bluuebunny/crossref_metadata_2025_split huggingface dataset:
The non-anthropocentric informational agents: Codes, software, and the logic of emergence in cybersecurity
Authors: Fouad Noran Shafik 
Published: December 2021

AbstractMany theoretical approaches to cybersecurity adopt an anthropocentric conceptualisation of agency; that is, tying the capacity to act to human subjectivity and disregarding the role of the non-human in co-constructing its own (in)security. This article argues that such approaches are insufficient in capturing the complexities of cyber incidents, particularly those that involve self-perpetuating malware and autonomous cyber attacks that can produce unintentional and unpredictable consequences. Using interdisciplinary insights from the philosophy of information and software studies, the article counters the anthropocentrism in the cybersecurity literature by investigating the agency of syntactic information (that is, codes/software) in co-producing the logics and politics of cybersecurity. It specifically studies the complexities of codes/software as informational agents, their self-organising capacities, and their autonomous properties to develop an understanding of cybersecurity as emergent security. Emergence is introduced in the article as a non-linear security logic that captures the peculiar agential capacities of codes/software and the ways in which they challenge human control and intentionality by co-constructing enmity and by co-producing the subjects and objects of cybersecurity.
Analyzing the modes of reasoning in design using the SAPPhIRE model of causality and the Extended Integrated Model of Designing
Authors: Bhatt Apoorv Naresh , Majumder Anubhab , Chakrabarti Amaresh 
Published: December 2021

AbstractLiterature suggests that people typically understand knowledge by induction and produce knowledge by synthesis. This paper revisits the various modes of reasoning – explanatory abduction, innovative abduction, deduction, and induction – that have been proposed by earlier researchers as crucial modes of reasoning underlying the design process. First, our paper expands earlier work on abductive reasoning – an essential mode of reasoning involved in the process of synthesis – by understanding its role with the help of the “SAPPhIRE” model of causality. The explanations of abductive reasoning in design using the SAPPhIRE model have been compared with those using existing models. Second, the paper captures and analyzes various modes of reasoning during design synthesis with the help of the “Extended Integrated Model of Designing”. The analysis of participants' verbal speech and outcomes shows the model's ability to explain the various modes of reasoning that occur in design. The results indicate the above models to provide a more extensive account of reasoning in design synthesis. Earlier empirical validation of both the models lends further support to the claim of their explanatory capacity.
Longitudinal pathways between emotional difficulties and school absenteeism in middle childhood: Evidence from developmental cascades
Authors: Panayiotou Margarita , Finning Katie , Hennessey Alexandra , Ford Tamsin , Humphrey Neil 
Published: December 2021

AbstractEmotional difficulties are associated with both authorized and unauthorized school absence, but there has been little longitudinal research and the temporal nature of these associations remains unclear. This study presents three-wave random-intercepts panel models of longitudinal reciprocal relationships between teacher-reported emotional difficulties and authorized and unauthorized school absence in 2,542 English children aged 6 to 9 years old at baseline, who were followed-up annually. Minor differences in the stability effects were observed between genders but only for the authorized absence model. Across all time points, children with greater emotional difficulties had more absences, and vice versa (authorized: ρ = .23–.29, p < .01; unauthorized: ρ = .28, p < .01). At the within-person level, concurrent associations showed that emotional difficulties were associated with greater authorized (β = .15–.17, p < .01) absence at Time 3 only, but with less unauthorized (β = −.08–.13, p < .05) absence at Times 1 and 2. In cross-lagged pathways, neither authorized nor unauthorized absence predicted later emotional difficulties, and emotional difficulties did not predict later authorized absence at any time point. However, greater emotional difficulties were associated with fewer unauthorized absences across time (β = −13–.22, p < .001). The implications of these findings are discussed.
Automated SEM Image Analysis of the Sphere Diameter, Sphere-Sphere Separation, and Opening Size Distributions of Nanosphere Lithography Masks
Authors: Riedl Thomas , Lindner Jörg K.N. 
Published: December 2021

