, lifestyle, sense of coherence and social support with self-reported mental health status among dental students at a university in Brazil: a cross-sectional study
Authors: Silva Andréa Neiva da , Vettore Mario Vianna
Published: December 2023

Objectives

The study evaluated the association of academic environment, lifestyle, sense of coherence (SOC) and social support with self-reported mental health status among dental students.

Design

Secondary analysis of data from a cross-sectional, questionnaire-based survey conducted from August to October 2018.

Setting

Dental school of a public-funded university in the south-eastern region of Brazil.

Participants

233 undergraduate dental students recruited across all years of the course.

Outcome measures

Socioeconomic and demographic characteristics, city of origin and student’s academic semester were obtained through self-completed questionnaires. Perception of the academic environment (Dundee Ready Education Environment Measure (DREEM)), individual lifestyle (Individual Lifestyle Profile Questionnaire (ILPQ)), SOC (SOC Scale (SOC-13)), social support (Medical Outcomes Study Scale (MOS)), and depression, anxiety and stress (Depression, Anxiety and Stress Scale-21 (DASS-21)) were assessed using validated instruments. The relationships between variables were investigated through multivariable negative binomial regression to obtain the rate ratios (RRs) and 95% CIs.

Results

Female sex was associated with greater scores of anxiety (RR 1.74, 95% CI 1.10 to 1.97) and stress (RR 1.52, 95% CI 1.12 to 2.06). Students who perceived a better academic environment and those reporting a greater SOC had a lower probability of depression, anxiety and stress. Furthermore, a favourable lifestyle was associated with lower depression scores (RR 0.99, 95% CI 0.97 to 0.99). Social support did not remain associated with depression, anxiety and stress after adjustment.

Conclusions

The present findings suggest that self-reported mental health status is associated with students’ sex, academic environment, SOC and lifestyle. Enhancing the educational environment and SOC, and promoting a healthy lifestyle may improve the psychological health of dental students.
Diet in relation to Metabolic, sleep and psychological health Status (DiMetS): protocol for a cross-sectional study
Authors: Poursalehi Donya , Shahdadian Farnaz , Hajhashemy Zahra , Lotfi Keyhan , Moradmand Zahra , Rouhani Parisa , Mohammadi Sobhan , Mokhtari Elahe , Saneei Parvane
Published: December 2023

Introduction

Metabolic disturbances are of major health concerns in the world. In addition to their high prevalence, these disorders have substantial roles in developing other physical and mental diseases. Diet could have a considerable influence on managing the progression of these conditions and their consequent health-related effects. The aim of the ‘Diet in relation to Metabolic, sleep and psychological health Status’ Project is to explore the association of nutrition with metabolic, sleep and mental health, considering potential mediators including brain-derived neurotrophic factor (BDNF) and adropin.

Methods and analysis

This cross-sectional study will be conducted on adults (20–65 years) working in schools of Isfahan, Iran. A multistage cluster random sampling method will be used to select participants. Anthropometric, body composition and biochemical values including fasting blood glucose, lipid profile, 25-hydroxy vitamin D, insulin, BDNF, adropin, malondialdehyde, superoxide dismutase, glutathione peroxidase, uric acid, creatinine and C reactive protein will be measured for each participant. National Cholesterol Education Program and Adult Treatment Panel III will be considered to define metabolic syndrome. Diet will be assessed through a validated Food Frequency Questionnaire. Furthermore, sleep status, mental health, quality of life, physical activity and demographic status of individuals will be assessed by validated questionnaires. The collected data will be analysed using appropriate statistical methods.

Ethics and dissemination

The study protocol was approved by the local Ethics Committee of Isfahan University of Medical Sciences. All participants will provide written informed consent. Dissemination will be through conference presentations and publications in peer-reviewed journals.
Cohort study to characterise surgical site infections after open surgery in the UK’s National Health Service
Authors: Guest Julian F , Fuller Graham W , Griffiths Ben
Published: December 2023

Objective

To characterise surgical site infections (SSIs) after open surgery in the UK’s National Health Service.

Design

Retrospective cohort analysis of electronic records of patients from Clinical Practice Research Datalink, linked with Hospital Episode Statistics’ secondary care datasets.

Setting

Clinical practice in the community and secondary care.

Participants

Cohort of 50 000 adult patients who underwent open surgery between 2017 and 2022.

Outcome measures

Incidence of SSI, clinical outcomes, patterns of care and costs of wound management.

