bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models
Authors: Oesterle Jonathan , Krämer Nicholas , Hennig Philipp , Berens Philipp 
Published: August 2022

AbstractUnderstanding neural computation on the mechanistic level requires models of neurons and neuronal networks. To analyze such models one typically has to solve coupled ordinary differential equations (ODEs), which describe the dynamics of the underlying neural system. These ODEs are solved numerically with deterministic ODE solvers that yield single solutions with either no, or only a global scalar error indicator on precision. It can therefore be challenging to estimate the effect of numerical uncertainty on quantities of interest, such as spike-times and the number of spikes. To overcome this problem, we propose to use recently developed sampling-based probabilistic solvers, which are able to quantify such numerical uncertainties. They neither require detailed insights into the kinetics of the models, nor are they difficult to implement. We show that numerical uncertainty can affect the outcome of typical neuroscience simulations, e.g. jittering spikes by milliseconds or even adding or removing individual spikes from simulations altogether, and demonstrate that probabilistic solvers reveal these numerical uncertainties with only moderate computational overhead.
Attention-based advantage actor-critic algorithm with prioritized experience replay for complex 2-D robotic motion planning
Authors: Zhou Chengmin , Huang Bingding , Hassan Haseeb , Fränti Pasi 
Published: August 2022

AbstractRobotic motion planning in dense and dynamic indoor scenarios constantly challenges the researchers because of the motion unpredictability of obstacles. Recent progress in reinforcement learning enables robots to better cope with the dense and unpredictable obstacles by encoding complex features of the robot and obstacles into the encoders like the long-short term memory (LSTM). Then these features are learned by the robot using reinforcement learning algorithms, such as the deep Q network and asynchronous advantage actor critic algorithm. However, existing methods depend heavily on expert experiences to enhance the convergence speed of the networks by initializing them via imitation learning. Moreover, those approaches based on LSTM to encode the obstacle features are not always efficient and robust enough, therefore sometimes causing the network overfitting in training. This paper focuses on the advantage actor critic algorithm and introduces an attention-based actor critic algorithm with experience replay algorithm to improve the performance of existing algorithm from two perspectives. First, LSTM encoder is replaced by a robust encoder attention weight to better interpret the complex features of the robot and obstacles. Second, the robot learns from its past prioritized experiences to initialize the networks of the advantage actor-critic algorithm. This is achieved by applying the prioritized experience replay method, which makes the best of past useful experiences to improve the convergence speed. As results, the network based on our algorithm takes only around 15% and 30% experiences to get rid of the early-stage training without the expert experiences in cases with five and ten obstacles, respectively. Then it converges faster to a better reward with less experiences (near 45% and 65% of experiences in cases with ten and five obstacles respectively) when comparing with the baseline LSTM-based advantage actor critic algorithm. Our source code is freely available at the GitHub (https://github.com/CHUENGMINCHOU/AW-PER-A2C).
Recursive encoder network for the automatic analysis of STEP files
Authors: Miles Victoria , Giani Stefano , Vogt Oliver 
Published: August 2022

AbstractAutomated tools which can understand and interface with CAD (computer-aided design) models are of significant research interest due to the potential for improving efficiency in manufacturing processes. At present, most research into the use of artificial intelligence to interpret three-dimensional data takes input in the form of multiple two-dimensional images of the object or in the form of three-dimensional grids of voxels. The transformation of the input data necessary for these approaches inevitably leads to some loss of information and limitations of resolution. Existing research into the direct analysis of model files in STEP (standard for the exchange of product data) format tends to follow a rules-based approach to analyse models of a certain type, resulting in algorithms without the benefits of flexibility and complex understanding which artificial intelligence can provide. In this paper, a novel recursive encoder network for the automatic analysis of STEP files is presented. The encoder network is a flexible model with the potential for adaptation to a wide range of tasks and finetuning for specific CAD model datasets. Performance is evaluated using a machining feature classification task, with results showing accuracy approaching 100% and training time comparable to that of existing multi-view and voxel-based solutions without the need for a GPU.
Screening for PTSD and functional impairment in trauma-exposed young children: evaluation of alternative CBCL-PTSD subscales
Authors: Bartels Lasse , Haag Ann-Christin , Keller Fabia , Storch Eric A. , De Young Alexandra , Salloum Alison , Landolt Markus A. 
Published: August 2022

