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Optimized feature selection and zero-parameter channel attention BiLSTM for RPL-attack classification in IoT networks
The increasing adoption of Internet of Things (IoT) devices introduces significant security challenges, particularly in networks based on the Routing Protocol for Low-Power and Lossy Networks (RPL), where resource constraints limit the effectiveness of conventional security solutions. This work presents an optimized deep learning framework for detecting and classifying RPL-based routing attacks. The framework integrates Chaotic Pied Kingfisher Optimization (Ch-PKO) for feature selection with a Zero-parameter Channel Attention Bidirectional Long Short-Term Memory (ZCAtt-BiLSTM) model for classification. Data preprocessing includes cleaning, one-hot encoding, and Pareto scaling to improve data quality and learning stability. The approach is evaluated on the IoT-RPL dataset, covering Blackhole, Flooding, DODAG Version Number, and Decreased Rank attacks. Experimental results show strong performance, achieving 99.305% accuracy, 98.57% F1-score, 0.61% false discovery rate, and 97.949% MCC. Comparative analysis indicates improved performance over baseline models. However, the evaluation is based on simulated data, and the training process introduces additional computational cost, which may affect real-time deployment.
Electroporation of pLI50 harboring qacA or qacB increases chlorhexidine minimal inhibitory concentrations in transformed Staphylococcus aureus strain RN4220
Thyroid V40 as a potential early predictor of hypothyroidism following hypofractionated locoregional breast radiotherapy
Radiotherapy (RT) is used quite often among breast cancer patients, and because these patients now live longer than they used to, long-term treatment-related adverse effects, such as hypothyroidism, are becoming increasingly relevant. Radiation-induced hypothyroidism is a late side effect of radiation to the thyroid gland, which could develop months to years after radiotherapy. However, there are insufficient data on hypothyroidism in patients with breast cancer who receive locoregional RT, which usually affects a portion of the thyroid gland. In this prospective study, we aimed to evaluate the association between radiation dose to the thyroid gland and early thyroid dysfunction in breast cancer patients treated with hypofractionated locoregional radiotherapy, and to establish potential planning objectives that could help in sparing the thyroid gland. Our study included 109 women who received 3-D conformal locoregional breast radiotherapy. These patients had normal thyroid function prior to start of radiotherapy. Patients had follow-up thyroid function tests 6 months after finishing radiotherapy. Based on dose volume histograms (DVH), the percentages of the thyroid volume, and ipsilateral thyroid lobe, receiving 5, 10, 15, 20, 25, 30, 35, and 40 Gy (V5, V10, V15, V20, V25, V30, V35, and V40 respectively), in addition to the mean and maximum thyroid doses, were estimated. Follow-up assessment of thyroid function and statistical analysis unveiled incidence of radiotherapy induced hypothyroidism to be 8.3%. Possible risk factors included high maximum radiation dose and V40 to the thyroid gland and the ipsilateral thyroid lobe, as well as high mean dose and smaller volume of the ipsilateral thyroid lobe. The likelihood of hypothyroidism was significantly increased with V40 of >5% of the thyroid gland, and V40 of >11% of the ipsilateral thyroid lobe. Further study is recommended for larger populations and longer follow-up periods.
Bisphosphane‐Stabilized Borylenes: Unlocking Borylene Transfer Reactivities
ABSTRACT The development of borylene‐transfer reactions—a powerful yet underdeveloped strategy for the efficient construction of boron‐containing compounds—has been hindered by the scarcity of reliable reagents. A fundamental challenge lies in balancing the high ambiphilic reactivity required for transfer with the requisite molecular stability. Herein, we report the synthesis of a series of bisphosphane‐stabilized borylenes and disclose their exceptional borylene‐transfer capabilities. The target borylenes ( 3 ) were prepared via facile deprotonation of the corresponding bisphosphane‐coordinated hydroboronium precursors using KHMDS (potassium bis(trimethylsilyl)amide). Notably, borylene 3a undergoes formal B─H bond insertion with hydroboranes to yield diborane (6) derivatives. Furthermore, 3a facilitates unprecedented borylene transfer to polar π systems, including benzaldehyde and chalcone, providing efficient access to three‐membered oxaboriranes and boriranes. Experimental and computational studies reveal that the labile phosphorus–boron (P–B) coordination is pivotal in maintaining the high borylene‐transfer capability of 3a . These preliminary results set the stage for the use of stable hydroboronium compounds as practical borylene‐transfer reagent precursors in synthetic chemistry.
