bluuebunny/crossref_metadata_2025_split huggingface dataset:
White shark optimizer via support vector machine for video-based gender classification system
Authors: Oyediran Mayowa Oyedepo , Ajagbe Sunday Adeola , Ojo Olufemi Samuel , Alshahrani Reem , Awodoye Olufemi O. , Adigun Matthew O. 
Published: January 2025

Abstract
Gender identification from videos is a challenging task with significant real-world applications, such as video content analysis and social behavior research. In this study, we propose a novel approach, the White Shark Optimizer-Support Vector Machine (WSO-SVM), tailored specifically for gender identification from video data. The WSO-SVM integrates the White Shark Optimizer, a bio-inspired optimization algorithm mimicking the hunting behavior of white sharks, with the Support Vector Machine, a powerful machine learning technique for classification. By combining these two methods, we aim to exploit the advantages of both algorithms and enhance gender identification accuracy. To evaluate the performance of the WSO-SVM in gender identification, the work conducted extensive experiments using a diverse dataset of video clips containing individuals of various genders and backgrounds. The work compared the results with conventional SVM-based gender identification and state-of-the-art methods. The findings demonstrate that the WSO-SVM achieves superior accuracy in gender identification compared to traditional SVM-based approaches. The WSO-SVM's ability to efficiently explore the solution space and select optimal SVM parameters contributes to its improved performance. Moreover, the WSO-SVM exhibits robustness in handling variations in lighting conditions, poses, and facial expressions, making it well-suited for real-world video-based gender identification tasks. The outcomes derived from the SVM approach demonstrate that WSO-SVM produced an average FPR of 7.14%, Sensitivity of 93.06%, Specificity of 92.86%, Precision of 91.0%, and overall accuracy of 93.00% in 45.83 s with a recognition time of 45.83 s.
Effects of neighbouring vegetation on planted indigenous tree establishment in modified environments: a New Zealand case study
Authors: Rolando Carol A. , Richardson Brian , Elleouet Joane , Henry John , Paul Thomas , Firm Dejan 
Published: January 2025

Abstract
Large-scale tree planting with indigenous trees is one approach to combatting climate change and environmental degradation. However, a significant challenge with establishing planted indigenous forests at scale, particularly in New Zealand, is that our knowledge and capacity to achieve this in highly modified environments, covered by invasive species, is relatively poor. The purpose of our study was to quantify the survival and growth of five indigenous tree species (three gymnosperms, two angiosperms) planted either on their own (weed-free) or in association with an indigenous (Leptospermum scoparium J.R. Forst) or exotic (Cytisus scoparius (L.) Link) shrub species. We monitored survival and growth following planting for 2.5 years. Results showed that survival for the gymnosperms was > 90% for all treatments. In contrast, survival of the two angiosperms was poor, and, in general, not significantly related to the presence or absence of neighbouring vegetation. The response to vegetation management for tree height was similar across all species: weed-free treatment > L. scoparium treatment > C. scoparius treatment. Diameter growth was also highest for all tree species in the weed-free treatment, compared to the two other vegetation management treatments, but the extent of the increase varied by tree species. We found no direct evidence for neighbouring vegetation facilitating early survival and growth of the five indigenous tree species tested at our study site. However, the outcomes require testing at scale and across environments to underpin future forest restoration efforts.
Improving postsurgical paresis in brain tumor patients by transcranial magnetic stimulation
Authors: Rosenstock Tizian , Picht Thomas , Engelhardt Melina , Grittner Ulrike , Mönch Maximilian , Vajkoczy Peter , Lavrador José Pedro , Mirallave-Pescador Ana , Vergani Francesco , Schwendner Maximilian , Schroeder Axel , Kram Leonie , Zhang Haosu , Prabhu Sujit , Prinsloo Sarah , Meyer Bernhard , Ille Sebastian , Krieg Sandro M. 
Published: January 2025

Abstract

Background and objectives
Recently, reduction of transcallosal inhibition by contralateral navigated repetitive transcranial magnetic stimulation (nrTMS) improved neurorehabilitation of glioma patients with new postoperative paresis. This multicentric study examines the effect of postoperative nrTMS in brain tumor patients to treat surgery-related upper extremity paresis.

