bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distal fusion level, complications, and reoperations in individuals with cerebral palsy undergoing surgery for scoliosis
Authors: Green-Petersen I. , Magnano L. , Charalampidis A. , Gerdhem P. 
Published: September 2023

Abstract
Purpose
To compare radiological outcome, complications and reoperations in individuals with cerebral palsy and scoliosis fused to the fifth lumbar vertebra (L5), the sacrum, or the ilia.

Methods
208 individuals were identified in the national quality registry Swespine. Lowest level of fusion was L5 in 58, the sacrum in 92, and the ilia in 58 individuals. A subanalysis on 58 matched pairs operated to L5 or the pelvis (sacrum = 42, ilia = 16) with similar pelvic obliquity (± 5°) was performed.

Results
The median (interquartile range) follow-up for the last radiograph was 1.7 (1.7) years and for reoperations 6.0 (5.9) years. Preoperatively, median Cobb angle of the major curve was 65° (23°) in the L5 group, 68° (28°) in the sacrum group, and 78° (25°) in the ilia group (p = 0.006). Preoperative median pelvic obliquity according to Maloney was 16° (19°), 21° (13°), and 27° (28°), respectively (p = 0.004). Immediate postoperative Cobb angles were 28° (18°), 28° (16°), and 32° (25°), respectively (p = 0.11). Immediate postoperative pelvic obliquity was 7° (10°), 7° (8°), and 8° (10°), respectively (p = 0.28). The median change in pelvic obliquity from the first to the last postoperative radiograph was − 5° (7°), − 3° (6°), − 3° (6°), respectively (p = 0.55). 7 (12%), 11 (12%), and 7 (12%) patients required at least one reoperation (p = 1.0), respectively. In the matched analysis, no significant differences in the radiological outcomes were found (all p ≥  0.38).

Conclusions
Maintained curve and pelvic obliquity correction with no significant difference in complication and reoperation rates were found irrespective of distal fusion level.
Estimating surgery, radiotherapy and systemic anti-cancer therapy treatment costs for cancer patients by stage at diagnosis
Authors: Wills Lorna , Nagarwalla Diana , Pearson Clare , McPhail Sean , Hinchliffe Rose , Sharpless Ben , Fardus-Reid Fahmina , Ambler Lyndsy , Harrison Samantha , Shelton Jon 
Published: September 2023

Abstract
Background
The increasing burden of cancer has economic implications for the healthcare system in England. However, there is limited evidence on the cost of cancer treatment. We calculated the costs of initial cancer treatment (resection, radiotherapy, systemic anti-cancer therapy [SACT]) based on stage at diagnosis.

Methods
Data from England’s National Cancer Registration Dataset were matched to English Hospital, Radiotherapy and SACT data for breast, lung, prostate, colon and rectal cancers diagnosed between 2016 and 2018. Treatment data were matched to National Schedule of Reference Costs data to calculate the cost of each treatment event.

Results
Breast, colon and rectal cancers treated with resection, radiotherapy or SACT had increasing costs with later stage at diagnosis; costs for lung and prostate cancers were lower at stages 1 and 4 compared to stages 2 and 3. In general, surgery and SACT were the most expensive treatments. Radiotherapy and SACT costs showed little change across stages 1–3; radiotherapy costs decreased in stage 4, while SACT costs increased.

Conclusions
This analysis estimates initial treatment costs by stage based on observed data. Future research can build on this to provide more comprehensive costings associated with cancer; this is important for future planning of cancer services.
Prediction of skull fractures in blunt force head traumas using finite element head models
Authors: Lindgren Natalia , Henningsen Mikkel J. , Jacobsen Christina , Villa Chiara , Kleiven Svein , Li Xiaogai 
Published: September 2023