When BMI exceeds 50: what ten years of follow-up reveal after bariatric surgery (BARI-10-POL study)
Hybrid quantum-classical neural networks for real-time fault detection in power systems
As modern power systems continue to be integrated with renewable energy sources, the ability to detect faults in these systems quickly and accurately is becoming more sophisticated. A Hybrid Quantum Classical Neural Network (HQCNN) model is presented in this paper that addresses the real-time fault detection challenge in transmission systems. A classical feature extractor, in this case a 1D CNN, and a quantum circuit are combined by the model, which aids in the classification of faults. Evaluations were conducted on simulated IEEE 14 and 39-bus system and on approximately 800 real PMU fault events. An accuracy of 96.43% on simulated data and 94.74% on real PMU data was achieved by the model, outperforming traditional deep learning models and maintaining detection times under 3 milliseconds. Various kind of fault like SDL (single line to ground), DL (double line), TP (three phase), and high-impedance faults, were correctly classified by the system. In a study in which elements of the model were removed, the quantum layer was found to be very important for improved performance. Issues like hardware limits and quantum noise were also looked at. As for the future, larger PMD data sets will be worked on, model explainability will be improved with hybrid XAI methods, and smaller HQCNN models will be developed for use in substation edge devices.
CrayStack: a simplified crayfish optimization driven stacking ensemble for prediction of machining quality characteristics under data scarcity
Visual and textual cues in online presentations of natural foods are associated with taste inference and cognitive engagement
Digital environments have become important contexts in which consumers form sensory expectations and evaluate food quality prior to consumption. Drawing on the elaboration likelihood model and attribution theory, this study develops a theoretically grounded process model to explain how visual and textual cues in online presentations of natural foods shape food-related cognition. Specifically, we propose that perceived naturalness serves as an initial perceptual input that can trigger cognitive engagement through multiple mechanisms: directly, via credibility as a validation mechanism, via taste inference as an experiential simulation, and through a sequential chain in which credibility enables taste inference that subsequently sustains elaboration. A 2 (platform type: content-oriented vs. transaction-oriented) × 2 (image scene: lifestyle-oriented vs. nature-oriented) × 2 (text framing: consumption-oriented vs. production-oriented) between-subjects experiment (N = 320) was conducted. Partial least squares structural equation modeling was employed to test direct and indirect effects; multi-group analysis examined boundary conditions across experimental contexts; and necessary condition analysis identified minimum required levels of predictors for high engagement states. The results indicate that perceived naturalness has a significant direct effect on cognitive engagement, as well as indirect effects through credibility and taste inference independently and in sequence. The indirect pathway is more pronounced in content-oriented environments, particularly when nature-oriented images and consumption-oriented text are used. Taste inference emerged as the strongest necessary condition for high cognitive engagement, followed by credibility; perceived naturalness showed a weaker but significant necessity effect. These findings demonstrate how visual and textual cues jointly guide anticipatory sensory processing and cognitive engagement in digital food contexts, offering both theoretical contributions to cue-based processing research and practical implications for the design of online presentations of natural foods.
Reprogramming the Fate of Stored Excitation Energy in Persistent Phosphors for Dark Photocatalysis
ABSTRACT Solar‐driven CO 2 reduction is fundamentally constrained by the intermittency of sunlight, resulting in a temporal mismatch between energy harvesting and catalytic conversion. Persistent phosphors offer a unique platform to bridge this gap by storing excitation energy; however, this stored energy is predominantly dissipated via radiative recombination rather than being utilized as chemically accessible redox power. Here, we demonstrate that the fate of stored excitation energy can be reprogrammed in persistent phosphors, enabling chemical reactions to proceed in the absence of light. By constructing single‐crystalline Sr 2 MgSi 2 O 7 :Eu 2+ , Dy 3+ platelets with co‐exposed {100} and {001} facets, anisotropic surface potentials enforce directional charge separation and spatially separated carrier localization, enabling the formation of a long‐lived electron reservoir. These stored electrons are subsequently extracted through Pt cocatalyst sites to drive sustained CO 2 ‐to‐CH 4 conversion in complete darkness for over 8 h, maintaining a high CH 4 selectivity of 93.6%. This work establishes a general strategy for reprogramming the fate of stored excitation energy, thereby redefining the role of persistent phosphors from luminescent materials to platforms for sustained chemical reactivity beyond illumination.
