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This is an article in the field of metallurgical engineering. Titanium gypsum is an industrial waste residue mainly composed of calcium sulfate dehydrate when the titanium dioxide is produced by the sulfuric acid method. At present, the utilization rate of titanium gypsum is relatively low due to its high impurity content , difficulty in dehydration and poor mechanical properties of the subsequent products. A large amount of titanium gypsum stored in the open air has caused great environmental and economic stress on the titanium dioxide enterprises, which is a serious waste of land resources. In this article, the current situation and research progress of global titanium gypsum in building materials, chemical industry, agriculture and climate change were summarized. The suggestions and prospects for the effective reduction and high-quality resource utilization of titanium gypsum from the aspects of structure adjustment, technological innovation, green development, standard formulation and policy support were provided.

Abstract Objective To evaluate the accuracy of transthoracic echocardiography (TTE) and cardiac computed tomography angiography (CTA) in detecting the size and location of ventricular septal defects (VSD) in infants. Methods Data from 258 infants diagnosed with VSD between January 2020 and December 2022 were retrospectively analyzed. All infants underwent both TTE and cardiac CTA. The accuracy of these imaging modalities was assessed by comparing their findings with intraoperative observations of VSD size and location. Results Intraoperatively, the average VSD size was 6.1 ± 2.5 mm. The defects were classified as committed VSD (Type 1) in 45 patients, noncommitted VSD (Type 2) in 198 patients, inlet VSD (Type 3) in 12 patients, and muscular VSD (Type 4) in 3 patients. Echocardiography estimated the average VSD size at 5.6 ± 2.7 mm, with 42 patients identified as Type 1, 203 as Type 2, 10 as Type 3, and 3 as Type 4. Cardiac CTA estimated the average size at 5.9 ± 3.2 mm, with 48 patients identified as Type 1, 196 as Type 2, 11 as Type 3, and 3 as Type 4. The accuracy rates of TTE and cardiac CTA in diagnosing VSD location were 98.1% and 98.8%, respectively. A survey of surgeons indicated that 80% believe both TTE and cardiac CTA are essential preoperative evaluations. Conclusions TTE accurately diagnoses the size and location of VSD, while cardiac CTA serves as a valuable complementary method to TTE. Most surgeons advocate for the combined use of these examinations for preoperative assessment.

ABSTRACT: Wenchang chicken, a prized local breed in Hainan Province of China renowned for its exceptional adaptability to tropical environments and good meat quality, is deeply favored by the public. However, an insufficient understanding of its population architecture and the unclear genetic basis that governs its typical attributes have posed challenges in the protection and breeding of this precious breed. To address these gaps, we conducted whole-genome resequencing on 200 Wenchang chicken samples derived from 10 distinct strains, and we gathered data on an array of 21 phenotype traits. Population genomics analysis unveiled distinctive population structures in Wenchang chickens, primarily attributed to strong artificial selection for different feather colors. Selection sweep analysis identified a group of candidate genes, including PCDH9, DPF3, CDIN1, and SUGCT, closely linked to adaptations that enhance resilience in tropical island habitats. Genome-wide association studies (GWAS) highlighted potential candidate genes associated with diverse feather color traits, encompassing TYR, RAB38, TRPM1, GABARAPL2, CDH1, ZMIZ1, LYST, MC1R, and SASH1. Through the comprehensive analysis of high-quality genomic and phenotypic data across diverse Wenchang chicken resource groups, this study unveils the intricate genetic backgrounds and population structures of Wenchang chickens. Additionally, it identifies multiple candidate genes linked to environmental adaptation, feather color variations, and production traits. These insights not only provide genetic reference for the purification and breeding of Wenchang chickens but also broaden our understanding of the genetic basis of phenotypic diversity in chickens.

Phosphorus (P) is a finite natural resource and is increasingly considered to be a challenge for global sustainability. Agriculture in China plays a key role in global sustainable P management. Rhizosphere and soil-based P management are necessary for improving P-use efficiency and crop productivity in intensive agriculture in China. A previous study has shown that the future demand for phosphate fertilizer by China estimated by the LePA model (legacy phosphorus assessment model) can be greatly reduced by soil-based P management (the building-up and maintenance approach). The present study used the LePA model to predict the phosphate demand by China through combined rhizosphere and soil-based P management at county scale under four P fertilizer scenarios: (1) same P application rate as in 2012; (2) rate maintained same as 2012 in low-P counties or no P fertilizer applied in high-P counties until targeted soil Olsen-P (TPOlsen) level is reached, and then rate was the same as P-removed at harvest; (3) rate in each county decreased to 1–7 kg ha–1 yr–1 after TPOlsen is reached in low-P counties, then increased by 0.1–9 kg ha–1 yr–1 until equal to P-removal; (4) rate maintained same as 2012 in low-P counties until TPOlsen is reached and then equaled to P-removal, while the rate in high-P counties is decreased to 1–7 kg ha–1 yr–1 until TPOlsen is reached and then increased by 0.1–9 kg ha–1 yr–1 until equal to P-removal. Our predictions showed that the total demand for P fertilizer by whole China was 693 Mt P2O5 and according to scenario 4, P fertilizer could be reduced by 57.5% compared with farmer current practice, during the period 2013–2080. The model showed that rhizosphere P management led to a further 8.0% decrease in P fertilizer use compared with soil-based P management. The average soil Olsen-P level in China only needs to be maintained at 17 mg kg–1 to achieve high crop yields. Our results provide a firm basis for government to issue-relevant policies for sustainable P management in China.

