bluuebunny/crossref_metadata_2025 huggingface dataset:
Screening over 100 000 patients in 39 general practices in the Netherlands for anticoagulation underprescription in atrial fibrillation: a descriptive, cross-sectional study
Authors: Voorhout Leonard , Pisters Ron , Geurts Constants H P H , Oostindjer Andrew , van Doorn Sander , Rila Harrie , Fuijkschot Wessel W , Verheugt Freek , Hemels Martin E W
Published: August 2023

Objectives

To investigate the underprescription of oral anticoagulation (OAC) in individual atrial fibrillation (AF) patients in primary care.

Setting

Screening of patient records in 39 participating general practitioners (GPs) across the Netherlands.

Participants

We screened 101 207 patient records identifying 2375 non-valvular AF patients.

Methods

Using electronic patient files, we were able to screen the entire GP population for AF, CHA2DS2-VASc stroke risk scores, and the use of guidelines recommended OAC prescription. In case of a deviation from guidelines recommended OAC prescription, we checked the electronic patient file for any documented reason. Additionally, 6 weeks following the screening, we asked all GPs to provide information on any actions taken for the underprescribed patients.

Results

We found a mean CHA2DS2-VASc score of 3.2. OAC prescription consisted of direct OAC in 1342/1984 (68%) and vitamin K-antagonists in the remainder of patients. OAC underprescription was present in 93/944 (9.9%) females and 101/1374 (9.7%) in males, respectively. In 111/146 (76.0%) of the underprescribed AF patients, no reason to withhold OAC was reported. Reported reasons to withhold OAC were patient refusal (n=10), cardiologist advice (n=7) and high risk of bleeding (n=7). Data regarding actions following the identification of OAC underprescription were available for 92/194 (47%) of the OAC underprescribed cases. After consultation OAC was initiated in 9/92 (10%) only.

Conclusions

In this large Dutch study among GPs, we observed 9.8% underprescription of OAC in AF patients. In 76% of the AF patients lacking a prescription for OAC, no documentation for deviating from the guidelines was found. Only in a minority of cases detection of OAC underprescription lead to OAC initiation.
Cancer risk factors and access to cancer prevention services for people experiencing homelessness: a scoping review protocol
Authors: Schiffler Tobias , Jeleff Maren , Gil-Salmerón Alejandro , Yang Lin , Haider Sandra , Schuch Felipe B , Grabovac Igor
Published: August 2023

Introduction

Homelessness is a complex social issue that significantly impairs the health of those affected. People experiencing homelessness (PEH) have a higher prevalence of adverse health outcomes, including premature mortality, compared with the general population, with cancer being the second-leading cause of death. The objective of this scoping review is to map the evidence to assess the exposure of PEH to known cancer risk factors and identify barriers and facilitators PEH experience in accessing cancer prevention services.

Methods and analysis

This scoping review will be conducted in line with the Joanna Briggs Institute guidelines for scoping reviews. For a time window from the date of database establishment until 20 February 2023, the research team will create a detailed search strategy and apply it to the following databases: CINAHL, Embase, Global Index Medicus, PubMed, Scopus and Web of Science. In addition, we will search OpenGrey and Google for grey literature and contact non-governmental organisations to request relevant reports. In the first stage, eligibility criteria will be assessed through a blinded title/abstract assessment, and following this assessment, a full-text screening will be performed. Subsequently, the research team will perform the data extraction and synthesise all relevant information in relation to the scoping review question.

Ethics and dissemination

As this protocol does not involve gathering primary data, ethical approval is not necessary. The results of this review will be published in a peer-reviewed journal and on institutional websites.
Implementation of a palliative care consultation trigger tool for hospitalised patients with acute decompensated heart failure
Authors: Bhattacharya Adhiraj , Chakrabarty Satyaki , Cabrales Jose , VanHorn Alixis , Lemoine Jaclyn , Tsao Lana , Jaber Bertrand L
Published: August 2023

Heart failure is a leading cause of hospitalisations. Integration of palliative care services with medical therapy in the management of hospitalised patients with heart failure is imperative. Unfortunately, there are no standardised criteria for palliative care referrals among hospitalised patients with acute decompensated heart failure. The objective of our quality improvement project was to develop and implement a palliative care consult trigger tool for hospitalised patients with acute decompensated heart failure. We found that among eligible patients, palliative care referrals were underused, likely contributing to misalignment of goals of care and suboptimal advance care planning. We developed a trigger tool and designed and implemented structured multicomponent educational interventions to improve the appropriateness and timeliness of inpatient palliative care consultations in this high-risk population. The educational interventions led to a significant increase in the rate of appropriate inpatient palliative care consultations among hospitalised patients with acute decompensated heart failure (46.3% vs 27.7%; p=0.02). In addition, palliative care referrals resulted in better alignment of goals of care at the time of hospital discharge, as measured by a significant increase in the completion rate of a healthcare proxy form (11.4% vs 47.2%; p<0.001) and a Medical Order for Life-Sustaining Treatment form (2.0% vs 24.1%; p<0.001), as well as the establishment of a Do-Not-Resuscitate order (2.7% vs 29.6%; p<0.001). Furthermore, the intervention resulted in a significant decrease in the hospital readmission rate up to 90 days post-discharge (43.6% vs 8.3%; p<0.001). This quality improvement project calls for the development and adoption of standardised criteria for palliative care referrals to benefit hospitalised patients with heart failure and reduce symptom burden, align goals of care and improve quality of life.
Optimal length of oral anticoagulant treatment for maximum benefit within 5 years after discontinuation of oral anticoagulants in patients with acute pulmonary embolism who require secondary thromboprophylaxis
Authors: Zhao Yunfeng , Luo Yong , Cheng Yi , Wang Hongwei , Du He , Sun Jinyuan , Xu Mei , Xiong Wei
Published: August 2023

Background

Extended oral anticoagulant (OA) use is recommended in patients with acute pulmonary embolism (PE) who require secondary thromboprophylaxis. Nevertheless, the optimal length of OA use for the maximum long-term benefit in this patient population has been undefined to date.

