bluuebunny/crossref_metadata_2025 huggingface dataset:
Impacts of shelterbelt systems on pasture production and soil bacterial and fungal communities in agricultural fields
Authors: Nguyen Thi Bao‐Anh , Henao Lina A. , Li Zelin , Cheng Long , Hu Hang‐Wei
Published: July 2023

Introduction

Shelterbelts, which provide protection for livestock and crops against severe weather conditions, have been recognised as important contributors to increased crop yields. Soil microorganisms play important roles in nutrient cycling, soil health and plant performance, thereby exerting significant influence on ecological services in terrestrial ecosystems. However, impacts of shelterbelts on soil microbial communities in pasture ecosystems remain poorly studied.

Materials and Methods

Here, we assessed the effect of shelterbelts (composed of Eucalyptus and native shrubs) on the pasture and nutrient productivity as well as soil bacterial and fungal communities at four distances from the shelterbelts with two different heights in two fields during spring and summer by applying amplicon sequencing, physicochemical and nutritional value analyses.

Results

The results showed that the shelterbelt height, distances from shelterbelts, seasons and their interactive effects substantially affected pasture yield, neutral detergent fibre, metabolisable energy and crude protein yields, but did not increase the pasture productivity in the rows adjacent to the shelterbelts. We also identified that the alpha diversity of bacteria and fungi did not significantly change across distances from the shelterbelts in both fields, but the community structure of soil bacteria and fungi was significantly influenced by distances from the shelterbelts. Interestingly, soil calcium (Ca) and shelterbelts were identified as top predictors of fungal community while soil pH and Ca was key drivers of bacterial community.

Conclusion

Our study provides novel knowledge in the impact of shelterbelts on pasture and nutritional production and soil microbial communities, which contributes to appropriate application and strategic management of the windbreak systems in agriculture production.
Development of Pyr‐TPA as Interfacial Passivation Layer Enabling Efficient and Stable n–i–p Perovskite Solar Cells
Authors: Liang Lusheng , Zhang Zilong , Li Yuheng , Yu Xuteng , Lin Fulin , Xu Yuan , Lan Zhang , Cavazzini Marco , Pozzi Gianluca , Orlandi Simonetta , Gao Peng
Published: July 2023

Interfacial passivation is a crucial technique for improving the performance of perovskite solar cells (PSCs) by suppressing nonradiative recombination. Incorporating electron‐rich functional groups into organic semiconductors can combine the advantages of Lewis bases and organic semiconductors to achieve defect passivation of perovskite films and interfacial charge transport improvement simultaneously. However, interlayers generated by organic semiconductors are often destroyed during the deposition of the hole transport layer (HTL) in n–i–p PSCs. This prevents the accurate evaluation of interfacial passivation effects. Herein, a pyromellitic derivative, 2,6‐bis(4‐(bis(4‐methoxyphenyl)amino)phenyl)pyrrolo[3,4‐f]isoindole‐1,3,5,7(2 H,6 H)‐tetraone (Pyr‐TPA), containing four carbonyl groups that can passivate defects and enhance hole transport while simultaneously acting as a stable interlayer at the perovskite/HTL interface due to its ideal solubility profile is introduced. As a result, Pyr‐TPA as an interlayer can minimize nonradiative recombination loss, resulting in a power conversion efficiency of up to 24.16%. Additionally, the interfacial Pyr‐TPA passivation layer also exhibits strong resistance to moisture and ion migration, leading to enhanced long‐term ambient stability of PSCs based on this material. Findings provide valuable insights into developing efficient and stable PSCs with simple and effective organic semiconductor interfacial passivation materials.
Machine Learning as an Enabler for Automated Assistance Systems for the Classification of Tool Wear on Milling Tools
Authors: Papenberg Björn , Hogreve Sebastian , Tracht Kirsten
Published: July 2023

Tool wear and the decision when to replace tools is a universal challenge in the metal cutting industry. While the tool wear state can be accurately determined using optical measuring methods, the tool wear of milling tools is often examined by the CNC-machine operators, especially in small and medium enterprises. In order to increase the accuracy with which tool wear can be correctly classified, it is advisable to use an assistance system that automatically removes the tools from a buffer, examines the tool wear state based on visual sensor data and sorts them into separate boxes according to the classification result. In this context, the accurate classification of tool wear is a key capability that can be enabled using methods of machine learning, based on image data that was labeled by human experts. In this paper different machine learning models are examined based on their ability to classify images of milling tools into the categories worn and not worn. The EfficientNet_b0 model achieves an accuracy of 91.47% and outperforms human experts that classified similar images by 22.87%.
Input and Tracking System for Augmented Reality-Assisted Robot Programming
Authors: Brand Michael , Gravert Marvin , Wulff Lukas Antonio , Schüppstuhl Thorsten
Published: July 2023

Augmented Reality-assisted robot programming systems (ARRPS) aim to make the programming of industrial robots more efficient by providing an AR-based human machine interface that allows operators to program robots intuitively and quickly. This work aims to contribute to the field by presenting an input and tracking system based on the VIVE Lighthouse technology that can act as a basis for ARRPS systems, improving maturity, costs and accessibility. To evaluate the system, ARRPS core functionality has been implemented so as to demonstrate its basic feasibility. An extensive evaluation of the system accuracy has been conducted, as this is one of the key criteria for potential adoption of the technology. The feasibility could be successfully demonstrated and it could be shown that the end-to-end mean absolute error of the robot path point placement amounts to 11 mm in a workspace of 0.6 × 0.6 × 0.25 m3 volume. Finally, the robustness and setup time of the system still need to be improved.
A Methodology for Developing a Model for Energy Prediction in Additive Manufacturing Exemplified by High-Speed Laser Directed Energy Deposition
Authors: Ehmsen S. , Glatt M. , Linke B. S. , Aurich J. C.
Published: July 2023

