bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the antecedents of Chinese people’s pro-environmental behavior: the role of self-construal and news attention
Authors: Li Li , Song Cuiyou 
Published: July 2024

Abstract
This study aims to extend the attitude-intention-behavior model by adding news attention and interdependent self-construal as antecedents to understand the pro-environmental behavior of Chinese people. Results of the structural equation modeling (SEM) analysis based on web survey data of 715 Chinese individuals show that interdependent self-construal significantly and positively affected individuals’ attention to environmental news messages on new media platforms. Such news attention then positively affected their attitude toward pro-environmental behavior. In turn, pro-environmental behavioral attitude positively affected their pro-environmental behavioral intention. Finally, individuals’ pro-environmental behavioral intention positively led to their actual pro-environmental behavior. Besides, the results demonstrated that interdependent self-construal also significantly and positively affects individuals’ intention of engaging in pro-environmental behavior, but little evidence was found to support the significant association between interdependent self-construal and pro-environmental attitude. Theoretical and practical implications were discussed.
Assessing the social risks of flooding for coastal societies: a case study for Prince Edward Island, Canada
Authors: Pang Tianze , Shah Mohammad Aminur Rahman , Dau Quan Van , Wang Xiuquan 
Published: July 2024

Abstract
With the worldwide growing threat of flooding, assessing flood risks for human societies and the associated social vulnerability has become a necessary but challenging task. Earlier research indicates that islands usually face heightened flood risks due to higher population density, isolation, and oceanic activities, while there is an existing lack of experience in assessing the island-focused flood risk under complex interactions between geography and socioeconomics. In this context, our study employs high-resolution flood hazard data and the principal component analysis (PCA) method to comprehensively assess the social risk of flood exposure and social vulnerability in Prince Edward Island (PEI), Canada, where limited research has been delivered on flood risk assessments. The findings reveal that exposed populations are closely related to the distribution of flood areas, with increasingly severe impact from current to future climate conditions, especially on the island’s north shore. Exposed buildings exhibit a concentrated distribution at different levels of community centers, with climate change projected to significantly worsen building exposure compared to population, possibly due to the urban agglomeration effect. The most populated cities and towns show the highest social vulnerabilities in PEI, and the results reflect a relatively less complex economic structure of islands. Recommendations for research and management in the coming stage include the necessity of particular climate actions, recognizing community centers as critical sites for flood hazard responses, and incorporating flood hazards into urban planning and management to mitigate the impacts of continuous urbanization on ecosystem services for flood prevention.
Evaluation of SENTINEL-2 products-based algorithms in estimating water pollutants of the River Niger in Bamako
Authors: Coulibaly Nana , Sanogo Souleymane , BA Abdramane 
Published: July 2024

Abstract
Monitoring surface water quality on a spatio-temporal scale is very important to restrict the entry of polluting components into water bodies, particularly rivers. Traditional techniques of assessing water quality are typically costly and time-consuming. With the advent of remote sensing technologies and the availability of high-resolution satellite images in recent years, a significant opportunity for water quality monitoring has arisen. Our study aims to test the use of Sentienl-2 multispectral imaging sensors in estimating three important water quality parameters: chlorophyll-a, Colored Dissolved Organic Matter and Total Suspended Matter in Niger River. Sentinel-2 satellite data were acquired in 2020. Atmospheric correction was performed using Sen2cor from the Sentinel toolbox to obtain a geometrically corrected Sentinel-2 multispectral image. We selected multiple water-body indices from the literature based on their spectral reflection characteristics, analyze correlations between the reflectance values of water body indices and the water quality parameters of synchronous measured sampling points in order to obtain an optimal water body index for estimating water quality parameters (WQP) in Niger River. Five regression functions were used in this study: linear regression, exponential, logarithmic, power and polynomial regression. The performance and accuracy of these regression models were evaluated by correlating spectral reflectance band ratio against the in situ water quality parameters (WQP) concentrations. Polynomial regression gave a higher performance and accuracy based on their R values. The best spectral index was selected to assess the spatio-temporal distribution of water pollutants in the Niger River in Bamako and its surroundings. The results showed that the polynomial regression of 6th degree provided the best fit had the best spectral band ratio and in situ Chl-a, CDOM and TSM concentrations which were respectively achieved with band index of B2/B3 (R2 = 0.78), B3/B6 (R

2
= 0.79) and B3/B4 (R

2
= 0.63). Therefore, the best band ratio was selected to evaluate Chl-a spatio-temporal in Niger River water in Bamako. The results of this study showed seasonal variability of the water pollutants in the Niger River. This highlights the potential of the Sentinel-2 products for water quality analysis. As a conclusion, the Sentinel-2 images could be helpful for precise water quality control of Niger River in Bamako.
TDDAM: transformer based deep domain adaptation methodology for lithium-ion battery prognosis
Authors: Yang Shanzhe , Jia Runda , Ma Xiaoguang , Li Shuai 
Published: July 2024

