Diffusion-Limited Crystal Growth of Gallium Nitride Using Active Machine Learning

Gallium nitride (GaN) is an important semiconductor with properties that make it particularly suitable for high-temperature applications in power systems. Unfortunately, its crystalline synthesis involves an energy-intensive process requiring high temperatures and pressures. A new additive manufacturing process offers a lower-temperature alternative, but little is understood of the molecular-scale mechanisms that drive its crystallization from the melt. Traditional semiempirical force fields within a molecular dynamics (MD) simulation are typically unable to capture bond-making and -breaking, whereas ab initio MD, while more accurate, suffers from high computational expense. This paper uses a machine-learned force field based on the FLARE++ framework to mimic the liquid-phase epitaxy of GaN, simulating the diffusion of nitrogen atoms through liquid gallium to form GaN. We show that nitrogen diffusion through Ga is slow, and relatedly, there is a pronounced tendency for nitrogen to phase-segregate within liquid Ga. This leads to nitrogen being less available to react and form crystalline GaN. As a result, the predicted crystal growth at the melt/crystal interface is extremely slow, as seen experimentally. In this work, we demonstrate the potential of a MLFF to describe complex, multiphase behavior under different conditions. We also uncover the key atomistic-level mechanism of diffusion-limited GaN crystal growth, which is an important step toward further control of the additive manufacturing process

DataSheet_1_A bidirectional causal relationship study between mental disorders and male and female infertility.docx

BackgroundThe relation between mental disorders (MDs) and infertility can be reciprocal. But exactly which MD affects infertility remains controversial. Our aim was to use Mendelian randomization (MR) to explore bidirectional causality between 15 MDs and male infertility and female infertility.MethodsThe data of MDs, male infertility, and female infertility were derived from published genome-wide association studies (GWAS). The inverse variance weighted method was considered to be the main analytical approach. Sensitivity analysis was performed using MR-Egger, Cochran’s Q, radial MR, and MR-PRESSO tests.ResultsOur results found that mood disorders (OR, 1.4497; 95% CI, 1.0093 – 2.0823; P = 0.0444) and attention deficit hyperactivity disorder (OR, 1.3921; 95% CI, 1.0943 – 1.7709; P = 0.0071) were positively correlated with male infertility, but obsessive-compulsive disorder (OR, 0.8208; 95% CI, 0.7146 – 0.9429; P = 0.0052) was negatively associated with male infertility. For females, anorexia nervosa (OR, 1.0898; 95% CI, 1.0070 – 1.1794; P = 0.0329), attention deficit hyperactivity disorder (OR, 1.1013; 95% CI, 1.0041 – 1.2079; P = 0.0406), and major depressive disorder (OR, 1.1423; 95% CI, 1.0213 – 1.2778; P = 0.0199) increased risk of infertility. In reverse relationship, female infertility increased the incidence of bipolar disorder (OR, 1.0009; 95% CI, 1.0001 – 1.0017; P = 0.0281).ConclusionWe demonstrated the association between five MDs and male or female infertility. Female infertility was also found to be associated with an increased risk of one MD. We look forward to better designed epidemiological studies to support our results.</p

Datasheet1_“LEARN”, a novel teaching method for Chinese clinical clerkship: A cross-sectional study.docx

BackgroundDespite the clerkship being crucial in the training of a future doctor, no widely accepted education model has been proposed. This study devised a new model for clinical clerkship rotations, titled “LEARN” for Lecture, English-video, Advisor, Real-case and Notion, and evaluated whether the LEARN model is appropriate for medical education in China.MethodsA cross-sectional study was performed among 101 fourth-year students from the Xiangya School of Medicine during an Orthopaedic Surgery clerkship rotation in the Third Xiangya Hospital. They were divided into seven groups and took clerkship based on the LEARN model. A questionnaire was collected at the conclusion to measure learning outcomes.ResultsThe LEARN model was highly accepted with the acceptance of five sessions being 95.92% (94/98), 93.88% (92/98), 96.98% (97/98), 100% (98/98) and 96.94% (95/98). The outcomes of two genders were comparable, whereas a difference was observed in the test score among groups (group 3 scored 93.93 ± 5.20, higher than others). Quantitative analysis showed that positive correlations existed in participation in the Notion (Notion means students’ case discussion) section with leadership (r = 0.84, 95% CI: 0.72–0.94, p ConclusionOur results support the LEARN model is a promising method for medical clerkship in China. Further research involving more participants and more meticulous design is planned to test its efficacy. For refinement, educators may try to promote students’ participation in the English-video session.</p

