Browse Articles

Robust higher-order feedback feedforward ILC for networked nonlinear system with varying trial lengths, data dropouts and disturbances

Dynamic decision-support for engineering course evaluation and improvement: a case study of the electric machinery and drives course

Abstract Engineering education accreditation emphasizes that course evaluation should enable continuous improvement. However, existing evaluation models are often constrained by static characteristics, single-dimensional assessment, insufficient predictive capability, and a disconnected closed-loop optimization mechanism. To address these challenges, this study develops a dynamic educational decision-support framework encompassing evaluation, diagnosis, prediction, and optimization. Using five-period data from 2021 to 2025 (n = 882) for the Electric Machinery and Drives (EMD) course, the framework is empirically demonstrated the proposed framework on a single-course longitudinal dataset, establishing 16 dynamic evaluation indicators covering both student and instructor dimensions. The framework integrates temporally adaptive weighting, correlation-aware multidimensional evaluation, trend-aware shortcoming diagnosis, and uncertainty-aware prediction. Specifically, sliding-window entropy weighting captures temporal changes in indicator importance, Mahalanobis-distance TOPSIS accounts for inter-indicator correlations, Markov prediction with Bootstrap confidence intervals estimates future state distributions, and D-SRC is formulated as a trend-aware extension of the Shortcoming Repair Coefficient to support proactive teaching intervention. On the basis of the three traditional dimensions (importance, deficiency, and student differentiation), the short-term evolutionary trend of indicator scores is introduced to realize bottleneck identification with both status diagnosis and prospective early warning. A three-dimensional, nine-measure optimization path is then formulated. The five-year analysis showed that the weights of technology-driven and ethics-related indicators changed substantially, with b10 and b15 increasing by 228% and 150%, respectively. M-TOPSIS provided correlation-aware evaluation and increased the SD-based relative dispersion of closeness coefficients by 10.7%, while Markov prediction with Bootstrap confidence intervals generated a short-term baseline projection of the 2026 excellent rate. After D-SRC-guided interventions for b15, b10, and b8, the corresponding scores increased by 7.7, 7.3, and 6.3 points, and the overall excellent rate increased from 24.1% to 39.6%. The proposed framework provides a decision-support tool for engineering education continuous improvement. By incorporating temporal trend information, D-SRC extends static shortcoming diagnosis toward prospective early warning and supports targeted intervention planning. The three-dimensional, nine-measure strategy further links diagnosis with teaching improvement, supporting the transition from static course assessment to dynamic, feedback-oriented educational decision support. Future studies should validate the framework across additional courses and institutions.

Synergistic effect of garbage enzyme and FeSO₄ on iron availability and radish (Raphanus sativus L.) productivity in calcareous soil

Sonoplasma treatment of drinking water reduces yeast culturability both immediately and progressively during holding

Environmental awareness and perceived utility shape the value–intention gap in green consumption

Design and optimization of electro-functional polymeric components exercising entropy-weighted TOPSIS method

HyCANet: a hybrid convolutional-attention network with cross-attention fusion for lung cancer histopathological classification

Energy-efficient logarithmic floating-point multipliers for neural network and image processing applications

Optimizing nutrient supply to enhance biomass, nutrient status, phytochemicals, and photosynthetic pigments in sweet basil (Ocimum basilicum L.)

Enhancing salinity tolerance in potato (Solanum tuberosum L.) using foliar-applied branched-chain amino acids

Abstract Salinity stress is a major constraint to potato production in sandy soils under arid environments. This study evaluated the effectiveness of foliar-applied branched-chain amino acids (BCAAs)—valine, leucine, and isoleucine—applied individually or in combinations to enhance salinity tolerance of potato ( Solanum tuberosum L. cv. Kara) during the 2023 and 2024 growing seasons in Wadi El Natrun. A split-plot randomized complete block design with three replicates was used, where three salinity levels (0, 1500, and 3000 ppm NaCl) were assigned to main plots, while eight BCAA treatments were allocated to subplots: control (water spray), valine (2 g L⁻¹), leucine (2 g L⁻¹), isoleucine (2 g L⁻¹), valine + leucine (1 g L⁻¹ each), valine + isoleucine (1 g L⁻¹ each), leucine + isoleucine (1 g L⁻¹ each), and valine + leucine + isoleucine (0.75 g L⁻¹ each). Salinity significantly reduced vegetative growth, tuber number, and total yield, particularly at 3000 ppm NaCl. Foliar BCAA application mitigated these adverse effects. Under moderate salinity, isoleucine and dual combinations increased yield up to 45.22 tons ha⁻¹ versus 29.35 tons ha⁻¹ in untreated plants. Under severe salinity, the combined treatment (V + L+I) produced the highest yield (42.05 tons ha⁻¹). Enhanced proline accumulation, protein content, and antioxidant enzyme activity indicated improved stress tolerance. BCAAs represent an effective strategy for sustaining potato productivity in salt-affected soils.

