This study aimed to compare the nanoleakage of retrograde fillings with premixed calcium silicate-based putty and mineral trioxide aggregate (MTA), using two different techniques (traditional and Lid). Sixty-four extracted human teeth were decoronated, then root canals and ends were instrumented for retrograde filling and divided into four groups according to the retrograde filling technique: the traditional and the Lid technique. Each group (n = 15) was filled with Ceraseal + Well-Root putty, Well-Root putty, Ceraseal + ProRoot MTA, and ProRoot MTA. The nanoleakage was evaluated using the Nanoflow device (IB Systems) on days 1, 3, 7, 15 and 30. Data were collected twice per second at the nanoscale (nL/s) and calculated after archiving the stabilization of fluid flow. The Kruskal–Wallis and Mann–Whitney U-tests were used for statistical analysis. All groups showed enhanced sealing ability over time. Regardless of filling materials, the Well-Root putty, Ceraseal+Well-Root putty, and Ceraseal+ProRoot MTA groups indicated less nanoleakage than the ProRoot MTA group in the first week of evaluation (p < 0.05). Although all groups did not show significant differences after 2 weeks, the Ceraseal+ProRoot MTA group leaked less than ProRoot MTA on Days 3 and 7 (p < 0.05). The scanning electron microscopic examined good adaptation to the cavity wall, which was similar to nanoleakage results. Premixed calcium silicate-based putty retrograde filling material alone and using the “lid technique” were shown to be faster and less prone to nanoleakage when compared to MTA. Full article

In this study, we investigated the feasibility of using electroencephalogram (EEG) signals to differentiate between four distinct subject-driven cognitive states: resting state, narrative memory, music, and subtraction tasks. EEG data were collected from seven healthy male participants while performing these cognitive tasks, and the raw EEG signals were transformed into time–frequency maps using continuous wavelet transform. Based on these time–frequency maps, we developed a convolutional neural network model (TF-CNN-CFA) with a channel and frequency attention mechanism to automatically distinguish between these cognitive states. The experimental results demonstrated that the model achieved an average classification accuracy of 76.14% in identifying these four cognitive states, significantly outperforming traditional EEG signal processing methods and other classical image classification algorithms. Furthermore, we investigated the impact of varying lengths of EEG signals on classification performance and found that TF-CNN-CFA demonstrates consistent performance across different window lengths, indicating its strong generalization capability. This study validates the ability of EEG to differentiate higher cognitive states, which could potentially offer a novel BCI paradigm. Full article

This study examined the impact of tea polyphenols (TPs) on the intestinal flora of loaches (Paramisgurnus dabryanus) under chronic ammonia nitrogen stress using high-throughput sequencing. Two groups of 600 loaches were studied over one month, and they were separated into a control group and tea polyphenol group. Alpha and beta diversity analyses showed diverse bacterial communities, with significant differences in the abundance and uniformity observed initially but not between sampling time points. Cluster analyses revealed distinct differences in microbial communities between groups. A predictive function analysis indicated enrichment in pathways related to amino acid and nucleotide biosynthesis. These findings offer initial insights into how tea polyphenols may affect intestinal microbial communities in loaches under ammonia nitrogen stress. Full article

For a micro-indentation hardness test with non-destructivity, the Nix–Gao model is widely used to describe tested hardness or microhardness variation with an indentation depth induced by indentation size effect, in which tested hardness approaches the macrohardness when the indentation depth is large enough. Based on an analysis of hardness measurements on 10 body-centered cubic steels with diverse microstructure, this paper proposes an analytical relation between microhardness to macrohardness ratio and the indentation depth by explicitly linking characteristic indentation depth (a data-fitting parameter) to grain size and ferrite volume fraction using two different methods. In addition, the normal distribution theory is incorporated to consider the inevitable scatter of identical measurements resulting from material heterogeneity and machining/testing errors. Results show that the proposed model, with 96% reliability, can effectively predict microhardness variation with the indentation depth and its scatter. Full article

