Language Paradigm Research Articles

Optimizing Nurse Rostering: A Case Study Using Integer Programming to Enhance Operational Efficiency and Care Quality

Background/Objectives: This study addresses the complex challenge of Nurse Rostering (NR) in oncology departments, a critical component of healthcare management affecting operational efficiency and patient care quality. Given the intricate dynamics of healthcare settings, particularly in oncology clinics, where patient needs are acute and unpredictable, optimizing nurse schedules is paramount for enhancing care delivery and staff satisfaction. Methods: Employing advanced Integer Programming (IP) techniques, this research develops a comprehensive model to optimise NR. The methodology integrates a variety of constraints, including legal work hours, staff qualifications, and personal preferences, to generate equitable and efficient schedules. Through a case study approach, the model’s implementation is explored within a clinical setting, demonstrating its practical application and adaptability to real-world challenges. Results: The implementation of the IP model in a clinical setting revealed significant improvements in scheduling efficiency and staff satisfaction. The model successfully balanced workload distribution among nurses, accommodated individual preferences to a high degree, and ensured compliance with work-hour regulations, leading to optimised shift schedules that support both staff well-being and patient care standards. Conclusions: The findings underscore the effectiveness of IP in addressing the complexities of NR in oncology clinics. By facilitating a strategic allocation of nursing resources, the proposed model contributes to operational excellence in healthcare settings, underscoring the potential of Operations Research in enhancing healthcare delivery and management practices.

Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MPPNB sites in the Southern Levant

This study was aimed at introducing a new method for predicting the original metrics of fragmented standardized artifacts, specifically of flint blades from the Middle Pre-Pottery Neolithic B (10,200/100–9,500/400 cal B.P.) in the Southern Levant. The excessive re-use of these artifacts or poor preservation conditions often prevent a complete set of metric data from being obtained. Our suggested approach is based on readily accessible machine learning (artificial intelligence) and neural network analysis. These are performed in a multi-paradigm programming language and numeric computing environment, with parameters represented by a rapid measurement system based on the technological features shared by all lithic artifacts of the studied assemblages. This method can be applied to various chronologies and/or contexts. A full set of metric data, including potential typological and functional elements of the assemblages studied, may provide a better understanding of the lithic technology involved; highlight cultural aspects related to the chaîne opératoire of the studied lithic production; and address issues related to cultural sub-divisions in larger-scale applications. Herein, neural network analysis was performed on blade samples from Middle Pre-Pottery Neolithic B sites from the Southern Levant specifically Nahal Yarmuth 38, Motza, Yiftahel, and Nahal Reuel.

DVRT: Design and evaluation of a virtual reality drone programming teaching system

Virtual Reality (VR) is an immersive virtual environment generated through computer technology. VR teaching, by utilizing an immersive learning model, offers innovative learning methods for Science, Technology, Engineering and Mathematics (STEM) education as well as programming education. This study developed a Drone Virtual Reality Teaching (DVRT) system aimed at beginners in drone operation and programming, with the goal of addressing the challenges in traditional drone and programming education, such as difficulty in engaging students and lack of practicality. Through the system's curriculum, students learn basic drone operation skills and advanced programming techniques. We conducted a course experiment primarily targeting undergraduate students who are beginners in drone operation. The test results showed that most students achieved scores above 4 out of 5, indicating that DVRT can effectively promote the development of users' comprehensive STEM literacy and computational thinking, thereby demonstrating the great potential of VR technology in STEM education. Through this innovative teaching method, students not only gain knowledge but also enjoy the fun of immersive learning.

