bluuebunny/crossref_metadata_2025 huggingface dataset:
Prognostic value of immunotherapy-induced organ inflammation assessed on 18FDG PET in patients with metastatic non-small cell lung cancer
Authors: Humbert Olivier , Bauckneht Matteo , Gal Jocelyn , Paquet Marie , Chardin David , Rener David , Schiazza Aurelie , Genova Carlo , Schiappa Renaud , Zullo Lodovica , Rossi Giovanni , Martin Nicolas , Hugonnet Florent , Darcourt Jacques , Morbelli Silvia , Otto Josiane
Published: May 2022

Purpose

We evaluated the prognostic value of immunotherapy-induced organ inflammation observed on 18FDG PET in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs).

Methods

Data from patients with IIIB/IV NSCLC included in two different prospective trials were analyzed. 18FDG PET/CT exams were performed at baseline (PETBaseline) and repeated after 7–8 weeks (PETInterim1) and 12–16 weeks (PETInterim2) of treatment, using iPERCIST for tumor response evaluation. The occurrence of abnormal organ 18FDG uptake, deemed to be due to ICPI-related organ inflammation, was collected.

Results

Exploratory cohort (Nice, France): PETInterim1 and PETInterim2 revealed the occurrence of at least one ICPI-induced organ inflammation in 72.8% of patients, including midgut/hindgut inflammation (33.7%), gastritis (21.7%), thyroiditis (18.5%), pneumonitis (17.4%), and other organ inflammations (9.8%). iPERCIST tumor response was associated with improved progression-free survival (p < 0.001). iPERCIST tumor response and immuno-induced gastritis assessed on PET were both associated with improved overall survival (OS) (p < 0.001 and p = 0.032). Combining these two independent variables, we built a model predicting patients’ 2-year OS with a sensitivity of 80.3% and a specificity of 69.2% (AUC = 72.7). Validation cohort (Genova, Italy): Immuno-induced gastritis (19.6% of patients) was associated with improved OS (p = 0.04). The model built previously predicted 2-year OS with a sensitivity and specificity of 72.0% and 63.6% (AUC = 70.7) and 3-year OS with a sensitivity and specificity of 69.2% and 80.0% (AUC = 78.2).

Conclusion

Immuno-induced gastritis revealed by early interim 18FDG PET in around 20% of patients with NSCLC treated with ICPI is a novel and reproducible imaging biomarker of improved OS.
Development and validation of a radiomic model for the diagnosis of dopaminergic denervation on [18F]FDOPA PET/CT
Authors: Comte Victor , Schmutz Hugo , Chardin David , Orlhac Fanny , Darcourt Jacques , Humbert Olivier
Published: May 2022

Purpose

FDOPA PET shows good performance for the diagnosis of striatal dopaminergic denervation, making it a valuable tool for the differential diagnosis of Parkinsonism. Textural features are image biomarkers that could potentially improve the early diagnosis and monitoring of neurodegenerative parkinsonian syndromes. We explored the performances of textural features for binary classification of FDOPA scans.

Methods

We used two FDOPA PET datasets: 443 scans for feature selection, and 100 scans from a different PET/CT system for model testing. Scans were labelled according to expert interpretation (dopaminergic denervation versus no dopaminergic denervation). We built LASSO logistic regression models using 43 biomarkers including 32 textural features. Clinical data were also collected using a shortened UPDRS scale.

Results

The model built from the clinical data alone had a mean area under the receiver operating characteristics (AUROC) of 63.91. Conventional imaging features reached a maximum score of 93.47 but the addition of textural features significantly improved the AUROC to 95.73 (p < 0.001), and 96.10 (p < 0.001) when limiting the model to the top three features: GLCM_Correlation, Skewness and Compacity. Testing the model on the external dataset yielded an AUROC of 96.00, with 95% sensitivity and 97% specificity. GLCM_Correlation was one of the most independent features on correlation analysis, and systematically had the heaviest weight in the classification model.

Conclusion

A simple model with three radiomic features can identify pathologic FDOPA PET scans with excellent sensitivity and specificity. Textural features show promise for the diagnosis of parkinsonian syndromes.
Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging
Authors: Sun Tao , Wang Zhenguo , Wu Yaping , Gu Fengyun , Li Xiaochen , Bai Yan , Shen Chushu , Hu Zhanli , Liang Dong , Liu Xin , Zheng Hairong , Yang Yongfeng , El Fakhri Georges , Zhou Yun , Wang Meiyun
Published: May 2022

Introduction

Distinct physiological states arise from complex interactions among the various organs present in the human body. PET is a non-invasive modality with numerous successful applications in oncology, neurology, and cardiology. However, while PET imaging has been applied extensively in detecting focal lesions or diseases, its potential in detecting systemic abnormalities is seldom explored, mostly because total-body imaging was not possible until recently.

Methods

In this context, the present study proposes a framework capable of constructing an individual metabolic abnormality network using a subject’s whole-body 18F-FDG SUV image and a normal control database. The developed framework was evaluated in the patients with lung cancer, the one discharged after suffering from Covid-19 disease, and the one that had gastrointestinal bleeding with the underlying cause unknown.