This study aimed to assess the potential contributions of the Myers–Briggs Type Indicator (MBTI) to the sustainable growth of communities by conducting a comprehensive analysis of social perceptions of the MBTI in South Korea through big data analysis. The investigation encompasses three primary stages: data collection, preprocessing, and analysis, involving text mining, network analysis, CONCOR analysis, and sentiment analysis. A total of 31,308 text data pieces (13.73 MB) from various sources, including news, blogs, and other sections of Naver and Google, over the past three years, were collected and analyzed using the keyword “MBTI.” Tools, such as Textom SV, UCINET, and NetDraw, were employed for data collection and analysis. The study’s key findings include the identification, through term frequency (TF) and TF-inverse document frequency analyses, of top-ranking terms, such as 16Types, 4Indicators, Test, Myself, OthersMBTI, Situation, and Contents. The CONCOR analysis further revealed six clusters, encompassing themes like interest in MBTI personality tests, application of 16 types in daily life, MZ’s MBTI consumption patterns, trending of MBTI characters, extension to K-Test, and professional use of MBTI. Moreover, sentiment analysis indicated that 68.5% of individuals in South Korea expressed a positive sentiment towards MBTI, while 31.5% conveyed a negative sentiment. The specific emotions identified included liking (Good Feeling), disgust, and interest, in order of prominence. In light of these findings, this study delineates a spectrum of perceptions regarding MBTI in South Korea, encompassing both positive interests and negative concerns. To ensure the responsible use of MBTI, it is imperative to implement reliable scientific testing and education, mitigate the potential harm of stereotyping, and reshape social perceptions surrounding MBTI usage. Only through these measures can MBTI genuinely contribute to the sustainable growth of communities without being confined to limiting stereotypes. Full article

Beat-to-beat (B2B) variability in biomedical signals has been shown to have high diagnostic power in the treatment of various cardiovascular and autonomic disorders. In recent years, new techniques and devices have been developed to enable non-invasive blood pressure (BP) measurements. In this work, we aim to establish the concept of two-dimensional signal warping, an approved method from ECG signal processing, for non-invasive continuous BP signals. To this end, we introduce a novel BP-specific beat annotation algorithm and a B2B-BP fluctuation (B2B-BPF) metric novel for BP measurements that considers the entire BP waveform. In addition to careful validation with synthetic data, we applied the generated analysis pipeline to non-invasive continuous BP signals of 44 healthy pregnant women (30.9 ± 5.7 years) between the 21st and 30th week of gestation (WOG). In line with established variability metrics, a significant increase (p < 0.05) in B2B-BPF can be observed with advancing WOGs. Our processing pipeline enables robust extraction of B2B-BPF, demonstrates the influence of various factors such as increasing WOG or exercise on blood pressure during pregnancy, and indicates the potential of novel non-invasive biosignal sensing techniques in diagnostics. The results represent B2B-BP changes in healthy pregnant women and allow for future comparison with those signals acquired from women with hypertensive disorders. Full article

Alzheimer’s disease (AD) is distinguished by the gradual loss of cognitive function, which is associated with neuronal loss and death. Accumulating evidence supports that protein phosphatases (PPs; PP1, PP2A, PP2B, PP4, PP5, PP6, and PP7) are directly linked with amyloid beta (Aβ) as well as the formation of the neurofibrillary tangles (NFTs) causing AD. Published data reported lower PP1 and PP2A activity in both gray and white matters in AD brains than in the controls, which clearly shows that dysfunctional phosphatases play a significant role in AD. Moreover, PP2A is also a major causing factor of AD through the deregulation of the tau protein. Here, we review recent advances on the role of protein phosphatases in the pathology of AD and other neurodegenerative diseases. A better understanding of this problem may lead to the development of phosphatase-targeted therapies for neurodegenerative disorders in the near future. Full article

