bluuebunny/crossref_metadata_2025_split huggingface dataset:
Office Openess Affects Stress Regulation and Teamwork: A Neurophysiological Field Study
Authors: Alexander Veronika , Dannhäuser Laura , Zak Paul J. 
Published: December 2023

AbstractStimulating and sustaining teamwork can be a strategic asset for an organization. Yet, little has been done to objectively assess how office design affects team performance. We conducted a neuroscience field experiment of employees (N = 96) to examine how different open-office configurations impact three measures of neurophysiologic stress, affect, and creative problem-solving in three existing office configurations that varied in their degree of openness. Physiologic stress was lowest in the most open work setting resulting in higher performance and more rapid post-work physiologic recovery compared to less open configurations. We identified three core factors driving these results: high perceived privacy, a more pleasant ambience, and increased autonomy. This multimodal approach identifies neurophysiologic mechanisms linking office design to team performance.
Hypericons for interpretability: decoding abstract concepts in visual data
Authors: Martinez Pandiani Delfina Sol , Lazzari Nicolas , Erp Marieke van , Presutti Valentina 
Published: December 2023

AbstractIn an era of information abundance and visual saturation, the need for resources to organise and access the vast expanse of visual data is paramount. Abstract concepts-such as comfort, power, or freedom-emerge as potent instruments to index and manage visual data, particularly in contexts like Cultural Heritage (CH). However, the variance and disparity in the visual signals that evoke a single abstract concept challenge conventional approaches to automatic visual management rooted in the Computer Vision (CV) field. This paper critically engages with the prevalent trend of automating high-level visual reasoning while placing exclusive reliance on visual signals, prominently featuring Convolutional Neural Networks (CNNs). We delve into this trend, scrutinising the knowledge sought by CNNs and the knowledge they ultimately encapsulate. In this endeavour, we accomplish three main objectives: (1) introduction of ARTstract, an extensive dataset encompassing cultural images that evoke specific abstract concepts; (2) presentation of baseline model performances on ARTstract to elucidate the intricate nuances of image classification based on abstract concepts; and, critically, (3) utilization of ARTstract as a case study to explore both traditional and non-traditional avenues of visual interpretability, a trajectory inspired by Offert and Bell (2021). To more comprehensively understand how CNNs assimilate and reflect cultural meanings, and to discern the echoes reverberating within these visions, we unveil SD-AM, a novel approach to explainability that collapses visuals into hypericon images through a fusion of feature visualization techniques and Stable Diffusion denoising. Overall, this study critically addresses abstract concept image classification’s challenges within the CNN paradigm. By embracing innovative methodologies and providing comprehensive analyses of explainability techniques, we make a substantial contribution to the broader discourse surrounding automatic high-level visual understanding, its interpretability, and the ensuing implications for comprehending culture within the digital era. Through our exploration, we illuminate the multifaceted trends, complexities, and opportunities that underlie the fusion of high-level visual reasoning and computer vision.
Twitter conversations on sustainable development goals in Brazilian public universities using natural language processing
Authors: Costa Abimael de Jesus Barros , Gomes Sonia Maria da Silva , Kouloukoui Daniel , de Marcellis-Warin Nathalie , Warin Thierry 
Published: December 2023