Methods

A retrospective study was performed to explore the role of different length of overall OA use (group 1 (≥1 year of OA use and <2 years of OA use), group 2 (≥2 years of OA use and <3 years of OA use), group 3 (≥ 3 years of OA use)) in outcomes within 5 years after OA discontinuation in patients with acute PE, who required secondary thromboprophylaxis. The primary outcome was mortality rates. The secondary outcomes comprised venous thromboembolism (VTE) recurrence, major bleeding during OA use and net clinical benefit. Net clinical benefit was defined as the composite of recurrent VTE and major bleeding.

Results

For a total of 385 patients in group 1 (n=220), group 2 (n=110) and group 3 (n=55), the PE-related mortality in group 1 was higher than that in group 2 (p=0.034) and 3 (p=0.040), respectively, whereas were similar between groups 2 and 3 (p=1.000). The net clinical benefit in group 1 was less than that in group 2 (p=0.024), whereas similar with that in group 3 (p=0.526). The net clinical benefit was comparable between groups 2 and 3 (p=0.716). The length of OA use was positively associated with major bleeding (HR, 2.510 (0.293 to 3.485), p=0.001), whereas negatively associated with PE-related mortality (HR, 0.668 (0.196 to 2.832), p=0.025) and VTE recurrence (HR, 0.694 (0.174 to 2.300), p=0.036), respectively. The sensitivity and specificity of the length of OA use for the tendency of PE-related mortality was 70.2% and 46.2%, respectively. The area under the curve (AUC) was 0.654 (0.514 to 0.793) (p=0.029). The sensitivity and specificity of the length of OA use for the tendency of net clinical benefit was 86.8% and 64.3%, respectively. The AUC was 0.628 (0.565 to 0.690) (p<0.001)

Conclusions

For patients with acute PE who require secondary thromboprophylaxis, 2 to 3 years (30 months preferred) of overall OA use after a diagnosis of acute PE could be an optimal length to achieve maximum benefit within 5 years after OA discontinuation.
Alcohol-associated bowel disease: new insights into pathogenesis
Authors: Maccioni Luca , Fu Yaojie , Horsmans Yves , Leclercq Isabelle , Stärkel Peter , Kunos George , Gao Bin
Published: August 2023

Excessive alcohol drinking can cause pathological changes including carcinogenesis in the digestive tract from mouth to large intestine, but the underlying mechanisms are not fully understood. In this review, we discuss the effects of alcohol on small and large intestinal functions, such as leaky gut, dysbiosis and alterations of intestinal epithelium and gut immune dysfunctions, commonly referred to as alcohol-associated bowel disease (ABD). To date, detailed mechanistic insights into ABD are lacking. Accumulating evidence suggests a pathogenic role of ethanol metabolism in dysfunctions of the intestinal tract. Ethanol metabolism generates acetaldehyde and acetate, which could potentially promote functional disruptions of microbial and host components of the intestinal barrier along the gastrointestinal tract. The potential involvement of acetaldehyde and acetate in the pathogenesis of the underlying ABD, including cancer, is discussed. We also highlight some gaps in knowledge existing in the field of ABD. Finally, we discuss future directions in exploring the role of acetaldehyde and acetate generated during chronic alcohol intake in various pathologies affecting different sites of the intestinal tract.
Tislelizumab plus chemotherapy for patients withEGFR-mutated non-squamous non-small cell lung cancer who progressed on EGFR tyrosine kinase inhibitor therapy
Authors: Zhong Hua , Zhang Xueyan , Tian Panwen , Chu Tianqing , Guo Qisen , Yu Xinmin , Yu Zhuang , Li Yalun , Chen Lijuan , Liu Jie , Zhang Yan , Guan Yan , Shi Xun , Wang Jing , Zhao Yanqiu , Han Baohui
Published: August 2023

Background

Treatment options are limited for epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) after treatment failure with EGFR tyrosine kinase inhibitors (TKIs). This multicenter open-label, phase II study aims to evaluate the efficacy and safety of tislelizumab plus chemotherapy (cohort 1, TIS+chemo) or tislelizumab plus chemotherapy and bevacizumab (cohort 2, TIS+chemo+ beva) in EGFR-mutated non-squamous NSCLC patients who progressed on EGFR TKI therapies. Here, the primary analysis of the TIS+chemo cohort is reported.

Methods

In the TIS+chemo cohort, patients with EGFR-sensitizing mutations with prior EGFR TKI failure received tislelizumab plus carboplatin and nab-paclitaxel as induction treatment, followed by maintenance with tislelizumab plus pemetrexed. The primary endpoint was 1-year progression-free survival (PFS) rate. The planned sample size was 66 with a historical control of 7%, an expected value of 20%, a one-sided α of 0.05, and a power of 85%.

