bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Autogenous Shrinkage of Concrete Including Superabsorbent Polymers and Other Cementitious Ingredients Using Convolution-based Algorithms
Authors: Barkhordari Mohammad Sadegh , Ghavaminejad Sobhan , Tehranizadeh Mohsen 
Published: June 2024

In this paper, the effectiveness of ensemble convolution-based deep learning models is evaluated for predicting autogenous shrinkage/swelling of cementitious materials. Various ensemble learning techniques are employed, including Simple Average Ensemble, Snapshot Ensemble, and Stacked Generalization, to develop predictive models. The models are trained and evaluated using performance metrics such as Root Mean Squared Error, Coefficient of Determination, Overall Index of model performance, Mean Absolute Error, and 95% Uncertainty. The results show that the integrated stacking model (ISM) outperforms other models in terms of predictive accuracy. Furthermore, the SHapley Additive exPlanation (SHAP) technique was used to interpret the ISM model. The analysis reveals that the most influential factors affecting shrinkage predictions include time, aggregate to cement ratio (A/C), superabsorbent polymer (SAP) content, water to binder ratio, cement content, water to cement ratio, and silica fume content. Also, the ISM model was compared with models developed previously by other researchers, namely, K-Nearest Neighbors (KNN), Random Forest (RF), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB). With the lowest RMSE and MAE values, the ISM model has exceptional accuracy, demonstrating its capacity to create predictions that closely resemble observed values. Additionally, it has the highest coefficient of determination value, demonstrating its effectiveness in explaining a sizable percentage of the data variance. The Overall Index (OI) statistic shows that the ISM model performs exceptionally well, indicating that it captures more of the underlying information in the data. Additionally, it displays lower 95% confidence intervals, demonstrating greater assurance in its forecasts.
Examining the psychometric properties of the Columbia Speech Quality Instrument in cochlear implant users
Authors: Lalwani Anil K. , Chun Michael B. , Hwa Tiffany P. , Chern Alexander , Tian Likun , Chen Stephanie Y. , Stewart Michael G. , Mancuso Dean , Cellum Ilana P. 
Published: June 2024

ObjectiveAlthough speech recognition among cochlear implant (CI) users improved over the past few decades, many still report poor speech quality. Currently, there is no validated tool to measure speech quality. The objective was to examine whether a previously validated speech quality tool is applicable in the CI population using psychometric analysis.DesignCross-sectional psychometric analysis of the Columbia Speech Quality Instrument (CSQI; previously validated in normal-hearing individuals; consists of 2 original and 7 manipulated speech clips designed to accentuate selected speech characteristics) was performed in adult English-speaking CI recipients (N = 36). Subjects rated each clip using a visual analog scale (VAS) on 14 characteristics: cartoonish/not-cartoonish, clear/unclear, like/dislike, breathy/not-breathy, smooth/rough, echo-y/not-echo-y, tinny/bassy, soothing/not-soothing, natural/unnatural, mechanical/not-mechanical, hoarse/smooth, pleasant/unpleasant, male/female, and speech-like/not-speech-like. Main outcome measures included validity, reliability, and factor structure.ResultsContent validity was previously confirmed during instrument design. Construct validity by item-item correlation analysis demonstrated correlation of 12/14 items with ≥1 other retained item (r ≥ 0.35, Spearman). Reliability was confirmed by internal consistency; factor analysis using two subsets selected by Scree plot and factor loading ≥0.4 demonstrated Cronbach alpha coefficients of 0.89 and 0.74 for factors 1 and 2, respectively. Tinny/bassy and male/female were the only characteristics that did not pass construct validity or internal consistency.ConclusionsThe CSQI has strong psychometric properties in the CI population; however, our findings support removal of tinny/bass and male/female characteristics from the final instrument prior to implementation in the CI population. The CSQI can be utilized in cochlear implantees to investigate effects of changes in speech processing strategies and postoperative outcomes with different devices.
A closer look at how the dispersive liquid–liquid microextraction method works. Investigation of the effect of solvent mixture composition on the quality and stability of the cloudy state
Authors: Zaruba Serhii , Ovšonková Michaela , Makoś-Chełstowska Patrycja , Andruch Vasil 
Published: June 2024

