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Owing to its sustainability and environmentally friendliness, bacterial cellulose (BC) has received attention as a zero-waste textile material. Since the color of original BC was mostly yellowish white, a dyeing process is necessary to suggest BC as a textile. Thus, this study aimed to suggest a natural dyeing method using coffee to produce an eco-friendly coffee-dyed bacterial cellulose (BC-COF) bio-leather and to propose a reusing method as a dye adsorbent. To determine the dyeing and mordanting conditions with the highest color strength value, parameters such as dyeing temperature, time, mordanting methods were evaluated. Fourier-transform infrared spectroscopy and X-ray diffraction analysis confirmed that BC-COF was successfully colorized with coffee without changing its chemical and crystalline structures. In addition, field-emission scanning electron microscopy and Brunauer-Emmett-Teller surface area analysis confirmed that coffee molecules were successfully incorporated into fiber structures of BC. The effects of pH, concentration, temperature, and time on the adsorption of methylene blue dye using BC-COF bio-leather were also evaluated using ultraviolet-visible spectroscopy and zeta potential measurement. The results showed that BC-COF was found to be most effective when pH 6 of methylene blue solution with a concentration of 50 mg/L was adsorbed for 30 minutes at 25°C. Moreover, BC-COF could be reused for multiple times and had better dye adsorption rate compared to the original BC. From the results, it was confirmed that BC-COF could be employed as a dye adsorbent.

This paper proposes an approximate string matching with k -mismatches when calculating the generalized edit distance. When the edit distance is generalized, more sophisticated string matching can be provided. However, the execution time increases because of the bundle of complex computations for calculating complicated edit distances. The computational costs for finding which steps or edit distances are over k -mismatches cannot be significant in the generalized edit distance metric. Therefore, we can reduce the execution time by determining steps over k -mismatches and then skipping them. The diagonal step calculations using the pruning register skips unnecessary distance calculations over k -mismatches. The overhead of control statements and reordered memory accesses can be amortized by skipping multiple steps. Even though the proposed skipping method requires additional overhead, the proposed scheme’s practical embodiments show that the execution time of string matching is reduced significantly when k is small.

Magic-angle twisted bilayer graphene (MATBG) exhibits a range of correlated phenomena that originate from strong electron–electron interactions. These interactions make the Fermi surface highly susceptible to reconstruction when ±1, ±2 and ±3 electrons occupy each moiré unit cell, and lead to the formation of various correlated phases 1 – 4 . Although some phases have been shown to have a non-zero Chern number 5 , 6 , the local microscopic properties and topological character of many other phases have not yet been determined. Here we introduce a set of techniques that use scanning tunnelling microscopy to map the topological phases that emerge in MATBG in a finite magnetic field. By following the evolution of the local density of states at the Fermi level with electrostatic doping and magnetic field, we create a local Landau fan diagram that enables us to assign Chern numbers directly to all observed phases. We uncover the existence of six topological phases that arise from integer fillings in finite fields and that originate from a cascade of symmetry-breaking transitions driven by correlations 7 , 8 . These topological phases can form only for a small range of twist angles around the magic angle, which further differentiates them from the Landau levels observed near charge neutrality. Moreover, we observe that even the charge-neutrality Landau spectrum taken at low fields is considerably modified by interactions, exhibits prominent electron–hole asymmetry, and features an unexpectedly large splitting between zero Landau levels (about 3 to 5 millielectronvolts). Our results show how strong electronic interactions affect the MATBG band structure and lead to correlation-enabled topological phases. Correlation-driven topological phases with different Chern numbers are observed in magic-angle twisted bilayer graphene in modest magnetic fields, indicating that strong electronic interactions can lead to topologically non-trivial phases.