Results

11% (5281/50 000) of patients developed an SSI a mean of 18.4±14.7 days after their surgical procedure, of which 15% (806/5281) were inpatients and 85% (4475/5281) were in the community after hospital discharge. The incidence of SSI varied according to anatomical site of surgery. The incidence also varied according to a patient’s risk and whether they underwent an emergency procedure. SSI onset reduced the 6 months healing rate by a mean of 3 percentage points and increased time to wound healing by a mean of 15 days per wound. SSIs were predominantly managed in the community by practice and district nurses and 16% (850/5281) of all patients were readmitted into hospital. The total health service cost of surgical wound management following SSI onset was a mean of £3537 per wound ranging from £2542 for a low-risk patient who underwent an elective procedure to £4855 for a high-risk patient who underwent an emergency procedure.

Conclusions

This study provides important insights into several aspects of SSI management in clinical practice in the UK that have been difficult to ascertain from surveillance data. Surgeons are unlikely to be fully aware of the true incidence of SSI and how they are managed once patients are discharged from hospital. Current SSI surveillance services appear to be under-reporting the actual incidence.
Shared decision-making improving efficacy in diarrhoea-dominant irritable bowel syndrome in Chinese outpatient setting: protocol of a prospective, randomised controlled trial
Authors: Song Kai , Fan Zhengyang , Chen Yang , Fei Guijun , Li Xiaoqing , Wu Dong
Published: December 2023

Introduction

Diarrhoea-dominant irritable bowel syndrome (IBS-D) is a disorder with multiple pathogenesis; many people with IBS-D may have psychosocial issues which can make assessment and treatment more difficult. Routine treatment procedure might not always achieve the desired outcome. Therefore, patients may not be satisfied with the conventional experience and would like to be more involved in clinical decision-making. A shared decision-making (SDM) model, that requires patient participation, has been demonstrated to have a powerful effect on the diagnosis and treatment of other diseases, which improves patients’ compliance, satisfaction, thus refining the clinical outcome. However, there is no corresponding evidence in IBS-D. Herein, we hope to verify the effect of SDM through clinical studies, and we anticipate that SDM can improve the therapeutic effect in patients with IBS-D.

Methods

The study is a prospective, randomised, single-centre trial. 166 IBS-D outpatients who attend Peking Union Medical College Hospital will be allocated into routine treatment group and SDM group. The primary endpoint is the severity of bowel symptoms, measured by the IBS symptom severity scale. Secondary endpoints include impact of disease and quality of life, negative psychology and the evaluation of diagnosis and treatment process.

Ethics and dissemination

Ethical approval has been obtained from the research ethics committee of Peking Union Medical College Hospital (I-23PJ470). This protocol has been approved by Chinese Clinical Trial Register (ChiCTR2300073681) in July 2023. The results of this trial will be published in an open-access way and disseminated among gastrointestinal physicians.

Trial registration number

Chinese Clinical Trial Register (ChiCTR2300073681).
Defining ‘therapeutic value’ of medicines: a scoping review
Authors: Glaus Camille E G , Kloeti Andrina , Vokinger Kerstin N
Published: December 2023

Objectives

In recent years, discussions on the importance and scope of therapeutic value of new medicines have intensified, stimulated by the increase of prices and number of medicines entering the market. This study aims to perform a scoping review identifying factors contributing to the definition of the therapeutic value of medicines.

Design

Scoping review.

Data sources

We searched the MEDLINE, CINAHL, Embase, Business Source Premier, EconLit, Regional Business News, Cochrane, Web of Science, Scope and Pool databases through December 2020 in English, German, French, Italian and Spanish.

Eligibility criteria

Studies that included determinants for the definition of therapeutic value of medicines were included.

Data extraction and synthesis

Data were extracted using the mentioned data sources. Two reviewers independently screened and analysed the articles. Data were analysed from April 2021 to May 2022.

Results

Of the 1883 studies screened, 51 were selected and the identified factors contributing to the definition of therapeutic value of medicines were classified in three categories: patient perspective, public health perspective and socioeconomic perspective. More than three-quarters of the included studies were published after 2014, with the majority of the studies focusing on either cancer disorders (14 of 51, 27.5%) or rare diseases (11 of 51, 21.6%). Frequently mentioned determinants for value were quality of life, therapeutic alternatives and side effects (all patient perspective), prevalence/incidence and clinical endpoints (all public health perspective), and costs (socioeconomic perspective).

