bluuebunny/crossref_metadata_2025 huggingface dataset:
Increased elasticity of sucrose demand during hyperdopaminergic states in rats
Authors: Minnaard A. Maryse , Luijendijk Mieneke C. M. , Baars Annemarie M. , Drost Lisa , Ramakers Geert M. J. , Adan Roger A. H. , Lesscher Heidi M. B. , Vanderschuren Louk J. M. J.
Published: January 2022

Rationale

Deficits in cost–benefit decision-making are a core feature of several psychiatric disorders, including substance addiction, eating disorders and bipolar disorder. Mesocorticolimbic dopamine signalling has been implicated in various processes related to cognition and reward, but its precise role in reward valuation and cost–benefit trade-off decisions remains incompletely understood.

Objectives

We assessed the role of mesocorticolimbic dopamine signalling in the relationship between price and consumption of sucrose, to better understand its role in cost–benefit decisions.

Methods

Dopamine neurons in the ventral tegmental area (VTA) were chemogenetically activated in rats, and a behavioural economics approach was used to quantify the relationship between price and consumption of sucrose. Motivation for sucrose was also assessed under a progressive ratio (PR) schedule of reinforcement. To further gauge the role of dopamine in cost–benefit trade-offs for sucrose, the effects of treatment with D-amphetamine and the dopamine receptor antagonist alpha-flupentixol were assessed.

Results

Chemogenetic activation of VTA dopamine neurons increased demand elasticity, while responding for sucrose under a PR schedule of reinforcement was augmented upon stimulation of VTA dopamine neurons. Treatment with amphetamine partially replicated the effects of chemogenetic dopamine neuron activation, whereas treatment with alpha-flupentixol reduced free consumption of sucrose and had mixed effects on demand elasticity.

Conclusions

Stimulation of mesocorticolimbic dopaminergic neurotransmission altered cost–benefit trade-offs in a complex manner. It reduced the essential value of palatable food, increased incentive motivation and left free consumption unaltered. Together, these findings imply that mesocorticolimbic dopamine signalling differentially influences distinct components of cost expenditure processes aimed at obtaining rewards.
Performance of free-flow field-step electrophoresis as cleanup step for the non-target analysis of environmental water samples
Authors: Rösch Tobias , Weber Gerhard , Bader Tobias , Wicht Anna-Jorina , Huhn Carolin
Published: January 2022

For the analysis of low concentrations of micropollutants in environmental water samples, efficient sample enrichment and cleanup are necessary to reduce matrix effects and to reach low detection limits. For analytes of low and medium polarity, solid-phase extraction is used, but robust methods for the preconcentration of highly polar or ionizable analytes are scarce. In this work, field-step electrophoresis (FSE) was developed as an environmental sample cleanup technique for ionizable micropollutants and ionic transformation products. The FSE electrolyte system preconcentrated 15 acidic model analytes (pKa from −2.2 to 9.1) present in aqueous samples in two fractions by factors of 5–10. Simultaneously, highly mobile matrix compounds were removed including inorganic ions such as sulfate and chloride. The fractions were either directly injected for downstream analysis by reversed-phase liquid chromatography (RPLC) or further processed by evaporative preconcentration with subsequent reconstitution in an organic solvent suitable for separation methods like hydrophilic interaction chromatography. The FSE/RPLC-MS method exhibited high quantitative precision with RSDs of 3–6%. The method was successfully applied to a spiked river water sample and its performance compared with common solid-phase extraction and evaporative concentration, demonstrating a high analyte coverage. FSE combined with non-target screening by RPLC-MS revealed a strong reduction in matrix load especially at low retention times. Seventeen compounds were identified in the FSE fractions sampled at the field step boundary by retention time, accurate mass, and mass fragments. Suspect screening by FSE/RPLC-MS was facilitated by FSE’s selectivity for anionic compounds.
Growth, crystal structure, Hirshfeld surface and vibrational properties of a new supramolecular hybrid material: (C4H7N2)2TeBr6
Authors: Mhiri Marwa , Kammoun Omar , Lhoste Jerome , Auguste Sandy , Boujelbene Mohamed
Published: January 2022

A novel tellurium (IV) hybrid compound with 2-methylimidazole was prepared. The crystal was grown by slow evaporation method from aqueous solutions at room temperature giving birth to a new compound with formula (C4H7N2)2TeBr6. The structure was determined by single-crystal X-ray diffraction. It crystallizes in the monoclinic system, space group C 2/c, with the following parameters: a = 18.577(2)Å, b = 9.1497(10)Å, c = 13.5355(17)Å, α = 90°, β = 123.835(5)°, γ = 90° and Z = 8. The structure was solved with a final R = 0.044 for 2783 independent reflections. The crystal arrangement consists of [TeBr6]2− anions surrounded by [C4H7N2]2+ cations. The stability of the structure was ensured by hydrogen bonding contacts (N–H…Br) lengths that are in the range of 3.490–3.682 Å. The infrared spectra (FTIR) were recorded in the 4000–550 cm−1, confirming the existence of vibrational modes that correspond to the organic and inorganic groups. The crystal packing was stabilized mainly by Br…H (73.6%) interactions. Hirshfeld surface calculations were conducted to further investigate intermolecular interactions, associated 2D fingerprint plots and enrichment ratio, revealing the quantitatively relative contribution of these interactions in the crystal packing.
Seasonal forecast skill of upper-ocean heat content in coupled high-resolution systems
Authors: McAdam Ronan , Masina Simona , Balmaseda Magdalena , Gualdi Silvio , Senan Retish , Mayer Michael
Published: January 2022

