bluuebunny/crossref_metadata_2025_split huggingface dataset:
Finite element analysis of the interaction between high-compliant balloon catheters and non-cylindrical vessel structures: towards tactile sensing balloon catheters
Authors: Bhave Ashish , Sittkus Benjamin , Urban Gerald , Mescheder Ulrich , Möller Knut 
Published: August 2023

AbstractAiming for sensing balloon catheters which are able to provide intraoperative information of the vessel stiffness and shape, the present study uses finite element analysis (FEA) to evaluate the interaction between high-compliant elastomer balloon catheters with the inner wall of a non-cylindrical-shaped lumen structure. The contact simulations are based on 3D models with varying balloon thicknesses and varying tissue geometries to analyse the resulting balloon and tissue deformation as well as the inflation pressure dependent contact area. The wrinkled tissue structure is modelled by utilizing a two-layer fibre-based Holzapfel-Gasser-Ogden constitutive model and the model parameters are adapted based on available biomechanical data for human urethral vessel samples. The balloon catheter structure is implemented as a high-compliant hyper-elastic silicone material (based on polydimethylsiloxane (PDMS)) with a varying catheter wall thickness between 0.5 and 2.5 µm. Two control parameters are introduced to describe the balloon shape adaption in reaction to a wrinkled vessel wall during the inflation process. Basic semi-quantitative relations are revealed depending on the evolving balloon deformation and contact surface. Based on these relations some general design guidelines for balloon-based sensor catheters are presented. The results of the conducted in-silico study reveal some general interdependencies with respect to the compliance ratio between balloon and tissue and also in respect of the tissue aspect ratio. Further they support the proposed concept of high-compliant balloon catheters equipped for tactile sensing as diagnosis approach in urology and angioplasty.
Comparative performance of ensemble machine learning for Arabic cyberbullying and offensive language detection
Authors: Khairy Marwa , Mahmoud Tarek M. , Omar Ahmed , Abd El-Hafeez Tarek 
Published: August 2023

AbstractSince cyberbullying impacts both individual victims and entire society, research on abusive language and its detection has attracted attention in recent years. Because social media sites like Facebook, Instagram, Twitter, and others are so widely accessible, hate speech, bullying, sexism, racism, aggressive material, harassment, poisonous comments, and other types of abuse have all substantially increased. Due to the critical requirement to detect, regulate, and limit the spread of harmful content on social networking sites, we conducted this study to automate the detection of offensive language or cyberbullying. We created a new Arabic balanced data set to be used in the offensive detection process because having a balanced data set for a model would result in improved accuracy models. Recently, the performance of single classifiers has been improved using ensemble machine learning. The purpose of this study is to examine the effectiveness of several single and ensemble machine learning algorithms in identifying Arabic text that contains foul language and cyberbullying. Applying them to three Arabic datasets, we have selected three machine learning classifiers and three ensemble models for this aim. Two of them are offensive datasets that are readily accessible in the public, while the third one was created. The results showed that the single learner machine learning strategy is inferior to the ensemble machine learning methodology. Voting performs is the best performing trained ensemble machine learning classifier, outperforming the best single learner classifier (65.1%, 76.2%, and 98%) for the same datasets with accuracy scores of (71.1%, 76.7%, and 98.5%) for each of the three datasets used. Finally, we improve the voting technique’s performance through hyperparameter tuning on the Arabic cyberbullying data set.
Does criminalizing the purchase of sex reduce sex-buying? Evidence from a European survey on prostitution
Authors: Jonsson Sofia 
Published: August 2023

AbstractWhether to criminalize or legalize the purchase of sex has given rise to heated discussions and different policy initiatives. Opponents of the criminalization of sex-buying argue that prohibition pushes the sector underground, increasing the harm for women in prostitution. Proponents instead view prostitution as violence against women, calling for prohibition. Despite these debates, few studies examine the effect of prostitution laws on the quantity of sex bought. By employing unique data on attitudes to, and experiences of sex-buying behaviour in different prostitution regimes in eight European countries, the paper examines the relationship between prostitution law and sex-buying. The results are robust to the inclusion of a list experiment, and the findings suggest that people living in countries where purchasing sex is criminalized buy less sex than people living in countries where sex-buying is legal.
Association study between some cultivated species and their wild relatives from Apiaceae, Asteraceae and Brassicaceae families based on molecular and DNA barcoding in Egypt
Authors: Essa Nerveen M. , Ibrahim Amira A. , Soliman Magda I. 
Published: August 2023

