bluuebunny/crossref_metadata_2025 huggingface dataset:
Correlating Impacts of Injected Fuels on Carbon Emissions in Blast Furnace with Computational Fluid Dynamics Modeling
Authors: Ugarte Orlando J. , Okosun Tyamo , Nielson Samuel , Zhou Chenn Q.
Published: June 2023

A major challenge for steelmaking is the reduction of CO2 emissions. In this regard, the blast furnace (BF) is critical due to the high associated CO2 levels. This investigation assesses the impact of tuyere‐injected fuels on BF CO2 emissions. Specifically, computational fluid dynamics results obtained previously at Purdue University Northwest are analyzed to obtain CO2 emissions when natural gas (NG), syngas, hydrogen, or hydrogen/NG are injected. CO2 emissions are compared with those produced when 95 kg of NG/thm is injected. Among these scenarios, the largest CO2 reduction occurs when 102 kg of syngas/thm (COG feedstock #1) is injected at 973 K, reducing CO2 by 190.6 kg thm−1. The largest CO2 reduction obtained with NG occurs when 130 kg thm−1 is injected at 600 K, reducing emissions by 65 kg thm−1. H2 injection also reduces CO2, but requires careful adjusting to reach stable operation. For instance, injecting 35 kg of H2/thm reduces CO2 by 52 kg thm−1. Increasing gaseous injection rates can significantly reduce CO2 emissions, with fuel preheating providing an addendum, but high injection rates can lead to unstable operation. Furthermore, results show a correlation between CO2 emissions and average temperature of shaft region for multiple fuels and injection conditions.
Valorization of Mango By‐Products: Extraction and Characterization of Starch from Seed Kernels
Authors: Choudhary Poonam , Devi Thingujam Bidyalakshmi , Dawange Sandeep Popatrao , Narsaiah Kairam
Published: June 2023

This study optimizes the starch extraction process from mango seed kernels using a combined Plackett–Burman and Box–Behnken design. Further, the morphological and functional properties of extracted starch are analyzed. The particle size, temperature, time, and mixing solid–liquid ratio significantly affect the starch yield (p ≤ 0.05). The optimized conditions (0.58 mm of particle size, 39.29 min duration, temperature of 49.29 °C, and mixing solid–liquid ratio of 1:5.02 g mL−1) yield 50.34% starch with 94.95% purity. In addition, the extracted starch shows excellent lightness value with a greenish and yellowish hue. The swelling power and water solubility index are improved by increasing the temperature. The granules are round to oval and of 19.4 µm particle size and exhibit 40.08% crystallinity and an A‐type pattern under X‐ray diffraction study. In addition, the extracted starch shows more elastic behavior during rheological analysis. Results suggest that the developed process would help industries to isolate high‐quality starch at a large scale, and starch extracted in this study has the potential for various applications.
Influence of habitat and other factors on Largemouth Bass abundance in Lake Okeechobee, Florida
Authors: Hanlon Charles G. , Jordan Alyssa
Published: June 2023

Objective

Submerged aquatic vegetation (SAV) is an important part of shallow lake ecosystems. It provides protective cover and foraging habitat for age-0 and juvenile Largemouth Bass Micropterus salmoides and other small fish, creates structure and habitat for macroinvertebrates and other fauna, and can influence the physical environment by stabilizing sediments and reducing water column turbidity.

Methods

For this study, we reviewed annual abundance data for Largemouth Bass collected via electrofishing from 2002 to 2019, along with environmental covariates that included SAV cover (habitat) and turbidity.

Result

All age-groups of Largemouth Bass were positively correlated with vascular SAV cover. Age-0 Largemouth Bass were most abundant when SAV cover exceeded approximately 24% (9400 ha) of the littoral and nearshore area, while the juvenile and all-ages groups were most abundant when SAV cover exceeded 20% and 12% of the area, respectively. Following major storm events, water depth and turbidity increased, SAV cover was reduced to <5% of the littoral and nearshore area, and the abundance of age-0 Largemouth Bass was reduced more than 90%.

