bluuebunny/crossref_metadata_2025_split huggingface dataset:
Solution validator and visualizer for (combined) vehicle routing and container loading problems
Authors: Krebs Corinna , Ehmke Jan Fabian 
Published: May 2023

AbstractThe optimization of cargo loading and transportation are two highly considered optimization problems (namely “3L-CVRP”). The combination of both has attracted increasing interest in the past decades. Hereby, 2D or 3D items have to be transported from one depot to a given set of customers using a homogeneous fleet of vehicles. Each route must be provided with a feasible packing plan taking various constraints into account. Combining the two optimization problems increases the complexity of the solution approaches, leading to a higher difficulty to check the results for correctness. To support the research progress and to enable transparency of solution structures, this paper provides an overview of recent literature, problem formulations, and best-known solutions. Furthermore, we introduce two open-source tools: The “Solution Validator” checks the feasibility of solutions in terms of considered constraints. The “Visualizer” provides two views and visualizes solutions. In the vehicle routing view, the tour plan and the corresponding schedule are displayed. In the loading view, the position of each item in the cargo space is demonstrated. In both views, it is possible to check the feasibility of the solution and highlight violated items. Besides the combined problem, the tool can be used also for one optimization problem (e.g. vehicle routing problem or container loading). The source codes for both tools are available at GitHub in C++ and Java and can be easily integrated into other researchers’ code.
Effects of Mixture Distribution on the Structure and Propagation of Turbulent Stratified Slot-Jet Flames
Authors: Brearley Peter , Ahmed Umair , Chakraborty Nilanjan 
Published: May 2023

AbstractThe influence of mixture stratification on the development of turbulent flames in a slot-jet configuration has been analysed using Direct Numerical Simulation data. Mixture stratification was imposed at the inlet by varying the equivalence ratio between 0.6 and 1.0 with different alignments to the reaction progress variable gradient: aligned gradients (back-supported), opposed gradients (front-supported) and misaligned gradients. An additional premixed case with a global equivalence ratio of 0.8 was simulated for comparison. The flame is shortest for the front-supported case, followed by the premixed flame, with the back-supported and misaligned gradient flames being the tallest and of comparable size. This behaviour has been explained in terms of the variations of the mean equivalence ratio within the flame and the volume-integrated reaction rate in the streamwise direction. The difference in mixture composition for these cases results in significant variations in the burning rate, flame area, flame wrinkling and flame brush thickness in the streamwise direction. The globally front-supported case has the highest volume-integrated burning rate and flame area, while the back-supported case has the lowest. The misaligned scalar gradient case exhibits qualitatively similar behaviour to that of the globally back-supported case. The burning intensity is unity for a major part of the flame length but assumes values greater than unity towards the flame tip where the effects of flame curvature become strong. All cases predominantly exhibit the premixed mode of combustion within the flamelet regime, so flamelet assumption-based reaction rate closures, originally proposed for premixed combustion, were evaluated using a priori analysis. The terms which require improved closures have been identified and existing closures have been improved where necessary. It was found that the global nature of mixture stratification does not influence the performance of the mean reaction rate closures or the parameterisation of marginal probability density functions of scalars in turbulent stratified mixture combustion.
Leveraging family history data to disentangle time-varying effects on disease risk using lifecourse mendelian randomization
Authors: Richardson Tom G , Urquijo Helena , Holmes Michael V , Davey Smith George 
Published: May 2023

AbstractLifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR) = 1.15, 95% CI = 1.07 to 1.23, P = 7.8 × 10− 5) and diabetes (OR = 1.43, 95% CI = 1.31 to 1.56, P = 9.4 × 10− 15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR = 0.87, 95% CI = 0.78 to 0.97, P = 0.01), corroborating findings from observational studies and large-scale genetic consortia.Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk.
Dietary patterns, brain morphology and cognitive performance in children: Results from a prospective population-based study
Authors: Mou Yuchan , Blok Elisabet , Barroso Monica , Jansen Pauline W. , White Tonya , Voortman Trudy 
Published: May 2023