AbstractColloidal nanosphere monolayers—used as a lithography mask for site-controlled material deposition or removal—offer the possibility of cost-effective patterning of large surface areas. In the present study, an automated analysis of scanning electron microscopy (SEM) images is described, which enables the recognition of the individual nanospheres in densely packed monolayers in order to perform a statistical quantification of the sphere size, mask opening size, and sphere-sphere separation distributions. Search algorithms based on Fourier transformation, cross-correlation, multiple-angle intensity profiling, and sphere edge point detection techniques allow for a sphere detection efficiency of at least 99.8%, even in the case of considerable sphere size variations. While the sphere positions and diameters are determined by fitting circles to the spheres edge points, the openings between sphere triples are detected by intensity thresholding. For the analyzed polystyrene sphere monolayers with sphere sizes between 220 and 600 nm and a diameter spread of around 3% coefficients of variation of 6.8–8.1% for the opening size are found. By correlating the mentioned size distributions, it is shown that, in this case, the dominant contribution to the opening size variation stems from nanometer-scale positional variations of the spheres.
Declarative Approaches to Counterfactual Explanations for Classification
Authors: BERTOSSI LEOPOLDO 
Published: December 2021

AbstractWe propose answer-set programs that specify and compute counterfactual interventions on entities that are input on a classification model. In relation to the outcome of the model, the resulting counterfactual entities serve as a basis for the definition and computation of causality-based explanation scores for the feature values in the entity under classification, namely responsibility scores. The approach and the programs can be applied with black-box models, and also with models that can be specified as logic programs, such as rule-based classifiers. The main focus of this study is on the specification and computation of best counterfactual entities, that is, those that lead to maximum responsibility scores. From them one can read off the explanations as maximum responsibility feature values in the original entity. We also extend the programs to bring into the picture semantic or domain knowledge. We show how the approach could be extended by means of probabilistic methods, and how the underlying probability distributions could be modified through the use of constraints. Several examples of programs written in the syntax of the DLV ASP-solver, and run with it, are shown.
Mean and Turbulent Characteristics of a Bottom Mixing‐Layer Forced by a Strong Surface Tide and Large Amplitude Internal Waves
Authors: Zulberti A. P. , Jones N. L. , Rayson M. D. , Ivey G. N. 
Published: December 2021

AbstractWe present 15 days of both mean and turbulent field observations bottom mixing‐layer at a gently sloping 250 m deep continental shelf site, energized by tides and nonlinear internal waves (NLIWs). The tidal frequency forcing was due to the combined effects of the barotropic tide and a mode‐1 internal tide (IT), while the NLIWs were predominantly mode‐1 waves of depression. The bottom mixing‐layer thickness varied at both semidiurnal and sub‐tidal ∼O(10)d frequencies, with an average thickness of around 10 m. Compression and expansion of the mixing‐layer by both the IT and NLIWs affected the mean velocity profiles in the mixing‐layer, while the phasing between the barotropic and baroclinic flows led to an asymmetry in mean velocity profiles between periods of rising and falling isotherms. With the exception of periods of flow reversal, the turbulent kinetic energy balance and turbulent stress observations were consistent with the existence of an inertial‐sublayer with thickness of approximately 10%–15% of the mixing‐layer thickness ( ∼1 m), even beneath NLIWs. In the outer portion of the mixing‐layer—that is, above the inertial‐sublayer—NLIWs modulated the local turbulence spectra. We discuss the observations in the context of a predictive model for mixing‐layer thickness. The analysis suggests that the high‐frequency variability in mixing‐layer thickness was dominated by internal wave pumping, though strength of the ambient stratification and the frequency of the forcing were important controls on the time‐averaged (sub‐tidal) variation.
Modeling Decadal Salt Marsh Development: Variability of the Salt Marsh Edge Under Influence of Waves and Sediment Availability
Authors: Willemsen P. W. J. M. , Smits B. P. , Borsje B. W. , Herman P. M. J. , Dijkstra J. T. , Bouma T. J. , Hulscher S. J. M. H. 
Published: December 2021

