bluuebunny/crossref_metadata_2025_split huggingface dataset:
Responding to change over time: A longitudinal case study on changes in coordination mechanisms in large-scale agile
Authors: Berntzen Marthe , Stray Viktoria , Moe Nils Brede , Hoda Rashina 
Published: August 2023

Abstract
Context
Responding to change and continuously improving processes, practices, and products are core to agile software development. It is no different in large-scale agile, where multiple software development teams need to respond both to changes in their external environments and to changes within the organization.

Objective
With this study, we aim to advance knowledge on coordination in large-scale agile by developing a model of the types of organizational changes that influence coordination mechanisms.

Method
We conducted a longitudinal case study in a growing large-scale agile organization, focusing on how external and internal changes impact coordination over time. We collected our data through 62 days of fieldwork across one and a half years. We conducted 37 interviews, observed 118 meetings at all organizational levels, collected supplementary material such as chat logs and presentations, and analyzed the data using thematic analysis.

Results
Our findings demonstrate how external events, such as onboarding new clients, and internal events, such as changes in the team organization, influence coordination mechanisms in the large-scale software development program. We find that external and internal change events lead to the introduction of new coordination mechanisms, or the adjustment of existing ones. Further, we find that continuous scaling requires continuous change and adjustment. Finally, we find that having the right mechanisms in place at the right time strengthens resilience and the ability to cope with change in coordination needs in complex large-scale environments.

Conclusions
Our findings are summarized in an empirically based model that provides a practical approach to analyzing change, aimed at supporting both researchers and practitioners dealing with change in coordination mechanisms in large-scale agile development contexts.
Mechanising Gödel–Löb Provability Logic in HOL Light
Authors: Maggesi Marco , Perini Brogi Cosimo 
Published: August 2023

AbstractWe introduce our implementation in HOL Light of the metatheory for Gödel–Löb provability logic (GL), covering soundness and completeness w.r.t. possible world semantics and featuring a prototype of a theorem prover for GL itself. The strategy we develop here to formalise the modal completeness proof overcomes the technical difficulty due to the non-compactness of GL and is an adaptation—according to the formal language and tools at hand—of the proof given in George Boolos’ 1995 monograph. Our theorem prover for GL relies then on this formalisation, is implemented as a tactic of HOL Light that mimics the proof search in the labelled sequent calculus$$\textsf{G3KGL}$$G3KGL, and works as a decision algorithm for the provability logic: if the algorithm positively terminates, the tactic succeeds in producing a HOL Light theorem stating that the input formula is a theorem of GL; if the algorithm negatively terminates, the tactic extracts a model falsifying the input formula. We discuss our code for the formal proof of modal completeness and the design of our proof search algorithm. Furthermore, we propose some examples of the latter’s interactive and automated use.
Responses of necrophilous beetles to animal mass mortality in the Australian Alps
Authors: Stone Rebecca L. , Bonat Stefanie , Newsome Thomas M. , Barton Philip S. 
Published: August 2023

AbstractA diversity of insects can be found at the remains of dead animals (carrion) and they play a vital role in its decomposition and recycling. An emerging global problem with carrion is animal mass mortality events – the sudden, rapid die-off of many animals resulting in a large increase to the localised carrion resource pool. Yet, little is known about how insects respond to sudden and large inputs of carrion. We conducted an experiment in a mountainous alpine region of south-eastern Australia and compared beetle assemblages found at single carcass and mass mortality sites. We also examined the effects of vertebrate exclusion, and decomposition stage on beetles. We found 4,774 beetles representing 146 different species/morphospecies from 17 families. The most abundant species wasSaprinus cyaneus cyaneus(Histeridae), and species of Staphylinidae and Silphidae also dominated the fauna, which is typical for necrophilous beetles in Australia. We also found a clear temporal change in beetle assemblages, with abundance and richness peaking during the active decay stage. We found that beetle abundance was greater at single carcasses than mass mortality sites, possibly as an artifact of sampling, and that species richness was similar among these two carcass treatment types. We found no significant effect of vertebrate exclusion on beetles, suggesting that large scavengers in the study system may not influence necrophilous insect communities around carrion.Implications for insect conservation: Our study highlights the diversity of beetles that can be found at carrion and their similar composition to the fauna found in other areas in the south-east of the Australian continent. Beetles may have reduced abundance at mass mortality sites which could affect their ability to contribute to carrion removal relative to smaller carrion quantities. Further research is required to quantify the role of other insects in carrion removal under a range of natural and mass mortality scenarios.
The 510(k) Third Party Review Program: Promise and Potential
Authors: Miller Brian J. , Blanks William , Yagi Brian 
Published: August 2023