Ocean heat content (OHC) anomalies typically persist for several months, making this variable a vital component of seasonal predictability in both the ocean and the atmosphere. However, the ability of seasonal forecasting systems to predict OHC remains largely untested. Here, we present a global assessment of OHC predictability in two state-of-the-art and fully-coupled seasonal forecasting systems. Overall, we find that dynamical systems make skilful seasonal predictions of OHC in the upper 300 m across a range of forecast start times, seasons and dynamical environments. Predictions of OHC are typically as skilful as predictions of sea surface temperature (SST), providing further proof that accurate representation of subsurface heat contributes to accurate surface predictions. We also compare dynamical systems to a simple anomaly persistence model to identify where dynamical systems provide added value over cheaper forecasts; this largely occurs in the equatorial regions and the tropics, and to a greater extent in the latter part of the forecast period. Regions where system performance is inadequate include the sub-polar regions and areas dominated by sharp fronts, which should be the focus of future improvements of climate forecasting systems.
Potential vorticity perspective of the genesis of a Tibetan Plateau vortex in June 2016
Authors: Wu Guoxiong , Tang Yiqiong , He Bian , Liu Yimin , Mao Jiangyu , Ma Tingting , Ma Ting
Published: January 2022

At midnight on 27–28 June 2016, a Tibetan Plateau (TP) Vortex (TPV) generated over the western TP that subsequently caused a downstream record-breaking rainstorm and extremely severe natural disaster. Based on reanalysis data and satellite imagery, this study investigates the formation of this TPV from a potential vorticity (PV) perspective. Results show that, in late June 2016, a remarkable circulation anomaly occurred over the TP and its peripheral area, with easterly flow in the middle and lower troposphere developing in the subtropical zone, replacing the normal westerly flow there. Its forefront merged with the southwesterly flow from the west and penetrated and converged over the western TP where the surface was warmer than normal, forming a low-level jet and downward slantwise isentropic surfaces in-situ. When the air parcel slid down the slantwise isentropic surface, its vertical relative vorticity developed owing to slantwise vorticity development associated with PV restructuring. At the same time, the penetrating southwesterly flow brought abundant water vapor to the western TP and induced increasing sub-cloud entropy and air ascent there. Low-layer cloud formed and the cloud liquid water content increased. The strong latent heat that was released in association with the formation of cloud produced strong diabatic heating near 400 hPa at night and strong PV generation below. The normal diurnal variation was interrupted and the vortex was generated near the surface. These results demonstrate that, against a favorable circulation background, both adiabatic and diabatic PV processes are crucial for TPV genesis.
Feedback of tropical cyclones on El Niño diversity. Part I: Phenomenon
Authors: Wang Qiuyun , Li Jianping
Published: January 2022

Understanding of the El Niño phenomenon is improving and several studies have considered the dynamics of El Niño diversity, however, the important role of tropical cyclones has rarely been reported. Here we show a clear feedback of tropical cyclones (TCs) over the western North Pacific (WNP) on the El Niño diversity. Strong (weak) accumulated cyclone energy helps to shift the center of strongest sea surface temperature anomalies 3 months later to the equatorial eastern (central) Pacific, and thus supporting the development of the eastern-Pacific (central-Pacific) El Niño. Local sea surface temperature anomalies in the Niño-3.4/Niño-3/Niño-4 region and tropical western Pacific, zonal wind anomalies over the tropical central-western Pacific and Madden‒Julian Oscillation play small roles in the process that WNP TCs affect El Niño diversity. Moreover, the greater number of central-Pacific El Niño events after 1999/2000 may be associated with weaker accumulated cyclone energy in this period.
Wind kinetic energy climatology and effective resolution for the ERA5 reanalysis
Authors: Bolgiani P. , Calvo-Sancho C. , Díaz-Fernández J. , Quitián-Hernández L. , Sastre M. , Santos-Muñoz D. , Farrán J. I. , González-Alemán J. J. , Valero F. , Martín M. L.
Published: January 2022