The dispersive liquid–liquid microextraction (DLLME) is one of the most popular miniaturized extraction procedures. In this paper, the degree of dispersion and dispersion stability were studied with the aim to assess the correlations of these parameters with efficiency for the selected analytical application. The dependence between the degree of dispersion (cloudy state quality) and its stability obtained by various emulsification procedures, such as solvent-assisted emulsification (using various dispersive solvents) and mechanical emulsification (using auxiliary energies), is investigated and discussed. It was found out that the degree of dispersion depends on the type of emulsification procedure and decreases in the series: solvent-assisted (SA-) = ultrasound-assisted (UA-) &gt; air-assisted (AA-) &gt; vortex-assisted (VA-) emulsification. The emulsion stability depends on the degree of dispersion and there were 1810 and 2070 s for the most effective emulsification procedures, such us solvent-assisted and ultrasound-assisted emulsification, respectively. A comparison between the sensitivity of the analytical methods (using spectrophotometric determination of the anionic surfactants) and the degree of dispersion have been made. The sensitivity of the methods was ranked as follows: DLLME &gt; UA-LLME &gt; VA-LLME &gt; AA-LLME.
Wall motion assessment by feature tracking in pediatric patients with coronary anomalies undergoing dobutamine stress CMR
Authors: Sachdeva Shagun , Molossi Silvana , Reaves-O’Neal Dana , Masand Prakash , Doan Tam T. 
Published: June 2024

BackgroundLeft ventricular (LV) wall motion assessment is an important adjunct in addition to perfusion defects in assessing ischemic changes. This study aims to investigate the feasibility and utility of performing feature tracking (FT) in pediatric patients with coronary anomalies undergoing dobutamine stress CMR to assess wall motion abnormalities (WMA) and perfusion defects.MethodThis is a retrospective study where 10 patients with an inducible first-pass perfusion (FPP) defect and 10 without were selected. Global LV circumferential strain/strain rate (GCS/GCSR) was measured at rest and at peak stress (systole and diastole) using a commercially available feature tracking software. Peak GCS and GCSR were compared to indexed wall motion score (WMSI) between groups with and without FPP defect and in subjects with and without WMA.ResultsThe median age of patients was 13.5 years (Q1, 11 years; Q3, 15 years). Five subjects had qualitatively WMA at peak stress. A moderate correlation of GCS with WMSI at peak stress (0.48, p = 0.026) and a significant difference between GCS at rest and stress in patients with no inducible WMA (p = 0.007) were seen. No significant difference was noted in GCS between rest and stress in patients with WMA (p = 0.13). There was a larger absolute GCS/GCSR at peak stress in subjects with no inducible FPP defect or WMA.ConclusionSmaller absolute GCS and a lack of significant change in GCS at peak stress in those with inducible WMA or perfusion defect are suggestive of compromised LV deformation in subjects with inducible WMA. Given these findings, GCS derived from CMR-FT may be used to objectively assess WMA in pediatric patients undergoing stress CMR.
Type 2 diabetes mellitus in acute myocardial infarction: a persistent significant burden on long-term mortality
Authors: Bouisset Frédéric , Bataille Vincent , Schiele François , Puymirat Etienne , Fayol Antoine , Simon Tabassome , Danchin Nicolas , Ferrières Jean 
Published: June 2024

ObjectiveThe long-term impact of type 2 diabetes mellitus (T2DM) after an acute myocardial infarction (AMI) has not been thoroughly investigated yet. This study aimed to assess the long-term impact of T2DM after AMI.Research design and methodsWe analyzed the data of three nationwide observational studies from the French Registry of Acute ST-elevation and non-ST-elevation Myocardial Infarction (FAST-MI) program, conducted over a 1-month period in 2005, 2010, and 2015. Patients presenting T2DM were classified as diabetic, and patients presenting type 1 diabetes mellitus were excluded. We identified factors related to all-cause death at 1-year follow-up and divided 1,897 subjects into two groups, paired based on their estimated 1-year probability of death as determined by a logistic regression model.ResultsA total of 9,181 AMI patients were included in the analysis, among them 2,038 (22.2%) had T2DM. Patients with diabetes were significantly older (68.2 ± 12.0 vs. 63.8 ± 14.4, p &lt; 0.001) and had a higher prevalence of a prior history of percutaneous coronary intervention (PCI), coronary artery bypass grafting (CABG), or heart failure (22.5% vs. 13.0%, 7.1% vs. 3.1% and 6.7 vs. 3.8% respectively, p &lt; 0.001 for all). Even after matching two groups of 1,897 patients based on propensity score for their 1-year probability of death, diabetes remained associated with long-term mortality, with an HR of 1.30, 95%CI (1.17–1.45), p &lt; 0.001.ConclusionsT2DM per se has an adverse impact on long-term survival after myocardial infarction. Independently of the risk of short-term mortality, patients with diabetes who survived an AMI have a 30% higher risk of long-term mortality.
Variable gearing at the ankle during walking in adults and young children: implications for foot development and evolution
Authors: Zeininger Angel , Schmitt Daniel , Jensen Jody L. , Shapiro Liza J. 
Published: June 2024