Conclusion

Once removed from the landscape and exposed to turbid conditions, vascular SAV will reestablish only if water clarity increases and light is sufficient to support plant growth. Lowering water levels for an extended period has been shown to reduce nearshore turbidity and jumpstart the recovery of SAV in Lake Okeechobee and other shallow lakes globally. Without adequate SAV habitat, recruitment of age-0 and juvenile Largemouth Bass will likely be suppressed. Maintaining a minimum coverage of vascular SAV (20–35%) in the littoral and nearshore area should increase the abundance of age-0 and juvenile Largemouth Bass and provide beneficial habitat for adult Largemouth Bass and other lake fauna.
Using the diagnostic assessment and achievement of college success (DAACS) to promote SRL skills among entry‐level college students: Challenges and recommendations
Authors: Cleary Timothy J. , Bryer Jason M. , Andrade Heidi L.
Published: June 2023

This chapter provides an overview of a novel computer‐based learning environment, the Diagnostic Assessment and Achievement of College Success (DAACS), designed to generate and leverage diagnostic assessment data about college students’ academic and self‐regulated learning (SRL) skills to create effective success pathways for students as they transition to college life. As implemented across multiple large‐scale research projects conducted in online, hybrid, and traditional brick and mortar college contexts, DAACS integrates diagnostic assessments with automated and actionable feedback, social supports (i.e., advisors), and various open educational resources (OERs), such as an SRL Lab and writing support. In this paper, we reveal two key challenges when implementing DAACS technology, specifically in relation to student SRL functioning and skills: (1) quality and level of participation among stakeholders, and (2) uptake of diagnostic data and feedback. Through illustrative examples and recommended solutions to these challenges, readers will gain insights about a few important yet thorny issues related to implementing and using SRL‐enhanced technological supports in college contexts.
Insects of Reproductive Structures
Authors: Strong Ward B. , Mangini Alex C. , Candau Jean-Noel
Published: June 2023

The insects that feed on reproductive structures of forest trees are not only economically important, they are fascinating examples of the ability of insects to adapt to and exploit the many niches available in forest ecosystems. Cones, fruits, seeds, nuts, catkins and pollen are rich food sources available to insect herbivores. These reproductive structures are qualitatively and quantitatively different from vegetative parts of the tree, in terms of food quality, spatial and temporal distribution, and plant protective strategies. In this chapter we will explore types of reproductive structure herbivory, nutritive value and host defenses, insect strategies and community structure, evolutionary consequences for the host, and implications for management.
IPM: The Forest Context
Authors: Sweeney Jon , Dodds Kevin J. , Fettig Christopher J. , Carnegie Angus J.
Published: June 2023

Integrated pest management (IPM) is perhaps best described as “…the maintenance of destructive agents, including insects, at tolerable levels by the planned use of a variety of preventative, suppressive or regulatory tactics that are ecologically and economically efficient and socially acceptable.
Spatial Tools and ppWebGIS Platforms for Sustainable Urban Development and Climate Change Adaptation
Authors: Mougiakou Eleni , Parskevopoulos Yannis , Tsadari Sofia
Published: June 2023

In the last decades, a shift towards more democratic, participatory processes has occurred, rooted in the need to address environmental problems and climate change threats. Moreover, these participatory processes have been increasingly required in today’s spatial plans, strategies, and studies, for example, in Sustainable Urban Mobility Plans, Urban Climate Change Adaptation and Resilience Plans, and Sustainable Development Plans. In this context, academia and industry have built various public participation web-based solutions (ppWebGIS) and other geospatial participation tools to facilitate participatory procedures and support and inform the participants (planners, policymakers, citizens, etc.) towards spatial decision-making.