AbstractThe Child Behavior Checklist (CBCL 1.5–5 years) posttraumatic stress disorder (PTSD) subscale by Dehon & Scheeringa (2006) as a screener for PTSD in trauma-exposed young children has yielded inconsistent results so far. Therefore, the aim of this study was to create and examine the validity of alternative CBCL-PTSD subscales and compare them to the existing CBCL-PTSD subscale based on the DSM-5 PTSD diagnostic criteria for children 6 years and younger. Further, the CBCL-PTSD subscales were examined regarding their usefulness in screening for posttraumatic stress-related functional impairment. The sample comprised 116 trauma-exposed young children (Mage = 3.42 years, SDage = 1.21 years, female = 49.1%). The psychometric properties of the existing CBCL-PTSD subscale as well as the alternative subscales based on expert rating (CBCL-PTSD-17) and based on variable importance (CBCL-PTSD-6) were evaluated by means of receiver operating characteristic curves, sensitivity, specificity, positive predictive values, and negative predictive values. Area under the curves for all three investigated CBCL-PTSD subscales were good to excellent for PTSD and functional impairment. Further, all three CBCL-PTSD subscales showed high sensitivity for PTSD and functional impairment. Considering the length and the performance of the three investigated subscales, the CBCL-PTSD-6 appears to be a promising and clinically useful CBCL-PTSD subscale as a screener for PTSD and functional impairment due to the easiest and most practicable application. For purposes of discriminant validation of the CBCL-PTSD-6, young children without a history of trauma should be compared to young children with trauma history.
Opening Pandora’s Loot Box: Weak Links Between Gambling and Loot Box Expenditure in China, and Player Opinions on Probability Disclosures and Pity-Timers
Authors: Xiao Leon Y. , Fraser Tullia C. , Newall Philip W. S. 
Published: August 2022

AbstractLoot boxes are quasi-gambling virtual products in video games that provide randomised rewards of varying value. Previous studies in Western contexts have identified a positive correlation between loot box purchasing and problem gambling severity. A preregistered survey of People’s Republic of China (PRC) video game players (N = 879) failed to replicate this correlation. We observed statistically significant but weak positive correlations between loot box expenditure and past-year gambling participation, and between loot box expenditure and impulsiveness. This study cannot prove that loot boxes are not disproportionately purchased by people with problem gambling symptomatology in the PRC or that PRC players are not potentially at risk of loot box-related harms. Instead, the evidence suggests that the relationship between loot boxes and gambling might be weaker in the PRC than in Western countries. We identified multiple unique factors about the PRC that might be affecting this relationship. For example, the lotteries are the only legally permitted form of gambling. More gamified electronic gambling products are unavailable. The limited availability of gambling meant that a low level of gambling participation (n = 87) was observed, which is a limitation of this study. Additionally, the PRC is presently the only country to legally require loot box probability disclosures as a consumer protection measure. Most loot box purchasers (84.6%) reported seeing loot box probability disclosures, but only 19.3% of this group reported consequently spending less money. Most loot box purchasers (86.9%) thought that pity-timers, which increase the winning probabilities of obtaining rarer rewards, are appropriate for implementation. Future loot box research should give greater consideration to differing cultural contexts and novel consumer protection measures.
DB-CMT: A New Concurrent Multi-path Stream Control Transport Protocol
Authors: Verma Lal Pratap , Sharma Varun Kumar , Kumar Mahesh , Kanellopoulos Dimitris , Mahanti Aniket 
Published: August 2022

AbstractStream Control Transmission Protocol (SCTP) exploits multiple network interfaces to provide multi-streaming and data chunk ordering in a stream. An extended feature of SCTP, i.e., Concurrent Multi-path Transfer (CMT), bids concurrent data transmission in a multi-path data transfer environment and guarantees bandwidth aggregation, load sharing, robustness, and reliability. In such an environment, the paths usually have distinct characteristics (i.e., delay, Packet Loss Rate (PLR), and bandwidth). Thus, data chunks are received out-of-ordered at the destination. As a result, CMT causes excessive receiver buffer blocking and unnecessary congestion window (cwnd) reductions. Also, during the selection of the retransmission destination path (to resend a lost data chunk), CMT does not take into account vital Quality of Service (QoS) parameters such as the PLR of a path under consideration. This paper introduces a new Delay-Based Concurrent Multi-path Transfer (DB-CMT) approach that transmits data on multiple paths according to their delay. In this scheme, we present a Delay-Based Data chunk Scheduling Policy (DB-DSP), a Retransmission Path Selection Policy (RTX-CL), and a new Delay-Based Fast Retransmission Policy (DB-FRP). The simulation results show that the DB-CMT’s RTX-CL policy performs better than the well-known RTX-CWND and RTX-LOSSRATE retransmission schemes. Also, the overall performance of DB-CMT witnesses improved throughput, fewer timeouts, and reduced File Transfer Time (FTT) performances.
Corporate governance and financial distress: lessons learned from an unconventional approach
Authors: Tron Alberto , Dallocchio Maurizio , Ferri Salvatore , Colantoni Federico 
Published: August 2022