Results

Between July 11, 2020 and December 13, 2021, 69 patients were enrolled. As of June 30, 2022, the median follow-up was 8.2 months. Among the 62 patients in the efficacy analysis set, estimated 1-year PFS rate was 23.8% (90% CI 13.1% to 36.2%), and its lower bound of 90% CI was higher than the historical control of chemotherapy (7%), which met the primary endpoint. The median PFS was 7.6 (95% CI 6.4 to 9.8) months. Median overall survival (OS) was not reached (95% CI 14.0 to not estimable), with a 1-year OS rate of 74.5% (95% CI 56.5% to 86.0%). The objective response rate and disease control rate were 56.5% (95% CI 43.3% to 69.0%) and 87.1% (95% CI 76.1% to 94.3%), respectively. Patients who had progressed on first-generation/second-generation and third-generation EGFR-TKIs at baseline had shorter PFS than those who progressed on first-generation/second-generation EGFR-TKIs (median 7.5 vs 9.8 months, p=0.031). Patients with positive ctDNA had shorter PFS (median 7.4 vs 12.3 months, p=0.031) than those with negative ctDNA. No grade 5 treatment-emergent adverse events (TEAEs) were observed. Grades 3–4 TEAEs occurred in 40.6% (28/69) of patients. Grades 3–4 immune-related AEs occurred in 5 (7.2%) patients.

Conclusion

The study met the primary endpoint for the TIS+chemo cohort. Tislelizumab plus chemotherapy is effective with an acceptable safety profile forEGFR-mutated non-squamous NSCLC after EGFR TKI failure.
Low molecular weight heparin synergistically enhances the efficacy of adoptive and anti-PD-1-based immunotherapy by increasing lymphocyte infiltration in colorectal cancer
Authors: Quan Yibo , He Jie , Zou Qi , Zhang Liuxi , Sun Qihui , Huang Hongli , Li Wanglin , Xie Keping , Wei Fang
Published: August 2023

Background

Immunotherapy, including adoptive cell therapy (ACT) and immune checkpoint inhibitors (ICIs), has a limited effect in most patients with colorectal cancer (CRC), and the efficacy is further limited in patients with liver metastasis. Lack of antitumor lymphocyte infiltration could be a major cause, and there remains an urgent need for more potent and safer therapies for CRC.

Methods

In this study, the antitumoral synergism of low molecular weight heparin (LMWH) combined with immunotherapy in the microsatellite stable (MSS) highly aggressive murine model of CRC was fully evaluated.

Results

Dual LMWH and ACT objectively mediated the stagnation of tumor growth and inhibition of liver metastasis, neither LMWH nor ACT alone had any antitumoral activity on them. The combination of LMWH and ACT obviously increased the infiltration of intratumor CD8+T cells, as revealed by multiplex immunohistochemistry, purified CD8+T-cell transfer assay, and IVIM in vivo imaging. Mechanistically, evaluation of changes in the tumor microenvironment revealed that LMWH improved tumor vascular normalization and facilitated the trafficking of activated CD8+T cells into tumors. Similarly, LMWH combined with anti-programmed cell death protein 1 (PD-1) therapy provided superior antitumor activity as compared with the single PD-1 blockade in murine CT26 tumor models.

Conclusions

LMWH could enhance ACT and ICIs-based immunotherapy by increasing lymphocyte infiltration into tumors, especially cytotoxic CD8+T cells. These results indicate that combining LMWH with an immunotherapy strategy presents a promising and safe approach for CRC treatment, especially in MSS tumors.
Depicting the landscape of gut microbial-metabolic interaction and microbial-host immune heterogeneity in deficient and proficient DNA mismatch repair colorectal cancers
Authors: Li Jinming , Guo Yangyang , Liu Jianqiang , Guo Fanying , Du Lutao , Yang Yongzhi , Li Xinxiang , Ma Yanlei
Published: August 2023

Background

Accumulating evidence has indicated the role of gut microbiota in remodeling host immune signatures, but various interplays underlying colorectal cancers (CRC) with deficient DNA mismatch repair (dMMR) and proficient DNA mismatch repair (pMMR) remain poorly understood. This study aims to decipher the gut microbiome-host immune interactions between dMMR and pMMR CRC.

Method

We performed metagenomic sequencing and metabolomic analysis of fecal samples from a cohort encompassing 455 participants, including 21 dMMR CRC, 207 pMMR CRC, and 227 healthy controls. Among them, 50 tumor samples collected from 5 dMMR CRC and 45 pMMR CRC were conducted bulk RNA sequencing.

