bluuebunny/crossref_metadata_2025 huggingface dataset:
Sociobiology on Screen. The Controversy Through the Lens of Sociobiology: Doing What Comes Naturally
Authors: Stuhrmann Cora
Published: June 2023

When the sociobiology debate erupted in 1975, there were almost too many contributions to the heated exchanges between sociobiologists and their critics to count. In the fall of 1976, a Canadian educational film entitled Sociobiology: Doing What Comes Naturally sparked further controversy due to its graphic visuals and outrageous narration. While critics claimed the film was a promotional tool to further the sociobiological agenda in educational settings, sociobiologists quickly distanced themselves from the film and, in turn, accused the critics of consciously misrepresenting sociobiology by organizing showings of the film. Using audio, video, archival, and published sources, this paper explores the complicated history of Sociobiology: Doing What Comes Naturally and demonstrates how the public debate about the film reflects the positions, polemics, and polarization of the sociobiology debate as a whole.
Effects of dissolved organic carbon gradient on epilimnetic zooplankton communities in lakes
Authors: Estlander Satu , Horppila Jukka
Published: June 2023

Lake browning is expected to change aquatic ecosystems considerably. The changes that may occur in zooplankton communities with a high concentration of dissolved organic carbon (DOC) are little studied and not yet sufficiently understood. We studied zooplankton communities in Finland in 27 lakes with a wide DOC range. We explored how zooplankton diversity and biomass vary along a DOC gradient and how species belonging to different functional groups respond to varying DOC concentrations. The total biomass of zooplankton was not related to DOC concentration, but diversity decreased and the negative linear trend in diversity coincided with an increase in omnivorous zooplankton taxa, whereas several other herbivorous zooplankton taxa were displaced from the community along the gradient of DOC. The results of our study suggest that some well-adapted taxa, especially omnivorous taxa, can benefit from lake browning, but a larger number of taxa suffer from unfavourable conditions caused by high DOC concentration. DOC-induced changes in predation pressure and changes in phytoplankton community in terms of resource availability for zooplankton should be emphasized in future research to understand the effects of lake browning on zooplankton.
Mapping international research output within ethical, legal, and social implications (ELSI) of assisted reproductive technologies
Authors: Alon Ido , Chebance Zacharie , Massucci Francesco Alessandro , Bounartzi Theofano , Ravitsky Vardit
Published: June 2023

Purpose

Research about ethical, legal, and social implications (ELSI) of assisted reproductive technologies (ART) is influenced by cultural and value-based perspectives. It impacts regulations, funding, and clinical practice, and shapes the perception of ART in society. We analyze trends in the global literature on ELSI of ART between 1999 and 2019. As most output is produced by North America, Western Europe, and Australia, we focus on international research, i.e., academic articles studying a different country than that of the corresponding author.

Methods

The corpus, extracted from PubMed, Web of Science, and Scopus, includes 7714 articles, of which 1260 involved international research. Analysis is based on titles, abstracts and keywords, classification into ART fields and Topic Modeling, the countries of corresponding author, and countries mentioned in abstracts.

Results

An absolute increase in the number of international studies, and their relative proportion. Trends of decentralization are apparent, yet geographic centralization remains, which reflects an unequal distribution of research funds across countries and may result in findings that do not reflect global diversity of norms and values. Preference for studying conceptual challenges through philosophical analysis, and for fields that concern only a portion of ART cycles. Less attention was dedicated to economic analysis and barriers to access, or to knowledge of and attitudes. International studies provide an opportunity to expand and diversify the scope of ELSI research.

Conclusion

We call on the research community to promote international collaborations, focus on less explored regions, and divert more attention to questions of cost, access, knowledge, and attitudes.
SSMSPC: self-supervised multivariate statistical in-process control in discrete manufacturing processes
Authors: Biegel Tobias , Helm Patrick , Jourdan Nicolas , Metternich Joachim
Published: June 2023

Self-supervised learning has demonstrated state-of-the-art performance on various anomaly detection tasks. Learning effective representations by solving a supervised pretext task with pseudo-labels generated from unlabeled data provides a promising concept for industrial downstream tasks such as process monitoring. In this paper, we present SSMSPC a novel approach for multivariate statistical in-process control (MSPC) based on self-supervised learning. Our motivation for SSMSPC is to leverage the potential of unsupervised representation learning by incorporating self-supervised learning into the general statistical process control (SPC) framework to develop a holistic approach for the detection and localization of anomalous process behavior in discrete manufacturing processes. We propose a pretext task called Location + Transformation prediction, where the objective is to classify both, the type and the location of a randomly applied augmentation on a given time series input. In the downstream task, we follow the one-class classification setting and apply the Hotelling’s $$T^2$$

T
2

statistic on the learned representations. We further propose an extension to the control chart view that combines metadata with the learned representations to visualize the anomalous time steps in the process data which supports a machine operator in the root cause analysis. We evaluate the effectiveness of SSMSPC with two real-world CNC-milling datasets and show that it outperforms state-of-the-art anomaly detection approaches, achieving $$100\%$$

