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Tuning refractive indices in nematic liquid crystal via nanoparticles coupling
Narrowband signal generation by spintronic THz emitters
We report a technique for generating narrowband, high-frequency electrical signals using spintronic terahertz emitters (STEs) integrated onto coplanar waveguides (CPWs). Conventional STE operation typically yields ultrashort, broadband pulses spanning tens of terahertz. Our method employs multiple STEs positioned at precisely defined intervals along the CPW to produce a burst like signal, where the inter-emitter spacing determines the time delay between pulses, thus the fundamental burst frequency, which theoretically can be tuned across the STE bandwidth. Meander-shaped CPW geometries are used to enable compact integration and uniform optical excitation. First test devices demonstrate electrical signals up to 30 GHz with a bandwidth of 4.7 GHz corresponding to a quality factor of 6.38.
Pseudohypoxia induced by iron chelators preserves working memory performance in aged mice
>95% TM-polarized 780 nm diode laser enabled by GA–NN co-optimization of quantum states and optical states
We demonstrate a high-performance 780 nm diode laser, achieving a transverse-magnetic degree of polarization of >95.2% and a wall-plug efficiency of 56.23% at an injection current of 10 A. This performance stems from the synergistic co-optimization of a tensile-strained GaAsP quantum well and the P-side cladding and contact layers. A hybrid genetic-algorithm–neural-network framework was employed to navigate the complex design space, reducing device evaluation time from 540 to 4 ms. Our work establishes an efficient, physically grounded design paradigm for polarization-sensitive lasers critical in atomic physics and quantum technology.
Association of serum uric acid to high density lipoprotein cholesterol ratio with stroke
Surface acoustic wave enabled all-optical determination of the interlayer elastic constants of a van der Waals interface
Understanding the properties of two-dimensional material interfaces with the substrate is necessary for device applications. Surface acoustic wave propagation through a layered material flake on a substrate could provide unique information on the transverse rigidity of the flake-to-substrate interaction. Ultrasonic waves were generated by a focused femtosecond laser pulse at the surface of a model system—fused silica with hBN flake transferred above. Using an all-optical spatially resolved pump–probe interferometric technique, the spatial dependencies of the surface vertical velocity profiles were measured. The measurements reveal the appearance of surface acoustic wave dispersion in the hBN flake region compared to the fused silica surface. Multilayer modeling allows us to access the longitudinal and shear elastic coupling constants c33* and c44* between hexagonal BN and the substrate.
Low perceived warmth of AI agents reduces trust towards them
Abstract Artificial intelligence (AI) agents represent a new class of social actors within social and economic systems. To ensure the smooth functioning of human-AI societies, it is crucial to understand how trust between humans and AI agents is developed. The present study ( N = 400), conducted on a representative sample of U.S. residents, investigated how the fundamental dimensions of social perception may affect differences in trust towards humans and AI agents. We manipulated human and AI trustees’ warmth and competence and measured trust towards them in a trust game. Overall, AI trustees were trusted less than human trustees were, especially in the low warmth conditions. We discuss warmth as a crucial determinant of trust in the context of human-AI interactions and suggest potential implications of these results for designing trustworthy AI systems.
Quantum cascade detectors based on dual-upper-state active regions with a broadband response
We propose broadband quantum cascade detectors based on a dual-upper-state active region design. The dual-upper-state concept is known to produce broad gain in quantum cascade lasers and is also expected to provide a wide spectral response for quantum cascade detectors. Compared with quantum cascade detectors employing a bound-to-bound design, dual-upper-state devices are anticipated to exhibit broader bandwidth and can achieve higher responsivity. To validate this, we designed and fabricated quantum cascade detectors for each mid-wave (∼5 μm) and long-wave (∼10 μm) infrared regions, implementing anti-crossed dual-upper states in the main absorbing transition. At 300 K, the fabricated devices exhibited responsivities of ∼13.5 mA/W at λpeak ∼5.1 μm and ∼7.1 mA/W at λpeak ∼10 μm. The measured relative bandwidth of the devices Δλ/λcenter are approximately ∼20.8% and ∼21.1%. These results indicate that the dual-upper-state not only enables a wide spectral response but also may provide enhanced responsivity. The experimental findings are further supported by non-equilibrium Green's function simulations. Overall, our results highlight the potential of the dual-upper-state approach for broadband, high-performance infrared detection.