The need for energy-efficient manufacturing technologies is growing due to the increasing pressure from climate change, consumers, and regulations. Additive manufacturing is claimed to be a sustainable manufacturing technology, especially for individualized products and small batches. To include the energy demand in the decision-making process on whether a part should be manufactured by additive or rather by subtractive or formative manufacturing, the energy demand which arises during manufacturing of a part must be predicted before the manufacturing process. For this, individual energy prognosis models are needed for each individual AM system. This paper, therefore, presents a methodology that enables users to develop a customized model to predict the energy demand of their AM System.

Four steps are necessary to create a model for energy prediction. First, the structure of the investigated system has to be captured. Here the subsystems and their corresponding process parameters are identified. Then the build cycle is analyzed and divided into several process steps in which the power consumption of the subsystems repeatedly follows the same pattern. Afterwards, those process parameters, that have a significant influence on the energy demand of each subsystem are identified within full factorial design of experiments and subsequently analyzed in detail. In the final step, individual models are developed for the energy demand of each subsystem for each process step. These individual models are then aggregated to create an overall model. The application of the methodology is also demonstrated and validated by the example of high-speed laser directed energy deposition.
A Holistic Framework for Factory Planning Using Reinforcement Learning
Authors: Klar M. , Mertes J. , Glatt M. , Ravani B. , Aurich J. C.
Published: July 2023

The generation of an optimized factory layout is a central element of the factory planning process. The generated factory layout predefines multiple characteristics of the future factory, such as the operational costs and proper resource allocations. However, manual layout planning is often time and resource-consuming and involves creative processes. In order to reduce the manual planning effort, automated, computer-aided planning approaches can support the factory planner to deal with this complexity by generating valuable solutions in the early phase of factory layout planning. Novel approaches have introduced Reinforcement Learning based planning schemes to generate optimized factory layouts. However, the existing research mainly focuses on the technical feasibility and does not highlight how a Reinforcement Learning based planning approach can be integrated into the factory planning process. Furthermore, it is unclear which information is required for its application. This paper addresses this research gap by presenting a holistic framework for Reinforcement Learning based factory layout planning that can be applied at the initial planning (greenfield planning) stages as well as in the restructuring (brownfield planning) of a factory layout. The framework consists of five steps: the initialization of the layout planning problem, the initialization of the algorithm, the execution of multiple training sets, the evaluation of the training results, and a final manual planning step for a selected layout variant. Each step consists of multiple sub-steps that are interlinked by an information flow. The framework describes the necessary and optional information for each sub-step and further provides guidance for future developments.
Häusliche Gewalt und ihre psychischen Folgen während der COVID-19-Pandemie – Zentrale Befunde aus dem deutschsprachigen Raum
Authors: Lotzin Annett , Flechsenhar Aleya , Garthus-Niegel Susan , Georg Anna Katharina , Holl Julia , von Hülsen Leonie , Kenntemich Laura , Kliem Sören , Kröger Christoph , Mack Judith T. , Mojahed Amera , Nunius Sabine , Schröder Johanna , Seitz Katja , von Thadden Alexandra , Volkert Jana , Zrnic Novakovic Irina , Lueger-Schuster Brigitte
Published: July 2023

Die Auswirkungen traumatischer Erfahrungen auf die psychische Gesundheit während der COVID-19-Pandemie sind im deutschsprachigen Raum bisher unzureichend diskutiert worden. Vor diesem Hintergrund wurde im Auftrag der Deutschsprachigen Gesellschaft für Psychotraumatologie (DeGPT) eine Arbeitsgruppe aus wissenschaftlich und praktisch tätigen Fachkolleginnen und -kollegen gebildet. Ziel der Arbeitsgruppe war es, zentrale Forschungsbefunde zur Prävalenz von häuslicher Gewalt und damit einhergehende psychische Belastungen während der COVID-19-Pandemie im deutschsprachigen Raum zusammenzufassen und deren Implikationen zu diskutieren. Darüber hinaus sollten Zusammenhänge zwischen vorbestehenden Kindheitstraumata und psychischen Belastungen während der Pandemie beleuchtet werden. Hierzu wurde die vorliegende narrative Übersichtsarbeit erstellt.

Die Ergebnisse der durchgeführten Studien weisen auf hohe Prävalenzen häuslicher Gewalt während der COVID-19-Pandemie hin, die jedoch überwiegend den Prävalenzen vor der Pandemie entsprechen. Erwachsene, die während der Pandemie oder bereits in ihrer Kindheit oder Jugend interpersonaler Gewalt ausgesetzt waren, wiesen während der Pandemie eine erhöhte psychische Belastung im Vergleich zu Erwachsenen ohne Gewalterfahrungen auf. Eine Reihe an Faktoren (z. B. weibliches Geschlecht, geringe Sozialkontakte) erhöhten das Risiko für psychische Belastung und Symptome einer posttraumatischen Belastungsstörung während der Pandemie. Nach diesen Ergebnissen stellen Menschen mit aktuellen, aber auch zurückliegenden Gewalterfahrungen eine vulnerable Gruppe dar, die während einer Pandemie besondere Unterstützungsbedarfe aufweist.
[18F]FDG PET/MRI combined with chest HRCT in early cancer detection: a retrospective study of 3020 asymptomatic subjects
Authors: Peng Liling , Liao Yi , Zhou Rui , Zhong Yan , Jiang Han , Wang Jing , Fu Yu , Xue Le , Zhang Xiaohui , Sun Mingxiang , Feng Gang , Meng Zhaoting , Peng Sisi , He Xuexin , Teng Gaojun , Gao Xin , Zhang Hong , Tian Mei
Published: July 2023