Results

Pronounced microbiota and metabolic heterogeneity were identified with 211 dMMR-enriched species, such asFusobacterium nucleatumandAkkermansia muciniphila, 2 dMMR-depleted species, such asFlavonifractor plautii, 13 dMMR-enriched metabolites, such as retinoic acid, and 77 dMMR-depleted metabolites, such as lactic acid, succinic acid, and 2,3-dihydroxyvaleric acid.F. plautiiwas enriched in pMMR CRC and it was positively associated with fatty acid degradation, which might account for the accumulation of dMMR-depleted metabolites classified as short chain organic acid (lactic acid, succinic acid, and 2,3-dihydroxyvaleric acid) in pMMR CRC. The microbial-metabolic association analysis revealed the characterization of pMMR CRC as the accumulation of lactate induced by the depletion of specific gut microbiota which was negatively associated with antitumor immune, whereas the nucleotide metabolism and peptide degradation mediated by dMMR-enriched species characterized dMMR CRC. MMR-specific metabolic landscapes were related to distinctive immune features, such as CD8+T cells, dendritic cells and M2-like macrophages.

Conclusions

Our mutiomics results delineate a heterogeneous landscape of microbiome-host immune interactions within dMMR and pMMR CRC from aspects of bacterial communities, metabolic features, and correlation with immunocyte compartment, which infers the underlying mechanism of heterogeneous immune responses.
Serratus plane block versus standard of care for pain control after totally endoscopic aortic valve replacement: a double-blind, randomized controlled, superiority trial
Authors: Vandenbrande Jeroen , Jamaer Bob , Stessel Björn , van Hilst Eline , Callebaut Ina , Yilmaz Alaaddin , Packlé Loren , Sermeus Luc , Blanco Rafael , Jalil Hassanin
Published: August 2023

Introduction

Serratus anterior plane block has been proposed to reduce opioid requirements after minimally invasive cardiac surgery, but high-quality evidence is lacking.

Methods

This prospective, double-blinded, randomized controlled trial recruited patients undergoing totally endoscopic aortic valve replacement. Patients in the intervention arm received a single-injection serratus anterior plane block on arrival to the intensive care unit added to standard of care. Patients in the control group received routine standard of care, including patient-controlled intravenous analgesia. Primary outcome was piritramide consumption within the first 24 hours after serratus anterior plane block placement. We hypothesized that compared with no block, patients in the intervention arm would consume 25% less opioids.

Results

Seventy-five patients were analyzed (n=38 in intervention arm, n=37 in control arm). When comparing the serratus anterior plane group with the control group, median 24-hour cumulative opioid use was 9 (IQR 6–19.5) vs 15 (IQR 11.3–23.3) morphine milligram equivalents, respectively (p<0.01). Also, pain scores at 4, 8 and 24 hours were lower in the intervention arm at 4, 8 and 24 hours, respectively.

Conclusion

Combined deep and superficial single-injection serratus anterior plane block is superior to standard of care in reducing opioid requirements and postoperative pain intensity up to 24 hours after totally endoscopic aortic valve replacement.

Trial registration number

NCT04699422.
Physical properties of a quintessence anisotropic stellar model in f(Q) gravity and the mass–radius relation
Authors: Bhar Piyali
Published: August 2023

In this article, we present a new family of solutions to the Einstein field equations of an uncharged spherically symmetric anisotropic matter distribution in the context of f(Q) gravity by choosing $$f(Q)=Q+aQ^2$$

f

(
Q
)

=
Q
+
a

Q
2

, a being the coupling constant. Along with the fundamental quintessence dark energy defined by the equation of state parameter $$-1<\omega _q<-\frac{1}{3}$$

-
1
<

ω
q

<
-

1
3

, we have generated the field equations in modified gravity. Using the linear relationship between radial pressure and energy density along with the Krori–Barua (KB) metric potential, we are able to solve the field equations. Next, we discuss the smooth matching between the exterior Schwarzschild spacetime and the interior spherically symmetric spacetime. We have presented a thorough physical analysis of several factors analytically and graphically to show the physical viability of our suggested model. For the compact star SAXJ 1808.4-3658, our entire graphical analysis was carried out in the context of our solutions for various values of the coupling constant connection to the f(Q) gravity. The influence of coupling constant “a” on different model parameters has been numerically determined and is presented in tabular form. We checked the radial and tangential sound speeds, the stability factor, the adiabatic index, etc. to determine whether our model was stable. It is evident from our analysis that the model is potentially stable when coupling constant $$a \in [0,\,5]$$

a
∈
[
0
,

5
]

. The maximum allowable mass and radius from our present model have been obtained through the mass–radius ($$M-R$$

M
-
R

) plot for different values of a.
Neutrino oscillations in the interaction picture
Authors: Blasone Massimo , Giacosa Francesco , Smaldone Luca , Torrieri Giorgio
Published: August 2023

We study the mixing of different kind of fields (scalar in 0+1D, scalar in 3+1D, fermion in 3+1D) treating the mixing term as an interaction. To this aim, we employ the usual perturbative series in the interaction picture. We find that expression for flavor changing probability exhibits corrections with respect to the usual quantum mechanical (e.g. neutrino) oscillation formula, in agreement with the result previously obtained in the non-perturbative flavor Fock space approach.
A short proof of the Baker–Pixley theorem for classes
Authors: Campercholi Miguel , Vaggione Diego
Published: August 2023

An important theorem by Baker and Pixley states that if [Formula: see text] is a finite algebra with a [Formula: see text]-ary near-unanimity term and [Formula: see text] is any function, then f is a term-function of [Formula: see text] if f preserves all subuniverses of [Formula: see text]. This result was generalized recently for (classes of) not necessarily finite algebras using sheaf-theoretic tools. In this work, we give a short model-theoretic proof of this generalization. Also, we apply the theorem to obtain a characterization of dual discriminator varieties, and to give necessary and sufficient conditions for a variety with a near-unanimity term to be congruence permutable.
On matrix-valued Gabor frames over locally compact abelian groups
Authors: Sinha Uttam Kumar , Vashisht Lalit Kumar , Das Pankaj Kumar
Published: August 2023

