bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of Dysphagia and Risk of Malnutrition in Elderly Living in Nursing Homes
Authors: Engberg Alva Vilpi , Rångevall Gustav , Eriksson Karin , Tuomi Lisa 
Published: March 2024

AbstractSwallowing difficulties commonly co-occur with malnutrition in the elderly. However, there is no consensus on which assessment tools to use, and thus reported prevalence varies. The aim of this study was to survey the prevalence of dysphagia and risk of malnutrition in elderly people in nursing homes, evaluate the possible associations between swallowing function and malnutrition and survey whether there were associations between self-perceived function and the results of a screening of dysphagia. A total of 35 residents (aged 67–100 years old) without serious cognitive impairment in the general wards of two nursing homes in Gothenburg were investigated. Swallowing ability was assessed with the Gugging Swallowing Screen (GUSS) test, self-rated swallowing ability with the 4QT and the Swedish Eating Assessment Tool-10 (S-EAT-10) and risk of malnutrition with the Minimal Eating Observation and Nutrition Form-Version 2 (MEONF-II). Eleven participants (31.4%) exhibited dysphagia according to the GUSS and 10 participants (29.4%) showed moderate or high risk of malnutrition. In total 16 (46%) participants reported abnormal swallowing on 4QT and 14 (40%) participants reported abnormal swallowing on S-EAT-10. However, less than half of these had dysphagia according to the GUSS. No association was found between swallowing ability measured by the GUSS and risk of malnutrition, although a tendency towards a weak association was noted, or self-rated swallowing ability measured by the 4QT and S-EAT-10. The study found that approximately one-third of the tested participants presented with signs of dysphagia as measured with the screening instrument GUSS, even though only a few were known to have any difficulties prior to testing. This highlights that dysphagia is probably more prevalent than patients themselves and caregivers are aware of, thus, screening is of importance, to enable safer nutritional intake.
Improving the operational forecasts of outdoor Universal Thermal Climate Index with post-processing
Authors: Kuzmanović Danijela , Banko Jana , Skok Gregor 
Published: March 2024

AbstractThe Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature and considers physiological aspects of the human body. It takes into account the effect of air temperature, humidity, wind, radiation, and clothes. It is increasingly used in many countries as a measure of thermal comfort for outdoor conditions, and its value is calculated as part of the operational meteorological forecast. At the same time, forecasts of outdoor UTCI tend to have a relatively large error caused by the error of meteorological forecasts. In Slovenia, there is a relatively dense network of meteorological stations. Crucially, at these stations, global solar radiation measurements are performed continuously, which makes estimating the actual value of the UTCI more accurate compared to the situation where no radiation measurements are available. We used seven years of measurements in hourly resolution from 42 stations to first verify the operational UTCI forecast for the first forecast day and, secondly, to try to improve the forecast via post-processing. We used two machine-learning methods, linear regression, and neural networks. Both methods have successfully reduced the error in the operational UTCI forecasts. Both methods reduced the daily mean error from about 2.6$$^{\circ }$$

∘

C to almost zero, while the daily mean absolute error decreased from 5$$^{\circ }$$

∘

C to 3$$^{\circ }$$

∘

C for the neural network and 3.5$$^{\circ }$$

∘

C for linear regression. Both methods, especially the neural network, also substantially reduced the dependence of the error on the time of the day.
Prevalence and assessment tools of cancer-related cognitive impairment in lung cancer survivors: a systematic review and proportional meta-analysis
Authors: Ho Mu-Hsing , So Tsz Wei , Fan Chun Lun , Chung Yiu Tak , Lin Chia-Chin 
Published: March 2024

Abstract
Purpose
Cancer-related cognitive impairment (CRCI) is a significant risk factor influencing the quality of life in lung cancer survivors. No absolute assessment tool has been confirmed to assess CRCI in lung cancer survivors. This review was undertaken to pool the overall prevalence of CRCI and to summarize the assessment tools in assessing CRCI among lung cancer survivors.