AbstractDietary patterns in childhood have been associated with child neurodevelopment and cognitive performance, while the underlying neurobiological pathway is unclear. We aimed to examine associations of dietary patterns in infancy and mid-childhood with pre-adolescent brain morphology, and whether diet-related differences in brain morphology mediate the relation with cognition. We included 1888 and 2326 children with dietary data at age one or eight years, respectively, and structural neuroimaging at age 10 years in the Generation R Study. Measures of brain morphology were obtained using magnetic resonance imaging. Dietary intake was assessed using food-frequency questionnaires, from which we derived diet quality scores based on dietary guidelines and dietary patterns using principal component analyses. Full scale IQ was estimated using the Wechsler Intelligence Scale for Children-Fifth Edition at age 13 years. Children with higher adherence to a dietary pattern labeled as ‘Snack, processed foods and sugar’ at age one year had smaller cerebral white matter volume at age 10 (B = -4.3, 95%CI -6.9, -1.7). At age eight years, higher adherence to a ‘Whole grains, soft fats and dairy’ pattern was associated with a larger total brain (B = 8.9, 95%CI 4.5, 13.3), and larger cerebral gray matter volumes at age 10 (B = 5.2, 95%CI 2.9, 7.5). Children with higher diet quality and better adherence to a ‘Whole grains, soft fats and dairy’ dietary pattern at age eight showed greater brain gyrification and larger surface area, clustered primarily in the dorsolateral prefrontal cortex. These observed differences in brain morphology mediated associations between dietary patterns and IQ. In conclusion, dietary patterns in early- and mid-childhood are associated with differences in brain morphology which may explain the relation between dietary patterns and neurodevelopment in children.
Financial intermediation through risk sharing vs non-risk sharing contracts, role of credit risk, and sustainable production: evidence from leading countries in Islamic finance
Authors: Saleem Adil , Daragmeh Ahmad , Zahid R. M. Ammar , Sági Judit 
Published: May 2023

AbstractThe asset side of Islamic banks has two different portfolios running side by side, namely risk-sharing (PLS) and non-risk sharing (non-PLS) financing. The segregation of PLS and non-PLS financing has gathered some attention recently owning to its relative importance for sustainable economic output. This study attempts to analyze the impact of decomposed Islamic financing modes (PLS and non-PLS) with a particular focus on their impact on real economic activity. In addition, we moderated the relationship with asset quality of aggregate Islamic banking sector. Quarterly data from 2014 to 2021 have been sourced from datasets of the Islamic financial service board (IFSB), the International Monetary Fund (IMF), World Bank, and Central banks’ data streams. Eleven countries have been selected based on the highest local and global share in global Islamic financial assets. Panel data regression model has been used in this study. The findings indicate that PLS financing is a weaker driver to channelize funds. However, industrial production output is significantly affected by non-PLS financing. Further the results suggest, Islamic finance–output nexus found to have a stronger relationship in the presence of higher asset quality of Islamic banks. The results show that firms mostly rely on non-PLS financing, due to reduced asymmetry and higher transparency in non-PLS contracts compared to PLS modes. The results have implications for governing bodies of Islamic financial system in boosting risk-sharing contracts and firms to limit agency conflicts arising from fluctuating cost of financing.
Nomogram for Predicting Early Mortality after Umbilical Cord Blood Transplantation in Children with Inborn Errors of Immunity
Authors: Wang Ping , Liu Chao , Wei Zhongling , Jiang Wenjin , Sun Hua , Wang Yuhuan , Hou Jia , Sun Jinqiao , Huang Ying , Wang Hongsheng , Wang Yao , He Xinjun , Wang Xiaochuan , Qian Xiaowen , Zhai Xiaowen 
Published: May 2023

Abstract
Purpose
Pediatric patients with inborn errors of immunity (IEI) undergoing umbilical cord blood transplantation (UCBT) are at risk of early mortality. Our aim was to develop and validate a prediction model for early mortality after UCBT in pediatric IEI patients based on pretransplant factors.

