bluuebunny/crossref_metadata_2025_split huggingface dataset:
Barium titanate–silicon elastomer based body coupled antenna for wearable microwave head imaging applications
Authors: Tayab Sakib Md Abu , Riza Bashri Mohd Saiful , Islam Md. Rafiqul 
Published: April 2024

This paper presents a flexible monopole antenna fed by a coplanar waveguide (CPW) feeding line with a barium titanate (BaTiO3) silicon-elastomer impedance matching layer for microwave head imaging applications. The operating frequency bandwidth of the proposed antenna is 614 MHz which is from 0.475 GHz to 1.089 GHz. In biomedical microwave sensing and imaging applications, the major challenge is the high power loss due to reflection between the BaTiO3 and the antenna due to impedance mismatch. Therefore, the proposed BaTiO3 silicon-elastomer composite is designed to have dielectric property of 20 which acts as an impedance matching layer for the monopole antenna. The proposed antenna has dimensions of 70×30×6 mm. The flexibility of the antenna is provided by the use of the silicon elastomer. It has been shown that the power radiated into an artificial head phantom improved by almost 160% as compared to antenna without impedance matching layer. Moreover, the SAR level is 0.0286 W/kg when 1 mW of power is transmitted, which is well below the limit set by the regulation. This makes the antenna suitable for wearable biomedical applications due to its wideband characteristic and improved power penetration into human head.
Verifiable data distribution technique for multiple applicants in a cloud computing ecosystem
Authors: Karemallaiah Jayalakshmi , Revaiah Prabha 
Published: April 2024

<span lang="EN-US"><span lang="EN-US">Cloud computing is the most exploited research technology in both industry and academia due to wide application and increases in adoption from global organizations. In cloud, computing data storage is one of the primary resources offered through cloud computing, however, an increase in participants raises major security concerns, as the user has no hold over the data. Furthermore, recent research has shown great potential for efficient data sharing with multiple participants. Existing researches suggest complicated and inefficient cloud security architecture. Hence, this research work proposes identifiable data sharing for multiple users (IDSMU) mechanism, which aims to provide security for multiple users in a particular cloud group. A novel signature scheme is used for identifying the participants, further verification of the Novel Signature Scheme is proposed along with a retraction process where the secret keys of the participant and the sender is cross-verified; at last, a module is designed for the elimination of any malicious participants within the group. IDSMU is evaluated on computation count and efficiency is proved by comparing with an existing model considering computation count. IDSMU performs marginal improvisation over the existing model in comparison with the existing model using the novel signature scheme. </span><br /></span>
Model for motivating learners with personalized learning objects in a hypermedia adaptive learning system
Authors: Ikram Chelliq , Lamya Anoir , Mohamed Erradi , Mohamed Khaldi 
Published: April 2024

<span lang="EN-US">A number of weaknesses were demonstrated in the E-learning platforms during the Covid-19 pandemic despite the efforts invested. This has negatively influenced learners' motivation and consequently their performance. With the proliferation of technology and the revolution of information and communication technologies (ICT), learning objects have become new epitomes widely used, accessible, and implemented with educational resources and technological support. The integration of learning objects into E-learning has enhanced educational progress, but during critical periods, it is crucial to ensure pedagogical continuity and learner motivation. Based on this observation, we will propose architecture of a personalized learning object model in the context of an adaptive hypermedia learning system (AHS). The objective of our model is to increase the motivation factor which is a determining element in the success of E-learning, our model aims to improve the performance of the learners in order to avoid the abounding of learning and to promote the attendance of the learners. This will be useful later for any design or development of learning objects in hypermedia learning systems that are adaptive to the needs of the learners and in line with their preferences and profiles throughout the learning process offered by the system. </span>
A hybrid deep learning optimization for predicting the spread of a new emerging infectious disease
Authors: Nastiti Faulinda Ely , Musa Shahrulniza , Yafi Eiad 
Published: April 2024

<span lang="EN-US">In this study, a novel approach geared toward predicting the estimated number of coronavirus disease (COVID-19) cases was developed. Combining long short-term memory (LSTM) neural networks with particle swarm optimization (PSO) along with grey wolf optimization (GWO) employ hybrid optimization algorithm techniques. This investigation utilizes COVID-19 original data from the Ministry of Health of Indonesia, period 2020-2021. The developed LSTM-PSO-GWO hybrid optimization algorithm can improve the performance and accuracy of predicting the spread of the COVID-19 virus in Indonesia. In initiating LSTM initial weights with weaknesses, using the hybrid optimization algorithm helps overcome these problems and improve model performance. The results of this study suggest that the LSTM-PSO-GWO model can be utilized as an effective and reliable predictive tool to gauge the COVID-19 virus’s spread in Indonesia. </span>
A new efficient decoder of linear block codes based on ensemble learning models: case of boosting
Authors: El Assad Mohammed , Nouh Said , Chemseddine Idrissi Imrane , Alaoui Seddiq El Kasmi , AYLAJ Bouchaib , Azzouazi Mohamed 
Published: April 2024