100
%

and $$99.6\%$$

99.6
%

AUROC, respectively. Lastly, we deploy SSMSPC at a CNC-milling machine to demonstrate its practical applicability when used as a process monitoring tool in a running process.
Assessing the performance of QSP models: biology as the driver for validation
Authors: Singh Fulya Akpinar , Afzal Nasrin , Smithline Shepard J. , Thalhauser Craig J.
Published: June 2023

Validation of a quantitative model is a critical step in establishing confidence in the model’s suitability for whatever analysis it was designed. While processes for validation are well-established in the statistical sciences, the field of quantitative systems pharmacology (QSP) has taken a more piecemeal approach to defining and demonstrating validation. Although classical statistical methods can be used in a QSP context, proper validation of a mechanistic systems model requires a more nuanced approach to what precisely is being validated, and what role said validation plays in the larger context of the analysis. In this review, we summarize current thoughts of QSP validation in the scientific community, contrast the aims of statistical validation from several contexts (including inference, pharmacometrics analysis, and machine learning) with the challenges faced in QSP analysis, and use examples from published QSP models to define different stages or levels of validation, any of which may be sufficient depending on the context at hand.
A Practical Approach to SOS Relaxations for Detecting Quantum Entanglement
Authors: Bhardwaj Abhishek
Published: June 2023

This article introduces PnCP, a MATLAB toolbox for constructing positive maps which are not completely positive. We survey optimization and sum of squares relaxation techniques to find the most numerically efficient methods and establish some benchmarks for this construction. We also show how this package can be applied to the problem of classifying entanglement in quantum states.
User experience evaluation of Edurell interface for video augmentation
Authors: Coccoli Mauro , Torre Ilaria , Galluccio Ilenia
Published: June 2023

This paper deals with the use of videos in education and describes an approach to improve the learners’ experience in the first-watch and rewatch learning contexts. Actually, learning through videos raises challenging issues like non-linear navigation and poor structure of the video content. Hence, a novel application is presented, designed to address such issues. To this aim, the proposed Edurell environment enriches standard video lessons with new services based on the contents’ structure of the video, resulting in a new hypervideo educational application. The system extracts the concepts explained in a given video lesson, their prerequisite relations, and the segments of the video where they occur, together with other pieces of knowledge. The resulting knowledge graph allows creating augmented video lessons and enables learners to perform non-linear navigation and in-depth exploration of their learning contents. This idea was implemented in a custom web-based video player with interactive visual tools. Then, a heuristic usability evaluation was performed with HCI experts. Also, a user study with university students was done, aimed to evaluate the perceived usability and the student’s experience in the two mentioned learning contexts. The first results achieved show the effectiveness of the proposed approach.
Derivative-based time-adjusted analysis of diurnal and within-tree variation in the OJIP fluorescence transient of silver birch
Authors: Akinyemi Olusegun Olaitan , Čepl Jaroslav , Keski-Saari Sarita , Tomášková Ivana , Stejskal Jan , Kontunen-Soppela Sari , Keinänen Markku
Published: June 2023

The JIP test, based on fast chlorophyll fluorescence (ChlF) kinetics and derived parameters, is a dependable tool for studying photosynthetic efficiency under varying environmental conditions. We extracted additional information from the whole OJIP and the normalized variable fluorescence (Vt) transient curve using first and second-order derivatives to visualize and localize points of landmark events. To account for light-induced variations in the fluorescence transient, we present a time-adjusted JIP test approach in which the derivatives of the transient curve are used to determine the exact timing of the J and I steps instead of fixed time points. We compared the traditional JIP test method with the time-adjusted method in analyzing fast ChlF measurements of silver birch (Betula pendula) in field conditions studying diurnal and within-crown variation. The time-adjusted JIP test method showed potential for studying ChlF dynamics, as it takes into account potential time shifts in the occurrence of J and I steps. The exact occurrence times of J and I steps and other landmark events coincided with the times of significant differences in fluorescence intensity. Chlorophyll fluorescence parameters were linearly related to photosynthetic photon flux density (PPFD) at different times of day, and the values obtained by the time-adjusted JIP test showed a stronger linear regression than the traditional JIP test. For fluorescence parameters having significant differences among different times of day and crown layers, the time-adjusted JIP test resulted in more clear differences than the traditional JIP test. Diurnal ChlF intensity data indicated that differences between the southern and northern provenance were only evident under low light conditions. Taken together, our results emphasize the potential relevance of considering the time domain in the analysis of the fast ChlF induction.
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences
Authors: Anastasiou Andreas , Papanastasiou Angelos
Published: June 2023

