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Resilient cybersecurity in smart grid ICS communication using BLAKE3-driven dynamic key rotation and intrusion detection
Abstract The increasing convergence of Industrial Control Systems (ICS) with critical infrastructure, such as smart grids, has increased their exposure to advanced cyber threats, demanding advanced security frameworks to maintain security and operational integrity. This paper shows an innovative cybersecurity approach for ICS, using the IEC 60870-5-104 dataset, that combines machine learning, cryptographic resilience, and forensic analysis to predict and neutralize various attack vectors–containing false data injections, denial-of-service assaults, and covert rogue infiltrations. The approach uses a hybrid ecosystem combining synthetic data augmentation via the Synthetic Minority Oversampling Technique, a Random Forest Classifier with an accuracy of 1.00, and real-time anomaly detection through an Isolation Forest. Various components in this study are individual components and function independently. This framework is strengthened by a dynamic AES-256-CBC encryption technique that achieves a cryptographic complexity above $$2^{384}$$ against ciphertext-only attacks using BLAKE3-derived keys verified by cryptanalytic research. Various security tests, such as the Chi-square test, Shannon entropy test, pattern detection test, and other tests have been evaluated to validate the strength of the model. Additionally, the proposed system was evaluated against evolving and zero-day attack patterns through real-time streaming simulations using an unsupervised Isolation Forest model. A Bayesian-driven forensic methodology further enhances the strength by examining post-attack dynamics, exposing systemic vulnerabilities, and enabling precise attribution. With far-reaching effects on operational strength and national security, this study fills critical gaps in ICS security.
Artificial neural network based optimization of engine performance using domestic biomass as a clean fuel
Low carbon optimization for wind integrated power systems with carbon capture and energy storage under carbon pricing
Coexistence of Metallocene Cations and Anions
Correction: Global motion coherent deficits in individuals with autism spectrum disorder and their family members are associated with retinal function
<i>De Novo</i> Chemoenzymatic Assembly of Complex Sulfated <i>N</i>-Glycans to Comprehensively Profile the Ligand Binding of Human Siglecs
Evaluation of a DNA methylation-based measure of chronic inflammation in two generations of adults in metropolitan Cebu, Philippines
Synthesis of Diverse Glycosyl Bicyclo[1.1.1]pentanes Enabled by Electrochemical Functionalization of [1.1.1]Propellane
Investigation of argon plasma treatment on the structural, surface morphology and electrical properties of bovine cortical bone
Abstract In this study, bovine cortical bone was investigated under plasma treatment process to investigate the potential for improvements in their structural characteristics. The bone specimens were treatment with low pressure argon cold plasma at different treatment times; 15, 30, and 45 min. Various techniques such as X-ray diffraction, scanning electron microscopy, surface roughness testing and automatic LCR Bridge were utilized to study the plasma-induced modifications on the structural and dielectric properties of the bone. SEM images revealed the elimination of some outer atoms from the bone surface during the 30-minute plasma ablation process, leading to more noticeable grain size of hydroxyapatite. XRD measurements confirmed the obtained results as mentoring the changes in crystallite size and strain parameters. As the treatment time approached 45 min, crystallite size increased, along with surface roughness parameters and relaxation time. These findings contribute to a better understanding of the microstructural and morphological changes occurring on the bone surface during cold argon plasma treatment.
Metacontrol is reflected in phasic but not tonic cognitive control dynamics
Abstract Metacontrol, the regulation of cognitive strategies to balance persistence and flexibility, has been theorized to operate either as a tonic state, maintaining a consistent neural bias, or as a phasic mechanism, dynamically adjusting to situational demands. This study tested these scenarios by examining the relationship between metacontrol biases and changes in the aperiodic exponent of EEG activity. Behavioral results replicated well-established effects. Neural analyses revealed significant post-stimulus increases in the aperiodic exponent during incongruent trials, reflecting enhanced persistence in response to high-conflict conditions. Crucially, the absence of pre-stimulus effects supports the phasic hypothesis, suggesting metacontrol biases emerge dynamically rather than maintaining a stable tonic state. Correlational analyses showed task-specific and transient metacontrol biases. Persistence aligned with high-conflict demands in incongruent trials, while flexibility remained general across conditions. The lack of cross-task correlations between creativity and Flanker tasks further supports the phasic view, where biases adapt to immediate task requirements rather than representing stable traits. These findings align with reactive control theories, emphasizing transient, context-dependent neural adjustments. This study provides evidence for a phasic account of metacontrol, where cognitive control states dynamically shift to meet task-specific demands. This adaptive flexibility underscores the importance of real-time adjustments in human cognition.
Tandem Catalysis Enables the Hydrocarboxylation of γ-Valerolactone with CO<sub>2</sub> and H<sub>2</sub> to Produce Adipic Acid
Patient needs in the context of gynecologic oncology and breast cancer: a validation study
Abstract Medical advancements and therapeutic innovations are progressing rapidly, necessitating corresponding adaptations in the delivery of patient-centered care. This study explores the needs of women diagnosed with gynecologic and breast cancers, using the frameworks of the National Academy of Medicine and the Picker Institute as reflective lenses. We conducted a qualitative, single-center study employing grounded theory methodology. Semi-structured interviews were carried out with 20 patients undergoing treatment for gynecologic malignancies and breast cancer at a university medical center. Interviews covered multiple phases of illness, including treatment initiation, adaptation, abstention, and future-oriented decisions. Data were analyzed inductively using constant comparative methods. Findings largely affirmed the relevance of the eight established domains of patient-centered care - personal values, clear information and education, emotional support, involvement of family and friends, physical comfort, coordinated care, continuity, and access to treatment. Three additional insights emerged: needs vary according to illness phase and tend to taper over time; they are grounded in ethical dimensions, including social identity, epistemic agency, and moral distress; and they are interdependent, requiring holistic rather than isolated responses. These results highlight that effective patient-centered care must account not only for the content of care but also for its timing, context and ethical significance, warranting integration into standard oncological practice.
Cage Balancing Enhances Optoelectronic and Lasing Performance in Stable Quasi-2D Tin Iodide Perovskites
A computational model elucidates the effects of oncogene-induced expression alterations on the energy metabolism of neuroblastoma
Abstract Alterations in energy metabolism are recognized as a hallmark of cancer. Experimental evidence shows that oncogenes play a key role in the reprogramming of metabolism. In neuroblastoma, the oncogene MYCN, a main risk factor of poor prognosis, has been demonstrated to lead to expression changes in numerous glycolytic enzymes. It is not clear whether all these targets are required and how they jointly shape metabolic responses. Here we use a computational modeling approach to dissect the effects of MYCN targets on the pathway individually and in combination. We develop the first mathematical model of the energy metabolism in neuroblastoma cells based on our published experimental data. The analysis shows that overall, MYCN overexpression leads to Warburg-like flux alterations. However, individual MYCN targets can have opposing and sometimes unexpected effects. Interestingly, not all of them contribute to notable flux alterations, at least with regard to glycolysis. Moreover, our model predicts a potential bistability of cellular metabolism with a low-flux state likely representing a non-proliferative state. Overall, our study emphasizes that perturbations such as expression changes should be analysed in the context of realistic pathway models, in which specific interactions and complex regulations are captured.