Conclusions

Multiple determinants have been developed to define the therapeutic value of medicines, most of them focusing on cancer disorders and rare diseases. Considering the relevance of value of medicines to guide patients and physicians in decision-making as well as policymakers in resource allocation decisions, a development of evidence-based factors for the definition of therapeutic value of medicines is needed across all therapeutic areas.
Incorporating usability evaluation into iterative development of an online platform to support research participation in Parkinson’s disease: a mixed methods protocol
Authors: Chapman Rebecca , Zeissler Marie-Louise , Meinert Edward , Mullin Stephen , Whipps Sue , Whipps John , Hockey Kate , Hockey Philip , Carroll Camille B
Published: December 2023

Introduction

Many people with Parkinson’s (PwP) are not given the opportunity or do not have adequate access to participate in clinical research. To address this, we have codeveloped with users an online platform that connects PwP to clinical studies in their local area. It enables site staff to communicate with potential participants and aims to increase the participation of the Parkinson’s community in research. This protocol outlines the mixed methods study protocol for the usability testing of the platform.

Methods and analysis

We will seek user input to finalise the platform’s design, which will then be deployed in a limited launch for beta testing. The beta version will be used as a recruitment tool for up to three studies with multiple UK sites. Usability data will be collected from the three intended user groups: PwP, care partners acting on their behalf and site study coordinators. Usability questionnaires and website analytics will be used to capture user experience quantitatively, and a purposive sample of users will be invited to provide further feedback via semistructured interviews. Quantitative data will be analysed using descriptive statistics, and a thematic analysis undertaken for interview data. Data from this study will inform future platform iterations.

Ethics and dissemination

Ethical approval was obtained from the University of Plymouth (3291; 3 May 2022). We will share our findings via a ‘Latest News’ section within the platform, presentations, conference meetings and national PwP networks.
Acceptability of aspirin for cancer preventive therapy: a survey and qualitative study exploring the views of the UK general population
Authors: Lloyd Kelly E , Hall Louise H , Ziegler Lucy , Foy Robbie , Green Sophie M C , MacKenzie Mairead , Taylor David G , Smith Samuel G
Published: December 2023

Objectives

Aspirin could be offered for colorectal cancer prevention for the UK general population. To ensure the views of the general population are considered in future guidance, we explored public perceptions of aspirin for preventive therapy.

Design

We conducted an online survey to investigate aspirin use, and awareness of aspirin for cancer prevention among the UK general population. We conducted semistructured interviews with a subsample of survey respondents to explore participants’ acceptability towards aspirin for cancer preventive therapy. We analysed the interview data using reflexive thematic analysis and mapped the themes onto the Theoretical Domains Framework, and the Necessity and Concerns Framework.

Setting

Online survey and remote interviews.

Participants

We recruited 400 UK respondents aged 50–70 years through a market research company to the survey. We purposefully sampled, recruited and interviewed 20 survey respondents.

Results

In the survey, 19.0% (76/400) of respondents were aware that aspirin can be used to prevent cancer. Among those who had previously taken aspirin, 1.9% (4/216) had taken it for cancer prevention. The interviews generated three themes: (1) perceived necessity of aspirin; (2) concerns about side effects; and (3) preferred information sources. Participants with a personal or family history of cancer were more likely to perceive aspirin as necessary for cancer prevention. Concerns about taking aspirin at higher doses and its side effects, such as gastrointestinal bleeding, were common. Many described wanting guidance and advice on aspirin to be communicated from sources perceived as trustworthy, such as healthcare professionals.

Conclusions

Among the general population, those with a personal or family history of cancer may be more receptive towards taking aspirin for preventive therapy. Future policies and campaigns recommending aspirin may be of particular interest to these groups. Multiple considerations about the benefits and risks of aspirin highlight the need to support informed decisions on the medication.
Accuracy of antibiotic concentrations in drug dispensing in neonates: a laboratory-based study
Authors: Zheng Li-Yuan , Gu Wei-Ping , Liang Na , Gao Li-Li , Guo Wen-Wen , Li Rui-Rui , Wang Xin , Hao Guo-Xiang , Van Den Anker John , Wu Yue-E , Zhao Wei
Published: December 2023

Background

Antibacterial therapy plays a crucial role in neonatal infections. The efficacy of antibacterial agents is closely related to the actual dose given to neonates. So we evaluated factors potentially affecting the actual dose of intravenous antibiotics during dispensing process in neonates.

Methods

Meropenem, cefoperazone/sulbactam and piperacillin/tazobactam with two strengths were used to evaluate three methods. Method A (MA) was diluted once and the volumes of 5% glucose for MAwere meropenem 4.00 mL, cefoperazone/sulbactam 3.00 mL, piperacillin/tazobactam 9.00 mL. Method B (MB) differed by doubling the volume of 5% glucose. The difference in method C (MC) involved diluting with 5% glucose twice. The concentrations were measured by high-performance liquid chromatography. Relative error (RE) was used to evaluate the preparation accuracy.