AbstractConcerns about food security worldwide have been raised due to the adverse impacts of climate change on agricultural productivity. Utilizing wild relatives of cultivated plants in breeding schemes is a potential solution to address the abovementioned challenges. Wild relatives refer to indigenous plant species that share genetic ancestry with recently cultivated plants. The capacity of plants to withstand abiotic stresses and enhance crop yield stability in cold and arid environments renders them a valuable prospective resource for breeding programs. Molecular markers are employed to assess the genetic variability of cultivated plants and their wild relatives under investigation. This study employed a set of five primers derived from ISSR (Inter Simple Sequence Repeats) and SCoT (Start Codon Targeted) to assess comparative research between cultivated species and their wild relatives from three families: Apiaceae (Apium gravolens L., A. leptophyllum (Pers.) F.Muell., Daucus carota L.& D. litoralis Sm.), Asteraceae (Lactuca sativa L. & L. serriola L.) and Brassicaceae (B. oleracea L., Brassica tourneforttii Gouan., Raphanus sativus L. & R. raphanistrum L.). The ISSR technique yields approximately 206 bands, whereas the SCoT primers generate approximately 207 bands. The ISSR primers yielded 169 polymorphic bands, exhibiting a polymorphism rate of 82.04%, whereas the SCoT primers produced 169 polymorphic bands with a polymorphism rate of 81.64%. The Brassicaceae has been found to exhibit the highest resolving power (RP) of 48.25, as determined by ISSR. The primary objective of DNA barcoding is to create a communal database of DNA sequences that can be utilized to identify organisms and clarify their taxonomic classification. The findings indicate that the internal transcribed spacer (ITS) regions exhibit high efficacy as a DNA barcoding tool. Overall, the results obtained from two molecular markers and DNA barcoding analyses suggest a significant degree of genetic diversity and relatedness among the cultivated taxa and their wild relatives examined in this study.
Increasing homogeneity of Mediterranean landscapes limits the co-occurrence of mesocarnivores in space and time
Authors: Linck Paloma , Palomares Francisco , Negrões Nuno , Rossa Mariana , Fonseca Carlos , Couto André , Carvalho João 
Published: August 2023

Abstract
Context
The Mediterranean basin is characterized by a heterogeneous landscape historically shaped by human activities. Land abandonment and extensive monocultures, however, have led to increasing homogeneity of Mediterranean habitats. Albeit the effects of habitat heterogeneity on wildlife have been widely studied, the available information on how habitat homogenization impacts the organization of mesocarnivore communities is still scant.

Objectives
We investigated the relationship of environmental characteristics with occupancy, activity, community organization, and co-occurrence of mesocarnivore species in space and time. We focused on five key species (Vulpes vulpes, Genetta genetta, Meles meles, Herpestes ichneumon, and Martes foina) widely distributed throughout Mediterranean ecosystems.

Methods
The study was conducted in north-central Portugal between June 2019 and June 2020. We used 300 camera trap sampling points coupled with occupancy, activity, and co-occurrence analysis to assess how different environmental characteristics influence mesocarnivores community.

Results
We found that the occupancy of mesocarnivores is influenced by topography, landscape composition and structure, and human activity. We observed that landscape homogeneity limits the co-occurrence of mesocarnivores. In heterogeneous landscapes we recorded a greater overlap in activity (seven of ten species pairs) and spatial co-occurrence (six of the seven species pairs analyzed) of mesocarnivores species.