AbstractTraumatic head injuries remain a leading cause of death and disability worldwide. Although skull fractures are one of the most common head injuries, the fundamental mechanics of cranial bone and its impact tolerance are still uncertain. In the present study, a strain-rate-dependent material model for cranial bone has been proposed and implemented in subject-specific Finite Element (FE) head models in order to predict skull fractures in five real-world fall accidents. The subject-specific head models were developed following an established image-registration-based personalization pipeline. Head impact boundary conditions were derived from accident reconstructions using personalized human body models. The simulated fracture lines were compared to those visible in post-mortem CT scans of each subject. In result, the FE models did predict the actual occurrence and extent of skull fractures in all cases. In at least four out of five cases, predicted fracture patterns were comparable to ones from CT scans and autopsy reports. The tensile material model, which was tuned to represent rate-dependent tensile data of cortical skull bone from literature, was able to capture observed linear fractures in blunt indentation loading of a skullcap specimen. The FE model showed to be sensitive to modeling parameters, in particular to the constitutive parameters of the cortical tables. Nevertheless, this study provides a currently lacking strain-rate dependent material model of cranial bone that has the capacity to accurately predict linear fracture patterns. For the first time, a procedure to reconstruct occurrences of skull fractures using computational engineering techniques, capturing the all-in-all fracture initiation, propagation and final pattern, is presented.
A machine learning enhanced multi-start heuristic to efficiently solve a serial-batch scheduling problem
Authors: Uzunoglu Aykut , Gahm Christian , Tuma Axel 
Published: September 2023

AbstractSerial-batch scheduling problems are widespread in several industries (e.g., the metal processing industry or industrial 3D printing) and consist of two subproblems that must be solved simultaneously: the grouping of jobs into batches and the sequencing of the created batches. This problem’s NP-hard nature prevents optimally solving large-scale problems; therefore, heuristic solution methods are a common choice to effectively tackle the problem. One of the best-performing heuristics in the literature is the ATCS–BATCS(β) heuristic which has three control parameters. To achieve a good solution quality, most appropriate parameters must be determined a priori or within a multi-start approach. As multi-start approaches performing (full) grid searches on the parameters lack efficiency, we propose a machine learning enhanced grid search. To that, Artificial Neural Networks are used to predict the performance of the heuristic given a specific problem instance and specific heuristic parameters. Based on these predictions, we perform a grid search on a smaller set of most promising heuristic parameters. The comparison to the ATCS–BATCS(β) heuristics shows that our approach reaches a very competitive mean solution quality that is only 2.5% lower and that it is computationally much more efficient: computation times can be reduced by 89.2% on average.
Geographical variation in Canarium indicum (Burseraceae) nut characteristics across Vanuatu
Authors: Grant Elektra , Macdonell Paul , Tungon Joseph , Tabi Michael , David May , Kaku Sammy , Page Tony 
Published: September 2023

AbstractTropical forests in the Pacific region contain many tree species that bear edible nuts (kernels). Canarium indicum (canarium) is an overstorey tree indigenous to Melanesia that produces commercially valuable kernels due to their pleasant taste and high oil content. This study characterises natural variation in fruit, nut-in-shell (NIS) and kernels of C. indicum across eight islands in Vanuatu. Significant tree-to-tree variation in fruit, NIS and kernel characteristics as well as kernel recovery (kernel:NIS) was found. This variation was largely due to tree-to-tree differences and little of this variation could be attributed to location. There were significant linear correlations among fruit, NIS and kernel traits, including kernel mass with fruit mass (R2 0.57) and kernel mass with NIS mass (R2 0.56). Therefore, trees suitable for cultivation may be screened based on fruit and nut characters before making final selections based on kernel mass. Trees sampled over two fruiting seasons showed that kernel mass and kernel number varied significantly between years for 63.6% and 25.9% of the trees respectively. However, by rank order, those trees that produced larger kernels in the first year of sampling, tended to also produce relatively larger kernels in the subsequent year. The implications of these results for the further domestication of the species for planting in commercial agroforestry systems is explored.
Evaluation of Extracurricular Medical Education in Cardiothoracic Surgery and Cardiology; Students’ Opinion On Current Medical Training
Authors: el Mathari Sulayman , Arrouby Aïmane , Boulidam Noor , Kluin Jolanda 
Published: September 2023