Methods
This is a secondary analysis of two randomized and three one-arm studies in brain tumor patients with new/progressive postoperative paresis. Patients underwent either low frequency contralesional nrTMS or sham stimulation followed by physiotherapy. Outcome was assessed on postoperative day 1, 7, and after 3 months using British Medical Research Council score (BMRC), Fugl-Meyer assessment (FMA), Karnofsky Performance Scale (KPS) and National Institutes of Health Stroke Scale (NIHSS).

Results
A total of 135 patients (mean age of 53.8 years, 60 women) were included, of whom 51 patients were treated in RCTs (30 treatment group, 21 sham group) and 84 in prospective, single-arm studies. Linear mixed models showed an advantage for the treatment group for the BMRC (7 days: OR 3.28; 95%CI: 1.08–9.99; 3 months: OR 2.03, 95%CI: 0.65–6.39) and KPS (7 days: mean difference (MD) 11, 95%CI: 2–19; 3 months: MD 11, 95%CI: 2–20), less pronounced for the FMA (7 days: MD 0.28, 95%CI: -0.34-0.9; 3 months: MD 0.14, 95%CI: -0.52-0.81). A stronger treatment effect was evident with proven ischemia on the postoperative MRI. To observe an improvement by at least one grade at 3 months, the number needed to treat (NNT) for the entire cohort is 4 (BMRC) and 3 patients (KPS), respectively.

Conclusion
Our multicenter data confirm the positive treatment effect of nrTMS to reduce transcallosal inhibition with a considerably low NNT - especially if caused by ischemia.
Continuation of periodic orbits in conservative hybrid dynamical systems and its application to mechanical systems with impulsive dynamics
Authors: Raff Maximilian , Remy C. David 
Published: January 2025

Abstract
In autonomous differential equations where a single first integral is present, periodic orbits are well-known to belong to one-parameter families, parameterized by the first integral’s values.This paper shows that this characteristic extends to a broader class of conservative hybrid dynamical systems (cHDSs).We study periodic orbits of a cHDS, introducing the concept of a hybrid first integral to characterize conservation in these systems. Additionally, our work presents a methodology that utilizes numerical continuation methods to generate these periodic orbits, building upon the concept of normal periodic orbits introduced by Sepulchre and MacKay (1997). We specifically compare state-based and time-based implementations of an cHDS as an important application detail in generating periodic orbits. Furthermore, we showcase the continuation process using exemplary conservative mechanical systems with impulsive dynamics.
The Perron Method Associated with Finely p-harmonic Functions on Finely Open Sets
Authors: Björn Anders , Björn Jana , Latvala Visa 
Published: January 2025

Abstract
Given a bounded finely open set V and a function f on the fine boundary of V, we introduce four types of upper Perron solutions to the nonlinear Dirichlet problem for p-energy minimizers,

$$1<p<\infty $$

1
<
p
<
∞

, with f as boundary data. These solutions are given as pointwise infima of suitable families of fine p-superminimizers in V. We show (under natural assumptions) that the four upper Perron solutions are equal quasieverywhere and that they are fine p-minimizers of the p-energy integral. We moreover show that the upper and the lower Perron solutions coincide quasieverywhere for Sobolev and for uniformly continuous boundary data, i.e. that such boundary data are resolutive. For the uniformly continuous boundary data, the Perron solutions are also shown to be finely continuous and thus finely p-harmonic. We prove our results in a complete metric space X equipped with a doubling measure supporting a p-Poincaré inequality, but they are new also in unweighted

$$\textbf{R}^n$$

R
n

.
Making Argumentation-Based Learning and Teaching Happen: Exploring the Development of Pre-Service Science Teachers’ Argumentation Competencies
Authors: Altun Ebru , Ozsevgec Tuncay 
Published: January 2025