Results

The framework could successfully capture the deviation of these patients from healthy subjects at the level of both system and organ. The strength of the altered network edges revealed the abnormal metabolic connection between organs. The overall deviation of the network nodes was observed to be highly correlated to the organ SUV measures. Therefore, the molecular connectivity of glucose metabolism was characterized at a single subject level.

Conclusion

The proposed framework represents a significant step toward the use of PET imaging for identifying metabolic dysfunction from a systemic perspective. A better understanding of the underlying biological mechanisms and the physiological interpretation of the interregional connections identified in the present study warrant further research.
Sensitivity to water deficit of the second stage of fruit growth in late mandarin trees
Authors: Berríos Pablo , Temnani Abdelmalek , Zapata Susana , Forcén-Muñoz Manuel , Franco José Antonio , Pérez-Pastor Alejandro
Published: May 2022

In citrus fruits, phases I and II of fruit growth are sensitive to water deficit, and for this reason, deficit irrigation (DI) has been usually restricted to the final ripening phase. However, the optimal timing and intensity of stress during sensitive phases have not been clearly defined. The main objective was to determine the sensitivity of the second stage of fruit growth to water deficit in adult mandarin trees, and to explore the suitability of different soil and plant water status indicators, including the leaf-scale spectrum, according to the water stress level. Four irrigation treatments were tested: a control (CTL) irrigated at ~ 80% of ETc during the entire crop cycle, and three irrigation suppression treatments, in which no water was applied during the end of phase I and the beginning of phase II (DI1), the second half of phase II (DI2), and phase III of fruit growth (DI3), respectively. Phase II of fruit growth can be considered as a non-critical phenological period until the fruit reaches approximately 60% of its final size, with the application of a water deficit using an irrigation threshold of midday stem water potential of − 1.8 MPa, and a cumulative water stress integral close to 28 MPa day. The novel visible infrared ratio index (VIRI) showed a high sensitivity for trees subjected to moderate and severe water stress and can be complementarily used to estimate on a larger temporal and spatial scale the plant water status. Wavelengths in the short-wave infrared (SWIR) region allowed differentiation between non-stressed, moderately, and severely water-stressed trees, and can be considered as an initial basis for determining the water status of mandarin trees at various stress intensities by remote sensing.
Pre- and post-harvest evapotranspiration, carbon exchange and water use efficiency of a mature peach orchard in semi-arid climate
Authors: Testi Luca , Orgaz Francisco , López-Bernal Álvaro , Villalobos Francisco J.
Published: May 2022

Better knowledge of the evapotranspiration and carbon exchange of fruit trees is needed to optimize the trade-off between water use and carbon assimilation and to better understand the role of agriculture in the biogeochemical cycles. In this work, we measured water and carbon fluxes with eddy covariance and transpiration with sap flow in a drip-irrigated peach orchard of 70% ground cover located in southern Spain for 2 years. The empirically measured crop coefficient (Kc) under good watering conditions in the summer ranged from 1 to 1.1. The daytime net ecosystem exchange (NEE) flux of the orchard averaged 30 g CO2 m2 day−1 during the period of maximum activity in July. The daytime ecosystem water use efficiency (WUE) of the orchard reached a minimum in late June, flattened around 4 g CO2 L−1 throughout the summer, and increased in autumn, but was unaffected by fruit removal or post-harvest irrigation reduction imposed by the farm (30% reduction). The response of instantaneous peach ecosystem WUE to VPD was also investigated. Both Kc, NEE, leaf water potential and stomatal conductance decreased sharply after harvest. Transpiration data from some purposely over-irrigated experimental trees demonstrated that the post-harvest alterations we found were not caused by fruit removal, but are result of mild water stress originated by the irrigation reduction. Hence, the often-observed alterations in water relations after harvest in well-watered trees were not observed in this experiment. This work adds insight on peach irrigation efficiency and on the contribution of orchards to agricultural carbon budgets.
The role of computer-assisted radiographer reporting in lung cancer screening programmes
Authors: Hall Helen , Ruparel Mamta , Quaife Samantha L. , Dickson Jennifer L. , Horst Carolyn , Tisi Sophie , Batty James , Woznitza Nicholas , Ahmed Asia , Burke Stephen , Shaw Penny , Soo May Jan , Taylor Magali , Navani Neal , Bhowmik Angshu , Baldwin David R. , Duffy Stephen W. , Devaraj Anand , Nair Arjun , Janes Sam M.
Published: May 2022

Objectives

Successful lung cancer screening delivery requires sensitive, timely reporting of low-dose computed tomography (LDCT) scans, placing a demand on radiology resources. Trained non-radiologist readers and computer-assisted detection (CADe) software may offer strategies to optimise the use of radiology resources without loss of sensitivity. This report examines the accuracy of trained reporting radiographers using CADe support to report LDCT scans performed as part of the Lung Screen Uptake Trial (LSUT).

Methods

In this observational cohort study, two radiographers independently read all LDCT performed within LSUT and reported on the presence of clinically significant nodules and common incidental findings (IFs), including recommendations for management. Reports were compared against a ‘reference standard’ (RS) derived from nodules identified by study radiologists without CADe, plus consensus radiologist review of any additional nodules identified by the radiographers.