The extensive emergence of big data techniques has led to an increasing interest in the development of change-point detection algorithms that can perform well in a multivariate, possibly high-dimensional setting. In the current paper, we propose a new method for the consistent estimation of the number and location of multiple generalized change-points in multivariate, possibly high-dimensional, noisy data sequences. The number of change-points is allowed to increase with the sample size and the dimensionality of the given data sequence. Having a number of univariate signals, which constitute the unknown multivariate signal, our algorithm can deal with general structural changes; we focus on changes in the mean vector of a multivariate piecewise-constant signal, as well as changes in the linear trend of any of the univariate component signals. Our proposed algorithm, labeled Multivariate Isolate–Detect (MID) allows for consistent change-point detection in the presence of frequent changes of possibly small magnitudes in a computationally fast way.
Connexive Logic, Probabilistic Default Reasoning, and Compound Conditionals
Authors: Pfeifer Niki , Sanfilippo Giuseppe
Published: June 2023

We present two approaches to investigate the validity of connexive principles and related formulas and properties within coherence-based probability logic. Connexive logic emerged from the intuition that conditionals of the formif not-A,thenA, should not hold, since the conditional’s antecedentnot-Acontradicts its consequentA. Our approaches cover this intuition by observing that the only coherent probability assessment on the conditional event$${A| \overline{A}}$$A|A¯is$${p(A| \overline{A})=0}$$p(A|A¯)=0. In the first approach we investigate connexive principles within coherence-based probabilistic default reasoning, by interpreting defaults and negated defaults in terms of suitable probabilistic constraints on conditional events. In the second approach we study connexivity within the coherence framework of compound conditionals, by interpreting connexive principles in terms of suitable conditional random quantities. After developing notions of validity in each approach, we analyze the following connexive principles:Aristotle’s theses,Aristotle’s Second Thesis,Abelard’s First Principle, andBoethius’ theses. We also deepen and generalize some principles and investigate further properties related to connexive logic (likenon-symmetry). Both approaches satisfyminimalrequirements for a connexive logic. Finally, we compare both approaches conceptually.
Acute myeloid leukemia cells and MSC-derived exosomes inhibiting transformation in myelodysplastic syndrome
Authors: Liu Xiaoli , Ren Fanggang , Li Shuo , Zhang Na , Pu Jeffrey J. , Zhang Hongyu , Xu Zhifang , Tan Yanhong , Chen Xiuhua , Chang Jianmei , Wang Hongwei
Published: June 2023

Aims

To investigate the mechanism of exosomes' role in the transformation of MDS to AML.

Methods

Exosomes in culture supernatants of MDS and AML cell lines, were extracted by ultrafiltration and identified in three ways: morphology, size, and exosome protein surface markers. Exosomes from AML cell lines were then co-cultured with MDS cell lines and their impacts on MDS cell microenvironment, proliferation, differentiation, cell cycle, and apoptosis were analyzed by CCK-8 assay and flow cytometry. Furthermore, exosomes from MSC were extracted for further authentication.

Results

The transmission electron microscopy, nanoparticle tracking analysis, Western blotting, and flow cytometry methods all verify that ultrafiltration is a reliable method to extract exosomes in the culture medium. Exosomes from AML cell lines inhibit the proliferation of MDS cell lines, block cell cycle progression, and promote apoptosis and cell differentiation. It also leads to increased secretion of tumor necrosis factor-α (TNF-α) and reactive oxygen species (ROS) in MDS cell lines. In addition, MSC-derived exosomes were found to inhibit the proliferation of MDS cell lines, arrest cell cycle progression, promote apoptosis, and inhibit differentiation.

Conclusion

Ultrafiltration is a proper methodology in extracting exosomes. The exosomes of AML origin and MSC origin may play a role in MDS leukemia transformation via targeting TNF-α/ROS-Caspase3 pathway.
Few-shot and meta-learning methods for image understanding: a survey
Authors: He Kai , Pu Nan , Lao Mingrui , Lew Michael S.
Published: June 2023

State-of-the-art deep learning systems (e.g., ImageNet image classification) typically require very large training sets to achieve high accuracies. Therefore, one of the grand challenges is called few-shot learning where only a few training samples are required for good performance. In this survey, we illuminate one of the key paradigms in few-shot learning called meta-learning. These meta-learning methods, by simulating the tasks which will be presented at inference through episodic training, can effectively employ previous prior knowledge to guide the learning of new tasks. In this paper, we provide a comprehensive overview and key insights into the meta-learning approaches and categorize them into three branches according to their technical characteristics, namely metric-based, model-based and optimization-based meta-learning. Due to the major importance of the evaluation process, we also present an overview of current widely used benchmarks, as well as performances of recent meta-learning methods on these datasets. Based on over 200 papers in this survey, we conclude with the major challenges and future directions of few-shot learning and meta-learning.
Using a Latent Variable Method to Develop a Composite, Multidimensional Measure of Structural Racism at the City Level
Authors: Siegel Michael , Rieders Madeline , Rieders Hannah , Moumneh Jinan , Asfour Julia , Oh Jinseo , Oh Seungjin
Published: June 2023

Introduction

Although structural racism is strongly related to racial health disparities, we are not aware of any composite, multidimensional measure of structural racism at the city level in the United States. However, many of the policies, programs, and institutions that create and maintain structural racism are located at the city level. To expand upon previous research, this paper uses a novel measure to measure structural racism at the city level for the non-Hispanic Black population.