Empirical validation of a generative AI framework for personalized education assessment
Abstract The tension between personalized learning demands and standardized evaluation mechanisms presents a persistent challenge in contemporary education. This study proposes a comprehensive personalized education assessment framework driven by generative artificial intelligence technologies. The framework adopts a five-layer hierarchical architecture integrating data collection, processing, intelligent analysis, assessment generation, and feedback optimization components. ChatGLM3-6B, fine-tuned on 50,000 expert-curated programming feedback instances assembled through a human-in-the-loop process combining authentic instructor records, newly authored examples, and AI-assisted human-verified content, enables contextually responsive feedback generation, while dynamic learner profiling and knowledge graph modeling support precise diagnostic assessment. Empirical validation involving 449 undergraduate students in introductory Python programming courses demonstrated that the framework achieved assessment accuracy correlating at 0.847 with expert consensus (Fleiss’ κ = 0.74 for inter-rater reliability) while reducing generation time by over 99% compared to manual evaluation. Ablation experiments confirmed that knowledge graph integration contributed most substantially to accuracy improvements, with removal of this component reducing correlation by 0.055. Experimental participants exhibited significantly higher learning gains (Cohen’s d = 0.56), with particularly pronounced effects among initially lower-performing students. The framework also enhanced learner engagement and satisfaction compared to conventional assessment approaches. These findings suggest that generative AI can effectively operationalize personalized assessment at scale while maintaining pedagogical quality and transparency.
Sub-3 V monolithic integration of GaN-based micro-LEDs with <i>p</i> -MOSFETs
Low threshold voltage (VTH) is essential for monolithic integration of GaN-based Micro-LEDs with metal-oxide-semiconductor field-effect transistors (MOSFETs), enabling low-power, long-lifetime micro-displays. In this work, we achieve record-low VTH = −2.3 V in a monolithically integrated Micro-LED with a p-channel MOSFET (p-MOSFET), enabling efficient operation below 3 V. By reducing the gate dielectric thickness from 50 to 30 nm, VTH decreases from −9.2 to −2.3 V, in excellent agreement with simulation, while preserving a high on/off current ratio (&gt;107). The integrated Micro-LED delivers a light output power of 155 μW, external quantum efficiency of 20.6%, and luminance of 2.8 M nits—matching standalone Micro-LED performance. These results establish a practical pathway toward low-voltage, high-performance monolithic active-matrix Micro-LEDs, paving the way for energy-efficient extended reality displays.
AVPDN: learning motion-robust and scale-adaptive representations for polyp detection in dynamic colonoscopy frames
(Poly)Borylated Species as Modern Reactive Groups toward Unusual Synthetic Applications
Abstract (Poly)borylated species, molecules bearing multiple carbon–boron groups, have emerged as powerful building blocks in modern synthetic chemistry owing to their rich, tunable reactivity. Their distinctive steric and electronic properties, together with their ability to participate in both ionic and radical pathways, make them uniquely versatile synthons for the selective construction of carbon─carbon and carbon─heteroatom bonds. These frameworks provide strategic opportunities for late‐stage functionalization and the assembly of architecturally complex molecules. This review highlights recent advances in the chemistry of (poly)borylated compounds, particularly molecules bearing multiple boron substituents on a single carbon site, with emphasis on their anionic, cationic, radical, alkene, 1,2‐diradical, and carbene‐based variants. It underscores the synergistic behavior of these multiple boron‐substituted reactive carbon‐centered intermediates and the diverse functionalization of C─metalloid bonds. Key reactivity modes are examined across structural classes such as gem ‐diborylalkanes, gem ‐diborylalkenes, 1,1,2‐polyborylated systems, and emerging tri‐ and tetra‐borylated frameworks. Central transformations include transition‐metal‐catalyzed cross‐couplings, stereoselective transmetalation and functionalizations, addition reactions, and polymerizations, along with boron‐masking, boron‐retentive, and boron‐eliminative strategies. Furthermore, alkylations, radical‐mediated reactions, and energy‐transfer photocatalysis pathways are critically discussed. By elucidating the mechanistic principles and synthetic potential of (poly)borylated species, this review aims to provide a unified framework to better understand their reactivity and to highlight the significant advances made since 2019 at the interface of organoboron chemistry, catalysis, and advanced materials science.
