bluuebunny/crossref_metadata_2025 huggingface dataset:
Service disruptions, trauma and burnout during the COVID-19 pandemic among healthcare providers delivering immunisation and maternal and child health services in Indonesia
Authors: Randell Madeleine , Wahyono Tri Yunis Miko , Dynes Michelle , Tinessia Adeline , Li Mu , Danchin Margie , Oktarinda  , Fitriyani Fitriyani , Saraswati Lintang Dian , Jenkins Kylie , Aung Khin Devi , Noorzad Abdul Khalil , Shetye Mrunal , Dewi Lulu , Yosephine Prima , Leask Julie , Sheel Meru
Published: July 2024

Background

The COVID-19 pandemic resulted in extreme strain on health systems including the health workforce, essential health services and vaccination coverage. We examined disruptions to immunisation and maternal and child health (MCH) services, concerns of personal well-being and delivery of healthcare during the pandemic as well as factors associated with self-reported trauma or burnout among healthcare providers (HCPs).

Methods

In March–April 2022, we conducted a cross-sectional survey among HCPs in two provinces of Indonesia. HCPs involved in COVID-19 or routine immunisation and MCH services were randomly selected from district/city health office registration lists. We descriptively analysed service disruptions experienced by HCPs as well as trauma, burnout and concerns of personal well-being and delivery of healthcare during the pandemic. Multivariate logistic regression analyses were undertaken to identify factors associated with trauma or burnout.

Results

We recruited 604 HCPs. Mobilisation of staff from routine health services to COVID-19 response duties was a key reason for service disruptions (87.9%). Strategies such as community outreach and task shifting were implemented to overcome disruptions. Trauma or burnout during the pandemic was reported by 64.1% HCPs, with 23.5% reporting worse mental or emotional health.

Factors associated with trauma or burnout included delivery of COVID-19 immunisation (adjusted OR (aOR) 2.54, 95% CI 1.08 to 5.94); and delivery of both COVID-19 immunisation and routine immunisation compared with no involvement in vaccination programmes (aOR 2.42, 95% CI 1.06 to 5.52); poor treatment in the workplace (aOR 2.26, 95% CI 1.51 to 3.38) and lower confidence to respond to patient queries on COVID-19 immunisation (aOR 1.51, 95% CI 1.03 to 2.22).

Conclusion

HCPs experienced service disruptions, trauma and burnout and implemented strategies to minimise disruptions to service delivery and improve patient experiences. Our study highlights the need to ensure that workforce resilience and strategies to protect and support HCPs are considered for pandemic planning, preparedness and management.
Living with mesothelioma: a systematic review of mental health and well-being impacts and interventions for patients and their informal carers
Authors: Sherborne Virginia , Ejegi-Memeh Stephanie , Tod Angela Mary , Taylor Bethany , Hargreaves Sarah , Gardiner Clare
Published: July 2024

Objectives

Mesothelioma is an aggressive cancer predominantly affecting the lung and abdominal linings. It can have a unique impact on mental health and well-being (MHWB) due to its incurability, poor prognosis and asbestos-exposure causation. This review’s aims were to identify/synthesise international evidence on mesothelioma’s MHWB impacts; explore MHWB interventions used by patients and carers; and identify evidence of their effectiveness.

Design

Systematic review.

Data sources

Databases, searched March 2022 and March 2024, were MEDLINE; CINAHL; PsycINFO; Cochrane Library; ASSIA.

Eligibility criteria

We included study designs focusing on psychological impacts of living with mesothelioma and MHWB interventions used by patients and informal carers, published in English since January 2002.

Data extraction and synthesis

A team of reviewers screened included studies using standardised methods. Quality was assessed using validated tools: Mixed-Methods Appraisal tool for primary research and Joanna Briggs Institute Critical Appraisal Checklist for Systematic Reviews.

Results

Forty-eight studies met the inclusion criteria: 20 qualitative, 16 quantitative, nine reviews, two mixed-methods, one combined systematic review/qualitative study. UK studies predominated. Many MHWB impacts were reported, including traumatic stress, depression, anxiety and guilt. These were influenced by mesothelioma’s causation, communication issues and carer-patient relational interactions. Participants used wide-ranging MHWB interventions, including religious/spiritual practice; talking to mental-health professionals; meaning-making. Some strategies were presented as unhelpful, for example, denial. Participants reported lack of access to support.

Conclusions

Most qualitative studies were rated high quality. The quality of the quantitative studies and reviews varied. The sparse literature regarding MHWB in mesothelioma means more research is needed into impacts on patients and carers, including trauma. To enable access to evidence-based support, research is recommended concerning MHWB interventions’ effectiveness in mesothelioma.

PROSPERO registration number

CRD42022302187.
Assessing the efficacy of a brief universal family skills programme on child behaviour and family functioning in Gilgit-Baltistan, Pakistan: protocol for a feasibility randomised controlled trial of the Strong Families programme
Authors: El-Khani Aala , Asif Muqaddas , Shahzad Salman , Bux Majid Sain , Maalouf Wadih , Rafiq Noor ul Zaman , Khoso Ameer B , Chaudhry Imran Bashir , Van Hout Marie-Claire , Zadeh Zainab , Tahir Azam , Memon Rakhshi , Chaudhry Nasim , Husain Nusrat
Published: July 2024

Purpose

The global burden of mental health difficulties among children underscores the importance of early prevention. This study aims to assess the efficacy, feasibility and acceptability of the Strong Families programme in enhancing child behaviour and family functioning in low-resource settings in Gilgit-Baltistan, Pakistan.