Methods
PubMed, Cochrane Library, Embase, CINAHL, and CNKI were searched to retrieve articles reported CRCI prevalence. Summary prevalence estimates were pooled using a random effects model, along with corresponding 95% prediction intervals (PIs). The Freeman-Tukey double arcsine transformation of proportions was incorporated in the analysis. Additionally, subgroup analysis, meta-regression, and leave-one-out analysis were performed.

Results
A total of 12 studies, involving 1934 survivors, were included in the review. All of these studies were found to have a low risk of bias in terms of their methodological quality. Four studies (33.3%) utilized the International Cognition and Cancer Task Force (ICCTF) criteria to identify CRCI through neuropsychological tests. The pooled prevalence rate of CRCI was found to be 26% (95% PI, 16–37%), I2 = 95.97%. The region in which the studies were conducted was identified as a significant factor contributing to this heterogeneity (p = 0.013). No indication of small-study effects was found (Egger’s test: p = 0.9191).

Conclusion
This review provides an overview of CRCI prevalence and assessment tools in lung cancer survivors. The findings can serve as epidemiological evidence to enhance clinicians’ and researchers’ understanding of early detection and assessment.
Radiative Neutron Capture Rate of $$^{11}$$B$$(n,\gamma )^{12}$$B Reaction from the Coulomb Dissociation of $$^{12}$$B
Authors: Shubhchintak  , Singh G. , Chatterjee R. , Dan M. 
Published: March 2024

AbstractWe calculate the $$^{11}$$

11

B$$(n,\gamma )^{12}$$

(
n
,
γ
)

12

B reaction rate which is an important constituent in nucleosynthesis networks and is contributed by resonant as well as non-resonant capture. For the resonant rate, we use the narrow resonance approximation whereas the non-resonant contribution is calculated with the Coulomb dissociation method for which we use finite-range distorted wave Born approximation theory. We then compare our calculated rate of $$^{11}$$

11

B$$(n,\gamma )^{12}$$

(
n
,
γ
)

12

B reaction with those reported earlier and with other charged particle reactions on $$^{11}$$

11

B.
Generation time-out grows up: young adults’ reports about childhood time-out use and their mental health, attachment, and emotion regulation
Authors: Xu Jingyi , Tully Lucy A. , Dadds Mark R. 
Published: March 2024

AbstractTime-out (TO) is a widely utilised parental discipline technique with a strong evidence-base that nonetheless has attracted controversy regarding potential adverse effects on mental health in developing children. Associations between TO implementation and mental health outcomes have rarely been investigated, especially through the eyes of children who grew up experiencing TO. This study recruited 407 university students (Study 1) and a community sample of 535 young adults (Study 2); both samples aged 18–30 years. Young adults were surveyed on their retrospective reports of childhood TO experience, childhood experiences of adversity, perceived parenting style and parental attachment, and their current mental health outcomes (attachment style, emotion regulation and mental health). In Study 1, 334 (82.1%) young adults reported experiencing TO in childhood, but with widely varied implementation that differed considerably from its evidence-based ideal. Reports of more TO appropriate implementation were associated with less avoidant attachment, better mental health, and emotion regulation, over and above the effects associated with authoritative parenting and secure attachment in childhood. While exposure to childhood adversity was associated with poorer adulthood outcomes, TO implementation did not moderate the association. Study 2 replicated most findings from Study 1, except that appropriate TO implementation displayed a positive association with mental health and no associations with anxious and avoidant attachment and emotion regulation. These findings suggest the safety of TO use with young children, including those who experienced childhood adversity, and highlight the importance of disseminating sufficient parenting information on TO in the community.
An unsupervised automatic organization method for Professor Shirakawa’s hand-notated documents of oracle bone inscriptions
Authors: Yue Xuebin , Wang Ziming , Ishibashi Ryuto , Kaneko Hayata , Meng Lin 
Published: March 2024