Purpose

PET/MRI has become an important medical imaging approach in clinical practice. In this study, we retrospectively investigated the detectability of fluorine-18 (18F)-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ([18F]FDG PET/MRI) combined with chest computerized tomography (CT) for early cancer in a large cohort of asymptomatic subjects.

Methods

This study included a total of 3020 asymptomatic subjects who underwent whole-body [18F]FDG PET/MRI and chest HRCT examinations. All subjects received a 2–4-year follow-up for cancer development. Cancer detection rate, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the [18F]FDG PET/MRI with or without chest HRCT were calculated and analyzed.

Results

Sixty-one subjects were pathologically diagnosed with cancers, among which 59 were correctly detected by [18F]FDG PET/MRI combined with chest HRCT. Of the 59 patients (32 with lung cancer, 9 with breast cancer, 6 with thyroid cancer, 5 with colon cancer, 3 with renal cancer, 1 with prostate cancer, 1 with gastric cancer, 1 with endometrial cancer, and 1 with lymphoma), 54 (91.5%) were at stage 0 or stage I (according to the 8th edition of the tumor-node-metastasis [TNM] staging system), 33 (55.9%) were detected by PET/MRI alone (27 with non-lung cancers and 6 with lung cancer). Cancer detection rate, sensitivity, specificity, PPV, and NPV for PET/MRI combined with chest CT were 2.0%, 96.7%, 99.6%, 83.1%, and 99.9%, respectively. For PET/MRI alone, the metrics were 1.1%, 54.1%, 99.6%, 73.3%, and 99.1%, respectively, and for PET/MRI in non-lung cancers, the metrics were 0.9%, 93.1%, 99.6%, 69.2%, and 99.9%, respectively.

Conclusions

[18F]FDG PET/MRI holds great promise for the early detection of non-lung cancers, while it seems insufficient for detecting early-stage lung cancers. Chest HRCT can be complementary to whole-body PET/MRI for early cancer detection.

Trial registration

ChiCTR2200060041. Registered 16 May 2022. Public site: https://www.chictr.org.cn/index.html
Upper Eyelid Blepharoplasty: Surgical Techniques and Results—Systematic Review and Meta-analysis
Authors: Rodrigues Catarina , Carvalho Francisco , Marques Marisa
Published: July 2023

Background

Upper eyelid blepharoplasty is a surgical procedure that aims to correct the typical changes that occur with aging to the periorbital area. The outcomes of this surgery are aesthetic, as well as functional. Many studies have described an impact on the cornea, intraocular pressure, dry eye syndrome, and visual quality. The aim of this systematic review is to compare the different surgical techniques and their outcomes.

Methods

The authors performed a literature review through online databases PubMed, Web of Science, Clinicaltrials.gov, and CENTRAL libraries. Information was collected about the surgery techniques and the functional and aesthetic outcomes as well as complications of the interventions. Six types of upper blepharoplasty surgery were studied. Data were analyzed using Cochrane RevMan.

Results

Twenty studies were included in our systematic review and nine in our meta-analysis. We presented results about intraocular pressure, central corneal thickness, flattest keratometry, steepest keratometry, corneal astigmatism, visual acuity, Schirmer test 1 and 2, tear film break-up time and the ocular surface disease index questionnaire, according to type of surgery. Our meta-analysis showed no significant results.

Conclusions

No significant results were found; however, many studies reported an impact of upper blepharoplasty surgery in the outcomes studied. Only a small number of complications were reported, and patients were satisfied with the aesthetic outcomes.

Level of Evidence III

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors https://www.springer.com/00266.
The Effect of Microwave and Radiofrequency Ablation (MWA/RFA) on Liver Volume in Patients with Primary and Secondary Liver Tumours: A Retrospective Analysis
Authors: Knapen Robrecht R. M. M. , Korenblik Remon , James Sinead , Dams Glenn , Olij Bram , de Boer Sanne W. , van Dam Ronald M. , van der Leij Christiaan
Published: July 2023

Purpose

It is known that thermal liver ablation can induce liver hypertrophy. However, exact impact in liver volume remains unclear. The aim of this study is to assess the influence of radiofrequency or microwave ablation (RFA/MWA) on liver volume in patients with primary and secondary liver lesions. Findings can be relevant in assessing the potential extra benefit of thermal liver ablation in preoperatively performed liver hypertrophy inducing procedures, such as portal vein embolization (PVE).

Methods

Between January 2014–May 2022, 69 invasive treatment naïve patients with primary (n = 43) or secondary/metastatic (n = 26) liver lesions (in all segments, except in segments II/III) treated percutaneously by RFA/MWA were included. Total liver volume (TLV), segment II + III volume (serving as “distant liver volume”), ablation zone volume and absolute liver volume (ALV, calculated by subtracting the ablation zone volume from the TLV) were the study outcomes.