<p>Error-correcting codes are used to partially or completely correct errors as much as possible, while ensuring high transmission speeds. Several Machine Learning (ML) models such as Logistic Regression and Decision tree have been applied to correct transmission errors. Among the most powerful ML techniques are aggregation methods which have yielded to excellent results in many areas of research. It is this excellence that has prompted us to consider their application for the hard decoding problem. In this sense, we have successfully designed, tested and validated our proposed EL-BoostDec decoder (hard decision decoder based on Ensemble Learning - Boosting technique) which is based on computing of the syndrome of the received word and on using Ensemble Learning techniques to find the corresponding corrigible error. The obtained results with EL-BoostDec are very encouraging in terms of the binary error rate (BER) that it offers. Practically EL-BoostDec has succeed to correct 100% of errors that have weights less than or equal to the correction capacity of studied codes. The comparison of EL-BoostDec with many competitors proves its power. A study of parameters which impact on EL-BoostDec performances has been established to obtain a good BER with minimum run time complexity.</p>
CREST‐2 Commitment to Rigorous Assessment of Carotid Stenting for Primary Prevention of Stroke
Authors: Meschia James F. , Edwards Lloyd , Roubin Gary , Brott Thomas G. , Lal Brajesh K. 
Published: April 2024

Background

Rather than considering carotid stenting and endarterectomy to be rival procedures, they ought to be seen as complementary, with some patients more suited to one procedure over another. The respective patient populations best suited for optimal outcomes with stenting and endarterectomy differ substantially. Hence, the CREST‐2 (Carotid Revascularization, Endarterectomy Versus Stent Trial‐2)
(
study was designed as 2 separate 2‐arm randomized trials run in parallel. One trial compares intensive medical management with and without stenting; the other, intensive medical management with and without endarterectomy. Each trial has a recruitment target of 1240 patients with ≥70% asymptomatic carotid stenosis, randomized 1:1 in each arm. To ensure patient safety and give stenting the best possible chance of demonstrating net benefits in stroke prevention, CREST‐2 adopted a rigorous procedure for evaluating, monitoring, and approving operators to enroll in the trial. The CREST‐2 Registry was established to allow for recent experience for applicant stent operators.

Methods
The CREST‐2 Registry is a prospective, multicenter, short‐term observational study of carotid stenting allowing use of multiple devices.

Results
The registry enrolled its first patient in September 2014, and as of October 2, 2023, a total of 9830 patients have been treated by 207 different stent operators from 103 different clinical centers. In this mixed cohort of asymptomatic (61.1% of the cohort) and symptomatic (38.9%) patients, the 30‐day stroke rate is 1.8% and the combined 30‐day stroke or death rate is 2.6%. At its peak in March 2016, the registry achieved an enrollment rate of 142 cases/month. As of October 20, 2023, a total of 104 patients remain to be enrolled in the CREST‐2 stenting trial.

Conclusion
The registry has facilitated assembly of a high‐performing team of stent operators for the CREST‐2 trial. With continued support of the many operators, we anticipate completing enrollment by the summer of 2024.
The Important Role of the Right Dorsolateral Prefrontal Cortex in Conflict Adaptation: A Combined Voxel-Based Morphometry and Continuous Theta Burst Stimulation Study
Authors: Xu Ping , Lin Feng , Alimu Gulibaier , Zhang Junjun , Jin Zhenlan , Li Ling 
Published: April 2024

Abstract
Humans can flexibly adjust their executive control to resolve conflicts. Conflict adaptation and conflict resolution are crucial aspects of conflict processing. Functional neuroimaging studies have associated the dorsolateral prefrontal cortex (DLPFC) with conflict processing, but its causal role remains somewhat controversial. Moreover, the neuroanatomical basis of conflict processing has not been thoroughly examined. In this study, the Stroop task, a well-established measure of conflict, was employed to investigate (1) the neuroanatomical basis of conflict resolution and conflict adaptation with the voxel-based morphometry analysis, (2) the causal role of DLPFC in conflict processing with the application of the continuous theta burst stimulation to DLPFC. The results revealed that the Stroop effect was correlated to the gray matter volume of the precuneus, postcentral gyrus, and cerebellum, and the congruency sequence effect was correlated to the gray matter volume of superior frontal gyrus, postcentral gyrus, and lobule paracentral gyrus. These findings indicate the neuroanatomical basis of conflict resolution and adaptation. In addition, the continuous theta burst stimulation over the right DLPFC resulted in a significant reduction in the Stroop effect of RT after congruent trials compared with vertex stimulation and a significant increase in the Stroop effect of accuracy rate after incongruent trials than congruent trials, demonstrating the causal role of right DLPFC in conflict adaptation. Moreover, the DLPFC stimulation did not affect the Stroop effect of RT and accuracy rate. Overall, our study offers further insights into the neural mechanisms underlying conflict resolution and adaptation.
Neuroethics, Covert Consciousness, and Disability Rights: What Happens When Artificial Intelligence Meets Cognitive Motor Dissociation?
Authors: Fins Joseph J. , Shulman Kaiulani S. 
Published: April 2024