AbstractMedical students in the Netherlands have a relatively low exposure to cardiothoracic surgery and cardiology. This results in discrepancies between starting levels of medical residents and expected standards in clinical practice. Another side effect is the international decline in interest in a career in these cardiovascular fields. To compensate for this, extracurricular education programs focused on cardiothoracic surgery and cardiology have been set up. This study aims to evaluate the impact and benefits of an extracurricular education program on students' knowledge of cardiothoracic surgery and cardiology and to explore possible factors involved in (academic) career decision making. 66 participants were enrolled in the extracurricular education program VECTOR and were included in a cross-sectional cohort study. All participants scored their familiarity with different aspects of cardiothoracic surgery and cardiology prior to and after the course. Data was analyzed using Linear regression and Wilcoxon Signed Rank testing. Participants demonstrated a significant trend towards improved familiarity with cardiothoracic surgery and cardiology after the program (p = < .001). Significant increased knowledge scores were reported for all specified subdomains after the course with an increase in academic interest in cardiology (p = < .001) and cardiothoracic surgery (p = < .001). Students revealed that clinical responsibilities and a healthy work-life balance were considered most important when deciding upon their future career. This study highlights the benefit of an extracurricular education program in cardiothoracic surgery and cardiology for undergraduates and could possibly aid students in preparing for clinical practice.
The Access to Grammatical Number in Spanish Children and Adults
Authors: Dominguez Alberto , Santos Anthea , Fu Yang 
Published: September 2023

AbstractIn Spanish, the plural form in plural dominant frequency pairs, like “diente/dientes” [tooth/teeth], occurs more frequently than the corresponding singular form. On the other hand, for the singular dominant frequency pairs such as “cometa/cometas” [kite/kites], the singular form is more common than the plural. The recognition of singular forms by adult readers is dependent on the dominance factor, while the identification of plural forms relies on the frequency of the stem. Given that age and reading experience may influence morphological processing of words, we investigate the representation of singulars and plurals in Spanish primary school children in Third Grade (8/9) and Sixth Grade (11/12) and adults through a lexical decision task. Though children’s lexical decisions were twice as slow as adults, the pattern of morphological processing was consistent across ages: dominant plural forms resulted in decision times that were comparable to those of non-dominant singular forms, while recognition of singular-dominant forms was quicker than recognition of plural non-dominant forms. It appears that singulars are accessed and stored in the lexical memory as separate entities, while plurals depend on their morphological closer relatives, in this case, the singular forms.
Measurement of Critical Temperatures, Critical Pressures and Densities of Acetone–Water Solutions for Simulation
Authors: Chen Zhirong , Yao Yang , Yuan Shenfeng , Yin Hong 
Published: September 2023

AbstractCritical temperature, critical pressure and P–T–ρ–X data of acetone–water solutions with water mole fractions in a range of 0–60% were measured to provide fundamental data for CFD simulations. Critical temperatures were determined via observing critical opalescence in fused quartz capillary tubes. Meanwhile, critical pressures were measured by heating acetone–water solutions to its critical temperature in an autoclave. The standard deviations of critical temperature and critical pressure were 0.55 K and 0.029 MPa, respectively. The results indicate that only one phase exists during mixing of acetone with water. Moreover, P–T–ρ–X data under 15 and 20 MPa in the temperature range of 460–550 K were measured in the autoclave. The relative deviation of density was 0.32%. Volume-translated Peng-Robinson and Soave–Redlich–Kwong state equations were used to illustrate the P–V–T–X relationship of acetone–water solutions, and the Peng–Robinson state equation with an average absolute relative deviation of 1.19% between fitting and experimental densities was found more accurate.
Brain image fusion using the parameter adaptive-pulse coupled neural network (PA-PCNN) and non-subsampled contourlet transform (NSCT)
Authors: Ibrahim Sa. I. , El-Tawel Gh. S. , Makhlouf M. A. 
Published: September 2023

AbstractMedical imaging has played an essential role in medicine and disease diagnosis. Medical images from a single modality contain limited data about the organ. On the other hand, images from different modalities contain valuable structural and functio nal data about an organ. Medical image fusion (MIF) strategies integrate complementary information from two medical images captured using distinct modalities. This paper offered a new multimodal MIF approach using the parameter-adaptive pulse-coupled neural networks (PA-PCNN) within the non-subsampled contourlet transform (NSCT). The NSCT decomposes those images into high- and low-frequency bands. PA-PCNN combines those bands. The fused image was created using the inverse of the NSCT approach. To prove the proposed approach’s performance, we appoint a variety of medical images like computed tomography (CT), magnetic resonance imaging (MRI), single-photon emission CT (SPECT), and positron emission tomography (PET). Our experiments use five fusion metrics to validate the proposed approach’s performance, such as entropy (EN), mutual information (MI), weighted edge information (Q$$^{AB/F}$$

