Browse Articles

Realizing high power factor and thermoelectric performance in band engineered AgSbTe2

Design and numerical simulation of CuBi2O4 solar cells with graphene quantum dots as hole transport layer under ideal and non-ideal conditions

Abstract The simulation of ideal and non-ideal conditions using the SCAPS-1D simulator for novel structure Ag/FTO/CuBi 2 O 4 /GQD/Au was done for the first time. The recombination of charge carriers in CuBi 2 O 4 is an inherent problem due to very low hole mobility and polaron transport in the valence band. The in-depth analysis of the simulation result revealed that Graphene Quantum Dots (GQDs) can act as an appropriate hole transport layer (HTL) and can enhance hole transportation. The simulation was done under ideal and nonideal conditions. The non-ideal conditions include parasitic resistances, reflection losses, radiative, and Auger recombination whereas the ideal condition was studied without the inclusion of any losses. Under ideal conditions, the cell Ag/FTO/CuBi 2 O 4 /GQD/Au exhibited a photovoltaic (PV) parameter such as open circuit voltage (V oc ), short circuit current (J sc ), fill factor (FF), photo conversion efficiency (PCE) are 1.39 V, 25.898 mA/cm 2 , 90.92%, and 32.79%, respectively. The effect of various cell parameters such as the thickness of the absorber layer, HTL layer, and FTO, acceptor and defect density, the bandgap of the absorber and HTL layer, series and shunt resistance, back and front contact materials, radiation and Auger recombination of the absorber layer, reflection losses on the efficiency of the proposed cell is analysed. The drastic reduction in all PV parameters was observed under non-ideal conditions and the PV parameters are V oc (1.22 V), J sc (2.904 mA/cm 2 ), FF (86.3), and PCE of 3.06%. The charge kinetics such as impedance, conductivity, and capacitance plots, and possible reasons for reductions in PV parameters are discussed in detail.

The development of an efficient artificial intelligence-based classification approach for colorectal cancer response to radiochemotherapy: deep learning vs. machine learning

Viral RNA polymerase as a SUMOylation decoy inhibits RNA quality control to promote potyvirus infection

Brain-model neural similarity reveals abstractive summarization performance

AbstractDeep language models (DLMs) have exhibited remarkable language understanding and generation capabilities, prompting researchers to explore the similarities between their internal mechanisms and human language cognitive processing. This study investigated the representational similarity (RS) between the abstractive summarization (ABS) models and the human brain and its correlation to the performance of ABS tasks. Specifically, representational similarity analysis (RSA) was used to measure the similarity between the representational patterns (RPs) of the BART, PEGASUS, and T5 models’ hidden layers and the human brain’s language RPs under different spatiotemporal conditions. Layer-wise ablation manipulation, including attention ablation and noise addition was employed to examine the hidden layers’ effect on model performance. The results demonstrate that as the depth of hidden layers increases, the models’ text encoding becomes increasingly similar to the human brain’s language RPs. Manipulating deeper layers leads to more substantial decline in summarization performance compared to shallower layers, highlighting the crucial role of deeper layers in integrating essential information. Notably, the study confirms the hypothesis that the hidden layers exhibiting higher similarity to human brain activity play a more critical role in model performance, with their correlations reaching statistical significance even after controlling for perplexity. These findings deepen our understanding of the cognitive mechanisms underlying language representations in DLMs and their neural correlates, potentially providing insights for optimizing and improving language models by aligning them with the human brain’s language-processing mechanisms.

Risk factors, urodynamic characteristics, and distress associated with nocturnal enuresis in overactive bladder -wet women

Optical single-shot readout of spin qubits in silicon

AbstractSmall registers of spin qubits in silicon can exhibit hour-long coherence times and exceeded error-correction thresholds. However, their connection to larger quantum processors is an outstanding challenge. To this end, spin qubits with optical interfaces offer key advantages: they can minimize the heat load and give access to modular quantum computing architectures that eliminate cross-talk and offer a large connectivity. Here, we implement such an efficient spin-photon interface based on erbium dopants in a nanophotonic resonator. We demonstrate optical single-shot readout of a spin in silicon whose coherence exceeds the Purcell-enhanced optical lifetime, paving the way for entangling remote spins via photon interference. As erbium dopants can emit coherent photons in the minimal-loss band of optical fibers, and tens of such qubits can be spectrally multiplexed in each resonator, the demonstrated hardware platform offers unique promise for distributed quantum information processing based on scalable, integrated silicon devices.

Microbial safety and chemical characteristics of sausage coated by chitosan and postbiotics obtained from Lactobacillus bulgaricus during cold storage

Experimental and theoretical study on ceiling temperature distributions in mountain tunnel with a lateral open shaft

De novo biosynthesis of nylon 12 monomer ω-aminododecanoic acid

Changes of health-related quality of life within 6 months after stroke by clinical and sociodemographic factors

Incremental learning algorithm for dynamic evolution of domain specific vocabulary with its stability and plasticity analysis

The Nordic-walking mechanism and its explanation of deconfined pseudocriticality from Wess-Zumino-Witten theory

MOFs-based adsorbents for the removal of tetracycline from water and food samples

An enhanced Bayesian approach for damage identification utilizing prior knowledge from refined elemental modal strain energy ratios

Acquisition of Fc-afucosylation of PfEMP1-specific IgG is age-dependent and associated with clinical protection against malaria

Cytosolic phospholipase A2 in infiltrating monocyte derived macrophages does not impair recovery after spinal cord injury in female mice

The zinc finger protein560(ZNF560) functions as a novel oncogenic gene in osteosarcoma

Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware

In situ synthesis of ZnO/g-C3N4 based composites for photodegradation of methylene blue under visible light

AbstractIn this study, in situ-synthesized ZnO/g-C3N4 based composites were used as photocatalysts for organic pollution removal. These nanocomposites were prepared through simple calcination of a mixture of melamine and ZnO nanoparticles and underwent comprehensive evaluation of their structural, morphological, optical, and photocatalytic properties, using various analytical techniques. As the g-C3N4 content increased, the band gap decreased from 3.02 to 2.94 eV. Additionally, the reduction in photoluminescence intensity confirmed the heterojunction interface between the g-C3N4 and ZnO components. The photodegradation rate of methylene blue (MB) dye exhibited an increase, rising from 0.016 (min−1) for ZnO and 0.011 (min−1) for g-C3N4 to 0.022 (min−1) for the ZnO/g-C3N4 (10 wt%) composite. Furthermore, combining ZnO (50 wt%) with g-C3N4 led to a significant enhancement in the MB dye removal efficiency, reaching 97% compared to the ZnO/g-C3N4 (10 wt%) composite. In contrast, the removal efficiencies were 90% for pristine ZnO and 73% for g-C3N4 phases.