Integrated market scheduling with flexibility options

This work presents a generic optimization framework using advanced mixed-integer programming techniques to integrate day-ahead and balancing markets with distributed energy resources such as storage, electric vehicles, demand response, and Transmission and Distribution System Operators' coordination schemes. The day-ahead model determines optimal initial energy scheduling, while the balancing model optimizes energy and reserve products for three market designs with varying Transmission and Distribution System Operators’ coordination. The framework is applied to the interconnected Greek-Bulgarian-Romanian power system, considering 2030 installed capacities.The model outputs illustrate market coupling scenarios among Romania, Bulgaria, and Greece, highlighting clear price signals and distributed energy resources flexibility. Results reveal the significance of a diverse energy mix for energy security and show that Transmission and Distribution System Operators’ coordination significantly influences ancillary service prices, with reductions of up to 80 % in certain scenarios. Net demand values determine electricity flow direction. Flexibility providers like storage can cover up to 100 % of the upward congestion management requirements and 11 % of upward balancing energy, helping smooth energy allocation from intermittent renewables. The impact of electric vehicle penetration on generation scheduling is minimal. The proposed model offers valuable insights for system operators, market participants, and policymakers, enabling them to provide accurate price signals and optimize resource allocation.The integrated day-ahead and balancing market models support efficient renewable energy integration, emissions reduction, enhanced grid stability, and investment in low-carbon technologies. This aligns with the United Nations Framework Convention on Climate Change goals, contributing to the development of sustainable and resilient energy systems.

Chunk Duration Limits the Learning of Multiword Chunks: Behavioral and Electroencephalography Evidence from Statistical Learning.

Language comprehension involves the grouping of words into larger multiword chunks. This is required to recode information into sparser representations to mitigate memory limitations and counteract forgetting. It has been suggested that electrophysiological processing time windows constrain the formation of these units. Specifically, the period of rhythmic neural activity (i.e., low-frequency neural oscillations) may set an upper limit of 2-3 sec. Here, we assess whether learning of new multiword chunks is also affected by this neural limit. We applied an auditory statistical learning paradigm of an artificial language while manipulating the duration of to-be-learned chunks. Participants listened to isochronous sequences of disyllabic pseudowords from which they could learn hidden three-word chunks based on transitional probabilities. We presented chunks of 1.95, 2.55, and 3.15 sec that were created by varying the pause interval between pseudowords. In a first behavioral experiment, we tested learning using an implicit target detection task. We found better learning for chunks of 2.55 sec as compared to longer durations in line with an upper limit of the proposed time constraint. In a second experiment, we recorded participants' electroencephalogram during the exposure phase to use frequency tagging as a neural index of statistical learning. Extending the behavioral findings, results show a significant decline in neural tracking for chunks exceeding 3 sec as compared to both shorter durations. Overall, we suggest that language learning is constrained by endogenous time constraints, possibly reflecting electrophysiological processing windows.

Portraying political violence, rape and masculinities in post-apartheid African language literature: the case of the novel Ngiyolibala Ngifile

The canon of African language literature has been critiqued in its entirety by local and foreign scholars on the premise that it has failed to respond to sociopolitical and colonial realities. This article argues that African language literature has been and continues to be socially committed in the post-apartheid epoch. This is argued through an analysis of the novel Ngiyolibala Ngifile by Sibiya. The analysis focuses on the portrayal of violence, rape and the construction of masculinities in post-apartheid South Africa. Through the utilisation of a post-colonial framework, the article shows how African language writers like Sibiya use the African milieu to link political violence, rape and masculinities to the colonial matrix, while simultaneously pointing to the causes and continuum of these topics. It further displays the author’s critique of the black bourgeoisie as stakeholders of colonialism, which unleashed violence on black bodies. This study is a significant insertion of masculinity as a critical unit, along with race, language and women, in the analysis of African language literature. This study recommends and proposes an expansion of the theoretical paradigm of reading African languages to accommodate neoteric frameworks of reading. It further suggests a close reading of African language literary texts through the postcolonial lens and with masculinities as a critical unit.

Test-retest reliability of the "Home Town Walk" fMRI paradigm for memory activation and lateralization in the pre-surgical evaluation of patients with temporal lobe epilepsy.