With the increasing awareness of architectural heritage conservation and the development of digital technology, there is an urgent need in the field of architectural heritage restoration for a novel solution that can enhance data security, collaboration efficiency, and file management capabilities. This study proposes an Architectural Heritage Restoration Distributed Common Data Environment (AHR-DCDE) framework based on blockchain and IPFS technologies to address the above challenges. The AHR-DCDE framework significantly improves data security and collaborative efficiency in architectural heritage restoration projects by creating a decentralized collaborative design process that achieves data immutability, traceability, and efficient large-scale file processing capabilities. The AHR-DCDE framework significantly improves data security and collaborative efficiency in architectural heritage restoration projects by creating a decentralized collaborative design process that achieves data immutability, traceability, and efficient large-scale file processing capabilities. In this study, the practicality and effectiveness of the AHR-DCDE framework is verified by taking the heritage restoration design project of Pinghe Packing Factory in Wuhan, Hubei Province, as an example. Evaluation of the framework’s network latency, throughput, and storage costs indicates that AHR-DCDE can meet the requirements of architectural heritage restoration projects, possessing efficient capabilities for handling and sharing project data. Furthermore, the implementation of the AHR-DCDE framework also facilitates efficient collaboration among interdisciplinary teams, providing robust technical support for the protection and restoration of architectural heritage. Full article

Tissue engineering is considered a promising approach to treating advanced degenerative maculopathies such as nonexudative age-related macular degeneration (AMD), the leading cause of blindness worldwide. The retina consists of several hierarchical tissue layers, each of which is supported by a layer underneath. Each of these layers has a different morphology and requires distinct conditions for proper assembly. In fact, a prerequisite step for the assembly of each of these layers is the organization of the layer underneath. Advanced retinal degeneration includes degeneration of the other retina layers, including the choroid, the retinal pigmented epithelium (RPE), and the photoreceptors. Here, we report a step-by-step fabrication process of a three-layer retina-like structure. The process included the 3D printing of a choroid-like structure in an extracellular matrix (ECM) hydrogel, followed by deposition of the RPE monolayer. After the formation of the blood vessel–RPE interface, the photoreceptor cells were deposited to interact with the RPE layer. At the end of the fabrication process, each layer was characterized for its morphology and expression of specific markers, and the integration of the three-layer retina was evaluated. We envision that such a retina-like structure may be able to attenuate the deterioration of a degenerated retina and improve engraftment and regeneration. This retinal implant may potentially be suitable for a spectrum of macular degenerative diseases for which there are currently no cures and may save millions from complete blindness. Full article

 Low-carbon urban policy (LCUP) and corporate green innovation are considered crucial strategies and methods for reducing urban carbon emissions, addressing climate change, and promoting urban environmental sustainability. This study constructed a quasi-natural experiment based on the low-carbon city strategy program implemented in China in 2010, utilizing data from Chinese prefecture-level cities and publicly listed companies from 2005 to 2020. Employing a multi-period difference-in-differences (DID) approach, this paper reveals that the establishment of low-carbon model cities effectively fosters green innovation in corporations. Further analysis demonstrates that this promotional effect is particularly significant in non-state-owned enterprises, enterprises with high media attention, those with a high level of digitalization, and enterprises located in cities with high levels of green finance and in the Eastern and Central regions of China. These conclusions withstood a series of robustness tests, confirming their validity. Meanwhile, the examination of policy mechanisms reveals that public environmental awareness, government environmental regulation, and corporate environmental information disclosure are three key policy transmission mechanisms through which LCUP affects corporate green innovation. The findings of this study provide significant empirical insights for addressing climate change and enhancing the sustainable capacity of urban environments. Full article

The need to import phosphorus raw materials for fertilizer purposes in Europe as well as the need to manage increasing amounts of waste contributed to the search for alternative sources of phosphorus. One of these is waste sodium–potassium phosphate from the production of polyols. Additionally, a current problem is providing an adequate amount of food, where fertilizers play the main role. Due to the increase in meat consumption, the attractiveness of growing corn for feed is increasing due to its high yield potential and rich composition. The article presents the impact of suspension fertilizers based on waste from the production of polyols on the yield of corn intended for green fodder. In a 3-year field study, the effects of a waste phosphorus source were compared with a commercial granulated phosphorus fertilizer—fosdar. In addition, the suspension fertilizers were assessed according to their composition by testing fertilizers containing only basic nutrients (NPK) and ones enriched with secondary ingredients (S and Mg) and microelements (Zn, Mn and B). The research confirmed the effectiveness of the tested suspension fertilizers. Although the yield obtained was lower than in the case of fosdar fertilization, it still remained at a high level of over 70 t∙ha⁻¹ of fresh yield. Full article