Results

The RE values using MA/MB/MCwere: (1) meropenem 0.5 g: 15.1%, 8.0%, 10.4%; 0.25 g: 7.8%, 3.1%, 6.0%; (2) cefoperazone/sulbactam 1.5 g: 13.6%, 4.2%, 3.4%; 0.75 g: 8.8%, 3.5%, 4.0%; (3) piperacillin/tazobactam 4.5 g: 18.2%, 8.7%, 6.3%; 562.5 mg: 8.1%, 2.8%, 6.1%. MBwas better than MAin all three drugs. No difference in RE values was found between single and double dilution, except meropenem with 0.25 g. Using MB, meropenem and piperacillin/tazobactam with small drug strength had higher accuracy in preparation.

Conclusions

MBwas suitable for neonatal drug dispensing because of its high accuracy and simple operation. Drugs with small strength were promoted due to the high accuracy.
Overview of road traffic injuries among migrant workers in Guangzhou, China, from 2017 to 2021
Authors: Yang Tengfei , Kong Jiangwei , Chen Xinzhe , Zeng Haotian , Zhou Nian , Yang Xingan , Miao Qifeng , Liao Xinbiao , Zhang Fu , Lan Fengchong , Wang Huijun , Li Dongri
Published: December 2023

Introduction

There are many migrant workers in China’s first-tier cities, but little is known about road safety. This paper systematically analysed road traffic injuries and risk factors among migrant workers in Guangzhou, China.

Methods

Road traffic crash data from 2017 to 2021 were obtained from the Guangzhou Public Security Traffic Management Integrated System. We plotted the crash network of road users in road traffic crashes and used logistic regression to analyse the risk factors for migrant workers of motorcycle and four-wheeled vehicle crashes. Moreover, the roles of migrant workers and control individuals as perpetrators in road traffic crashes were also analysed.

Results

Between 2017 and 2021, 76% of road traffic injuries were migrant workers in Guangzhou. Migrant workers who were motorcyclist drivers most commonly experienced road traffic injuries. Crashes between motorcyclists and car occupants were the most common. The illegal behaviours of migrant worker motorcyclists were closely related to casualties, with driving without a licence only and driving without a licence and drunk driving accounting for the greatest number. Migrant workers were responsible for many injuries of other road users. Motorcycle drivers have a higher proportion of drunk driving.

Discussion

Migrant workers play an important role in road traffic safety. They were both the leading source of road traffic injuries and the main perpetrators of road traffic crashes. Measures such as strict requirements for migrant workers to drive motorcycles with licences, prohibit drunk driving, greater publicity of road safety regulations, and combining compulsory education with punishment for illegal behaviours.
Disease activity and neonatal outcomes after exposure to natalizumab throughout pregnancy
Authors: Thiel Sandra , Litvin Nastassja , Haben Sabrina , Gold Ralf , Hellwig Kerstin
Published: December 2023

Background

After natalizumab discontinuation severe relapses can occur despite pregnancy, but third trimester exposure is associated with neonatal haematological abnormalities (HA). The best time point for stopping natalizumab during pregnancy is unclear.

Methods

Prospective, observational cohort with 350 natalizumab exposed pregnancies from the German Multiple Sclerosis and Pregnancy Registry. Clinical disease activity and neonatal outcomes are compared between women with natalizumab discontinuation during (1st Trim-group) versus after the first trimester (maintaining-group) and for subgroup analysis before (<30-subgroup) or after (≥30-subgroup) the 30th gestational week (gw).

Results

Baseline characteristics did not significantly differ between the 1st Trim-group (n=179; median exposure duration: 2.60 gw, IQR 1.30–3.60) and the maintaining-group (n=171; median exposure duration: 30.9 gw, IQR 26.9–33.3). Fewer relapses occurred during pregnancy and the postpartum year in the maintaining-group (25.7%) compared with the 1st Trim-group (62.6%; p<0.001). Women in ≥30-subgroup had a significantly lower relapse risk in the first 6 months postpartum (relapse rate ratio: 0.36, 95% CI: 0.15 to 0.84). In total, 7.5% retained meaningful disability 12 months postpartum. No significant effect on neonatal outcomes were observed, but anaemia (OR: 2.62, 95% CI: 1.12 to 6.52) and thrombocytopaenia (OR: 2.64, 95% CI: 1.15 to 6.46) were significantly more common in the ≥30-subgroup. 21.8% of all neonates were born small for gestational age, independent of the timing of natalizumab discontinuation.