Magic-angle twisted trilayer graphene (MATTG) has emerged as a moiré material that exhibits strong electronic correlations and unconventional superconductivity 1 , 2 . However, local spectroscopic studies of this system are still lacking. Here we perform high-resolution scanning tunnelling microscopy and spectroscopy of MATTG that reveal extensive regions of atomic reconstruction favouring mirror-symmetric stacking. In these regions, we observe symmetry-breaking electronic transitions and doping-dependent band-structure deformations similar to those in magic-angle bilayers, as expected theoretically given the commonality of flat bands 3 , 4 . Most notably in a density window spanning two to three holes per moiré unit cell, the spectroscopic signatures of superconductivity are manifest as pronounced dips in the tunnelling conductance at the Fermi level accompanied by coherence peaks that become gradually suppressed at elevated temperatures and magnetic fields. The observed evolution of the conductance with doping is consistent with a gate-tunable transition from a gapped superconductor to a nodal superconductor, which is theoretically compatible with a sharp transition from a Bardeen–Cooper–Schrieffer superconductor to a Bose–Einstein-condensation superconductor with a nodal order parameter. Within this doping window, we also detect peak–dip–hump structures that suggest that superconductivity is driven by strong coupling to bosonic modes of MATTG. Our results will enable further understanding of superconductivity and correlated states in graphene-based moiré structures beyond twisted bilayers 5 . High-resolution scanning tunnelling microscopy and spectroscopy are used to provide evidence for unconventional superconductivity in magic-angle twisted trilayer graphene.

Soil respiration (R S ) comprises terrestrial ecosystems’ second-largest carbon flux. Yet, methodological errors in R S partitioning and uncertainties in seasonal responses of R S make it difficult to predict future R S . Here, we tested the assumption of R S partitioning (similar microbial respiration between planted and root-free soils), and explored two components of R S , autotrophic and heterotrophic respiration (R A , R H , respectively), in a temperate grassland under monsoon continental climate. Microbial respiration in soils from planted plots was 3.88 times higher than that from root-free plots during lab incubation. In field, R H :R S ratio was relatively low during non-monsoon, but increased during monsoon. The R H was more sensitive to temperature than R S , indicating a greater Q 10 of R H than that of estimated R A . The annual R H :R S excluding the monsoon period was comparable to those reported in the global Soil Respiration Database (SRDB) and other Korean literature. This study highlights that the assumption of R S partitioning can be violated, that R H exhibits a greater sensitivity to changes in temperature and soil water content than R A , and that annual R H :R S may be similar across the globe when extreme precipitation (e.g., monsoon) is excluded.

This study develops an artificial intelligence model to quickly and easily determine correct mask-wearing in real time using thermal videos that ascertained temperature changes caused by air trapped inside the mask. Five types of masks approved by the Korean Ministry of Food and Drug Safety were worn in four different ways across 50 participants, generating 5000 videos. The results showed that 3DCNN outperformed ConvLSTM in both binary and multi-classification for mask wearing methods, with the highest AUROC of 0.986 for multi-classification. Each mask type scored AUROC values > 0.9, with KF-AD being the best classified. This improved use of thermal imaging and deep learning for mask fit-checking could be useful in high-risk environments. It can be applied to various mask types, which enables easy generalizability and advantages in public and occupational health and healthcare system.

Background As the global population ages, the decline in cognitive and physical functions presents significant challenges for individuals and healthcare systems. In older adults, conventional assessment methods are often subjective, time-consuming, and influenced by external factors, highlighting the need for objective and efficient evaluation tools. Neuroimaging biomarkers, particularly diffusion tensor imaging (DTI) metrics, offer promising insights into brain structure and function, potentially serving as reliable indicators of functional decline. Methods This study examines the relationship between DTI-derived metrics and cognitive and physical functions in older adults ( n  = 106). Four primary diffusion metrics, such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, were analyzed to assess their strength of association with functional decline. To enhance this association, principal component analysis (PCA) was applied, integrating multiple diffusion features. Age, sex, and educational level were included as covariates to control for their potential confounding effects. Results Neuroimaging biomarkers were significantly associated with both cognitive and physical functions in older adults. Key neural pathways, including the corpus callosum, anterior and retrolenticular internal capsule, fornix, and superior fronto-occipital fasciculus, showed strong associations across domains. PCA combining metrics enhanced these associations, highlighting integrated patterns of white matter contributions. Models selecting multiple neural tracts demonstrated increased predictive accuracy, especially when adjusting for age, sex, and education. Distinct tract-function relationships were observed across physical and cognitive subdomains, emphasizing the complex and domain-specific roles of white matter in functional outcomes. Conclusions The findings highlight the potential of neuroimaging biomarkers as objective tools for evaluating functional decline in aging. Identifying key neural pathways linked to cognitive and physical functions may contribute to early diagnosis and targeted interventions. The integration of multiple neuroimaging features enhances the strength of associations, suggesting that advanced neuroimaging techniques could play a crucial role in aging research and clinical applications.

