bluuebunny/crossref_metadata_2025_split huggingface dataset:
ThermoMaze: A behavioral paradigm for readout of immobility-related brain events
Authors: Vöröslakos Mihály , Zhang Yunchang , McClain Kathryn , Huszár Roman , Rothstein Aryeh , Buzsáki György 
Published: July 2023

AbstractBrain states fluctuate between exploratory and consummatory phases of behavior. These state changes affect both internal computation and the organism’s responses to sensory inputs. Understanding neuronal mechanisms supporting exploratory and consummatory states and their switching requires experimental control of behavioral shifts and collecting sufficient amounts of brain data. To achieve this goal, we developed the ThermoMaze, which exploits the animal’s natural warmth-seeking homeostatic behavior. By decreasing the floor temperature and selectively heating unmarked areas, mice avoid the aversive state by exploring the maze and finding the warm spot. In its design, the ThermoMaze is analogous to the widely used water maze but without the inconvenience of a wet environment and, therefore, allows the collection of physiological data in many trials. We combined the ThermoMaze with electrophysiology recording, and report that spiking activity of hippocampal CA1 neurons during sharp-wave ripple events encode the position of the animal. Thus, place-specific firing is not confined to locomotion and associated theta oscillations but persist during waking immobility and sleep at the same location. The ThermoMaze will allow for detailed studies of brain correlates of immobility, preparatory-consummatory transitions and open new options for studying behavior-mediated temperature homeostasis.
Graph Attention Site Prediction (GrASP): Identifying Druggable Binding Sites Using Graph Neural Networks with Attention
Authors: Smith Zachary , Strobel Michael , Vani Bodhi P. , Tiwary Pratyush 
Published: July 2023

ABSTRACTIdentifying and discovering druggable protein binding sites is an important early step in computer-aided drug discovery but remains a difficult task where most campaigns rely ona prioriknowledge of binding sites from experiments. Here we present a novel binding site prediction method called Graph Attention Site Prediction (GrASP) and re-evaluate assumptions in nearly every step in the site prediction workflow from dataset preparation to model evaluation. GrASP is able to achieve state-of-the-art performance at recovering binding sites in PDB structures while maintaining a high degree of precision which will minimize wasted computation in downstream tasks such as docking and free energy perturbation.
AnglesRefine: refinement of 3D protein structures using Transformer based on torsion angles
Authors: Zhang Lei , Zhu Junyong , Wang Sheng , Hou Jie , Si Dong , Cao Renzhi 
Published: July 2023

ABSTRACTMotivationThe goal of protein structure refinement is to enhance the precision of predicted protein models, particularly at the residue level of the local structure. Existing refinement approaches primarily rely on physics, whereas molecular simulation methods are resource-intensive and time-consuming. In this study, we employ deep learning methods to extract structural constraints from protein structure residues to assist in protein structure refinement. We introduce a novel method, AnglesRefine, which focuses on a protein’s secondary structure and employs a transformer model to refine various protein structure angles (psi, phi, omega, CA_C_N_angle, C_N_CA_angle, N_CA_C_angle), ultimately generating a superior protein model based on the refined angles.ResultsWe evaluate our approach against other cutting-edge protein structure refinement methods using the CASP11-14 and CASP15 datasets. Experimental outcomes indicate that our method generally surpasses other techniques on the CASP11-14 test dataset, while performing comparably or marginally better on the CASP15 test dataset. Our method consistently demonstrates the least likelihood of model quality degradation, e.g., the degradation percentage of our method is less than 10%, while other methods are about 50%. Furthermore, as our approach eliminates the need for conformational search and sampling, it significantly reduces computational time compared to existing protein structure refinement methods.Availabilityhttps://github.com/Cao-Labs/AnglesRefine.gitContactcaora@plu.eduCCS CONCEPTS*Computing methodologies→Machine learning.ACM Reference FormatLei Zhang, Junyong Zhu, Sheng Wang, Jie Hou, Dong Si, and Renzhi Cao. 2023. AnglesRefine: refinement of 3D protein structures using Transformer based on torsion angles. InProceedings of 22nd International Workshop on Data Mining in Bioinformatics (BIOKDD 2023) (BIOKDD ‘2023). ACM, New York, NY, USA, 10 pages. https://doi.org/XXXXXXX.XXXXXXX
Altering a complex serial reaction time task using dual DLPFC and M1-transcranial direct current stimulation
Authors: Kaminski E. , Carius D. , Knieke J. , Mizuguchi N. , Ragert P. 
Published: July 2023

AbstractTranscranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique which was found to have a positive modulatory effect on online sequence acquisition or offline motor consolidation, depending on the relative role of the associated brain region. Primary motor regions (M1) and dorsolateral prefrontal cortices (DLPFC) have both been related to sequential learning. However, research so far did not systematically disentangle their differential roles in online and offline learning especially in more complex sequential paradigms. In this study, the influence of M1-tDCS and DLPFC-tDCS on complex sequential learning (online and offline) was investigated using a complex whole body serial reaction time task (CWB-SRTT) in 42 healthy volunteers. TDCS groups did not differ from sham tDCS group regarding their total time to complete the sequence and reaction time (online) and also not in terms of over-night consolidation (offline). Results may be related to unspecific parameters such as timing of the stimulation or current intensity but can also be attributed to the relative role of M1 and DLPFC during early complex learning. Future studies should consider investigating neural parameters during early complex CWB-SRTT learning to gain information on changes in neural activation within sequence acquisition with a specific focus on M1 and DLPFC.
Reliability and generalizability of neural speech tracking in younger and older adults
Authors: Panela Ryan A. , Copelli Francesca , Herrmann Björn 
Published: July 2023

AbstractNeural tracking of continuous, spoken speech is increasingly used to examine how the brain encodes speech and is considered a potential clinical biomarker, for example, for age-related hearing loss. A biomarker must be reliable (intra-class correlation [ICC] >0.7), but the reliability of neural-speech tracking is unclear. In the current study, younger and older adults (different genders) listened to stories in two separate sessions while electroencephalography (EEG) was recorded in order to investigate the reliability and generalizability of neural speech tracking. Neural speech tracking was larger for older compared to younger adults for stories under clear and background noise conditions, consistent with a loss of inhibition in the aged auditory system. For both age groups, reliability for neural speech tracking was lower than the reliability of neural responses to noise bursts (ICC >0.8), which we used as a benchmark for maximum reliability. The reliability of neural speech tracking was moderate (ICC ∼0.5-0.75) but tended to be lower for younger adults when speech was presented in noise. Neural speech tracking also generalized moderately across different stories (ICC ∼0.5-0.6), which appeared greatest for audiobook-like stories spoken by the same person. This indicates that a variety of stories could possibly be used for clinical assessments. Overall, the current data provide results critical for the development of a biomarker of speech processing, but also suggest that further work is needed to increase the reliability of the neural-tracking response to meet clinical standards.Significance statementNeural speech tracking approaches are increasingly used in research and considered a biomarker for impaired speech processing. A biomarker needs to be reliable, but the reliability of neural speech tracking is unclear. The current study shows in younger and older adults that the neural-tracking response is moderately reliable (ICC ∼0.5-0.75), although more variable in younger adults, and that the tracking response also moderately generalize across different stories (ICC ∼0.5-0.6), especially for audiobook-like stories spoken by the same person. The current data provide results critical for the development of a biomarker of speech processing, but also suggest that further work is needed to increase the reliability of the neural-tracking response to meet clinical standards.
Enhanced cell segmentation with limited annotated data using generative adversarial networks
Authors: Zargari Abolfazl , Mashhadi Najmeh , Shariati S. Ali 
Published: July 2023