Abstract
It is essential for pre-service science teachers to have knowledge and skills about argumentation, which has a central role in science education, to be able to create learning environments based on argumentation, to gain written and oral argumentation competencies, and to equip students with these competencies. In this regard, this study aims to improve the argumentation competencies of pre-service science teachers, and it consists of two interrelated phases. In the first phase, pre-service science teachers participated in a 10-session instructional module on argumentation. In this process, the improvement of the pre-service teachers’ argumentation competencies was examined. In the second phase, the transfer of argumentation competencies gained by the pre-service teachers in the first phase to their learning environments was assessed. The result of the study indicated that the pre-service science teachers’ written and oral argumentation competencies were improved, they preferred to use certain argumentation schemes (causal argumentation schemes, argument from consequences, argument from examples, and argument from classification) when constructing their arguments, they employed some argumentation schemes as alternatives to each other according to their standpoints, and they chose to present their standpoints by using multiple argumentation schemes. The study also determined that the participants were able to transfer the knowledge and skills they gained during the instructional module process to real learning environments, became more confident in using different pedagogical strategies as they gained experience, and were successful in creating argumentation-based learning environments.
Fecal carriage of extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli in South American camelids and biosecurity practices among farms in northern Italy
Authors: Pavesi Laura Filippone , Rapi Maria Cristina , Penati Martina , Musa Laura , Santandrea Federica , Ferrulli Vincenzo , Martucci Ilaria , Boccardo Antonio , Grilli Guido , Addis Maria Filippa , Bronzo Valerio 
Published: January 2025

Abstract
South American camelids (SACs), particularly llamas (Lama glama) and alpacas (Vicugna pacos) are gaining popularity in Europe. Initially valued for their fiber and land management capabilities, these animals are now also kept for animal therapy, outdoor activities, and as companion animals. Despite their close interactions with humans and other animals, there is limited research on the transmission of microbes or antimicrobial resistance genes from SACs. This study aimed to survey the fecal carriage of extended-spectrum beta-lactamase ESBL-producing Escherichia coli (ESBL- E. coli) in SACs. A questionnaire was administered on-site to the farmers to survey management and biosecurity measures. Twelve farms from northern Italy (Lombardy, Piedmont, Veneto, and Emilia-Romagna) participated in the study. Fecal samples were analyzed to identify ESBL- E. coli and subjected to bacteriological culture on CHROMagar™ ESBL plates. Isolate identification was accomplished by MALDI-TOF MS, then subjected to the double-disk synergy test (DDST) and examined for 3 ESBL-encoding genes (bla
CTX−M, bla
TEM, bla
SHV) via PCR analysis. A total of 125 SACs (19 llamas and 106 alpacas) were included. Four (3.2%) of these animals were positive for ESBL- E. coli. Two isolates carried the bla
CTX−M gene; one had both bla
CTX−M and bla
TEM, and one was negative for all ESBL-encoding genes. Furthermore, none of the ESBL- E. coli isolates tested positive for the bla
SHV gene. Several data from our questionnaire revealed a lack of biosecurity protocols, which aligns with other studies. The prevalence of ESBL-producing bacteria identified in this study was lower than in different other studies. Despite the low biosecurity levels observed on the SAC farms, our findings showed a low occurrence of ESBL- E. coli and a low carriage rate of multidrug-resistant (MDR) ESBL- E. coli.
Exploring the diversity of culturable fungi on corpses for forensic applications
Authors: Piepenbring Meike , Baschien Christiane , Hoffmann Luisa , Olesiuk Martyna , Gehrels Doreen , Amendt Jens 
Published: January 2025