Abstract
In this article, we consider the intersection of cognitive motor dissociation (CMD) and artificial intelligence (AI), hence when CMD meets AI. In covert consciousness, there is a discordance between the observed behavior, the traditional bedside mode of assessment, and the response to volitional commands as depicted by neuroimaging or EEG studies. This alphabet soup of acronyms represents both the promise and peril of nascent technology in covert consciousness. On the diagnostic side, there is the complexity and uncertainty of identifying the discordance between cognitive activity and overt behavior. On the therapeutic side, when AI is used to generate speech, there is the possibility of misrepresenting the thoughts and intentions of those who are otherwise voiceless. This concordance of factors makes the application of AI to CMD worthy of deeper consideration. We offer this analysis in the spirit of anticipatory governance, a prudential process by which one plans to prevent or mitigate unintended consequences of novel technology. We first consider the normative challenges posed by CMD for clinical practice, neuroethics, and the law. We then explore the history of covert consciousness and the relationship of severe brain injury to the right-to-die movement, before introducing three biographies of brain injury that highlight the potential impact of disability bias or ableism in clinical practice, assistive technology, and translational research. Subsequently, we explore how AI might give voice to conscious individuals who are unable to communicate and the ethical challenges that this technology must overcome to promote human flourishing drawing upon what Nussbaum and Sen have described as a “capabilities approach” to promote normative reasoning.
Inferring Consciousness in Phylogenetically Distant Organisms
Authors: Godfrey-Smith Peter 
Published: April 2024

Abstract
The neural dynamics of subjectivity (NDS) approach to the biological explanation of consciousness is outlined and applied to the problem of inferring consciousness in animals phylogenetically distant from ourselves. The NDS approach holds that consciousness or felt experience is characteristic of systems whose nervous systems have been shaped to realize subjectivity through a combination of network interactions and large-scale dynamic patterns. Features of the vertebrate brain architecture that figure in other accounts of the biology of consciousness are viewed as inessential. Deep phylogenetic branchings in the animal kingdom occurred before the evolution of complex behavior, cognition, and sensing. These capacities arose independently in brain architectures that differ widely across arthropods, vertebrates, and cephalopods, but with conservation of large-scale dynamic patterns of a kind that have an apparent link to felt experience in humans. An evolutionary perspective also motivates a strongly gradualist view of consciousness; a simple distinction between conscious and nonconscious animals will probably be replaced with a view that admits differences of degree, perhaps on many dimensions.
Age-related Differences in Response Inhibition Are Mediated by Frontoparietal White Matter but Not Functional Activity
Authors: Parimoo Shireen , Grady Cheryl , Olsen Rosanna 
Published: April 2024

Abstract
Healthy older adults often exhibit lower performance but increased functional recruitment of the frontoparietal control network during cognitive control tasks. According to the cortical disconnection hypothesis, age-related changes in the microstructural integrity of white matter may disrupt inter-regional neuronal communication, which in turn can impair behavioral performance. Here, we use fMRI and diffusion-weighted imaging to determine whether age-related differences in white matter microstructure contribute to frontoparietal over-recruitment and behavioral performance during a response inhibition (go/no-go) task in an adult life span sample (n = 145). Older and female participants were slower (go RTs) than younger and male participants, respectively. However, participants across all ages were equally accurate on the no-go trials, suggesting some participants may slow down on go trials to achieve high accuracy on no-go trials. Across the life span, functional recruitment of the frontoparietal network within the left and right hemispheres did not vary as a function of age, nor was it related to white matter fractional anisotropy (FA). In fact, only frontal FA and go RTs jointly mediated the association between age and no-go accuracy. Our results therefore suggest that frontal white matter cortical “disconnection” is an underlying driver of age-related differences in cognitive control, and white matter FA may not fully explain functional task-related activation in the frontoparietal network during the go/no-go task. Our findings add to the literature by demonstrating that white matter may be more important for certain cognitive processes in aging than task-related functional activation.
Implicit Adaptation Is Modulated by the Relevance of Feedback
Authors: Tsay Jonathan , Parvin Darius E. , Dang Kristy V. , Stover Alissa R. , Ivry Richard B. , Morehead J. Ryan 
Published: April 2024