Frequency dependent dielectric study on liquid crystal based aptasensor for the sensitive and selective detection of tumor biomarker
A liquid crystal (LC)-based dielectric aptasensor was developed for the sensitive and selective detection of tumor biomarker, platelet-derived growth factor (PDGF-BB). The LC aptasensor was prepared by immobilization of PDGF-BB specific aptamer on silane modified patterned indium-tin-oxide-glass substrates of the LC cell through a cross linker, glutaraldehyde. Frequency-dependent dielectric measurements were carried out with the 4-cyano-4′-pentylbiphenyl LC material in an aptasensor with electrodes pretreated with different concentrations of PDGF-BB spiked human serum. A significant change in the dielectric property was observed corresponding to the disruption of uniform homeotropic LC alignment at LC–electrode interface, caused by accumulated bulky charged species due to PDGF-BB binding with aptamer at the electrode surface. The LC aptasensor cell exhibited a linear response in relative dielectric permittivity (Δεr′) at 100 Hz with PDGF-BB over a wide concentration range of 10 pM to 100 nM with a lowest detection limit of 4.8 pM. The experimental data fitted well with the Cole–Cole model of dielectric relaxation showed a gradual increase in LC dielectric strength with increasing concentration of PDGF-BB binding to aptamer at ˂10 kHz, suggesting a dominant surface interfacial phenomenon than bulk molecular process at higher frequency. The LC aptasensor cell exhibited either minimal or insignificant dielectric response to other PDGF isoforms, viz. PDGF-AB and PDGF-AA, and other potential interferents, revealing high specificity to PDGF-BB. The present study demonstrated that the proposed concept of dielectric LC aptasensor may find potential application in tumor detection.
Hierarchical multi-attention neural networks for sensor fault diagnosis and mitigation in digital twins
Enhanced pseudocapacitance rectification by doping metalloid phosphorus in high entropy oxide (CrMnFeCoNi)3O4
Metalloid phosphorus-doped spinel-type high-entropy oxide (CrMnFeCoNi)3O4 is synthesized to solve the challenges of limited pseudocapacitance rectification for supercapacitor diodes. It demonstrates both pseudocapacitive energy storage and ionic rectification in a 1 M KOH electrolyte. This material achieves a high specific capacitance of 394.05 F g−1 at 0.5 A g−1 along with a reverse rectification ratio of 0.85 at 3 mV s−1. These properties are driven by phosphorus electronegativity, which enhances electron transfer, creates oxygen vacancies, and accelerates ion transport. The assembled supercapacitor diodes delivered a high energy density of 241.35 W h kg−1 at a power density of 5250 W kg−1 while maintaining a rectification ratio RRI of 6.95–8.8 at scan rates of 3–30 mV s−1 and a sustained RRII of 0.86. After 1000 cycles, the diode retained 84% rectification efficiency with minimal capacitance decay. This work advances iontronic circuits through dual-functional electrodes.