AbstractThe application of deep learning is rapidly transforming the field of bioimage analysis. While deep learning has shown great promise in complex microscopy tasks such as single-cell segmentation, the development of generalizable foundation deep learning segmentation models is hampered by the scarcity of large and diverse annotated datasets of cell images for training purposes. Generative Adversarial Networks (GANs) can generate realistic images that can potentially be easily used to train deep learning models without the generation of large manually annotated microscopy images. Here, we propose a customized CycleGAN architecture to train an enhanced cell segmentation model with limited annotated cell images, effectively addressing the challenge of paucity of annotated data in microscopy imaging. Our customized CycleGAN model can generate realistic synthetic images of cells with morphological details and nuances very similar to that of real images. This method not only increases the variability seen during training but also enhances the authenticity of synthetic samples, thereby enhancing the overall predictive accuracy and robustness of the cell segmentation model. Our experimental results show that our CycleGAN-based method significantly improves the performance of the segmentation model compared to conventional training techniques. Interestingly, we demonstrate that our model can extrapolate its knowledge by synthesizing imaging scenarios that were not seen during the training process. Our proposed customized CycleGAN method will accelerate the development of foundation models for cell segmentation in microscopy images.
Hippocampal timestamp for goals
Authors: Montagrin Alison , Croote Denise E. , Preti Maria Giulia , Lerman Liron , Baxter Mark G. , Schiller Daniela 
Published: July 2023

AbstractOur brain must manage multiple goals that differ in their temporal proximity. Some goals require immediate attention, while others have already been accomplished, or will be relevant later in time. Here, we examined how the hippocampus represents the temporal distance to different goals using a novel space-themed paradigm during 7T functional MRI (n=31). The hippocampus has an established role in mental time travel and a system in place to stratify information along its longitudinal axis on the basis of representational granularity. Previous work has documented a functional transformation from fine-grained, detail rich representations in the posterior hippocampus to coarse, gist-like representations in the anterior hippocampus. We tested whether the hippocampus uses this long axis system to dissociate goals based upon their temporal distance from the present. We hypothesized that the hippocampus would distinguish goals relevant for ones’ current needs from those that are removed in time along the long axis, with temporally removed past and future goals eliciting increasingly anterior activation. We sent participants on a mission to Mars where they had to track goals that differed in when they needed to be accomplished. We observed a long-axis dissociation, where temporally removed past and future goals activated the left anterior hippocampus and current goals activated the left posterior hippocampus. Altogether, this study demonstrates that the timestamp attached to a goal is a key driver in where the goal is represented in the hippocampus. This work extends the scope of the hippocampus’ long axis system to the goal-mapping domain.
The adsorption and inhibition efficiency of 2-amino-4-methoxy-6-methyl-1,3,5-triazine for corrosion of mild steel in hydrochloric acid solution
Authors: Ökten Veysi , Yıldız Reşit , Sığırcık Gökmen 
Published: July 2023

PurposeThis study aims to prevent mild steel (MS) against corrosion in 0.5 M HCl solution, 2-amino-4-methoxy-6-methyl-1,3,5-triazine was used. The effectiveness of the compound as a corrosion inhibitor was studied via electrochemical, surface and theoretical calculation techniques.Design/methodology/approachFor concentrations ranging from 0.5 to 10.0 mM, almost similar polarization resistances were obtained from electrochemical impedance spectroscopy (EIS) and linear polarization resistance tests. It also investigated inhibitive activity of 2-amino-4-methoxy-6-methyl-1,3,5-triazine on the steel surface using scanning electron and atomic force microscope instruments. Langmuir adsorption is the best matched isotherm for the adsorption of the inhibitor to the steel surface.FindingsEIS method was used to determine inhibition efficiency, which was determined to be 95.7% for 10.0 mM inhibitor containing acid solution. Density functional theory’s predictions for quantum chemistry agreed well with the other experimental results.Originality/valueThe methods used in this study are effective and applicable; the used organic inhibitor is 2-amino-4-methoxy-6-methyl-1,3,5-triazine; and protective effectiveness is important, which is crucial for the task of MS corrosion prevention.
Development process for preliminary aircraft sizing methods with regard to new technologies
Authors: Schneider Johannes , Strohmayer Andreas 
Published: July 2023

Purpose
The purpose of this study is to develop and describe a process which can be applied to develop new methods in the context of preliminary aircraft sizing in a successful and efficient way.