Abstract
Given that informative and relevant feedback in the real world is often intertwined with distracting and irrelevant feedback, we asked how the relevancy of visual feedback impacts implicit sensorimotor adaptation. To tackle this question, we presented multiple cursors as visual feedback in a center-out reaching task and varied the task relevance of these cursors. In other words, participants were instructed to hit a target with a specific task-relevant cursor, while ignoring the other cursors. In Experiment 1, we found that reach aftereffects were attenuated by the mere presence of distracting cursors, compared with reach aftereffects in response to a single task-relevant cursor. The degree of attenuation did not depend on the position of the distracting cursors. In Experiment 2, we examined the interaction between task relevance and attention. Participants were asked to adapt to a task-relevant cursor/target pair, while ignoring the task-irrelevant cursor/target pair. Critically, we jittered the location of the relevant and irrelevant target in an uncorrelated manner, allowing us to index attention via how well participants tracked the position of target. We found that participants who were better at tracking the task-relevant target/cursor pair showed greater aftereffects, and interestingly, the same correlation applied to the task-irrelevant target/cursor pair. Together, these results highlight a novel role of task relevancy on modulating implicit adaptation, perhaps by giving greater attention to informative sources of feedback, increasing the saliency of the sensory prediction error.
The Costs (and Benefits?) of Effortful Listening for Older Adults: Insights from Simultaneous Electrophysiology, Pupillometry, and Memory
Authors: Silcox Jack W. , Bennett Karen , Copeland Allyson , Ferguson Sarah Hargus , Payne Brennan R. 
Published: April 2024

Abstract
Although the impact of acoustic challenge on speech processing and memory increases as a person ages, older adults may engage in strategies that help them compensate for these demands. In the current preregistered study, older adults (n = 48) listened to sentences—presented in quiet or in noise—that were high constraint with either expected or unexpected endings or were low constraint with unexpected endings. Pupillometry and EEG were simultaneously recorded, and subsequent sentence recognition and word recall were measured. Like young adults in prior work, we found that noise led to increases in pupil size, delayed and reduced ERP responses, and decreased recall for unexpected words. However, in contrast to prior work in young adults where a larger pupillary response predicted a recovery of the N400 at the cost of poorer memory performance in noise, older adults did not show an associated recovery of the N400 despite decreased memory performance. Instead, we found that in quiet, increases in pupil size were associated with delays in N400 onset latencies and increased recognition memory performance. In conclusion, we found that transient variation in pupil-linked arousal predicted trade-offs between real-time lexical processing and memory that emerged at lower levels of task demand in aging. Moreover, with increased acoustic challenge, older adults still exhibited costs associated with transient increases in arousal without the corresponding benefits.
Relationship Between Resting State Functional Connectivity and Reading-Related Behavioural Measures in 69 Adults
Authors: Bathelt Joe , Rastle Kathleen , Taylor J. S. H. 
Published: April 2024

Abstract
In computational models of reading, written words can be read using print-to-sound and/or print-to-meaning pathways. Neuroimaging data associate dorsal stream regions (left posterior occipitotemporal cortex, intraparietal cortex, dorsal inferior frontal gyrus [dIFG]) with the print-to-sound pathway and ventral stream regions (left anterior fusiform gyrus, middle temporal gyrus) with the print-to-meaning pathway. In 69 typical adults, we investigated whether resting state functional connectivity (RSFC) between the visual word form area (VWFA) and dorsal and ventral regions correlated with phonological (nonword reading, nonword repetition, spoonerisms), lexical-semantic (vocabulary, sensitivity to morpheme units in reading), and general literacy (word reading, spelling) skills. VWFA activity was temporally correlated with activity in both dorsal and ventral reading regions. In pre-registered whole-brain analyses, spoonerisms performance was positively correlated with RSFC between the VWFA and left dorsal regions (dIFG, superior parietal and intraparietal cortex). In exploratory region-of-interest analyses, VWFA-dIFG connectivity was also positively correlated with nonword repetition, spelling, and vocabulary. Connectivity between the VWFA and ventral stream regions was not associated with performance on any behavioural measure, either in whole-brain or region-of-interest analyses. Our results suggest that tasks such as spoonerisms and spellings, which are both complex (i.e., involve multiple subprocesses) and have high between-subject variability, provide greater opportunity for observing resting-state brain-behaviour associations. However, the complexity of these tasks limits the conclusions we can draw about the specific mechanisms that drive these associations. Future research would benefit from constructing latent variables from multiple tasks tapping the same reading subprocess.
Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past
Authors: Johnson Andrew E. , Renambot Luc , Marai G. Elisabeta , Tsoupikova Daria , Papka Michael E. , Long Lance , Plepys Dana , Talandis Jonas , Brown Maxine D. , Leigh Jason , Sandin Daniel J. , DeFanti Thomas A. 
Published: April 2024

Abstract
September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.