In this paper, we study Gabor frames in the matrix-valued signal space [Formula: see text], where [Formula: see text] is a locally compact abelian group which is metrizable and [Formula: see text]-compact, and [Formula: see text] is a positive integer. First, we give sufficient conditions on scalars in an infinite combination of vectors (from a given matrix-valued Gabor frame) to constitute a new frame for the space [Formula: see text]. This generalizes a result due to Aldroubi. Second, we discuss frame conditions for finite sums of matrix-valued Gabor frames. Sufficient conditions for finite sums of matrix-valued Gabor frames in terms of frame bounds are established. It is shown that the sum of images of matrix-valued Gabor frames under bounded linear operators acting on [Formula: see text] constitute a frame for the space [Formula: see text] provided operators are adjointable with respect to the matrix-valued inner product and satisfy a majorization. Finally, we show that matrix-valued Gabor frames are stable under small perturbations.
Error analysis of deep Ritz methods for elliptic equations
Authors: Jiao Yuling , Lai Yanming , Lo Yisu , Wang Yang , Yang Yunfei
Published: August 2023

Using deep neural networks to solve partial differential equations (PDEs) has attracted a lot of attention recently. However, why the deep learning method works is falling far behind its empirical success. In this paper, we provide a rigorous numerical analysis on the deep Ritz method (DRM) for second-order elliptic equations with Dirichlet, Neumann and Robin boundary conditions, respectively. We establish the first nonasymptotic convergence rate in [Formula: see text] norm for DRM using deep neural networks with smooth activation functions including logistic and hyperbolic tangent functions. Our results show how to set the hyper-parameter of depth and width to achieve the desired convergence rate in terms of the number of training samples.
On linear higher-order parabolic equations in Morrey spaces
Authors: Cholewa Jan W. , Rodríguez-Bernal Aníbal
Published: August 2023

In this paper, linear higher-order parabolic equation is shown to define a semigroup in Morrey spaces. For higher-order diffusion equation, the associated semigroup is proved analytic and sharp semigroup estimates in Morrey scale are derived. The analysis also includes semigroups in Morrey scale related to solving linear higher-order fractional diffusion equations.
Circle-Inspired Sine Cosine Optimization-Enabled CRF-RNN and ZFNet for Brain Tumor Segmentation and Classification Using MRI Images
Authors: Ulaganathan Sakthi , Chen Thomas M. , Sathiyanarayanan Mithileysh
Published: August 2023

The segmentation and classification of brain tumor are a attractive regions, which distinguish tumor as well as nontumor cells for identifying a level of tumor. Segmentation and classification from MRI images is a great challenge due to their altering image sizes and vast databases. Various schemes are designed for the segmentation and classification of the brain tumor, but these methods failed to offer better classification accuracy and decision-making. Here, Circle-inspired sine cosine Optimization_conditional random field-recurrent neural network (CISCO-CRF-RNN) and CISCO-Zeiler and Fergus network (CISCO-ZFNet) are introduced for brain tumor segmentation and classification. A pre-processing phase in this research is executed by the median filter to eliminate noises from an image. The segmentation is done by CRF-RNN, which is trained by CISCO. Furthermore, CISCO is newly introduced by incorporation of Circle-Inspired Optimization Algorithm (CIOA) and Sine Cosine Algorithm (SCA). Thereafter, image augmentation is performed utilizing some image augmentation techniques, and thereafter, features namely statistical features, Convolutional Neural Network (CNN) features, haralick features, pyramid histogram of orientation gradients (PHoG), and Local Vector Pattern (LVP) are extracted. Finally, the classification of brain tumor is accomplished utilizing ZFNet, which is tuned using CISCO. In addition, CISCO-CRF-RNN obtained maximal segmentation accuracy of 90.6% whereas CISCO-ZFNet achieved maximum pixel accuracy, negative predictive value (NPV), positive predictive value (PPV), and True positive rate TPR of 92.5%, 89.2%, 90.1% and 93% as well as minimum FNR of 15%.
On μF-contraction: New types of fixed points and common fixed points in Banach spaces
Authors: Jaid Amine , Touail Youssef , El Moutawakil Driss
Published: August 2023

In this work, we define a new notion of [Formula: see text]-contraction in Banach spaces, by modeling with measure of non-compactness the well-known concept of [Formula: see text]-contraction given by Wardowski in metric spaces. We prove a fixed-point theorem and a common fixed-point theorem for our contraction. Our results extend the well-known Darbo contraction principle and large contractions in the literature. Furthermore, the paper contains examples and applications that show the validity of our results.
Baire one path systems, Baire∗ one path systems and path derivatives
Authors: Alikhani-Koopaei Aliasghar
Published: August 2023