Design of a Li-ion battery cooling system incorporating PCM, heat pipes, and liquid circuits using marine predator algorithm-enhanced ANN and multi-verse optimization
Ferroelectric control of the layer-polarized anomalous Hall effect in a 2D TiClAsH bilayer via superposition engineering
Ferrovalley (FV) materials have attracted much attention due to their unique spin-valley coupled properties. In this work, we predict FV single-layer TiClAsH, which has 77 meV of intrinsic valley polarization. The electronic correlation effect can drive the topological phase transition from the FV state to the quantum anomalous Hall state, and its critical half-valley metallic phase can achieve complete spin polarization. By breaking the mirror symmetry of bilayer TiClAsH, the layer-locked Berry curvature distribution is achieved, and furthermore, the layer-polarized anomalous Hall effect (LPAHE) is induced. Meanwhile, reversible LPAHE switching can be achieved through sliding control of ferroelectricity. Our findings offer a good material platform to manipulate the spin splitting, valley polarization, ferroelectricity, and topological states for multi-functional device applications.
Ant colony optimization approach for sustainable end-milling with minimum quantity nano-green lubrication
Small polaron hopping conduction mechanism in Mg-doped LaMnO3 ceramics
The cold sintering process (CSP) is frequently applied for the fabrication of ceramics with a low melting point and sintering temperature. However, the effect of CSP on electrical performance in LaMnO3-based ceramics has seldom been explored. In this paper, the LaMg0.5Mn0.5O3 ceramics were prepared using both CSP and conventional sintering (CS) for comparison. X-ray diffraction results demonstrated that both the CSP and CS ceramics consist of the LaMnO3 phase and the MgMn2O4 phase. To investigate the relationship between temperature and electrical performance, the small polaron hopping (SPH) and Mott variable range hopping (Mott-VRH) conductivity mechanisms were employed. Notably, the CSP ceramic exhibits a high SPH mechanism fitted linearity (R-squared value = 99.90%) in a wide temperature range from 198 to 1273 K. In contrast, while the CS ceramic also exhibits high linearity (R-squared value = 99.98%) in the high-temperature range (473–1273 K), it deviates from this behavior at lower temperatures. Considering the phase transition process, the Jahn–Teller effect, and the high Mn3+ content (91.21%), the MgMn2O4 secondary phase appears to play a crucial role in the properties.
Protocol of the randomized double blind sham controlled AddVNS study of transcutaneous vagus nerve stimulation mechanisms in depression
Abstract Depression is among the most prevalent mental disorders worldwide, carrying one of the highest burden of disease among all mental disorders. While invasive vagus nerve stimulation has been approved for treatment-resistant depression for decades, its clinical use is limited by surgical risks and heterogeneous clinical efficacy. Transcutaneous auricular VNS (tVNS) may offer a non-invasive alternative, but to date it remains experimental due to limited high-quality evidence, unclear biological mechanisms of action, and rudimentary knowledge on optimal stimulation parameters. To address these gaps, we initiated the AddVNS study. The AddVNS study ( Add -on t VNS in depression) is a monocentric, exploratory, prospective, randomized, double-blind, sham-controlled interventional trial conducted at the Max Planck Institute of Psychiatry’s research hospital. Adult patients with a depressive episode (ICD-10: F31–33) were assigned to receive active or sham transcutaneous vagus nerve stimulation (tVNS) in addition to treatment-as-usual (TAU) over a six-week period. Stimulation is administered three times daily (30 to 60 min each), five days per week. A deep phenotyping strategy is applied, including repeated psychophysiological measures (e.g., pupillometry, ECG, photoplethysmography, electrogastrogram) and neuroimaging (structural and functional MRI) at baseline and post-intervention, continuous actigraphy, repeated blood and stool sample acquisition (pre-, mid-, and post-intervention) for multiomic investigation, comprehensive neuropsychology including self-rated personality assessment, and closely monitored clinical evaluations. The patient-reported outcomes are collected weekly, the clinician-rated scales pre-, mid-, and post-intervention. In addition, follow-up self-ratings are obtained at 6 and 12 weeks post-tVNS. The main objective of AddVNS is to improve our understanding of the biological effects elicited by tVNS in depression. By combining rigorous methodology with an extensive and longitudinal multimodal approach, AddVNS represents the most comprehensive investigation of tVNS effects and markers in depression to date. We believe it to significantly advance our mechanistic understanding and subsequently clinical translation of this promising intervention.