Abstract Polymer microspheres can be used as fuel containers for laser inertial confinement fusion (ICF) due to their low atomic number, low density, and high thermal stability. The thin-walled polymer [...]

While researchers' interest in online impulsive buying is increasing, there is currently a paucity of research that examines at consumers impulse purchase urges while communicating with sellers utilizing instantaneous messaging services. Categorizing cognition into normative evaluation, this study examines normative evaluation influences on consumers’ affective (positive affect) and behavior (urge to buy impulsively while purchasing interaction with sellers utilizing instantaneous messaging services), thereby affirming the applicability of Cognition Emotion Theory in impulse purchase context. This study analyses the 245 collected data in SmartPLS 4 using structural equation modelling. This study found that normative evaluation positively influences positive affect. Normative evaluation and positive affect contribute in explaining the variance explained in the urge to buy impulsively. The current study found that consumers' internal emotional states (positive affect) had a significant mediation effect on the relationship between normative evaluation and urge to buy impulsively. The findings may help businesses in discovering the causes of impulsive purchases by consumers, with an emphasis on psychological factors such as positive purchasing interactions with sellers via instant messaging.

Romance has never felt the same way since the inception of online dating. A match is made not in Heaven but in the Cloud. Swiping profiles could sweep someone’s feet off. This work aims to assess the factors predicting the continuous use intention of online dating applications among young Malaysians through the lens of the UTAUT2 model and privacy risk. The research model was analyzed using Partial Least Squares Structural Equation Modelling per 282 valid responses from online daters in Malaysia. The results indicate the model’s substantial predictive power with social influence, price value, and habit as significant drivers to continuous use intention of online dating applications. Habit has the strongest effect on the intention to use online dating applications continuously. This research adds to the body of knowledge on the behavioral intention of online dating applications and offers practical suggestions for online dating service providers to increase the likelihood of their continuous adoption.

Bleb leakage is a notorious complication of glaucoma filtration surgery which increases the risk of sight-threatening conditions. A 25-year-old female with severe bilateral juvenile open-angle glaucoma was treated for blebitis and exogenous endophthalmitis secondary to chronic bleb leak after undergoing XEN implantation, followed by multiple rounds of bleb needling, and augmented trabeculectomy. In the right eye, visual acuity was hand movement with cataract, intraocular pressure was 6 mmHg and the bleb was large, highly elevated from 10 to 1 o’clock, avascular, thin wall, and cystic with leaking points. Combined surgery of low-setting phacoemulsification and amniotic membrane transplantation without excising and manipulating the bleb was performed in the same setting. At postoperative 1 month, 6 months, and 1 year, her right vision had improved to 6/24, and the intraocular pressure was 12–14 mmHg, and the bleb leakage had resolved. This successful treatment was accomplished by maintaining the bleb’s viability, preventing additional injury, and promoting wound healing.

This study aims to develop a competitiveness assessment index for global aviation training organizations. The study utilizes the four factors of the Diamond model developed by Michael Porter. To select candidate indices, expert consultations were made, and two stages of Delphi survey were conducted on 24 experts in the area of global aviation training and education. Finally, 19 indices were selected for analysis. In order to assess the reliability of the final indices and justify selection, an empirical study was conducted with 100 participants, yielding statistically significant results. The 19 indices were organized into a three-level hierarchy system, and an analytical hierarchy process (AHP) was conducted to evaluate the importance of each index. The results of the AHP indicated that 'quality of instructors' was the most important index, followed by 'feedback from trainees for the course (level of satisfaction with the course)' and 'director's management skills and leadership'. This study will contribute to enhancing the competitiveness of global aviation training organizations.