Results

ALV in patients with secondary liver lesions increased to a median percentage of 106.87% (IQR = 99.66–113.03%, p = 0.016), volume of segments II/III increased to a median percentage of 105.81% (IQR = 100.06–115.65%, p = 0.003). ALV and segments II/III in patients with primary liver tumours remained stable, with a median percentage of 98.72% (IQR = 92.99–108.35%, p = 0.856) and 100.43% (IQR = 92.85–109.41%, p = 0.699), respectively.

Conclusion

In patients with secondary liver tumours, ALV and segments II/III increased after MWA/RFA by an average of approximately 6%, while ALV in patients with primary liver lesions remained unchanged. Besides the curative intent, these findings indicate the potential added benefit of thermal liver ablation on FLR hypertrophy inducing procedures in patients with secondary liver lesions.

Level of evidence

Level 3, non-controlled retrospective cohort study.

Graphical abstract
U–Pb and trace element zircon and apatite petrochronology of eclogites from the Scandinavian Caledonides
Authors: Jaranowski Maciej , Budzyń Bartosz , Barnes Christopher J. , Majka Jarosław , Sláma Jiří , Kozub-Budzyń Gabriela A. , Kośmińska Karolina
Published: July 2023

The petrochronological records of eclogites in the Scandinavian Caledonides are investigated using EPMA and LA-ICPMS of zircon and apatite for U–Pb geochronology, combined with major and trace element characteristics. Metamorphic zircon from two eclogites from the Lofoten-Vesterålen Complex (Lofoten Archipelago region) collectively yielded a Concordia age 427.8 ± 5.7 Ma and an upper intercept U–Pb age 425 ± 30 Ma. Apatites from the same eclogites provided U–Pb lower intercepts at 322 ± 28 Ma and 354 ± 33 Ma, with the latter also yielding a younger age of 227 ± 24 Ma. Two eclogites from the Lower Seve Nappe (Northern Jämtland) demonstrate different zircon and apatite age records. Metamorphic zircon provided Concordia ages of 467.2 ± 5.9 Ma and 444.5 ± 5.5 Ma, which resolve the age of prograde metamorphism and zircon growth during retrogression, respectively. The lower intercept U–Pb ages of apatites from the same eclogites are 436 ± 18 and 415 ± 25 Ma, respectively. In combination with their geochemical characteristics, they suggest two separate stages of exhumation of eclogite bodies in the Lower Seve Nappe. Zircons from an eclogite from the Blåhø Nappe (Nordøyane Archipelago) yielded a continuum of concordant U–Pb dates from ca. 435 to 395 Ma, which suggests several cycles of HT metamorphism within short intervals. Distinctive trace element characteristics of apatites from the Blåhø Nappe eclogite suggest formation coeval with zircon and garnet during HT metamorphism, but Pb diffusion behaved as an open system until cooling during exhumation of the nappe at 390 ± 12 Ma (lower intercept U–Pb age of apatite). To summarize, this study presents the high potential of coupled zircon and apatite petrochronology of eclogites in resolving their metamorphic evolution, particularly with respect to using trace element characteristics of apatites to constrain the records of their growth, alterations and the meaning of their U–Pb age record.
Lithium und Cobalt – Chancen und Probleme in Bezug auf zwei kritische Rohstoffe in der EU
Authors: Lughofer Clemens , Tost Michael
Published: July 2023

Um die Abhängigkeit der Kobalt- und Lithiumversorgung der Europäischen Union von Nicht-EU Ländern zu minimieren, werden neue Möglichkeiten zur Selbstversorgung gesucht. Sowohl die primäre als auch die sekundäre Gewinnung dieser beiden Rohstoffe besitzt innerhalb der Europäischen Union großes Potenzial. Lagerstätten in Finnland (Kobalt) und Spanien (Lithium) dienen neben dem Recycling von Kobalt- und Lithiumhaltigen Lithium-Ionen-Batterien in Norwegen und Deutschland als Basis für eine geringere Abhängigkeit der EU. In diesem Artikel werden die oben genannten Potenziale sowie Substitutionsmöglichkeiten dieser beiden kritischen Rohstoffe näher beschrieben.
GLP-1RAs and cardiovascular disease: is the endothelium a relevant platform?
Authors: Menghini Rossella , Casagrande Viviana , Rizza Stefano , Federici Massimo
Published: July 2023

Hyperglycemia strongly affects endothelial function and activation, which in turn increases the risk of atherosclerotic cardiovascular disease. Among pharmacotherapies aimed at lowering blood glucose levels, glucagon-like peptide 1 receptor agonists (GLP-1RA) represent a class of drugs involved in the improvement of the endothelium damage and the progression of cardiovascular diseases. They show antihypertensive and antiatherosclerotic actions due at least in part to direct favorable actions on the coronary vascular endothelium, such as oxidative stress reduction and nitric oxide increase. However, cumulative peripheral indirect actions could also contribute to the antiatherosclerotic functions of GLP-1/GLP-1R agonists, including metabolism and gut microbiome regulation. Therefore, further research is necessary to clarify the specific role of this drug class in the management of cardiovascular disease and to identify specific cellular targets involved in the protective signal transduction. In the present review, we provide an overview of the effects of GLP-1RAs treatment on cardiovascular disease with particular attention on potential molecular mechanisms involving endothelium function on formation and progression of atherosclerotic plaque.
Sentinel lymph node identification using contrast-enhanced ultrasound in breast cancer: review of the literature
Authors: Omoto Kiyoka , Futsuhara Kazushige , Watanabe Tamami
Published: July 2023