Methods
Data from 230 pediatric IEI patients who received their first UCBT between 2014 and 2021 at a single center were analyzed retrospectively. Data from 2014–2019 and 2020–2021 were used as training and validation sets, respectively. The primary outcome of interest was early mortality. Machine learning algorithms were used to identify risk factors associated with early mortality and to build predictive models. The model with the best performance was visualized using a nomogram. Discriminative ability was measured using the area under the curve (AUC) and decision curve analysis.

Results
Fifty days was determined as the cutoff for distinguishing early mortality in pediatric IEI patients undergoing UCBT. Of the 230 patients, 43 (18.7%) suffered early mortality. Multivariate logistic regression with pretransplant albumin, CD4 (absolute count), elevated C-reactive protein, and medical history of sepsis showed good discriminant AUC values of 0.7385 (95% CI, 0.5824–0.8945) and 0.827 (95% CI, 0.7409–0.9132) in predicting early mortality in the validation and training sets, respectively. The sensitivity and specificity were 0.5385 and 0.8154 for validation and 0.7667 and 0.7705 for training, respectively. The final model yielded net benefits across a reasonable range of risk thresholds.

Conclusion
The developed nomogram can predict early mortality in pediatric IEI patients undergoing UCBT.
Comparing Continuous with Periodic Vital Sign Scoring for Clinical Deterioration Using a Patient Data Model
Authors: Peelen Roel V. , Eddahchouri Yassin , Koeneman Mats , Melis René , van Goor Harry , Bredie Sebastian J. H. 
Published: May 2023

AbstractTo evaluate a minute-by-minute monitoring algorithm against a periodic early warning score (EWS) in detecting clinical deterioration and workload. Periodic EWSs suffer from large measurement intervals, causing late detection of deterioration. This might be prevented by continuous vital sign monitoring with a real-time algorithm such as the Visensia Safety Index (VSI). This prospective comparative data modeling cohort study (NCT04189653) compares continuous algorithmic alerts against periodic EWS in continuous monitored medical and surgical inpatients. We evaluated sensitivity, frequency, number of warnings needed to evaluate (NNE) and time of initial alert till escalation of care (EOC): Rapid Response Team activation, unplanned ICU admission, emergency surgery, or death. Also, the percentage of VSI alerting minutes was compared between patients with or without EOC. In 1529 admissions continuous VSI warned for 55% of EOC (95% CI: 45-64%) versus 51% (95% CI: 41-61%) by periodic EWS. NNE for VSI was 152 alerts per detected EOC (95% CI: 114-190) compared to 21 (95% CI: 17-28). It generated 0.99 warnings per day per patient compared to 0.13. Time from detection score till escalation was 8.3 hours (IQR: 2.6-24.8) with VSI versus 5.2 (IQR: 2.7-12.3) hours with EWS (P=0.074). The percentage of warning VSI minutes was higher in patients with EOC than in stable patients (2.36% vs 0.81%, P<0.001). Although sensitivity of detection was not significantly improved continuous vital sign monitoring shows potential for earlier alerts for deterioration compared to periodic EWS. A higher percentage of alerting minutes may indicate risk for deterioration.
The effect of the introduction of livestock on the erosion of alpine soils: a comparison of five dating techniques applied to sediments of the Australian alpine Blue Lake
Authors: De Deckker Patrick , Hancock Gary J. , Olley Jon M. , Stanley Shawn , Hope Geoffrey 
Published: May 2023