However, despite the recent advancements in methodological and technological participatory geospatial tools, they are weak in addressing the complex issues found in “outlier” urban areas, i.e., areas with challenging conditions and characteristics. This paper introduces a comprehensive methodological framework for participatory spatial planning that conceptualizes and utilizes geospatial tools and platforms to address the challenges and opportunities in areas with special conditions. As part of an ongoing research program, the paper’s main contribution is to provide methodological innovation for participatory spatial planning in areas with special conditions through conceptualizing and implementing participatory geospatial tools to solve complex and multifactorial spatial problems.
Prozess- und Kostenanalyse an der Universitätsmedizin Greifswald
Authors: Krohn Markus
Published: June 2023

Im Abschnitt 2.2.3 wurde aufgezeigt, dass die Zusatzentgelte für extrakorporale Dialyseverfahren nach Verfahrensart, Dauer und Patientenalter differenzieren. Weiterhin kann durch die OPS-Kodes eine Differenzierung nach der Antikoagulation vorgenommen werden. Eine Kostenanalyse der deutschen Arbeitsgemeinschaft für Klinische Nephrologie (DAGKN) zeigt zusätzlich, dass auch die Art des Gefäßzuganges einen Einfluss auf die Kosten haben kann.
The Sustainable Housing Challenge
Authors: Moore Trivess , Doyon Andréanne
Published: June 2023

This chapter explores historic, current, and future challenges that are contributing to holding back a sustainable housing transition. In doing this, we highlight a range of challenges across different domains (e.g., technical, financial, knowledge, practice). The intent of this chapter is to present some of the common challenges to help us develop an understanding of the types of things we need to address in order to scale up the provision of sustainable housing. Some of these challenges are deeply complex and play out differently at different scales. We discuss the various challenges around the scales where decisions are typically made: the dwelling scale, the neighbourhood and city scale, and the state, national and international scale. We follow this with a discussion of the wider residential market and the unwillingness to change and the complexity of housing.
Socio-Technical Dimensions for a Sustainable Housing Transition
Authors: Moore Trivess , Doyon Andréanne
Published: June 2023

In this chapter, we explore key socio-technical dimensions that we have identified through the wider literature and our own sustainable housing research which we feel are important to address if a transition to sustainable housing is to be achieved. The ten socio-technical dimensions we cover in this chapter are:

guiding principles,

physical attributes,

knowledge,

geography,

industrial structures and organizations,

markets, users, and power,

policy, regulations, and governance,

everyday life and practices,

culture, civil society, and social movements,

ethical aspects.

This chapter explores each dimension in turn by providing a definition, overview of how the current housing regime engages with the dimension and how sustainable housing offers a different approach. We also provide a short example of how this is being provided or considered in practice.
Facilitating the Sustainable Housing Transition
Authors: Moore Trivess , Doyon Andréanne
Published: June 2023

In this chapter, we reflect on the preceding chapters of the book to discuss implications of the evidence and current context for facilitating the sustainable housing transition. We do this across three core sections. (1) We discuss the importance of drawing upon sustainability transitions theory to inform the sustainable housing transitions. This includes reflections on how we need to extend the theory to align with the unique challenges of the housing sector. (2) We discuss the sustainable housing transition, including where we are placed in that transition, potential pathways forward, and challenges that still need to be addressed. (3) We reflect on the types of innovations that are required across policy, practice, and research to help facilitate the sustainable housing transition.
Relevant dilaton stabilization
Authors: Csáki Csaba , Geller Michael , Heller-Algazi Zamir , Ismail Ameen
Published: June 2023