Design/methodology/approach
The tasks to development new aircraft sizing methods are systematically analyzed. In particular, repeating and nonrepeating tasks and common or unique tasks. Then ordered in a sequence and described generically.

Findings
A development process for new aircraft design methods which are necessary for new technologies or configurations is introduced and explained step by step.

Practical implications
Introducing the capability to deal with new technologies or configurations, aircraft design tools or aircraft concepts requires new sizing methods.

Originality/value
The paper presents a systematic approach which can be used to develop a great amount of new sizing methods with a comparable usability and quality standard in an efficient and effective way.
Exploring the experiences of researchers in the interdisciplinary humanities research teams on knowledge creation: a qualitative study
Authors: Karparvar Zahra , Mirzabeigi Mahdieh , Salimi Ghasem 
Published: July 2023

PurposeThe process of knowledge creation is recognized as an essential process for organizational learning and innovation. Creating knowledge to solve the problems and complexities of today's world is like opening a black box. Hence, the higher education system and universities are exploring ways to overcome the complexities and cope with global changes. In this regard, interdisciplinary collaborations and activities are crucial in creating knowledge and innovation to counter these changes. This study aimed to know the experiences of Shiraz university interdisciplinary researchers in the field of humanities and also design and explain the conceptual model of knowledge creation in interdisciplinary research teams in the field of humanities.Design/methodology/approachIn this qualitative research, grounded theory was implemented based on Strauss and Corbin's systematic approach. The sampling method was purposeful, and the participants included sixteen faculty members of shiraz university who had at least one experience of performing an interdisciplinary activity in one of the humanities fields. The first participant was selected as a pilot, and the rest were selected by snowball sampling. Semi-structured interviews were also used to collect data and continued until theoretical saturation was attained. After collecting the available information and interviewing the people, the data were organized and analyzed in three stages, open coding, axial coding, and selective coding, using the proposed framework of Strauss and Corbin. Finally, the researcher reached a final and meaningful categorization.FindingsIn this research, the results were presented as a paradigm model of knowledge creation in the interdisciplinary research teams in the field of humanities. The paradigm model of the study consists of causal factors (internal and external factors), main categories (specialized competencies, scientific discourse, understanding of knowledge domains), strategies (structuring and synchronizing), context (individual and organizational), interfering factors (leadership, industry, and society), and consequences (individual and group achievement).Originality/valueThe present study aimed to explore the experiences of researchers in the interdisciplinary humanities research teams on knowledge creation in qualitative research. The study used Strauss and Corbin's systematic approach to recognize the causal factors of knowledge creation and the contexts. Discovering the main category of knowledge creation in interdisciplinary research teams, the authors analyze the strategies and consequences of knowledge creation.
Critical indicators for assessing the life cycle social footprint of Australian freeways
Authors: Vijayakumar Ankitha , Mahmood Muhammad Nateque , Gurmu Argaw , Kamardeen Imriyas , Alam Shafiq 
Published: July 2023

Purpose
Freeways in Australia play a significant role in connecting distant communities, shifting freight and strengthening the country’s economy. To meet the growing needs of present and future generations, delivering a socially sustainable road infrastructure that creates generational benefits is essential. However, the existing literature reveals the lack of comprehensive indicators to assess the social sustainability performance of freeway projects. Therefore, this paper aims to identify a critical set of system-specific indicators to evaluate the life cycle social footprint of Australian freeways.