The impact of general pedagogical knowledge on student engagement as mediated by instructional communication

Abstract Teachers’ ability to apply pedagogical knowledge through effective classroom communication is an important factor in shaping student engagement, yet this pathway remains underexplored in Ethiopian higher education. This study examined how general pedagogical knowledge (GPK) relates to student engagement (SE) through the process role of instructional communication (IC). Using a quantitative explanatory design, data were collected from 278 teachers across ten Ethiopian colleges and analyzed with structural equation modeling (SEM). Three validated instruments measured GPK, IC, and SE based on teachers’ perceptions. Results showed that GPK had a significant effect on IC (β = 0.26, p = .013), and IC strongly predicted SE (β = 0.82, p < .001). The direct effect of GPK on SE was not significant, indicating that IC functioned as the process variable fully linking GPK to SE. These findings suggest that teachers’ pedagogical knowledge supports engagement primarily through communicative clarity and responsiveness. However, because engagement was assessed only through teacher self-reports, the results should be interpreted as perceptions rather than direct measures of student behavior. The study contributes to understanding the GPK–IC–SE pathway and highlights the need for teacher education programs to strengthen communicative competence alongside pedagogical expertise.

Green synthesis of tetrahydropyridine-3-carboxylate derivatives and evaluation of antimicrobial and antimalarial activities supported by molecular docking, POM studies, and drug-likeness analysis

Thermally symbiotic integration of osmotic membrane distillation and electrolysis for direct seawater hydrogen production

Abstract Integrating water purification membranes with electrolysis for in situ hydrogen (H 2 ) production from seawater offers a rapid pathway to net-zero, but is limited by salt crossover and insufficient water production in existing approaches. Here we overcome these limitations by integrating osmotic membrane distillation (OMD) with alkaline water electrolysis (AWE). Driven by dual thermal and osmotic gradients to enhance salt-free water vapour transport, the OMD-AWE delivers a H 2 production rate of 60 kg m –2 day –1 with excellent stability over 500 h of continuous operation. To eliminate the external heating energy penalty of OMD, we propose a thermally symbiotic architecture that converts the AWE’s waste heat to OMD’s thermal driving force while OMD simultaneously providing cooling to maintain AWE optimal temperatures, as validated by our thermal-water-hydrogen model. This thermal symbiosis not only makes OMD-AWE energy self-sufficient with energy efficiency of 51 kWh kg(H 2 ) –1 but also establishes a self-regulating mechanism that phase-locks thermal driving force to fluctuating electrical inputs, synchronising water supply with demand to overcome renewable intermittency. Our approach enables flexible component matching and thermal self-sufficiency at any scale, providing a framework for membrane-integrated electrolysis, demonstrating both technical excellence and economic viability towards a sustainable hydrogen economy.

Flow cores and the problem of vulnerability of complex network systems

Anti-PD-1 plus anti-CTLA-4 blockade overcomes immune exclusion in NSCLC brain metastases by enhancing CD8+ T cell responses and promoting tertiary lymphoid structure formation

Abstract Brain metastases (BrMs) in non-small cell lung cancer (NSCLC) respond poorly to anti-PD-1 monotherapy, but the underlying immune resistance remains incompletely defined. Here we integrate clinical outcome analyses, paired human tissue profiling and syngeneic mouse models to characterize the BrM immune microenvironment. Clinical analyses suggest improved intracranial disease control with nivolumab plus ipilimumab compared with nivolumab alone. Paired human specimens show that BrMs contain fewer cytotoxic T lymphocytes (CTLs) and tertiary lymphoid structures (TLSs) than primary tumors, defining an immune-excluded phenotype. A syngeneic BrM model recapitulates this phenotype and resists anti-PD-1 monotherapy, whereas combined anti-PD-1 and anti-CTLA-4 blockade suppresses tumor growth and prolongs survival. Single-cell RNA sequencing, flow cytometry and immunofluorescence show increased CTL infiltration and effector function after combination therapy. CD8 + T cell depletion abrogates therapeutic benefit, and combination therapy expands T follicular helper-like cells and induces TLS-like structures. These findings manifest increased adaptive immune response of dual checkpoint blockade in NSCLC BrMs.