Alzheimer’s disease, the most common type of dementia worldwide, lacks effective disease-modifying therapies despite significant research efforts. Passive anti-amyloid immunotherapies represent a promising avenue for Alzheimer’s disease treatment by targeting the amyloid-beta peptide, a key pathological hallmark of the disease. This approach utilizes monoclonal antibodies designed to specifically bind amyloid beta, facilitating its clearance from the brain. This review offers an original and critical analysis of anti-amyloid immunotherapies by exploring several aspects. Firstly, the mechanisms of action of these therapies are reviewed, focusing on their ability to promote Aβ degradation and enhance its efflux from the central nervous system. Subsequently, the extensive history of clinical trials involving anti-amyloid antibodies is presented, from initial efforts using first-generation molecules leading to mixed results to recent clinically approved drugs. Along with undeniable progress, the authors also highlight the pitfalls of this approach to offer a balanced perspective on this topic. Finally, based on its potential and limitations, the future directions of this promising therapeutic strategy for Alzheimer’s disease are emphasized. Full article

Soil copper (Cu) contamination in mining areas poses a serious threat to the surrounding environment and human health. Timely determination of Cu concentrations is crucial for the ecological protection of mining areas. Hyperspectral remote sensing technology, with its non-destructive monitoring advantages, is essential for monitoring soil Cu pollution and achieving sustainable agricultural development. Using the hyperspectral technique for assessing soil Cu concentration, four machine learning models (support vector regression (SVR), random forest (RF), partial least squares regression (PLSR), and artificial neural network (ANN)), combined with three types of input variables (the full-band, sensitive bands, and optimized spectral indices (Opt-TBIs)) were employed. The hyperspectral reflectance of 647 soil samples from an abandoned tailings mine in western Inner Mongolia, China was collected. The sensitive bands were extracted using the successive projections algorithms (SPA), and 12 Opt-TBIs were selected. Results showed that the regions with higher soil Cu concentration extracted by SPA and Opt-TBIs were concentrated in the red edge and near-infrared regions. Compared with the full spectrum and SPA-sensitive bands, models based on Opt-TBIs successfully predicted soil Cu concentrations. The Opt-TBIs-RF model provided higher accuracy in estimating soil Cu among the four models. Using only four Opt-TBIs as input variables, the model maintained a stable performance in estimating Cu concentrations in different mining areas (R²_Val = 0.72, RPD_Val = 1.90). In conclusion, Opt-TBIs as input variables demonstrate good predictive capabilities for soil Cu concentrations in the study area, providing a basis for the formulation of sustainable strategies for soil reclamation and environmental protection in Inner Mongolia. Full article

Telerehabilitation (TR) shows promise as a method of remote service delivery, yet there is little guidance to inform implementation in the context of the National Health Service (NHS) in England. This paper presents the protocol for a realist synthesis study aiming to investigate how TR can be implemented to support the provision of high-quality, equitable community-based stroke rehabilitation, and under what conditions. Using a realist approach, we will synthesise information from (1) an evidence review, (2) qualitative interviews with clinicians (n ≤ 30), and patient–family carer dyads (n ≤ 60) from three purposively selected community stroke rehabilitation services in England. Working groups including rehabilitation professionals, service-users and policy-makers will co-develop actionable recommendations. Insights from the review and the interviews will be synthesised to test and refine programme theories that explain how TR works and for whom in clinical practice, and draw key messages for service implementation. This protocol highlights the need to improve our understanding of TR implementation in the context of multidisciplinary, community-based stroke service provision. We suggest the use of a realist methodology and co-production to inform evidence-based recommendations that consider the needs and priorities of clinicians and people affected by stroke. Full article