AbstractThis study aims to provide insight into the behavior of Twitter conversations related to the Sustainable Development Goals (SDGs) by Brazilian public universities (UPBs) using Natural Language Processing (NLP). To achieve this goal, it was decided to develop descriptive research as it explores the characteristics of conversations focused on Twitter, one of the world's most used social media channels. Natural language processing (NLP) techniques based on the R programming language were used to extract and treat conversations held by the UPBs about the SDG objectives on Twitter. The study period is comprised of the creation of the first Twitter account by the universities until the data collection date, that is, between 2008 and 2022, therefore, 15 years of study, during this period, 326,114 tweets were identified. Evidence points to a substantial evolution in tweet publications by universities over the 15 years of studies. Thus, the practically zero publications in 2008 jumped to more than 15 thousand tweets in 2020. These findings show and confirm that universities use this social media to interact with their stakeholders. In addition, the results indicate that the analyzed universities make few publications on their Twitter about SDGs. In fact, of the 46 universities, only 6 tweeted about the subject, representing 13%. During the 15 years of studies, only 31 tweets were made on the subject. We found that the conversations and positions of universities on this subject in their social networks are few, insufficient, timid, and weak. As a second practical implication of this study, universities as centers of research, knowledge construction, and humanistic training urgently need to position themselves more on this subject in their social networks in order to demonstrate the relevance of the subject and inform about their accomplishments, and the need to everyone got involved in the theme.
Tiling and weak tiling in $$(\mathbb {Z}_p)^d$$
Authors: Kiss Gergely , Matolcsi Dávid , Matolcsi Máté , Somlai Gábor 
Published: December 2023

AbstractWe discuss the relation of tiling, weak tiling and spectral sets in finite abelian groups. In particular, in elementary p-groups $$(\mathbb {Z}_p)^d$$

(

Z
p

)

d

, we introduce an averaging procedure that leads to a natural object of study: a 4-tuple of functions which can be regarded as a common generalization of tiles and spectral sets. We characterize such 4-tuples for $$d=1, 2$$

d
=
1
,
2

, and prove some partial results for $$d=3$$

d
=
3

.
Ensuring a ‘Responsible’ AI future in India: RRI as an approach for identifying the ethical challenges from an Indian perspective
Authors: Bhalla Nitika , Brooks Laurence , Leach Tonii 
Published: December 2023

Abstract
Artificial intelligence (AI) can be seen to be at an inflexion point in India, a country which is keen to adopt and exploit new technologies, but needs to carefully consider how they do this. AI is usually deployed with good intentions, to unlock value and create opportunities for the people; however it does not come without its challenges. There are a set of ethical–social issues associated with AI, which include concerns around privacy, data protection, job displacement, historical bias and discrimination. Through a series of focus groups with knowledgeable people embedded in India and its culture, this research explores the ethical–societal changes and challenges that India now faces. Further, it investigates whether the principles and practices of responsible research and innovation (RRI) might provide a framework to help identify and deal with these issues. The results show that the areas in which RRI could offer scope to improve this outlook include education, policy and governance, legislation and regulation, and innovation and industry practices. Some significant challenges described by participants included: the lack of awareness of AI by the public as well as policy makers; India’s access and implementation of Western datasets, resulting in a lack of diversity, exacerbation of existing power asymmetries, increase in social inequality and the creation of bias; the potential replacement of jobs by AI. One option was to look at a hybrid approach, a mix of AI and humans, with expansion and upskilling of the current workforce. In terms of strategy, there seems to be a gap between the rhetoric of the government and what is seen on the ground, and therefore going forward there needs to be a much greater engagement with a wider audience of stakeholders.
Innovative image interpolation based reversible data hiding for secure communication
Authors: Punia Riya , Malik Aruna , Singh Samayveer 
Published: December 2023

AbstractIn an increasingly digitized world, secure communication plays a pivotal role in safeguarding sensitive information and ensuring the confidentiality of data transmission. Conventional encryption techniques are robust but often result in a loss of data during transmission, making it challenging to achieve both security and image quality simultaneously. To address this issue, an innovative technique for interpolation-based reversible data hiding (RDH) within images is presented in this study. The interpolation scheme considers the Min function of the neighboring pixels and generates the cover image. After that, a data hiding method is applied to the cover image by considering the intensity range of the pixels using the least-significant bit (LSB) substitution method. The suggested embedding approach first encrypts the secret message, and then it encodes the encrypted secret message into interpolated pixels based on pixel intensity range groups. This technique enables the image to be consistently recreated once the data has been extracted. The percentage increment in the embedding capacity and peak signal-to-noise ratio (PSNR) is 40.00 and 8.64% for the proposed method as compared to the existing method. The experimental results indicate that the proposed technique enhanced the embedding capacity for all test pictures and produced higher PSNR values.
Current research and future directions of melatonin's role in seed germination
Authors: Liu Ze , Dai Hengrui , Hao Jinjiang , Li Rongrong , Pu Xiaojun , Guan Miao , Chen Qi 
Published: December 2023