Conclusions
We demonstrated the importance of landscape characteristics in the composition of the mesocarnivores community. Our findings support the adoption of management measures able to mitigate the impacts of landscape homogenization. Maximizing the heterogeneity is an important step to benefit the mesocarnivore community in altered Iberian landscapes.
Data-driven agriculture and sustainable farming: friends or foes?
Authors: Rozenstein Offer , Cohen Yafit , Alchanatis Victor , Behrendt Karl , Bonfil David J. , Eshel Gil , Harari Ally , Harris W. Edwin , Klapp Iftach , Laor Yael , Linker Raphael , Paz-Kagan Tarin , Peets Sven , Rutter S. Mark , Salzer Yael , Lowenberg-DeBoer James 
Published: August 2023

AbstractSustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies between the domains of natural systems that are key to simultaneously achieve sustainability and food security. In the quest for agricultural sustainability, some high-payoff research areas are suggested to resolve critical legal and technical barriers as well as economic and social constraints. These include: the development of holistic decision-making systems, automated animal intake measurement, low-cost environmental sensors, robot obstacle avoidance, integrating remote sensing with crop and pasture models, extension methods for data-driven agriculture, methods for exploiting naturally occurring Genotype x Environment x Management experiments, innovation in business models for data sharing and data regulation reinforcing trust. Public funding for research is needed in several critical areas identified in this paper to enable sustainable agriculture and innovation.
Dynamic Context Removal: A General Training Strategy for Robust Models on Video Action Predictive Tasks
Authors: Xu Xinyu , Li Yong-Lu , Lu Cewu 
Published: August 2023

AbstractPredicting future actions is an essential feature of intelligent systems and embodied AI. However, compared to the traditional recognition tasks, the uncertainty of the future and the reasoning ability requirement make prediction tasks very challenging and far beyond solved. In this field, previous methods usually care more about the model architecture design but little attention has been put on how to train models with a proper learning policy. To this end, in this work, we propose a simple but effective training strategy, Dynamic Context Removal (DCR), which dynamically schedules the visibility of context in different training stages. It follows the human-like curriculum learning process, i.e., gradually removing the event context to increase the prediction difficulty till satisfying the final prediction target. Besides, we explore how to train robust models that give consistent predictions at different levels of observable context. Our learning scheme is plug-and-play and easy to integrate widely-used reasoning models including Transformer and LSTM, with advantages in both effectiveness and efficiency. We study two action prediction problems, i.e., Video Action Anticipation and Early Action Recognition. In extensive experiments, our method achieves state-of-the-art results on several widely-used benchmarks.
Kin ball to promote the motor development of students with special educational needs: effects of an intervention programme
Authors: Zurita-Ortega Félix , Ortiz-Franco Manuel , Ubago-Jiménez José Luis , González-Valero Gabriel , Alonso-Vargas José Manuel , Melguizo-Ibáñez Eduardo 
Published: August 2023

Abstract
Background
The scientific literature establishes that people with mental impairments show high levels of sedentary behaviour.

Aim
This research has the objectives of (a) Studying the effect of the intervention programme on the effect of basic physical qualities, balance and coordination and (b) Comparing the results obtained before and after carrying out the intervention programme according to the sex of the participants through a structural equation model.

Methods
A quasi-experimental study was carried out with a pre-test-post-test group design, with a sample of 47 participants (46.8% male and 53.2% female). Questionnaires adapted to the characteristics of the sample were carried out to collect the data.

Results
It is observed that the intervention programme has helped to improve the effect of basic physical qualities on balance and coordination.

Conclusion
It is concluded that Kin Ball is a sport that improves the quality of life of people with special educational needs and that gender is a key factor influencing the development of basic physical qualities.
Digital competence of K-12 pre-service and in-service teachers in China: a systematic literature review
Authors: Yang Li , García-Holgado Alicia , Martínez-Abad Fernando 
Published: August 2023