Abstract
The status of health (SOH) is a vital indicator to characterize the remaining life of lithium-ion batteries (LIBs), and precise prognosis of the SOH is of great importance for battery management systems. In order to prognosis the SOH of LIBs, this paper proposed a Transformer based deep domain adaptation methodology (TDDAM). This paper applies the transformer model, which is widely used in natural language processing and other fields, to the prediction of LIBs. Meanwhile in order to solve the problem of model matching in different types of batteries or different environments, this paper combines domain adaptation method based on the maximum mean discrepancy. Firstly, we extract the data features of LIBs through position encoding and processing of the encoder structure with the multi-head self-attention mechanism as the core. Then, based on the maximum mean discrepancy index, the target domain data and the source domain data features are aligned, and the decoder part of the original transformer model is replaced with a fully connected layer for the prediction of SOH of LIBs in the target domain. This is the first time that a Transformer has been combined with the maximum mean discrepancy to be applied to LIBs prediction. Comprehensive experiments on two CALCE LIBs data showed that the TDDAM achieved smaller prognostic prediction errors over popular SOH diagnostic methods, indicating its great potential as a generic backbone for LIBs prognosis.
Explainable Gaussian processes: a loss landscape perspective
Authors: Niroomand Maximilian P , Dicks Luke , Pyzer-Knapp Edward O , Wales David J 
Published: July 2024

Abstract
Prior beliefs about the latent function to shape inductive biases can be incorporated into a Gaussian process (GP) via the kernel. However, beyond kernel choices, the decision-making process of GP models remains poorly understood. In this work, we contribute an analysis of the loss landscape for GP models using methods from chemical physics. We demonstrate ν-continuity for Matérn kernels and outline aspects of catastrophe theory at critical points in the loss landscape. By directly including ν in the hyperparameter optimisation for Matérn kernels, we find that typical values of ν can be far from optimal in terms of performance. We also provide an a priori method for evaluating the effect of GP ensembles and discuss various voting approaches based on physical properties of the loss landscape. The utility of these approaches is demonstrated for various synthetic and real datasets. Our findings provide insight into hyperparameter optimisation for GPs and offer practical guidance for improving their performance and interpretability in a range of applications.
Metaethics and the Nature of Properties
Authors: Suikkanen Jussi 
Published: July 2024

Abstract
This paper explores the connection between two philosophical debates concerning the nature of properties. The first, metaethical debate is about whether normative properties are ordinary natural properties or some unique kind of non-natural properties. The second, metaphysical debate is about whether properties are sets of objects, transcendent or immanent universals, or sets of tropes. I argue that nominalism, transcendent realism and immanent realism are not neutral frameworks for the metaethical debate but instead lead to either metaethical naturalism or non-naturalism. We can therefore investigate the metaethical question on its own terms only within the framework of trope theory.
The Incidence of Nasal Tip and Upper Lip Malposition in Primary Rhinoplasty
Authors: Swanson Marco , DeLeonibus Anthony , Ku Ying , Guyuron Bahman 
Published: July 2024

Abstract

Background
For an optimal aesthetic plan for correction of nasal tip disharmony, it is crucial to note lip and tip disproportions.

Objectives
In this study we sought to investigate the incidence of preoperative upper lip malposition in primary rhinoplasty patients.

Methods
In total, 150 consecutive primary rhinoplasty patients were included. The position of the upper lip was measured during smiling relative to the incisors and gum line, and categorized as ideal, inadequate incisor show, or excessive gum show. Nasal length was categorized based on soft tissue cephalometic analysis of life-size photographs as long, ideal, or short. Tip projection was categorized as overprojected, ideal, or underprojected. The columella was categorized as hanging, ideal, or retracted.

Results
Standardized photographs of 139 primary rhinoplasty patients met inclusion criteria. Forty-seven (34%) patients had an ideal upper lip position, 83 (61%) inadequate incisor show, and 7 (5%) excessive gum show. Sixteen (12%) had a short nose, 45 (33%) ideal length, and 76 (55%) a long nose. Fourteen (10%) had an underprojected tip, 38 (28%) had an ideal tip projection and 85 (62%) an overprojected tip. None of the nasal parameters were predictive of upper lip position. Tip overprojection (odds ratio [OR] 3.03, P = .02) and hanging columella (OR 2.97, P = .001) were predictive of a long nose. Tip underprojection was predictive of short length (OR 35, P &lt; .0001).

Conclusions
There is a high incidence of upper lip malposition in patients undergoing primary rhinoplasty. It is vital for the rhinoplasty surgeon to identify it preoperatively and plan the surgical maneuvers accordingly to prevent exacerbating an insufficient incisor show or excessive gum show.