AbstractSalt marshes can contribute to coastal protection, but the magnitude of the protection depends on the width of the marsh. The cross‐shore width of the marsh is to a large extent determined by the delicate balance between seaward expansion and landward retreat. The influence of the magnitude of daily occurring mild weather conditions and sediment availability on the variability of salt marsh width has not been systematically assessed. This paper investigates how the magnitude of homogeneous hydrodynamic forcing, combined with sediment availability, affects the biophysical development, and more specifically retreat and expansion of salt marshes. The dynamic extent of the salt marsh is assessed by modeling online‐coupled hydrodynamics, morphodynamics and vegetation growth using the numerical Delft3D‐Flexible Mesh model, and a vegetation growth module. Simulated patterns around the salt marsh edge resembled field observations, as well as the simulated temporal variability of the lateral position of the salt marsh edge. In the model, the salt marsh extended seaward at low wave forcing (0.00 m; 0.05 m), and retreated landward at higher wave forcing (0.10 m; 0.15 m). With increasing physical stress, the salt marsh edge was found at lower elevations, indicating an unhealthy system with a retreating marsh edge due to vegetation mortality, whereas decreasing physical stresses result in a higher salt marsh edge, enabling expansion. This balance suggests the importance of response time of vegetation to physical stress. Yet, the salt marsh forced with higher waves was able to switch from a retreating extent retrogradational to an expansional behavior as sediment supply increased.
A High‐Resolution Atlas of the Eastern Tropical Pacific Oxygen Deficient Zones
Authors: Kwiecinski Jarek V. , Babbin Andrew R. 
Published: December 2021

AbstractOxygen deficient zones (ODZs) are important biogeochemical provinces of the global oceans wherein standing dissolved oxygen concentrations decrease to nanomolar levels. Despite their confinement, these regions are disproportionally important to the ocean's role in modulating Earth's climate through the interactions between the marine nitrogen cycle and that of carbon. Moreover, the spatial domain of low oxygen regions of the ocean is predicted to change as a consequence of ocean warming, increased stratification, and changes in circulation and productivity. However, the expanse of the modern ODZs is poorly resolved due to a dearth of direct sampling compounded with errors that arise in the processing and gridding of the sparse measurements that do exist. Here, we take a novel approach to map the horizontal and vertical extent of the two major ODZs of the eastern tropical Pacific via analysis of meter‐scale resolution electrode sensors from both ship casts and Argo profiles, rather than from discretized bottle measurements. The resulting three‐dimensional data product is based on a compendium of nearly 15 million measurements taken across three decades and provides the precise locations of low oxygen water, elucidating the ODZs' three‐dimensional structures. It can be utilized by researchers to validate models, plan cruise occupations, and as a comparison for future change. Calculations made with this high‐resolution atlas also provide the volumes, layers of maximal areal extent, and other descriptive statistics for both Pacific ODZs. Finally, the atlas reveals fine‐scale features of oxygenated water mass intrusions and regional differences across these anoxic zones.
Synthetic Evaluation of Infrasonic Multipole Waveform Inversion
Authors: Iezzi Alexandra M. , Matoza Robin S. , Fee David , Kim Keehoon , Jolly Arthur D. 
Published: December 2021

AbstractAcoustic source inversions estimate the mass flow rate of volcanic explosions or yield of chemical explosions and provide insight into potential source directionality. However, the limitations of applying these methods to complex sources and their ability to resolve a stable solution have not been investigated in detail. We perform synthetic infrasound waveform inversions that use 3‐D Green’s functions for a variety of idealized and realistic deployment scenarios using both a flat plane and Yasur volcano, Vanuatu as examples. We investigate the ability of various scenarios to retrieve the input source functions and relative amplitudes for monopole and multipole (monopole and dipole) inversions. Infrasound waveform inversions appear to be a robust method to quantify mass flow rates from simple sources (monopole) using deployments of infrasound sensors placed around a source, but care should be taken when analyzing and interpreting results from more complex acoustic sources (multipole) that have significant directional components. In the examples we consider the solution is stable for monopole inversions with a signal‐to‐noise ratio greater than five and the dipole component is small. For most scenarios investigated, the vertical dipole component of the multipole explosion source is poorly constrained and can impact the ability to recover the other source term components. Because multipole inversions are ill‐posed for many deployments, a low residual does not necessarily mean the proper source vector has been recovered. Synthetic studies can help investigate the limitations and place bounds on information that may be missing using monopole and multipole inversions for potentially directional sources.
Bayesian Model Calibration Using Surrogate Streamflow in Ungauged Catchments
Authors: Yoon Hae Na , Marshall Lucy , Sharma Ashish , Kim Seokhyeon 
Published: December 2021