Methods

We used confirmatory factor analysis to model the latent construct of structural racism for 776 U.S. cities. The model included six indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status. We generated factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each city. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates.

Results

There were profound differences in the magnitude of structural racism across cities. There were also striking differences in the magnitude of the racial disparity in firearm homicide across cities. Structural racism was a significant predictor of the magnitude of these racial disparities in firearm homicide. Each one standard deviation increase in the structural racism factor score increased the firearm homicide rate ratio by a factor of approximately 1.2 (95% confidence interval, 1.1-1.3).

Conclusions

These new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.
Path-guided intelligent switching over knowledge graphs with deep reinforcement learning for recommendation
Authors: Tao Shaohua , Qiu Runhe , Cao Yan , Xue Guoqing , Ping Yuan
Published: June 2023

Online recommendation systems process large amounts of information to make personalized recommendations. There has been some progress in research on incorporating knowledge graphs in reinforcement learning for recommendation; however, some challenges still remain. First, in these approaches, an agent cannot switch paths intelligently, because of which, the agent cannot cope with multi-entities and multi-relations in knowledge graphs. Second, these methods do not have predefined targets and thus cannot discover items that are closely related to user-interacted items and latent rich semantic relationships. Third, contemporary methods do not consider long rational paths in knowledge graphs. To address these problems, we propose a deep knowledge reinforcement learning (DKRL) framework, in which path-guided intelligent switching was implemented over knowledge graphs incorporating reinforcement learning; this model integrates predefined target and long logic paths over knowledge graphs for recommendation systems. Specifically, the designed novel path-based intelligent switching algorithm with predefined target enables an agent to switch paths intelligently among multi-entities and multi-relations over knowledge graphs. In addition, the weight of each path is calculated, and the agent switches paths between multiple entities according to path weights. Furthermore, the long logic path has better recommendation performance and interpretability. Extensive experiments with actual data demonstrate that our work improves upon existing methods.The experimental results indicated that DKRL improved the baselines of NDCG@10 by 3.7%, 9.3%, and 4.7%; of HR@10 by 12.39%, 20.8%, and 13.86%; of Prec@10 by 5.17%, 3.57%, 6.2%; of Recall@10 by 3.01%, 4.2%, and 3.37%. The DKRL model achieved more effective recommendation performance using several large benchmark data sets compared with other advanced methods.
Rockburst prediction based on optimization of unascertained measure theory with normal cloud
Authors: Hu Xingmiao , Huang Linqi , Chen Jiangzhan , Li Xibing , Zhang Hongzhong
Published: June 2023

Rockburst is one of the common geological disasters in deep underground areas with high stress. Rockburst prediction is an important measure to know in advance the risk of rockburst hazards to take a scientific approach to the response. In view of the fuzziness and uncertainty between quantitative indexes and qualitative grade assessments in prediction, this study proposes the use of a normal cloud model to optimize the theory of unascertained measures (NC-UM). The uniaxial compressive strength (σc), stress coefficient (σθ/σc), elastic deformation energy index (Wet), and brittleness index of rock (σc/σt) are selected as the index of prediction. After data screening, 249 groups of rockburst case data are selected as the original data set. To reduce the influence of subjective and objective factors of index weight on the prediction results, the game theory is used to synthesize the three weighting methods of Criteria Importance Through Intercriteria Correlation (CRITIC), Entropy Weight (EW), and Analytic Hierarchy Process (AHP) to obtain the comprehensive weight of the index. After validating the model with example data, the results showed that the model was 93.3% accurate with no more than one level of prediction deviation. Compared with the traditional unascertained measure (UM) rockburst prediction model, the accuracy is 15–20% higher than that of the traditional model. It shows that the model is valid and applicable in predicting the rockburst propensity level.
Decision variable contribution based adaptive mechanism for evolutionary multi-objective cloud workflow scheduling
Authors: Li Jun , Xing Lining , Zhong Wen , Cai Zhaoquan , Hou Feng
Published: June 2023