Before breast cancer surgery, sentinel lymph node (SLN) identification and biopsy using blue dye, radioisotope (RI) with a gamma probe, or a combination of the two are mainly performed. The dye-guided method requires skilled technique to make an incision in the skin and identify SLNs without damaging the lymphatic vessels. In addition, dye-induced anaphylactic shock has been reported. To use the γ-probe-guided method, the facility must be able to handle RI. However, to overcome the drawbacks of these methods, Omoto et al. developed a new identification modality using contrast-enhanced ultrasound with an ultrasound contrast agent (UCA) in 2002. Since then, many basic experiments and clinical studies using various UCA have been reported. In particular, a number of studies in SLN detection using Sonazoid have been reported and are herein reviewed.
Reputation compensation for incentive alignment in a supply chain with trade credit under information asymmetry
Authors: Wang Zhihong , Zhao Lima , Shao Yuwei , Wen Xiaojuan
Published: July 2023

This paper examines a two-period dynamic contracting in a supply chain under information asymmetry, where a supplier sells a product to a retailer via a trade credit contract. It is found that the retailer always prefers to conceal her actual cost information thus signal as a higher-cost type in the first period to pursue a higher information rent, which would decrease the supplier’s profit and thereby the overall profit of the supply chain. To mitigate this ratchet effect, we introduce a reputation compensation mechanism in the two-period trade credit setting. This mechanism could alleviate the information asymmetry to a certain extent as there exists a threshold that incentivizes the retailer to share her true cost information in the earlier period. Moreover, the retailer might claim as a lower-cost type when the supplier offers a relatively higher reputation compensation to take full advantage of her information. Therefore, the supplier should provide trade credit with a reasonable reputation compensation in a two-period setting to enhance his expected profit.
TIMESS a power analysis tool to estimate the number of locations and repeated measurements for seasonally and clustered mosquito surveys
Authors: Sedda Luigi , Taylor Benjamin M. , Cain Russell , Vajda Élodie A. , Tatarsky Allison , Lobo Neil F.
Published: July 2023

Every day, hundreds of mosquito surveys are carried out around the world to inform policy and management decisions on how best to reduce or prevent the burden of mosquito-borne disease or mosquito nuisance. These surveys are usually time consuming and expensive. Mosquito surveillance is the essential component of vector management and control. However, surveillance is often carried out with a limited if not without a quantitative assessment of the sampling effort which can results in underpowered or overpowered studies, or certainly in overpowered studies when power analyses are carried out assuming independence in the measurements obtained from longitudinal and geographically proximal mosquito surveys. Many free, open-source and user-friendly tools to calculate statistical power are available, such as G*Power, glimmpse, powerandsamplesize.com website or R-cran packages (pwr and WebPower to name few of them). However, these tools may not be sufficient for powering mosquito surveys due to the additional properties of seasonal and spatially clustered repeated measurements required to reflect mosquito population dynamics. To facilitate power analysis for mosquito surveillance, we have developed TIMESS, a deployable browser-based Shiny app that estimates the number of repeated measurements and locations of mosquito surveys for a given effect size, power, significance level, seasonality and level of expected between-location clustering. In this article we describe TIMESS, its usage, strengths and limitations.
Learning rewards from exploratory demonstrations using probabilistic temporal ranking
Authors: Burke Michael , Lu Katie , Angelov Daniel , Straižys Artūras , Innes Craig , Subr Kartic , Ramamoorthy Subramanian
Published: July 2023

Informative path-planning is a well established approach to visual-servoing and active viewpoint selection in robotics, but typically assumes that a suitable cost function or goal state is known. This work considers the inverse problem, where the goal of the task is unknown, and a reward function needs to be inferred from exploratory example demonstrations provided by a demonstrator, for use in a downstream informative path-planning policy. Unfortunately, many existing reward inference strategies are unsuited to this class of problems, due to the exploratory nature of the demonstrations. In this paper, we propose an alternative approach to cope with the class of problems where these sub-optimal, exploratory demonstrations occur. We hypothesise that, in tasks which require discovery, successive states of any demonstration are progressively more likely to be associated with a higher reward, and use this hypothesis to generate time-based binary comparison outcomes and infer reward functions that support these ranks, under a probabilistic generative model. We formalise this probabilistic temporal ranking approach and show that it improves upon existing approaches to perform reward inference for autonomous ultrasound scanning, a novel application of learning from demonstration in medical imaging while also being of value across a broad range of goal-oriented learning from demonstration tasks.
Influence of microbial biomass content on biodegradation and mechanical properties of poly(3-hydroxybutyrate) composites
Authors: Eckel Felix , Sinzinger Korbinian , Van Opdenbosch Daniel , Schieder Doris , Sieber Volker , Zollfrank Cordt
Published: July 2023

Biodegradation rates and mechanical properties of poly(3-hydroxybutyrate) (PHB) composites with green algae and cyanobacteria were investigated for the first time. To the authors knowledge, the addition of microbial biomass led to the biggest observed effect on biodegradation so far. The composites with microbial biomass showed an acceleration of the biodegradation rate and a higher cumulative biodegradation within 132 days compared to PHB or the biomass alone. In order to determine the causes for the faster biodegradation, the molecular weight, the crystallinity, the water uptake, the microbial biomass composition and scanning electron microscope images were assessed. The molecular weight of the PHB in the composites was lower than that of pure PHB while the crystallinity and microbial biomass composition were the same for all samples. A direct correlation of water uptake and crystallinity with biodegradation rate could not be observed. While the degradation of molecular weight of PHB during sample preparation contributed to the improvement of biodegradation, the main reason was attributed to biostimulation by the added biomass. The resulting enhancement of the biodegradation rate appears to be unique in the field of polymer biodegradation. The tensile strength was lowered, elongation at break remained constant and Young’s modulus was increased compared to pure PHB.
Bioremoval of heavy metals from aqueous solution using dead biomass of indigenous fungi derived from fertilizer industry effluents: isotherm models evaluation and batch optimization
Authors: El-Gendy Mervat Morsy Abass Ahmed , Abdel-Moniem Shimaa M. , Ammar Nabila S. , El-Bondkly Ahmed Mohamed Ahmed
Published: July 2023