Methods and analysis

This is a two-arm, multisite feasibility randomised controlled trial with an embedded process evaluation in three districts of Gilgit-Baltistan, namely Gilgit, Hunza and Skardu. 90 families living in these challenged settings, comprising a female primary caregiver aged 18 or above, and at least one child aged 8–15 years, will participate. Participants will be randomly assigned to either receive the Strong Families programme or to the waitlist group. Strong Families is a 7-hour family skills group intervention programme attended by children and their primary caregivers over 3 weeks. The waitlist group will be offered the intervention after their outcome assessment. Three raters will conduct blind assessments at baseline, 2 and 6 weeks postintervention. The primary outcome measures include the feasibility of Strong Families, as determined by families’ recruitment and attendance rates, and programme completeness (mean number of sessions attended, attrition rates). The secondary outcomes include assessment of child behaviour, parenting practices, parental adjustment and child resilience. Purposefully selected participants, including up to five caregivers from each site, researchers and facilitators delivering the intervention, will be interviewed. Descriptive statistics will be used to analyse primary and secondary outcomes. The process evaluation will be conducted in terms of programme context, reach, fidelity, dose delivered and received, implementation, and recruitment.

Ethics and dissemination

This study has been approved by the UNODC Drug Prevention and Health Branch in the Headquarters office of Vienna and the National Bioethics Committee of Pakistan. Findings will be disseminated through publication in reputable journals, newsletters and presentations at conferences.

Trial registration number

NCT05933850.
Acceptability and feasibility of a theatre-based wellness programme to support people living with long COVID: a single-arm feasibility study
Authors: Burton Alexandra , Bone Jessica K , Lawrence-Lunniss Kate , Philip Keir EJ
Published: July 2024

Objectives

To determine acceptability and feasibility of a theatre-based wellness programme to support the health and well-being of people with long COVID.

Design

Single-group, repeated-measures feasibility study.

Setting

Community centre and online.

Participants

Adults with diagnosed long COVID experiencing breathlessness, pain and/or loneliness.

Intervention

Six-week participatory creative programme delivered to one online and one in-person group facilitated by movement, voice and drama consultants using breathing, visualisation, singing, poetry, storytelling and movement exercises.

Primary outcome measures

Programme acceptability and feasibility measured via uptake, reasons for non-attendance and barriers to engagement.

Secondary outcome measures

Feasibility of recruitment and data collection procedures measured through proportion of missing data and follow-up rates, mechanisms of action of the programme identified through qualitative interviews, changes in mental health, well-being, quality of life, loneliness, social support, fatigue, breathlessness and post-COVID-19 functional status at 8-week follow-up.

Results

21 people expressed interest in participating, 20 people took part in the programme, 19 completed baseline and 16 completed follow-up assessments. Participants attended an average of 4.8 of 6 sessions (SD=1.5, range 2–6). Exploratory analyses demonstrated significant improvements in self-rated health (t-test mean difference=0.12, 95% CI=0.00, 0.23, p=0.04) and chronic fatigue symptoms (mean difference=−3.50, 95% CI=−6.97, –0.03, p=0.05) at 8 weeks. Key mechanisms of action that supported health and well-being included: increased sense of community, illness acceptance, experiencing joy, increased confidence in managing everyday life, increased ability to relax and reconnection with previous identity. Barriers to engagement included: activities being outside of the participant's comfort zone, ongoing long COVID symptoms, emotional consequences of sharing experiences and connectivity and connecting online.

Conclusions

A 6-week theatre-based programme was perceived as acceptable to most participants and resulted in some positive psychosocial impacts. The findings provide a rationale for supporting the ongoing development and scale-up of this and related arts programmes to support people living with long COVID.
Cross-sectional study to investigate the seroprevalence and risk factors ofToxoplasma gondiiamong women attending the antenatal clinic in Namwala, Zambia
Authors: Daka Victor , Mukosha Moses , Zimba Sharon D , Phiri Andrew M
Published: July 2024

Background

Toxoplasmosis is a zoonotic parasitic disease caused byToxoplasma gondii (T. gondii). It has a wide host range and is capable of vertical transmission in pregnant women, which may lead to undesirable pregnancy outcomes such as congenital malformations, miscarriage, premature birth and stillbirth. This study investigated the seroprevalence ofT. gondiiinfection among pregnant women attending the antenatal clinic at Namwala District Hospital in Southern Zambia.

Methods

This was a cross-sectional study where blood was collected, and the serum was tested forToxoplasmaIgG and IgM. A questionnaire was administered to participants on demographic characteristics and risk factors. Data were entered in Microsoft Excel and exported to STATA version 14 for analysis.

Results

A total of 401 women were enrolled in the study from 3 March to 5 August 2021. The seroprevalence ofToxoplasmaIgG was 4.2% (n=17), while the seroprevalence ofToxoplasmaIgM was 0.7% (n=3). The median age was 27 (IQR: 24–30) years, and a larger proportion had primary-level education (n=223, 55.6%). The majority (81.6%) of the women were married. None of the risk factors investigated in this study were significant forT. gondiiinfection.