Abstract

We propose a simple modification of the Goldberger-Wise mechanism for stabilizing the scale of spontaneously broken conformal theories. The source of explicit conformal symmetry breaking is a relevant operator with a small coefficient, as opposed to the usual mechanism of an almost marginal operator with an order-one coefficient. In the warped 5D picture this relevant stabilization corresponds to a small tadpole for the bulk scalar on the UV brane, which can be technically natural if it is the only source for the breaking of a symmetry (for example, a discrete Z2). This modification of the stabilization mechanism has significant consequences for the nature of the conformal phase transition, since the radion/dilaton potential is no longer shallow. The bounce action is significantly reduced, leading to a weaker first-order phase transition instead of the supercooled and strongly first-order transition seen in Goldberger-Wise stabilization. This also leads to reduction of gravitational wave signals which, however, may still be observable at future detectors. We present numerical and analytical studies of the phase transition and the resulting gravitational wave signal strength, assuming that the effective dilaton potential provides a good leading approximation. While the dilaton is not expected to be generically light in this setup, in order to keep perturbative control over the effective theory one needs to mildly tune the dilaton quartic to be somewhat small.
Regularity properties of k-Brjuno and Wilton functions
Authors: Lee Seul Bee , Marmi Stefano , Petrykiewicz Izabela , Schindler Tanja I.
Published: June 2023

We study functions related to the classical Brjuno function, namelyk-Brjuno functions and the Wilton function. Both appear in the study of boundary regularity properties of (quasi) modular forms and their integrals. We consider various possible versions of them, based on the$$\alpha $$α-continued fraction developments. We study their BMO regularity properties and their behaviour near rational numbers of their finite truncations. We then complexify the functional equations which they fulfill and we construct analytic extensions of thek-Brjuno and Wilton functions to the upper half-plane. We study their boundary behaviour using an extension of the continued fraction algorithm to the complex plane. We also prove that the harmonic conjugate of the realk-Brjuno function is continuous at all irrational numbers and has a decreasing jump of$$\pi /q^k$$π/qkat rational pointsp/q.
Assessment of Machine Learning Methods to Predict Massive Blood Transfusion in Trauma
Authors: Strickland Matt , Nguyen Anthony , Wu Shinyi , Suen Sze‐Chuan , Mu Yanda , Del Rio Cuervo Juan , Shin Brandon J. , Kalakuntla Tej , Ghafil Cameron , Matsushima Kazuhide
Published: June 2023

Background

Accurately predicting which patients are most likely to benefit from massive transfusion protocol (MTP) activation may help patients while saving blood products and limiting cost. The purpose of this study is to explore the use of modern machine learning (ML) methods to develop and validate a model that can accurately predict the need for massive blood transfusion (MBT).

Methods

The institutional trauma registry was used to identify all trauma team activation cases between June 2015 and August 2019. We used an ML framework to explore multiple ML methods including logistic regression with forward and backward selection, logistic regression with lasso and ridge regularization, support vector machines (SVM), decision tree, random forest, naive Bayes, XGBoost, AdaBoost, and neural networks. Each model was then assessed using sensitivity, specificity, positive predictive value, and negative predictive value. Model performance was compared to that of existing scores including the Assessment of Blood Consumption (ABC) and the Revised Assessment of Bleeding and Transfusion (RABT).

Results

A total of 2438 patients were included in the study, with 4.9% receiving MBT. All models besides decision tree and SVM attained an area under the curve (AUC) of above 0.75 (range: 0.75–0.83). Most of the ML models have higher sensitivity (0.55–0.83) than the ABC and RABT score (0.36 and 0.55, respectively) while maintaining comparable specificity (0.75–0.81; ABC 0.80 and RABT 0.83).

Conclusions

Our ML models performed better than existing scores. Implementing an ML model in mobile computing devices or electronic health record has the potential to improve the usability.
Long-term outcomes following transcatheter aortic valve implantation with the Portico self-expanding valve
Authors: Giordano Arturo , Mas-Peiro Silvia , Fichtlscherer Stephan , Schaefer Andreas , Beyer Martin , Maisano Francesco , Ascione Guido , Buzzatti Nicola , Teles Rui , Brito João , Albuquerque Francisco , Sondergaard Lars , Vanhaverbeke Maarten , Quagliana Angelo , Costa Giuliano , Barbanti Marco , Ferraro Paolo , Morello Alberto , Cimmino Michele , Albanese Michele , Pepe Martino , Bardi Luca , Giordano Salvatore , Cittadini Antonio , Corcione Nicola , Biondi-Zoccai Giuseppe
Published: June 2023

Aim

Transcatheter aortic valve implantation (TAVI) is a mainstay in the management of severe aortic valve stenosis in elderly patients, but there is uncertainty on their long-term effectiveness. We aimed to assess the long-term outcome of patients undergoing TAVI with the Portico valve.