Due to the prevalence of complex data, data heterogeneity is often observed in contemporary scientific studies and various applications. Motivated by studies on cancer cell lines, we consider the analysis of heterogeneous subpopulations with binary responses and high-dimensional covariates. In many practical scenarios, it is common to use a single regression model for the entire data set. To do this effectively, it is critical to quantify the heterogeneity of the effect of covariates across subpopulations through appropriate statistical inference. However, the high dimensionality and discrete nature of the data can lead to challenges in inference. Therefore, we propose a novel statistical inference method for a high-dimensional logistic regression model that accounts for heterogeneous subpopulations. Our primary goal is to investigate heterogeneity across subpopulations by testing the equivalence of the effect of a covariate and the significance of the overall effects of a covariate. To achieve overall sparsity of the coefficients and their fusions across subpopulations, we employ a fused group Lasso penalization method. In addition, we develop a statistical inference method that incorporates bias correction of the proposed penalized method. To address computational issues due to the nonlinear log-likelihood and the fused Lasso penalty, we propose a computationally efficient and fast algorithm by adapting the ideas of the proximal gradient method and the alternating direction method of multipliers (ADMM) to our settings. Furthermore, we develop non-asymptotic analyses for the proposed fused group Lasso and prove that the debiased test statistics admit chi-squared approximations even in the presence of high-dimensional variables. In simulations, the proposed test outperforms existing methods. The practical effectiveness of the proposed method is demonstrated by analyzing data from the Cancer Cell Line Encyclopedia (CCLE).

Vancomycin-variable enterococci (VVE) are vanA-positive, vancomycin-susceptible enterococci with the ability to revert to a vancomycin-resistant phenotype on exposure to vancomycin. We sought to assess the prevalence of VVE and to determine clinical characteristics of patients infected with VVE. We prospectively collected Enterococcus faecium sterile site isolates from Toronto Invasive Bacterial Diseases Network hospitals from January 2015 to June 2016 and calculated VVE (defined as vanA-positive, vancomycin-susceptible isolates) prevalence among vanA-containing isolates. We performed chart reviews of VVE and vancomycin-resistant E. faecium (VRE) bacteremias identified from January 2012 to June 2016, and on a random sample of patients with bacteremia due to vanA/vanB-negative, vancomycin-susceptible enterococci (VSE) from January 2015 to June 2016. Clinical characteristics were compared and factors associated with mortality assessed. Because of the potential reversion from VVE to VRE, pulsed-field gel electrophoresis (PFGE) was performed for strains causing breakthrough bacteremia in order to identify relatedness among strains with different phenotypic resistance within the same patient. VVE comprised 47% (18/38) of vanA-positive isolates. The charts of 36 VRE, 25 VVE, and 79 VSE patients were reviewed. Central venous catheter associated bacteremia was more common in VVE (44%) and VRE patients (57%) than in VSE patients (28%) (P = 0.01). The Pitt bacteremia (OR 1.3, P = 0.002) and the Charlson score (OR 1.2, P = 0.008) were the only independent mortality predictors. PFGE of strains causing breakthrough bacteremia showed high within-patient clonality, irrespective of vanA-positivity or vancomycin-susceptibility. A substantial proportion of vanA-positive isolates are VVE and are therefore not detected with conventional selective culture methods. Bacteremia sources of patients with VVE are similar to those infected with VRE. We detected no association between VVE and 30-day mortality or breakthrough bacteremia.

Alzheimer's disease (AD) is a lethal progressive neurological disorder affecting the memory. Recently, US Food and Drug Administration mitigated the standard for drug approval, allowing symptomatic drugs that only improve cognitive deficits to be allowed to accelerate on to clinical trials. Our study focuses on taurine, an endogenous amino acid found in high concentrations in humans. It has demonstrated neuroprotective properties against many forms of dementia. In this study, we assessed cognitively enhancing property of taurine in transgenic mouse model of AD. We orally administered taurine via drinking water to adult APP/PS1 transgenic mouse model for 6 weeks. Taurine treatment rescued cognitive deficits in APP/PS1 mice up to the age-matching wild-type mice in Y-maze and passive avoidance tests without modifying the behaviours of cognitively normal mice. In the cortex of APP/PS1 mice, taurine slightly decreased insoluble fraction of Aβ. While the exact mechanism of taurine in AD has not yet been ascertained, our results suggest that taurine can aid cognitive impairment and may inhibit Aβ-related damages.