Results

A total of 716 scans were included, 158 of which had one or more clinically significant pulmonary nodules as per our RS. Radiographer sensitivity against the RS was 68–73.7%, with specificity of 92.1–92.7%. Sensitivity for detection of proven cancers diagnosed from the baseline scan was 83.3–100%. The spectrum of IFs exceeded what could reasonably be covered in radiographer training.

Conclusion

Our findings highlight the complexity of LDCT reporting requirements, including the limitations of CADe and the breadth of IFs. We are unable to recommend CADe-supported radiographers as a sole reader of LDCT scans, but propose potential avenues for further research including initial triage of abnormal LDCT or reporting of follow-up surveillance scans.

Key Points

• Successful roll-out of mass screening programmes for lung cancer depends on timely, accurate CT scan reporting, placing a demand on existing radiology resources.

• This observational cohort study examines the accuracy of trained radiographers using computer-assisted detection (CADe) software to report lung cancer screening CT scans, as a potential means of supporting reporting workflows in LCS programmes.

• CADe-supported radiographers were less sensitive than radiologists at identifying clinically significant pulmonary nodules, but had a low false-positive rate and good sensitivity for detection of confirmed cancers.
A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes—A Pilot Study
Authors: Ng Kelvin S. , Leckebusch Gregor C. , Hodges Kevin I.
Published: May 2022

Extreme Mei-yu rainfall (MYR) can cause catastrophic impacts to the economic development and societal welfare in China. While significant improvements have been made in climate models, they often struggle to simulate local-to-regional extreme rainfall (e.g., MYR). Yet, large-scale climate modes (LSCMs) are relatively well represented in climate models. Since there exists a close relationship between MYR and various LSCMs, it might be possible to develop causality-guided statistical models for MYR prediction based on LSCMs. These statistical models could then be applied to climate model simulations to improve the representation of MYR in climate models.

In this pilot study, it is demonstrated that skillful causality-guided statistical models for MYR can be constructed based on known LSCMs. The relevancy of the selected predictors for statistical models are found to be consistent with the literature. The importance of temporal resolution in constructing statistical models for MYR is also shown and is in good agreement with the literature. The results demonstrate the reliability of the causality-guided approach in studying complex circulation systems such as the East Asian summer monsoon (EASM). Some limitations and possible improvements of the current approach are discussed. The application of the causality-guided approach opens up a new possibility to uncover the complex interactions in the EASM in future studies.
Operative versus conservative treatment of acute Achilles tendon ruptures: preliminary results of clinical outcome, kinematic MRI and contrast-enhanced ultrasound
Authors: Kosiol Juana , Keiler Alexander , Loizides Alexander , Gruber Hannes , Henninger Benjamin , Bölderl Andreas , Gruber Leonhard
Published: May 2022

Introduction

There is no uniform consensus on the gold standard therapy for acute Achilles tendon rupture. The aim of this pilot study was to compare operative and conservative treatment regarding imaging findings and clinical outcome.

Materials and methods

Surgically or conservatively treated patients with acute Achilles tendon rupture were retrospectively evaluated. Differences in tendon length and diameter with and without load were analysed using kinematic MRI, tendon perfusion, structural alterations, movement and scar tissue by means of grey-scale and contrast-enhanced ultrasound (CEUS). Intra- and interobserver agreement were recorded.

Results

No significant difference was detected regarding clinical outcome, B mode ultrasonography, contrast-enhanced sonography or MRI findings, although alterations in MRI-based measurements of tendon elasticity were found for both groups. Considerable elongation and thickening of the injured tendon were detected in both groups.

Conclusion

Both, conservative and surgical treatment showed comparable outcomes in our preliminary results and may suggest non-inferiority of a conservative approach.
Effect of intra-nasal nitrilotriacetic acid trisodium salt in lowering elevated calcium cations and improving olfactory dysfunction in COVID-19 patients
Authors: Abdelazim Mohamed H. , Abdelazim Ahmed H. , Ismaiel Wael F. , Alsobky Mahmoud E. , Younes Ahmed , Hadeya Abdelgawad M. , Ramzy Sherif , Shahin Mohammed
Published: May 2022

Purpose

An association between COVID-19 and olfactory dysfunction has been noted in many patients worldwide. The olfactory adaptation process leads to an increase in intracellular calcium cation levels. Nitrilotriacetic acid trisodium salt has high selective chelation for calcium cations from olfactory mucus. The aim of this work is to test the effect of an intranasal nitrilotriacetic acid trisodium salt to lower the elevated calcium cations in COVID-19 patients with relevant symptoms of olfactory dysfunction.

Methods

Fifty-eight COVID-19 adult patients with relevant symptoms of olfactory dysfunction were enrolled in a prospective randomized controlled trial. They received a nasal spray containing either 0.9% sodium chloride or 2% nitrilotriacetic acid trisodium salt. Olfactory function was assessed before and after treatment using the Sniffin’ Sticks test. Quantitative analysis of calcium cation concentration in nasal secretions was performed using a carbon paste ion-selective electrode.

Results

After the application of nitrilotriacetic acid trisodium salt compared to sodium chloride, a significant improvement from functional anosmia to healthy normosmia with significant decrease in calcium cation concentration was observed.

