Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Carbon Emission Reduction Paths for the Production of Prefabricated Building Components Based on Evolutionary Game Theory

Prefabricated buildings are gradually being promoted from pilot demonstration to scale, to combat climate change and improve energy conservation and emission reduction in the building sector. Despite the carbon emission of assembled structures being substantially lower than that of cast-in-place buildings due to the significant reduction in energy demand during the materialization process, there is still a lot of room for improvement. This study looks at the strategy choices made by manufacturers of prefabricated building components in relation to lowering carbon emissions from the standpoint of manufacturing prefabricated building components. By building a dynamic evolutionary game model between two parties, we investigate the evolutionary process of the strategy chosen by prefabricated building component manufacturers and the government, analyzing the evolutionary stability of each side’s strategy choice, and finally using Matlab tools to simulate the effectiveness of the evolutionary stability. The study findings indicate that (1) low-carbon production costs, local government incentives and sanctions, and corporate low-carbon production benefits are the main influencing factors for manufacturers of prefabricated building components to adopt low-carbon production techniques; and that (2) the cost of regulation under low-carbon production methods and the local government performance assessment system are the key elements affecting regulations by the local government. Based on this finding, we suggest corresponding countermeasures in three areas, including investigating new low-carbon technology options for businesses, developing a new carbon emission accounting subsidy mechanism, and improving the regulatory framework of the government, to provide an efficient pathway for the growth of a low-carbon economy.
The Child–Mother–Father–Teacher Relationship Network in Kindergarten and Its Association with Children’s Social and Academic Development: An Ecological Perspective

This study examines how a set of the child’s proximal relationships (mother–child, father–child, and teacher–child) and parent–teacher relationships relate to the child’s prosocial and learning behaviors in kindergarten. The sample included 95 mother–father–child triads (child mean age 5.9 years) and 42 kindergarten teachers. All adults reported on their relationship with the child and on their perceptions of parent–teacher relationships. Teachers reported on the child’s behaviors. Main findings: (1) All proximal relationships and the teachers’ relationships with mothers and fathers were related to children’s outcomes; and (2) different patterns of associations were found between father–child and mother–child relationships, and teacher–child relationship, parent–teacher relationships, and children’s outcomes. These findings hint to the different roles of fathers and mothers in their children’s development and to distinguished patterns of relationships of mothers and fathers with kindergarten teachers.
Continual Pre-Training of Language Models for Concept Prerequisite Learning with Graph Neural Networks

: Prerequisite chains are crucial to acquiring new knowledge efﬁciently. Many studies have been devoted to automatically identifying the prerequisite relationships between concepts from educational data. Though effective to some extent, these methods have neglected two key factors: most works have failed to utilize domain-related knowledge to enhance pre-trained language models, thus making the textual representation of concepts less effective; they also ignore the fusion of semantic information and structural information formed by existing prerequisites. We propose a two-stage concept prerequisite learning model (TCPL), to integrate the above factors. In the ﬁrst stage, we designed two continual pre-training tasks for domain-adaptive and task-speciﬁc enhancement, to obtain better textual representation. In the second stage, to leverage the complementary effects of the semantic and structural information, we optimized the encoder of the resource–concept graph and the pre-trained language model simultaneously, with hinge loss as an auxiliary training objective. Extensive experiments conducted on three public datasets demonstrated the effectiveness of the proposed approach. Our proposed model improved by 7.9%, 6.7%, 5.6%, and 8.4% on ACC, F1, AP, and AUC on average, compared to the state-of-the-art methods.
SiC Electrochemical Sensor Validation for Alzheimer Aβ42 Antigen Detection