Conclusion

There was a low seroprevalence ofT. gondiiinfection among pregnant women in the Namwala district of Southern Province, Zambia, and regular screening may not be warranted in this population. Continued research on toxoplasmosis is recommended to understand its epidemiology across Zambia.
Impact of tonsillectomy on the efficacy of Alt-RAMEC/PFM treatment protocols in children with class III malocclusion and tonsillar hypertrophy: protocol for a cluster randomised controlled trial
Authors: Guo Feiyang , Li Qiujing , Ngan Peter , Guan Guoqiang , Chen Xiong , Yang Xiuping , Lv Chenxing , Hua Fang , Zhao Tingting , He Hong
Published: July 2024

Introduction

Orthodontic treatment using face mask protraction combined with an alternate rapid maxillary expansion and constriction/protraction face mask (Alt-RAMEC/PFM) protocol is effective in the early treatment of patients with class III malocclusion, but the stability of treatment outcomes represents a major concern. Previous studies have suggested that tonsillar hypertrophy can be a risk factor for class III malocclusion and tonsillectomy may prompt the normalisation of dentofacial growth. However, these studies had a low-to-moderate level of evidence. This study was designed to identify the impact of tonsillectomy before orthodontic treatment on the efficacy and stability of Alt-RAMEC/PFM protocols and the sleep quality and oral health in children with anterior crossbite and tonsillar hypertrophy.

Methods and analysis

This is a two-arm, parallel-group, superiority cluster randomised controlled trial, with four clinics randomly assigned to the surgery-first arm and the orthodontic-first arm in a 1:1 ratio. The Alt-RAMEC protocol involves alternate activation and deactivation of the expander’s jet screw over 6 weeks to stimulate maxillary suture distraction. Patients will be instructed to wear the PFM for a minimum of 14 hours per day. The primary outcomes are changes in Wits appraisal and the degree of maxillary advancement from baseline to the end of orthodontic treatment. Lateral cephalometric radiographs, polysomnography, Obstructive Sleep Apnoea-18 questionnaire and Oral Health Impact Profile-14 questionnaire will be traced, collected and measured. We will recruit 96 patients intofor the study. To assess differences, repeated multilevel linear mixed modelling analyses will be used.

Ethics and dissemination

This study has been granted ethical approval by the Ethics Committee of the School & Hospital of Stomatology, Wuhan University (approval No. 2023-D10). Written informed consent will be obtained from the participants and their guardians. The results of the trial will be disseminated through academic conferences and journal publications.

Trial registration number

ChiCTR2300078833.
Are the content and usability of a new direct observation tool adequate for assessing competency in delivering person-centred care: a think-aloud study with patients and healthcare professionals in Sweden
Authors: Ekman Nina , Fors Andreas , Moons Philip , Boström Eva , Taft Charles
Published: July 2024

Objective

To evaluate the content and usability of a new direct observation tool for assessing competency in delivering person-centred care based on the Gothenburg Centre for Person-Centred Care (gPCC) framework.

Design

This is a qualitative study using think-aloud techniques and retrospective probing interviews and analyzed using deductive content analysis.

Setting

Sessions were conducted remotely via Zoom with participants in their homes or offices.

Participants

11 participants with lengthy experience of receiving, delivering and/or implementing gPCC were recruited using purposeful sampling and selected to represent a broad variety of stakeholders and potential end-users.

Results

Participants generally considered the content of the four main domains of the tool, that is, person-centred care activities, clinician manner, clinician skills and person-centred care goals, to be comprehensive and relevant for assessing person-centred care in general and gPCC in particular. Some participants pointed to the need to expand person-centred care activities to better reflect the emphasis on eliciting patient resources/capabilities and psychosocial needs in the gPCC framework. Think-aloud analyses revealed some usability issues primarily regarding difficulties or uncertainties in understanding several words and in using the rating scale. Probing interviews indicated that these problems could be mitigated by improving written instructions regarding response options and by replacing some words. Participants generally were satisfied with the layout and structure of the tool, but some suggested enlarging font size and text spacing to improve readability.

Conclusion

The tool appears to satisfactorily cover major person-centred care activities outlined in the gPCC framework. The inclusion of content concerning clinician manner and skills was seen as a relevant embellishment of the framework and as contributing to a more comprehensive assessment of clinician performance in the delivery of person-centred care. A revised version addressing observed content and usability issues will be tested for inter-rater and intra-rater reliability and for feasibility of use in healthcare education and quality improvement efforts.
Hepatitis C risk score as a tool to identify individuals with HCV infection: a demonstration and cross-sectional epidemiological study in Egypt
Authors: El-Khoury Rayane , Chemaitelly Hiam , Alaama Ahmed S , Hermez Joumana G , Nagelkerke Nico , Abu-Raddad Laith J
Published: July 2024

Objectives

Hepatitis C virus (HCV) infection poses a global health challenge. By the end of 2021, the WHO estimated that less than a quarter of global HCV infections had been diagnosed. There is a need for a public health tool that can facilitate the identification of people with HCV infection and link them to testing and treatment, and that can be customised for each country.

Methods

We derived and validated a risk score to identify people with HCV in Egypt and demonstrated its utility. Using data from the 2008 and 2014 Egypt Demographic and Health Surveys, two risk scores were constructed through multivariable logistic regression analysis. A range of diagnostic metrics was then calculated to evaluate the performance of these scores.