Background: Echocardiographic myocardial work is a new load-independent echocardiographic technique to quantify left ventricle (LV) systolic performance. Our aim was to establish normal values for echocardiographic myocardial work in a large population of healthy children. Methods: For all the subjects 4-, 2-, and 3-chamber-view videos were stored. The following parameters were obtained by offline analysis: the global myocardial work (GMW), the global myocardial constructive work (GCW), the global myocardial wasted work (GWW), and the global myocardial work efficiency (GWE). Age, weight, height, heart rate, and body surface area (BSA) were used as independent variables in the statistical analysis. Results: In all, 516 healthy subjects (age range, 1 day—18 years; median age, 8.2 ± 5.3 years; 55.8% male; body surface area (BSA) range, 0.16 to 2.12 m²) were included. GWI, GCW, and GWW increased with weight, height, and BSA (ρ ranging from 0.635 to 0.226, p all < 0.01); GWI and GCW positively correlated with age (ρ 0.653 and 0.507). After adjusting for BSA differences, females showed higher mean GWI (p = 0.002) and GCW values (p < 0.001), thus Z-score equations for gender have been presented. Conclusions: We provided MW values in a large population of healthy pediatric subjects including lower ages. MW values increased with age and body size and, interestingly, were higher in females than in men. These data cover a gap in current nomograms and may serve as a baseline for the evaluation of MW analysis in children with congenital and acquired heart diseases. Full article

Conducting polymers like polypyrrole, polyaniline, and polythiophene with nanostructures offers several advantages, such as high conductivity, a conjugated structure, and a large surface area, making them highly desirable for energy storage applications. However, the direct synthesis of conducting polymers with nanostructures poses a challenge. In this study, we employed a hard template method to fabricate polystyrene@polypyrrole (PS@PPy) core–shell nanoparticles. It is important to note that PS itself is a nonconductive material that hinders electron and ion transport, compromising the desired electrochemical properties. To overcome this limitation, the PS cores were removed using organic solvents to create hollow PPy nanospheres. We investigated six different organic solvents (cyclohexane, toluene, tetrahydrofuran, chloroform, acetone, and N,N-dimethylformamide (DMF)) for etching the PS cores. The resulting hollow PPy nanospheres showed various nanostructures, including intact, hollow, buckling, and collapsed structures, depending on the thickness of the PPy shell and the organic solvent used. PPy nanospheres synthesized with DMF demonstrated superior electrochemical properties compared to those prepared with other solvents, attributed to their highly effective PS removal efficiency, increased specific surface area, and improved charge transport efficiency. The specific capacitances of PPy nanospheres treated with DMF were as high as 350 F/g at 1 A/g. And the corresponding symmetric supercapacitor demonstrated a maximum energy density of 40 Wh/kg at a power density of 490 W/kg. These findings provide new insights into the synthesis method and energy storage mechanisms of PPy nanoparticles. Full article

Measurements of atmosphere density in the upper thermosphere and exosphere are of great significance for studying space–atmosphere interactions. However, the region from 200 km to 1000 km has been a blind area for traditional ground-based active remote sensing techniques due to the limitation of facilities and the paucity of neutral atmosphere. To fulfill this gap, the University of Science and Technology of China is developing a powerful metastable helium resonance fluorescent lidar incorporating a 2 m aperture telescope, a high-energy 1083 nm pulsed laser, as well as a superconducting nanowire single-photon detector (SNSPD) with high quantum efficiency and low dark noise. The system is described in detail in this work. To evaluate the performance of the lidar system, numerical simulation is implemented. The results show that metastable helium density measurements can be achieved with a relative error of less than 20% above 370 km in winter and less than 200% in 270–460 km in summer, demonstrating the feasibility of metastable helium lidar. Full article

Examining the distribution patterns and spatiotemporal niche overlap of sympatric species is crucial for understanding core concepts in community ecology and for the effective management of multi-species habitats within shared landscapes. Using data from 26 camera-traps, recorded over two years (December 2020–November 2022), in Sidi Toui National Park (STNP), Tunisia, we investigate habitat use and activity patterns of the scimitar-horned oryx (n = 1865 captures) and dorcas gazelle (n = 1208 captures). Using information theory and multi-model inference methods, along with the Pianka index, we evaluated the habitat characteristics influencing species distribution and their spatial niche overlap. To delineate daily activity patterns, we applied kernel density estimation. Our findings indicate minimal spatial overlap and distinct environmental factors determining suitable habitats for each species. Furthermore, we found significant temporal niche overlaps, indicative of synchrony in daily activity patterns, with both species showing peak activity at dawn and dusk. Our results indicated that oryx and gazelle differ in at least one dimension of their ecological niche at the current density levels, which contributes to their long-term and stable coexistence in STNP. Full article