Introduction: The human foot has evolved over the past seven million years from a relatively mobile, grasping appendage to a highly derived structure with a heel pad and longitudinal arch that can absorb shock at heel strike and weight-bearing yet also function as a powerful lever at toe-off. It has been proposed that the modern human foot evolved to allow our species to use “variable gearing” during walking and running. In this model, the gears of the human foot are defined relative to the ankle center of rotation as R, the distance from the ground reaction resultant vector, and r, the distance from the calf muscle vector. The gear ratio defines the torque generated to propel the body or stretch the triceps surae muscles. We test the hypothesis that variable gearing is associated with modern human pedal anatomy and a heel-to-toe rollover that allows a shift from “low gear” to “high gear” during stance.Methods: Using force plate and video analysis, we examined variable gearing in adults and children engaging in adult heel strike (AHS = 35), flat foot contact (FFC = 39), or initial heel contact (IHC = 26).Results and Discussion: Our hypothesis was partly supported. Although variable gearing was observed in IHC steps and was greater than in FFC steps, it was not as developed as in AHS steps. This may be related to anatomical and motor control differences between juvenile and adult feet, suggesting that adult anatomy, including a high arch, and neural control are critical for full use of variable gearing and that this feature would have evolved in later hominins around two million years ago with the appearance of a fully modern foot.
Interpretable machine learning identifies metabolites associated with glomerular filtration rate in type 2 diabetes patients
Authors: An Tian-Feng , Zhang Zhi-Peng , Xue Jun-Tang , Luo Wei-Ming , Li Yang , Fang Zhong-Ze , Zong Guo-Wei 
Published: June 2024

ObjectiveThe co-occurrence of kidney disease in patients with type 2 diabetes (T2D) is a major public health challenge. Although early detection and intervention can prevent or slow down the progression, the commonly used estimated glomerular filtration rate (eGFR) based on serum creatinine may be influenced by factors unrelated to kidney function. Therefore, there is a need to identify novel biomarkers that can more accurately assess renal function in T2D patients. In this study, we employed an interpretable machine-learning framework to identify plasma metabolomic features associated with GFR in T2D patients.MethodsWe retrieved 1626 patients with type 2 diabetes (T2D) in Liaoning Medical University First Affiliated Hospital (LMUFAH) as a development cohort and 716 T2D patients in Second Affiliated Hospital of Dalian Medical University (SAHDMU) as an external validation cohort. The metabolite features were screened by the orthogonal partial least squares discriminant analysis (OPLS-DA). We compared machine learning prediction methods, including logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost). The Shapley Additive exPlanations (SHAP) were used to explain the optimal model.ResultsFor T2D patients, compared with the normal or elevated eGFR group, glutarylcarnitine (C5DC) and decanoylcarnitine (C10) were significantly elevated in GFR mild reduction group, and citrulline and 9 acylcarnitines were also elevated significantly (FDR&lt;0.05, FC &gt; 1.2 and VIP &gt; 1) in moderate or severe reduction group. The XGBoost model with metabolites had the best performance: in the internal validate dataset (AUROC=0.90, AUPRC=0.65, BS=0.064) and external validate cohort (AUROC=0.970, AUPRC=0.857, BS=0.046). Through the SHAP method, we found that C5DC higher than 0.1μmol/L, Cit higher than 26 μmol/L, triglyceride higher than 2 mmol/L, age greater than 65 years old, and duration of T2D more than 10 years were associated with reduced GFR.ConclusionElevated plasma levels of citrulline and a panel of acylcarnitines were associated with reduced GFR in T2D patients, independent of other conventional risk factors.
The positive association between hyperuricemia and polycystic ovary syndrome and analysis of related factors
Authors: Gong Zhentao , Sun Yanwen , Zhang Lingshan , Zhu Xiaoyong , Shi Yingli 
Published: June 2024