ERA5 represents the state of the art for atmospheric reanalyses and is widely used in meteorological and climatological research. In this work, this dataset is evaluated using the wind kinetic energy spectrum. Seasonal climatologies are generated for 30° latitudinal bands in the Northern Hemisphere (periodic domain) and over the North Atlantic area (limited-area domain). The spectra are also assessed to determine the effective resolution of the reanalysis. The results present notable differences between the latitudinal domains, indicating that ERA5 is properly capturing the synoptic conditions. The seasonal variability is adequate too, being winter the most energetic, and summer the least energetic season. The limited area domain results introduce a larger energy density and range. Despite the good results for the synoptic scales, the reanalysis’ spectra are not able to properly reproduce the dissipation rates at mesoscale. This is a source of uncertainties which needs to be taken into account when using the dataset. Finally, a cyclone tropical transition is presented as a case study. The spectrum generated shows a clear difference in energy density at every wavelength, as expected for a highly-energetic status of the atmosphere.
Prion disease modelled in Drosophila
Authors: Bujdoso Raymond , Smith Andrew , Fleck Oliver , Spiropoulos John , Andréoletti Olivier , Thackray Alana M.
Published: January 2022

Prion diseases are fatal neurodegenerative conditions of humans and various vertebrate species that are transmissible between individuals of the same or different species. A novel infectious moiety referred to as a prion is considered responsible for transmission of these conditions. Prion replication is believed to be the cause of the neurotoxicity that arises during prion disease pathogenesis. The prion hypothesis predicts that the transmissible prion agent consists of PrPSc, which is comprised of aggregated misfolded conformers of the normal host protein PrPC. It is important to understand the biology of transmissible prions and to identify genetic modifiers of prion-induced neurotoxicity. This information will underpin the development of therapeutic and control strategies for human and animal prion diseases. The most reliable method to detect prion infectivity is by in vivo transmission in a suitable experimental host, which to date have been mammalian species. Current prion bioassays are slow, cumbersome and relatively insensitive to low titres of prion infectivity, and do not lend themselves to rapid genetic analysis of prion disease. Here, we provide an overview of our novel studies that have led to the establishment of Drosophila melanogaster, a genetically well-defined invertebrate host, as a sensitive, versatile and economically viable animal model for the detection of mammalian prion infectivity and genetic modifiers of prion-induced toxicity.
Feature extraction-based intelligent algorithm framework with neural network for solving conditional nonlinear optimal perturbation
Authors: Yuan Shijin , Zhang Huazhen , Liu Yaxuan , Mu Bin
Published: January 2022

Conditional nonlinear optimal perturbation (CNOP) defines an optimization problem to study predictability and sensitivity of the oceanic and climatic events in the nonlinear system. One effective method to solve the corresponding problem is feature extraction-based intelligent algorithm (FEIA) framework. In the previous study, the mapper and the re-constructor of the framework are generally obtained by principal component analysis (PCA), but the solving performance still needs to further improve. Recently, neural network has attracted the attention of lots of researcher, and many structures of neural network can be used to construct the mapping-reconstruction structure of FEIA framework. However, the related studies applying neural network in FEIA framework are lacking. Compared with PCA, neural network might obtain a proper structure for FEIA framework with the well-directed training. Therefore, this paper suggests two ways applying neural network in FEIA framework, and the corresponding frameworks are tested to solve CNOP of double-gyre variation in Regional Ocean Modeling System (ROMS). The results show that FEIA framework with neural network can obtain the solutions with better objective function values, and the corresponding solutions have a larger probability leading to the related physical phenomenon.
Automated ECG multi-class classification system based on combining deep learning features with HRV and ECG measures
Authors: Eltrass Ahmed S. , Tayel Mazhar B. , Ammar Abeer I.
Published: January 2022

Electrocardiogram (ECG) serves as the gold standard for noninvasive diagnosis of several types of heart disorders. In this study, a novel hybrid approach of deep neural network combined with linear and nonlinear features extracted from ECG and heart rate variability (HRV) is proposed for ECG multi-class classification. The proposed system enhances the ECG diagnosis performance by combining optimized deep learning features with an effective aggregation of ECG features and HRV measures using chaos theory and fragmentation analysis. The constant-Q non-stationary Gabor transform technique is employed to convert the 1-D ECG signal into 2-D image which is sent to a pre-trained convolutional neural network structure, called AlexNet. The pair-wise feature proximity algorithm is employed to select the optimal features from the AlexNet output feature vector to be concatenated with the ECG and HRV measures. The concatenated features are sent to different types of classifiers to distinguish three distinct subjects, namely congestive heart failure, arrhythmia, and normal sinus rhythm (NSR). The results reveal that the linear discriminant analysis classifier has the highest accuracy compared to the other classifiers. The proposed system is investigated with real ECG data taken from well-known databases, and the experimental results show that the proposed diagnosis system outperforms other recent state-of-the-art systems in terms of accuracy 98.75%, specificity 99.00%, sensitivity of 98.18%, and computational time 0.15 s. This demonstrates that the proposed system can be used to assist cardiologists in enhancing the accuracy of ECG diagnosis in real-time clinical setting.
Environmental identification of arbuscular mycorrhizal fungi using the LSU rDNA gene region: an expanded database and improved pipeline
Authors: Delavaux Camille S. , Ramos Robert J. , Sturmer Sidney L. , Bever James D.
Published: January 2022