Functional magnetic resonance imaging (fMRI) can be used to assess language and memory function as part of pre-surgical decision making in refractory epilepsy. Although language paradigms are well established, memory paradigms are not widely used in clinical practice due to a lack of evidence for robust and reliable methods. Here, we aim to investigate the clinical utility of the Home Town Walk (HTW) paradigm for personalized treatment decisions in medial temporal lobe epilepsy. A cohort of 123 consecutive patients having HTW-fMRI as part of routine MRI scans over a 7.5 year period were included in this retrospective study. Of these, 111 patients underwent repeated HTW-fMRI in two scanning sessions one to three days apart. fMRI analysis was performed at the time of the scans using clinically approved software and retrospectively validated using FSL. We assessed the test-retest within subject reliability of activations within the posterior parahippocampal gyri (pPHG) at the individual subject level. Activations within the pPHG region were observed for 101 patients (91%) in at least one of the fMRI sessions and for 88 patients (79%) in both fMRI sessions, with 82 patients showing overlapping unilateral or bilateral activations and 8 further patients showing overlapping activations in one of the hemispheres but not the other. Reproducibility was evaluated using metrics based on the concordance ratios for size (Rsize) and location (Roverlap) within the pPHG region, as well as the lateralization index (LI) metric to reflect the asymmetry of hemispheric activations, which is of crucial relevance to inform surgery. Test-retest reliability of visuospatial memory LIs, assessed by an intra-class correlation coefficient (ICC) yielded a value of 0.76, indicating excellent between session stability of memory lateralization. The HTW-fMRI paradigm shows reproducible activations in the medial temporal lobes of individual epilepsy patients sufficient to consistently lateralize visuospatial memory function, demonstrating the clinical utility of HTW memory fMRI and its potential for application in the pre-surgical assessment of people with temporal lobe epilepsy.

L2 English listeners’ perceived comprehensibility and attitudes towards speech produced by L3 English learners from China

ABSTRACT This study investigated the perceptions of second language (L2) English learners from Hong Kong on the speech produced by third language (L3) English learners from the Greater Bay Area (GBA) of China. Twenty L2 learners from a local university were asked to listen to speech recordings from two L3 learners, and then complete an online survey, which focused on comprehension of the speech and four dimensions of language attitudes, namely Appropriateness, Solidarity, Status, and Dynamism. Results showed correlations between the phonological performance of learners and the perception of listeners. Specifically, vowel replacement and addition, as well as consonant addition were found to have a negative correlation with the learners’ actual comprehensibility. Replacing /ə/ with Chinese ‘er’ /ɚ/ only affected their perceived comprehensibility. For perceived attitude, the presence of vowel replacement and addition had an adverse effect on the rating of Dynamism. These two features, along with consonant addition, also negatively affected the rating of Status. Moreover, consonant addition was the sole factor that negatively affected the rating of Solidarity. These findings provided pedagogical insights for learners to communicate in English as well as social implications for language paradigm, particularly in a multilingual and multicultural context such as the GBA.

The Learner-centered Glocalization and Evidence-based Educational Decision-making on Glocalization: Two Issues on the Global Development of Chinese Language Teaching

In the twentieth century, Chinese teachers and researchers in China primarily viewed Chinese language teaching as teaching the language to foreigners, specifically those learning Chinese within China. In the twenty-first century, with the rapid increase in the number of global Chinese language learners, Chinese teachers and researchers have begun to focus on global Chinese language learners, and to support and meet the needs of them. There are two critical issues in the global development of Chinese Language Teaching (CLT): the learner-centered glocalization and the evidence-based educational decision-making on how to glocalize. Learner-centered glocalization reflects the humanism of caring about learners all over the world, and educational decisions on how to glocalize need to be based on scientific evidence to improve the effectiveness and efficiency of teaching and education. In terms of the current state of the field, there is a growing consensus of common sense on the glocalization of Chinese language teaching materials and paradigm, and the training and education of local teachers, but the scientific educational decision-making based on evidence such as findings from neuroscience is more difficult to achieve, rarely even discussed. However, the latter is the key to scientific glocalization of this area in the future.

Probabilistic Presurgical Language fMRI Atlas of Patients with Brain Tumors.