DataSheet_1_Mendelian randomization reveals the impact of diet on infertility in men and women.docx

BackgroundAlthough studies on the effects of diet on fertility has progressed, some cumulative evidence has piled against popular hypotheses. The aim of our study was to investigate the effects of 31 diets including 23 individual dietary intakes and 8 dietary habits on infertility in men and women.MethodsThe datas of diets and infertility were collected from genome-wide association studies (GWAS). Mendelian randomization (MR) methods were used to analyze causal relationships. Multivariate MR (MVMR) adjusted for the effects of other exposures on causality. And MR-Egger, Cochran’s Q, radial MR, and MR-PRESSO tests were employed to assess heterogeneity and horizontal pleiotropy.ResultsOur study found that coffee intake (OR, 3.6967; 95% CI, 1.0348 – 13.2065; P = 0.0442) and cooked vegetable intakes (OR, 54.7865; 95% CI, 2.9011 – 1030.5500; P = 0.0076) increased the risk of male infertility. For women, beer was a risk factor for infertility (OR, 4.0932; 95% CI, 1.8728 – 8.9461; P = 0.0004); but processed meat was negatively associated with infertility (OR, 0.5148; 95% CI, 0.2730 – 0.9705; P = 0.0401). MVMR demonstrated selenium as a protective factor against female infertility (OR, 7.4474e-12; 95% CI, 5.4780e-22 – 1.0125e-01; P = 0.0314).ConclusionWe found the causal relationships between four diets and infertility. We look forward to more high-quality epidemiologic studies to prove our conclusions.</p

Transferable Force Field for Gallium Nitride Crystal Growth from the Melt Using On-The-Fly Active Learning

Atomic-scale simulations of reactive processes have been stymied by two factors: the lack of a suitable semiempirical force field on one hand and the impractically large computational burden of using ab initio molecular dynamics on the other hand. In this paper, we use an “on-the-fly” active learning technique to develop a nonparameterized force field that, in essence, exhibits the accuracy of density functional theory and the speed of a classical molecular dynamics simulation. We developed a force field capable of capturing the crystallization of gallium nitride (GaN) during a novel additive manufacturing process featuring the reaction of liquid Ga and gaseous nitrogen precursors to grow crystalline GaN thin films. We show that this machine learning model is capable of producing a single force field that can model solid, liquid, and gas phases involved in the process. We verified our computational predictions against a range of experimental measurements relevant to each phase and against ab initio calculations, showing that this nonparametric force field produces properties with excellent accuracy as well as exhibits computationally tractable efficiency. The force field is capable of allowing us to simulate the solid–liquid coexistence interface and the crystallization of GaN from the melt. The development of this transferable force field opens the opportunity to simulate the liquid-phase epitaxial growth more accurately than before to analyze reaction and diffusion processes and ultimately to establish a growth model of the additive manufacturing process to create the gallium nitride thin films

Annulation Reaction of 3‑Acylmethylidene Oxindoles with Huisgen Zwitterions and Its Applications in the Syntheses of Pyrrolo[4,3,2-<i>de</i>]quinolinones and Marine Alkaloids Ammosamides

A novel annulation reaction of 3-acylmethylidene oxindoles with Huisgen zwitterions is unveiled that leads to an unprecedented synthetic method for complex pyrrolo­[4,3,2-<i>de</i>]­quinolinones and marine alkaloids ammosamides A–C. This method features simplicity, high efficiency, and broad substrate scope and is accordingly anticipated to significantly facilitate the preparation and bioassay of the relevant pyrroloquinoline alkaloids and their analogues

Presentation1_“LEARN”, a novel teaching method for Chinese clinical clerkship: A cross-sectional study.pdf

BackgroundDespite the clerkship being crucial in the training of a future doctor, no widely accepted education model has been proposed. This study devised a new model for clinical clerkship rotations, titled “LEARN” for Lecture, English-video, Advisor, Real-case and Notion, and evaluated whether the LEARN model is appropriate for medical education in China.MethodsA cross-sectional study was performed among 101 fourth-year students from the Xiangya School of Medicine during an Orthopaedic Surgery clerkship rotation in the Third Xiangya Hospital. They were divided into seven groups and took clerkship based on the LEARN model. A questionnaire was collected at the conclusion to measure learning outcomes.ResultsThe LEARN model was highly accepted with the acceptance of five sessions being 95.92% (94/98), 93.88% (92/98), 96.98% (97/98), 100% (98/98) and 96.94% (95/98). The outcomes of two genders were comparable, whereas a difference was observed in the test score among groups (group 3 scored 93.93 ± 5.20, higher than others). Quantitative analysis showed that positive correlations existed in participation in the Notion (Notion means students’ case discussion) section with leadership (r = 0.84, 95% CI: 0.72–0.94, p ConclusionOur results support the LEARN model is a promising method for medical clerkship in China. Further research involving more participants and more meticulous design is planned to test its efficacy. For refinement, educators may try to promote students’ participation in the English-video session.</p