AbstractUsing a and a unique set of Italian non-listed Unlikely to Pay (UTP) positions, that consist in the phase that precedes the insolvency but where it is still possible for the company to succeed in restructuring, this paper aims to analyze the relationships between corporate governance characteristics and financial distress status. We compare the performance of corporate governance variables in predicting corporate defaults, using both the Logit and Random Forest models, which previous researchers have deemed to be the most efficient machine learning techniques. Our results show that the use of corporate governance variables – especially with regards to CEO renewal and stability in the composition of the board of directors – increases the accuracy of the Random Forest technique and influences the success of the turnaround process. This paper also confirms the Random Forest technique’s ability to significantly outperform the Logit model in terms of accuracy.
Assessing the efficacy of a Tier 2 early intervention for transcription skills in Spanish elementary school students
Authors: Jiménez Juan E. , de León Sara C. , García Eduardo , Seoane Rocío C. 
Published: August 2022

AbstractThe main objective of this study was to evaluate the efficacy of a Tier 2 intervention within the context of the Response to Intervention (RtI) model implemented by Spanish first- to second-grade primary school teachers to improve at-risk students’ transcription skills. Teachers were instructed in the administration of a writing curriculum-based measure composed of 5 isolates measures (allographs, dictated words with arbitrary spelling or non-ruled, dictated words with rule-based spelling, dictated nonsense words, and dictated sentences) to identify at-risk students and to monitor their progress; and in the implementation of a systematic and explicit instructional program to improve transcription skills in at-risk students. A total of 164 at-risk students from 12 schools from the Canary Islands participated in the study. Teachers were provided with a support system that included a web-based training program for writing. Implementation fidelity was analyzed using direct observations and self-reports. All students were assessed three times during the academic year. In a hierarchical linear growth modeling procedure, differences in growth rates of transcription skills were compared between students who received the intervention, those who did not, and their typically achieving peers. Additionally, the effects of the intervention in the experimental at-risk group were also analyzed, differentiating between those who left the risk status and those who remained at-risk. Children at-risk in the intervention condition appeared to benefit more in handwriting skills than at-risk children in the control condition, but to a lesser extent in spelling accuracy. Nevertheless, improvements in both transcription skills had only been made in the experimental risk group that had left the risk situation.
Reading the biomineralized book of life: expanding otolith biogeochemical research and applications for fisheries and ecosystem-based management
Authors: Reis-Santos Patrick , Gillanders Bronwyn M. , Sturrock Anna M. , Izzo Christopher , Oxman Dion S. , Lueders-Dumont Jessica A. , Hüssy Karin , Tanner Susanne E. , Rogers Troy , Doubleday Zoë A. , Andrews Allen H. , Trueman Clive , Brophy Deirdre , Thiem Jason D. , Baumgartner Lee J. , Willmes Malte , Chung Ming-Tsung , Charapata Patrick , Johnson Rachel C. , Trumble Stephen , Heimbrand Yvette , Limburg Karin E. , Walther Benjamin D. 
Published: August 2022

AbstractChemical analysis of calcified structures continues to flourish, as analytical and technological advances enable researchers to tap into trace elements and isotopes taken up in otoliths and other archival tissues at ever greater resolution. Increasingly, these tracers are applied to refine age estimation and interpretation, and to chronicle responses to environmental stressors, linking these to ecological, physiological, and life-history processes. Here, we review emerging approaches and innovative research directions in otolith chemistry, as well as in the chemistry of other archival tissues, outlining their value for fisheries and ecosystem-based management, turning the spotlight on areas where such biomarkers can support decision making. We summarise recent milestones and the challenges that lie ahead to using otoliths and archival tissues as biomarkers, grouped into seven, rapidly expanding and application-oriented research areas that apply chemical analysis in a variety of contexts, namely: (1) supporting fish age estimation; (2) evaluating environmental stress, ecophysiology and individual performance; (3) confirming seafood provenance; (4) resolving connectivity and movement pathways; (5) characterising food webs and trophic interactions; (6) reconstructing reproductive life histories; and (7) tracing stock enhancement efforts. Emerging research directions that apply hard part chemistry to combat seafood fraud, quantify past food webs, as well as to reconcile growth, movement, thermal, metabolic, stress and reproductive life-histories provide opportunities to examine how harvesting and global change impact fish health and fisheries productivity. Ultimately, improved appreciation of the many practical benefits of archival tissue chemistry to fisheries and ecosystem-based management will support their increased implementation into routine monitoring.Graphical abstract
Research performance and scholarly communication profile of competitive research funding: the case of Academy of Finland
Authors: Pölönen Janne , Auranen Otto 
Published: August 2022