In this paper, we study the class of Baire one path systems as a metric space and as a multifunction and show that some known classes of path systems such as continuous path systems, composite continuous path systems, and first return path systems are subclasses of the class of Baire one path systems. In particular, we show that a path system is composite continuous if and only if it is Baire[Formula: see text] one path system. We also show that for a composite continuous path system [Formula: see text], the upper (respectively, lower) extreme path derivatives [Formula: see text] (respectively, [Formula: see text]) of a function [Formula: see text] are upper (respectively, lower) Baire two functions, and when [Formula: see text] is [Formula: see text]-differentiable, [Formula: see text].
The Challenge of Engaging Communities on Hidden Risks: Co-developing a Framework for Adaptive Participatory Storytelling Approaches (APSA)
Authors: Roberts Liz , Liguori Antonia , McEwen Lindsey , Wilson Mike
Published: August 2023

The transdisciplinary Drought Risk and You (DRY) project aimed to interweave storytelling and science as a way of increasing the different voices and types of knowledge (specialist, local) within drought risk decision-making in the UK. This paper critically reflects on our emergent process of drawing across different methodologies to create Adaptive Participatory Storytelling Approaches (APSA). APSA enable more tailoring to people and setting than existing methods, recognizing the specificity of local risk contexts and communities, and in terms of social dynamics, cultural values and local knowledge. APSA are situated, storytelling methodologies applied in the social sciences and arts/humanities, giving strong attention to meaningful participation and sustainable coproduction in both process and outputs. The paper offers other researchers and practitioners insights into working with APSA as a suite of creative storytelling options prioritizing methodological principles of active listening and adapting. APSA require creative thinking along multiple spectra, including how to balance different axes in APSA including: topic (drought risk)-focused with topic (drought risk)-peripheral or oblique, participant-led with researcher-led, and visualization-led with audio-led. We reflect on the challenges, opportunities and values of co-working with APSA, and offer a flexible framework for its application and iterative evaluation embedded through the process. We propose this as a starting point for other transdisciplinary projects to tackle themes that prove difficult for communities to connect with during community-engaged research, in this case, hidden risks like drought and climate change. This is timely given the power and mounting popularity of storytelling for behavior change, research insight and policy, and the need to capture and share different knowledges for climate resilience.
The Future of Volunteering in Extreme Weather Events: Critical Reflections on Key Challenges and Opportunities for Climate Resilience
Authors: Forrest Steven , Dostál Jakub , McEwen Lindsey
Published: August 2023

Volunteers are playing a significant role in interacting with ongoing societal shocks and stresses, such as mobilizing resources and supporting responses to extreme weather events. Their actions contribute to the pursuit of local climate resilience by shaping the local level and influencing socio-ecological systems. Therefore, academics, communities, practitioners and policymakers responsible for understanding, encouraging, developing and sustaining volunteering activity can benefit from critical reflections on volunteering in extreme weather events in order to support ongoing research initiatives, future research and policy agendas, and the development of funding strategies and public programs for climate resilience. This Policy Forum paper critically reflects on the current status of volunteering for extreme weather events and local climate resilience, using experiences from flood risk management, to identify key challenges and opportunities for the future. It builds on the ESRC CASCADE-NET project in discussing both academic puzzles and practical challenges faced in volunteering for local climate resilience in an attempt to bridge gaps and foster further debates between theory and practice. These insights are drawn from a series of dialogic exchanges that reflect the authors’ diverse perspectives and lived experiences of volunteering that emerge in their research and practice in England, the Czech Republic, and The Netherlands. We identify and share ten urgent challenges, followed by discussion of four cross-cutting themes that exist: volunteers as a renewable energy source, stakeholder narratives of volunteering, learning from other contexts, and transformative resilience. In exploring the futures of volunteering, this Policy Forum challenges existing thought by proposing the need to move beyond traditional narratives of “the volunteer” and “volunteering” to a more inclusive and nuanced understanding. Through this, we believe that volunteering can play an essential role in pursuing a just transition, with volunteers being able to challenge the status quo to contribute to transformative climate resilience practice and policy.
Frozen-Thawed Embryo Transfer Using Autologous Oocytes Retrieved from Women Aged ≥45 Years: A Retrospective Study
Authors: Suzuki Yosuke , Matsubayashi Hidehiko , Ohara Yasuhiro , Yamaguchi Kohei , Doshida Masakazu , Takeuchi Takumi , Ishikawa Tomomoto
Published: August 2023

Objective: To assess the pregnancy outcomes, including live birth rate and pregnancy loss for women aged 45–49 years at the time of oocyte retrieval, who underwent frozen autologous transfer of embryos.

Methods: Among frozen-thawed embryo transfers (ET) performed at our clinic from September 2013 to March 2021, 1,114 cycles of women aged 45–49 years at the time of oocyte retrieval were examined retrospectively. Positive pregnancy test, clinical pregnancy, pregnancy loss, and live birth rates per transfer among each age group were analyzed using one-way analysis of variance or the Fisher’s exact test.

Results: The mean age at the time of oocyte retrieval and ET was 45.8 and 46.5 years, respectively. Positive pregnancy test rate was 7.6%, of which 72.9% resulted in pregnancy loss. The clinical pregnancy and live birth rates were 5.1% and 2.0%, respectively, with a live birth rate of 3.0% for women with oocytes retrieved at 45 years of age. Multivariate analysis revealed that younger oocyte retrieval age was associated with biochemical and clinical pregnancy; however, no such association was observed for cases with live birth. The oocyte retrieval age of patients with live births was 45 years in 16 cases, 46 years in six cases, and 47 years in one case. In one case of live birth (46 years old), 21 trisomy was observed in the child; however, congenital abnormalities were not observed in other cases. Chorionic tests were performed on the fetuses in 12 of the 33 clinical abortions, of which 11 showed chromosomal abnormalities.