Conclusion

Continuing natalizumab during pregnancy after gw 30 decreases the relapse risk postpartum going along with a higher risk for HA in the newborns. These results add relevant knowledge as a basis for informed risk–benefit discussion.
Perioperative pain management for cleft palate surgery: a systematic review and procedure-specific postoperative pain management (PROSPECT) recommendations
Authors: Suleiman Nergis Nina , Luedi Markus M , Joshi Girish , Dewinter Geertrui , Wu Christopher L , Sauter Axel R
Published: December 2023

Background/importance

Cleft palate surgery is associated with significant postoperative pain. Effective pain control can decrease stress and agitation in children undergoing cleft palate surgery and improve surgical outcomes. However, limited evidence often results in inadequate pain control after cleft palate surgery.

Objectives

The aim of this review was to evaluate the available evidence and to develop recommendations for optimal pain management after cleft palate surgery using procedure-specific postoperative pain management (PROSPECT) methodology.

Evidence review

MEDLINE, Embase, and Cochrane Databases were searched for randomized controlled trials and systematic reviews assessing pain in children undergoing cleft palate repair published in English language from July 2002, through August 2023.

Findings

Of 1048 identified studies, 19 randomized controlled trials and 4 systematic reviews met the inclusion criteria. Interventions that improved postoperative pain, and are recommended, include suprazygomatic maxillary nerve block or palatal nerve block (if maxillary nerve block cannot be performed). Addition of dexmedetomidine to local anesthetic for suprazygomatic maxillary nerve block or, alternatively, as intravenous administration perioperatively is recommended. These interventions should be combined with a basic analgesic regimen including acetaminophen and nonsteroidal anti-inflammatory drugs. Of note, pre-incisional local anesthetic infiltration and dexamethasone were administered as a routine in several studies, however, because of limited procedure-specific evidence their contribution to pain relief after cleft palate surgery remains unknown.

Conclusion

The present review identified an evidence-based analgesic regimen for cleft palate surgery in pediatric patients.

PROSPERO registration number

CRD42022364788.
Evolution of techniques and tools for replication fork proteome and protein interaction studies
Authors: Jurkovic Carla-Marie , Boisvert François-Michel
Published: December 2023

Understanding the complex network of protein–protein interactions (PPI) that govern cellular functions is essential for unraveling the molecular basis of biological processes and diseases. Mass spectrometry (MS) has emerged as a powerful tool for studying protein dynamics, enabling comprehensive analysis of protein function, structure, post-translational modifications, interactions, and localization. This article provides an overview of MS techniques and their applications in proteomics studies, with a focus on the replication fork proteome. The replication fork is a multi-protein assembly involved in DNA replication, and its proper functioning is crucial for maintaining genomic integrity. By combining quantitative MS labeling techniques with various data acquisition methods, researchers have made significant strides in elucidating the complex processes and molecular mechanisms at the replication fork. Overall, MS has revolutionized our understanding of protein dynamics, offering valuable insights into cellular processes and potential targets for therapeutic interventions.
Exploring the low-temperature performance of MPP-modified asphalt binders and mixtures using wet method
Authors: Qabur Ali , Baaj Hassan , El-Hakim Mohab
Published: December 2023

Thermal cracking significantly impacts the structural integrity of flexible pavements, particularly in colder regions like Canada. Limited studies investigated the impact of plastic modification of asphalt binders and mixtures using the wet method on the low-temperature performance of asphalt materials. The plastic material utilized in this project is multilayer plastic packaging (MPP). This study aims to determine whether MPP can be integrated to enhance the performance of the MPP-modified binder and MPP-modified mixtures, especially considering that MPP accounts for just over 40% of total plastic usage, making it the largest end-use market segment. This research evaluates the impact on rheological and mechanical behaviour when introducing MPP additives to conventional hot mix asphalt. This study used the wet method to test MPP-modified asphalt materials at 2%, 4%, and 8% (by weight of the asphalt binder). Test results demonstrate that the MPP modification percentage should ideally not exceed 2% as blends with 4% MPP or higher exhibited lower performance at low temperatures. The use of a softer binder as a base binder would help increase the MPP modification rates, but this hypothesis needs to be validated experimentally.
Lorentz force detuning in heterodyne gravitational wave experiments
Authors: Löwenberg Robin , Moortgat-Pick Gudrid
Published: December 2023

Heterodyne cavity experiments for gravitational wave (GW) detection experience a rising interest since recent studies showed that they allow to probe the ultra high frequency regime above $$10\,\text {kHz}$$

10

kHz

. In this paper, we present a concise theoretical study of the experiment based on ideas from the former MAGO collaboration which already started experiments in turn of the millenium. It extends the former results via deriving an additional term originating from a back-action of the electromagnetic field on the cavity walls, also known as Lorentz Force Detuning. We argue that this term leads to a complex dependence of the signal power $$P_{\text {sig}}$$