Conclusions

Further collaborative research is needed to fully investigate the effect of an intranasal nitrilotriacetic acid trisodium salt in the treatment of olfactory disorders.
Predicting clinical scores in Huntington’s disease: a lightweight speech test
Authors: Riad Rachid , Lunven Marine , Titeux Hadrien , Cao Xuan-Nga , Hamet Bagnou Jennifer , Lemoine Laurie , Montillot Justine , Sliwinski Agnes , Youssov Katia , Cleret de Langavant Laurent , Dupoux Emmanuel , Bachoud-Lévi Anne-Catherine
Published: May 2022

Objectives

Using brief samples of speech recordings, we aimed at predicting, through machine learning, the clinical performance in Huntington’s Disease (HD), an inherited Neurodegenerative disease (NDD).

Methods

We collected and analyzed 126 samples of audio recordings of both forward and backward counting from 103 Huntington’s disease gene carriers [87 manifest and 16 premanifest; mean age 50.6 (SD 11.2), range (27–88) years] from three multicenter prospective studies in France and Belgium (MIG-HD (ClinicalTrials.gov NCT00190450); BIO-HD (ClinicalTrials.gov NCT00190450) and Repair-HD (ClinicalTrials.gov NCT00190450). We pre-registered all of our methods before running any analyses, in order to avoid inflated results. We automatically extracted 60 speech features from blindly annotated samples. We used machine learning models to combine multiple speech features in order to make predictions at individual levels of the clinical markers. We trained machine learning models on 86% of the samples, the remaining 14% constituted the independent test set. We combined speech features with demographics variables (age, sex, CAG repeats, and burden score) to predict cognitive, motor, and functional scores of the Unified Huntington’s disease rating scale. We provided correlation between speech variables and striatal volumes.

Results

Speech features combined with demographics allowed the prediction of the individual cognitive, motor, and functional scores with a relative error from 12.7 to 20.0% which is better than predictions using demographics and genetic information. Both mean and standard deviation of pause durations during backward recitation and clinical scores correlated with striatal atrophy (Spearman 0.6 and 0.5–0.6, respectively).

Interpretation

Brief and examiner-free speech recording and analysis may become in the future an efficient method for remote evaluation of the individual condition in HD and likely in other NDD.
Validation of an autonomous artificial intelligence–based diagnostic system for holistic maculopathy screening in a routine occupational health checkup context
Authors: Font Octavi , Torrents-Barrena Jordina , Royo Dídac , García Sandra Banderas , Zarranz-Ventura Javier , Bures Anniken , Salinas Cecilia , Zapata Miguel Ángel
Published: May 2022

Purpose

This study aims to evaluate the ability of an autonomous artificial intelligence (AI) system for detection of the most common central retinal pathologies in fundus photography.

Methods

Retrospective diagnostic test evaluation on a raw dataset of 5918 images (2839 individuals) evaluated with non-mydriatic cameras during routine occupational health checkups. Three camera models were employed: Optomed Aurora (field of view — FOV 50º, 88% of the dataset), ZEISS VISUSCOUT 100 (FOV 40º, 9%), and Optomed SmartScope M5 (FOV 40º, 3%). Image acquisition took 2 min per patient. Ground truth for each image of the dataset was determined by 2 masked retina specialists, and disagreements were resolved by a 3rd retina specialist. The specific pathologies considered for evaluation were “diabetic retinopathy” (DR), “Age-related macular degeneration” (AMD), “glaucomatous optic neuropathy” (GON), and “Nevus.” Images with maculopathy signs that did not match the described taxonomy were classified as “Other.”

Results

The combination of algorithms to detect any abnormalities had an area under the curve (AUC) of 0.963 with a sensitivity of 92.9% and a specificity of 86.8%. The algorithms individually obtained are as follows: AMD AUC 0.980 (sensitivity 93.8%; specificity 95.7%), DR AUC 0.950 (sensitivity 81.1%; specificity 94.8%), GON AUC 0.889 (sensitivity 53.6% specificity 95.7%), Nevus AUC 0.931 (sensitivity 86.7%; specificity 90.7%).

Conclusion

Our holistic AI approach reaches high diagnostic accuracy at simultaneous detection of DR, AMD, and Nevus. The integration of pathology-specific algorithms permits higher sensitivities with minimal impact on its specificity. It also reduces the risk of missing incidental findings. Deep learning may facilitate wider screenings of eye diseases.
Price of robustness optimization through demand forecasting with an application to waste management
Authors: Gentile Claudio , Pinto Diego Maria , Stecca Giuseppe
Published: May 2022