AbstractWe present a novel approach for modeling streamflow in ungauged catchments. Because of their widespread availability and global coverage, remotely sensed data provide an attractive alternative to supplement the absence of streamflow data in hydrological model calibration. One observable signal holds particular appeal; the satellite‐derived calibration ratio‐measurement (C/M ratio) has been widely studied as a direct measurement of streamflow because of its physical relationship to streamflow and demonstrated correlation with in situ streamflow. This study identifies the challenges in calibrating a hydrological model using a satellite‐derived C/M ratio, presenting a rationale designed to account for the limitations that these data pose. A new Bayesian calibration approach is developed that uses the surrogate streamflow derived from the C/M ratio in place of direct streamflow observations. We assess and demonstrate our approach for three Australian Hydrologic Reference Stations, which can be considered free from anthropogenic effects, with distinct attributes. The results indicate the competency of the proposed approach, showing model performance with 0.54 ∼ 0.78 Nash‐Sutcliffe efficiency values, with the uncertainties in the model calibration quantified via Markov Chain Monte Carlo sampling. Overall, our study finds the new model calibration promising for predictions in ungauged basins (PUB), as the global data coverage of satellite data and the suitability of the approach suggest significant improvements over traditional approaches to PUB.
Patch individual filter layers in CNNs to harness the spatial homogeneity of neuroimaging data
Authors: Eitel Fabian , Albrecht Jan Philipp , Weygandt Martin , Paul Friedemann , Ritter Kerstin 
Published: December 2021

AbstractConvolutional neural networks (CNNs)—as a type of deep learning—have been specifically designed for highly heterogeneous data, such as natural images. Neuroimaging data, however, is comparably homogeneous due to (1) the uniform structure of the brain and (2) additional efforts to spatially normalize the data to a standard template using linear and non-linear transformations. To harness spatial homogeneity of neuroimaging data, we suggest here a new CNN architecture that combines the idea of hierarchical abstraction in CNNs with a prior on the spatial homogeneity of neuroimaging data. Whereas early layers are trained globally using standard convolutional layers, we introduce patch individual filters (PIF) for higher, more abstract layers. By learning filters in individual latent space patches without sharing weights, PIF layers can learn abstract features faster and specific to regions. We thoroughly evaluated PIF layers for three different tasks and data sets, namely sex classification on UK Biobank data, Alzheimer’s disease detection on ADNI data and multiple sclerosis detection on private hospital data, and compared it with two baseline models, a standard CNN and a patch-based CNN. We obtained two main results: First, CNNs using PIF layers converge consistently faster, measured in run time in seconds and number of iterations than both baseline models. Second, both the standard CNN and the PIF model outperformed the patch-based CNN in terms of balanced accuracy and receiver operating characteristic area under the curve (ROC AUC) with a maximal balanced accuracy (ROC AUC) of 94.21% (99.10%) for the sex classification task (PIF model), and 81.24% and 80.48% (88.89% and 87.35%) respectively for the Alzheimer’s disease and multiple sclerosis detection tasks (standard CNN model). In conclusion, we demonstrated that CNNs using PIF layers result in faster convergence while obtaining the same predictive performance as a standard CNN. To the best of our knowledge, this is the first study that introduces a prior in form of an inductive bias to harness spatial homogeneity of neuroimaging data.
Utilizing DeepSqueak for automatic detection and classification of mammalian vocalizations: a case study on primate vocalizations
Authors: Romero-Mujalli Daniel , Bergmann Tjard , Zimmermann Axel , Scheumann Marina 
Published: December 2021