AbstractAs one of the most influential Chinese cultural researchers in the second half of the twentieth-century, Professor Shirakawa is active in the research field of ancient Chinese characters. He has left behind many valuable research documents, especially his hand-notated oracle bone inscriptions (OBIs) documents. OBIs are one of the world’s oldest characters and were used in the Shang Dynasty about 3600 years ago for divination and recording events. The organization of OBIs is not only helpful in better understanding Prof. Shirakawa’s research and further study of OBIs in general and their importance in ancient Chinese history. This paper proposes an unsupervised automatic organization method to organize Prof. Shirakawa’s OBIs and construct a handwritten OBIs data set for neural network learning. First, a suite of noise reduction is proposed to remove strangely shaped noise to reduce the data loss of OBIs. Secondly, a novel segmentation method based on the supervised classification of OBIs regions is proposed to reduce adverse effects between characters for more accurate OBIs segmentation. Thirdly, a unique unsupervised clustering method is proposed to classify the segmented characters. Finally, all the same characters in the hand-notated OBIs documents are organized together. The evaluation results show that noise reduction has been proposed to remove noises with an accuracy of 97.85%, which contains number information and closed-loop-like edges in the dataset. In addition, the accuracy of supervised classification of OBIs regions based on our model achieves 85.50%, which is higher than eight state-of-the-art deep learning models, and a particular preprocessing method we proposed improves the classification accuracy by nearly 11.50%. The accuracy of OBIs clustering based on supervised classification achieves 74.91%. These results demonstrate the effectiveness of our proposed unsupervised automatic organization of Prof. Shirakawa’s hand-notated OBIs documents. The code and datasets are available at http://www.ihpc.se.ritsumei.ac.jp/obidataset.html.
Quantifying robustness: 3D tree point cloud skeletonization with smart-tree in noisy domains
Authors: Dobbs Harry , Batchelor Oliver , Peat Casey , Atlas James , Green Richard 
Published: March 2024

AbstractExtracting tree skeletons from 3D tree point clouds is challenged by noise and incomplete data. While our prior work (Dobbs et al., in: Iberian conference on pattern recognition and image analysis, Springer, Berlin, pp. 351–362, 2023) introduced a deep learning approach for approximating tree branch medial axes, its robustness against various types of noise has not been thoroughly evaluated. This paper addresses this gap. Specifically, we simulate real-world noise challenges by introducing 3D Perlin noise (to represent subtractive noise) and Gaussian noise (to mimic additive noise). To facilitate this evaluation, we introduce a new synthetic tree point cloud dataset, available at https://github.com/uc-vision/synthetic-trees-II. Our results indicate that our deep learning-based skeletonization method is tolerant to both additive and subtractive noise.
Prediction of mangrove recovery in natural protected areas of the Yucatan Peninsula
Authors: Osorio-Olvera Laura , Rioja-Nieto Rodolfo , Guerra-Martínez Francisco 
Published: March 2024

AbstractNatural protected areas (NPAs) in the Yucatan Peninsula favour the conservation of mangrove forests, which are valuable ecosystems for their provision of ecosystem services. However, mangroves are vulnerable to destruction due to natural and anthropogenic pressures. Therefore, it is important to assess their spatial and temporal dynamics and the potential for deforestation and recovery of cover. In this study, we analyse and model mangrove forest cover change in six NPAs of the Yucatan Peninsula by 2025. Predictions were made using the cellular automata method (CA-Markov) based on attributes that drive rates of change (obtained Kappa coefficients between 0.78 and 0.91). Anthropogenic development was the most dominant potential driver of land use and land cover change in all NPAs except the Flora and Fauna Protection Area-Yum Balam. During the period 2005–2015, the Biosphere Reserves-Petenes and Celestún showed the greatest mangrove loss, followed by the Flora and Fauna Protection Area-Nichupté. These processes changed for the simulated period (2015–2025), where an increase in mangrove cover is projected in these protected areas. Flora and Fauna Protection Area-Términos is the only protected area where a projected transition of mangroves to anthropogenic development has been identified. Therefore, it should be considered an area vulnerable to mangrove transformation and loss.
Fostering computational thinking through digital storytelling: a distinctive approach to promoting computational thinking skills of pre-service teachers
Authors: Haşlaman Tülin , Mumcu Filiz Kuşkaya , Uslu Nilüfer Atman 
Published: March 2024