Robust optimization can be effectively used to protect production plans against uncertainties. This is particularly important in sectors where variability is inherent the process to be planned. The drawback of robust optimization is the chance of producing over-conservative solutions with respect to the real occurrences of the stochastic parameters. Information can be added in order to better control the extra cost resulting from considering the parameter variability. This work investigates how demand forecasting can be used in conjunction with robust optimization in order to achieve an optimal planning while considering demand uncertainties. In the proposed procedure, forecast is used to update uncertain parameters of the robust model. Moreover, the robustness budget is optimized at each planned stage in a rolling planning horizon. In this way, the parameters of the robust model can be dynamically updated tacking information from the data. The study is applied to a reverse logistics case, where the planning of sorting for material recycling is affected by uncertainties in the demand, consisting of waste material to be sorted and recycled. Results are compared with a standard robust optimization approach, using real case instances, showing potentialities of the proposed method.
Assessing cloud QoS predictions using OWA in neural network methods
Authors: Hussain Walayat , Gao Honghao , Raza Muhammad Raheel , Rabhi Fethi A. , Merigó Jose M.
Published: May 2022

Quality of Service (QoS) is the key parameter to measure the overall performance of service-oriented applications. In a myriad of web services, the QoS data has multiple highly sparse and enormous dimensions. It is a great challenge to reduce computational complexity by reducing data dimensions without losing information to predict QoS for future intervals. This paper uses an Induced Ordered Weighted Average (IOWA) layer in the prediction layer to lessen the size of a dataset and analyse the prediction accuracy of cloud QoS data. The approach enables stakeholders to manage extensive QoS data better and handle complex nonlinear predictions. The paper evaluates the cloud QoS prediction using an IOWA operator with nine neural network methods—Cascade-forward backpropagation, Elman backpropagation, Feedforward backpropagation, Generalised regression, NARX, Layer recurrent, LSTM, GRU and LSTM-GRU. The paper compares results using RMSE, MAE, and MAPE to measure prediction accuracy as a benchmark. A total of 2016 QoS data are extracted from Amazon EC2 US-West instance to predict future 96 intervals. The analysis results show that the approach significantly decreases the data size by 66%, from 2016 to 672 records with improved or equal accuracy. The case study demonstrates the approach's effectiveness while handling complexity, reducing data dimension with better prediction accuracy.
Development of root resorption during orthodontic tooth movement after cleft repair using different grafting materials in rats
Authors: Möhlhenrich Stephan Christian , Kniha Kristian , Magnuska Zuzanna , Chhatwani Sachin , Hermanns-Sachweh Benita , Gremse Felix , Hölzle Frank , Danesh Gholamreza , Modabber Ali
Published: May 2022

Objective

The aim of the present study was to investigate the influence of three grafting materials for cleft repair on orthodontic tooth movement in rats.

Materials and methods

Artificial alveolar clefts were created in 21 Wistar rats and were repaired 4 weeks later using autografts, human xenografts and synthetic bone substitute (beta-tricalcium phosphate/hydroxyapatite [β-TCP/HA]). A further 4 weeks later, the first molar was moved into the reconstructed maxilla. Microfocus computed tomography (μCT) was performed six times (T0–T5) to assess the tooth movement and root resorption. After 8 weeks, the affected reconstructed jaw was resected for histopathological investigation.

Results

Total distances reached ranged from 0.82 ± 0.72 mm (β-TCP/HA) to 0.67 ± 0.27 mm (autograft). The resorption was particularly determined at the mesiobuccal root. Descriptive tooth movement slowed and root resorption increased slightly. However, neither the radiological changes during tooth movement (µCT T1 vs. µCT T5: autograft 1.85 ± 0.39 mm3 vs. 2.38 ± 0.35 mm3, p = 0.30; human xenograft 1.75 ± 0.45 mm3 vs. 2.17 ± 0.26 mm3, p = 0.54; β-TCP/HA: 1.52 ± 0.42 mm3 vs. 1.88 ± 0.41 mm3, p = 0.60) nor the histological differences after tooth movement (human xenograft: 0.078 ± 0.05 mm2; β-TCP/HA: 0.067 ± 0.049 mm2; autograft: 0.048 ± 0.015 mm2) were statistically significant.

Conclusion

The autografts, human xenografts or synthetic bone substitute used for cleft repair seem to have a similar effect on the subsequent orthodontic tooth movement and the associated root resorptions.

Clinical relevance

Development of root resorptions seems to have a secondary role in choosing a suitable grafting material for cleft repair.
Data-driven decision management of urban underground infrastructure through groundwater-level time-series cluster analysis: the case of Milan (Italy)
Authors: Sartirana Davide , Rotiroti Marco , Bonomi Tullia , De Amicis Mattia , Nava Veronica , Fumagalli Letizia , Zanotti Chiara
Published: May 2022

The significant increase in urbanization has resulted in greater use of the subsurface in urban planning and, therefore, increased interaction between groundwater and underground infrastructure. Numerical models are the primary tool adopted to manage the resulting problems; however, their construction is time- and cost-consuming. Groundwater-level time-series analysis can be a complementary method, as this data-driven approach does not require an extensive understanding of the geological and boundary conditions, even if providing insights into the hydrogeologic behaviour. Thus, a data-driven approach was adopted to analyse groundwater time-series of the shallow aquifer, occupied by several underground structures, beneath Milan city (Northern Italy). Statistical (Mann-Kendall and Sen’s slope estimator, autocorrelation and cross-correlation, hierarchical cluster analysis) and geospatial techniques were used to detect the potential variables influencing the groundwater levels of 95 monitoring wells, covering the period 2005–2019. A general rising trend of the water table was identified, with local hydrogeologic differences in the western and southernmost areas. Based on time-series analysis results, four management areas have been identified. These areas could act as future geographic units with specific groundwater management strategies. In particular, subsurface public car parks can be classified with respect to groundwater flooding as (1) not submerged, (2) possibly critical, or (3) submerged at different groundwater conditions. According to these outcomes, targeted guidelines for constructing new car parks have been elaborated for each management area. The methodology proved to be efficient in improving the urban conceptual model and helping stakeholders design the planned underground development, considering groundwater aspects.
Integrated uncertainty quantification and sensitivity analysis of single-component dynamic column breakthrough experiments
Authors: Ward Adam , Pini Ronny
Published: May 2022