Addressing common challenges such as limited indicators, poor adaptability, and imprecise modeling in gas pre-warning systems for driving faces, this study proposes a hybrid predictive and pre-warning model grounded in time-series analysis. The aim is to tackle the effects of broad application across diverse mines and insufficient data on warning accuracy. Firstly, we introduce an adaptive normalization (AN) model for standardizing gas sequence data, prioritizing recent information to better capture the time-series characteristics of gas readings. Coupled with the Gated Recurrent Unit (GRU) model, AN demonstrates superior forecasting performance compared to other standardization techniques. Next, Ensemble Empirical Mode Decomposition (EEMD) is used for feature extraction, guiding the selection of the Variational Mode Decomposition (VMD) order. Minimal decomposition errors validate the efficacy of this approach. Furthermore, enhancements to the transformer framework are made to manage non-linearities, overcome gradient vanishing, and effectively analyze long time-series sequences. To boost versatility across different mining scenarios, the Optuna framework facilitates multiparameter optimization, with xgbRegressor employed for accurate error assessment. Predictive outputs are benchmarked against Recurrent Neural Networks (RNN), GRU, Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM), where the hybrid model achieves an R-squared value of 0.980975 and a Mean Absolute Error (MAE) of 0.000149, highlighting its top performance. To cope with data scarcity, bootstrapping is applied to estimate the confidence intervals of the hybrid model. Dimensional analysis aids in creating real-time, relative gas emission metrics, while persistent anomaly detection monitors sudden time-series spikes, enabling unsupervised early alerts for gas bursts. This model demonstrates strong predictive prowess and effective pre-warning capabilities, offering technological reinforcement for advancing intelligent coal mine operations. Full article

The advancement of autonomous capabilities in maritime navigation has gained significant attention, with a trajectory moving from decision support systems to full autonomy. This push towards autonomy has led to extensive research focusing on collision avoidance, a critical aspect of safe navigation. Among the various possible approaches, dynamic programming is a promising tool for optimizing collision avoidance maneuvers. This paper presents a DP formulation for the collision avoidance of autonomous vessels. We set up the problem framework, formulate it as a multi-stage decision process, define cost functions and constraints focusing on the actual requirements a marine maneuver must comply with, and propose a solution algorithm leveraging parallel computing. Additionally, we present a greedy approximation to reduce algorithm complexity. We put the proposed algorithms to the test in realistic navigation scenarios and also develop an extensive test on a large set of randomly generated scenarios, comparing them with the RRT* algorithm using performance metrics proposed in the literature. The results show the potential benefits of an autonomous navigation or decision support framework. Full article

Over the past three decades, Sri Lanka has observed a substantial rise in landslide occurrences linked to intensified rainfall. However, the lack of comprehensive landslide inventories has hampered the development of effective risk analysis and simulation systems, requiring Sri Lanka to rely heavily on foreign-developed models, despite the difficulty of fully examining the similarities between the characteristics of landslides in Sri Lanka and the areas where the model has been developed. Satellite images have become readily available in recent years and have provided information about the Earth’s surface conditions over the past few decades. Thus, this study verifies the utility of satellite images as a cost-effective remote-sensing method to clarify the commonalities and differences in the characteristics of landslides in two regions Ikawa, Japan, and Sabaragamuwa, Sri Lanka, which exhibit different geological formations despite similar annual rainfall. Using Google Earth satellite images from 2013 to 2023, we evaluated land-slide density, types, and geometry. The findings reveal that Ikawa exhibits a higher landslide density and experiences multiple-type landslides. In contrast, both areas have similar initiation areas; however, Sabaragamuwa predominantly experiences single landslides that are widespread and mobile. The findings also reveal that various characteristics of landslides are mainly influenced by varied topography. Here, we confirmed that even in areas where comprehensive information on landslides is conventionally lacking, we can understand the characteristics of landslides by comparing landslide geometry between sites using satellite imagery. Full article