bluuebunny/crossref_metadata_2025_split huggingface dataset:
Opening a can of worms: a test of the co-infection facilitation hypothesis
Authors: Rodgers Maria L. , Bolnick Daniel I. 
Published: June 2023

AbstractParasitic infections are a global occurrence and impact the health of many species. Coinfections, where two or more species of parasite are present in a host, are a common phenomenon across species. Coinfecting parasites can interact directly or indirectly via their manipulation of (and susceptibility to) the immune system of their shared host. Helminths, such as the cestode Schistocephalus solidus, are well known to suppress immunity of their host (threespine stickleback, Gasterosteus aculeatus), potentially facilitating other parasite species. Yet, hosts can evolve a more robust immune response (as seen in some stickleback populations), potentially turning facilitation into inhibition. Using wild-caught stickleback from 20 populations with non-zero S. solidus prevalence, we tested an a priori hypothesis that S. solidus infection facilitates infection by other parasites. Consistent with this hypothesis, individuals with S. solidus infections have 18.6% higher richness of other parasites compared to S. solidus-uninfected individuals from the same lakes. This facilitation-like trend is stronger in lakes where S. solidus is particularly successful but is reversed in lakes with sparse and smaller cestodes (indicative of stronger host immunity). These results suggest that a geographic mosaic of host–parasite co-evolution might lead to a mosaic of between-parasite facilitation/inhibition effects.
Data-driven profiles of attention-deficit/hyperactivity disorder using objective and ecological measures of attention, distractibility, and hyperactivity
Authors: Fernández-Martín Pilar , Rodríguez-Herrera Rocío , Cánovas Rosa , Díaz-Orueta Unai , Martínez de Salazar Alma , Flores Pilar 
Published: June 2023

AbstractIn the past two decades, the traditional nosology of attention-deficit/hyperactivity disorder (ADHD) has been criticized for having insufficient discriminant validity. In line with current trends, in the present study, we combined a data-driven approach with the advantages of virtual reality aiming to identify novel behavioral profiles of ADHD based on ecological and performance-based measures of inattention, impulsivity, and hyperactivity. One hundred and ten Spanish-speaking participants (6–16 years) with ADHD (medication-naïve, n = 57) and typically developing participants (n = 53) completed AULA, a continuous performance test embedded in virtual reality. We performed hybrid hierarchical k-means clustering methods over the whole sample on the normalized t-scores of AULA main indices. A five-cluster structure was the most optimal solution. We did not replicate ADHD subtypes. Instead, we identified two clusters sharing clinical scores on attention indices, susceptibility to distraction, and head motor activity, but with opposing scores on mean reaction time and commission errors; two clusters with good performance; and one cluster with average scores but increased response variability and slow RT. DSM-5 subtypes cut across cluster profiles. Our results suggest that latency of response and response inhibition could serve to distinguish among ADHD subpopulations and guide neuropsychological interventions. Motor activity, in contrast, seems to be a common feature among ADHD subgroups. This study highlights the poor feasibility of categorical systems to parse ADHD heterogeneity and the added value of data-driven approaches and VR-based assessments to obtain an accurate characterization of cognitive functioning in individuals with and without ADHD.
Special Issue: Epigraphy and Paleography: Bringing Records from the Distant Past to the Present
Authors: Griffin Stephen M. 
Published: June 2023

AbstractThis special issue brings together three areas of research and scholarly work areas that would have demonstrated few obvious relationships three decades ago. Digital libraries research, practices and infrastructures have transformed the study of ancient inscriptions by providing organizing principles for collections building, defining interoperability requirements and developing innovative user tools and services. Yet linking collections and their contents to support advanced scholarly work in epigraphy and paleography tests the limits of current digital libraries applications. This is due, in part, to the magnitude and heterogeneity of works created over a time period of more than five millennia. The remarkable diversity ranges from the number of types of artifacts to the methods used in their production to the singularity of individual marks contained within them. Conversion of analog collections to digital repositories is well underway—but most often not in a way that meets the basic requirements needed to support scholarly workflows. This is beginning to change. In addition to efforts to develop complex data objects, linking strategies and repositories aggregation, there is a new use of imaging technologies and computational approaches to recognize, enhance, recover and restore writings. Most recently, leading-edge artificial intelligence methods are being applied for the automated transcription of handwritten text into machine readable forms. The articles in this special issue will give examples of each.
Optimization with uncertainties: a scheduling example
Authors: Hegyháti Máté , Bakon Krisztián Attila , Holczinger Tibor 
Published: June 2023