Patients with brain tumors have high intersubject variation in putative language regions, which may limit the utility of straightforward application of healthy subject brain atlases in clinical scenarios. The purpose of this study was to develop a probabilistic functional brain atlas that consolidates language functional activations of sentence completion and Silent Word Generation language paradigms using a large sample of patients with brain tumors. The atlas was developed using retrospectively collected fMRI data from patients with brain tumors who underwent their first standard-of-care presurgical language fMRI scan at our institution between July 18, 2015, and May 13, 2022. Three hundred seventeen patients (861 fMRI scans) were used to develop the language functional atlas. An independent presurgical language fMRI data set of 39 patients with brain tumors from a previous study was used to evaluate our atlas. Family-wise error-corrected binary functional activation maps from sentence completion, letter fluency, and category fluency presurgical fMRI were used to create probability overlap maps and pooled probabilistic overlap maps in Montreal Neurological Institute standard space. The Wilcoxon signed-rank test was used to determine a significant difference in the maximum Dice coefficient for our atlas compared with a meta-analysis-based template with respect to expert-delineated primary language area activations. Probabilities of activating the left anterior primary language area and left posterior primary language area in the temporal lobe were 87.9% and 91.5%, respectively, for sentence completion, 88.5% and 74.2%, respectively, for letter fluency, and 83.6% and 67.6%, respectively, for category fluency. Maximum Dice coefficients for templates derived from our language atlas were significantly higher than the meta-analysis-based template in the left anterior primary language area (0.351 and 0.326, respectively, P < .05) and the left posterior primary language area in the temporal lobe (0.274 and 0.244, respectively, P < .005). Brain tumor patient- and paradigm-specific probabilistic language atlases were developed. These atlases had superior spatial agreement with fMRI activations in individual patients compared with the meta-analysis-based template.

The changing landscape of electrical stimulation language mapping with subdural electrodes and stereoelectroencephalography for pediatric epilepsy: A literature review and commentary.

Electrical stimulation mapping (ESM) is used to locate the brain areas supporting language directly within the human cortex to minimize the risk of functional decline following epilepsy surgery. ESM is completed by utilizing subdural grid or depth electrodes (stereo-electroencephalography [sEEG]) in combination with behavioral evaluation of language. Despite technological advances, there is no standardized method of assessing language during pediatric ESM. To identify current clinical practices for pediatric ESM of language, we surveyed neuropsychologists in the Pediatric Epilepsy Research Consortium. Results indicated that sEEG is used for functional mapping at >80% of participating epilepsy surgery centers (n = 13/16) in the United States. However, >65% of sites did not report a standardized protocol to map language. Survey results indicated a clear need for practice recommendations regarding ESM of language. We then utilized PubMed/Medline and PsychInfo to identify 42 articles that reported on ESM of language, of which 18 met inclusion criteria, which included use of ESM/signal recording to localize language regions in children (<21 years) and a detailed account of the procedure and language measures used, and region-specific language localization outcomes. Articles were grouped based on the language domain assessed, language measures used, and the brain regions involved. Our review revealed the need for evidence-based clinical guidelines for pediatric language paradigms during ESM and a standardized language mapping protocol as well as standardized reporting of brain regions in research. Relevant limitations and future directions are discussed with a focus on considerations for pediatric language mapping.