AbstractBioacoustic analyses of animal vocalizations are predominantly accomplished through manual scanning, a highly subjective and time-consuming process. Thus, validated automated analyses are needed that are usable for a variety of animal species and easy to handle by non-programing specialists. This study tested and validated whether DeepSqueak, a user-friendly software, developed for rodent ultrasonic vocalizations, can be generalized to automate the detection/segmentation, clustering and classification of high-frequency/ultrasonic vocalizations of a primate species. Our validation procedure showed that the trained detectors for vocalizations of the gray mouse lemur (Microcebus murinus) can deal with different call types, individual variation and different recording quality. Implementing additional filters drastically reduced noise signals (4225 events) and call fragments (637 events), resulting in 91% correct detections (Ntotal = 3040). Additionally, the detectors could be used to detect the vocalizations of an evolutionary closely related species, the Goodman’s mouse lemur (M. lehilahytsara). An integrated supervised classifier classified 93% of the 2683 calls correctly to the respective call type, and the unsupervised clustering model grouped the calls into clusters matching the published human-made categories. This study shows that DeepSqueak can be successfully utilized to detect, cluster and classify high-frequency/ultrasonic vocalizations of other taxa than rodents, and suggests a validation procedure usable to evaluate further bioacoustics software.
Tracing contacts to evaluate the transmission of COVID-19 from highly exposed individuals in public transportation
Authors: Ponte Caio , Carmona Humberto A. , Oliveira Erneson A. , Caminha Carlos , Lima Antonio S. , Andrade José S. , Furtado Vasco 
Published: December 2021

AbstractWe investigate, through a data-driven contact tracing model, the transmission of COVID-19 inside buses during distinct phases of the pandemic in a large Brazilian city. From this microscopic approach, we recover the networks of close contacts within consecutive time windows. A longitudinal comparison is then performed by upscaling the traced contacts with the transmission computed from a mean-field compartmental model for the entire city. Our results show that the effective reproduction numbers inside the buses, $$Re^{bus}$$

R

e

bus

, and in the city, $$Re^{city}$$

R

e

city

, followed a compatible behavior during the first wave of the local outbreak. Moreover, by distinguishing the close contacts of healthcare workers in the buses, we discovered that their transmission, $$Re^{health}$$

R

e

health

, during the same period, was systematically higher than $$Re^{bus}$$

R

e

bus

. This result reinforces the need for special public transportation policies for highly exposed groups of people.
A triple-blind randomized clinical trial of different associations between dexamethasone and non-steroids anti-inflammatories for preemptive action in third molar extractions
Authors: Momesso Gustavo Antonio Correa , Grossi-Oliveira Gustavo Augusto , Silva William Phillip Pereira , Akira Renan , Chiba Fernando , Polo Tárik Ocon Braga , de Lima Neto Tiburtino José , Rios Bárbara Ribeiro , Bassi Ana Paula Farnezi , Sumida Doris Hissako , Han Michael , Miloro Michael , Faverani Leonardo Perez 
Published: December 2021

AbstractThe aim of this study is to evaluate the preemptive analgesic effects of dexamethasone (DEX) alone or combined with non-steroidal anti-inflammatory drugs (NSAIDs) in third molar surgeries. The subjects were divided into five groups (n = 20 teeth/group); subjects received only 8 mg of dexamethasone 1 h before the surgical procedure (DEX group), or in combination with etodolac (DEX + ETO), ketorolac (DEX + KET), ibuprofen (DEX + IBU), loxoprofen (DEX + LOX). Paracetamol 750 mg was provided as the number of rescue analgesics (NRA). Salivary PGE2 expression was measured preoperatively and at 48 h. Edema and Maximum mouth opening (MMO) were measured postoperatively at 48 h and 7 days. A visual analog scale (VAS) was performed postoperatively at 6, 12, 24, 48, 72 h, and 7 days. Salivary expression of PGE2 showed a decrease only for the DEX group. Edema and MMO and NRA consumption showed no significant differences among the groups (P > 0.05). The VAS showed a significantly lower pain perception at 6 h after the surgery for the DEX + ETO and DEX + KET groups (P < 0.05). The combination of DEX and NSAIDS should be considered for preemptive acute postsurgical pain management in third molar surgery. In some drug associations such as dexamethasone 8 mg + NSAIDS (ETO and KET) in the pre-operative time, only a few rescue analgesics are necessary.