AbstractThe present study illustrates digital storytelling (DS) as an open-ended learning environment, which is one of the ways of preparing pre-service teachers (PST) to practice computational thinking (CT) in their future teaching. An 8-week teacher training program was organized and presented. The study aims to investigate the program’s impact on the PST's CT skills, CT-integrated DS design skills, and their perspectives. A study group of fifty-two second-year PSTs took part in the Instructional Technologies course. An embedded mixed-method design was used. The CT scale was used as a pre-test and post-test to examine the development of the PST’s CT skills for quantitative data collection. The qualitative data comprise the CT-integrated DS projects developed by the PST during the training and the reflection reports they wrote at the end of the training. The paired samples t-test was used in the analysis of quantitative data. The DS projects were evaluated using the rubrics with the story/storyboard, DS, and CT skills dimensions. Reflection reports were analyzed using thematic analysis. The findings revealed a significant improvement in the PST’s CT skills after the training program. The qualitative findings show the PST’s perspectives on CT definitions, the perceived benefits of CT and DS, and the use of DS to promote CT. The qualitative findings also present evidence for the CT-integrated DS design skills of the PST. Therefore, the study presents early findings showing that CT components could be integrated with DS and used in teacher education effectively without any pressure to use programming tools. The study also shows how DS is gradually integrated with the CT components as a suggestion for future studies.
Projector deep feature extraction-based garbage image classification model using underwater images
Authors: Demir Kubra , Yaman Orhan 
Published: March 2024

AbstractMarine and ocean pollution is one of the most serious environmental problems in the world. Marine plastics pose a significant threat to the marine ecosystem due to their negative effects. After passing through various processes, plastic waste accumulates on the seafloor and fragments into very small pieces known as microplastics. These microplastics are to blame for the extinction and death of aquatic life. This study obtained a hybrid underwater dataset containing 13,089 images, sized 300 × 300, including garbage and sea animals. In the proposed method, this dataset is used to develop our example projector deep feature generator. In this study, using the Resnet101 network in a sample projector build, the feature generator creates 6,000 features. Using NCA (Neighborhood Component Analysis), the best 1000 features from a pool of 6,000 are selected. The kNN (k-nearest neighbor) algorithm is then used to classify the resulting feature vectors. As validation techniques, both tenfold cross-validations were used. The hybrid dataset's best accuracy was calculated to be 99.35%. Our recommendation is successful based on the comparisons and calculated performance measures.
The Effect of Thermal Residual Stress on the Stress State in a Short-Fiber Reinforced Thermoplastic
Authors: Wismans M. , van Breemen L. C. A. , Govaert L. E. , Engels T. A. P. 
Published: March 2024

AbstractUpon their cooling and solidification, significant thermal residual stresses can develop in short-fiber reinforced thermoplastics due to the mismatch in coefficient of thermal expansion between fiber and matrix. In this study we set out to investigate this effect numerically. The build-up of thermal residual stresses is modeled by expanding a well-established constitutive model, the Eindhoven glassy polymer (EGP) model, with thermal expansion. The experimentally measured thermal residual stresses can be described using an effective glass-transition temperature and a constant coefficient of thermal expansion without the need for complex equilibrium kinetics associated with the glass transition itself. Subsequently, the influence of thermal residual stress on the deformation behavior for a short-fiber reinforced thermoplastic is studied employing multi-fiber representative volume elements (RVEs) for different fiber-weight fractions. The micromechanical models are evaluated on the importance of thermal residual stresses on the local and nominal stress state. From these analyses it can be concluded that the thermal residual stresses should be accounted for when assessing the quantitative local stress state and are therefore essential when local mechanisms are studied. In contrast, thermal residual stresses are not required to capture the nominal transient stress–strain response.
A Review of Shared Decision-Making, Published Protocols, and Post-desensitization Strategies in Oral Immunotherapy (OIT)
Authors: Laubach Susan , Kim Edwin H. , Greenhawt Matthew , Bailey Sally , Anagnostou Aikaterini 
Published: March 2024