Abstract210Pb and137Cs dating of bulk sediments obtained from the alpine Blue Lake, located in the Snowy Mountains of southeastern Australia, was applied here to date recent lacustrine sediments. In addition, the presence ofPinuspollen (a taxon introduced in Australia about 150 years ago) down to a sediment depth of 56 cm in the core is used to obtain a chronology for the upper part of the core. Accelerated Mass Spectrometry radiocarbon dates obtained from organic muds from the same core do not agree with the chronology constructed using the three other dating techniques. In addition, optically stimulated luminescence (OSL) dating of single quartz grains, from sediment-core samples collected from the same lake, was applied to date recent lacustrine sediments. The optical age of 185 ± 20 years for a sample at 60–62 cm depth, and 470 ± 50 years at 116–118 cm depth are well over 1000 years younger than the ages inferred from radiocarbon dates. We therefore infer that the ‘old’ radiocarbon ages result from carbon stored for considerable time within the catchment prior to its transport and deposition on the lake floor. As plant decomposition occurs at much slower rates in high altitude environments, these results bring into question the veracity of previously published radiocarbon dates from Blue Lake and alpine lake sediments in general. The deposition ages inferred from the210Pb-137Cs and OSL dating, and the first appearance ofPinuspollen, indicate that for the 100-year period after European settlement (from the mid 1800s to early 1900s) the sediment-accumulation rate increased by a factor of about 2, from 0.19 ± 0.01 cm yr−1to 0.35 ± 0.02 cm yr−1. In the 1900s the accumulation rate increased further to 0.60 cm yr−1. The accumulation rate was particularly rapid in the 20-year period from 1940–1960, reaching a rate 18 times higher than the pre-European rate in the mid-1950s. The increase in sedimentation rate is attributed to changes in land use resulting from European activities in the lake catchment, primarily through sheep and cattle grazing in the Blue Lake catchment.
Can Narrative Skills Improve in Autism Spectrum Disorder? A Preliminary Study with Verbally Fluent Adolescents Receiving the Cognitive Pragmatic Treatment
Authors: Hilviu Dize , Frau Federico , Bosco Francesca M. , Marini Andrea , Gabbatore Ilaria 
Published: May 2023

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental condition affecting social and communicative skills, including narrative ability, namely the description of real-life or fictive accounts of temporally and causally related events. With this study, we aimed to determine whether a communicative-pragmatic training, i.e., the version for adolescents of the Cognitive-Pragmatic Treatment, is effective in improving the narrative skills of 16 verbally fluent adolescents with ASD. We used a multilevel approach to assess pre- and post-training narrative production skills. Discourse analysis focused on micro- (i.e., mean length of utterance, complete sentences, omissions of morphosyntactic information) and macrolinguistic measures (i.e., cohesion, coherence errors, lexical informativeness). Results revealed a significant improvement in mean length of utterance and complete sentences and a decrease in cohesion errors. No significant change was found in the other narrative measures investigated. Our findings suggest that a pragmatically oriented training may be useful in improving grammatical efficiency in narrative production.
Ensemble and continual federated learning for classification tasks
Authors: Casado Fernando E. , Lema Dylan , Iglesias Roberto , Regueiro Carlos V. , Barro Senén 
Published: May 2023

AbstractFederated learning is the state-of-the-art paradigm for training a learning model collaboratively across multiple distributed devices while ensuring data privacy. Under this framework, different algorithms have been developed in recent years and have been successfully applied to real use cases. The vast majority of work in federated learning assumes static datasets and relies on the use of deep neural networks. However, in real-world problems, it is common to have a continual data stream, which may be non-stationary, leading to phenomena such as concept drift. Besides, there are many multi-device applications where other, non-deep strategies are more suitable, due to their simplicity, explainability, or generalizability, among other reasons. In this paper we present Ensemble and Continual Federated Learning, a federated architecture based on ensemble techniques for solving continual classification tasks. We propose the global federated model to be an ensemble, consisting of several independent learners, which are locally trained. Thus, we enable a flexible aggregation of heterogeneous client models, which may differ in size, structure, or even algorithmic family. This ensemble-based approach, together with drift detection and adaptation mechanisms, also allows for continual adaptation in situations where data distribution changes over time. In order to test our proposal and illustrate how it works, we have evaluated it in different tasks related to human activity recognition using smartphones.
Mean nutrient uptake depths of cereal crops change with compost incorporation into subsoil – evidence from 87Sr/86Sr ratios
Authors: Uhlig David , Berns Anne E. , Wu Bei , Amelung Wulf 
Published: May 2023