AbstractEvery year, the Food and Drug Administration (FDA) clears approximately 3,000 medical devices for marketing via the 510(k) pathway. These constitute 99% of all devices approved for human use and includes the premarket review of many devices incorporating newer technology such as artificial intelligence (AI), machine learning (ML), and other software. As the complexity of these novel technologies and the number of applications is expected to increase in the coming years, statutory changes such as the 2016 21st Century Cures Act, regulations, and guidance documents have increased both the volume and complexity of device review. Thus, the ability to streamline the review of less complex, low-to-moderate risk devices through the 510(k) pathway will maximize the FDA’s capability to address other important, future-oriented regulatory questions. For over twenty five years, third party review organizations have served a defined function to assist with the review of 510(k) applications for a set of enumerated device classes. This paper reviews the history of FDA device regulation, the evolution of the 510(k) review pathway, and the recent history of the 510(k) third party review program. Finally, the paper addresses policy concerns from all stakeholders – including the FDA – along with policy suggestions to improve the third party review program and FDA device regulation writ large.
Effect of fungal isolates from different samples upon radionuclide behavior and environmental hazard indices during bioleaching process in Gabal Um Hamd, Um Bogma area, southwestern Sinai, Egypt
Authors: Mohamed Walaa S. , Abbas Yehia M. M. , Ammar Amal A. A. , Aly Hanan A. S. , Rezk Mohamed M. , Negm Sameh H. , Kawady Nilly A. 
Published: August 2023

AbstractTwo fungal species were isolated from the studied rock samples and identified morphologically asAspergillus hollandicusandPenicillium citrinum. Bioleaching process was applied to W1, W2 and W3. The average concentration activity of238U,226Ra,232Th, and40K are 5134.03, 5708.64, 189.51, and 1456.8 BqKg−1, respectively. Radionuclide’s distribution in leach liquor, residual, and fungal adsorption were followed and environmental hazard indices (Raeq, Iγ, Hex, Hin, and ECLR) were calculated. From the observed outcomes, the isolated fungal strains have the potential to reduce the harmful effect up to 50% compared to the original. As a result, application of these fungal strains offers a potential strategy for environmental remediation of radionuclides.
In-vivo screening implicates endoribonuclease Regnase-1 in modulating senescence-associated lysosomal changes
Authors: Venz Richard , Goyala Anita , Soto-Gamez Abel , Yenice Tugce , Demaria Marco , Ewald Collin Y. 
Published: August 2023

AbstractAccumulation of senescent cells accelerates aging and age-related diseases, whereas preventing this accumulation extends the lifespan in mice. A characteristic of senescent cells is increased staining with β-galactosidase (β-gal) ex vivo. Here, we describe a progressive accumulation of β-gal staining in the model organism C. elegans during aging. We show that distinct pharmacological and genetic interventions targeting the mitochondria and the mTORC1 to the nuclear core complex axis, the non-canonical apoptotic, and lysosomal-autophagy pathways slow the age-dependent accumulation of β-gal. We identify a novel gene, rege-1/Regnase-1/ZC3H12A/MCPIP1, modulating β-gal staining via the transcription factor ets-4/SPDEF. We demonstrate that knocking down Regnase-1 in human cell culture prevents senescence-associated β-gal accumulation. Our data provide a screening pipeline to identify genes and drugs modulating senescence-associated lysosomal phenotypes.
Clusia chuj (Clusiaceae), a new tree species from the border between Guatemala and Mexico
Authors: Luján Manuel 
Published: August 2023