AbstractThe Academy of Finland (AKA), Finland’s major public research funding agency, uses a Web of Science (WoS) based bibliometric indicator to assess the performance of research it has funded. We use an alternative methodology to compare (1) the research performance and (2) the scholarly communication profile of AKA-funded research to the Finnish universities’ entire output across the major fields of arts and sciences. Our data consists of 142,742 publications (years 2015–2018) registered in the national information service, which integrates Current Research Information System (CRIS) data of 13 Finnish universities. Research performance is analyzed using the Finnish community-curated expert-based rating of publication channels (so-called JUFO). Our results show that compared to the Finnish universities’ entire output a larger share of AKA-funded research is published in leading JUFO rated journals and book publishers. JUFO and WoS-based indicators produced consonant results regarding the performance of AKA-funded research. Analysis of publication profiles shows that AKA-funded research is more focused than the universities’ output on using peer-reviewed publications, articles published in journals, English language, foreign publishers and open access publishing. We conclude that the CRIS-based publication data can support multidimensional assessments of research performance and scholarly communication profiles, potentially also in other countries and institutions. CRIS development and maintenance require multi-stakeholder commitment, resources and incentives to ensure data quality and coverage. To fully recognize diverse open science practices and to enable international comparisons, CRISs need further development and integration as data sources.
Coopetition between frenemies–interrelations and effects of seven collaboration problems in research clusters
Authors: Hückstädt Malte 
Published: August 2022

AbstractPrincipal Investigators in research clusters find themselves in a Janus-faced situation: if they want to achieve their common research goals, fulfil their overarching function of integrative knowledge production and thus secure the continuity of their collaboration, they are required to cooperate closely. At the same time, they compete with each other for scientific recognition or third-party funding. Taking this as a background, the article explores the effects and interrelationships of seven collaboration problems that arise in the context of the tension between cooperation and competition. Based on the state of research, a club-theoretical heuristic is developed that captures the effects and interrelationships of seven collaboration problems. The specified hypothesis model is tested with the help of a structural equation model using data from a large-scale online survey of PIs and spokespeople involved in research collaborations. The data analysis confirms the assumption that especially conflictual personal relationships between the partners in a research collaboration (relationship problems) form a central node in the network of collaboration problems: A lack of reciprocity of costs and benefits (fairness problems) as well as the self-interested behaviour of the spokesperson of a research cluster (management problems) promote relationship problems between the partners in a research team. Likewise, relationship problems in turn promote an erosion of communication between collaboration partners (communication problems), of goal progress evaluation (certainty problems), of cross-disciplinary exchange (difference problems) and of partners’ commitment to the common goals of the research collaboration (goal commitment problems). The structural equation model thus supports the widely held, but by no means trivial view in cooperation research that trusting and fair interaction between cooperating PIs in a research cluster is a necessary, if not sufficient, condition for their joint success.
Leptin mutation and mycobacterial infection lead non-synergistically to a similar metabolic syndrome
Authors: Ding Yi , Haks Mariëlle C. , van den Eeden Susan J. F. , Ottenhoff Tom H. M. , Harms Amy C. , Hankemeier Thomas , Eeza Muhamed N. H. , Matysik Jörg , Alia A. , Spaink Herman P. 
Published: August 2022

Abstract
Introduction
The leptin signaling pathway plays an important role as a key regulator of glucose homeostasis, metabolism control and systemic inflammatory responses. However, the metabolic effects of leptin on infectious diseases, for example tuberculosis (TB), are still little known.

Objectives
In this study, we aim to investigate the role of leptin on metabolism in the absence and presence of mycobacterial infection in zebrafish larvae and mice.

Methods
Metabolites in entire zebrafish larvae and the blood of mice were studied using high-resolution magic-angle-spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and mass spectrometry, respectively. For transcriptome studies of zebrafish larvae, deep RNA sequencing was used.

Results
The results show that leptin mutation leads to a similar metabolic syndrome as caused by mycobacterial infection in the two species, characterized by the decrease of 11 amine metabolites. In both species, this metabolic syndrome was not aggravated further when the leptin mutant was infected by mycobacteria. Therefore, we conclude that leptin and mycobacterial infection are both impacting metabolism non-synergistically. In addition, we studied the transcriptomes of lepbibl54 mutant zebrafish larvae and wild type (WT) siblings after mycobacterial infection. These studies showed that mycobacteria induced a very distinct transcriptome signature in the lepbibl54 mutant zebrafish compared to WT sibling control larvae. Furthermore, lepbibl55 Tg (pck1:luc1) zebrafish line was constructed and confirmed this difference in transcriptional responses.

Conclusions
Leptin mutation and TB lead non-synergistically to a similar metabolic syndrome. Moreover, different transcriptomic responses in the lepbibl54 mutant and TB can lead to the similar metabolic end states.