AbstractThe optimization of manufacturing systems is rarely a deterministic task in practice, as uncertainties of various origins often have significant impact on the feasibility or quality of a production plan. The decision making process is often a complex multi-stage mechanism that anticipates and reacts to numerous parameter changes, both internal and external. Such optimization problems and the corresponding approaches are often classified and categorized based on the features of the addressed uncertainties and the desired objective. The goal of this paper is twofold. First, a systematic approach is presented to enumerate the possible optimization problems for a given set of uncertainties and degree of freedom in the planning. This approach is illustrated via a scheduling example that is inspired by literature case studies and focuses on financial objectives with varying demands and prices in the market. Then, selected problem classes identified by the approach are discussed in detail, illustrating and examining the available techniques to tackle them, citing literature studies applying the same or similar approaches.
Landslide displacement forecasting using deep learning and monitoring data across selected sites
Authors: Nava Lorenzo , Carraro Edoardo , Reyes-Carmona Cristina , Puliero Silvia , Bhuyan Kushanav , Rosi Ascanio , Monserrat Oriol , Floris Mario , Meena Sansar Raj , Galve Jorge Pedro , Catani Filippo 
Published: June 2023

AbstractAccurate early warning systems for landslides are a reliable risk-reduction strategy that may significantly reduce fatalities and economic losses. Several machine learning methods have been examined for this purpose, underlying deep learning (DL) models’ remarkable prediction capabilities. The long short-term memory (LSTM) and gated recurrent unit (GRU) algorithms are the sole DL model studied in the extant comparisons. However, several other DL algorithms are suitable for time series forecasting tasks. In this paper, we assess, compare, and describe seven DL methods for forecasting future landslide displacement: multi-layer perception (MLP), LSTM, GRU, 1D convolutional neural network (1D CNN), 2xLSTM, bidirectional LSTM (bi-LSTM), and an architecture composed of 1D CNN and LSTM (Conv-LSTM). The investigation focuses on four landslides with different geographic locations, geological settings, time step dimensions, and measurement instruments. Two landslides are located in an artificial reservoir context, while the displacement of the other two is influenced just by rainfall. The results reveal that the MLP, GRU, and LSTM models can make reliable predictions in all four scenarios, while the Conv-LSTM model outperforms the others in the Baishuihe landslide, where the landslide is highly seasonal. No evident performance differences were found for landslides inside artificial reservoirs rather than outside. Furthermore, the research shows that MLP is better adapted to forecast the highest displacement peaks, while LSTM and GRU are better suited to model lower displacement peaks. We believe the findings of this research will serve as a precious aid when implementing a DL-based landslide early warning system (LEWS).
Error bounds for a least squares meshless finite difference method on closed manifolds
Authors: Davydov Oleg 
Published: June 2023

AbstractWe present an error bound for a least squares version of the kernel based meshless finite difference method for elliptic differential equations on smooth compact manifolds of arbitrary dimension without boundary. In particular, we obtain sufficient conditions for the convergence of this method. Numerical examples are provided for the equation$$-\Delta _{\mathcal {M}} u + u = f$$-ΔMu+u=fon the 2- and 3-spheres, where$$\Delta _{\mathcal {M}} $$ΔMis the Laplace-Beltrami operator.
Chaotic coexistence of librational and rotational dynamics in the averaged planar three-body problem
Authors: Di Ruzza Sara 
Published: June 2023

AbstractThrough an appropriate change of reference frame and rescalings of the variables and the parameters introduced, the Hamiltonian of the three-body problem is written as a perturbed Kepler problem. In this system, new Delaunay variables are defined and a suitable configuration of the phase space and the mass parameters is chosen. In such a system, wide regions of librational and rotational motions where orbits are regular and stable are found. Close to the separatrix of these regions, the existence of chaotic motions presenting a double rotational and librational dynamics is proved, numerically, through Poincaré sections and the use of FLI.
Low-Carbon Investment and Credit Rationing
Authors: Haas Christian , Kempa Karol 
Published: June 2023

AbstractThis paper develops a principal-agent model with adverse selection to analyse firms’ decisions between an existing carbon-intensive technology and a new low-carbon technology requiring an externally funded initial investment. We find that a Pigouvian emission tax alone may result in credit rationing and under-investment in low-carbon technologies. Combining the Pigouvian tax with interest subsidies or loan guarantees resolves credit rationing and yields a first-best outcome. An emission tax set above the Pigouvian level can also resolve credit rationing and, in some cases, yields a first-best outcome. If a carbon price is (politically) not feasible, intervention on the credit market alone can promote low-carbon development. However, such a policy yields a second-best outcome. The issue of credit rationing is temporary if the risks of low-carbon technologies decline. However, there are social costs of delay if credit rationing is not addressed.
Beyond Belief: On Disinformation and Manipulation
Authors: Harris Keith Raymond 
Published: June 2023