Results

The 2008 and 2014 risk scores exhibited similar dependencies on sex, age and type of place of residence. Both risk scores demonstrated high and similar areas under the curve of 0.77 (95% CI: 0.76 to 0.78) and 0.78 (95% CI: 0.77 to 0.80), respectively. For the 2008 risk score, sensitivity was 73.7% (95% CI: 71.5% to 75.9%), specificity was 68.5% (95% CI: 67.5% to 69.4%), positive predictive value (PPV) was 27.8% (95% CI: 26.4% to 29.2%) and negative predictive value (NPV) was 94.1% (95% CI: 93.5% to 94.6%). For the 2014 risk score, sensitivity was 64.0% (95% CI: 61.5% to 66.6%), specificity was 78.2% (95% CI: 77.5% to 78.9%), PPV was 22.2% (95% CI: 20.9% to 23.5%) and NPV was 95.7% (95% CI: 95.4% to 96.1%). Each score was validated by applying it to a different survey database than the one used to derive it.

Conclusions

Implementation of HCV risk scores is an effective strategy to identify carriers of HCV infection and to link them to testing and treatment at low cost to national programmes.
Unbalanced core detector (UCD): a novel direct-reading dosimeter for FLASH radiotherapy
Authors: Bedogni R. , Russo L. , Calamida A. , Castro-Campoy A. I. , Fontanilla A. , Dashdondog D. , Caballero-Pacheco M. A. , Napolitano T. , Cantone C. , Pietropaolo A. , Felici G.
Published: July 2024

FLASH radiotherapy (FRT) is a novel radiotherapy technique based on dose rates that are several orders of magnitude greater than those used in conventional radiotherapy (40 Gy/s vs. 0.5–5 Gy/min). FRT is still in its preclinical and early clinical stage of development. However these studies indicate that FRT is more effective in sparing normal tissues from radiation-related side effects, as compared to conventional radiotherapy. This is the so-called "FLASH effect" and was observed with multi-MeV electron beams. Before FRT is made available to humans, more basic research is needed to fully understand its radiobiology fundamentals. Meanwhile, suitable radiation sources and dosimetric tools are gradually becoming available. Within this framework, INFN-LNF developed the Unbalanced Core Detector (UCD), a novel type of electron dosimeter designed to operate in the FRT domain. UCD main characteristics are the nearly isotropic response, the independence from the electron energy, the very high radiation resistance, the linearity up to dose rates of MGy/s and the possibility to record the time evolution of a single radiation pulse. UCD was tested using 7 and 9 MeV electron beams produced with the ElectronFlash accelerator from Sordina IORT Technologies (SIT S.p.A.) in Aprilia, Italy. UCD was used to measure dose distributions in a water phantom. The results well compare to those obtained with a flashDiamond detector from PTW.
Predictability of information spreading on online social networks
Authors: Meng Fanhui , Xie Jiarong , Ma Xiao , Wang Jinghui , Hu Yanqing
Published: June 2024

With the rapid development of the mobile Internet, online social networks are playing an increasingly vital role in the dissemination of information. Accurately predicting the size of information cascades in advance has become a crucial issue, particularly in the realms of viral marketing, risk management and resource allocation. There are numerous studies that have tackled this prediction task, but the outcomes are unsatisfactory. In this paper, we explore the predictability of information cascade size through the lens of percolation theory. Our investigation reveals that the accuracy of cascade size prediction is notably diminished in the proximity of the threshold, evident in both artificial and empirical networks. Moreover, we observe a degradation and an user-level difference in prediction performance as social media platforms undergo evolution. Our findings underscore the necessity for additional factors to enhance prediction accuracy.
Scaling laws of multi-scale coherence and multifractal analysis in the stock market
Authors: Li Xuebo , Hu Xin , Hu Lan , Deng Shenyan , Zhang Langxi , Wu Helin
Published: June 2024

In this study, we utilize the coherence spectrum and structure-function methods to examine the multi-scale coherence and multifractal characteristics of financial time series. The phase spectrum reveals the temporal shift between two indices, indicating whether one leads or lags by several days within a region of high correlation that is scale-dependent. This information can serve as a predictive model for quantitative analysis. The Fourier power spectrum and scaling exponents, derived from the structure-function method, exhibit universal patterns across indices from various countries. Our findings suggest that stock market indices display behavior akin to turbulence, as demonstrated by the structure-function, power-law scaling and multifractal movements. Our results suggest that the fluctuations of indices could be accurately represented by a multifractal random walk model, offering a complex and insightful view of the financial market.
Soret and Dufour effects on Sutterby nanofluid flow over a Riga stretching surface with variable thermal conductivity
Authors: Ali Mohsin , Abbas Nadeem , Shatanawi Wasfi
Published: June 2024