Advancing occupational and environmental safety in greenhouse agriculture: an extended elaboration likelihood model of safety technology adoption
Correction: The Covid-19 pandemic in Sweden: Prolonged and unevenly distributed effects on the volume of pediatric anesthesia and surgery demonstrated by data from the Swedish Perioperative Register
Ketal Protection of Glycerol for Selective Electrosynthesis of Glyceric Acid in Highly Alkaline Media
ABSTRACT Electrocatalytic glycerol oxidation represents a sustainable route for glycerol valorization, yet high selectivity toward glyceric acid (GLA) remains challenging on non‐noble‐metal catalysts due to competing C─C bond cleavage and complex oxidation pathways. Herein, we introduce solketal, a ketal‐protected glycerol derivative, to steer reaction selectivity. Its rigid five‐membered ketal structure selectively exposes the primary hydroxyl group while shielding vicinal diols, thereby enforcing site‐selective oxidation and suppressing C–C scission. Using a non‐noble Cu 3 Mo 2 O 9 catalyst in 6.0 M KOH with 0.2 M solketal, the system achieves a record‐high GLA selectivity of 90.1% with a production rate of 675.45 µmol cm −2 h −1 at 1.40 V versus RHE, reaching ∼95% substrate conversion within 5 h and maintaining stable operation over 100 h. Mechanistic investigations reveal that highly alkaline conditions promote solketal deprotonation to reactive alkoxide species, weaken the C α ─H bond to accelerate dehydrogenation kinetics, and mitigate local interfacial acidification, thus stabilizing the ketal‐protected intermediate and suppressing side reactions. Furthermore, practical feasibility is demonstrated through integrated upstream solketal synthesis (90% yield, 99% purity) and downstream GLA isolation (99% purity). This work establishes a substrate‐protection strategy for steering reaction pathways, offering new insights into the selective conversion of biomass‐derived polyols into value‐added oxygenates.
Biotransformation of common NSAIDs by Cunninghamella species and resulting metabolite toxicity
Abstract Nonsteroidal anti-inflammatory drugs (NSAIDs) such as diclofenac (DCF), ibuprofen (IBU), and ketoprofen (KET) are commonly found in the environment and pose potential toxicological risks. This study investigates the microbial biotransformation of these NSAIDs by Cunninghamella spp. and evaluates the toxicity of the Cunninghamella -processed samples. The results demonstrate that Cunninghamella efficiently biotransformed DCF and IBU into multiple metabolites, whereas the biotransformation of KET was negligible. Microbial treatment reduced the ecotoxicity of IBU and DCF, as confirmed by Microtox ® and algal growth inhibition assays. In vitro cytotoxicity tests using human hepatocytes (HepG2), neuroblastoma cells (SH-SY5Y), astrocytes, and rat cardiomyocytes (H9c2) showed lower toxicity of the biotransformation products compared to the parent compounds. The Ames assay revealed no mutagenicity for any of the samples. Endocrine disruption assays indicated a loss of antagonistic estrogenic and androgenic effects post-biotransformation, with minor estrogenic agonistic activity observed. In conclusion, fungal biotransformation by Cunninghamella appears to be a promising strategy for reducing the environmental toxicity of NSAIDs. However, the generation of transformation products with altered biological activity underscores the importance of combining analytical identification with comprehensive toxicological assessment.
Author Correction: Attenuated fusogenicity and pathogenicity of SARS-CoV-2 Omicron variant
Attitudes and Behaviors toward traditional music among Chinese students: the role of individual, family, and school factors
Background Traditional music is vital for cultural identity, particularly among youth in China, yet factors influencing students’ engagement with it remain underexplored. Purpose This study investigates the key factors affecting primary and secondary school students’ attitudes and behaviors toward traditional music in Guangdong Province, focusing on gender, grade level, parental support, and regional disparities. Methods Utilizing a mixed-methods design, the research involved surveys and interviews with students, parents, and educators to gather comprehensive insights. Major Findings The study revealed significant gender differences: female students displayed more positive attitudes and higher participation. Younger students exhibited greater enthusiasm, which declines with academic pressure. Parental involvement was identified as crucial, but the unexpected negative impact of parental artistic ability suggests more nuanced dynamics. Implications These findings highlight the need for tailored music education policies that are inclusive and responsive to diverse student backgrounds, particularly in less developed regions. Conclusion By understanding the multifaceted influences on students’ engagement, this study underscores the importance of fostering youth involvement in traditional music as a means of cultural preservation in an evolving educational landscape.
