A Future for the Chinese Diaspora and Australia: Great Story and the Golden Rule

Chinese in Australia have grown into a variegated diaspora with a mainland-born majority. Diasporas are channels of cultural, economic and political influence; and seen as such by sending and receiving countries. They interact in international cultural relations between sending and receiving countries, as expressions of civic virtue oriented to either or both. Cooperative interactions between the respective countries can bring prosperity to all; but when security considerations cast clouds over relations between countries, the concerned countries and communities have careful paths to tread. This input visits the Chinese diaspora past and present. It emphasises the rules of friendship and hospitality as guiding principles for healthy international cultural relations

A010: The Effect of Coordinated Bilateral Movements on Selective Attention in Fourth Graders

Introduction: Selective attention is a core component of children and adolescents\u27 intelligence and a source of individual differences. The status of selective attention of children and adolescents in China is not optimistic. In foreign countries, coordinated bilateral movement can help improve children’s and adolescents\u27 attention. The fact that Chinese parents, schools, and society know little about coordinated bilateral movement, teachers in Chinese physical education and health programs almost never intentionally train students in this area. Objectives: The purpose of this study was to explore whether coordinated bilateral exercise can improve the selective attention levels of Chinese children and adolescents, so as to facilitate parents and schools to convey a healthy and effective learning and living method for students to carry out efficient exercise. Methods: In this experimental study, various measurement methods and mathematical statistics methods were adopted using the d2 attention test scale as a measurement tool. Fourth grade students of Shenzhen Longhua Central Primary School from class 1 to class 4 were selected as the experimental participants, with 49 students allocated to the experimental class (class 1 and class 2) and 49 students to the control class (class 2 and class 3), with a total of 92 students within the sample. Data were analyzed using SPSS 23.0 software to explore the factors affecting the changes in students\u27 selective attention using analysis of variance tests (ANOVA), repeated measures ANOVA, and paired samples t-tests. Results: There were significant intervention main effects on centralized performance CP (F=6.73, p = 0.003, η² = 0.149) and accuracy E% (F=6.94, p = 0.023, η² = 0.11). There were also significant time main effects on processing speed TN (F=104.72, p \u3c 0.001), overall performance TN-E (F=118.90, p \u3c 0.001), focused performance CP (F=76.37, p \u3c 0.001), processing error rate E% (F=38.95, p \u3c 0.001), and attentional span FR (F=15.61, p \u3c 0.001). Conclusion: The inclusion of short bursts of coordinated bilateral movements to break up classroom routines helped children to maintain and improve their concentration. By helping children find better ways to learn, schools can reduce more self-control issues, which in turn improved the academic performance of all pupils. Engaging pupils in coordinated bilateral movements is an effective strategy for improving the selective attention of children and adolescents

Filamentation and inhibition of prokaryotic CTP synthase with ligands

Cytidine triphosphate synthase (CTPS) plays a pivotal role in the de novo synthesis of cytidine triphosphate (CTP), a fundamental building block for RNA and DNA that is essential for life. CTPS is capable of directly binding to all four nucleotide triphosphates: adenine triphosphate, uridine triphosphate, CTP, and guanidine triphosphate. Furthermore, CTPS can form cytoophidia in vivo and metabolic filaments in vitro, undergoing regulation at multiple levels. CTPS is considered a potential therapeutic target for combating invasions or infections by viral or prokaryotic pathogens. Utilizing cryo‐electron microscopy, we determined the structure of Escherichia coli CTPS (ecCTPS) filament in complex with CTP, nicotinamide adenine dinucleotide (NADH), and the covalent inhibitor 6‐diazo‐5‐oxo‐ l‐norleucine (DON), achieving a resolution of 2.9 Å. We constructed a phylogenetic tree based on differences in filament‐forming interfaces and designed a variant to validate our hypothesis, providing an evolutionary perspective on CTPS filament formation. Our computational analysis revealed a solvent‐accessible ammonia tunnel upon DON binding. Through comparative structural analysis, we discern a distinct mode of CTP binding of ecCTPS that differs from eukaryotic counterparts. Combining biochemical assays and structural analysis, we determined and validated the synergistic inhibitory effects of CTP with NADH or adenine on CTPS. Our results expand our comprehension of the diverse regulatory aspects of CTPS and lay a foundation for the design of specific inhibitors targeting prokaryotic CTPS

The In-Sample Softmax for Offline Reinforcement Learning

Reinforcement learning (RL) agents can leverage batches of previously collected data to extract a reasonable control policy. An emerging issue in this offline RL setting, however, is that the bootstrapping update underlying many of our methods suffers from insufficient action-coverage: standard max operator may select a maximal action that has not been seen in the dataset. Bootstrapping from these inaccurate values can lead to overestimation and even divergence. There are a growing number of methods that attempt to approximate an \emph{in-sample} max, that only uses actions well-covered by the dataset. We highlight a simple fact: it is more straightforward to approximate an in-sample \emph{softmax} using only actions in the dataset. We show that policy iteration based on the in-sample softmax converges, and that for decreasing temperatures it approaches the in-sample max. We derive an In-Sample Actor-Critic (AC), using this in-sample softmax, and show that it is consistently better or comparable to existing offline RL methods, and is also well-suited to fine-tuning