The present work investigated the utilization of dead biomass of the highly multi-heavy metals tolerant indigenous fungal strain NRCA8 isolated from the mycobiome of fertilizer industry effluents that containing multiple heavy metal ions at high levels to remove Pb2+, Ni2+, Zn2+, and Mn2+ as multiple solutes from multi-metals aqueous solutions for the first time. Based on morphotype, lipotype and genotype characteristics, NRCA8 was identified as Cladosporium sp. NRCA8. The optimal conditions for the bioremoval procedure in the batch system were pH 5.5 for maximum removal (91.30%, 43.25%, and 41.50%) of Pb2+, Zn2+ and Mn2+ but pH 6.0 supported the maximum bioremoval and uptake of Ni2+ (51.60% and 2.42 mg/g) by NRCA8 dead biomass from the multi-metals aqueous solution, respectively. The 30 min run time supported the highest removal efficiency and uptake capacity of all heavy metals under study. Moreover, the equilibrium between the sorbent NRCA8 fungal biomass and sorbates Ni2+, Pb2+ and Zn2+ was attained after increasing the dead biomass dose to 5.0 g/L. Dead NRCA8 biomass was described by scanning electron microscopy, energy-dispersive X-ray spectroscopy and Fourier transform infrared spectrometer before and after biosorption of Pb2+, Ni2+, Zn2+ and Mn2+ under multiple metals system. The Langmuir, Freundlich and Dubinin-Kaganer-Radushkevich isotherms were applied to characterize the adsorption equilibrium between Pb2+, Ni2+, Mn2+ and Zn2+ and the adsorbent NRCA8. By comparing the obtained coefficient of regression (R2) by Freundlich (0.997, 0.723, 0.999, and 0.917), Langmiur (0.974, 0.999, 0.974, and 0.911) and Dubinin-Radushkevich (0.9995, 0.756, 0.9996 and 0.900) isotherms values for Pb2+, Zn2+, Ni2+ and Mn2+ adsorption, respectively, it was found that the isotherms are proper in their own merits in characterization the possible of NRCA8 for removal of Pb2+, Zn2+, Ni2+ and Mn2+. DKR isotherm is the best for Pb2+ and Ni2+ (0.9995 and 0.9996) while Langmiur isotherm giving a good fit to the Zn2+ sorption (0.9990) as well as Freundlich isotherm giving a good fit to the Mn2+ sorption (0.9170). The efficiencies of Cladosporium sp. NRCA8 dead biomass for bioremoval of heavy metals from real wastewater under the optimized conditions were Pb2+, Ag+, Mn2+, Zn2+ and Al3+ ˃ Ni2+ ˃ Cr6+ ˃ Co2+ ˃ Fe3+ ˃ Cu2+ ˃ Cd2+. Dead NRCA8 biomass showed efficient ability to adsorb and reduce harmful components in the industrial effluents to a level acceptable for discharge into the environment.
Improved numerical predictions of inclined negatively buoyant jet behaviour
Authors: Law Shuen , Davidson Mark J. , McConnochie Craig , Lagrava Daniel
Published: July 2023

The results of numerical simulations of inclined negatively buoyant jets are presented. These simulations address previously highlighted difficulties in capturing sufficient detail of critical flow processes to effectively predict the detailed flow behaviour. In particular, the new simulations are able to accurately capture the details of the buoyancy-induced instabilities, which are clearly evident in associated experimental investigations and that have significant impacts on the flow behaviour. This new information is captured for inclined negatively buoyant jets discharged at 45° above a horizontal reference plane. A Large Eddy Simulation (LES) approach is implemented that makes use of a Lagrangian Dynamic Sub-grid scale (SGS) model and a novel criterion for the adaptive meshing system. Comparisons with previously published simulation results and experimental data demonstrate that these new Adaptive LES simulations provide improved predictions of flow path, concentration and velocity fields, and associated mean and turbulent statistics. In addition, this study provides a set of methods for generating high-quality LES data sets for free shear flows, which are well beyond the level of detail that can be captured by current experimental systems.
The essential work of fracture in peridynamics
Authors: Stenström Christer , Eriksson Kjell , Bobaru Florin , Golling Stefan , Jonsén Pär
Published: July 2023

