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Early and accurate identification of heart conditions from electrocardiogram (ECG) signals is particularly important for ongoing patient health monitoring, yet classical deep learning frameworks have …

Early and accurate identification of heart conditions from electrocardiogram (ECG) signals is particularly important for ongoing patient health monitoring, yet classical deep learning frameworks have been inadequate at achieving high accuracy and low latency under noisy, real-time conditions. This work focuses on developing a quantum-accelerated cardiac ECG (electrocardiogram) analysis. The study introduces a novel hybrid quantum–classical framework capable of simultaneously performing ECG denoising, feature embedding, and arrhythmia classification with reduced latency and improved robustness under noisy real-time conditions. The one introduced in the article is the hybrid quantum-classical architecture, including Quantum Variational ECG Embedding (QVEE) for high-dimensional morphological representation, Quantum Enhanced Denoising Module (QEDM) for noise suppression and signal distortion, and hybrid quantum classification for arrhythmia recognition. Experiments were conducted on the MIT-BIH Arrhythmia Database, and a corpus with noise augmentation showed that the proposed framework was found to be 99.4% correct with an F1 score of 0.97 and reduced the inference latency by 23.7% compared to state-of-the-art CNN-LSTM, Transformer-based models, and showed higher robustness under the condition of low signal-to-noise ratios. The results show that quantum embeddings tend to improve ECG feature separability and that quantum denoising helps preserve clinically relevant waveform structure (i.e., structure detection), particularly for rare arrhythmias. The proposed framework is a promising approach for establishing real-time quantum-assisted monitoring of the human heart, enabling more reliable early diagnosis in wearable and clinical environments.

This repository contains the COMSOL Multiphysics 6.3 finite-element model files and raw parameter-sweep simulation outputs used to generate the results reported in the manuscript "Comparative Electrot…

This repository contains the COMSOL Multiphysics 6.3 finite-element model files and raw parameter-sweep simulation outputs used to generate the results reported in the manuscript "Comparative Electrothermal Analysis of Single and Small-Electrode Grid Configurations for HD-Inspired Peripheral Transcutaneous Neurostimulation" (submitted to Frontiers in Bioengineering and Biotechnology, Manuscript ID 1904885). The dataset compares a conventional single-electrode reference configuration against a series of HD-inspired small-electrode grid configurations (grid1 through grid16), evaluating current-density distribution and electrothermal (Joule heating) behavior under current-controlled pulsed stimulation, across the complete 128-combination current-amplitude/pulse-width/frequency parameter sweep for all seventeen configurations. In addition to this primary series, the dataset includes: (i) an area-matched control series (electrode radius increased to hold total active area constant while electrode count varies), (ii) a mesh-convergence study across five refinement levels for representative configurations, and (iii) alternative electrode fill-pattern variants used to isolate the effect of spatial arrangement independent of electrode count and total active area. See the included README.md for a full description of the folder structure and how each file maps to the manuscript's figures and tables.

This paper on Moroccan MSMEs makes an in-depth examination of CC for its impact and enabling of the digital transformation journeys. The rapidly changing environment of technological innovation and di…

This paper on Moroccan MSMEs makes an in-depth examination of CC for its impact and enabling of the digital transformation journeys. The rapidly changing environment of technological innovation and disruption that many firms face presents a complicated and dual challenge; while there are also the increased pressures and demands that will be encountered with this digitalization, organizations cannot escape the adaptation to forces which may collaterally constrain them through pre-existing inherited structures, routines or ways in which they have been performing their operations traditionally. Consequently, the current analysis investigates whether a range of internal cognitive and organizational mechanisms (e.g. knowledge sharing, collective learning, organizational adaptability, and proactive orientations toward change) are indeed statistically linked to higher levels of digital maturity (and hence also sophistication), and consequently can be said to induce such improvement in performance.A sound mixed-method research design was deliberately staunchly embraced to provide answers to the above research objectives. Quantitative data were carefully collected from the diverse sample of 150 Moroccan SMEs from different industries and sectors, ensuring a broad and representative dataset. In concert with this, qualitative data were collected through semi-structured in-depth interviews with managerial profiles who play a crucial role in and are accountable for leading their organizations digital transformation. These interviews yielded rich contextual and often subtle insights into the processes. Quantitative analyses were conducted in the statistical software package SPSS (version 28.0) to conduct robust statistical testing and confirmation of hypothesized relationships using these data.The empirical results tangibly demonstrate the positive and statistically significant connection between overall intelligence of firms quantified as cognitive capital and level of digital maturity achieved by these firms. In particular, organizations are more likely to implement and realize benefits from complex digital solutions such as enterprise resource planning (ERP), customer relationship management (CRM), integration of different business applications in the cloud or on-premise if they display heavier, deeper learning-related organizational capabilities and more intensified knowledge exchange activities. These results provide strong evidence that the extent to which smaller firms in Morocco successfully undertake their digital transformation is not solely dependent on investing in those new technologies, but rather it is highly reliant on an organizational environment conducive for continuous learning, coordination and ability to change effectively.This study is an important contribution to the literature based on objective preference linkage between cognitive capital mechanisms and digital maturity, especially establishing this link in the concentration of an emerging-economy setting. It also emphasizes the enduring role of knowledge management as a core organizational logic, both in enabling continual transformation and ensuring firm viability and sustainability in dynamic but often unstable environmental contexts.