Conclusions: Fertility treatment with autologous oocytes in advanced-age women has a low success rate. Although prognosis is poor above 45 years of age, these results can help in providing information to aid patients in their decisions regarding whether or not to pursue treatment.
Disentangling Content Information by Combining ASR and TTS Bottleneck Features for Voice Conversion
Authors: Zhao Zeqing , Ma Sifan , Jia Yan , Hou Jingyu , Yang Lin , Wang Junjie
Published: August 2023

With the development of deep learning, nonparallel voice conversion (VC) has achieved a significant progress recently. Automatic speech recognition (ASR) and text-to-speech (TTS) for leveraging knowledge are the two mainstream methods in VC research. In this paper, we demonstrate that the two bottleneck features (BNFs) in the above methods are complementary. ASR-BNFs are more robust especially in any-to-many tasks, but suffer from leakage of source speaker’s timbre information; TTS-BNFs are less likely to reveal speaker’s timbre information, but lack robustness. Therefore, a nonparallel any-to-many voice conversion model is proposed by combining ASR-BNFs and TTS-BNFs. The whole modules in the proposed model can be trained jointly without any pre-trained models. Experiments are conducted on a private multi-speaker TTS dataset. It is demonstrated that the proposed model achieves the best balance in speech quality, timbre similarity and robustness compared to baseline models.
On Computing the Time-varying Distance between Moving Bodies
Authors: Schoemans Maxime , Sakr Mahmoud , Zimányi Esteban
Published: August 2023

A moving body is a geometry that may translate and rotate over time. Computing the time-varying distance between moving bodies and surrounding static and moving objects is crucial to many application domains including safety at sea, logistics robots, and autonomous vehicles. Not only is it a relevant analytical operation in itself, but also it forms the basis of other operations, such as finding the nearest approach distance between two moving objects. Most moving objects databases represent moving objects using a point representation, and the computed temporal distance is thus inaccurate when working with large moving objects. This article presents an efficient algorithm to compute the temporal distance between a moving body and other static or moving geometries. We extend the idea of the V-Clip and Lin-Canney closest features algorithms of computational geometry to track the temporal evolution of the closest pair of features between two objects during their movement. We also present a working implementation of this algorithm in an open-source moving objects database and show, using a real-world example on AIS data, that this distance operator for moving bodies is only about 1.5 times as slow as the one for moving points while providing significant improvements in correctness and accuracy of the results.
Towards Causal Analysis of Empirical Software Engineering Data: The Impact of Programming Languages on Coding Competitions
Authors: Furia Carlo A. , Torkar Richard , Feldt Robert
Published: August 2023

There is abundant observational data in the software engineering domain, whereas running large-scale controlled experiments is often practically impossible. Thus, most empirical studies can only report statistical
correlations
—instead of potentially more insightful and robust
causal
relations.

To support analyzing purely observational data for causal relations and to assess any differences between purely predictive and causal models of the same data, this article discusses some novel techniques based on structural causal models (such as directed acyclic graphs of causal Bayesian networks). Using these techniques, one can rigorously express, and partially validate, causal hypotheses and then use the causal information to guide the construction of a statistical model that captures genuine causal relations—such that correlation
does imply
causation.

We apply these ideas to analyzing public data about programmer performance in Code Jam, a large world-wide coding contest organized by Google every year. Specifically, we look at the impact of different programming languages on a participant’s performance in the contest. While the overall effect associated with programming languages is weak compared to other variables—regardless of whether we consider correlational or causal links—we found considerable differences between a purely associational and a causal analysis of the very same data.

The takeaway message is that even an imperfect causal analysis of observational data can help answer the salient research questions more precisely and more robustly than with just purely predictive techniques—where genuine causal effects may be confounded.
Adaptive Neighbor Graph Aggregated Graph Attention Network for Heterogeneous Graph Embedding
Authors: Kaibiao Lin , Chen Jinpo , Ruicong Chen , Fan Yang , Yang Zhang , Min Lin , Ping Lu
Published: August 2023

Graph attention network can generate effective feature embedding by specifying different weights to different nodes. The key of the research on heterogeneous graph embedding is the way to combine its rich structural information with semantic relations to aggregate the neighborhood information. Most of the existing heterogeneous graph representation learning methods guide the selection of neighbors by defining various meta-paths on heterogeneous graphs. However, these models only consider the information contained in the nodes under different paths and ignore the potential semantic relationships of nodes in different neighbor graph structures, which leads to the underutilization of graph structure information. In this article, we propose a novel adaptive framework named Neighbor Graph Aggregated Graph Attention Network (NGGAN) to fully exploit graph topological details in heterogeneous graph, and aggregates their information to obtain an effective embedding. The key idea is to use different levels of sampling methods to define neighborhood, and use neighbor graphs to represent the complex structural interaction between nodes. In this way, the high-order relationship between nodes and the latent semantics of neighbor graphs can be fully explored. Afterward, a hierarchical attention mechanism is applied to adaptively learn the importance of different objects, including node information, path information, and neighbor graph information. Multiple downstream tasks are performed on four real-world heterogeneous graph datasets, and the experimental results demonstrate the effectiveness of NGGAN.
Scraping Relevant Images from Web Pages without Download
Authors: Uzun Erdinç
Published: August 2023