Arbuscular mycorrhizal fungi (AMF; Glomeromycota) are difficult to culture; therefore, establishing a robust amplicon-based approach to taxa identification is imperative to describe AMF diversity. Further, due to low and biased sampling of AMF taxa, molecular databases do not represent the breadth of AMF diversity, making database matching approaches suboptimal. Therefore, a full description of AMF diversity requires a tool to determine sequence-based placement in the Glomeromycota clade. Nonetheless, commonly used gene regions, including the SSU and ITS, do not enable reliable phylogenetic placement. Here, we present an improved database and pipeline for the phylogenetic determination of AMF using amplicons from the large subunit (LSU) rRNA gene. We improve our database and backbone tree by including additional outgroup sequences. We also improve an existing bioinformatics pipeline by aligning forward and reverse reads separately, using a universal alignment for all tree building, and implementing a BLAST screening prior to tree building to remove non-homologous sequences. Finally, we present a script to extract AMF belonging to 11 major families as well as an amplicon sequencing variant (ASV) version of our pipeline. We test the utility of the pipeline by testing the placement of known AMF, known non-AMF, and Acaulospora sp. spore sequences. This work represents the most comprehensive database and pipeline for phylogenetic placement of AMF LSU amplicon sequences within the Glomeromycota clade.
Association between relapses, stress, and depression in people with multiple sclerosis during the COVID-19 pandemic
Authors: Sparaco Maddalena , Miele Giuseppina , Lavorgna Luigi , Abbadessa Gianmarco , Bonavita Simona
Published: January 2022

Background

Stress is a potential trigger for clinical and radiological activity in Multiple Sclerosis (MS). COVID-19 pandemic has been a relevant source of mental distress in people with MS (pwMS) and deeply impacted on disease management.

Objective

To investigate the association between stress, anxiety, depression, and risk of relapse during the COVID-19 pandemic.

Methods

From an electronic database used for clinical practice, we extracted data of relapsing–remitting (RR) or relapsing-progressive (RP) MS patients and calculated the annualized relapse rate (ARR) during 2019 and 2020. From 01/12/2020 to 30/12/2020, enrolled patients were invited to fill in a Google Forms survey to investigate depression, anxiety, stress, and Post-Traumatic Stress Disorder (PTSD).

Results

We selected 216 patients with RR or RP-MS to calculate ARR: compared to 2019, in 2020 there was a significant increase in ARR (p = 0.0142).

Over 216 selected pwMS, 154 completed the survey. Matching the survey responses and incidence of relapses in 2020, there was a significant association between relapses and stress (p = 0.030) and relapses and depression (p = 0.011), but not between relapses and anxiety (p = 0.130) or PTSD (p = 0.279).

Conclusions

Our results support the hypothesis that pandemic-related stress is associated to clinical exacerbations, both as a possible consequence of the COVID-19 impact on MS care.
Arboricity games: the core and the nucleolus
Authors: Xiao Han , Fang Qizhi
Published: January 2022

The arboricity of a graph is the minimum number of forests required to cover all its edges. In this paper, we examine arboricity from a game-theoretic perspective and investigate cost-sharing in the minimum forest cover problem. We introduce the arboricity game as a cooperative cost game defined on a graph. The players are edges, and the cost of each coalition is the arboricity of the subgraph induced by the coalition. We study properties of the core and propose an efficient algorithm for computing the nucleolus when the core is not empty. In order to compute the nucleolus in the core, we introduce the prime partition which is built on the densest subgraph lattice. The prime partition decomposes the edge set of a graph into a partially ordered set defined from minimal densest minors and their invariant precedence relation. Moreover, edges from the same partition always have the same value in a core allocation. Consequently, when the core is not empty, the prime partition significantly reduces the number of variables and constraints required in the linear programs of Maschler’s scheme and allows us to compute the nucleolus in polynomial time. Besides, the prime partition provides a graph decomposition analogous to the celebrated core decomposition and the density-friendly decomposition, which may be of independent interest.
Not kennt kein Gebot? Sondervermögen als Speicher von Notlagenkrediten
Authors: Büttner Thiess
Published: January 2022

The German federal government is facing criticism for using the exemption from the national debt brake due to the coronavirus crisis to expand the fiscal leeway for its future energy and climate policies. The budget dispute is taking place against the backdrop of a massive expansion of government debt in Europe. In the following, the author explain the critique of the latest supplementary budget and argues that the federal government has missed the opportunity to prove that the fiscal policy options within the existing rules are sufficient.
A paradox of age in early childhood education: A review of the literature and survey of Australian educators working with three-year-old children
Authors: Elwick Sheena , White E. Jayne
Published: January 2022