A pesquisa investigou a aderência do Plano Diretor de Tecnologia da Informação (PDTI) 2016-2019 da Universidade Federal de Viçosa (UFV) à Estratégia de Governa…

A pesquisa investigou a aderência do Plano Diretor de Tecnologia da Informação (PDTI) 2016-2019 da Universidade Federal de Viçosa (UFV) à Estratégia de Governança Digital (EGD) do Governo Federal, utilizando como parâmetro os resultados do Índice de Governança em TI (iGovTI) do Tribunal de Contas da União (TCU) nos anos de 2017 e 2018. O estudo concluiu que o PDTI da UFV não apresenta aderência efetiva à EGD 2016-2019. Embora a EGD seja citada formalmente como documento de referência, suas diretrizes, metas e princípios práticos não foram integrados no conteúdo do PDTI, o qual permaneceu alinhado aos preceitos da antiga Estratégia Geral de Tecnologia da Informação (EGTI 2011-2012)

Os pareceres emitidos pelas unidades de auditoria interna (AUDINS) das Instituições Federais de Ensino Superior (IFES) desempenham um papel fundamental na promoçã…

Os pareceres emitidos pelas unidades de auditoria interna (AUDINS) das Instituições Federais de Ensino Superior (IFES) desempenham um papel fundamental na promoção da governança pública, garantindo maior transparência, accountability eeficiência na gestão dos recursos institucionais. Os pareceres emitidos por essas unidades não apenas subsidiam o processo de deliberação dos conselhos universitários sobre a prestação de contas, mas também fornecem insumos fundamentais para os órgãos de controle externo e a sociedade. A negativa de opinião nesses pareceres pode indicar fragilidades estruturais e operacionais na governança das IFES, comprometendo a confiabilidade do processo de elaboração das demonstrações contábeis e financeiras. Adotando uma abordagem qualitativa edescritiva, a pesquisa utilizou procedimentos de análise documental e entrevistas semiestruturadas realizadas com chefes das AUDINS das IFES de Minas Gerais. Os resultados indicam que a frequente emissão de pareceres com negativa de opinião está associada a diversos fatores, tais como insuficiência de corpo técnico especializado na área contábil, deficiências no planejamento das atividades de auditoria, lacunas nos controles internos das instituições auditadas e a ausência de metodologias eficazes para avaliação do processo de elaboração dasdemonstrações contábeis. Ademais, identificou-se que a compreensão sobre os requisitos normativos e a padronização dos procedimentos de auditoria apresentam desafios significativos para as AUDINS. Observou-se, ainda, que a fragilidade daInstrução Normativa nº 05/2021, por ser considerada genérica e não fornecer informações necessárias detalhadas, contribui para a insegurança dos auditores no momento da emissão de pareceres. A pesquisa contribui para a literatura ao destacar as dificuldades enfrentadas pelas auditorias internas no cumprimento de sua função de controle e recomenda a implementação de iniciativas voltadas à capacitação contínua dos auditores, aprimoramento dos fluxos de trabalho, alocação adequada de recursos e revisão das normativas aplicáveis, visando à melhoria da qualidade dos pareceres emitidos.