AbstractThis systematic review consisted of 50 theoretical and empirical articles taking China as a specific case study for identifying efforts and challenges to teachers' digital competence, establishing an understanding of their use of concepts, disciplines, regions, methods, and analysis. The review follows the methodology based on the PRISMA statement and PICO strategy using the 2010–2023 search period. This research has four primary findings: (1) “teachers' ICT competency” and “teachers’ information literacy” are the main terms used for describing teacher’s use of technology for teaching and learning; (2) the current research mainly focused on investigating the status of teachers' digital competence, the influencing factors, and teacher training; (3) non-experimental study for the population of in-service teachers is the leading research directions related to teachers’ digital competence in the context of China; (4) creating good ICT atmosphere by government and schools, conducting teacher training, and using good pedagogical strategies are three main proposals have been made to improve teachers' digital competence in China. The research findings provide the starting points for a subject of reflection and analysis of the Chinese teachers' digital competence status, and it can also support future empirical research.
Recent innovative seed treatment methods in the management of seedborne pathogens
Authors: Moumni Marwa , Brodal Guro , Romanazzi Gianfranco 
Published: August 2023

AbstractSeed is a critically important basic input of agriculture, because sowing healthy seeds is essential to food production. Using high quality seed enables less use of synthetic pesticides in the field. Seedborne pathogens can reduce yield quantity and quality of the crops produced. Seed treatments protect plant seedlings from pathogen attacks at emergence and at the early growth stages, contributing to healthy crop plants and good yield. However, there is increased concern about the application of synthetic pesticides to seeds, while alternatives are becoming increasingly addressed in seedborne pathogen research. A series of strategies based on synthetic fungicides, natural compounds, biocontrol agents (BCAs), and physical means has been developed to reduce seed contamination by pathogens. The volume of research on seed treatment has increased considerably in the past decade, along with the search for green technologies to control seedborne diseases. This review focuses on recent research results dealing with protocols that are effective in the management of seedborne pathogens. Moreover, the review illustrated an innovative system for routine seed health testing and need-based cereal seed treatment implemented in Norway.
Graphical Abstract
Is Accurate Lumen Segmentation More Important than Outlet Boundary Condition in Image-Based Blood Flow Simulations for Intracranial Aneurysms?
Authors: Korte Jana , Voß Samuel , Janiga Gábor , Beuing Oliver , Behme Daniel , Saalfeld Sylvia , Berg Philipp 
Published: August 2023

Abstract
Purpose
Image-based blood flow simulations are increasingly used to investigate the hemodynamics in intracranial aneurysms (IAs). However, a strong variability in segmentation approaches as well as the absence of individualized boundary conditions (BCs) influence the quality of these simulation results leading to imprecision and decreased reliability. This study aims to analyze these influences on relevant hemodynamic parameters within IAs.

Methods
As a follow-up study of an international multiple aneurysms challenge, the segmentation results of five IAs differing in size and location were investigated. Specifically, five possible outlet BCs were considered in each of the IAs. These are comprised of the zero-pressure condition (BC1), a flow distribution based on Murray’s law with the exponents n = 2 (BC2) and n = 3 (BC3) as well as two advanced flow-splitting models considering the real vessels by including circular cross sections (BC4) or anatomical cross sections (BC5), respectively. In total, 120 time-dependent blood flow simulations were analyzed qualitatively and quantitatively, focusing on five representative intra-aneurysmal flow and five shear parameters such as vorticity and wall shear stress.

Results
The outlet BC variation revealed substantial differences. Higher shear stresses (up to Δ9.69 Pa), intrasaccular velocities (up to Δ0.15 m/s) and vorticities (up to Δ629.22 1/s) were detected when advanced flow-splitting was applied compared to the widely used zero-pressure BC. The tendency of outlets BCs to over- or underestimate hemodynamic parameters is consistent across different segmentations of a single aneurysm model. Segmentation-induced variability reaches Δ19.58 Pa, Δ0.42 m/s and Δ957.27 1/s, respectively. Excluding low fidelity segmentations, however, (a) reduces the deviation drastically (>43%) and (b) leads to a lower impact of the outlet BC on hemodynamic predictions.