This research investigated the impact of Sorret and Dufour on the flow of Sutterby nanofluid over a stretchable Riga sheet while considering the variable thermal conductivity. The analysis was based on the Buongiorno nanofluid model, and nonlinear partial differential equations were formulated using the governing laws and applying the boundary layer approximations. These equations were transformed into ordinary differential equations using appropriate similarity variables. The bvp4c numerical scheme in MATLAB was used to calculate numerical and graphical results. The figures show how various parameters affect the velocity, temperature, and concentration profiles. Additionally, numerical results of the skin friction, Nusselt number, and Sherwood number for various parameters were presented in tables. The velocity distribution profile decreases with an increase in the Sutterby fluid parameter value but increases with the modified Hartmann number. The temperature profile rises with increased Dufour number and thermal conductivity. The concentration profile decreases with an increase in the Schmidt number and chemical reaction but increases with an increase in the Soret number.
Investigation of planar sliding deformation and analysis of the damage mechanism of a rocky landslide in Yaoping triggered by highway excavation in Hubei, China
Authors: Ruan Di , Song Kun , Lyu Honglin , Qu Liupanpan , Zhang Lianghua , Huang Wei , Yuan Jingjing
Published: June 2024

During projects to build roads in China's mountainous areas, which are often characterized by the poor stability of rocky slopes, cases of deformation damage occur frequently. Because of the wide distribution of rocky landslides in the smooth layer, the unavoidable perturbation caused by engineering construction and the seriousness of landslide disasters, the destruction of this type of landslide and the research into prevention of the mechanism cannot be ignored. On 6 February 2023, a rock slide occurred in Yaoping village, Hubei Province, China. Using field investigations, Google satellite images, unmanned aerial vehicle photography, indoor testing and numerical simulations, we analysed the geological situation, deformation characteristics, damage process and triggering mechanism. The results show that the Yaoping landslide is a typical downward plane-sliding rock slide induced by the excavation of a highway. When strain softening occurs, the shear strength and friction coefficient of the slip zone soil are significantly reduced. Excavation caused the factor of safety of the slope to decrease substantially, with a maximum decrease rate of 60.7%. Excavation is considered to be the extrinsic factor that triggered the occurrence of the Yaoping landslide, while the reduction of landslide resistance caused by strain softening of the soil in the slip zone is the intrinsic direct factor that led to the occurrence of this type of landslide. The Yaoping landslide has obvious traction landslide characteristics. The landslide from deformation to destruction has four stages: creep at the leading edge of the landslide; traction deformation in the middle and back of the landslide; slip belt softening; and integral sliding. The prevention and control of this type of landslide requires a larger scope and depth of investigation, in order to identify in advance the possible soft surface in the rock layer, to speculate on the possible formation of landslide destruction mode, and to determine the support scheme and scope according to the geological conditions of the slopes on both sides of the highway. The slip zone soil of the Yaoping landslide was used to obtain the strength index of slip zone soil, which provides data support for the overall deformation characterization of the landslide. The results can provide a reference for the risk management and prevention of rock slides caused by human engineering activities during the excavation of roads.
The Influence that the Complexity of the Three-Dimensional Eye Model Used to Generate Simulated Eye-tracking Data Has on the Gaze Estimation Errors Achieved Using the Data
Authors: Fischer Joshua David , van der Merwe Johan , Vandenheever David
Published: June 2024

Simulated eye-tracking data are an integral tool in the development of eye-tracking methods. Most of the simulated data used in eye-tracking-related research has been generated using low-complexity eye models that include a single spherical corneal surface. This study investigated the influence of eye-model complexity on the ability of simulated eye-tracking data to predict real-world outcomes. The experimental procedures of two pertinent comparative eye-tracking studies were replicated in a simulated environment using various eye-model complexities. The simulated outcomes were then evaluated against the findings of the comparative studies that were derived from real-world outcomes. The simulated outcomes of both comparative studies were significantly influenced by the eye-model complexity. Eye models that included an aspheric corneal surface best replicated experimental eye-tracking outcomes, while including a posterior corneal surface did not improve the ability of simulated data to replicate real-world outcomes. Using a wide-angle eye model that accurately replicates the peripheral optics of the eye did not improve simulated outcomes relative to a paraxial eye model.
No Tech For Apartheid and No Tech For Tyrants: A Conversation Around Organizing and Technology
Authors: Schubiner Gabriel , Dharmaraj Nikhil
Published: June 2024

Organizers at the intersection of anticolonial justice and technology, Gabriel Schubiner and Nikhil Dharmaraj discuss their journeys, the historical context of their work, and organizing strategies.
Fixed-Parameter Tractability of Maximum Colored Path and Beyond
Authors: Fomin Fedor V. , Golovach Petr A. , Korhonen Tuukka , Simonov Kirill , Stamoulis Giannos
Published: June 2024

We introduce a general method for obtaining fixed-parameter algorithms for problems about finding paths in undirected graphs, where the length of the path could be unbounded in the parameter. The first application of our method is as follows. We give a randomized algorithm, that given a colored

\(n\)

-vertex undirected graph, vertices

\(s\)

and

\(t\)

, and an integer

\(k\)

, finds an

\((s,t)\)

-path containing at least

\(k\)

different colors in time

\(2^{k}n^{\mathcal{O}(1)}\)

. This is the first FPT algorithm for this problem, and it generalizes the algorithm of Björklund, Husfeldt, and Taslaman on finding a path through

\(k\)

specified vertices. It also implies the first

\(2^{k}n^{\mathcal{O}(1)}\)

time algorithm for finding an

\((s,t)\)

-path of length at least

\(k\)

. Our method yields FPT algorithms for even more general problems. For example, we consider the problem where the input consists of an

\(n\)