A
B
/
F

), nonlinear correlation information entropy (Q$$_{ncie}$$

ncie

), and average gradient (AG). Outcomes show that the proposed approach achieves high overall performance in visual and objective characteristics when compared with five well-known MIF methods. The average values for EN, MI, Q$$^{AB/F}$$

A
B
/
F

, Q$$_{ncie}$$

ncie

, and AG with the proposed approach are 5.2144,3.1282,.6600,.8071, and 8.9874, respectively.
Strict pseudocontractions and demicontractions, their properties, and applications
Authors: Cegielski Andrzej 
Published: September 2023

AbstractWe give properties of strict pseudocontractions and demicontractions defined on a Hilbert space, which constitute wide classes of operators that arise in iterative methods for solving fixed point problems. In particular, we give necessary and sufficient conditions under which a convex combination and composition of strict pseudocontractions as well as demicontractions that share a common fixed point is again a strict pseudocontraction or a demicontraction, respectively. Moreover, we introduce a generalized relaxation of composition of demicontraction and give its properties. We“ apply these properties to prove the weak convergence of a class of algorithms that is wider than the Douglas–Rachford algorithm and projected Landweber algorithms. We have also presented two numerical examples, where we compare the behavior of the presented methods with the Douglas–Rachford method.
The long and the short of it: Russian predicate adjectives with zero copula
Authors: Nesset Tore , Janda Laura A. 
Published: September 2023

AbstractThe present article presents an empirical investigation of the choice between so-called long (e.g., prostoj ‘simple’) and short (e.g., prost ‘simple’) forms of predicate adjectives in Russian, based on data from the syntactic subcorpus of the Russian National Corpus. The data under scrutiny suggest that short forms represent the dominant option for predicate adjectives. It is proposed that long forms are descriptions of thematic participants in sentences with no complement, while short forms may take complements and describe both participants (thematic and rhematic) and situations. Within the “space of competition” where both long and short forms are well attested, it is argued that the choice of form to some extent depends on subject type, gender/number, and frequency. On the methodological level, the approach adopted in the present study may be extended to other cases of competition in morphosyntax. It is suggested that one should first “peel off” contexts where (nearly) categorical rules are at work, before one undertakes a statistical analysis of the “space of competition”.
Knowledge distillation for efficient standard scanplane detection of fetal ultrasound
Authors: Dapueto Jacopo , Zini Luca , Odone Francesca 
Published: September 2023

Abstract
In clinical practice, ultrasound standard planes (SPs) selection is experience-dependent and it suffers from inter-observer and intra-observer variability. Automatic recognition of SPs can help improve the quality of examinations and make the evaluations more objective. In this paper, we propose a method for the automatic identification of SPs, to be installed onboard a portable ultrasound system with limited computational power. The deep Learning methodology we design is based on the concept of Knowledge Distillation, transferring knowledge from a large and well-performing teacher to a smaller student architecture. To this purpose, we evaluate a set of different potential teachers and students, as well as alternative knowledge distillation techniques, to balance a trade-off between performances and architectural complexity. We report a thorough analysis of fetal ultrasound data, focusing on a benchmark dataset, to the best of our knowledge the only one available to date.

Graphical abstract
Vibration and Audio Measurements in the Monitoring of Basic Oxygen Furnace Steelmaking
Authors: Nissilä Juhani , Pylvänäinen Mika , Visuri Ville-Valtteri , Ruotsalainen Pasi , Laurila Jouni , Rankinen Atte , Palovaara Tuomas , Liedes Toni 
Published: September 2023