Workflow scheduling is vital to simultaneously minimize execution cost and makespan for cloud platforms since data dependencies among large-scale workflow tasks and cloud workflow scheduling problem involve large-scale interactive decision variables. So far, the cooperative coevolution approach poses competitive superiority in resolving large-scale problems by transforming the original problems into a series of small-scale subproblems. However, the static transformation mechanisms cannot separate interactive decision variables, whereas the random transformation mechanisms encounter low efficiency. To tackle these issues, this paper suggests a decision-variable-contribution-based adaptive evolutionary cloud workflow scheduling approach (VCAES for short). To be specific, the VCAES includes a new estimation method to quantify the contribution of each decision variable to the population advancement in terms of both convergence and diversity, and dynamically classifies the decision variables according to their contributions during the previous iterations. Moreover, the VCAES includes a mechanism to adaptively allocate evolution opportunities to each constructed group of decision variables. Thus, the decision variables with a strong impact on population advancement are assigned more evolution opportunities to accelerate population to approximate the Pareto-optimal fronts. To verify the effectiveness of the proposed VCAES, we carry out extensive numerical experiments on real-world workflows and cloud platforms to compare it with four representative algorithms. The numerical results demonstrate the superiority of the VCAES in resolving cloud workflow scheduling problems.
Generic Group Metacognitive Therapy for Patients with Major Depressive Disorder and Related Problems: a Preliminary Evaluation in Specialized Mental Health Care
Authors: Strand Eivind R. , Veium Lise T. , Engvik Liv S. S. , Nordahl Henrik
Published: June 2023

Metacognitive therapy (MCT) is a transdiagnostic treatment approach with substantial empirical support that is well suited to be delivered in a group format. The present study reports on data from a service evaluation of generic group metacognitive therapy delivered to individuals seeking treatment for major depressive disorder (MDD) at a specialized mental health outpatient clinic. A total of 17 patients diagnosed with MDD where comorbidity was frequent received 10 sessions of generic group MCT delivered by two therapists. Group MCT was associated with large effect sizes for symptoms of depression, anxiety, interpersonal problems, self-esteem, general functioning, dysfunctional metacognitions, and treatment satisfaction was very high. The average number of therapist sessions used to treat each patient was seven. These preliminary findings support the continued use and evaluation of group MCT for patients seeking treatment for depression in specialized mental health care which likely is a cost-effective treatment option.
Diagnostik und Therapie des polyzystischen Ovarsyndroms (PCOS) in der Adoleszenz
Authors: Walch Katharina
Published: June 2023

Bei jugendlichen Mädchen ist die eindeutige Diagnosestellung des polzystischen Ovarsyndroms (PCOS) oft schwierig, weil sog. „key features“ des Syndroms (wie unregelmäßige Zyklen, vorübergehend erhöhte männliche Hormone und sog. Pubertätsakne) unter Teenagern weit verbreitet sind und auch im Rahmen der physiologischen Pubertätsentwicklung auftreten können. Daher ist empfohlen, betroffene Mädchen primär nicht mit der definitiven Diagnose eines PCOS zu konfrontieren, sondern diese regelmäßig zu reevaluieren. Erst anhaltende Zyklusunregelmäßigkeiten (zumeist Oligomenorrhö) und persistierende klinische oder biochemische Hyperandrogenämie bestätigen die Verdachtsdiagnose. Weder erhöhte Serum-AMH-Spiegel noch ein auffälliger Ultraschallbefund sollen zur Diagnosestellung bei Adoleszentinnen herangezogen werden. Die sog. „Lifestyle-Modifikation“ ist immer die erste und wichtigste Therapieoption bei übergewichtigen Jugendlichen mit PCOS. Je nach der im Vordergrund stehenden Beschwerdesymptomatik gibt es noch zusätzliche Therapieoptionen. Zur Endometriumprotektion soll eine regelmäßige Abbruchblutung – zumindest 1 × im Quartal – induziert werden. Bei vielen jungen Mädchen gehen die kutanen Hyperandrogenisierungserscheinungen mit großem Leidensdruck einher. Unter Beachtung der Kontraindikationen sind die niedrig dosierten kombinierten oralen Kontrazeptiva die erste Therapieoption in diesen Fällen. Ein interdisziplinärer Betreuungsansatz ist bei der Therapie von jungen Mädchen mit PCOS obligat.
Characterisation of dry spells for agricultural applications in Malawi
Authors: Chimimba Ellasy Gulule , Ngongondo Cosmo , Li Chengxiu , Minoungou Bernard , Monjerezi Maurice , Eneya Levis
Published: June 2023

Dry spells are one of the climate change hazards that continue to exert pressure on the agriculture sector, hence affecting food security. Understanding dry spell characteristics of an area helps in coming up with interventions and adaptive measures among other advantages. This study aimed at understanding characteristics of dry spells for Malawi by using climate hazards group infrared precipitation with stations precipitation data from 1981 to 2019. The study focused on the spatial distribution, maximum number of dry days, trend of maximum dry days and time of occurrence of dry spells. Data was analysed using Mann–Kendal trend analysis in R software. The results indicate a high number of occurrences of dry spells in the southern region than the other two regions of Malawi. In addition, the southern region experienced the highest maximum number of dry days. However, there is an upward trend for maximum days of dry spells in central region than all other regions. Local scale topographic influences on dry spell occurrence were also apparent. The study further established that the number of dry spell occurrence in the rainfall season starts to increase towards end of March. In this regard, although rainfall season in the study area is considered to be from November to April, the study recommends that growing season should be considered to be November to March so that crops are not affected by end of season dry spells which are common. Farmers should ensure that they plant crops that will mature with this growing period.
Single and Combined Effect of Cd and Zn on Growth, Metal Accumulation and Mineral Nutrition in Tobacco Plants (Nicotiana tabacum L.)
Authors: Cham Ramin , Moghtaderi Tahereh , Rodríguez-Seijo Andrés , Alamdar Razieh
Published: June 2023