-vertex undirected graph

\(G\)

, a matroid

\(M\)

whose elements correspond to the vertices of

\(G\)

and which is represented over a finite field of order

\(q\)

, a positive integer weight function on the vertices of

\(G\)

, two sets of vertices

\(S,T\subseteq V(G)\)

, and integers

\(p,k,w\)

, and the task is to find

\(p\)

vertex-disjoint paths from

\(S\)

to

\(T\)

so that the union of the vertices of these paths contains an independent set of

\(M\)

of cardinality

\(k\)

and weight

\(w\)

, while minimizing the sum of the lengths of the paths. We give a

\(2^{p+\mathcal{O}(k^{2}\log(q+k))}n^{\mathcal{O}(1)}w\)

time randomized algorithm for this problem.
Subspace-Contrastive Multi-View Clustering
Authors: Fu Lele , Huang Sheng , Zhang Lei , Yang Jinghua , Zheng Zibin , Zhang Chuanfu , Chen Chuan
Published: June 2024

Most multi-view clustering methods based on shallow models are limited in sound nonlinear information perception capability, or fail to effectively exploit complementary information hidden in different views. To tackle these issues, we propose a novel Subspace-Contrastive Multi-View Clustering (SCMC) approach. Specifically, SCMC utilizes a set of view-specific auto-encoders to map the original multi-view data into compact features capturing its nonlinear structures. Considering the large semantic gap of data from different modalities, we project multiple heterogeneous features into a joint semantic space, namely the embedded compact features are passed through the self-expression layers to learn the subspace representations, respectively. In order to enhance the discriminability and efficiently excavate the complementarity of various subspace representations, we use the contrastive strategy to maximize the similarity between positive pairs while differentiate negative pairs. Thus, the graph regularization is employed to encode the local geometric structure within varying subspaces for optimizing the consistent affinity matrix. Furthermore, to endow the proposed SCMC with the ability of handling the multi-view out-of-samples, we develop a consistent sparse representation (CSR) learning mechanism over the in-samples. To demonstrate the effectiveness of the proposed model, we conduct a large number of comparative experiments on ten challenging datasets, and the experimental results show that SCMC outperforms existing shallow and deep multi-view clustering methods. In addition, the experimental results on out-of-samples illustrate the effectiveness of the proposed CSR.
ReIPE: Recycling Idle PEs in CNN Accelerator for Vulnerable Filters Soft-Error Detection
Authors: Wei Xiaohui , Wang Chenyang , Yue Hengshan , Tan Jingweijia , Guan Zeyu , Jiang Nan , Zheng Xinyang , Zhao Jianpeng , Qiu Meikang
Published: June 2024

To satisfy prohibitively massive computational requirements of current deep Convolutional Neural Networks (CNNs), CNN-specific accelerators are widely deployed in large-scale systems. Caused by high-energy neutrons and α-particle strikes, soft error may lead to catastrophic failures when CNN is deployed on high integration density accelerators. As CNNs become ubiquitous in mission-critical domains, ensuring the reliable execution of CNN accelerators in the presence of soft errors is increasingly essential.

In this article, we propose to
Re
cycle
I
dle
P
rocessing
E
lements (PEs) in the CNN accelerator for vulnerable filters soft error detection (ReIPE). Considering the error-sensitivity of filters, ReIPE first carries out a filter-level gradient analysis process to replace fault injection for fast filter-wise error resilience estimation. Then, to achieve maximal reliability benefits, combining the hardware-level systolic array idleness and software-level CNN filter-wise error resilience profile, ReIPE preferentially duplicated loads the most vulnerable filters onto systolic array to recycle idle-column PEs for opportunistically redundant execution (error detection). Exploiting the data reuse properties of accelerators, ReIPE incorporates the error detection process into the original computation flow of accelerators to perform real-time error detection. Once the error is detected, ReIPE will trigger a correction round to rectify the erroneous output. Experimental results performed on LeNet-5, Cifar-10-CNN, AlexNet, ResNet-20, VGG-16, and ResNet-50 exhibit that ReIPE can cover 96.40% of errors while reducing 75.06% performance degradation and 67.79% energy consumption of baseline dual modular redundancy on average. Moreover, to satisfy the reliability requirements of various application scenarios, ReIPE is also applicable for pruned, quantized, and Transformer-based models, as well as portable to other accelerator architectures.
Hidden Barcode in Sub-Images with Invisible Locating Marker
Authors: Jia Jun , Gao Zhongpai , Yang Yiwei , Sun Wei , Zhu Dandan , Liu Xiaohong , Min Xiongkuo , Zhai Guangtao
Published: June 2024