GalaPy: A highly optimised C++/Python spectral modelling tool for galaxies

Bolstered by upcoming data from new-generation observational campaigns, we are about to enter a new era in the study of how galaxies form and evolve. The unprecedented quantity of data that will be collected from distances that have only marginally been grasped up to now will require analytical tools designed to target the specific physical peculiarities of the observed sources and handle extremely large datasets. One powerful method to investigate the complex astrophysical processes that govern the properties of galaxies is to model their observed spectral energy distributions (SEDs) at different stages of evolution and times throughout the history of the Universe. To address these challenges, we have developed GalaPy, a new library for modelling and fitting SEDs of galaxies from the X-ray to the radio band, as well as the evolution of their components and dust attenuation and reradiation. On the physical side, GalaPy incorporates both empirical and physically motivated star formation histories (SFHs), state-of-the-art single stellar population synthesis libraries, a two-component dust model for attenuation, an age-dependent energy conservation algorithm to compute dust reradiation, and additional sources of stellar continuum such as synchrotron, nebular and free-free emission, as well as X-ray radiation from low-and high-mass binary stars. On the computational side, GalaPy implements a hybrid approach that combines the high performance of compiled C++with the user-friendly flexibility of Python. Also, it exploits an object-oriented design via advanced programming techniques. GalaPy is the fastest SED-generation tool of its kind, with a peak performance of almost 1000 SEDs per second. The models are generated on the fly without relying on templates, thus minimising memory consumption. It exploits a fully Bayesian parameter space sampling, which allows for the inference of parameter posteriors and thereby facilitates the study of the correlations between the free parameters and the other physical quantities that can be derived from modelling. The application programming interface (API) and functions of GalaPy are under continuous development, with planned extensions in the near future. In this first work, we introduce the project and showcase the photometric SED fitting tools already available to users. GalaPy is available on the Python Package Index (PyPI) and comes with extensive online documentation and tutorials.

INTEGER LINEAR PROGRAMMING MODEL FOR AGGREGATE PRODUCTION PLANNING, APPLICATION OF LEARNING CURVES, AND HYPOTHESIS TESTING

ABSTRACT: Efficient production management and business administration are essential to maintain competitiveness in a business environment in constant change and complexity; the optimization of production systems becomes imperative to minimize costs and maximize operational efficiency. In this context, the implementation of advanced integer linear programming techniques emerges as a solution for aggregate production planning, based on the establishment of a uniform flow of processes to contribute to improving the efficiency of the system and reducing associated cost overruns. This article presents the analysis of the use of integer linear programming for aggregate production planning, applied to the production process of concrete blocks and concrete for structural masonry in the company Blocks del Sinú SAS in the department of Córdoba - Colombia. An optimization model is proposed that satisfies the forecasted demand through adjustments to the levels of production, labor, inventories, contracting and raw materials. The results show that with the standardization of the production process and work methods to minimize the costs of the production plan and meet the demand requirements in accordance with the company's capacity, demand will strictly occur within the planning horizon. , which implies that there will be no shortage of raw materials. Keywords: Aggregate planning, integer linear programming, production.

The role of awareness in implicit and explicit knowledge

Abstract This study investigates the initial incidental acquisition of two L2 morphosyntactic rules and their immediate usage in production. Using a miniature artificial language paradigm, multiple exposure sessions, realistic exposure, non-salient linguistic features, as well as multiple outcome measures, we demonstrate that adult learners can learn animacy with low levels of awareness, but not case. Forty adult native speakers of English participated in the experiment. Participants were exposed to audio sentences in the artificial language paired with pictures on the computer screen for three sessions. Knowledge of animacy and case was measured with production and grammaticality judgment tests. Results demonstrated that concrete, contiguous and easily trackable L2 properties that lend themselves to distributional learning, such as animacy marking, can benefit from incidental exposure. However, more abstract L2 properties, like the morphological paradigm of case, seem not to be learnable by incidental means, and opportunities for explicit learning must be provided.

Postmodernism Paradigm and its View on the Existence of Language

Objective: The emergence of postmodernism as a continuation and correction of the shortcomings of modernism is expected to provide new alternatives and complement the repertoire of human thinking, especially about the existence of language and culture. Although, in principle, all paradigms of thinking have their own advantages and disadvantages. This paper aims to examine the issues surrounding the postmodernism paradigm, which is focused on two main things, namely: the concept and basic principles of the paradigm and the view of the postmodern paradigm in relation to the existence of language phenomena. Method: Methodologically, this article is based on a literature study, which is conducted by identifying various theories related to postmodernism, to answer the problems that have been raised. Results and Discussion: From the results of this study, the following conclusions can be drawn. Firstly, the postmodernism paradigm is an approach to philosophy, art and culture that emerged as a response to the ideas and values of modernism that were dominant in the 19th and early 20th centuries. Postmodernism rejects the idea that there is a single narrative or truth that can explain the world, and instead, emphasizes the diversity, complexity and relative nature of everything. Second, in the context of its view on language, postmodernism offers several perspectives, among which the key ones are openness to the plurality of languages, the destruction of the concept of binaries and oppositions, the importance of meta-narrative, and intertextuality. Postmodernism is present to provide an alternative to new ways of thinking in knowledge, especially by prioritizing the principle of respecting differences in plural particularities, as a counter to the thesis of modernism which believes in the importance of the principle of uniformity and universality. Research Implications: Studying the postmodernist paradigm and its views on language can open insight into the complexity and dynamics of language in various contexts. This influences how we understand the world, interact with others, and organize our knowledge. Originality/Value: The value and originality of the study of postmodernism and language paradigms lies in its ability to raise new questions, provoke critical thinking, and open space for new developments in various disciplines and cultural practices.