P
sig

on the coupling coefficient between the mechanical shell modes and the electromagnetic eigenmodes of the cavity. It turns out that one has to adapt the coupling over the whole parameter space since the optimal value depends on the mechanical mode $$\omega _l$$

ω
l

and the GW frequency $$\omega _g$$

ω
g

. This result is particularly relevant for the design of future experiments.
Ground states of all mesons and baryons in a quark model with hidden local symmetry
Authors: He Bing-Ran , Harada Masayasu , Zou Bing-Song
Published: December 2023

We extend the chiral quark model for u,  d,  c and b quarks with vector mesons, which we proposed in the previous analysis, to a model with the s quark. We include the nonet pseudo-scalar and vector mesons together with the singlet scalar meson based on the SU(3)$$_L \times $$

L

×

 SU(3)$$_R$$

R

chiral symmetry combined with the hidden local symmetry, which mediate force among u,  d and s quarks. We fit the model parameters to the known ground state mesons and baryons. We show that the mass spectra of those hadrons are beautifully reproduced. We predict the masses of missing ground states, 1 meson and 20 baryons, which will be tested in the future experiment.
Studying social networks in the age of computational social science
Authors: Xu Xinwei
Published: December 2023

Social and behavioral sciences now stand at a critical juncture. The emergence of Computational Social Science has significantly changed how social networks are studied. In his keynote at IC2S2 2021, Lehmann presented a series of research based on the Copenhagen Network Study and pointed out an important insight that has mostly gone unnoticed for many network science practitioners: the data generation process — in particular, how data is aggregated over time and the medium through which social interactions occur — could shape the structure of networks that researchers observe. Situating the keynote in the broader field of CSS, this commentary expands on its relevance for the shared challenges and ongoing development of CSS.
Deflating the Chinese balloon: types of Twitter bots in US-China balloon incident
Authors: Ng Lynnette Hui Xian , Carley Kathleen M.
Published: December 2023

As digitalization increases, countries employ digital diplomacy, harnessing digital resources to project their desired image. Digital diplomacy also encompasses the interactivity of digital platforms, providing a trove of public opinion that diplomatic agents can collect. Social media bots actively participate in political events through influencing political communication and purporting coordinated narratives to influence human behavior. This article provides a methodology towards identifying three types of bots: General Bots, News Bots and Bridging Bots, then further identify these classes of bots on Twitter during a diplomatic incident involving the United States and China. In the balloon incident that occurred in early 2023, where a balloon believed to have originated from China is spotted across the US airspace. Both countries have differing opinions on the function and eventual handling of the balloon. Using a series of computational methods, this article examines the impact of bots on the topics disseminated, the influence and the use of information maneuvers of bots within the social communication network. Among others, our results observe that all three types of bots are present across the two countries; bots geotagged to the US are generally concerned with the balloon location while those geotagged to China discussed topics related to escalating tensions; and perform different extent of positive narrative and network information maneuvers. The broader implications of our work towards policy making is the systematic identification of the type of bot users and their properties across country lines, enabling the evaluation of how automated agents are being deployed to disseminate narratives and the nature of narratives propagated, and therefore reflects the image that the country is being projected as on social media; as well as the perception of political issues by social media users.
Maximum Bipartite Subgraphs of Geometric Intersection Graphs
Authors: Jana Satyabrata , Maheshwari Anil , Mehrabi Saeed , Roy Sasanka
Published: December 2023

We study the Maximum Bipartite Subgraph ([Formula: see text]) problem, which is defined as follows. Given a set [Formula: see text] of [Formula: see text] geometric objects in the plane, we want to compute a maximum-size subset [Formula: see text] such that the intersection graph of the objects in [Formula: see text] is bipartite. We first give an [Formula: see text]-time algorithm that computes an almost optimal solution for the problem on circular-arc graphs. We show that the [Formula: see text] problem is [Formula: see text]-hard on geometric graphs for which the maximum independent set is [Formula: see text]-hard (hence, it is [Formula: see text]-hard even on unit squares and unit disks). On the other hand, we give a [Formula: see text] for the problem on unit squares and unit disks. Moreover, we show fast approximation algorithms with small-constant factors for the problem on unit squares, unit disks, and unit-height axis parallel rectangles. Additionally, we prove that the Maximum Triangle-free Subgraph ([Formula: see text]) problem is NP-hard for axis-parallel rectangles. Here the objective is the same as that of the [Formula: see text] except the intersection graph induced by the set [Formula: see text] needs to be triangle-free only (instead of being bipartite).
Configurations of Digital Participatory Budgeting
Authors: Palacin Victoria , McDonald Samantha , Aragón Pablo , Nelimarkka Matti
Published: December 2023