Detecting malicious software in Internet of Things (IoT) datasets and environments remain a significant challenge for researchers striving to secure IoT networks. As the massive interconnection of Int…

Detecting malicious software in Internet of Things (IoT) datasets and environments remain a significant challenge for researchers striving to secure IoT networks. As the massive interconnection of Internet devices causes, most previous research has explored deep learning approaches, particularly the LSTM model, in detecting malware within operation codes (Opcodes) for ARM-based IoT applications, owing to its strong classification capabilities. Despite the advantages of using opcode features for detecting malicious software, the length of the opcode sequence poses a major challenge for deep learning methods such as the LSTM algorithm. Long opcode sequences can lead to information loss and increased computational burden, which may result in the vanishing gradient problem in the LSTM algorithm. To address this issue. This paper proposes a tokenization-based truncating and padding method to solve this problem. It shortens the length of the opcode sequence while keeping the classification performance the same. This approach extracts a subset of opcode sequences based on uniqueness, significantly reducing the length and size of the sequence while preserving the quality of the dataset. The method was evaluated on three IoT datasets from the Linux system and one dataset from the Windows system. The findings show that, for all datasets, the suggested approach performs better than current approaches in terms of accuracy and time. 

Introdução: A garantia de uma educação inclusiva e equitativa desempenha um papel crucial no desenvolvimento de crianças com deficiência na primeira infâ…

Introdução: A garantia de uma educação inclusiva e equitativa desempenha um papel crucial no desenvolvimento de crianças com deficiência na primeira infância. Desde os marcos legais recentes, o Atendimento Educacional Especializado tem sido essencial para assegurar a aprendizagem e a socialização, destacando a importância de uma abordagem interseccional que considere marcadores sociais como gênero e classe na formulação dessas práticas. Objetivos: Este estudo tem como principal objetivo analisar e compreender a relevância do contexto socioeconômico familiar nas barreiras de acesso de meninas com autismo ao atendimento especializado. Além disso, busca identificar padrões de exclusão e vulnerabilidades institucionais que dificultam a identificação precoce do transtorno e a efetivação do suporte pedagógico nessa etapa escolar. Metodologia: A metodologia adotada consiste em uma revisão abrangente de bibliografia relacionada à educação especial, gênero e desigualdade social. Utilizaram-se plataformas renomadas como PUBMED e SCIELO, empregando palavras-chave específicas como "educação infantil", "transtorno do espectro autista", e "atendimento educacional especializado". A análise focou na identificação de obstáculos socioeconômicos e nas práticas recomendadas por especialistas. Resultados: Os resultados revelaram que o acesso ao suporte especializado para meninas com transtorno do espectro autista na educação infantil requer uma abordagem intersetorial e sensível à renda. A clareza no diagnóstico, a escassez de recursos públicos e as barreiras geográficas são determinantes para a exclusão desse grupo. Além disso, observou-se uma subnotificação de casos, indicando a necessidade de capacitação docente conforme a realidade local. Conclusão: Conclui-se que a superação das barreiras de acesso ao atendimento especializado para meninas autistas em situação de vulnerabilidade é uma prática essencial. A padronização de políticas de busca ativa, aliada à adaptação às características financeiras de cada família, é crucial para a eficácia da equidade escolar. Este estudo contribui para a compreensão dos impactos da desigualdade, promovendo uma reflexão mais clara e impactante no contexto da inclusão.

The blistering development of the Internet of Medical Things (IoMT) and telemedicine platforms has radically changed the healthcare delivery, providing the opportunity to conduct remote monitoring, di…

The blistering development of the Internet of Medical Things (IoMT) and telemedicine platforms has radically changed the healthcare delivery, providing the opportunity to conduct remote monitoring, diagnose in real-time, and manage electronic health records. Nevertheless, these developments present the serious weaknesses in data protection, especially when it comes to ciphertext integrity, unauthorized access, and the potential threat posed by quantum computing. In this paper, a single framework has been provided to consider the short-term and long-term cryptographic issues in healthcare data sharing. As a follow-up of a blockchain-mimicking Proxy Re-Encryption (PRE) protocol and an extensive post-quantum cryptographic (PQC) benchmarking analysis, we present a single security architecture of IoMT settings. In the scheme based on PRE, identity hash binding is also introduced when creating keys to ensure that there can be verifiable connections between the identity of the user and the public keys to improve accountability in data sharing between the Data Owners and the Data Users. The transactions of blockchain are used to create a pairing-function ciphertext verification scheme that is used to effectively stop the manipulation of encrypted data stored on the cloud server. Accumulators that are managed by smart contracts make it easy to manage user identities as well as perform queries efficiently. At the same time, despite the fact that traditional encryption protocols like RSA and ECC are becoming obsolete when quantum adversaries use the Shor algorithm, the framework compares four PQC algorithms that have been standardized by NIST Kyber, Dilithium, Falcon, and SPHINCS+. The performance benchmarking indicates that Falcon has better encryption efficiency of 17.16 ms with optimized storage capacity of 2.05 MB hence it can be found to be highly suitable in the telemedicine applications that require low latency whereas Kyber has a balance of speed and low computational overhead of 35.98. One-way statistical analysis based on ANOVA helps prove that performance differences are statistically significant between PQC algorithms. The evaluation of the healthcare institutional preparedness indicates that technical expertise and infrastructure capacity is a significant predictor of the success of PQC adoption compared to budget allocation, with high-preparedness institutions registering a score of 6.97/10 on both dimensions. The combined scheme entails a computational efficiency improvement of the currently existing methods and will cut down on the time of encryption, re-encryption, decryption, and re-decryption by around 23.8, 71.4, 48 and 15.3 percent respectively and yet will not compromise on the IND-ID-CPA security with the DBDH-assumption. All these findings support a gradual hybrid cryptography migration plan, which includes the introduction of quantum-resistant algorithms into the current IoMT systems without interruption of care. [1,2]