The prevalence of the Internet of Things has led to the widespread adoption of 2D barcodes as a means of offline-to-online communication. Whereas, 2D barcodes are not ideal for publicity materials due to their space-consuming nature. Recent works have proposed 2D image barcodes that contain invisible codes or hyperlinks to transmit hidden information from offline to online. However, these methods undermine the purpose of the codes being invisible due to the the requirement of markers to locate them. The conference version of this work presented a novel imperceptible information embedding framework for display or print-camera scenarios, which includes not only hiding and recovery but also locating and correcting. With the assistance of learned invisible markers, hidden codes can be rendered truly imperceptible. A highly effective multi-stage training scheme is proposed to achieve high visual fidelity and retrieval resiliency, wherein information is concealed in a sub-region rather than the entire image. However, our conference version does not address the optimal sub-region for hiding, which is crucial when dealing with local region concealment problems. In this article extension, we consider human perceptual characteristics and introduce an optimal hiding region recommendation algorithm that comprehensively incorporates Just Noticeable Difference and visual saliency factors into consideration. Extensive experiments demonstrate superior visual quality and robustness compared to state-of-the-art methods. With the assistance of our proposed hiding region recommendation algorithm, concealed information becomes even less visible than the results of our conference version without compromising robustness.
A Novel Dynamic Pricing Time‐Based Demand Response Program for Net‐Load Flexibility of Microgrids
Authors: Nojavan Majid , Maghouli Pouria
Published: July 2024

In recent years, concerns about electrical energy supply have led to the extensive use of renewable energy sources (RESs). In addition to all the benefits and reasons that justify the unlimited use of RESs, the unplanned exploitation of these sources can challenge the reliability indices of the power system. Demand‐side management (DSM) by demand response programs (DRPs) is one of the most effective and powerful measurements to provide flexibility for the system. DRPs can change the pattern of customer consumption as well as the shape of the load curve. In this study, a novel time‐based demand response model is proposed to control the slope of demand changes. Consequently, dynamic/fixed pricing models with a controllable time step are extracted. These models are implemented on experimental networks, and the results are analyzed and presented for three cases. According to the desired model, the electricity price management at particular hours of the day affects the behavior of the consumers, and it reduces the steep slope in the net‐load ramping curves (62.5% and 50% reduction in peak to valley (P2V) distance for hourly curve and daily curve, respectively).
Hybrid Models for Emotion Classification and Sentiment Analysis in Indonesian Language
Authors: Ahmadian Hendri , Abidin Taufik F. , Riza Hammam , Muchtar Kahlil
Published: June 2024

The swift growth of social networks has enabled easy access to a wealth of user‐created information for public assessment. These data hold potential for various uses, including analyzing comments and reviews through text analysis. The study utilizes a specialized version of the Bidirectional Encoder Representations from Transformers (BERT) model known as IndoBERT, tailored explicitly for Bahasa Indonesia. It aims to improve accuracy in the Indonesian natural language understanding benchmark by boosting performance in sentiment analysis and emotion classification tasks. The testing for both tasks involved a hybrid methodology that merged the summations of the four last hidden layers from the IndoBERT model with a combination of bidirectional long short‐term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU), and an attention model. The resulting model’s performance was assessed using the F1‐score metric. Based on the experimental results, the proposed model achieves an accuracy of 93% for sentiment analysis and 78% for emotion classification on the Indonesian natural language understanding (IndoNLU) benchmark dataset. The implementation result shows that the optimal accuracy of the models’ performance evaluation was obtained using different hybrid models.
A Dynamic Model of Information‐Vaccination‐Disease That Accounts for Emerging Viral Variants: Model Development and a Case Study for COVID‐19 in Iceland
Authors: Zhao Laijun , Ying Mingmin , Qian Ying , Zhou Lixin , Yang Pingle
Published: June 2024

Pathogens mutate as diseases spread, and variants that become epidemic or pandemic strains have higher transmission rates and a greater capacity to escape vaccine protection. Considering different vaccine efficacy and vaccination rates is of great significance for the prevention and control of infectious diseases. The spread of vaccination information and the level of trust in vaccinations determine whether people will choose to be vaccinated. To analyze these factors, we developed mean‐field equations for system dynamics to model the complex system of vaccine information dissemination and vaccination, calculated the basic reproduction rate number, and used the Icelandic COVID‐19 outbreak (Omicron variant) as a case study. We found that in the face of emerging variants, increasing vaccine efficacy is more effective than increasing vaccination rates. If vaccine efficacy increases from 40% to 90%, infections can be decreased by 98.5%. However, even a 100% vaccination rate cannot stop the spread of a mutated virus if vaccine efficacy falls below a certain level. High vaccination rates decrease the virus transmission rate. If the efficacy of the vaccine diminishes, the infection will spread rapidly, leading to a greater number of individuals becoming infected with the infectious disease. Due to the high vaccine efficacy against major illnesses and fatalities, improving vaccination rates can lower deaths. Iceland could decrease deaths by 44.8% by raising the vaccination rate from 75.9% to 95.0%. To combat emerging virus variants, it is therefore necessary to both create more effective vaccines and raise awareness of the benefits of vaccination to increase vaccination rates.
The Usefulness of Atopic Dermatitis Control Tool in Upadacitinib Treatment for Patients with Atopic Dermatitis
Authors: Hagino Teppei , Saeki Hidehisa , Fujimoto Eita , Kanda Naoko
Published: June 2024