Contamination by heavy metals (HM) is a global concern due to their impact on terrestrial and aquatic environments. This question has great relevance in agricultural areas due to excessive chemical fertilization. In this sense, Cd is a toxic element that can reach agricultural soils through chemical fertilization or sewage sludges. Tobacco plants (Nicotiana tabacum L.)can uptake and accumulate Cd in their tissues, and therefore, an increased risk for human health due to tobacco consumption. This study was performed to evaluate the response of tobacco plants to a single and combined amendment of Cd and Zn on agricultural soil with a pot experiment. A factorial experiment was performed with four Cd levels (0, 25, 50 and 100 mg kg-1) and three Zn levels (0, 15 and 25 mg kg-1). Growth, Cd and Zn bioaccumulation and nutrient uptake parameters were assessed. The results revealed that during the tobacco growth, Cd was bioaccumulated on roots (translocation factor <1), while Zn was bioaccumulated on the aerial part (TF>1). Besides, the Zn amendment significantly decreased the Cd uptake and accumulation, especially under intermediate doses (15 mg kg-1Zn). Zinc amendments could be helpful as a mitigation measure for Cd uptake in tobacco plants and, therefore, for health risk reduction.
Novel typology of accelerated carbonation curing: using dry and pre-soaked biochar to tune carbon capture and mechanical properties of cementitious mortar
Authors: Kua H. W. , Tan S. M. H.
Published: June 2023

One of the challenges of promoting accelerated carbonation curing (ACC) of concrete as a carbon sequestration strategy is ensuring that carbonation will not deteriorate mechanical strength. This study examined the mechanical strength, water sorptivity and carbonation efficiency of ten types of mortar containing dry or pre-soaked biochar subjected to internal and/or external carbonation. The results obtained enabled a typology of ACC to be proposed, in which the carbon dioxide absorption of mortar containing various types of CO2-dosed biochar ranged between 0.022% and 0.068% per unit dosage hour. In particular, the mortar containing dry biochar dosed with carbon dioxide was the top candidate for concurrently increasing both compressive strength (54.9 MPa) and carbon dioxide absorption (0.055% per unit dosage hour). Mortar containing pre-soaked biochar dosed with carbon dioxide was identified as a strategy that achieved the highest carbonation efficiency (0.068% per unit dosage hour), but it also reduced compressive strength (45.1 MPa). Collectively, the proposed typology offers a useful overview of the different ways by which biochar can be used to tune ACC in mortar, according to any technical constraints and/or intended functions of the carbonated concrete components.

Graphical Abstract
Graph-Enhanced Biomedical Abstractive Summarization Via Factual Evidence Extraction
Authors: Frisoni Giacomo , Italiani Paolo , Moro Gianluca , Bartolini Ilaria , Boschetti Marco Antonio , Carbonaro Antonella
Published: June 2023

Infusing structured semantic representations into language models is a rising research trend underpinning many natural language processing tasks that require understanding and reasoning capabilities. Decoupling factual non-ambiguous concept units from the lexical surface holds great potential in abstractive summarization, especially in the biomedical domain, where fact selection and rephrasing are made more difficult by specialized jargon and hard factuality constraints. Nevertheless, current graph-augmented contributions rely on extractive binary relations, failing to model real-world n-ary and nested biomedical interactions mentioned in the text. To alleviate this issue, we present EASumm, the first framework for biomedical abstractive summarization empowered by event extraction, namely graph-based representations of relevant medical evidence derived from the source scientific document. By relying on dual text-graph encoders, we prove the promising role of explicit event structures, achieving better or comparable performance than previous state-of-the-art models on the CDSR dataset. We conduct extensive ablation studies, including a wide experimentation of graph representation learning techniques. Finally, we offer some hints to guide future research in the field.
Existence and non-uniqueness of stationary states for the Vlasov–Poisson equation on $${{\mathbb {R}}}^3$$ subject to attractive background charges
Authors: Winter Raphael
Published: June 2023

We prove the existence of stationary solutions for the density of an infinitely extended plasma interacting with an arbitrary configuration of background charges. Furthermore, we show that the solution cannot be unique if the total charge of the background is attractive. In this case, infinitely many different stationary solutions exist. The non-uniqueness can be explained by the presence of trapped particles orbiting the attractive background charge.
The Hidden Origins of the German Enlightenment
Authors: Mulsow Martin
Published: June 2023