Abstract
Fungi form part of saprotrophic communities that are responsible for the decomposition of carrion and corpses. While necrophagous insects are known in detail and can be therefore used for forensic investigation, information provided by fungi is rarely used in forensic investigations. By the present study, we further our understanding of fungal diversity on corpses in order to make fungi useful for forensic investigation. We sampled macroscopically visible microfungi on 36 corpses at the place of discovery or at the Institute of Legal Medicine in Frankfurt am Main. Forty-seven strains of fungi were isolated, cultivated, and identified based on morphological characteristics and molecular barcoding. Together with records of fungi on corpses found in literature, this information is compiled in a checklist which contains 306 records and context information on 104 species of fungi. By our investigation, 17 species of fungi have been detected for corpses for the first time. Information on localities and the decomposition stages of the corpses is compared to characteristics of fungal species as known by literature. Many fungal species use a broad spectrum of substrates in diverse habitats, but some indicate special circumstances concerning the habitat, humidity, and temperature. The degree of decomposition of the corpses significantly correlates negatively with the value of water activity for optimal growth of individual fungal species. The checklist is a first step for the documentation of the diversity of culturable fungi on corpses, but it is still very incomplete. More records of microfungi on corpses are required, and more detailed information on characteristics of individual fungal species is needed in order to interpret and use the occurrence of fungi for criminal investigation.
Contested adaptation futures: the role of global imaginaries in climate adaptation governance
Authors: Kanarp G. C. S. , Böhm Steffen , Löf Annette 
Published: January 2025

Abstract
Despite increasing recognition of climate risks, there is a lack of adequate adaptation responses, which we argue is partly due to how governance actors imagine the future. In this article, we contend that ‘imaginaries’—collective visions of desirable futures—shape governance regimes and their approaches to climate adaptation. This framework allows us to explore the various goals and political dynamics integral to climate adaptation governance, revealing the processes through which desired futures are constructed, promulgated, and contested. Using an abductive, qualitative content analysis method, we study academic and grey literature to map and understand globally-influential climate adaptation imaginaries. We identify six distinct imaginaries: Eco-Modern State, Just Adaptation, Promethean (Green) Growth, High-Tech Society, Human Stewardship, and Knowledge Society. These adaptation imaginaries, rooted in deep-seated ethical and ontological beliefs, each present a unique vision of the future, complete with preferred adaptation strategies and key stakeholders. We contribute to the literature by showing how the globally dominant climate adaptation imaginaries reproduce existing power relations and business-as-usual approaches. Our analysis thereby provides political impetus for questioning business-as-usual approaches to climate change, enabling us to go beyond taken-for-granted assumptions of what future societies and economies might look like, and critically examining the interplay between different sociopolitical actors in adaptation governance.
Community prevalence of blood-borne viruses (hepatitis B and HIV) in Ireland
Authors: McCormick P. Aiden , O’Grady Marie , Holder Paul , De Gascun Cillian F. , Lambert John S. , Crosbie Orla , McKiernan Susan , Skelly Maeve , Courtney Garry , Hennessy Brian , Walsh Kevin , Twohig Roisin , Browne Kate , O’Gorman Tessa , Crowley Vivion , Costelloe Seán J. , O’Byrne Roz , Gildea Orla , Montgomery Noreen 
Published: January 2025

Abstract

Background
Chronic infection with hepatitis B virus and HIV causes significant morbidity and mortality. Effective antiviral treatment is available for both. Ireland has historically been considered a low prevalence country. However, with increasing inward migration and diversity, this may be changing.

Aims
The aim of this study was to measure the community prevalence of hepatitis B virus and HIV infections in Irish residents born between the years 1965 and 1985.

Methods
Anonymised residual serum samples from blood tests ordered by community general practitioners and tested in eight general hospital laboratories, spread across Ireland, were analysed for the presence of Hepatitis B surface antigen and antibodies to HIV.

Results
A total of 6080 samples were analysed for hepatitis B surface antigen including 2993 males, 2807 females and 280 samples for which gender was not recorded. HBsAg was detected in 28/6067 samples giving an estimated prevalence of 0.46% (95% CI 0.32–0.67%). Antibodies to HIV were identified in 18/6064 giving an estimated prevalence of 0.33% (95% CI 0.19–0.47%). The prevalence of both hepatitis B and HIV was significantly higher in Cork (Southwest Ireland) than other centres: hepatitis B (12/1050 vs 16/5017, p = 0.014) and HIV (11/1049 vs 7/5015, p < 0.001).