Retraction Note: Liposome co-incubation with cancer cells secreted exosomes (extracellular vesicles) with different proteins expressions and different uptake pathways

Empowering clinical trial design with agentic intelligence and real-world data

Static stretching duration-dependent changes in flexibility, muscle oxygen saturation, and blood flow in the forearm flexors

Abstract Static stretching (SS) is commonly performed to improve flexibility; however, whether mechanical responses and local haemodynamic responses are temporally coordinated remains unclear. This study examined the effects of SS duration on flexibility and haemodynamic responses in the forearm flexors. Seventeen healthy men completed a randomized, repeated-measures protocol including four SS durations (30, 60, 180, and 300 s) and a no-stretch control. Outcome measures included wrist range of motion (ROM), maximum dynamic passive torque (DPT max , used as an index of stretch tolerance), passive stiffness, tissue oxygenation index (TOI), and muscle blood flow (mBF), assessed before and up to 9 min after stretching. Longer SS durations (≥ 180 s) resulted in greater increases in ROM and DPT max and more persistent reductions in passive stiffness. In contrast, TOI exhibited a duration-dependent post-stretch overshoot, whereas mBF increased immediately after stretching but returned to baseline within 3 min irrespective of duration. Changes in ROM were more strongly associated with changes in DPT max than with changes in passive stiffness, and no significant associations were observed between mechanical variables and haemodynamic responses. These findings indicate that mechanical and haemodynamic responses to SS follow distinct temporal profiles. Importantly, the present study was not designed to establish a causal relationship between these responses, but rather to determine whether they exhibit coordinated or independent temporal behaviour. Accordingly, improvements in flexibility appear to be primarily related to stretch tolerance, whereas haemodynamic responses occur in parallel but are not directly linked to mechanical changes.

Membrane-anchored DNA nanodevice with allosteric aptamer arms enables parallel probing and on-site drug delivery

Abstract DNA-based molecular computation enables targeting of cells via multiple surface receptors. However, existing platforms are often limited to single-receptor detection per operation or rely on freely diffusing components, a common source of off-target interference. Here we show an intelligent DNA nanodevice (DND) that integrates multivalent recognition, logic‑gated computation, and spatially precise drug delivery in a single nanostructure. The DND comprises a doxorubicin-loaded tetrahedral DNA framework (tFNA@Dox) connected via three allosteric aptamer arms to a cholesterol-modified membrane anchor. Simultaneous binding of all three aptamers triggers an AND‑logic gate, releasing tFNA@Dox specifically at the target cell membrane. This localized sense‑and‑act mechanism maximizes therapeutic specificity and minimizes systemic exposure. In tumor-bearing mice, DND@Dox effectively accumulated in tumors, significantly inhibited tumor growth under local and systemic administration, and reduced systemic toxicity. This work establishes a versatile platform for logic‑controlled, multimarker‑guided cancer theranostics.

A generalized electrode mechanism unifying classical electrochemical pathways in square-wave voltammetry

Abstract The electrochemical framework consisting of two successive electron-transfer steps (EE) separated by a reversible homogeneous chemical equilibrium (Crev), followed by an irreversible regenerative chemical reaction (C′) linked to the participants in the second electron-transfer step is assigned as ECrevEC′ mechanism. The ECrevEC′ electrochemical scheme can be considered as a comprehensive and unifying mechanism that covers a broad spectrum of important classical electrochemical mechanisms as limiting cases. Depending on the magnitude of equilibrium constant of the intermediate chemical step ( K eq), the associated chemical rate parameter governing this equilibrium ( k chem ), and the kinetic rate constant of the irreversible regenerative reaction ( k c ), the ECrevEC′ mechanism can coherently reproduce the features of the simple “E mechanism”, as well as the “ECrev”, “CErev”, “EC′ (regenerative)”, and also the “EE”, “ECrevE” and EEC’ mechanisms. Theoretical treatment of this complex reaction scheme is of fundamental importance, as it enables a systematic and unified exploration of the entire mechanistic landscape within a single mathematical formalism. Mathematical modeling of this complex mechanism affords detailed insight into the coupled effects of electron-transfer kinetics, chemical equilibria, and homogeneous regeneration reactions. Voltammetric simulations based on the ECrevEC′ mechanism exhibit rich and valuable diagnostic features in both forward and backward current responses, permitting important mechanistic distinctions to be resolved via analysis of relevant parameters of the voltammetric patterns. The ECrevEC’ framework provides a powerful tool for the interpretation of experimental data in complex voltammetric systems involving multiple coupled chemical reactions. This electrochemical scheme is widely applicable theoretical platform with high relevance to redox catalysis, bioelectrochemistry and energy-conversion systems.