We have carried out the traditional analysis of a set of dynamic breakthrough experiments on the $$\hbox {CO}_2$$

CO
2

/He system adsorbing onto activated carbon by fitting a 1D dynamic column breakthrough model to the transient experimental profiles. We have quantified the uncertainties in the fitted model parameters using the techniques of Bayesian inference, and have propagated these parametric uncertainties through the dynamic model to assess the robustness of the modelling. We have found significant uncertainties in the outlet mole fraction profile, internal temperature profile and internal adsorption profiles of approximately $$\pm 15\%$$

±
15
%

. To assess routes to reduce these uncertainties we have applied a global variance-based sensitivity analysis to the dynamic model using the Sobol method. We have found that approximately $$70\%$$

70
%

of the observed variability in the modelling outputs can be attributed to uncertainties in the adsorption isotherm parameters that describe its temperature dependence. We also make various recommendations for practitioners, using the developed Bayesian statistical tools, regarding the choice of the isotherm model, the choice of the fitting data for the extraction of system specific parameters and the simplification of the wall energy balance.
Deformable image registration with attention-guided fusion of multi-scale deformation fields
Authors: He Zhiquan , He Yupeng , Cao Wenming
Published: May 2022

Deformable medical image registration plays a crucial role in theoretical research and clinical application. Traditional methods suffer from low registration accuracy and efficiency. Recent deep learning-based methods have made significant progresses, especially those weakly supervised by anatomical segmentations. However, the performance still needs further improvement, especially for images with large deformations. This work proposes a novel deformable image registration method based on an attention-guided fusion of multi-scale deformation fields. Specifically, we adopt a separately trained segmentation network to segment the regions of interest to remove the interference from the uninterested areas. Then, we construct a novel dense registration network to predict the deformation fields of multiple scales and combine them for final registration through an attention-weighted field fusion process. The proposed contour loss and image structural similarity index (SSIM) based loss further enhance the model training through regularization. Compared to the state-of-the-art methods on three benchmark datasets, our method has achieved significant performance improvement in terms of the average Dice similarity score (DSC), Hausdorff distance (HD), Average symmetric surface distance (ASSD), and Jacobian coefficient (JAC). For example, the improvements on the SHEN dataset are 0.014, 5.134, 0.559, and 359.936, respectively.
Integrated Quadrant Analysis: A New Method for Analyzing Turbulent Coherent Structures
Authors: Mangan Mary Rose , Oldroyd Holly J. , Paw U Kyaw Tha , Clay Jenae’ M. , Drake Stephen A. , Kelley Jason , Suvočarev Kosana
Published: May 2022

Integrated quadrant analysis is a novel technique to identify and to characterize the trajectory and strength of turbulent coherent structures in the atmospheric surface layer. By integrating the three-dimensional velocity field characterized by traditional quadrant analysis with respect to time, the trajectory history of individual coherent structures can be preserved with Eulerian turbulence measurements. We develop a method to identify the ejection phase of coherent structures based on turbulence kinetic energy (TKE). Identifying coherent structures within a time series using TKE performs better than identifying them with the streamwise and vertical velocity components because some coherent structures are dominated by the cross-stream velocity component as they pass the sensor. By combining this identification method with the integrated quadrant analysis, one can animate or plot the trajectory of individual coherent structures from high-frequency velocity measurements. This procedure links a coherent ejection with the subsequent sweep and quiescent period in time to visualize and quantify the strength and the duration of a coherent structure. We develop and verify the method of integrated quadrant analysis with data from two field studies: the Eclipse Boundary Layer Experiment (EBLE) in Corvallis, Oregon in August 2017 (grass field) and the Vertical Cherry Array Experiment (VACE) in Linden, California in November 2019 (cherry orchard). The combined TKE identification method and integrated quadrant analysis are promising additions to conditional sampling techniques and coherent structure characterization because the identify coherent structures and couple the sweep and ejection components in space. In an orchard (VACE), integrated quadrant analysis verifies each coherent structure is dominated by a sweep. Conversely, above the roughness sublayer (EBLE), each coherent structure is dominated by an ejection.
Characterizing experiences of non-medical switching to trastuzumab biosimilars using data from internet-based surveys with US-based oncologists and breast cancer patients
Authors: Papautsky Elizabeth Lerner , Carlson Martha , Johnson Sheila M. , Montague Hannah , Attai Deanna J. , Lustberg Maryam B.
Published: May 2022

Purpose

To characterize current experiences with communication and decision-making practices when non-medical switching to a biosimilar trastuzumab is proposed or required by cancer center or insurer.