Level of Evidence: 4
TemBERTure: advancing protein thermostability prediction with deep learning and attention mechanisms
Authors: Rodella Chiara , Lazaridi Symela , Lemmin Thomas 
Published: July 2024

Abstract

Motivation
Understanding protein thermostability is essential for numerous biotechnological applications, but traditional experimental methods are time-consuming, expensive, and error-prone. Recently, deep learning (DL) techniques from natural language processing (NLP) was extended to the field of biology, since the primary sequence of proteins can be viewed as a string of amino acids that follow a physicochemical grammar.

Results
In this study, we developed TemBERTure, a DL framework that predicts thermostability class and melting temperature from protein sequences. Our findings emphasize the importance of data diversity for training robust models, especially by including sequences from a wider range of organisms. Additionally, we suggest using attention scores from Deep Learning models to gain deeper insights into protein thermostability. Analyzing these scores in conjunction with the 3D protein structure can enhance understanding of the complex interactions among amino acid properties, their positioning, and the surrounding microenvironment. By addressing the limitations of current prediction methods and introducing new exploration avenues, this research paves the way for more accurate and informative protein thermostability predictions, ultimately accelerating advancements in protein engineering.

Availability and implementation
TemBERTure model and the data are available at: https://github.com/ibmm-unibe-ch/TemBERTure.
Spermatogonial stem cell technologies: applications from human medicine to wildlife conservation
Authors: Damyanova Katerina B , Nixon Brett , Johnston Stephen D , Gambini Andrés , Benitez Patricio P , Lord Tessa 
Published: July 2024

Abstract
Spermatogonial stem cell (SSC) technologies that are currently under clinical development to reverse human infertility hold the potential to be adapted and applied for the conservation of endangered and vulnerable wildlife species. The biobanking of testis tissue containing SSCs from wildlife species, aligned with that occurring in pediatric human patients, could facilitate strategies to improve the genetic diversity and fitness of endangered populations. Approaches to utilize these SSCs could include spermatogonial transplantation or testis tissue grafting into a donor animal of the same or a closely related species, or in vitro spermatogenesis paired with assisted reproduction approaches. The primary roadblock to progress in this field is a lack of fundamental knowledge of SSC biology in non-model species. Herein, we review the current understanding of molecular mechanisms controlling SSC function in laboratory rodents and humans, and given our particular interest in the conservation of Australian marsupials, use a subset of these species as a case-study to demonstrate gaps-in-knowledge that are common to wildlife. Additionally, we review progress in the development and application of SSC technologies in fertility clinics and consider the translation potential of these techniques for species conservation pipelines.
Deep learning–based and BI-RADS guided radiomics model for tumour-infiltrating lymphocytes evaluation in breast cancer
Authors: Lu Xiangyu , Jia Yingying , Zhang Hongjuan , Wu Ruichao , Zhao Wuyuan , Yao Zihuan , Nie Fang , Ma Yide 
Published: July 2024

Abstract

Objectives
To investigate an interpretable radiomics model consistent with the clinical decision-making process and realize tumour-infiltrating lymphocytes (TILs) levels prediction in breast cancer (BC) from ultrasound images.

Methods
A total of 378 patients with invasive BC confirmed by pathological results were retrospectively enrolled in this study. Radiomics features were extracted guided by the breast imaging reporting and data system (BI-RADS) lexicon from the regions of interest (ROIs) segmented with deep learning models. After features were selected using the least absolute shrinkage and selection operator regression, 4 machine learning classifiers were used to establish the radiomics signature (Rad-score). Then, the integrated model was developed on the basis of the best Rad-score incorporating the independent clinical factors for TIL level prediction.

Results
Tumours were segmented using the deep learning models with an accuracy of 97.2%, sensitivity of 93.4%, specificity of 98.1%, and the posterior areas were also obtained. Eighteen morphology and texture-related features were extracted from the ROIs and 14 features were selected to construct the Rad-score models. Combined with independent clinical characteristics, the integrated model achieved an area under the curve of 0.889 (95% CI, 0.739-0.990) in the validation cohort, which outperformed the traditional radiomics model and achieved comparable performance with the deep learning models.

Conclusions
This study established a promising model for TIL levels prediction with numerable interpretable features and showed great potential to help decision-making and clinical applications.