Design of metamaterial-based heat manipulators using isogeometric level-set topology optimization

We exploit level-set topology optimization to find the optimal material distribution for metamaterial-based heat manipulators. The level-set function, geometry, and solution field are parameterized using the Non-Uniform Rational B-Spline (NURBS) basis functions to take advantage of easy control of smoothness and continuity. In addition, NURBS approximations can produce conic geometries exactly and provide higher efficiency for higher-order elements. The values of the level-set function at the control points (called expansion coefficients) are utilized as design variables. For optimization, we use an advanced mathematical programming technique, Sequential Quadratic Programming. Taking into account a large number of design variables and the small number of constraints associated with our optimization problem, the adjoint method is utilized to calculate the required sensitivities with respect to the design variables. The efficiency and robustness of the proposed method are demonstrated by solving three numerical examples. We have also shown that the current method can handle different geometries and types of objective functions. In addition, regularization techniques such as Tikhonov regularization and volume regularization have been explored to reduce unnecessary complexity and increase the manufacturability of optimized topologies.

Linguistic Models of Mass Media Genres` Stylistic Diffusion in the Communicative Space of Ukraine and Bulgaria

Research attention is focused on fundamental changes in techniques and methods of informing , which activate the communicative capabilities of language and give rise to new genres, forms and formats of interpersonal communication in various spheres and discourses. It actualizes the research problem of the diffuse stylistic nature of mass media genres, argued by the processes of assimilation of public communication`s spheres. The author’s argumentation is based on the vectors of the dynamics of the literary language`s evolutionary potential, that is focused on the format and tasks of social communication. Predictably, the architectonic heterogeneity and polyfunctionality of the language of media texts explain the syncretic nature of the genres. And also the tendency to their constant modification and transformation regarding the structure, meanings and communicative valence of language units. The article interprets models of updating of the functional and stylistic paradigm of modern literary languages in their genre projection and perspective, which do not depend on the time and space of culture. To prove this thesis, the texts of the Ukrainian and Bulgarian media space in the genre of posts in social networks were chosen as the object of analysis. The main research aim is to determine the typicality / atypicality of stylistic diffusion in the genre paradigm of Ukrainian and Bulgarian media. The attention is paid to the bloggers and companies that are well- known in Ukraine and Bulgaria as influencers who make professional activities in the fields of health, beauty, sport, etc., and really model the current mass language consciousness. The research base is formed by texts that were published in the social networks Instagram, Facebook in 2023 – 2024. The functional and stylistic methodology of the mentioned material`s interpretation allows in a comparative discourse to prove the typicality of communicative processes that are resulted in the stylistic diffusion of modern mass media genres.