PurposeTo examine the potential association between polycystic ovary syndrome (PCOS) and hyperuricemia and to elucidate the underlying contributory factors.MethodsRetrospective study on 603 women with PCOS and 604 women without PCOS. Anthropometric features, reproductive hormone profiles, and metabolic parameters were measured and compared between two groups of patients. Examinations of correlations between SUA levels and other parameters were conducted to discern potential correlations.ResultsBoth serum uric acid levels and the incidence of hyperuricemia exhibited statistically significant elevations in women with PCOS when compared to their counterparts without PCOS. Nonetheless, this statistical difference was not found between the obese subgroup after stratifying study subjects by body mass index (BMI). Pearson’s correlation analysis underscored the prominence of BMI as a robust factor influencing SUA levels in women, regardless of their PCOS status. Furthermore, multivariable linear regression model demonstrated significant positive associations between SUA levels and several variables, namely dehydroepiandrosterone sulfate (DHEA-S), free androgen index (FAI), total cholesterol (TC), triglycerides (TG), free fatty acids (FFA), fasting insulin (FINS), homeostatic model assessment of insulin resistance (HOMA-IR), area under the curve for insulin (AUC-I), alanine aminotransferase (ALT), and aspartate aminotransferase (AST). Additionally, it is noteworthy that the prevalence of hyperuricemia exhibited a positive association with fasting plasma glucose (FPG) levels, while conversely, it displayed a negative association with estradiol (E2) levels.ConclusionsPCOS is associated with a significant elevation of SUA level and hyperuricemia prevalence. HA, IR, and dyslipidemia may be the mediators in the pathogenesis of hyperuricemia in women with PCOS.
Impact of breastfeeding on risk of glucose intolerance in early postpartum after gestational diabetes
Authors: Vanlaer Yana , Minschart Caro , Vrolijk Hannah , Van Crombrugge Paul , Moyson Carolien , Verhaeghe Johan , Devlieger Roland , Vandeginste Sofie , Verlaenen Hilde , Vercammen Chris , Maes Toon , Dufraimont Els , Roggen Nele , De Block Christophe , Jacquemyn Yves , Mekahli Farah , De Clippel Katrien , Van Den Bruel Annick , Loccufier Anne , Van Pottelbergh Inge , Myngheer Nele , Abrams Pascale , Vinck Wouter , Leuridan Liesbeth , Driessens Sabien , Billen Jaak , Matthys Christophe , Bogaerts Annick , Laenen Annouschka , Mathieu Chantal , Benhalima Katrien 
Published: June 2024

AimsTo determine the impact of breastfeeding on the risk of postpartum glucose intolerance in women with gestational diabetes.MethodsSub-analysis of two multi-centric prospective cohort studies (BEDIP-N and MELINDA) in 1008 women with gestational diabetes. Data were collected during pregnancy and at a mean of 12 weeks postpartum. Multivariate logistic regression was used to estimate the effect of breastfeeding on glucose intolerance, with adjustment for ethnicity, education, income, professional activity and BMI.ResultsOf all participants, 56.3% (567) breastfed exclusively, 10.1% (102) gave mixed milk feeding and 33.6% (339) did not breastfeed. Mean breastfeeding duration was 3.8 ± 2.4 and 3.7 ± 2.1 months in the breastfeeding and mixed milk feeding groups (p=0.496). The rate of glucose intolerance was lower in both the breastfeeding [22.3% (126)] and mixed milk feeding [25.5% (26)] groups compared to the no breastfeeding group [29.5% (100)], with an adjusted OR of 0.7 (95% CI 0.5–1.0) for glucose intolerance in the breastfeeding group compared to no breastfeeding group and an adjusted OR of 0.7 (95% CI 0.4–1.2) for the mixed milk feeding group compared to the no breastfeeding group. Postpartum, breastfeeding women had a lower BMI, less often postpartum weight retention, lower fasting triglycerides, less insulin resistance and a higher insulin secretion-sensitivity index-2 than the mixed milk feeding and no breastfeeding group. The mixed milk feeding group was more often from an non-White background, had a lower blood pressure and lower fasting triglycerides compared to the no breastfeeding group.ConclusionsBreastfeeding (exclusive and mixed milk feeding) is associated with less glucose intolerance and a better metabolic profile in early postpartum in women with gestational diabetes.
Analysis of single nucleotide polymorphisms of the metabotropic glutamate receptors in a transgender population
Authors: Fernández Rosa , Ramírez Karla , Lorente-Bermúdez Roberto , Gómez-Gil Esther , Mora Mireia , Guillamon Antonio , Pásaro Eduardo 
Published: June 2024