Alzheimer’s disease (AD) is a neurodegenerative disease with only late-stage detection; thus, diagnosis is made when it is no longer possible to treat the disease, only its symptoms. Consequently, this often leads to caregivers who are the patient’s relatives, which adversely impacts the workforce along with severely diminishing the quality of life for all involved. It is, therefore, highly desirable to develop a fast, effective and reliable sensor to enable early-stage detection in an attempt to reverse disease progression. This research validates the detection of amyloid-beta 42 (Aβ42) using a Silicon Carbide (SiC) electrode, a fact that is unprecedented in the literature. Aβ42 is considered a reliable biomarker for AD detection, as reported in previous studies. To validate the detection with a SiC-based electrochemical sensor, a gold (Au) electrode-based electrochemical sensor was used as a control. The same cleaning, functionalization and Aβ1–28 antibody immobilization steps were used on both electrodes. Sensor validation was carried out by means of Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS) aiming to detect an 0.5 µg·mL−1 Aβ42 concentration in 0.1 M buffer solution as a proof of concept. A repeatable peak directly related to the presence of Aβ42 was observed, indicating that a fast SiC-based electrochemical sensor was constructed and may prove to be a useful approach for the early detection of AD.
Increase of Prevalence of Obesity and Metabolic Syndrome in Children and Adolescents in Korea during the COVID-19 Pandemic: A Cross-Sectional Study Using the KNHANES

(1) Background: The aim of this study was to evaluate the prevalence of obesity and metabolic syndrome since the COVID-19 pandemic outbreak utilizing representative data on youth aged 2–18 years from the Korean National Health and Nutrition Examination Surveys (KNHANES) conducted in 2019–2020. (2) Methods: The survey consists of three parts: health interviews, health examinations, and nutrition surveys. From the 2019 and 2020 surveys, 1371 (2–9 years = 702 and 10–18 years = 669) and 1124 (2–9 years = 543 and 10–18 years = 581) individuals were included in the analysis. (3) Results: The mean body mass index (BMI) increased significantly among youth aged 2–9 years from 16.53 kg/m2 in 2019 to 17.1 kg/m2 in 2020 (p < 0.01). In youth aged 10–18 years, the BMI was found to increase slightly from 21.25 kg/m2 in 2019 to 21.41 kg/m2 in 2020 (p = 0.64). The increasing prevalence of extreme obesity was significant in girls, especially those aged 2–9 years (p < 0.01). However, extreme obesity had increased in 10–18-year-old boys (p = 0.08). The overall prevalence of metabolic syndrome in adolescents increased from 3.79% to 7.79% during the COVID-19 pandemic (p = 0.01). (4) Conclusions: We observed that the prevalence of obesity and metabolic syndrome among children and adolescents has increased after the COVID-19 outbreak. This is believed to be associated with an increase in the rate of early comorbidities in adulthood. The prevention of the progression of pediatric obesity has recently become an urgent public health concern in Korea.
Investigation of the Wear Behavior of Dual-Matrix Aluminum–(Aluminum–Carbon Nanotube) Composites

Aluminum (Al)–aluminum–carbon nanotube (Al–CNT) dual-matrix (DM) composites are a novel class of nanocomposite materials that combine the ductility of the Al matrix with the hardness and wear resistance of the Al–CNT composite and thus can offer a unique combination of properties that make them suitable for a wide range of wear applications such as cutting tools, bearings, brake pads, wear-resistant coatings, etc. However, the specific properties of the DM Al–(Al–CNT) composite will depend on several factors related to the material’s composition and the friction conditions. This study investigates the wear behavior of DM Al–(Al–CNT) composites consisting of a primary matrix of soft aluminum in which milled hard particles of (Al–CNT) are dispersed as affected by five parameters: (1) wt. % CNT in the reinforcement particles, (2) mixing ratio between the reinforcement particles and the soft Al matrix, (3) sliding speed, (4) applied load, and (5) distance. The experimental design used a Taguchi fractional factorial orthogonal array (OA) L27 to reduce the number of experiments, and analysis of variance (ANOVA) was used to determine the significance and to model the effect of each control parameter. Results showed that the wear rate could be reduced by up to 80% by tailoring the composition and controlling the friction conditions. It was found that the mixing ratio significantly impacts the wear behavior of DM Al–(Al–CNT) composites. A mixing ratio of 50% and a CNT content of 3 wt. % at the lowest applied load gave the lowest wear rate and coefficient of friction. Scanning electron microscopy investigations showed fragmentations in the reinforced matrix at higher loads and mixing ratios, which negatively impacted the wear behavior. Our findings confirm that DM Al–(Al–CNT) composites are promising for wear applications. However, the wear behavior depends on the composition and microstructural design of the composite, which needs to be carefully studied and understood.
Screening of Fungal Strains and Formulations of Metarhizium anisopliae to Control Phyllotreta striolata in Chinese Flowering Cabbage