Formation of Gallium Monofluoride in the Coordination Sphere of Nickel
ABSTRACT Monovalent gallium halides are intrinsically unstable compounds at room temperature and can only be generated in the gas phase at temperatures of about 1000 °C. Although they are isoelectronic to carbon monoxide, dinitrogen, and the cyanide ion, which are pivotal ligands in coordination chemistry, monovalent gallium halides are largely unexplored as ligands with transition metals. Herein, we report the isolation of a dicationic nickel complex bearing a gallium monofluoride ligand. The +I oxidation state of the gallium centre is supported by NMR‐spectroscopic methods, X‐ray photoelectron spectroscopy, as well as density functional theory calculations. Analysis of the bonding situation between the GaF ligand and the central nickel atom suggests strong σ‐donating, but negligible π‐accepting properties for the supported GaF fragment. The GaF moiety forms as a product of C(sp 3 )–F bond activation of the weakly coordinating BAr F24 (tetrakis[(bis‐3,5‐trifluoromethyl)phenyl]borate) anion and serves as a fluorine source for silicon and carbon electrophiles. This leads to facile defluorination, forming the fluoride‐free complex and fluorinated products such as fluorotrimethylsilane or benzoyl fluoride.
Analysis of ultrasound Doppler flow pattern recognition method for drilling gas intrusion monitoring
Chromosomal fusions trigger rediploidization of autopolyploid genomes
Abstract The ancestor of all vertebrates is thought to have undergone autopolyploid whole-genome duplication (WGD) 1,2 , doubling the genetic raw material for evolutionary diversification 3–5 . However, we still do not understand the first steps of rediploidization that followed, required for the emergence and divergence of duplicated genes (ohnologues) created by WGD 6,7 . Consequently, how the functional potential created by autopolyploidy becomes realized during evolution remains unclear. Snow carps (Schizothoracine) have a history of recent WGDs and evolved high-altitude adaptations 8–10 , making these fish a particularly suitable system to study the early stages and consequences of rediploidization. Here genomic data from all snow carp genera reveal their autopolyploid origin, including tetraploids, hexaploids and one icosaploid (20 n ). We present haplotype-resolved genomes for two snow carp species ( Schizopygopsis younghusbandi and Schizothorax curvilabiatus ) from divergent lineages, revealing a single ancestral autotetraploidy event. Comparative genomic, meiotic pairing and allele composition analyses indicate that unbalanced chromosome fusions were responsible for the transition from tetrasomic to disomic inheritance, creating genomic regions harbouring diploid ohnologue pairs, with non-rearranged chromosomes remaining tetraploid. This study suggests that this mechanism initiated rediploidization and documents its early chromosomal and genomic consequences. It starts at chromosome fusion sites and expands outwards towards chromosomal arms, a process that remained incomplete post-speciation, leading to a mixture of ancestral and lineage-specific ohnologue divergence on highly syntenic chromosomes.
Novel Carborane Based Metal Organic Framework for Record Electronic Specialty Gas C <sub>2</sub> F <sub>6</sub> Purification via Molecular Sieving
ABSTRACT The production of high‐purity perfluoroethane (C 2 F 6 ), an essential electronic specialty gas, requires the removal of its partially‐fluorinated analog, pentafluoroethane C 2 F 5 H. This separation is exceptionally challenging due to their similar physicochemical properties. Herein, we report a novel carborane‐based metal‐organic framework, ZNU‐23 (Ni‐CB‐HPBTA), engineered with a pearl‐chain‐like pore architecture to achieve unprecedented molecular sieving separation. The narrow pore channel and large cavity in ZNU‐23 facilitate the high and fast uptake of C 2 F 5 H (65.2 cm 3 ·g −1 at 298 K and 1 bar) while nearly completely excluding C 2 F 6 , leading to a record‐high IAST selectivity exceeding 5000 for a C 2 F 5 H/C 2 F 6 (1/99) mixture. Dynamic breakthrough experiments confirm its excellent separation performance across various mixture ratios, remarkable stability under humid and elevated‐temperature conditions, and superb recyclability. Mechanistic studies via GCMC simulations and DFT calculations attribute this performance to the multi‐site confinement of C 2 F 5 H within the pearl‐chain pores and the complete steric exclusion of the larger C 2 F 6 molecule. The potential C 2 F 5 H binding sites within the framework were further revealed by C 2 F 5 H‐loaded single crystal structure of ZNU‐23.