A paradox concerning age exists in early childhood education (ECE) across many countries today, evident in the literature, curriculum, policy, funding, and provision. This paradox comprises two distinct approaches that call for either a specialised developmental approach to discrete age groups or a generic attitude concerning childhoods with no age distinction at all. This article traces the presence and impact of the paradox of age through an Australian study comprising two components: a review of the literature concerning age; and, a survey undertaken in two states where different treatments of age were evident: NSW and Victoria—with a particular interest in what was happening for three-year-olds. 171 responses were received 102 (NSW) and 69 (Victoria). The review of the literature generated four main themes that when considered in relation to the survey responses revealed the tendency of ECE researchers, policymakers, and educators to situate children within a “discourse of becoming” that focusses attention towards children’s maturity and skills, and school readiness. While this discourse has been used productively, its prevalence in this study suggests that many children attending ECE services are likely to experience learning environments that do not always acknowledge the importance of the here and now, or the wealth of experience and knowledge they bring to these environments. This calls attention to the attitudes and assumptions of educators themselves concerning the treatment of younger learners; as well as the constraints and opportunities that policymakers provide for effective provision, and that influence both the nature of and access to ECE.
Automotive Perception System Evaluation with Reference Data from a UAV’s Camera Using ArUco Markers and DCNN
Authors: Blachut Krzysztof , Danilowicz Michal , Szolc Hubert , Wasala Mateusz , Kryjak Tomasz , Komorkiewicz Mateusz
Published: January 2022

Testing and evaluation of an automotive perception system is a complicated task which requires special equipment and infrastructure. To compute key performance indicators and compare the results with real-world situation, some additional sensors and manual data labelling are often required. In this article, we propose a different approach, which is based on a UAV equipped with a 4K camera flying above a test track. Two computer vision methods are used to precisely determine the positions of the objects around the car – one based on ArUco markers and the other on a DCNN (we provide the algorithms used on GitHub). The detections are then correlated with the perception system readings. For the static and dynamic experiments, the differences between various systems are mostly below 0.5 m. The results of the experiments performed indicate that this approach could be an interesting alternative to existing evaluation solutions.
The Spatial Dynamics of Homelessness in Australia: Urbanisation, Intra-City Dynamics and Affordable Housing
Authors: Batterham Deb , Cigdem-Bayram Melek , Parkinson Sharon , Reynolds Margaret , Wood Gavin
Published: January 2022

While homelessness in Australia has remained relatively stable at the national level, its spatial distribution is becoming more nuanced. This paper draws on homelessness estimates produced by the Australian Bureau of Statistics to explore the spatial dynamics of homelessness in Australia over a fifteen-year period. Building on existing work, we show that homelessness is becoming more urbanised with evidence of spatial convergence, mainly driven by a surge in severe crowding in our major cities. However, when exploring intra-city patterns, we find distinctive intra-city spatial dynamics featuring strong suburbanisation of ‘couch surfing’ in state capital cities, contrasting with shifts in severe crowding numbers toward middle and inner regions of most state capitals. We argue that these dynamics reflect the retreat of affordable rental housing supply to the outer suburban fringe, and the coping strategies that ‘couch surfers’ and those aspiring to live in the inner cities are compelled to follow in response to the changing spatial configuration of affordable housing.
Oil utilization degree at various pore sizes via different displacement methods
Authors: Li Teng , Gao Hui , Wang Chen , Cheng Zhilin , Xue Junjie , Zhang Zhe , Luo Kaiqing , Li Ning , Liu Xufei , Cao Jiangfeng
Published: January 2022

A reasonable displacement method is essential to improve the oil displacement efficiency of tight reservoirs. In this study, three different displacement methods were utilized on the tight core samples obtained from the Yanchang Formation Chang 8 and Chang 9 tight oil reservoirs: spontaneous imbibition displacement, various water flooding rate displacement and water flooding displacement after spontaneous imbibitions; furthermore, the oil utilization degree of the residual oil in various pores was discussed. The oil displacement efficiency of the spontaneous imbibitions was approximately 26.91% and 29.56% for the Chang 8 and Chang 9 samples, respectively. With an increasing water flooding rate, the oil displacement efficiency features an inverse “V”-like tendency, and a water flooding rate of 0.06 mL/min was the optimal value as; the oil displacement efficiency achieved was 63.56% and 60.27% for the Chang 8 and Chang 9, respectively. When compared with spontaneous imbibitions, at a displacement rate of 0.06 mL/min after spontaneous imbibition, the oil displacement efficiency could be further increased to 50.02% and 30.35%, respectively. The differences in the oil displacement efficiency using various displacement methods are primarily related to the degree of utilization of residual oil in various pores. The progressively refined pore classification method is used to study the degree of oil utilization in various pores, and the pores in the tight reservoir can be divided into four types: P1, P2, P3 and P4. Regarding the spontaneous imbibition displacement, the displacement of the residual oil is dominantly determined by the residual oil present in the P2 and P3 pores; as the residual oil massively accumulates in the P2 pores, the discharging of the residual oil in this part finally determines the oil displacement efficiency when the water flooding rates changed. At a water flooding rate of 0.06 mL/min after spontaneous imbibition, the oil utilization degree of residual oil in various pores is enhanced, particularly for the P2, P3, and P4 pores, and the pore structure contributes to the increase in the oil displacement efficiency. Using the progressively refined pore classification method, the complexity of the distribution of residual oil in tight reservoirs could be studied quantitatively and elaborately, and the results can efficiently guide the development of residual oil in tight oil reservoirs.
Images of Artificial Intelligence: a Blind Spot in AI Ethics
Authors: Romele Alberto
Published: January 2022