Methods

We developed and launched 60- and 51-item internet surveys to elicit US breast cancer patient and medical oncologist lived experiences with trastuzumab biosimilars and patient information needs and seeking practices. We recruited participants using social media and administered via REDCap in 2020–2021.

Results

143 breast cancer patients and 33 medical oncologists completed the surveys. 63.9% patients reported having switched to a trastuzumab biosimilar and 40.8% reported receiving no prior notification about switching. 44% of patients reported learning about biosimilars primarily through self-directed learning and 41% wanting more time to discuss with oncologist. None of the oncologists reported that the decision to switch a patient to a biosimilar was initiated by them, but rather more frequently by the insurer (45.2%). About 54.8% reported not receiving any pharmaceutical manufacturer material related to the selected biosimilar. Patients and oncologists diverged in their responses to items regarding patient opportunities to ask questions, adequacy of resources, effectiveness of treatment, patient worry, and magnitude of change.

Conclusion

There is a need for tailored and effective patient and oncologist information and education on trastuzumab biosimilars, along with improved healthcare communication regarding switching. The discrepancy between patient-reported experiences and oncologist perceptions of the patient experience, suggests a lack of adequate information that may be a challenge not only to the uptake of trastuzumab biosimilars, but to the patient-oncologist relationship.
Child’s Play: Examining the Association Between Time Spent Playing and Child Mental Health
Authors: Dodd Helen F. , Nesbit Rachel J. , FitzGibbon Lily
Published: May 2022

It is theorised that adventurous play offers learning opportunities that help to prevent mental health problems in children. In this study, data from two samples is used to examine associations between the time that children aged 5–11 years spent playing adventurously and their mental health. For comparison, time spent playing unadventurously and time spent playing outdoors are also examined. Study 1 includes a sample of 417 parents, Study 2 includes data from a nationally representative sample of 1919 parents. Small, significant associations between adventurous play and internalising problems, as well as positive affect during the first UK-wide Covid-19 lockdown, were found; children who spend more time playing adventurously had fewer internalising problems and more positive affect during the Covid-19 lockdown. Study 2 showed that these associations were stronger for children from lower income families than for children from higher income families. The results align with theoretical hypotheses about adventurous play.
The performance effects of international study placements versus work placements
Authors: Jones Chris , Wang Yuan
Published: May 2022

To be competitive, universities across the world are embedding an international perspective into every layer of an institution’s operational structure. For higher education (HE) providers that offer sandwich degrees (4-year undergraduate courses with a compulsory placement after the second year), this allows students to choose a range of options. Students can enter the labour market for one year, or they can go overseas to study at a foreign institution. For some students, it might even be possible to do both. However, regarding final year degree performance, which option leads to higher student performance? In this paper, we aim to shed light on this empirical question. Our results are drawn from Aston University (UK) which is a world-leading University in Advanced Technology. Overall, using a large student dataset, we find that for students who have a compulsory placement built into their degree programme, the work placement has a more powerful impact on student performance compared to an international study placement abroad. Our findings have important implications for universities across the world that offer sandwich degrees to their students.
From Unobservable to Observable: Scientific Realism and the Discovery of Radium
Authors: Allzén Simon
Published: May 2022

I explore the process of changes in the observability of entities and objects in science and how such changes impact two key issues in the scientific realism debate: the claim that predictively successful elements of past science are retained in current scientific theories, and the inductive defense of a specific version of inference to the best explanation with respect to unobservables. I provide a case-study of the discovery of radium by Marie Curie in order to show that the observability of some entities can change and that such changes are relevant for arguments seeking to establish the reliability of success-to-truth inferences with respect to unobservables.
Numerical Calculation of the Thermodynamic Properties of Silver Erbium Alloys for Use in Metallic Magnetic Calorimeters
Authors: Herbst Matthew , Barth Arnulf , Fleischmann Andreas , Gastaldo Loredana , Hengstler Daniel , Kovac Neven , Mantegazzini Federica , Reifenberger Andreas , Enss Christian
Published: May 2022

Using dilute silver erbium alloys as a paramagnetic temperature sensor in metallic magnetic calorimeters (MMCs) has the advantage of the host material not having a nuclear quadrupole moment, in contrast to the alternative of using gold erbium alloys. We present numerical calculations of the specific heat and magnetization of Ag:Er, which are necessary for designing and optimizing MMCs using this type of alloy as sensor material. The parameter ranges we consider are temperatures between $$1\,{\text {{mK}}}$$

1

mK

and $$1\,{\text {{K}}}$$

1

K

, external magnetic fields of up to $$20\,{\text {{mT}}}$$

20

mT

, and erbium concentrations of up to $$2000\,{\text {{ppm}}}$$

2000

ppm

. The system is dominated by an interplay of crystal field effects, Zeeman splitting, and the RKKY interaction between erbium ions, with certain specific constellations of erbium ions having noticeable effects on the specific heat. Increasing the external magnetic field or assuming a decreased strength of the RKKY interaction leads to a higher magnetization and a narrowing of the main Schottky peak, while changes in the erbium concentration can be well described by parameter scaling.
Ductal Carcinoma in Situ: Molecular Changes Accompanying Disease Progression
Authors: Wilson Gemma M. , Dinh Phuong , Pathmanathan Nirmala , Graham J. Dinny
Published: May 2022