IntroductionGender incongruence (GI) is characterized by a marked incongruence between an individual’s experienced/expressed gender and the assigned sex at birth. It includes strong displeasure about his or her sexual anatomy and secondary sex characteristics. In some people, this condition produces a strong distress with anxiety and depression named gender dysphoria (GD). This condition appears to be associated with genetic, epigenetics, hormonal as well as social factors. Given that L-glutamate is the major excitatory neurotransmitter in the central nervous system, also associated with male sexual behavior as well as depression, we aimed to determine whether metabotropic glutamate receptors are involved in GD.MethodsWe analyzed 74 single nucleotide polymorphisms located at the metabotropic glutamate receptors (mGluR1, mGluR3, mGluR4, mGluR5, mGluR7 and mGluR8) in 94 transgender versus 94 cisgender people. The allele and genotype frequencies were analyzed by c2 test contrasting male and female cisgender and transgender populations. The strength of the associations was measured by binary logistic regression, estimating the odds ratio (OR) for each genotype. Measurement of linkage disequilibrium, and subsequent measurement of haplotype frequencies were also performed considering three levels of significance: P ≤ 0.05, P ≤ 0.005 and P ≤ 0.0005. Furthermore, false positives were controlled with the Bonferroni correction (P ≤ 0.05/74 = 0.00067).ResultsAfter analysis of allele and genotypic frequencies, we found twenty-five polymorphisms with significant differences at level P ≤ 0.05, five at P ≤ 0.005 and two at P ≤ 0.0005. Furthermore, the only two polymorphisms (rs9838094 and rs1818033) that passed the Bonferroni correction were both related to the metabotropic glutamate receptor 7 (mGluR7) and showed significant differences for multiple patterns of inheritance. Moreover, the haplotype T/G [OR=0.34 (0.19–0.62); P&lt;0.0004] had a lower representation in the transgender population than in the cisgender population, with no evidence of sex cross-interaction.ConclusionWe provide genetic evidence that the mGluR7, and therefore glutamatergic neurotransmission, may be involved in GI and GD.
Phosphorus in farm roadway substrates: contrasting spatial and temporal patterns in dairy and beef farms
Authors: Sifundza Lungile Senteni , Murnane John G. , Daly Karen , Lopez-Sangil Luis , Leach Simon , Tuohy Patrick , Cardiff John , Fenton Owen 
Published: June 2024

The mobilisation and impact of roadway runoff on dairy farms has been established as a sub-component of the nutrient transfer continuum. It is acknowledged that fresh nutrient sources deposited on roadways dominate runoff and recent work has shown that available phosphorus (P) in roadway substrates is also an important source component. The objectives of this study were to understand spatial and temporal available P concentrations in roadway substrate (aggregate and soil mix) across dairy and beef farms during the open (February–October, when cows use the roadway network and fields) and closed (November–January, when cows were housed) periods and identify locations which could be considered critical source areas (CSA). For the study, roadway substrate samples were taken at 18 locations on each farm, across eight sampling periods, and were analysed for available P. Results showed that mean available P concentrations (Morgan’s P) in the sampling locations ranged from 15.9 to 101.4 mg L-1 for the Dairy Farm, from 4.1 to 59.4 mg L-1 for Beef Farm 1 and from 6.3 to 23.2 mg L-1 for Beef Farm 2. In open period, the results showed that mean available P concentrations were 75.4 ± 30.9, 14.9 ± 3.2 and 13.4 ± 2.5 mg L-1 for the Dairy Farm, Beef Farm 1 and Beef Farm 2, respectively. In closed period, the mean available P were 40.3 ± 17.2, 10.4 ± 1.0 and 9.8 ± 0.2 mg L-1 for Dairy Farm, Beef Farm 1 and Beef Farm 2, respectively. Overall, P concentrations on the Dairy Farm roadways was up to 4 times greater than that in the Beef Farms’ roadways. Compared to soils in adjacent fields, P concentrations in the Dairy and Beef Farms roadways was up-to 7 and 2 times higher, respectively. Critical roadway sections that required mitigation were two in the Dairy Farm, one in Beef Farm 1 and two in Beef Farm 2. In addition to fresh faeces and urine (i.e., dominant source of nutrients in farm roadways), this study showed that nutrient enriched roadway materials are a labile P source. Thus, future mitigation of roadway runoff must consider all roadway nutrient sources, including livestock fresh excreta as well as used roadway surface materials.