Abstract
Existing analyses of disinformation tend to embrace the view that disinformation is intended or otherwise functions to mislead its audience, that is, to produce false beliefs. I argue that this view is doubly mistaken. First, while paradigmatic disinformation campaigns aim to produce false beliefs in an audience, disinformation may in some cases be intended only to prevent its audience from forming true beliefs. Second, purveyors of disinformation need not intend to have any effect at all on their audience’s beliefs, aiming instead to manipulate an audience’s behavior through alteration of sub-doxastic states. Ultimately, I argue that attention to such non-paradigmatic forms of disinformation is essential to understanding the threat disinformation poses and why this threat is so difficult to counter.
Covid-19 Data Manipulation and Reaction of Stock Markets
Authors: Bolek Monika , Bolek Cezary 
Published: June 2023

AbstractThe influence of Covid-19 pandemic crisis on rates of return is analyzed in this paper in the light of possible data manipulation related to reporting systems provided by the administration in the USA, Turkey and Poland. The study used various methods of analyzing the relationship of a discrete, non-discrete and dichotomous data nature between the studied variables. As a result, the strongest reaction of the market was observed in Turkey followed by the USA and Poland. It can be concluded that the reaction of the surveyed markets was influenced by the data manipulations. The added value of the article is related to the use of various methods to study phenomena and detect the impact of data manipulation on the markets.
High-Temperature Measurements on Viscosity and Surface Tension of the Ionic Liquid 1-Ethyl-3-methylimidazolium Bis(trifluoromethylsulfonyl)imide ([EMIM][NTf2]) up to 473 K
Authors: Zhai Ziwen , Koller Thomas M. 
Published: June 2023

AbstractIn the present study, the viscosity and surface tension of the commercial low-viscosity ionic liquid (IL) 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)-imide ([EMIM][NTf2]) were determined by a combination of surface light scattering (SLS) and the pendant-drop (PD) method between (303 and 473) K. Both methods operating at thermodynamic equilibrium were applied inside the same measurement cell at identical experimental conditions under an argon atmosphere at 0.1 MPa. For SLS measurements performed in the temperature range from (303 to 323) K, the overdamped behavior of the surface fluctuations allowed access to the viscosity with an expanded uncertainty of 2.3 % using the surface tensions determined via the PD method with an uncertainty of 2 % as input quantities. Above 323 K up to 473 K, the oscillatory behavior of the probed surface fluctuations by SLS enabled a simultaneous determination of viscosity and surface tension with average expanded uncertainties of (4 and 3) %, respectively. Multiple repetition measurements by both methods have been conducted at 323 K after experiments at larger temperatures up to 473 K, and the consistency of their results could indicate a sound thermal stability of the IL sample. The mutual agreement of the surface tension results from SLS and the PD method between (353 and 473) K demonstrates that both techniques analyze the very same IL surface. For both properties, the results from this work agree well with the majority of experimental data reported in the literature typically up to 353 K. In summary, the viscosity and surface tension results presented in this study contribute to an improved data landscape for this particular IL and ILs in general at elevated temperatures.
Sea grape (Caulerpa lentillifera) aquaculture in Van Phong Bay, Viet Nam: Evaluation of the post-harvest quality
Authors: Stuthmann Lara Elisabeth , Du Hoang Trung , Brix da Costa Beatrice , Kunzmann Andreas , Springer Karin 
Published: June 2023

AbstractCaulerpa lentillifera, known as `sea grapes´ or `green caviar´, is increasingly in demand as a sea vegetable for human consumption. The seaweed is cultivated in ponds in the Khánh Hòa province in Van Phong Bay, Viet Nam, during the dry season (March-October). The harvested sea grape fronds are graded into different qualities based on their physical characteristics for retail on the local market or for export. Based on systematic observations of sea grape fronds of two different qualities, the frond weight, frond length and rachis coloration were identified as physical characteristics important for grading. Fronds of the best quality had significantly longer (12.59 ± 2.89 vs 10.01 ± 2.51 cm) and heavier (2.37 ± 0.59 vs 1.60 ± 0.5 g) fronds with darker rachis than the other quality group. However, a logistic regression model revealed that frond weight was the best predictor of frond quality. The physiological parameter of Fv/Fm was slightly different between the qualities, but always with means > 0.7, whereas the antioxidant activity and the total phenolic content were similar (98.34 ± 19.22 vs 95.96 ± 24.98 mmol TE (100 g)−1 DW and 163.8 ± 20.14 vs 149.85 ± 15.44 mg GAE (100 g)−1 DW). To the best of our knowledge, this study took a first approach to identify quality characteristics of sea grape fronds from Van Phong Bay, Viet Nam, which can serve as a basis for adjusting cultivation parameters to improve the harvest quality by developing cultivation and post-harvest protocols. However, further research is needed to investigate the effect of certain cultivation parameters on the specific frond characteristics.
Organized Care as Antidote to Organized Violence: An Engaged Clinical Ethnography of the Los Angeles County Jail System
Authors: Levenson Jeremy , Samra Shamsher 
Published: June 2023