Design/methodology/approach
This study conducted 31 interview questionnaire surveys with actively engaged stakeholders involved in various freeway projects around Australia. The data collected was analysed using fuzzy set theory and other statistical approaches.

Findings
The study identified 42 critical indicators for assessing the social sustainability performance throughout the life cycle of freeways in the Australian context. For example, stakeholder involvement, reduction of casualty rate due to road accidents, fair remuneration to project workforce and improved accessibility to required services.

Practical implications
The context-specific opinions extracted from the industry experts and the comprehensive set of critical indicators identified would ensure that all the vital aspects of social sustainability are considered throughout the life cycle of Australian freeways in the future, assisting the decision-makers in enhancing the project’s social sustainability performance.

Originality/value
The linguistic explanations associated with the ratings given by the industry experts provide greater insight into the context of the life cycle social sustainability assessment of Australian freeways exclusively.
Determining the post-adoptive intention of millennials for MOOCs: an information systems perspective
Authors: Shah Jinal , Khanna Monica 
Published: July 2023

Purpose
This study aims to understand the learner behaviour of millennials for Massive Open Online Courses (MOOCs) in the post-adoption stage by extending the theory of Unified Theory of Acceptance and User Technology 2 (UTAUT2) with expectancy confirmation model (ECM) along with personal innovativeness as the exogenous, satisfaction as a mediating and continued intention as an endogenous construct.

Design/methodology/approach
This study applied a cross-sectional research design by using a survey method to collect primary data with a structured questionnaire. Convenience sampling was used to collect data from millennial MOOC users, and partial least square structural equation modelling method was applied for data analysis.

Findings
The results indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation influence satisfaction. Similarly, performance expectancy, hedonic motivation, personal innovativeness and satisfaction influence the continued intention for MOOCs.

Research limitations/implications
In terms of limitations, the study applied a cross-sectional research design that could lead to data collection bias. Similarly, the study used convenience sampling as the authors did not have access to the participant list of users from MOOC platforms.

Practical implications
The research highlights various insights to all the stakeholders on improving MOOC satisfaction and enhance the continued intention for millennial learners.

Originality/value
The findings of this research bridge this gap by examining the post-adoption usage behaviour of MOOCs by extending the baseline model of UTAUT2 with personal innovativeness and integrating it with ECM.
Strategic adaptability in negotiation: a framework to distinguish strategic adaptable behaviors
Authors: Heunis Henrike , Pulles Niels J. , Giebels Ellen , Kollöffel Bas , Sigurdardottir Aldis G. 
Published: July 2023

Purpose
This study aims to propose and evaluate a novel framework of strategic adaptability in dyadic negotiations. The authors define strategic adaptability as a reaction to a cue that leads to shifts between integrative and distributive strategies. Based on the literature on turning points, phase models and strategic negotiations, the authors developed an initial framework identifying five distinct strategic adaptations.

Design/methodology/approach
To verify the framework, the authors analyzed two negotiation simulations with a diverse set of negotiation students. Negotiations were content-coded, and adaptations were labeled.

Findings
The authors found a consistent pattern across two studies. Overall, 12% (study 1) and 18% (study 2) of all speaking turns were identified as strategic adaptations. The findings empirically confirmed four of their strategic adaptation types: adapt to deadlock, follow adaptation by opponent, adapt to priority of issue under discussion and adapt to new information on issue. Moreover, findings of this study revealed two new types of strategic adaptability: delayed adaptation to opponent and adapt to understand opponent. Study 2 additionally revealed that strategies vary with the negotiation phase, and negotiation outcome seems to benefit more from the constellation rather than the frequency of adaptations. Furthermore, lower-scoring negotiators tended to adapt to the opponent’s strategy instead of initiating a change in strategy.

Originality/value
The findings of this study provide preliminary insights into how strategic adaptations unfold. These findings present future research opportunities to further test the framework's robustness, increase the knowledge of individual and cultural factors, explore the relationship with negotiation outcomes and develop educational interventions to enhance strategic adaptability.