A pesquisa conclui que, apesar das limitações e da parca presença de financiamento dos governos federal e estadual — agravada pela tendência de concentraç&atild…

A pesquisa conclui que, apesar das limitações e da parca presença de financiamento dos governos federal e estadual — agravada pela tendência de concentração e mercadorização da produção cultural decorrente do modelo de incentivo fiscal da Lei Rouanet —, o município de Carmo do Paranaíba apresentou mobilização e iniciativa própria na promoção do setor cultural. A criação e a atuação do Conselho Municipal do Patrimônio Cultural (COMPAC) e do Fundo de Proteção do Patrimônio Cultural do Município (FUMPAC) foram fundamentais para captar recursos estaduais (como o ICMS Patrimônio Cultural) e viabilizar ações permanentes e temporárias de preservação do patrimônio material e imaterial local. Entretanto, observou-se que as políticas culturais municipais ainda carecem de maior estruturação orçamentária e previsibilidade nos instrumentos de planejamento (PPA, LDO e LOA) para evitar a descontinuidade de projetos. Os gestores entrevistados demonstraram uma visão de cultura estreitamente vinculada à educação, à identidade e à formação cidadã. Para garantir a sustentabilidade das ações, o estudo sugere a ampliação dos recursos orçamentários do município para a cultura, o fortalecimento de parcerias com a sociedade civil, a elaboração de cartilhas de educação patrimonial e projetos de longo prazo, tais como a reativação da Casa da Cultura e a criação de um Museu Municipal.

Athena: Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Introduction This is the official codebase for the paper "Enhancing Code Understandi…

Athena: Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Introduction This is the official codebase for the paper "Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs". In this work, We leverage neural code models including CodeBERT, UniXCoder, and GraphCodeBERT, prominent Transformer-based code models, for initial method embedding extraction. These pre-trained neural code models are fine-tuned on code search to learn richer representations that are aware of underlying code intent and potentially transferring the additional knowledge learnt from code search to IA. To integrate the global dependence information into local code semantics, the initial method embeddings are further enhanced using an embedding propagation strategy inspired by graph convolutional networks (GCN) [Kipf and Welling 2016] based on the constructed dependence graphs. Dependency CUDA 11.0 python 3.7 pytorch 1.7.1 torchvision 0.8.2 Installation git clone https://github.com/yanyanfu/Athena.git cd Athena pip install -r requirements.txt   Evaluation Benchmark To evaluate Athena for the task of impact analysis, we created a large-scale benchmark, called Alexandria, that leverages an existing dataset of fine-grained, manually untangled commit information from bug-fixes. The benchmark consists of 910 commits across 25 open-source Java projects, which we use to construct 4,405 IA tasks. The benchmark is available at dataset/alexandria.csv. Reproduce Results python main_multi.py \ --project_path=./projects \ --pretrained_model_name=microsoft/graphcodebert-base \ --finetuned_model_path=./finetuned_models/graphcodebert.bin \ --lang=java \ --output_dir=./athena_reproduction_package/results/graphcodebert \   Fine-tuned models The code search task is used as the proxy for the impact analysis. Specifically, we fine-tune the pre-trained models for code search based on the dataset of CodeSearchNet Java split. The fine-tuned models are available at https://drive.google.com/drive/folders/1b7xkAA5XWSY2io6smAk-c7PeTdxt5I5a?usp=drive_link.