Conclusion
With a more realistic lumen segmentation, the influence of the BC on the resulting hemodynamics is decreased. A realistic lumen segmentation can be ensured, e.g., by using high-resolved 2D images. Furthermore, the selection of an advanced outflow-splitting model is advised and the use of a zero-pressure BC and BC based on Murray’s law with exponent n = 3 should be avoided.
A two-pronged approach against glioblastoma: drug repurposing and nanoformulation design for in situ-controlled release
Authors: Mendes Maria , Branco Francisco , Vitorino Rui , Sousa João , Pais Alberto , Vitorino Carla 
Published: August 2023

AbstractGlioblastoma (GB) is one of the most lethal types of neoplasms. Its biologically aggressive nature and the presence of the blood–brain barrier (BBB) limit the efficacy of standard therapies. Several strategies are currently being developed to both overcome the BBB and deliver drugs site specifically to tumor cells. This work hypothesizes a two-pronged approach to tackle GB: drug repurposing with celecoxib (CXB) and a nanoformulation using ultra-small nanostructured lipid carriers (usNLCs). CXB antitumor druggable activity was inspected bioinformatically and screened in four glioma cell lines aiming at the comparison with temozolomide (TMZ), as standard of care. Delving into formulation design, it was tailored aiming at (i) improving the drug solubility/loading properties, (ii) assigning a thermal-triggerable drug release based on a lipid matrix with a low melting point, and (iii) enhancing the cytotoxic effect by selecting a template targetable to tumor cells. For this purpose, an integrated analysis of the critical material attributes (CMAs), critical process parameters (CPPs), and critical quality attributes (CQAs) was conducted under the umbrella of a quality by design approach. CMAs that demonstrate a high-risk level for the final quality and performance of the usNLCs include the drug solubility in lipids (solid and liquid), the lipid composition (envisioning a thermoresponsive approach), the ratio between lipids (solid vs. liquid), and the surfactant type and concentration. Particle size was shown to be governed by the interaction lipid-surfactant followed by surfactant type. The drug encapsulation did not influence colloidal characteristics, making it a promising carrier for lipophilic drugs. In general, usNLCs exhibited a controlled drug release during the 72 h at 37 °C with a final release of ca. 25%, while at 45 °C this was doubled. The in vitro cellular performance depended on the surfactant type and lipid composition, with the formulations containing a sole solid lipid (Suppocire® NB) and Kolliphor® RH40 as surfactant being the most cytotoxic. usNLCs with an average diameter of ca. 70 nm and a narrow size distribution (PdI lower than 0.2) were yielded, exhibiting high stability, drug protection, sustained and thermo-sensitive release properties, and high cytotoxicity to glioma cells, meeting the suitable CQAs for parenteral administration. This formulation may pave the way to a multi-addressable purpose to improve GB treatment.
Graphical Abstract
Long-acting somatostatin analogs and well differentiated neuroendocrine tumors: a 20-year-old story
Authors: Faggiano A. 
Published: August 2023

Abstract
Purpose
The specific indications of somatostatin analogs (SSAs) in patients with neuroendocrine tumor (NET) emerged over the time. The objective of this review is to summarize and discuss the most relevant data concerning long-acting SSAs in NET.

Methods
A narrative review was performed including publications focusing on therapy with the long-acting octreotide, lanreotide, and pasireotide in patients with NET.

Results
Long-acting SSAs confirm to be a manageable and widely used tool in patients with NET. Both long-acting octreotide and lanreotide are safe as the short-acting formulations, while patient compliance and adherence is further improved. Together with some randomized phase-3 trials, many retrospective and prospective studies have been performed in the last 20 years revealing a variable but substantial impact on progression free survival, not only in gastroenteropancreatic but also in lung and unknown primary NETs. The most frequent tumor response to SSAs is stable disease, but an objective response can be observed, more frequently by using high-dose schedules and in MEN1-related pancreatic NETs. Low tumor burden, low tumor grade (G1 and low G2), good performance status and use as first-line therapy are the main predictive factors to SSAs in NET patients. Pasireotide has been evaluated in few studies. This compound remains a promising SSA and would deserve to be further evaluated as a potential additional indication in NET therapy.

Conclusions
Long-acting SSAs are an effective and safe initial therapy of patients with well differentiated NET, allowing tumor growth as well as symptoms control for long-time in selected patients.