Background. Atopic dermatitis control tool (ADCT) is a patient‐reported measure to assess disease control of atopic dermatitis (AD), consisting of the severity of symptoms, itch duration, bother, sleep, daily activities, and mood/emotions. Objectives. We evaluated the alterations of total and individual ADCT item scores during treatment with Janus kinase 1 inhibitor upadacitinib in AD patients. Methods. Forty‐seven patients aged ≥12 years with moderate‐to‐severe AD were treated with oral upadacitinib 15 mg/day plus topical corticosteroids. Total and individual ADCT item scores, eczema area, and severity index (EASI) and peak pruritus numerical rating scale (PP‐NRS) were evaluated. Results. Before treatment, total ADCT correlated with EASI and PP‐NRS. The median percent reduction at months 1, 3, and 6 of upadacitinib treatment was 80%, 76.2%, and 67.4% in total ADCT, 75.28%, 85.06%, and 81.73% in EASI, 66.67%, 75%, and 75% in PP‐NRS, respectively, and percent reduction of total ADCT correlated with that of EASI and PP‐NRS except for no correlations with that of EASI at month 1. The percent reduction of ADCT no.4 was the highest among the 6 items. Conclusions. These results suggest that changes in ADCT reflect the therapeutic effects of upadacitinib and that ADCT can be a treatment target for upadacitinib therapy. Upadacitinib might preferentially improve sleep disturbance.
Enhancing Photovoltaic Reliability: A Global and Local Feature Selection Approach with Improved Harris Hawks Optimization for Efficient Hotspot Detection Using Infrared Imaging
Authors: Ali Muhammad Umair , Zafar Amad , Ahmed Waqas , Aslam Muhammad , Kim Seong Han
Published: July 2024

The photovoltaic (PV) systems’ inherent ability to transform solar light directly into electrical energy has contributed to their increasing popularity. However, malfunctions can reduce system dependability. Therefore, rapid hotspot identification is critical for efficient, dependable, and risk‐free PV operation. This work presents a method for determining the most optimal hybrid features using the infrared (IR) images of PV panels for hotspot and fault detection. The information at the global (texture, HoG, and color histograms) and local (local binary pattern, SURF, and KAZE) levels were extracted from the IR images of PV panels using a uniform window size of 8 × 8. A binary improved Harris hawks optimization (b‐IHHO) optimal feature selection strategy was used to get the optimal feature subset for model training using PV IR images. The IR images of PV were acquired to test the presented framework. The findings suggested that the proposed framework can classify the IR images of solar panels with an accuracy of 98.41% with lesser feature vector size into three classes (normal, hotspot, and defective). Furthermore, the findings were also compared with the latest literature. The presented technique plays a vital role in carbon‐free cities and is simple to adopt for PV system inspection.
A Hybrid GARCH and Deep Learning Method for Volatility Prediction
Authors: Araya Hailabe T. , Aduda Jane , Berhane Tesfahun
Published: July 2024

Volatility prediction plays a vital role in financial data. The time series movements of stock prices are commonly characterized as highly nonlinear and volatile. This study is aimed at enhancing the accuracy of return volatility forecasts for stock prices by investigating the prediction of their price volatility through the integration of diverse models. Thus, the study integrated four powerful methods: seasonal autoregressive (AR) integrated moving average (MA), generalized AR conditional heteroskedasticity (ARCH) family models, convolutional neural network (CNN), and bidirectional long short‐term memory (LSTM) network. The hybrid model was developed using the residuals generated by the seasonal AR integrated MA model as input for the generalized ARCH model. Following this, the estimated volatility obtained was utilized as an input feature for both the hybrid CNNs and bidirectional LSTM models. The model’s forecasting performance was assessed using key evaluation metrics, including mean absolute error (MAE) and root mean squared error (RMSE). Compared to other hybrid models, our new proposed hybrid model demonstrates an average reduction in MAE and RMSE of 60.35% and 60.61%, respectively. The experimental results show that the model proposed in this study has good performance and accuracy in predicting the volatility of stock prices. These findings offer valuable insights for financial data analysis and risk management strategies.
Failure Mechanism of Salt Barrier in Saline Soil Subgrade in Cold and Arid Plateau Areas
Authors: Zhang Yurong , Zhang Wen , Fan Yanbin , Liu Shiyi , He Yunxiu , Zou Yi
Published: June 2024

In traffic engineering design in saline soil environments, a salt barrier is usually installed in the embankment to prevent secondary salinization damage on the upper embankment and road surface. However, using this salt barrier method in saline soil subgrade projects in cold and arid highland areas has led to the problem of salt barrier failure, and the failure mechanism remains unclear. The study was performed in the saline soil distribution area in the Qaidam Basin on the northeastern part of the Qinghai–Tibet Plateau. We collected samples from the natural saline soil foundation and the structural layer of the subgrade soil using the method of excavating a road section that had undergone salt barrier failure. Laboratory tests and theoretical calculations were carried out on the particle gradation of the natural saline soils and the structural subgrade soil layers. In addition, their water and salt transport heights and the failure mechanism of the subgrade salt barrier were studied. The results showed that salt chemistry increases the capillary force between the soil grains in highly saline soil environments. This increases the water–salt transport of more than 850.00 mm in saline soils, which is much greater than the capillary water rise in ordinary soils (463.0–650.0 mm). When no water barrier geotextile layer is set in the subgrade structure, there is frequently a high headwater and salt transport in the soil layer of the subgrade structure for a long time. There is continuous vapor and salt transport in the large pores of the coarse‐grained salt barrier. The vibration load of the road surface causes the fine soil particles to migrate downward into the coarse‐grained salt barrier, reducing the thickness of the salt barrier. Under the combined effect of these three effects, the salt barrier of the saline soil subgrade in cold and arid areas fails to resist salt migration, and the subgrade is prone to secondary salinization.