SummaryClusia chuj (Clusiaceae) is described and illustrated. This new taxon differs from the other species of the genus by being a tree up to 15 m tall with many-flowered inflorescences. The non-resiniferous, quadrangular flowers have thick, pale-yellow petals, and the androecium in the staminate flowers have 20 (– 30) free, short stamens. This new species is mainly found in mountain forests around Tziscao and Yolnabaj lakes near the border between Guatemala and Mexico.
Perceptual Similarity: Insights From Crossmodal Correspondences
Authors: Di Stefano Nicola , Spence Charles 
Published: August 2023

AbstractPerceptual similarity is one of the most fiercely debated topics in the philosophy and psychology of perception. The documented history of the issue spans all the way from Plato – who regarded similarity as a key factor for human perceptual experience and cognition – through to contemporary psychologists – who have tried to determine whether, and if so, how similarity relationships can be established between stimuli both within and across the senses. Recent research on cross-sensory associations, otherwise known as crossmodal correspondences – that is, the existence of observable consensual associations, or mappings, between stimuli across different senses – represents an especially interesting field in which to study perceptual similarity. In fact, most accounts of crossmodal association that have been put forward in the literature to date evoke perceptual similarity as a key explanatory factor mediating the underlying association. At the same time, however, these various accounts raise several important theoretical questions concerning the very nature of similarity, with, for example, the sensory, affective, or cognitive underpinnings of similarity judgements remaining unclear. We attempt to shed light on these questions by examining the various accounts of crossmodal associations that have been put forward in the literature. Our suggestion is that perceptual similarity varies from being phenomenologically-based to conceptually-based. In particular, we propose that the nature of the associations underlying similarity judgements – whether these associations are phenomenologically-, structurally-, emotionally-, or conceptually-based – may be represented in a two-dimensional space with associative strength on one axis, and cognitive penetrability on the other.
Transitional pathways through middle school for First Nations students in the Northern Territory of Australia
Authors: Dadi Abel Fekadu , He Vincent , Guenther John , Su Jiunn-Yih , Ober Robyn , Guthridge Steven 
Published: August 2023

AbstractThe middle-school years (Year 7 to Year 9) is a particular challenge for socially disadvantaged populations, with high proportions of children either repeating school years or dropping out of school. In Australia, a group of particular concern is First Nations children for whom there is a collective effort by all governments to improve education outcomes, although there have been few studies of their transition through the middle-school years. This retrospective study, using individual-level linked data, followed a cohort of 7881 First Nations students for 2 years after enrolment in Year 7 (Y7) in any Northern Territory (NT) government school in the years from 2008 to 2014 to quantify the transitional pathways through middle school and identify the factors associated with faltering progress. We used multinomial multilevel logistic regression to identify the factors associated with school dropout and repeating Y7 or Y8 (Y7/8). Two years after Y7 enrolment, eight in ten First Nations students progressed to Y9 (78.8%), more than one in ten students had dropped out of school (13.3%) before reaching Y9, and one in 12 (7.9%) repeated Y7/8. The likelihood of either dropping out of school or repeating years was higher among students who were enrolled in Y7 when aged less than 11.5 years, had a low Y7 school attendance rate, moved to either interstate or non-government schools and who lived in a remote area. Students who were not born in the NT and those with a record of substantiated child maltreatment during Y7 were more likely to repeat Y7/8. Planning interventions to improve school retention through the middle-school years should consider these factors.
A Neural Inference of User Social Interest for Item Recommendation
Authors: Chen Junyang , Chen Ziyi , Wang Mengzhu , Fan Ge , Zhong Guo , Liu Ou , Du Wenfeng , Xu Zhenghua , Gong Zhiguo 
Published: August 2023