In this work, the essential work of fracture (EWF) method is introduced for a peridynamic (PD) material model to characterize fracture toughness of ductile materials. First, an analytical derivation for the path-independence of the PD J-integral is provided. Thereafter, the classical J-integral and PD J-integral are computed on a number of analytical crack problems, for subsequent investigation on how it performs under large scale yielding of thin sheets. To represent a highly nonlinear elastic behavior, a new adaptive bond stiffness calibration and a modified bond-damage model with gradual softening are proposed. The model is employed for two different materials: a lower-ductility bainitic-martensitic steel and a higher-ductility bainitic steel. Up to the start of the softening phase, the PD model recovers the experimentally obtained stress–strain response of both materials. Due to the high failure sensitivity on the presence of defects for the lower-ductility material, the PD model could not recover the experimentally obtained EWF values. For the higher-ductility bainitic material, the PD model was able to match very well the experimentally obtained EWF values. Moreover, the J-integral value obtained from the PD model, at the absolute maximum specimen load, matched the corresponding EWF value.
N2O emission factors for cattle urine: effect of patch characteristics and environmental drivers
Authors: Barczyk Lena , Kuntu-Blankson Kate , Calanca Pierluigi , Six Johan , Ammann Christof
Published: July 2023

Urine patches from grazing cattle are hotspots of nitrous oxide (N2O) emissions. The default IPCC emission factor for urine patches (EFurine) is 0.77% for wet climates and 0.32% for dry climates. However, literature reports a considerable range of cattle urine EF values and urine characteristics used in experimental studies, revealing contrary results on the effects of urine patch characteristics and seasonal pattern. Therefore, we examined N2O emissions and corresponding EFurine values in relation to urine patch characteristics (urine N concentration, urine volume, patch area, urine composition) and environmental drivers (precipitation, water filled pore space, soil temperature). Ten artificial urine application experiments were performed from July 2020 to June 2022 on a pasture located in Eastern Switzerland. Urine N concentration, patch area, volume and urine N composition showed no significant effects on the EFurine value (p > 0.05). EFurine varied, however, strongly over time (0.17–2.05%). A large part of the variation could be predicted either by cumulative precipitation 20 days after urine application using a second order polynomial model (Adj. R2 = 0.60) or average WFPS 30 days after urine application using a linear model (Adj. R2 = 0.45). The derived precipitation model was used to simulate EFurine weekly over the last 20 years showing no significant differences between the seasons of a year. The resulting overall average EFurine was 0.67%. More field studies are needed across sites/regions differing in climate and soil properties to implement a country-specific EF3 for Switzerland and to improve the quantification of N2O emissions at the national scales.
The large Hellenic Study of Uveitis: epidemiology, etiologic factors and classification
Authors: Kalogeropoulos Dimitrios , Asproudis Ioannis , Stefaniotou Maria , Moschos Marilita M. , Kozobolis Vassilios P. , Voulgari Paraskevi V. , Katsanos Andreas , Gartzonika Constantina , Kalogeropoulos Chris
Published: July 2023

Purpose

To analyse the demography, etiology, and classification of uveitis at a tertiary academic referral center.

Methods

An observational study was conducted on the archives of uveitic patients at the Ocular Inflammation Service of the Department of Ophthalmology at the University Hospital of Ioannina (Greece) from 1991 to 2020. This study aimed to investigate the epidemiological profile of patients, including their demographics and the main etiologic factors of uveitis.

Results

Out of 6191 cases with uveitis, 1925 were infectious, 4125 were non-infectious, and an overall of 141 masquerade syndromes were recorded. Among these cases, 5950 patients were adults, with a slight female predominance, while 241 were children (< 18 years old). Interestingly, 24.2% of cases (1500 patients) were associated with 4 specific microorganisms. Herpetic uveitis (HSV-1 and VZV/HZV) was the most common cause of infectious uveitis (14.87%), followed by toxoplasmosis (6.6%) and tuberculosis (2.74%). In 49.2% of non-infectious uveitis cases, no systematic correlation was found. The most frequent causes of non-infectious uveitis included sarcoidosis, white dot syndromes, ankylosing spondylitis, lens-induced uveitis, Adamantiades-Behçet disease, and idiopathic juvenile arthritis. Infectious uveitis was more common in the rural population, whereas non-infectious uveitis was more frequently recorded in the urban population

Conclusions

Although our study was conducted on a predominantly white Caucasian population, it also reflects the effect of increasing immigration, improvements of diagnostic techniques, changes in referral patterns, and various actual changes in disease incidence.
Comparing performance between clinics of an embryo evaluation algorithm based on time-lapse images and machine learning
Authors: Johansen Martin N. , Parner Erik T. , Kragh Mikkel F. , Kato Keiichi , Ueno Satoshi , Palm Stefan , Kernbach Manuel , Balaban Başak , Keleş İpek , Gabrielsen Anette V. , Iversen Lea H. , Berntsen Jørgen
Published: July 2023

Purpose

This article aims to assess how differences in maternal age distributions between IVF clinics affect the performance of an artificial intelligence model for embryo viability prediction and proposes a method to account for such differences.

Methods

Using retrospectively collected data from 4805 fresh and frozen single blastocyst transfers of embryos incubated for 5 to 6 days, the discriminative performance was assessed based on fetal heartbeat outcomes. The data was collected from 4 clinics, and the discrimination was measured in terms of the area under ROC curves (AUC) for each clinic. To account for the different age distributions between clinics, a method for age-standardizing the AUCs was developed in which the clinic-specific AUCs were standardized using weights for each embryo according to the relative frequency of the maternal age in the relevant clinic compared to the age distribution in a common reference population.

Results

There was substantial variation in the clinic-specific AUCs with estimates ranging from 0.58 to 0.69 before standardization. The age-standardization of the AUCs reduced the between-clinic variance by 16%. Most notably, three of the clinics had quite similar AUCs after standardization, while the last clinic had a markedly lower AUC both with and without standardization.