Participatory budgeting is a democratic innovation increasingly supported by digital platforms. Like any technology, participatory budgeting platforms are not value-free or politically neutral; their design, configuration, and deployment display assumptions and configure participant behaviour. To understand what kinds of configurations occur and what kinds of democratic values they hold, we studied 31 digital participatory budgeting cases in Spain, France, and Finland. These cases were all supported by the same technical platform,
Decidim
, allowing us to focus on the variations in their configurations. We examined the data from these cases and identified 25 different technical configurations and 15 participatory budgeting configurations. The configurations observed in our cases exhibit
individual
and
community-centred
assumptions about expected state-society interactions, as well as
open vs managerial
approaches to participatory budgeting. Based on these findings, we highlight a dilemma for civic technology designers: to what degree should platforms be open to configuration and customisation, and which political values should be enforced by platform design?
Investigations on CuCl/HCl Electrolysis Using a Pt/C Electrocatalyst-based Membrane Electrode Assembly
Authors: Banerjee Atindra Mohan , Antony Rajini P. , Nadar Ashish , Tripathi V. M. , Aich S. , Pai M. R. , Tripathi A. K.
Published: December 2023

The study reports the fabrication and performance evaluation of a Pt/C(Electrocatalyst) (20 wt% Pt)/Nafion MEA as cathode for CuCl/HCl electrolysis in a PEM-based electrolyser with an active area of ∼4 cm2. The electrolyser is indigenously developed consisting of graphite plates with serpentine fluid flow channels grooved. The anode half-cell reaction i.e. Cu+ oxidation is investigated by electrochemical (LSV, CV, EIS) methods, and I-V characteristics. An oxidation peak for Cu+ to Cu2+ is observed at a cell voltage of ∼0.55 V in the LSV curve recorded at 20 mVs−1 in the electrolyser with an anolyte of 0.2 M CuCl in ∼2 M HCl flowing at 2.2 ml min−1. The effect of the concentration of CuCl in the anolyte and its flow rate is also studied. A current density of ∼128 mAcm−2 is attained for CuCl/HCl electrolysis at a cell voltage of 1 V with an anolyte of 0.4 M CuCl in ∼4 M HCl flowing at 8.8 ml min−1. Further, a model showing the working of the above electrolyser is generated using COMSOL 6.0. Higher concentration of CuCl in the anolyte and higher anolyte flow rates favoring the electrolysis is evident from electrochemical characterizations.
A High-Potential Trapped State Upon H2-Starvation of a Platinum Electrode in Aqueous Electrolyte
Authors: Heinritz A. , Leidinger P. , Buhk B. , Herranz J. , Schmidt T. J.
Published: December 2023

The insufficient supply of H
2 to the anode of a fuel cell (so-called “H
2-starvation”) leads to a high electrode potential that can ultimately cause cell failure. Herein we mimicked this H
2-starvation in a liquid electrolyte using a polycrystalline Pt rotating disk electrode (RDE) and demonstrate that this Pt-RDE gets trapped at high potentials even when the H
2-supply is re-establishing. Our results could have significant implications for the durability of Pt-based anode catalysts, and highlight the urgency of verifying the occurrence of this “trapped state” in a fuel cell configuration.
Direction Consistency‐Guided Lightweight Power Line Detection Network for Aerial Images
Authors: Zhang Guanying , Shu Yunhao , Zhu Wenming , Ma Jianxun , Liu Yun , Xu Chang
Published: December 2023