Methods

We retrospectively collected the data on patients in whom TAVI with Portico was attempted from 7 high-volume centres. Only patients theoretically eligible for 3 or more years of follow-up were included. Clinical outcomes, including death, stroke, myocardial infarction, reintervention for valve degeneration and hemodynamic valve performance were systematically assessed.

Results

A total of 803 patients were included, with 504 (62.8%) women, mean age of 82 years, median EuroSCORE II of 3.1%, and 386 (48.1%) subjects at low/moderate risk. The median follow-up was 3.0 years (3.0; 4.0). The composite of death, stroke, myocardial infarction, and reintervention for valve degeneration occurred in 37.5% (95% confidence interval: 34.1–40.9%), with all-cause death in 35.1% (31.8–38.4%), stroke in 3.4% (1.3–3.4%), myocardial infarction in 1.0% (0.3–1.5%), and reintervention for valve degeneration in 1.1% (0.6–2.1%). The mean aortic valve gradient at follow-up was 8.1 ± 4.6 mmHg, and at least moderate aortic regurgitation was present in 9.1% (6.7–12.3%). Independent predictors of major adverse events or death were: peripheral artery disease, chronic obstructive pulmonary disease, estimated glomerular filtration rate, atrial fibrillation, prior pacemaker implantation, EuroSCORE II, and reduced left ventricular ejection fraction (all p < 0.05).

Conclusions

Portico use is associated with favorable long-term clinical outcomes. Clinical outcomes were largely impacted by baseline risk factors and surgical risk.
Role of dietary sodium restriction in chronic heart failure: systematic review and meta-analysis
Authors: Urban Szymon , Fułek Michał , Błaziak Mikołaj , Fułek Katarzyna , Iwanek Gracjan , Jura Maksym , Grzesiak Magdalena , Szymański Oskar , Stańczykiewicz Bartłomiej , Ptaszkowski Kuba , Zymlinski Robert , Ponikowski Piotr , Biegus Jan
Published: June 2023

Background

Dietary sodium restriction remains a guidelines-approved lifestyle recommendation for chronic heart failure (CHF) patients. However, its efficacy in clinical outcome improvement is dubious.

Objective

The study evaluated whether dietary sodium restriction in CHF reduces clinical events.

Methods

We performed a systematic review of the following databases: Academic Search Ultimate, ERIC, Health Source Nursing/Academic Edition, MEDLINE, Embase, Clinicaltrials.gov and Cochrane Library (trials) to find studies analysing the impact of sodium restriction in the adult CHF population. Both observational and interventional studies were included. Exclusion criteria included i.e.: sodium consumption assessment based only on natriuresis, in-hospital interventions or mixed interventions—e.g. sodium and fluid restriction in one arm only. The review was conducted following PRISMA guidelines. Meta-analysis was performed for the endpoints reported in at least 3 papers. Analyses were conducted in Review Manager (RevMan) Version 5.4.1.

Results

Initially, we screened 9175 articles. Backward snowballing revealed 1050 additional articles. Eventually, 9 papers were evaluated in the meta-analysis. All-cause mortality, HF-related hospitalizations and the composite of mortality and hospitalisation were reported in 8, 6 and 3 articles, respectively. Sodium restriction was associated with a higher risk of the composite endpoint (OR 4.12 [95% CI 1.23–13.82]) and did not significantly affect the all-cause mortality (OR 1.38 [95% CI 0.76–2.49]) or HF hospitalisation (OR 1.63 [95% CI 0.69–3.88]).