AbstractSeed germination is a complex process regulated by internal and external factors. Melatonin (N-acetyl-5-methoxytryptamine) is a ubiquitous signaling molecule, playing an important role in regulating seed germination under normal and stressful conditions. In this review, we aim to provide a comprehensive overview on melatonin's effects on seed germination on the basis of existing literature. Under normal conditions, exogenous high levels of melatonin can suppress or delay seed germination, suggesting that melatonin may play a role in maintaining seed dormancy and preventing premature germination. Conversely, under stressful conditions (e.g., high salinity, drought, and extreme temperatures), melatonin has been found to accelerate seed germination. Melatonin can modulate the expression of genes involved in ABA and GA metabolism, thereby influencing the balance of these hormones and affecting the ABA/GA ratio. Melatonin has been shown to modulate ROS accumulation and nutrient mobilization, which can impact the germination process. In conclusion, melatonin can inhibit germination under normal conditions while promoting germination under stressful conditions via regulating the ABA/GA ratios, ROS levels, and metabolic enzyme activity. Further research in this area will deepen our understanding of melatonin's intricate role in seed germination and may contribute to the development of improved seed treatments and agricultural practices.
ChatGPT and computational-based research: benefits, drawbacks, and machine learning applications
Authors: Atkinson Cameron F. 
Published: December 2023

AbstractGenerative artificial intelligence (GenAI) systems are disrupting how research is conducted across a wide range of disciplines. Many journals have decided not to allow these tools to be co-authors for the purposes of publication, but rather they must be acknowledged by authors as having been utilised in the writing process. Furthermore, due to the hallucinations that these models sometimes produce, authors are to review what is generated and recognise that they hold it to be true and accurate. To date, there has been varying research conducted on the accuracy of GenAI systems and their production of written text. However, new functions that allow GenAI systems to produce coding for constructing tools in computer programming languages highlights a new area that warrants investigation. Therefore, this article puts forth an account of using ChatGPT 3.5 to construct coding to be utilised for a Latent Dirichlet Allocation Topic Model (LDA-TM) for use in a Systematic Literature Review. This is hoped to address three elements of using ChatGPT 3.5 for coding: code review, error resolution, and scripting new code. The code will be aimed at designating an appropriate Hyper-parameter for the Random State for use in the LDA-TM. Within this context, this article will discuss the advantages and drawbacks of utilising this new tool and what it means for researchers who wish to augment their work with computer programming-based applications. To the authors knowledge, this is the first time this has been discussed within the context of the research being conducted.
3D quantum Hall effect in a topological nodal-ring semimetal
Authors: Zhao Guang-Qi , Li Shuai , Rui W. B. , Wang C. M. , Lu Hai-Zhou , Xie X. C. 
Published: December 2023

AbstractA quantized Hall conductance (not conductivity) in three dimensions has been searched for more than 30 years. Here we explore it in 3D topological nodal-ring semimetals, by employing a minimal model describing the essential physics. In particular, the bulk topology can be captured by a momentum-dependent winding number, which confines the drumhead surface states in a specific momentum region. This confinement leads to a surface quantum Hall conductance in a specific energy window in this 3D system. The winding number for the drumhead surface states and Chern number for their quantum Hall effect form a two-fold topological hierarchy. We demonstrate the one-to-one correspondence between the momentum-dependent winding number and wavefunction of the drumhead surface states. More importantly, we stress that breaking chiral symmetry is necessary for the quantum Hall effect of the drumhead surface states. The analytic theory can be verified numerically by the Kubo formula for the Hall conductance. We propose an experimental setup to distinguish the surface and bulk quantum Hall effects. The theory will be useful for ongoing explorations on nodal-ring semimetals.
Fractal characteristics and influencing factors of landscape space of Tibetan rural in Western Sichuan: a case study of three traditional villages
Authors: Fan Ding , Maliki Nor Zarifah Binti , Yu Siwei 
Published: December 2023