Automatically scraping relevant images from web pages is an error-prone and time-consuming task, leading experts to prefer manually preparing extraction patterns for a website. Existing web scraping tools are built on these patterns. However, this manual approach is laborious and requires specialized knowledge. Automatic extraction approaches, while a potential solution, require large training datasets and numerous features, including width, height, pixels, and file size, that can be difficult and time-consuming to obtain. To address these challenges, we propose a semi-automatic approach that does not require an expert, utilizes small training datasets, and has a low error rate while saving time and storage. Our approach involves clustering web pages from a website and suggesting several pages for a non-expert to annotate relevant images. The approach then uses these annotations to construct a learning model based on textual data from the HTML elements. In the experiments, we used a dataset of 635,015 images from 200 news websites, each containing 100 pages, with 22,632 relevant images. When comparing several machine learning methods for both automatic approaches and our proposed approach, the AdaBoost method yields the best performance results. When using automatic extraction approaches, the best f-Measure that can be achieved is 0.805 with a learning model constructed from a large training dataset consisting of 120 websites (12,000 web pages). In contrast, our approach achieved an average f-Measure of 0.958 for 200 websites with only six web pages annotated per website. This means that a non-expert only needs to examine 1,200 web pages to determine the relevant images for 200 websites. Our approach also saves time and storage space by not requiring the download of images and can be easily integrated into currently available web scraping tools, because it is based on textual data.
Recruitment Promotion via Twitter: A Network-centric Approach of Analyzing Community Engagement Using Social Identity
Authors: Ng Lynnette Hui Xian , Cruickshank Iain J.
Published: August 2023

With the proliferation of online technologies, social media recruitment has become an essential part of any company’s outreach campaign. A social media platform can provide marketing posts with access to a large pool of candidates and at a low cost. It also provides the opportunity to quickly customize and refine messages in response to the reception. With online marketing, the key question is: which communities are attracted by recruitment tweets on social media?

In this work, we profile the Twitter accounts that interact with a set of recruitment tweets by the U.S. Army’s Recruitment Command through a network-centric perspective. By harnessing how users signal their affiliations through user information, we extract and analyze communities of social identities. From Social Identity Theory, these social identities can be critical drivers of behavior, like the decision to enlist in the military. With this framework, we evaluate the effectiveness of the U.S. Army’s recruitment campaign on Twitter, observing that these campaigns typically attract communities with military exposure like veterans or those that identify with professional careers and fitness (e.g., student, professionals, athletes). The campaign also attracts, but at a much lower level, interaction from those in the digital industries—data scientists, cybersecurity professionals, and so forth. When analyzing the accounts in terms of their degree of automation, we find a set of intent-unknown bot accounts interacting with the tweets, and that many of the recruitment accounts are perceived as automated accounts. These observations can aid in campaign refinement: targeting the digital community and getting a broader reach for online recruitment publicity campaigns.
Fatigue Life Evaluation of Wind Turbine Tower Based on Measured Data
Authors: Zhao Yan , Li Xiaolu , Wang Xinwu , Jiang Jianqun , Wang Zhenyu
Published: August 2023

Fatigue life is a crucial design factor which dictates the safe operation of the wind turbines, but it is influenced by uncertain factors such as environmental loads, analytical models, material properties, and manufacturing methods. In this study, a 1.5 MW wind turbine was monitored in operation to understand the fatigue mechanism and enhance wind turbine design. The influence of different operating conditions on fatigue damage was analyzed by correlating strain monitoring data with supervisory control and data acquisition (SCADA) data. Furthermore, a fatigue evaluation method based on measured strain data was proposed. Fatigue damage increases with the increase of wind and rotation speed. More than 50% of the damage occurred at the rated rotation speed state, the corresponding wind speed was greater than the rated wind speed and the pitch control system was active. The findings of this study provide insights for investigating the real fatigue state of similar wind turbine towers and improving the return on investment by closely estimating their service life.
PSI-CA-Based Vehicle Selection Scheme for Data Sharing in Internet of Vehicles
Authors: Jiang Zhengtao , Yu Ting , Chen Ye , Li Huiqiang , Guo Xiaoxuan
Published: August 2023

In recent years, the development of the Internet of Vehicles (IoV) has led to an increase in the demand for data sharing services for the IoV. In the era of big data, safe and convenient data sharing services for IoV are inseparable from the support of reliable data. With the increase in the number of smart cars, how to filter the data provided by vehicles while protecting privacy to improve the quality of data sharing services has attracted the attention of scholars. However, in the existing data sharing scheme for IoV, the vehicles that provide data are selected based on the reputation mechanism or the voting mechanism. Our analysis shows that these two mechanisms lack objectivity and are vulnerable to cooperative attack. Therefore, based on spatiotemporal matching, a new trusted relationship establishment method, this paper proposes an objective and cooperative attack-resistant vehicle selection scheme for data sharing in IoV. Bloom filters and an exponential ElGamal encryption scheme are used to implement private set intersection cardinality (PSI-CA) technology for evaluating spatiotemporal matching level. In this paper, the scheme proposed is of great significance to improve existing vehicle services and improve driving safety.