Simple Summary The cabbage flea beetle (CFB; Phyllotreta striolata) is a significant pest of cruciferous vegetables in the world. CFB causes severe destruction of Chinese flowering cabbage (CFC; Brassica campestris L. ssp. chinensis var. utilis), a key leafy vegetable in South China. In practice, the current control approach of CFB is to kill adults by spraying chemical insecticides, but the control efficacy is not sufficient because the adults have a strong tolerance to insecticides; on the other hand, the larvae living in soil are not influenced by pesticides. It is urgent to develop sustainable technology to control CFB. Here, we provide a new technology to control larvae and adults through seed pelletization and stem–leaf spraying using Metarhizium anisopliae. This study provides new insights into the application of mycoinsecticides and the IPM of flea beetle. Abstract (1) Background: The cabbage flea beetle (CFB; Phyllotreta striolata) seriously damages the production of Chinese flowering cabbage (CFC; Brassica campestris L. ssp. chinensis var. utilis), which is a key leafy vegetable in South China. A large number of chemical insecticides have been sprayed to control this pest; as a result, residues and resistances are becoming an issue. It is necessary to develop biocontrol technologies to address this issue. (2) Methods: Fungal strains were selected based on bioactivity against CFB, and CFC seed pelletization with fungal conidia was subject to evaluation of control efficacy against CFB. The effective mixture of fungus and chemical insecticide was determined based on safety and joint toxicology tests. (3) Results: The screening of 103 strains from 14 genera identified the Metarhizium anisopliae strain MaGX19S02 (Ma) as the one with the highest virulence. The LC50s of Ma to CFB adult and second instar larvae on day 9 post-treatment were 3.04 × 106 and 27.2 × 106 spores/mL, respectively. In the pot test, the pelletization of CFC seeds with Ma conidia (50/25/12.5 mg in 1 g seed with 4 g fillers) demonstrated significant CFB mortalities (45–82%) 20 days after the larvae were introduced. In the field test, the seed pelletization achieved 57–81% control efficacy 14 days after sowing. Furthermore, the combination of Ma with chlorfenapyr (Chl) demonstrated a synergistic effect against CFB; based on this result, we prepared the mixture formulation of 20% Ma-Chl wettable powder (WP). The assessment of the effects of 20% Ma-Chl WP (500× diluent) against CFB revealed 93.33% mortality in the pot test and 61.3% control efficacy in the field test on day 7 post-treatment. (4) Conclusions: The findings demonstrate the potential of Ma to control CFB in the field. Seed pelletization with Ma conidia effectively controlled CFB larvae and protected CFC seedlings, wherein a mixture formulation of 20% Ma-Chl WP had substantial efficacy in controlling CFB adults. Our research provides new methods for CFB biocontrol.
Reconceptualizing Emotion Recognition Ability

Emotion decoding accuracy (EDA) plays a central role within the emotional intelligence (EI) ability model. The EI-ability perspective typically assumes personality antecedents and social outcomes of EI abilities, yet, traditionally, there has been very limited research to support this contention. The present paper argues that the way in which EDA has been conceptualized and operationalized in EI research has ignored developments in social perception theory and research. These developments point, on one hand, to the importance of embedding emotion expressions in a social context and, on the other, to reformulating the definitions of emotion decoding accuracy. The present paper outlines the importance of context in the framework of a truth and bias model of the social perception of emotions (Assessment of Contextualized Emotions, ACE) for EI abilities.
Serum and Bronchoalveolar Lavage Fluid Levels of Cytokines in Patients with Lung Cancer and Chronic Lung Disease: A Prospective Comparative Study