Abstract
Purpose of Review
The aim of this review is to highlight key published oral immunotherapy (OIT) protocols and post-desensitization strategies for the major food allergens and to cover important concepts to consider when evaluating OIT for food-allergic patients. Shared decision-making should help identify patient and family values which will help influence the type of evidence-based protocol and maintenance strategy to use.

Recent Findings
With food OIT emerging as a treatment option, there is a pressing need for patients, physicians, and other providers to have a nuanced understanding of the management choices available to them. There are now randomized controlled trials (RCT) of OIT for peanut, egg, milk, and wheat, and reports of cohorts of patients who have undergone OIT for tree nuts and sesame clinically. The current published protocols contain significant diversity in terms of starting dose, build-up schedule, maintenance dose, and even the product used for desensitization. Emerging data can help direct the long-term maintenance strategy for patients on OIT.

Summary
Based on patient and family values elicited through the shared decision-making process, an OIT protocol may be selected that balances the level of desensitization, potential side effects, frequency of clinic visits, and potential to induce sustained unresponsiveness, among other factors. Once maintenance dosing is reached, most patients will need to maintain regular exposure to the food allergen to remain desensitized. The option to transition to commercial food products with equivalent amounts of food protein as the OIT maintenance dose would simplify the dosing process and perhaps improve palatability as well. Less frequent or decreased OIT dosing can provide practical benefits but may affect the level of desensitization and safety for some patients.
Management of Patients with Early Myelofibrosis: A Discussion of Best Practices
Authors: Bose Prithviraj 
Published: March 2024

Abstract
Purpose of Review
Summarize best practices for management of patients with early myelofibrosis (MF).

Recent Findings
Myelofibrosis is a progressive myeloproliferative neoplasm (MPN) that generally produces burdensome symptoms and ultimately leads to worse overall survival than that observed in healthy controls or patients with other MPNs. Several Janus kinase inhibitors and various interferon formulations are now available for treatment of MF, with ruxolitinib notable for extending overall survival in addition to improving MF signs and symptoms.

Summary
The chronic nature of the disease can lead some patients to avoid immediate treatment in favor of a watch-and-wait approach. This review summarizes the patient management approach taken in my practice, providing guidance and a discussion of best practices with an emphasis on the importance and clinical benefits of active treatment in early MF. In particular, a case is made to consider treatment with ruxolitinib for patients with intermediate-1 risk disease and to minimize delay between diagnosis and treatment initiation for patients with intermediate or high-risk disease.
Behavioral selection in structured populations
Authors: Borgstede Matthias 
Published: March 2024

AbstractThe multilevel model of behavioral selection (MLBS) by Borgstede and Eggert (Behav Process 186:104370. 10.1016/j.beproc.2021.104370, 2021) provides a formal framework that integrates reinforcement learning with natural selection using an extended Price equation. However, the MLBS is so far only formulated for homogeneous populations, thereby excluding all sources of variation between individuals. This limitation is of primary theoretical concern because any application of the MLBS to real data requires to account for variation between individuals. In this paper, I extend the MLBS to account for inter-individual variation by dividing the population into homogeneous sub-populations and including class-specific reproductive values as weighting factors for an individual’s evolutionary fitness. The resulting formalism closes the gap between the theoretical underpinnings of behavioral selection and the application of the theory to empirical data, which naturally includes inter-individual variation. Furthermore, the extended MLBS is used to establish an explicit connection between the dynamics of learning and the maximization of individual fitness. These results expand the scope of the MLBS as a general theoretical framework for the quantitative analysis of learning and evolution.