This study addresses the adoption intention of ANA Chatbot, developed as part of the ''Chup! Jom Sembang Seks'' (translated as ''Wait a minute! Let's Talk about Sex'') campaign in Malaysia. ANA Chatbot provides youths with comprehensive sexual and reproductive health (SRH) information, empowering them in this vital aspect of their lives. Despite the emerging interest in chatbots conveying SRH information, research on the factors affecting the technology's adoption remains scarce. This paper proposes an adoption model straddling AI attributes (perceived intelligence and anthropomorphism), relational elements (perceived risk and trust), and the UTAUT's factors (performance expectancy, effort expectancy, social influence, and facilitating conditions). We empirically analyzed the model using Partial Least Squares Structural Equation Modelling based on 243 valid responses from participants engaging with ANA Chatbot. The results indicate that perceived intelligence positively relates to anthropomorphism, functional elements (performance expectancy and effort expectancy), trust, and SRH chatbot adoption intention. Anthropomorphism enhances performance expectancy but does not affect effort expectancy, trust, and SRH chatbot adoption intention. Performance expectancy, effort expectancy, facilitating conditions, and social influence are antecedents to ANA Chatbot adoption intention, thus affirming the UTAUT model. Contrary to predictions, perceived risk and trust do not influence the intention to adopt ANA Chatbot. Overall, this study contributes theoretical knowledge concerning AI-centric technology adoption models with a unique and novel focus on an SRH chatbot while providing pragmatic recommendations for promoting SRH chatbot adoption intention.

Changes in zooplankton composition, abundance, and some species in response to environmental variation were investigated over four seasons (2020) in Daya Bay. In total, 129 taxa of zooplankton (16 groups of planktonic larvae and 20 indeterminate species) were identified. Zooplankton communities exhibited a significant seasonal shift in abundance and taxonomic composition. The maximum number of zooplankton species was recorded in winter (72 species) and the lowest in spring (42 species). However, the abundance was highest in spring (1,372.01 ± 1,071.14 individuals/m³) and lowest in autumn (50.93 ± 34.05 individuals/m³). Pearson correlation analyses demonstrated that the zooplankton abundance and the variations of indicator species were obviously correlated with environmental parameters (e.g., salinity, temperature, pH, and chlorophyll-a). Based on specificity and occupancy analysis, a total of eight species were selected as indicator species. It is noteworthy that some kollaplankton (such as Dolioletta gegenbauri and Doliolum denticulatum) could potentially cause disaster to the nuclear power plant cooling system because of their relatively large body size and huge blooms in spring. In addition, Centropages tenuiremis blooms in spring and Penilia avirostris blooms in summer could attract assemblages of larval or adult pelagic fish, which would also threaten the cooling system security in Daya Bay. In conclusion, our results suggest that zooplankton communities and some species may be considered as favorable indicators of the marine environment.

Volume parameters such as the volume of voids (VV), voids filled with asphalt (VFA), and voids in mineral aggregates (VMA) all have significant impact on asphalt mixtures. In this study, the vertical vibration compaction method (VVCM) was employed to produce a large-particle-size asphalt mixture (LSAM-50). The correlations between the mechanical strengths of VVCM specimens, static compression test (PCT) specimens, and in situ core samples were verified. Additionally, the influence of volumetric parameters on the mechanical properties of VVCM specimens was assessed. Based on the principle of optimal mechanical properties, volume parameter design standards for the LSAM-50 asphalt mixture were proposed. Results indicated that the mechanical properties correlation between VVCM specimens and in situ core samples was substantial, reaching over 90%. With increasing VV and VFA, the compressive strength, splitting strength, and dynamic stability of the LSAM-50 asphalt mixture initially increased and then decreased. The design standards for VV were proposed to be between 3.5% and 4.8%, and for VFA between 49.7% and 52.9%. There was no clear correlation between VMA and the mechanical properties of the mixture; hence, based on the standards, the minimum design value for VMA was set at 7.5%. [ABSTRACT FROM AUTHOR]

Approximation frameworks for phase-field models of brittle fracture are presented and compared in this work. Such methods aim to address the computational cost associated with conducting full-scale simulations of brittle fracture in heterogeneous materials where material parameters, such as fracture toughness, can vary spatially. They proceed by combining a dimension reduction with learning between function spaces. Two classes of approximations are considered. In the first class, deep learning models are used to perform regression in ad hoc latent spaces. PCA-Net and Fourier neural operators are specifically presented for the sake of comparison. In the second class of techniques, statistical sampling is used to approximate the forward map in latent space, using conditioning. To ensure proper measure concentration, a reduced-order Hamiltonian Monte Carlo technique (namely, probabilistic learning on manifold) is employed. The accuracy of these methods is then investigated on a proxy application where the fracture toughness is modeled as a non-Gaussian random field. It is shown that the probabilistic framework achieves comparable performance in the L2 sense while enabling the end-user to bypass the art of defining and training deep learning models. [ABSTRACT FROM AUTHOR]