The early German Enlightenment is seen as a reform movement that broke free from traditional ties without falling into anti-Christian and extremist positions, on the basis of secular natural law, an anti-metaphysical epistemology, and new social ethics. But how did the works which were radical and critical of religion during this period come about? And how do they relate to the dominant 'moderate' Enlightenment? Martin Mulsow offers fresh and surprising answers to these questions by reconstructing the emergence and dissemination of some of the radical writings created between 1680 and 1720. The Hidden Origins of the German Enlightenment explores the little-known freethinkers, persecuted authors, and secretly circulating manuscripts of the era, applying an interdisciplinary perspective to the German Enlightenment. By engaging with these cross-regional, clandestine texts, a dense and highly original picture emerges of the German early Enlightenment, with its strong links with the experience of the rest of Europe.
Bilingualism Matters
Authors: Garraffa Maria , Sorace Antonella , Vender Maria
Published: June 2023

What happens in the brain when learning a second language? Can speaking more than one language provide cognitive benefits over a lifetime? What implications does an increase in bilingualism have for society? And what are the factors that can promote and support bilingualism in children and adults? This book – a translated and adapted version of Il Cervello Bilingue (2020) - answers these questions and more, providing the reader with a comprehensive yet concise guide on different topics related to bilingualism. Based on the results of the most recent studies conducted internationally, it discusses recent research findings, explains terminology, and elaborates on the current state of the field, with the aim of providing families and society with suggestions about how to encourage bilingualism. Written in an engaging and accessible style, it takes both academics and readers with no prior knowledge of the field on a journey into the bilingual brain.
Progress toward globally complete frontal ablation estimates of marine-terminating glaciers
Authors: Kochtitzky William , Copland Luke , Van Wychen Wesley , Hock Regine , Rounce David R. , Jiskoot Hester , Scambos Ted A. , Morlighem Mathieu , King Michalea , Cha Leo , Gould Luke , Merrill Paige-Marie , Glazovsky Andrey , Hugonnet Romain , Strozzi Tazio , Noël Brice , Navarro Francisco , Millan Romain , Dowdeswell Julian A. , Cook Alison , Dalton Abigail , Khan Shfaqat , Jania Jacek
Published: June 2023

Knowledge of frontal ablation from marine-terminating glaciers (i.e., mass lost at the calving face) is critical for constraining glacier mass balance, improving projections of mass change, and identifying the processes that govern frontal mass loss. Here, we discuss the challenges involved in computing frontal ablation and the unique issues pertaining to both glaciers and ice sheets. Frontal ablation estimates require numerous datasets, including glacier terminus area change, thickness, surface velocity, density, and climatic mass balance. Observations and models of these variables have improved over the past decade, but significant gaps and regional discrepancies remain, and better quantification of temporal variability in frontal ablation is needed. Despite major advances in satellite-derived large-scale datasets, large uncertainties remain with respect to ice thickness, depth-averaged velocities, and the bulk density of glacier ice close to calving termini or grounding lines. We suggest ways in which we can move toward globally complete frontal ablation estimates, highlighting areas where we need improved datasets and increased collaboration.
A Systematic Review of the Genetics and Pathology of Psychosis in Frontotemporal Dementia
Authors: Chatterjee Atri , Hirsch-Reinshagen Veronica , Scott Imogene , Cashman Neil , Hsiung Ging-Yuek Robin
Published: June 2023

Objectives:

Frontotemporal dementia (FTD) patients frequently present with psychosis, which complicates diagnosis and management. In this study, we aim to examine the relationship between psychosis and the most common genetic mutations predisposing to FTD, and in the different pathological subtypes of FTD.

Design:

We conducted a systematic review, searching the literature up to December 2022, and reviewed 50 articles that met our inclusion criteria. From the reviewed articles, we extracted and summarized data regarding the frequency of psychosis and patient characteristics in each major genetic and pathological subtype of FTD.

Results:

Among FTD patients with confirmed genetic mutations or pathological diagnosss, the frequency of psychosis was 24.2%. Among the genetic mutation carriers, C9orf72 mutation carriers had the highest frequency of psychosis (31.4%), whereas GRN (15.0%) and MAPT (9.2%) mutation carriers had lower frequencies of psychosis. MAPT mutation carriers notably developed psychosis at a younger age compared to other genetic groups. The most common psychotic symptoms were delusions among C9orf72 carriers and visual hallucinations among GRN mutation carriers. Among the pathological subtypes, 30% of patients with FUS pathology, 25.3% of patients with TDP-43 pathology, and 16.4% of patients with tau pathology developed psychosis. In the TDP-43 group, subtype B pathology was the most common subtype reported in association with psychosis.