AbstractThis study takes the landscape space of traditional Tibetan villages in western Sichuan as the research object, and three national-level traditional villages of different Tibetan clans in Gyatso, Amdo and Baima Tibet were selected as samples. Using the fractal theory, combined with counting-box dimension measurement and spatial analysis methods, it comparatively analyzes the fractal characteristics of their landscape space and their influencing factors. The study finds that the landscape space of these villages has certain fractal characteristics, which are characterized by self-similarity and irregularity. The fractal characteristics of different villages are influenced by various factors such as geographic location, natural conditions, religious beliefs, folk costumes, etc., showing differences and diversity. There is a certain correlation between the fractal dimension and the distribution of landscape elements and spatial patterns, which can be used to describe the complexity and diversity of landscape space pattern. The article believes that the fractal theory provides a new perspective and method for analyzing the landscape space of traditional Tibetan villages, which helps to reveal its intrinsic formation mechanism and cultural connotation and provides new insights for the protection of traditional village heritage and the maintenance of cultural traditions. Meanwhile, the study also points out the limitations and shortcomings of the fractal theory in the study of traditional villages and puts forward directions and suggestions for future research.
Human-environment nexus: evaluating the anthropo-geomorphology and urban expansion of the Weija Gbawe Municipality, Ghana
Authors: Adu-Boahen Kofi , Addai Millicent Obeng , Hayford Steve Clarke , Adjovu Ebenezer Teye , Yeboah Derrick Oppong , Mensah Philip 
Published: December 2023

AbstractThe study's overarching goal was to examine the dynamics of geomorphological interaction and their effects on the urban expansion of the Weija-Gbawe Municipality in Ghana's Greater Accra Region. The study deployed a quantitative research approach to achieve the objective. A descriptive research design was used in collecting and analyzing data from three hundred and fifty-one (351) participants with a closed-ended questionnaire. The study employed a cluster sampling technique to select the participants based on areas with high concentrations of built-ups and other areas with low concentrations. Using the important relative index (RII), the fundamental level is ranked by the index. SPSS version 26 was used to analyse the data, and the results are shown in a descriptive frequency distribution table. The findings revealed population growth in the Weija-Gbawe Municipality as the main human factor transforming the landscapes' geomorphology, as residents change the landscape for human occupation and industrial uses. Similarly, the topographical terrain, emphasizing slope and elevation were the predominant geomorphological characteristic modifying urban expansion in the Municipality, as settlements were mainly distributed on flat terrain, and the elevation and slope were significant constraints for expansion of the city. Furthermore, urban land utilization in the Weija Gbawe Municipality is distinguished by an industrialized economy and built-up facilities. The paper concludes that applying geographic information systems, remote sensing, and field surveys is essential for generating comprehensive knowledge of urban and anthropocene geomorphology; this is possible through the use of GIS and remote sensing in analyzing the land use land cover changes in the study area. The study suggests enacting, enforcing environmental by-laws, intensifying, and restructuring environmental education by various stakeholders, including the Environmental Protection Agency (EPA) and the Municipality's Physical Planning Agency (PPA). This could be done by bridging the weak linkage between land use/road planning and aborting applications received which were not in line with the planning standards and approving those that are accurate and standard.
Granulocyte Colony-Stimulating Factor (Neupogen®; Filgrastim) Accelerates Neutrophil Recovery in a Rodent Model of Sulfur Mustard-Induced Hematologic Toxicity
Authors: Beske Phillip H , Harvilchuck Jill A , Gibbs Seth T , Green Carol E , Iyer Lalitha , O’Loughlin Kathleen , Hu Tom C-C , Nealy Michael S , Platoff Gennady E , Yeung David T 
Published: December 2023

Abstract

Objective:
Evidence of myelosuppression has been negatively correlated with patient outcomes following cases of high dose sulfur mustard (SM) exposure. These hematologic complications can negatively impact overall immune function and increase the risk of infection and life-threatening septicemia. Currently, there are no approved medical treatments for the myelosuppressive effects of SM exposure.