The structural basis of the autoinhibition mechanism of glycogen synthase kinase 3β (GSK3β): molecular modeling and molecular dynamics simulation studies

The autoinhibition phenomenon has been frequently observed in enzymes and represents an important regulatory strategy to fine-tune enzyme activity. Evolution has exploited this mechanism to reduce enzymatic activity. Glycogen synthase kinase 3β (GSK3β) undergoes autoinhibition via the phosphorylation of Ser9 at the N-terminus of the kinase, which, acting as a pseudosubstrate, occupies the catalytic domain of GSK3β and subsequently blocks primed substrates from having access to the catalytic domain. The detailed structural basis of the autoinhibition mechanism of GSK3β by the pseudosubstrate, however, has not yet been fully resolved. Here, a three-dimensional model of the binary GSK3β-pseudosubstrate complex was built via the molecular modeling method. Based on the constructed model, extensive molecular dynamics (MD) simulations and subsequent molecular mechanics generalized Born/surface area (MM_GBSA) calculations were performed on the wild-type GSK3β-pseudosubstrate complex and three mutated systems (R4A, R6A, and S9A). Analyses of MD simulations and binding free energies revealed that the phosphorylation of Ser9 is the prerequisite for the autoinhibition of GSK3β, and both mutations of Arg4 and Arg6 to alanine markedly reduced the binding affinities of the mutated pseudosubstrate to the GSK3β catalytic domain, thereby disrupting the autoinhibition of the kinase. This study highlights the importance of Ser9, Arg6, and Arg4 in modulating the autoinhibition mechanism of GSK3β, contributing to a deeper understanding of GSK3β biology. Communicated by Ramaswamy H. Sarma</p

Table_1_The role of education attainment on 24-hour movement behavior in emerging adults: evidence from a population-based study.docx

PurposeThe purpose of this study was to explore the relationship between education level and health behavior including sleep, work activity, exercise activity, and sedentary behavior among emerging adults.MethodsThis study utilized data from the National Health and Nutrition Examination Survey (NHANES) collected between 2007 and 2018. The study sample included 4,484 emerging adults aged 18–25 years and the weighted participants were 30,057,813. Weighted multivariable regression analysis was performed to investigate the association between education level and the aforementioned health behavior, adjusting for age, gender, race/ethnicity, marital status, poverty-income ratio, BMI, smoking, and alcohol drinking status.ResultsThis study revealed that higher education level was associated with shorter sleep duration [Fully adjusted model, β (95% CI): −0.588 (−0.929, −0.246), p ConclusionThis study highlighted the importance of education level as a significant factor in promoting healthy behavior among emerging adults. The findings underscored the need for the Ministry of Education to prioritize educating this demographic about the significance of maintaining adequate sleep patterns and reducing sedentary habits. Encouraging them to allocate more time for work and physical activities can significantly contribute to their overall wellbeing and success, ultimately fostering a healthier next generation.</p

Quality of life and its influencing factors on children with asthma in China: a comparative study before and during the COVID-19 pandemic

This study compares the level of quality of life (QoL) and its influencing factors on children with asthma before and during the COVID-19 pandemic. The study carried out cross-sectional surveys on children with asthma and their parents in China before and during the epidemic. Data were collected using a demographic questionnaire, the Family Management Scale for Children with Asthma (FMSCA), and the Pediatric Asthma Quality of Life Questionnaire (PAQLQ). Participants from before the epidemic were matched by their propensity score in a 1:1 ratio with individuals from during the epidemic. The level of QoL of children with asthma was subsequently analyzed. Both univariate analysis and multiple linear regression were employed to identify the influencing factors. Compared to their level before the epidemic, the total score of PAQLQ and its three dimensions decreased during the epidemic. Regression analysis revealed that before the epidemic, the total score of PAQLQ was significantly associated with follow-up visits, attendance of asthma lectures, and the total score of FMSCA (p p  The QoL of children with asthma deteriorated during the epidemic. Influencing factors changed during the epidemic, with more emphasis on the family environment. Future intervention strategies need to take into account the development of interactions between children and environmental forces.</p