This paper argues that the AI ethics has generally neglected the issues related to the science communication of AI. In particular, the article focuses on visual communication about AI and, more specifically, on the use of certain stock images in science communication about AI — in particular, those characterized by an excessive use of blue color and recurrent subjects, such as androgyne faces, half-flesh and half-circuit brains, and variations on Michelangelo’s The Creation of Adam. In the first section, the author refers to a “referentialist” ethics of science communication for an ethical assessment of these images. From this perspective, these images are unethical. While the ethics of science communication generally promotes virtues like modesty and humility, similar images are arrogant and overconfident. In the second section, the author uses French philosopher Jacques Rancière’s concepts of “distribution of the sensible,” “disagreement,” and “pensive image.” Rancière’s thought paves the way to a deeper critique of these images of AI. The problem with similar images is not their lack of reference to the “things themselves.” It rather lies in the way they stifle any possible forms of disagreement about AI. However, the author argues that stock images and other popular images of AI are not a problem per se, and they can also be a resource. This depends on the real possibility for these images to support forms of pensiveness. In the conclusion, the question is asked whether the kind of ethics or politics of AI images proposed in this article can be applied to AI ethics tout court.
On the convergence of infinite towers of powers and logarithms for general initial data: applications to Lambert W function sequences
Authors: Toledo F. J.
Published: January 2022

The objective of this paper is to provide the exact sets of initial data ensuring the convergence or divergence of a special class of real towers of powers and logarithms. All the terms forming these towers have a common value except the cusp element, that is indeed the initial data of the sequences defining the towers. The results obtained will be applied to some Lambert W function sequences, providing also the whole set of initial data which ensure their convergence or divergence.
How commodity prices and technical development has influenced exploration strategies: a case study from Sweden
Authors: Weihed Pär
Published: January 2022

In Sweden, mining of metallic mineral resources goes back at least 1000 years, possibly much longer. This paper reviews the development of exploration over the past 500 years and discusses exploration based on 1) demand and price, 2) technical development, and 3) legislation. Without doubt, exploration efforts have been driven by an early demand, especially from the Swedish crown and well-known mines such as Falun copper mine and Sala silver mine sustained the Swedish crown and financed several wars during the seventeenth and eighteenth centuries for several centuries. The fluctuation in metal prices, basically a function of demand, due to technical development and industrialization, has been an important driver for the focus of exploration over the last 100 years, and even more so during the last 50 years when exploration, besides base metals and iron, has focussed on more critical raw materials for the energy transition and green technology. The technical development has also meant that new methods have become available for exploration, not the least deep exploration methods and Swedish innovations have played a major role in drilling technology, geophysical instrument development and other areas. This is discussed based on development in drilling technology, geological, geophysical and geochemical methods. Finally, a review of the how the mining legislation has changed over the last 500 years is provided where this is placed in the context of how it has influenced private investment in exploration and what role the Swedish state has played.
Students’ feedback experiences and expectations pre- and post-university entry
Authors: Gray Keith , Riegler Robert , Walsh Michael
Published: January 2022

Feedback on submitted work is a crucial element of students’ learning process, but UK undergraduate students are often dissatisfied with the nature and process of university feedback. This article explores the causes of this dissatisfaction by analysing students’ past feedback experiences pre-university and how these relate to their expectations regarding feedback at the Higher Education level. This study is based on a large survey undertaken at a UK Business School at the beginning of course induction meetings for 1st year undergraduate students. The results reveal that there is a significant misalignment between students’ university feedback expectations and actual university feedback. These findings highlight the importance of managing student expectations regarding the nature and timeliness of feedback. This paper offers suggestions for feedback design and managing students' feedback expectations for course leaders to facilitate students’ transition from schools and colleges to UK universities.
Reflections on educational leadership for sustainability: a Brazilian case study
Authors: Sudan Daniela Cassia , Zuin Vânia Gomes
Published: January 2022