Conclusion:

Our systematic review suggests a high frequency of psychosis in specific subgroups of FTD patients. Further studies are required to understand the structural and biological underpinnings of psychosis in FTD.
The Cholera Outbreak in Lebanon: October 2022
Authors: Helou Mariana , Khalil Mayar , Husni Rola
Published: June 2023

In recent years, Lebanon has been struggling with a socioeconomic crisis exacerbated by population displacement after the Syrian crisis, which put a significant burden on its healthcare system. An additional challenge has been the response to a cholera outbreak- a deadly waterborne disease transmitted through the fecal-oral route that usually manifests as severe watery diarrhea and can rapidly progress to death. After reports of a cholera outbreak in Syria were disclosed in September 2022, the Northern Governorate of Lebanon too began reporting cases immediately after, and the first case was confirmed on October 6, 2022. The outbreak rapidly spread to other parts of the country. As of December 9, 2022, a total of 5105 suspected cholera cases with 23 associated deaths were reported across Lebanon. An estimated 45% of these cases were of children and adolescents below the age of 15 years. With the start of the vaccination campaign, awareness programs emphasizing adequate sanitation and clean water sources have become an urgent need.
The Redress of Law – A rejoinder
Authors: Christodoulidis Emilios
Published: June 2023

The Rejoinder offers a first response to the reviews of The Redress of Law, published in this issue of ELO, and further pursues certain lines of theoretical inquiry in engagement with the reviewers’ suggestions and objections.
SHEA/IDSA/APIC Practice Recommendation: Strategies to prevent methicillin-resistant Staphylococcus aureus transmission and infection in acute-care hospitals: 2022 Update
Authors: Popovich Kyle J. , Aureden Kathy , Ham D. Cal , Harris Anthony D. , Hessels Amanda J. , Huang Susan S. , Maragakis Lisa L. , Milstone Aaron M. , Moody Julia , Yokoe Deborah , Calfee David P.
Published: June 2023

Previously published guidelines have provided comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals in implementing and prioritizing efforts to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission and infection. This document updates the “Strategies to Prevent Methicillin-Resistant Staphylococcus aureus Transmission and Infection in Acute Care Hospitals” published in 2014.1 This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.
Socioeconomic differences in antibiotic use for common infections in pediatric urgent-care centers—A quasi-experimental study
Authors: Nedved Amanda C. , Lee Brian R. , Wirtz Ann , Monsees Elizabeth , Burns Alaina , Turcotte Benedict Frances G. , El Feghaly Rana E.
Published: June 2023

Objective:

To investigate differences in the rate of firstline antibiotic prescribing for common pediatric infections in relation to different socioeconomic statuses and the impact of an antimicrobial stewardship program (ASP) in pediatric urgent-care clinics (PUCs).

Design:

Quasi-experimental.

Setting:

Three PUCs within a Midwestern pediatric academic center.

Patients and participants:

Patients aged >60 days and <18 years with acute otitis media, group A streptococcal pharyngitis, community-acquired pneumonia, urinary tract infection, or skin and soft-tissue infections who received systemic antibiotics between July 2017 and December 2020. We excluded patients who were transferred, admitted, or had a concomitant diagnosis requiring systemic antibiotics.

Intervention:

We used national guidelines to determine the appropriateness of antibiotic choice in 2 periods: prior to (July 2017–July 2018) and following ASP implementation (August 2018–December 2020). We used multivariable regression analysis to determine the odds ratios of appropriate firstline agent by age, sex, race and ethnicity, language, and insurance type.

Results:

The study included 34,603 encounters. Prior to ASP implementation in August 2018, female patients, Black non-Hispanic children, those >2 years of age, and those who self-paid had higher odds of receiving recommended firstline antibiotics for all diagnoses compared to male patients, children of other races and ethnicities, other ages, and other insurance types, respectively. Although improvements in prescribing occurred after implementation of our ASP, the difference within the socioeconomic subsets persisted.

Conclusions:

We observed socioeconomic differences in firstline antibiotic prescribing for common pediatric infections in the PUCs setting despite implementation of an ASP. Antimicrobial stewardship leaders should consider drivers of these differences when developing improvement initiatives.
A coherent composite approach for the continuous circular hydraulic jump and vortex structure
Authors: Wang Wenxi , Baayoun Abdelkader , Khayat Roger E.
Published: June 2023

We examine the structure of the continuous circular hydraulic jump and recirculation for a jet impinging on a disk. We use a composite mean-field thin-film approach consisting of subdividing the flow domain into three regions of increasing gravity strength: a developing boundary layer near impact, an intermediate supercritical viscous layer and a region comprising the jump and subcritical flow. Unlike existing models, the approach does not require any empirically or numerically adjusted boundary conditions. We demonstrate that the stress or corner singularity for a film draining at the edge is equivalent to an infinite slope of the film surface, which we impose as the downstream boundary condition. The model is validated against existing experiment and numerical simulation of the boundary-layer and Navier–Stokes equations. We find that the flow in the supercritical region remains insensitive to the change in gravity level but is greatly affected by viscosity. The existence of the jump is not necessarily commensurate with the presence of recirculation, which is strongly dependent on the upstream curvature and steepness of the jump.