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive ductal carcinoma (IDC), whereby if left untreated, approximately 12% of patients develop invasive disease. The current standard of care is surgical removal of the lesion, to prevent potential progression, and radiotherapy to reduce risk of recurrence. There is substantial overtreatment of DCIS patients, considering not all DCIS lesions progress to invasive disease. Hence, there is a critical imperative to better predict which DCIS lesions are destined for poor outcome and which are not, allowing for tailored treatment. Active surveillance is currently being trialed as an alternative management practice, but this approach relies on accurately identifying cases that are at low risk of progression to invasive disease. Two DCIS-specific genomic profiling assays that attempt to distinguish low and high-risk patients have emerged, but imperfections in risk stratification coupled with a high price tag warrant the continued search for more robust and accessible prognostic biomarkers. This search has largely turned researchers toward the tumor microenvironment. Recent evidence suggests that a spectrum of cell types within the DCIS microenvironment are genetically and phenotypically altered compared to normal tissue and play critical roles in disease progression. Uncovering the molecular mechanisms contributing to DCIS progression has provided optimism for the search for well-validated prognostic biomarkers that can accurately predict the risk for a patient developing IDC. The discovery of such markers would modernize DCIS management and allow tailored treatment plans. This review will summarize the current literature regarding DCIS diagnosis, treatment, and pathology.
Tracing the origins of incunabula through the automatic identification of fonts in digitised documents
Authors: Lacasta Javier , Nogueras-Iso Javier , Zarazaga-Soria F. Javier , Pedraza-Gracia Manuel-José
Published: May 2022

Incunabulaare the texts printed mainly during the second half of 15th century that are a key cultural element in a revolutionary period of the history and evolution of the book and the printing. In these books, the identification of their origin largely affects its academic, cultural, patrimonial, and economical value. This paper proposes a process to automate the identification of the origin of a digitised incunable document using the Proctor/Haebler method, a commonly established procedure in the field. This process has been validated with a selected dataset obtained from the incunabula collection at the digital repository of the University of Zaragoza.
Oxyprenylated secondary metabolites: a survey of their innovative extraction methodologies
Authors: Fiorito Serena , Collevecchio Chiara , Epifano Francesco , Genovese Salvatore , Palumbo Lucia
Published: May 2022

Oxyprenylated secondary metabolites of plant, fungal, and microbial origin have emerged as biologically active natural compounds with a great potential for the next future. While originally obtained from the respective sources merely by conventional techniques of the phytochemical practice like maceration, percolation, and Soxhlet extractions, during the last five years novel and alternative experimental protocols to get such chemicals in higher yields and purity degree and/or in form of enriched phytopreparations have been developed. Such new processes include ultrasounds and microwaves assisted extractions, use of auxiliary agents like deep eutectic solvents and QuEChERS, employment of novel extractive solvents like supercritical CO2 and subcritical butane, accelerated solvent extractions, and finally extractions in the heterogeneous phase using solid supports. All these new methodologies proved to be very powerful and efficient in terms of yields and selectivity in concentrating classes of secondary metabolites from the respective matrices, comparing favorably to the already and widespread “classic” extraction techniques. All the developed processes can be framed in a green chemical context stating the employment of nontoxic, non-pollutant, environmentally friend, recyclable, easy to handle and to store solvents and reagents. The aim of this review article is to make a detailed survey of these alternative extraction processes for oxyprenylated secondary metabolites providing not only the most relevant examples of the recent literature, but also concrete suggestions and addresses to accomplish future research activities in the same field.
On the possibilities of presenting the research performance of an institute over a long period of time: the case of the Institute of Information Science at the University of Graz in Austria
Authors: Reichmann Gerhard , Schlögl Christian
Published: May 2022

In this paper, we demonstrate how the research performance of a university institute (department) over a long period of time can be presented and evaluated. Using the example of an information science institute at a German-speaking university, namely the (former) Institute of Information Science at the University of Graz in Austria, we present the research performance of this institute over the entire duration of its existence (33 years) in different ways. In order to be able to contextualize its performance, we compare it with that of some related institutions from all over the world. Due to the high effort involved in collecting data and the lack of data availability, the comparison must be limited to a period of a few years and—with regard to the institutions from non-German-speaking countries—to the Web of Science as data source. In this international comparison, the institute in the focus of the study shows relatively poor results. As can be seen, the choice of the data source has a major influence on the evaluation results. Especially for institutes from non-English-speaking countries with publications in their respective national languages, an exclusive use of international databases, such as Web of Science or Scopus, cannot fully consider the whole research performance. The use of personal publication lists or local research databases seems almost indispensable in these cases. A major novelty of this article is the handling of a very long evaluation period and the discussion of different ways of subdividing it. With regard to the presentation of the results, in the case of a long observation period, not only should annual and overall results be presented, but also multi-year comparisons be performed. In this way, year-by-year fluctuations can be smoothed out, and longer-term developments can be well represented.