Accurate detection of power lines in aerial images is of great significance in ensuring grid security. However, complex power line scenarios and the thin and light structure of power lines both make it difficult to detect power lines accurately. Most of the existing approaches use traditional deep learning methods, using networks with a large number of parameters, computation, and memory occupation, thus making them not lightweight enough to perform on mobile devices. Based on this, a lightweight power line detection network based on direction consistency and location attention is proposed. The network is designed with a coordinate‐aware feature extraction layer, which performs feature extraction by four‐layer stacking to achieve faster inference speed while ensuring the network has fewer parameters. This layer is also able to sense the coordinates of the center pixel of the convolution in the image during the convolution process, thus preserving the location information of the power lines. In order to enhance the power line representation, a two‐stage context‐guided module is later utilized to simultaneously learn local features, surrounding context, and global context. Then, the features are input into a Gaussian kernel estimation module and features are aggregated in the corresponding directions through Gaussian kernels of eight different directions. The main directions of the power lines in the image and the corresponding Gaussian convolution kernels are obtained by filtering the feature responses. In addition, a kernel‐guided decoder module is proposed to take advantage of the estimated power line features in the main direction of Gaussian kernel aggregation. This module can effectively enhance the power line representation and maintain the continuity of power lines. Meanwhile, low‐level features are introduced to recover the edge details to realize high performance in distinguishing dense power lines. Both ablation experiments and comparison experiments on the transmission towers and power lines aerial‐image and Power Line Aerial Image Dataset show that the proposed power line detection network has a good segmentation performance in complex scenarios. The proposed method performs the best in the comparison experiments, improving over the suboptimal method by 3.51% on average for the max F‐measure metric.
Real‐Time Medical Image Classification with ML Framework and Dedicated CNN–LSTM Architecture
Authors: Salehin Imrus , Islam Md. Shamiul , Amin Nazrul , Baten Md. Abu , Noman S. M. , Saifuzzaman Mohd , Yazmyradov Serdar
Published: December 2023

In the domain of modern deep learning and classification techniques, the convolutional neural network (CNN) stands out as a highly successful and preferred method for image classification in artificial intelligence. Especially in the medical field, CNN has proven to be an ideal approach for analyzing medical data and accurately identifying diseases. Over the recent years, CNN has demonstrated significant potential and success in various computer vision tasks, with medical image classification being one of the prominent applications. In our study, we introduce a novel custom CNN model called MedvCNN, designed for classifying different types of classes. We conduct experiments with various image sizes to explore their versatility. In addition, long short‐term memory (LSTM), a type of recurrent neural network (RNN), is incorporated into our approach. LSTM is specifically tailored to handle sequential data, making it ideal for time series analysis. However, its capabilities extend beyond time series data and are effectively applied to various sequential data types, including sequential vectors derived from image data. One of the key advantages of utilizing LSTM for image classification is its ability to effectively memorize and capture important features in the image data. This feature is particularly advantageous in medical image processing, where precise and accurate identification of key attributes is crucial for successful diagnosis and analysis. Furthermore, our experiments reveal that the hybrid custom LSTM model, MedvLSTM, a RNN algorithm, surpasses other methods in the domain of medical image classification. Our study places significant emphasis on attaining robust classification performance for medical image data through a sophisticated, parameter free approach, complemented by an ablation study, and comprehensive statistical analysis. This comprehensive analysis and evaluation allow us to gain a deeper understanding of the model’s effectiveness and its potential impact in the field of medical image analysis. We compare these two approaches to a baseline CNN architecture, aiming to streamline the classification process, reduce time consumption, and improve cost efficiency. Additionally, we present a real‐time web‐based AutoML framework along with a practical demonstration. Ultimately, our research provides a thorough investigation of the current state‐of‐the‐art in medical image analysis accuracy, focusing on the utilization of neural networks and LSTM.
Numerical Simulation of Acoustic Emission Events in Supporting Roadways under Different Dynamic Loads
Authors: Shang Wenzheng , Liu Zhigang , Yuan Jianbo , You Wuchao , Han Shuai , Yu Lei , Zhang Shihua
Published: December 2023

This paper studies the distribution characteristics of acoustic emission (AE) events in supporting roadways under different dynamic load conditions through numerical simulation and theoretical analysis. According to the principle of AE numerical simulation, the roadway model is established by FLAC3D software, and the supporting structure of the bolt cable is established by editing the Fish function. According to the model dynamic load application criterion, the relationship between the peak velocity of the particle, the distance from the source center to the dynamic impact damage point, and the dynamic load intensity is introduced. The velocity-distance-energy relationship is deduced from the relationship to determine the magnitude of the dynamic load energy. The simulation results show that the intensity of the dynamic load source and the distance of the dynamic load source directly impact the AE events. The larger the dynamic load intensity and the closer to the dynamic load source, the more concentrated the AE events. The roadway has a blocking effect on the transmission of the dynamic load stress waves. According to this characteristic, the roadway can be protected by a high-pressure relief roadway. Rock lithology greatly influences the transmission of dynamic load stress waves and the number of AE events. When the dynamic load stress wave passes through the rock strata of different lithologies, the attenuation of the dynamic load energy and the number of AE events are large. However, when the dynamic load stress wave passes through the rock strata of the same lithology, the attenuation of the dynamic load energy and AE events is small. The surrounding rock structure in the bottom corner area of the roadway is susceptible to disturbance from dynamic load sources above the roadway. The results are greatly significant for studying the AE characteristics of support roadways with disturbance-typeimpact failure.