Conclusions
The prevalence of hepatitis B virus and HIV infections in this cohort appear to be higher than previously estimated. In addition, their prevalence in the Cork area appears particularly high. Whether this represents a true prevalence or a chance finding will require confirmatory studies.
Mathematical creativity in modelling: further development of the construct, its measurement, and its empirical implementation
Authors: Lu Xiaoli , Kaiser Gabriele , Zhu Yan , Ma Huimin , Yan Yuan 
Published: January 2025

Abstract
Although considerable research has been conducted on mathematical modelling and mathematical creativity separately, relatively few studies have explored their intersection. This study builds on the framework established by Lu and Kaiser to conceptualise creativity in mathematical modelling. In the paper an elaborated model of creativity that is unique to mathematical modelling is presented and appropriate assessment methods are developed. Creativity is redefined in this context and a new method for measuring it is proposed. The method extends the previously identified elements of creativity for mathematical modelling and includes an empirical test to assess creativity in mathematical modelling. In the study 141 pre-service mathematics teachers from two types of teacher education institutes in China were assessed on their creativity performance in mathematical modelling using the newly developed scoring system. Statistical analysis revealed significant findings: preservice mathematics teachers showed different levels of creativity in different modelling tasks, and significant differences in creativity were observed between the groups from two different institutes. These findings enrich the understanding of how creativity manifests itself in mathematical modelling. They also highlight the importance of developing pedagogical strategies to foster and assess creative competencies in future mathematics teachers.
A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations
Authors: Gabriel Rodney A. , Park Brian H. , Hsu Chun-Nan , Macias Alvaro A. 
Published: January 2025

Abstract

Purpose of Review
Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.

Recent Findings
Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations. Several machine learning-based models have been described to predict an individual’s propensity for opioid use disorder and opioid overdose. Natural language processing and large language model approaches have been described to detect opioid use disorder and persistent postsurgical opioid use from clinical notes.

Summary
AI holds significant promise in enhancing the management of acute and chronic opioids, which may offer tools to help optimize dosing, predict addiction risks, and personalize pain management strategies. By harnessing the power of AI, healthcare providers can potentially improve patient outcomes, reduce the burden of opioid addiction, and contribute to solving the opioid crisis.
Deep Learning Enabled Scoring of Pancreatic Neuroendocrine Tumors Based on Cancer Infiltration Patterns
Authors: Koc Soner , Eren Ozgur Can , Esmer Rohat , Kasapoglu Fatma Ulkem , Saka Burcu , Taskin Orhun Cig , Bagci Pelin , Adsay Nazmi Volkan , Gunduz-Demir Cigdem 
Published: January 2025

Abstract
Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms that include tumors with different histomorphologic characteristics that can be correlated to sub-categories with different prognoses. In addition to the WHO grading scheme based on tumor proliferative activity, a new parameter based on the scoring of infiltration patterns at the interface of tumor and non-neoplastic parenchyma (tumor-NNP interface) has recently been proposed for PanNET categorization. Despite the known correlations, these categorizations can still be problematic due to the need for human judgment, which may involve intra- and inter-observer variability. Although there is a great need for automated systems working on quantitative metrics to reduce observer variability, there are no such systems for PanNET categorization. Addressing this gap, this study presents a computational pipeline that uses deep learning models to automatically categorize PanNETs for the first time. This pipeline proposes to quantitatively characterize PanNETs by constructing entity-graphs on the cells, and to learn the PanNET categorization using a graph neural network (GNN) trained on these graphs. Different than the previous studies, the proposed model integrates pathology domain knowledge into the GNN construction and training for the purpose of a deeper utilization of the tumor microenvironment and its architectural changes for PanNET categorization. We tested our model on 105 HE stained whole slide images of PanNET tissues. The experiments revealed that this domain knowledge integrated pipeline led to a 76.70% test set F1-score, resulting in significant improvements over its counterparts.