Advances in knowledge
Imaging-based biomarkers have provided noninvasive ways for TIL levels evaluation in BC. Our model combining the BI-RADS-guided radiomics features and clinical data outperformed the traditional radiomics approaches and is comparable to deep learning methods.
Spontaneous cortical activity is altered in persons with HIV and related to domain-specific cognitive function
Authors: Petro Nathan M , Rempe Maggie P , Schantell Mikki , Ku Vivian , Srinivas Advika N , O’Neill Jennifer , Kubat Maureen E , Bares Sara H , May-Weeks Pamela E , Wilson Tony W 
Published: July 2024

Abstract
Whilst the average lifespan of persons with HIV now approximates that of the general population, these individuals are at a much higher risk of developing cognitive impairment with ∼35–70% experiencing at least subtle cognitive deficits. Previous works suggest that HIV impacts both low-level primary sensory regions and higher-level association cortices. Notably, multiple neuroHIV studies have reported elevated levels of spontaneous cortical activity during the pre-stimulus baseline period of task-based experiments, but only a few have examined such activity during resting-state conditions. In the current study, we examined such spontaneous cortical activity using magnetoencephalography in 79 persons with HIV and 83 demographically matched seronegative controls and related this neural activity to performance on neuropsychological assessments of cognitive function. Consistent with previous works, persons with HIV exhibited stronger spontaneous gamma activity, particularly in inferior parietal, prefrontal and superior temporal cortices. In addition, serostatus moderated the relationship between spontaneous beta activity and attention, motor and processing speed scores, with controls but not persons with HIV showing stronger beta activity with better performance. The current results suggest that HIV predominantly impacts spontaneous activity in association cortices, consistent with alterations in higher-order brain function, and may be attributable to deficient GABAergic signalling, given its known role in the generation of gamma and beta oscillations. Overall, these effects align with previous studies showing aberrant spontaneous activity in persons with HIV and provide a critical new linkage to domain-specific cognitive dysfunction.
Effect of benralizumab on histopathology and inflammatory signatures in a clinical cohort of eosinophilic esophagitis
Authors: Pyne Ashley L , Uchida Amiko M , Hazel Mark W , Stubben Chris J , Chang Joy W , Bailey Dominique D , Gonsalves Nirmala , Allen-Brady Kristina , Peterson Kathryn A , Pletneva Maria A 
Published: July 2024

Summary
A preliminary report from the recent phase 3 trial of benralizumab, a monoclonal antibody that binds to interleukin-5 receptor alpha (IL5Rα), in patients with EoE revealed that medication use led to tissue eosinophil eradication but did not meet the clinical endpoint of symptom resolution. Here, we characterized the clinical, endoscopic, histologic, and transcriptional changes in patients with active EoE following benralizumab treatment. We retrospectively examined patients with EoE treated with benralizumab at the University of Utah (n = 11) and reviewed reported clinical symptoms, circulating and tissue eosinophilia, and endoscopic and histologic scores. Gene expression profiles from available esophageal tissue from benralizumab-treated patients were compared to those from patients with remission EoE (n = 5), active EoE (n = 10), and controls (n = 22). Benralizumab treatment resulted in partial symptom improvement and significant reduction in tissue eosinophilia, and endoscopic and histologic disease scoring (P &lt; 0.01). Histologic score reductions were driven by eosinophil feature scores, while scores for epithelial features (basal cell hyperplasia and dilated intercellular spaces) were similar to those in active EoE. The gene signatures in benralizumab-treated patients mimicked those of active EoE (e.g. upregulation of POSTN, CDH26, CCL26, and downregulation of DSG1). RNA profiles and pathways support histologic findings of impaired epithelial function that persists despite benralizumab treatment. In conclusion, despite eosinophil eradication, patients treated with benralizumab had persistent epithelial injury at the histologic and transcriptional level. In this cohort, benralizumab therapy failed to eradicate inflammation and epithelial dysfunction showing that interleukin-5 receptor alpha blockade monotherapy is insufficient to control EoE.
A rare case of Lutembacher’s syndrome presenting with low-gradient severe mitral stenosis: case report and literature overview
Authors: El-Mhadi Samah , El Hajjaj Belghait , Laktib Nabil , Oukerraj Latifa , Cherti Mohamed 
Published: July 2024

Abstract

Background
Lutembacher’s syndrome refers to the rare combination of atrial septal defect and mitral stenosis. This condition is still underdiagnosed despite its distinct clinical, paraclinical, and therapeutic implications.

Case summary
We report the case of a 60-year-old woman presenting with acute congestive heart failure. Investigations revealed the combination of low-gradient severe rheumatic mitral stenosis and ostium secundum atrial septal defect. Despite the medical team’s conservative management of her condition and recommendation for surgical intervention, the patient chose to discharge herself against medical advice. She died 6 months later.

Conclusion
Lutembacher’s syndrome continues to be a rare condition in our practice. Once low-gradient severe mitral stenosis is diagnosed, it is essential to search for an associated atrial septal defect, especially when there is an early onset of significant right ventricular enlargement or dysfunction or when an intriguing inconsistency exists between the mitral area and the transmitral gradient.