Large-scale socio-environmental education to foster a culture of sustainability and transform degrading situations is considered a matter of worldwide urgency. Considering this, we present and discuss results from a thesis that investigated the potentials and challenges of a participatory methodology, capillarity architecture, to educate sustainability leaders used on a socio-environmental training programme for public servants from a Brazilian Higher Education Institution. Capillarity architecture, launched by the Brazilian Federal Government in 2005, is a methodological strategy that encompasses participatory action research and collective networks of educators for training in an exponential format. The participants in the process undergo training while developing educational practices for their university peers. The overall study included 2500 individuals, who were assigned to one of 160 learning collectives in seven university campuses. The research method includes a participatory-research approach, a focus group, participant observation and discursive textual analysis of process documents. The results are discussed considering two points: (1) Impacts of capillarity architecture on the university experience and; (2) Challenges and tensions between the commitment to leadership formation on a large scale and the search for emancipation in EE. It can be concluded that even considering the permanent risk of impairing quality in exponential Environmental Education training, capillarity (in its critical principles) allows for: gains in autonomy, critical reflection, exchanging experiences and repertoires within the university, educating new leaders, in addition to the concomitant engagement of a larger audience. The results of this project also provide us with evidence that leadership formation in sustainability is influenced by the access or not of the participants and coordinators to material conditions (budget, infrastructure, personnel). The relevance of promoting concrete investments in environmental education and training towards sustainability is indicated, so that large-scale training can take place in territories that have significant social inequalities. Capillarity architecture questions the traditional format of organisational training. It provides for the exchange of experiences among its participants, elaboration and development of courses in the socio-environmental area in a collective way, based on problems and social relations of the local territory. These are fundamental aspects when we think about leadership formation on a large scale in broad policies, which involve different cultures and diverse socioeconomic conditions worldwide.
Opportunities for antibiotic stewardship in emergency department or hospitalized patients with asymptomatic bacteriuria: identifying risk factors for antibiotic treatment
Authors: Bixby Morgan L. , Raux Brian R. , Bhalla Aakansha , McCoy Christopher , Hirsch Elizabeth B.
Published: January 2022

Antibiotic treatment of asymptomatic bacteriuria (ASB) is considered inappropriate and may lead to adverse events. This 2-center, retrospective cohort study including emergency department or inpatient adults identified pyuria (odds ratio, 2.43; 95% confidence interval, 1.17–5.01; P = .02) as the only independent risk factor for antibiotic treatment of ASB.
Developing a consensus-driven, plain-language clinical research glossary for study participants and the clinical research community
Authors: Baedorf Kassis Sylvia , White Sarah A. , Bierer Barbara E.
Published: January 2022

Clinical research is complex, and research-related terms can be challenging to understand. Clear, supportive communication with patients, potential study participants, and their caregivers must be prioritized by healthcare providers as well as investigators and their research teams. In clinical research, health literacy best practices support the ethical tenets of respect, justice, and beneficence. Plain language advances the understanding of informed consent documents, as well as comprehension of educational information, recruitment materials, study instructions, and study results summaries, among others. Further, a more collaborative research partnership is fostered when study participants are given understandable materials, while a lack of understanding can delay accrual and decrease adherence. We launched a pilot initiative to develop a consensus-driven, plain language clinical research glossary to promote clarity, consistency, and transparency across clinical research stakeholder groups. The resulting resource, described herein, is intended to be used widely to support a greater understanding of clinical research and empower study participants. Considerations for expansion are also discussed.
Ambient high-frequency seismic surface waves in the firn column of central west Antarctica
Authors: Chaput Julien , Aster Rick , Karplus Marianne , Nakata Nori
Published: January 2022

Firn is the pervasive surface material across Antarctica, and its structures reflect its formation and history in response to environmental perturbations. In addition to the role of firn in thermally isolating underlying glacial ice, it defines near-surface elastic and density structure and strongly influences high-frequency (> 5 Hz) seismic phenomena observed near the surface. We investigate high-frequency seismic data collected with an array of seismographs deployed on the West Antarctic Ice Sheet (WAIS) near WAIS Divide camp in January 2019. Cross-correlations of anthropogenic noise originating from the approximately 5 km-distant camp were constructed using a 1 km-diameter circular array of 22 seismographs. We distinguish three Rayleigh (elastic surface) wave modes at frequencies up to 50 Hz that exhibit systematic spatially varying particle motion characteristics. The horizontal-to-vertical ratio for the second mode shows a spatial pattern of peak frequencies that matches particle motion transitions for both the fundamental and second Rayleigh modes. This pattern is further evident in the appearance of narrow band spectral peaks. We find that shallow lateral structural variations are consistent with these observations, and model spectral peaks as Rayleigh wave amplifications within similarly scaled shallow basin-like structures delineated by the strong velocity and density gradients typical of Antarctic firn.
Understanding Deep Learning with Statistical Relevance
Authors: Räz Tim
Published: January 2022

This paper argues that a notion of statistical explanation, based on Salmon’s statistical relevance model, can help us better understand deep neural networks. It is proved that homogeneous partitions, the core notion of Salmon’s model, are equivalent to minimal sufficient statistics, an important notion from statistical inference. This establishes a link to deep neural networks via the so-called Information Bottleneck method, an information-theoretic framework, according to which deep neural networks implicitly solve an optimization problem that generalizes minimal sufficient statistics. The resulting notion of statistical explanation is general, mathematical, and subcausal.
The Perils of Estimating Disengagement Effects of Deadly Terrorist Attacks Utilizing Social Media Data
Authors: Hansen Tanja Marie
Published: January 2022