AbstractUser-generated content is daily produced in social media, as such user interest summarization is critical to distill salient information from massive information for recommendation tasks. While the interested messages (e.g., tags or posts) from a single user are usually sparse becoming a bottleneck for existing methods, we propose a neural inference method (NIGraphNet) by mining user social interest for item recommendation. It can unearth user latent topics combined with user relation learning. Specifically, we exploit a neural variational inference approach to learn the distributions between user interests and hidden topics. (We denote it as interest-topic distributions in the following.) Then, we adopt a unified graph-based training loss that jointly learns the hidden topics and user relations for item recommendation. Experiments on two datasets collected from well-known social media platforms demonstrate the superior performance of our model in the tasks of user interest summarization and item recommendation. Further discussions also show that exploiting the latent topic representations and user relations is conducive to the user’s automatic language understanding.
“Name Three Good Things About Yourself in Mathematics” – An Intervention to Reduce Pre-Service Teachers’ Shame in Mathematics
Authors: Jenßen Lars 
Published: August 2023

AbstractShame is an unpleasant and activating emotion that affects learners’ achievement, including in mathematics, and pre-service teachers’ identity development. It is closely connected with the self. The current study investigated the efficacy of an intervention adapted from positive psychology aiming to reduce pre-service primary teachers’ shame in mathematics. Accordingly, the three good things technique was adapted with respect to the self. The efficacy of the intervention was analyzed in comparison to a qualified control group and a control group receiving no intervention. Participants were allocated at random to the three groups. In total, n = 176 pre-service primary school teachers took part in the experiment for a duration of five weeks with exercises twice a week. Findings suggest small positive effects of the adapted intervention on shame reduction in mathematics and superior effects in comparison to both control groups.
Photostability, cytotoxicity, and photothermal impact of AgNPs, CoAgNC, and IOAgNC on HEp-2 laryngeal carcinoma cells
Authors: Ramadan Marwa A. , El-Tayeb Tarek A. 
Published: August 2023

AbstractMagnetic nanoparticles have shown promise in various medical applications, including cancer treatment and diagnostics. The objective of this study is to attain mastery over the synthesis of silver nanoparticles (AgNPs), Cobalt silver nanocomposite (CoAgNC) and magnetite silver nanocomposite (IOAgNC), while also examining their photostability, cytotoxicity, and photothermal impact on Human Laryngeal Carcinoma Cell line (HEp-2). The preparation and characterization of AgNPs, CoAgNC, and IOAgNC were described, including the assessment of their photostability and cytotoxicity on HEp-2 cell line. The photostability of these nanomaterials was determined by subjecting them to different light sources, while their morphology and magnetic properties were characterized using a spectrophotometer, Transmission Electron Microscopy (TEM), and Vibrating Sample Magnetometer (VSM). The results of the characterization of AgNPs, CoAgNC, and IOAgNC showed that the prepared nanomaterials have distinct optical and morphological properties. The synthesized nanomaterials were stable in aqueous solutions and exhibited magnetic properties. The cytotoxicity tests on HEp-2 cells showed that the nanomaterials were not toxic in the dark, but their toxicity increased under light exposure, with IOAgNC showing the most significant toxicity. CoAgNC was found to be photostable under UV light and Light Emitting Diode (LED) irradiation due to the little lattice mismatch between cobalt and silver. Nanocomposite systems of high magnetic moment, such as IOAgNC and CoAgNC, have potential for tumor treatment through magnetic fluid hyperthermia. The photostability, chemical stability, and biocompatibility of AgNPs, CoAgNC, and IOAgNC were investigated and found to be non-toxic even at high concentrations. These nanomaterials have multiple optical and magnetic functionalities and are promising candidates for biomedical applications.
Introducing TimPassLib – A Library for Integrated Periodic Timetabling and Passenger Routing
Authors: Schiewe Philine , Goerigk Marc , Lindner Niels 
Published: August 2023