Abstract
Background and Aims
Root restricting layers often hinder crops from accessing the large reservoir of bioavailable mineral nutrients situated in subsoil. This study aims to explore changes in the mean nutrient uptake depth of cereal crops when removing root restricting layers through subsoil management.

Methods
Subsoil management was performed by deep loosening, cultivation of lucerne as deep-rooting pre-crop, and their combination with compost incorporation. Management effects were evaluated by means of shoot biomass and element concentrations in shoots and soil compartments. The mean nutrient uptake depth was fingerprinted by graphically matching the 87Sr/86Sr ratios in shoots with the 87Sr/86Sr ratios in the exchangeable fraction in soil. Nutrient uplift from depth to topsoil was inferred from element concentrations in the exchangeable fraction in soil.

Results
Shoot biomass remained constant in management and control plots. The mean nutrient uptake depth changed with subsoil management in the order: deep loosening < control < deep loosening with compost incorporation. The latter coincided with a reallocation of compost-derived Na and hence resulted in increased levels of bioavailable Na below the depth of compost incorporation, which may have led to an improved water use efficiency of the crops. Thus, Na relocation triggered the deepening of the mean uptake depth of water and nutrients. Moreover, nutrient uplift from depth to topsoil was evident 21 months after subsoiling.

Conclusion
Subsoil management by deep loosening with compost incorporation provides a sustainable use of soil resources because otherwise unused deep geogenic-derived nutrient reservoirs were additionally involved in crop nutrition.
Achieving entrepreneurial growth despite resource and capability constraints: the role of service intermediaries
Authors: Mirkovski Kristijan , von Briel Frederik , Lowry Paul Benjamin , Liu Libo 
Published: May 2023

Abstract
Entrepreneurial growth—firm growth via the introduction of new market offerings or expansion into new markets—is an important topic for entrepreneurship scholars and practitioners alike. Any firm that wants to exploit opportunities for entrepreneurial growth needs resources and capabilities that it can use to develop new market offerings or to enter new markets. However, many firms face resource and capability constraints, and research has shown that strategic partnerships can provide external pathways for firms to exploit growth opportunities despite their resource and capability constraints. All the extant external growth pathways have in common that they require firms to have some resources and capabilities, which are valuable for partners and can be jointly appropriated with them. An alternative pathway for firms to leverage external resources and capabilities—especially knowledge-based ones—that has received little attention in the literature on growth is short-term contracting of professional service firms such as accounting firms, marketing agencies, or R&D consultancies. Hence, we investigate the role of service intermediaries—professional service firms that facilitate the exchange of services among other firms—as external managers who support their clients to access and leverage a broad range of required resources and capabilities from third parties. We conducted a nested multi-case study of two service intermediaries that enabled two small, wineries from North Macedonia to successfully seize entrepreneurial growth opportunities in markets abroad despite their resource and capability deficits. We identify seven support mechanisms—need articulating, social embedding, linking, governing, clarifying, renegotiating, and mediating—through which the service intermediaries orchestrated complementary external resources and capabilities on behalf of the wineries, thereby enabling the two firms to successfully develop two new product lines for and enter two new geographic markets each. We also identify process differences depending on the stage of the opportunity evaluation process, target market characteristics, and external stakeholder involvement for which we postulate three propositions about the influence of mechanisms on the growth opportunity development. Our study offers novel insights and makes a contribution to research on entrepreneurial growth and resource orchestration.