Analysis of hyperbolised phraseology and its cognitive aspect in media literacy

Relevance. The relevance of this study is motivated by a broad public interest in modern media communications, including the use of linguistic means to implement speech strategies and communicative tactics, maximising the impact on the selected audience, and the limited understanding of the functionality of hyperbole-based phraseological expressions in media discourse. Purpose. The purpose of the presented investigation is to comprehend the leading mechanisms of constructing a language paradigm in cognitive terms, linguistic analysis of stable units of speech as means of emotive-evaluation in text, the definition of the main lexical and semantic means, author's intentions and narrativity in media texts. Methodology. The main method employed is a theoretical approach to the study of media literacy in contemporary society, constructing linguistic templates for the perception of reality and its representation in a cognitive manner. Results. This investigation reveals the basic mechanisms of realization of communicative strategies in the media sphere by means of attracting a wide arsenal of linguistic resources, focusing on the functioning of phraseological units built on hyperbole by the example of the national language code (English and Kazakh). Conclusions. The materials presented in this study will contribute to further in-depth study of the frequency of use of such idioms, the functionality of texts using them and the ethical implementation of communication between author and recipient, to analyse the linguistic resources that can and cannot be used in media contexts, to structure the media field depending on the style and targeting, to establish basic rules and criteria to determine the media literacy of speakers of the national speech code. Keywords: phraseological unit; media communication; critical thinking; information space; phraseme; media field

Intraoperative application and early experience with novel high-resolution, high-channel-count thin-film electrodes for human microelectrocorticography.

The study objective was to evaluate intraoperative experience with newly developed high-spatial-resolution microelectrode grids composed of poly(3,4-ethylenedioxythiophene) with polystyrene sulfonate (PEDOT:PSS), and those composed of platinum nanorods (PtNRs). A cohort of patients who underwent craniotomy for pathological tissue resection and who had high-spatial-resolution microelectrode grids placed intraoperatively were evaluated. Patient demographic and baseline clinical variables as well as relevant microelectrode grid characteristic data were collected. The primary and secondary outcome measures of interest were successful microelectrode grid utilization with usable resting-state or task-related data, and grid-related adverse intraoperative events and/or grid dysfunction. Included in the analysis were 89 cases of patients who underwent a craniotomy for resection of neoplasms (n = 58) or epileptogenic tissue (n = 31). These cases accounted for 94 grids: 58 PEDOT:PSS and 36 PtNR grids. Of these 94 grids, 86 were functional and used successfully to obtain cortical recordings from 82 patients. The mean cortical grid recording duration was 15.3 ± 1.15 minutes. Most recordings in patients were obtained during experimental tasks (n = 52, 58.4%), involving language and sensorimotor testing paradigms, or were obtained passively during resting state (n = 32, 36.0%). There were no intraoperative adverse events related to grid placement. However, there were instances of PtNR grid dysfunction (n = 8) related to damage incurred by suboptimal preoperative sterilization (n = 7) and improper handling (n = 1); intraoperative recordings were not performed. Vaporized peroxide sterilization was the most optimal sterilization method for PtNR grids, providing a significantly greater number of usable channels poststerilization than did steam-based sterilization techniques (median 905.0 [IQR 650.8-935.5] vs 356.0 [IQR 18.0-597.8], p = 0.0031). High-spatial-resolution microelectrode grids can be readily incorporated into appropriately selected craniotomy cases for clinical and research purposes. Grids are reliable when preoperative handling and sterilization considerations are accounted for. Future investigations should compare the diagnostic utility of these high-resolution grids to commercially available counterparts and assess whether diagnostic discrepancies relate to clinical outcomes.

Computational strategy for aphasia support

Aphasia, a language disorder resulting from brain lesions, impacts communication abilities, and is commonly diagnosed through formal tests assessing speech fluency, comprehension, naming, and repetition abilities. These tests aid in devising treatment plans and evaluating recovery potential. Technological advances have enabled the development of devices and techniques for recording brain activity. Despite their potential, the high cost, device robustness, and complexity often limit their application in rehabilitation centers outside hospitals. In this study, we propose a computational strategy that uses electroencephalography devices to support aphasia rehabilitation therapies. The research was conducted with aphasic participants undergoing rehabilitation at the Center for Prevention and Rehabilitation of People with Disabilities within the Unified Health System in Bahia-Brazil. Preliminary results obtained from the silent word generation task, as outlined in the adult language paradigm by the American Society for Functional Neuroradiology, suggest that increased electrical activation in the right hemisphere may indicate language migration to the non-dominant hemisphere, potentially leading to improved recovery.