The role of chronic inflammation in the initiation and progression of carcinogenesis has been well-established in previous studies, particularly in the stages of malignant conversion, invasion, and metastasis. This study aimed to explore the potential correlation between the levels of cytokines in serum and bronchoalveolar lavage fluid (BALF) by comparing their levels between patients with lung cancer and those with benign lung diseases. The study measured the concentration of IFN-γ, TNF-α, IL-1β, IL-2, IL-4, IL-6, IL-10, and IL-12p70, in venous blood and BALF of a total of 33 patients with lung cancer and 33 patients with benign lung diseases. Significant differences were found between the two groups in various clinical parameters. The cytokine levels were significantly higher among patients with malignant disease, while the BALF analysis revealed higher cytokine levels compared with serum analysis. It was discovered that the levels of cancer-specific cytokines in the lavage fluid increased significantly sooner and were present at a greater concentration than those in the peripheral blood. After one month of treatment, the serum markers decreased significantly but slower in the lavage fluid. The differences between serum and BALF markers remained significant. It was observed that the highest correlation was among IL-6 (serum) and IL-6 (lavage), with a coefficient of 0.774 (p-value < 0.001), and IL-1 (serum) and IL-1β (lavage), with a coefficient value of 0.610 (p-value < 0.001). Other significant correlations among serum and lavage cytokines were observed between IL-6 (lavage) and IL-1 (serum) (rho = 0.631, p-value < 0.001) and CRP (rho = 0.428, p-value = 0.001), respectively. This study revealed significant differences and correlations in clinical parameters, serum markers, and BALF inflammatory markers between patients with lung cancer and those with benign lung pathologies. The results highlight the importance of understanding the inflammatory profiles of these conditions and could contribute to the development of targeted therapies or diagnostic approaches in the future. Further research is needed to validate these findings, explore their implications for clinical practice, and determine the diagnostic and prognostic value of these cytokines for lung cancer.
Determination of the Magnetic Intermediate Permeability of Special Materials Based on FEM-Simulation and Hall-Sensor Measurement

This document presents the process flow and the experimental conditions for calculating the static magnetic intermediate permeability of a specimen with a dedicated geometrical contour and surface for simulation parameter of metal detection systems. In this case, intermediate is explained and defined as probes with a magnetic permeability between 10 and 1000. An analysis of recent and current measurement standards as well as similar simulation principles leads to the contribution value of this new hybrid process flow. To calculate the permeability value in a first step, an electromagnetic circuit was constructed and excited with a defined electrical DC current with a dedicated tolerance for generating a static approximated homogenic magnetic field in a defined air gap space sector. Additionally, to the H-field generation part double copper coil, two magnetic ferrite cylinders with known permeability were used. The electrical and magnetic circuit has been modeled by an Ansys FEM Electronic Desktop software; the solver is magnetic static. Specifically, the simulated magnetic field distribution of the airgap was evaluated by using different Hall sensor elements with different tolerances. Subsequently, the electromagnetic circuit was expanded by implementing different cylindrical and cube shaped probes on a defined position inside the air gap sector with homogenic magnetization. Moreover, based on the analysis of the air gap structure without the probes, a detailed 3D-FEM model of the air gap magnetic field with special probes was established, which provides the environmental field distribution of the probes. The simulation models were compared with the corresponding Hall sensor measurements, which proved the high accuracy experimental validity of the models established in this paper. Finally, some key features related to parameter variations in the electromagnetic circuit were extracted, which can significantly reflect the characteristics of the robustness of the measurement principle. The main findings reported in this paper will be beneficial for magnetic parameter settings in electromagnetic simulation.
Lower Circulating Cytotoxic T-Cell Frequency and Higher Intragraft Granzyme-B Expression Are Associated with Inflammatory Interstitial Fibrosis and Tubular Atrophy in Renal Allograft Recipients