This comment discusses the impact of social media rule enforcement protocols on research on online data sources. It argues that the conclusions of the article ‘Do Islamic State's Deadly Attacks Disengage, Deter, or Mobilize Supporters?’ concerning the recruitment effects of deadly attacks cannot be assumed to hold when considering the timing of Twitter account suspensions. It highlights four ways in which suspensions can confound evidence of demobilization despite the introduction of control variables and fixed-effects model specifications. All change the composition of the sample in four non-random ways. First, suspending connected Islamic State accounts may result in follower loss. Secondly, Twitter suspension procedures may be tied to account characteristics, such as follower accrual rates. Thirdly, suspended accounts that re-emerge introduce replication bias. Fourthly, account closure may reflect user movement to other platforms in response to changing security environments following deadly attacks. In conclusion, caution is advised when platform-introduced variation risks altering the sample composition in non-random ways.
Healing after transoral carbon dioxide laser surgery for early glottic cancer
Authors: Jabbour N , Tracy J C , Du E , Tracy L F
Published: January 2022

Objective

This study aimed to evaluate the clinical significance of granulation tissue after endoscopic carbon dioxide laser surgery for glottic cancer.

Method

This was a retrospective review of 36 patients who underwent endoscopic carbon dioxide laser surgery for T1 and T2 glottic cancer. Post-operative, endoscopic examinations were rated by three blinded otolaryngologists for time to heal and presence of granulation. Patient and surgical factors were compared with time to heal and granulation.

Results

A total of 16 of 36 wounds (44 per cent) developed granulation tissue, and 24 wounds (67 per cent) healed without requiring surgical intervention. A total of 7 of 8 wounds biopsied more than 3.5 months after surgery had persistent cancer versus 1 of 4 wounds biopsied at equal to or less than 3.5 months (85.7 per cent vs 25 per cent; p = 0.03). Biopsy at more than 3.5 months was associated with 28-fold increased odds of cancer in biopsy compared with biopsy at equal to or less than 3.5 months (odds ratio, 28.0; 95 per cent confidence interval, 1.088–373.3).

Conclusion

After carbon dioxide laser surgery for glottic cancer, development of granulation tissue is common. Granulation that persists for more than 3.5 months necessitates biopsy because of increased risk of persistent cancer.
Emergence speed comparison by non-linear regression and approached by time-to-event models for censored data
Authors: Michelon Thomas B. , Belniaki Andreza C. , Taconeli Cesar A. , Vieira Elisa S. N. , Panobianco Maristela
Published: January 2022

Determining the germination speed is essential in experiments in the field of seed technology, as it allows the performance evaluation of a seed lot and the creation of predictive models. To this end, the literature addresses several methods and indexes. The objective of this study was to compare the main methods of emergence speed analysis in seeds, namely the non-linear regression models and the Emergence Speed Index (ESI), with the time-to-event models. The research was conducted with peach palm seeds (Bactris gasipaes) that were measured for viability and vigour through daily evaluations for 4 months. Vigour was evaluated by the quantification of the seed emergence speed, which was performed in three ways: ESI, non-linear regression and non-linear regression considering germination as a time-to-event event. From the results obtained, we conclude that the ESI is not a good indicator to evaluate the emergence speed; the non-linear regression model underestimates the errors and, thus, increases the probability of misclassifying treatments; the time-to-event model is more reliable in classifying treatments according to the emergence speed.
Increased Radon Exposure From Thawing of Permafrost Due To Climate Change
Authors: Glover P. W. J. , Blouin M.
Published: January 2022

Radon is a natural radioactive gas accounting for approximately one in 10 lung cancer deaths, with substantially higher death rates in sub‐Arctic communities. Radon transport is significantly reduced in permafrost, but permafrost is now thawing due to climate change. The effect of permafrost thawing on domestic radon exposure is unknown. Here we present results from radon transport modeling through soil, permafrost, and model buildings either with basements or built on piles. We find that permafrost acts as an effective radon barrier, reducing radiation exposure to a tenth of the background level while producing a ten‐fold increase in the radon activity behind the barrier. When we model thawing of the permafrost barrier, we find no increase in radon to the background level for buildings on piles. However, for buildings with basements, the radon increases to over one hundred times its initial value and can remain above the 200 Bq/m3 threshold for up to 7 years depending on the depth of the permafrost and the speed of thawing. When thawing speed is taken into account, radiations remain higher than the threshold for all scenarios where 40% thawing occurs within 15 years. This new information suggests that a significant sub‐Arctic population could be exposed to radon levels dangerous to health as a result of climate change thawing of permafrost, with implications for health provision, building codes, and ventilation advice.