Methods:
Leveraging a recently developed rodent model of SM-induced hematologic toxicity, post-exposure efficacy testing of the granulocyte colony-stimulating factor drug Neupogen® was performed in rats intravenously challenged with SM. Before efficacy testing, pharmacokinetic/pharmacodynamic analyses were performed in naïve rats to identify the apparent human equivalent dose of Neupogen® for efficacy evaluation.

Results:
When administered 1 d after SM-exposure, daily subcutaneous Neupogen® treatment did not prevent the delayed onset of hematologic toxicity but significantly accelerated recovery from neutropenia. Compared with SM controls, Neupogen®-treated animals recovered body weight faster, resolved toxic clinical signs more rapidly, and did not display transient febrility at time points generally concurrent with marked pancytopenia.

Conclusions:
Collectively, this work corroborates the results of a previous pilot large animal study, validates the utility of a rodent screening model, and provides further evidence for the potential clinical utility of Neupogen® as an adjunct treatment following SM exposure.
Neural representation of the stratospheric ozone chemistry
Authors: Mohn Helge , Kreyling Daniel , Wohltmann Ingo , Lehmann Ralph , Maass Peter , Rex Markus 
Published: December 2023

Abstract
In climate modeling, the stratospheric ozone layer is typically only considered in a highly simplified form due to computational constraints. For climate projections, it would be of advantage to include the mutual interactions between stratospheric ozone, temperature, and atmospheric dynamics to accurately represent radiative forcing. The overarching goal of our research is to replace the ozone layer in climate models with a machine-learned neural representation of the stratospheric ozone chemistry that allows for a particularly fast, but accurate and stable simulation. We created a benchmark data set from pairs of input and output variables that we stored from simulations of the ATLAS Chemistry and Transport Model. We analyzed several variants of multilayer perceptrons suitable for physical problems to learn a neural representation of a function that predicts 24-h ozone tendencies based on input variables. We performed a comprehensive hyperparameter optimization of the multilayer perceptron using Bayesian search and Hyperband early stopping. We validated our model by replacing the full chemistry module of ATLAS and comparing computation time, accuracy, and stability. We found that our model had a computation time that was a factor of 700 faster than the full chemistry module. The accuracy of our model compares favorably to the full chemistry module within a 2-year simulation run, also outperforms a previous polynomial approach for fast ozone chemistry, and reproduces seasonality well in both hemispheres. In conclusion, the neural representation of stratospheric ozone chemistry in simulation resulted in an ozone layer that showed a high accuracy, significant speed-up, and stability in a long-term simulation.
Remittances, Nonlabor Income as a Source of Hysteresis in Unemployment in Colombia, 2010–2020
Authors: Cardona-Arenas Carlos David , Sierra-Suarez Lya Paola 
Published: December 2023

AbstractThis study seeks to determine the impact of remittances and nonlabor income on the duration of unemployment, and therefore on the hysteresis phenomenon in Colombia for the period between January 2010 and January 2021. The long-term unemployment rate in Colombia (LAPU) is calculated, and a vector autoregressive (VAR) model is subsequently estimated to evaluate the impact of remittances and nonlabor income on the LAPU. The results suggest that the increase in nonlabor income significantly affected LAPU in Colombia in the period analyzed. The growth of remittances instead turned out to positively and significantly impact LAPU only during the COVID-19 pandemic crisis. This suggests that remittances have become a fundamental income in times of crisis that allow for financing the search for work for a longer period of time, thus increasing the duration of unemployment and generating a hysteresis effect.