Background and Objectives: Inflammatory interstitial fibrosis and tubular atrophy (i-IFTA) is an inflammation in the area of tubular atrophy and fibrosis. i-IFTA is poorly associated with graft outcome and associated with infiltration of inflammatory mononuclear cells. A cytotoxic T cell is a granzyme B+CD8+CD3+ T cell, mainly secret granzyme B. Granzyme B is a serine protease that may mediate allograft injury and inflammatory interstitial fibrosis and tubular atrophy (i-IFTA). However, there is no report identifying the association of granzyme B with i-IFTA after a long post-transplant interval. Material and Methods: In this study, we have measured the cytotoxic T-cell frequency with flow cytometry, serum and PBMCs culture supernatants granzyme-B levels with ELISA and intragraft granzyme-B mRNA transcript expression with the RT-PCR in RTRs in 30 patients with biopsy-proven i-IFTA and 10 patients with stable graft function. Result: The frequency of cytotoxic T cells (CD3+CD8+ granzyme B+) in SGF vs. i-IFTA was (27.96 ± 4.86 vs. 23.19 ± 3.85%, p = 0.011), the serum granzyme-B level was (100.82 ± 22.41 vs. 130.32 ± 46.60, p = 0.038 pg/mL) and the intragraft granzyme-B mRNA transcript expression was (1.01 ± 0.048 vs. 2.10 ± 1.02, p < 0.001 fold). The frequency of CD3+ T cells in SGF vs. i-IFTA was (66.08 ± 6.8 vs. 65.18 ± 9.35%; p = 0.68) and that of CD3+CD8+ T cells was (37.29 ± 4.11 vs. 34.68 ± 5.43%; p = 0.28), which were similar between the 2 groups. CTLc frequency was negatively correlated with urine proteinuria (r = −0.51, p < 0.001), serum creatinine (r = −0.28, p = 0.007) and eGFR (r = −0.28, p = 0.037). Similarly, the PBMC culture supernatants granzyme-B level was negatively correlated with urine proteinuria (r = −0.37, p < 0.001) and serum creatinine (r = −0.31, p = 0.002), while the serum granzyme-B level (r = 0.343, p = 0.001) and intragraft granzyme-B mRNA transcript expression (r = 0.38, p < 0.001) were positively correlated with proteinuria. Conclusions: A decrease in the CTLc frequency in circulation and an increased serum granzyme-B level and intragraft granzyme-B mRNA expression shows that cytotoxic T cells may mediate the allograft injury in RTRs with i-IFTA by releasing granzyme B in serum and intragraft tissue.
Adaptations of Potential Nitrogenase Activity and Microbiota with Long-Term Application of Manure Compost to Paddy Soil

Biological nitrogen fixation complements nitrogen from fertilizers in crop plants under natural conditions. It also contributes to the reduction in chemical fertilizer (CF) utilization in cultivated lands, which fits the concept of sustainable agriculture. From this viewpoint, however, it is still unknown in paddy fields how soil bacterial nitrogenase and microbiota are affected by applied materials in the soil. Therefore, in this study, the effects of long-term material applications on potential nitrogenase activity and the microbiota of soil bacteria were investigated. The nitrogenase activity tended to be higher in manure compost (MC)-applied soils than in CF-applied soils in both summer and winter. Soil bacterial alpha diversity increased whereas soil ammonia availability decreased with the MC application. The dynamic response of soil bacterial microbiota was caused by the MC application. The abundance of Nitrospira, a class of ammonia and nitrite oxidation bacteria, was lower and the abundance of alpha-Proteobacteria was higher in the MC-applied soils than in the CF-applied soils. These results suggest that the alpha diversity increase and restricted availability of NH3-N might contribute to the increase in potential nitrogenase activity in the long-term MC-applied soils.
Moisture-Induced Effects on Lignocellulosic and Humification Fractions in Aerobically Composted Straw and Manure

Humic substances affect compost stability and maturation. However, the intricate structure of lignocellulosic materials hinders the biodegradation of cellulose, hemicellulose, and lignin, often promoting the use of synthetic additives which results in microbial inactivation and death. Therefore, this study examined the effects of optimal moisture levels (MC1 = 45%, MC2 = 55%, and MC3 = 65%) on lignocellulosic and humification fractions in aerobically composted straw and manure. The study showed that 65% moisture content was more efficient in decomposing cellulose, hemicellulose, and lignin, with hemicellulose (115.3% w/w ≈ 47.1%) degrading more than cellulose (76.0% w/w ≈ 39.5%) and lignin (39.9% w/w ≈ 25.9%). However, in compost heaps with 45% moisture, the humic acid concentration increased significantly by 12.4% (3.1% w/w) and 17.3% (4.3% w/w) compared with 55% and 65% moisture, respectively. All moisture levels increased the mineralization of humic substances, but the index measured was highest at 65% MC (23.8% w/w) and lowest at 45% MC (18% w/w). In addition, the humification rate showed the trend: 0.083% w/w > 0.087% w/w > 0.100% w/w for MC1, MC2, and MC3, respectively. Overall, the results indicate that an initial moisture content of 65% is aerobically efficient for the conversion of corn straw and cow manure into stable and mature compost.