AbstractA basic oxygen furnace (BOF) is the main unit process for refining carbon steel. The aim of this work was to study the use of vibration and audio signal measurements to monitor, predict, and control the BOF process. Vibration and audio data from nearly 300 blows were collected and analyzed together with process variables. We could confirm high correlations between some of the process variables and vibration and audio measurements. Median filtered low-frequency (3–20 Hz) audio as well as X- and Z-direction acceleration root mean square (RMS) time series correlate with the off-gas temperature, although this is much more significant for the audio data. For Y-direction measurements (the upward direction) the correlation is negligible. The low-frequency audio and vibration data are likely related to the rate of decarburization. Median filtered mid-frequency (100–1000 Hz) audio as well as X-, Y-, and Z-direction acceleration RMS time series correlate with the lance height measurement during the interval 20–600 seconds from the beginning of oxygen blow. For the audio data, the correlation was high even without median filtering. We suggest that audio and vibration activity in this frequency range is possibly related to the formation of the metal–slag–gas foam and maybe even to slopping.
O$$^2$$-Bert: Two-Stage Target-Based Sentiment Analysis
Authors: Yan Yan , Zhang Bo-Wen , Ding Guanwen , Li Wenjie , Zhang Jie , Li Jia-Jing , Gao Wenchao 
Published: September 2023

AbstractTarget-based sentiment analysis (TBSA) is one of the most important NLP research topics for widespread applications. However, the task is challenging, especially when the targets contain multiple words or do not exist in the sequences. Conventional approaches cannot accurately extract the (target, sentiment) pairs due to the limitations of the fixed end-to-end architecture design. In this paper, we propose a framework namedO$$^2$$2-Bert, which consists ofOpinion target extraction (OTE-Bert) andOpinion sentiment classification (OSC-Bert) to complete the task in two stages. More specifically, we divide the OTE-Bert into three modules. First, an entity number prediction module predicts the number of entities in a sequence, even in an extreme situation where no entities are contained. Afterwards, with predicted number of entities, an entity starting annotation module is responsible for predicting their starting positions. Finally, an entity length prediction module predicts the lengths of these entities, and thus, accomplishes target extraction. In OSC-Bert, the sentiment polarities of extracted targets from OTE-Bert. According to the characteristics of BERT encoders, our framework can be adapted to short English sequences without domain limitations. For other languages, our approach might work through altering the tokenization. Experimental results on the SemEval 2014-16 benchmarks show that the proposed model achieves competitive performances on both domains (restaurants and laptops) and both tasks (target extraction and sentiment classification), with F1-score as evaluated metrics. Specifically, OTE-Bert achieves 84.63%, 89.20%, 83.16%, and 86.88% F1 scores for target extraction, while OSC-Bert achieves 82.90%, 80.73%, 76.94%, and 83.58% F1 scores for sentiment classification, on the chosen benchmarks. The statistics validate the effectiveness and robustness of our approach and the new “two-stage paradigm”. In future work, we will explore more possibilities of the new paradigm on other NLP tasks.
Baiting Insects with Pyrrolizidine Alkaloids (PAs): A Fieldwork-Oriented Review and Guide to PA-Pharmacophagy
Authors: Boppré Michael , Monzón Julio 
Published: September 2023

AbstractSince 1890, many observations of danaine butterflies visiting dry plants of several families in the Old and New World tropics have been published. For 50 years, it has been recognised that Danainae, along with various other insects, seek out 1,2-dehydropyrrolizidine ester alkaloids (PAs) independently of and in addition to their nutritive requirements and utilise them to increase their chances for survival and biological fitness. This represents an unusual type of insect-plant relationship (“PA-pharmacophagy”), with remarkable peculiarities but also with gaps in knowledge, many of which can be filled by employing PA-baiting. We review and analyse the history of records on the attraction of adult insects to PAs and unveil the complex background information on PA-chemistry, PA-producing plants (“PA-plants”), and PA-sequestering insects (“PA-insects”) in order to come up with practical tips for successful baiting with PAs (“PA-baiting”). Studying PA-pharmacophagy integrates taxonomy, behaviour, and ecology with evolutionary biology, chemistry, and toxicology. With basic knowledge of PA-chemistry and bearing the general peculiarities of PA-plants and PA-insects in mind, PA-baiting can be conducted easily and successfully to address many questions on the multifaceted ecology of pyrrolizidine alkaloids. We aim to encourage field researchers in the tropics to employ PA-baiting as a valuable research method in this field of integrative biology.