Conclusion

The method of using age-standardization of the AUCs that is proposed in this article mitigates some of the variability between clinics. This enables a comparison of clinic-specific AUCs where the difference in age distributions is accounted for.
Machine learning methods for predicting the admissions and hospitalisations in the emergency department of a civil and military hospital
Authors: Álvarez-Chaves Hugo , Muñoz Pablo , R-Moreno María D.
Published: July 2023

Hospitals’ Emergency Departments (ED) have a great relevance in the health of the population. Properly managing the ED department requires to optimise the service, while maintaining a high quality care. This trade-off implies to properly arrange the schedule for the personnel, so the service can duly attend all patients. In this regard, a key point is to know in advance how many patients will arrive to the service and the number that should be derived to hospitalisation. To provide such information, we present the results of applying different algorithms for forecasting ED admissions and hospitalisations for both seven days and four months ahead. To do this, we have employed the ED admissions and inpatients series from a Spanish civil and military hospital. The ED admissions have been aggregated on a daily basis and on the official workers’ shifts, while the hospitalisations series have been considered daily. Over that data we employ two algorithms types: time series (AR, H-W, SARIMA and Prophet) and feature matrix (LR, EN, XGBoost and GLM). In addition, we create all possible ensembles among the models in order to find the best forecasting method. The findings of our study demonstrate that the ensembles can be beneficial in obtaining the best possible model.
Norms for the Dutch Version of the Young Schema Questionnaire – Adolescent in a Clinical Population
Authors: Sijstermans Dyonne M.L. , Span Marjolijn , Van Breukelen Gerard J.P. , Bol Yvonne , Braet Caroline , Roelofs Jeffrey
Published: July 2023

The Young Schema Questionnaire (YSQ; Young, 1994) is a widely used instrument to assess early maladaptive schemas in adults and older adolescents. Despite its widespread use, no norm data are available, making it difficult to evaluate when an individual’s YSQ score can be considered as elevated or high. Such norms can be useful for screening purposes such as to identify those at risk for psychopathology and providing early and appropriate interventions. The aim of our study was to norm the five schema domains of the Dutch adolescent version of the Young Schema Questionnaire (YSQ-A: Van Vlierberghe et al., 2004). In addition to providing norm data for clinical practice, we also show the process of obtaining reliable and valid norm data with state-of-the-art regression analysis which does not necessarily require splitting the norm sample into subgroup by sex or age, yet does take these variables into account in obtaining norms.
Machine Learning Prediction Models to Reduce Length of Stay at Ambulatory Surgery Centers Through Case Resequencing
Authors: Tully Jeffrey L. , Zhong William , Simpson Sierra , Curran Brian P. , Macias Alvaro A. , Waterman Ruth S. , Gabriel Rodney A.
Published: July 2023

The post-anesthesia care unit (PACU) length of stay is an important perioperative efficiency metric. The aim of this study was to develop machine learning models to predict ambulatory surgery patients at risk for prolonged PACU length of stay - using only pre-operatively identified factors - and then to simulate the effectiveness in reducing the need for after-hours PACU staffing. Several machine learning classifier models were built to predict prolonged PACU length of stay (defined as PACU stay ≥ 3 hours) on a training set. A case resequencing exercise was then performed on the test set, in which historic cases were re-sequenced based on the predicted risk for prolonged PACU length of stay. The frequency of patients remaining in the PACU after-hours (≥ 7:00 pm) were compared between the simulated operating days versus actual operating room days. There were 10,928 ambulatory surgical patients included in the analysis, of which 580 (5.31%) had a PACU length of stay ≥ 3 hours. XGBoost with SMOTE performed the best (AUC = 0.712). The case resequencing exercise utilizing the XGBoost model resulted in an over three-fold improvement in the number of days in which patients would be in the PACU past 7pm as compared with historic performance (41% versus 12%, P<0.0001). Predictive models using preoperative patient characteristics may allow for optimized case sequencing, which may mitigate the effects of prolonged PACU lengths of stay on after-hours staffing utilization.
Pentaerythritol and Glycerol Esters Derived from Gum Rosin as Bio-Based Additives for the Improvement of Processability and Thermal Stability of Polylactic Acid
Authors: de la Rosa-Ramírez Harrison , Dominici Franco , Ferri José Miguel , Luzi Francesca , Puglia Debora , Torre Luigi , López-Martínez Juan , Samper María Dolores
Published: July 2023

Gum rosin esters are some of the most common gum rosin derivatives used in different applications, such as coatings, paper, varnishes, chewing gum, and food industries. In this study, gum rosin esters are used as additives for polylactic acid (PLA) to improve its processability and thermal stability. Blends of an amorphous PLA with two different gum rosin esters, pentaerythritol ester and glycerol ester, were prepared by melt extrusion process in concentrations from 1, 3, and 5 phr. Besides the comparison of thermal degradation, microstructure assessment, and melt flow index (MFI) analysis, the processability performance during testing samples production by injection molding process was evaluated. Experimental results showed that MFI values of PLA-gum rosin ester blends increased by 100%, 147%, and 164%, along with increasing content of gum rosin esters addition, in both cases. Also, both derivatives slightly improved PLA thermal stability (around 3ºC higher). Injection molding temperature decreased by at least 20 °C for PLA-gum rosin ester blends compared with neat PLA. Furthermore, the maximum tensile strength of PLA-gum rosin esters was negligibly affected in formulations with low content of gum rosin esters, and the FESEM images revealed a good dispersion and compatibility of gum rosin ester particles into PLA matrix in both concentrations.