Conclusions

In a meta-analysis, sodium restriction in CHF patients worsened the prognosis in terms of a composite of mortality and hospitalizations and did not influence all-cause mortality and HF hospitalisation rate.

Graphical abstract
Opening a can of worms: a test of the co-infection facilitation hypothesis
Authors: Rodgers Maria L. , Bolnick Daniel I.
Published: June 2023

Parasitic 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

In 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

This 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

The 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

Accurate 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

We 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

Through 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

This 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

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

The 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

In 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

Caulerpa 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

The 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

In 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

Rice 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

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.
A Mixed-Methods Approach for Evaluating Implementation Processes and Program Costs for a Hypertension Management Program Implemented in a Federally Qualified Health Center
Authors: Tucker-Brown Aisha , Spafford Michelle , Wittenborn John , Rein David , Marshall Ashley , Beasley Kincaid Lowe , Vaughan Marla , Nelson Natalie , Dougherty Michelle , Ahn Roy
Published: June 2023

Team-based care approaches are effective at improving hypertension control and have been used in clinical practice to improve hypertension outcomes. This study implemented and evaluated the Hypertension Management Program (HMP), which was originally developed in a high-resource health setting, in a health system with fewer resources and a patient population disproportionately affected by hypertension. Our objectives were to describe how a health system could adapt HMP to meet their needs and calculate total program costs. HMP uses a team-based, patient-centered approach involving clinical pharmacists who contribute to managing patients who have hypertension and ultimately preventing premature death due to uncontrolled hypertension. HMP has 10 components (e.g., EHR patient registries and outreach lists, no copayment walk-in blood pressure checks). Our project involved implementing the key components of HMP in a federally qualified health center (FQHC) in South Carolina. Adaptations from the key components of HMP were made to fit the participants’ settings. A mixed-methods evaluation assessed implementation processes, program costs, and implementation facilitators and barriers. From September 2018 to December 2019, clinical pharmacists conducted 758 hypertension management visits (HMVs) with 316 patients with hypertension. Total program costs for HMP were $325,532 overall and $16,277 per month. Monthly cost per patient was $3.62. The high engagement among clinical pharmacists, along with provider engagements, followed up by the subsequent referral of patients to HMP, facilitated the implementation process. Staff members observed improvements in hypertension control, which increased participation buy-in. Barriers included staff turnover, the perception among some providers that HMP took too much time, as well as perception of HMP as a pharmacy-specific initiative. A team-based, patient-centered approach to hypertension management can be adapted for FQHCs or similar settings that serve patient populations disproportionately affected by hypertension.
Underutilized Crocus Sativus L. Flowers: A Hidden Source of Sustainable High Value-Added Ingredients
Authors: Cerdá-Bernad Débora , Valero-Cases Estefanía , Pérez-Llamas Francisca , Pastor Joaquín Julián , Frutos María José
Published: June 2023

Crocus sativus L. is used as a spice due to its organoleptic characteristics. Only flower stigmas are used for its production, as the rest of the flower is discarded as waste. This fact represents a lack of sustainability, since around 230,000 flowers are necessary to produce 1 kg of saffron. The main aim of this study was to contribute to the valorization of Crocus sativus L. spice and its floral by-products, through the study of their nutritional value and composition, in terms of hydrophilic and lipophilic compounds, as well as their functional properties. The results showed that saffron stigmas and floral bio-residues presented high contents of fiber, and the most abundant macronutrient were the carbohydrates, followed by proteins, and a low content in fats. All samples had high concentrations of glucose, fructose, lactic and malic acids, and minerals, mainly K, Ca and Mg. Furthermore, the polyunsaturated fatty acids were predominant, being linoleic acid (C18:2n6) the most abundant. Therefore, this research provides more in-depth information about the composition of saffron stigmas and floral by-products, to be considered as promising sources for the development of functional ingredients with new applications in the food industry.