AbstractClassic models to derive a timetable for public transport often face a chicken-and-egg situation: A good timetable should offer passengers routes with small travel times, but the route choice of passengers depends on the timetable. While models that fix passenger routes were frequently considered in the literature, integrated models that simultaneously optimize timetables and passenger routes have seen increasing attention lately. This creates a growing need for a set of instances that allows to test and compare new algorithmic developments for the integrated problem. Our paper addresses this requirement by presenting TimPassLib, a new benchmark library of instances for integrated periodic timetabling and passenger routing.
Advanced electrochemical techniques for characterizing electrocatalysis at the single-particle level
Authors: Li Hongmei , Guo Yong , Jin Zhaoyu 
Published: August 2023

AbstractElectrocatalytic technologies play a vital role in the advancement of hydrogen energy and other renewable green energy sources, with nanocatalysts gaining significant attention due to their size-dependent electrocatalytic activity and broad applications. Single-particle electrochemistry offers a powerful approach to investigate the intrinsic catalytic activity and electrocatalytic mechanisms of individual nanoscale systems, thereby enabling a deeper understanding of the structure-activity relationship at the nanoscale. In this review, several cutting-edge high-resolution techniques for examining local reactivity at the single-particle level are discussed, such as scanning electrochemical microscopy (SECM), scanning electrochemical cell microscopy (SECCM), single-particle collision technique, and single-atom/molecule electrochemistry. We begin by concisely elucidating the working principles of these advanced electrochemical methodologies. Subsequently, we present recent advancements in high-resolution electrochemical techniques for characterizing electrocatalysis in detail with valuable insights into the local activity of various catalysts. In future research, the integration of multiple technologies through collaborative analysis is anticipated to further unveil the catalytic active sites of electrocatalysts with intricate structures and facilitate quantitative investigations of complex reaction processes.
Skip-YOLO: Domestic Garbage Detection Using Deep Learning Method in Complex Multi-scenes
Authors: Lun Zhao , Pan Yunlong , Wang Sen , Abbas Zeshan , Islam Md Shafiqul , Yin Sufeng 
Published: August 2023

AbstractIt is of great significance to identify all types of domestic garbage quickly and intelligently to improve people's quality of life. Based on the visual analysis of feature map changes in different neural networks, a Skip-YOLO model is proposed for real-life garbage detection, targeting the problem of recognizing garbage with similar features. First, the receptive field of the model is enlarged through the large-size convolution kernel which enhanced the shallow information of images. Second, the high-dimensional features of the garbage maps are extracted by dense convolutional blocks. The sensitivity of similar features in the same type of garbage increases by strengthening the sharing of shallow low semantics and deep high semantics information. Finally, multiscale high-dimensional feature maps are integrated and routed to the YOLO layer for predicting garbage type and location. The overall detection accuracy is increased by 22.5% and the average recall rate is increased by 18.6% comparing the experimental results with the YOLOv3 analysis. In qualitative comparison, it successfully detects domestic garbage in complex multi-scenes. In addition, this approach alleviates the overfitting problem of deep residual blocks. The application case of waste sorting production line is used to further highlight the model generalization performance of the method.
Predicting human poses via recurrent attention network
Authors: Tang Jianwei , Wang Jieming , Hu Jian-Fang 
Published: August 2023

AbstractHuman motion prediction is a challenging task due to the diversity and randomness of future poses. Due to the inherent topology of pose data, most recent work has used graph convolution networks (GCNs) to accomplish the task of human motion prediction. However, the GCN-based method has a major shortcoming in that the modeling of temporal information is insufficient. In this paper, we propose a simple approach that combines recurrent neural networks (RNNs) and attention mechanism for motion prediction, which considers both spatial relations between different joints and temporal correlation. The query, key and value of the attention mechanism allow us to select the information we need for the subsequent prediction. To solve the difficult problem of RNN training, we utilize uncertainty and strong short-term constraints to optimize the training process. We evaluate our method on several standard benchmark datasets for human motion prediction, i.e., the Human3.6M dataset and the CMU MoCap dataset. The experimental results show that our approach outperforms previous approaches.