AbstractThe field of medical action extends beyond the clinical encounter. Rather, clinical encounters are organized by wider regimes of governance and expertise, and broader geographies of care, abandonment and violence. Clinical encounters in penal institutions condense and render visible the fundamental situatedness of all clinical care. This article considers the complexity of clinical action in carceral institutions and their wider geographies through an examination of the crisis of mental health care in jails, an issue of significant public concern in the United States and much of the world. We present findings from our engaged, collaborative clinical ethnography, which was informed by and seeking to inform already existing collective struggles. Revisiting the concept of “pragmatic solidarity” (Farmer in Partner to the poor: a Paul Farmer reader, University of California Press, Berkeley, 2010) in an era of “carceral humanitarianism” (Gilmore in Futures of Black Radicalism, Verso, New York, 2017, see also Kilgore in Repackaging mass incarceration, Counterpunch, June 6–8,http://www.counterpunch.org/2014/06/06/repackaging-mass-incarceration/, 2014), we draw on theorists who consider prisons to be institutions of “organized violence” (Gilmore and Gilmore in: Heatherton and Camp (eds) Policing the planet: why the policing crisis led to Black lives matter, Verso, New York, 2016). We argue that clinicians may have an important role in joining struggles for “organized care” that can counter institutions of organized violence.
A novel deep learning-based technique for detecting prostate cancer in MRI images
Authors: Singh Sanjay Kumar , Sinha Amit , Singh Harikesh , Mahanti Aniket , Patel Abhishek , Mahajan Shubham , Pandit Amit Kant , Varadarajan Vijayakumar 
Published: June 2023

AbstractIn the western world,the prostate cancer is major cause of death in males. Magnetic Resonance Imaging (MRI) is widely used for the detection of prostate cancer due to which it is an open area of research. The proposed method uses deep learning framework for the detection of prostate cancer using the concept of Gleason grading of the historical images. A3D convolutional neural network has been used to observe the affected region and predicting the affected region with the help of Epithelial and the Gleason grading network. The proposed model has performed the state-of-art while detecting epithelial and the Gleason score simultaneously. The performance has been measured by considering all the slices of MRI, volumes of MRI with the test fold, and segmenting prostate cancer with help of Endorectal Coil for collecting the images of MRI of the prostate 3D CNN network. Experimentally, it was observed that the proposed deep learning approach has achieved overall specificity of 85% with an accuracy of 87% and sensitivity 89% over the patient-level for the different targeted MRI images of the challenge of the SPIE-AAPM-NCI Prostate dataset.
Effects of DBD Direct Air Plasma and Gliding Arc Indirect Plasma Activated Mist on Germination, and Physiological Parameters of Rice Seed
Authors: El Shaer Mohamed , Abdel-azim Mohamed , El-welily Hala , Hussein Yasser , Abdelghani Amira , Zaki Ahmed , Mobasher Mona 
Published: June 2023

AbstractRice seeds (Oryza sativa L.) have been treated with cold atmospheric plasma in air both directly in a dielectric barrier discharge and indirectly by gliding arc discharge with plasma activated mist. Comparisons of impacts of the two methods on rice seeds germination and physiological parameters are presented.Plasma has been found to increase seeds hydrophilization and water uptake through decrease of liquid contact angle and increase of total surface free energy of seed’s coat. Germination of treated seeds and their seedling growth parameters are enhanced by plasma application. After 20 min of seeds direct and indirect exposures respectively, germination potential increases by 36.73 and 50.4%, germination rate by 26.0 and 30.0%, and germination index by 25.92 and 36.53%. Also, total shoot length increases by 42.2 and 48.5%, and total root length by 15.93 and 22.42%. Plasma enhances physiological changes by increasing nonenzymatic antioxidants substances which in turn increase the tolerance against abiotic stresses. After 20 min for direct and indirect exposures respectively, free proline increases by 30.0 and 40.0%, total soluble carbohydrates by 49.7 and 54.6%. Also, cellular reactive oxygen species (ROS) increase by 52.0 and 60.0%, and malondialdehyde (MDA) decreases by 68.0 and 88.0%. Indirect exposure of rice seeds by plasma activated mist shows enhanced effects on germination and physiological parameters compared to direct one and could be more practical when applied to large scale seeds plasma treatment.
The Education-Job Satisfaction Paradox in the Public Sector
Authors: Pita Cristina , Torregrosa Ramón J. 
Published: June 2023

Abstract
We compare the self-reported satisfaction of workers, employed in the private and the public sectors across European countries, with their working conditions and pay and have reached a controversial conclusion. Although we have found there are more educated workers in the public sector than in the private sector, higher-educated workers report lower levels of satisfaction with their working conditions and income when employed in the public sector, which was the opposite for less educated workers employed in this same sector. In contrast, we found a positive association between education and job satisfaction for workers employed in the private sector.