Research progress and prospects of utilizing carbon-based nanomaterials in enhanced oil recovery

Carbon-based nanomaterials have received heightened global interest by petroleum researchers because of their abundant stocks of necessary raw materials, ease of size control, readiness for modification, and high stability. In light of the practical demand for oil development, this study reviews the recent progress in the research of enhancing oil recovery using carbon-based nanomaterials of various dimensions, including carbon dots, carbon nanotubes, carbon nanofibers, and graphene and its derivatives. Moreover, the study elaborates on the application of these materials in high-efficiency oil displacement, profile control and water shutoff, as well as the fracturing process. The related challenges and solutions in practical oil exploration and development are analyzed, and the application prospects of these materials in future oil reservoirs and oilfields are predicted. This review provides valuable theoretical and experimental references for the large-scale application of carbon-based nanomaterials.Document Type: Invited reviewCited as: Shen, M., Zhang, C., Yan, X., Wang, L., Wu, Y., Jin, X. Research progress and prospects of utilizing carbon-based nanomaterials in enhanced oil recovery. Advances in Geo-Energy Research, 2024, 14(3): 201-214. https://doi.org/10.46690/ager.2024.12.0

HarmonyDream: Task Harmonization Inside World Models

Model-based reinforcement learning (MBRL) holds the promise of sample-efficient learning by utilizing a world model, which models how the environment works and typically encompasses components for two tasks: observation modeling and reward modeling. In this paper, through a dedicated empirical investigation, we gain a deeper understanding of the role each task plays in world models and uncover the overlooked potential of sample-efficient MBRL by mitigating the domination of either observation or reward modeling. Our key insight is that while prevalent approaches of explicit MBRL attempt to restore abundant details of the environment via observation models, it is difficult due to the environment's complexity and limited model capacity. On the other hand, reward models, while dominating implicit MBRL and adept at learning compact task-centric dynamics, are inadequate for sample-efficient learning without richer learning signals. Motivated by these insights and discoveries, we propose a simple yet effective approach, HarmonyDream, which automatically adjusts loss coefficients to maintain task harmonization, i.e. a dynamic equilibrium between the two tasks in world model learning. Our experiments show that the base MBRL method equipped with HarmonyDream gains 10%-69% absolute performance boosts on visual robotic tasks and sets a new state-of-the-art result on the Atari 100K benchmark. Code is available at https://github.com/thuml/HarmonyDream.Comment: ICML 2024. Code is available at https://github.com/thuml/HarmonyDrea

Impact of apolipoprotein A1 on tumor immune microenvironment, clinical prognosis and genomic landscape in hepatocellular carcinoma

Background: Current knowledge on apolipoprotein A1 (APOA1) in hepatocellular carcinoma (HCC) is fragmented and even contradictory. Multi-dimensional analyses are required to comprehensively elucidate its value and underlying mechanism. Methods: We collected 49 RNA-seq datasets, 40 cell line types data and 70 scRNA pan-cancer datasets public available, including 17 HCC datasets (1754 tumor samples), and enrolled 73 pairs of HCC tissue and 516 blood samples independently from our clinics. APOA1 impacting on the HCC tumor microenvironment (TME) was analyzed using intensive data mining. Methylation sequencing, flow cytometry, quantitative PCR, western blot, immunohistochemistry and clinical chemistry assays were conducted for wet experimental investigation. Results: The APOA1 ontology fingerprint indicated that it played various crucial biological roles in HCC, primarily involved in cholesterol efflux. Consistent findings at histology, serology, and clinical follow-up revealed that high APOA1 was a good prognosis indicator of HCC. Hypermethylation in the APOA1 promoter region was found in clinical samples which is in accordance with the reduction of APOA1 in HCC. The cell cycle, DNA replication, mismatch repair pathways, and tumor cell proliferation were less observed in the HCC APOA1high subgroup. The favorable immunoregulatory abilities of APOA1 showed interesting findings: A positive correlation between APOA1 and anti-Tumor immune cells (NK, CD8+ T cells) and a negative association with immune cells exerting immunosuppressive effects, including M2 macrophages. Conclusion: This is an integrative multidimensional exploration of APOA1 using bioinformatics and experiments. Both the prognostic value and anti-Tumor effects based on APOA1 panoramic exploration in the HCC TME demonstrate a new potential clinical target for HCC assessment and intervention in the future.</p