基于文化自信的中外合作办学学科基础课“General Chemistry”课程思政建设探索与实践

“General Chemistry”是面向中外合作办学工科专业学生开设的一门学科基础课。为了提升教学质量,课程引入国外经典教材,在教学过程中面临外来文化的冲击和文化自信缺失的风险。因此,必须通过“General Chemistry”课程思政教学提升学生对自身文化的深度认同。本文中,“General Chemistry”课程思政建设坚持文化自信理念,积极挖掘中国思政元素,将中外思政元素合理融入到教学的每一个环节,不断助推课程思政教学内涵式发展,打造课程思政高效课堂,取得了较好的育人成效。

Defect chemistry for extrinsic doping in ductile semiconductor α-Ag_(2)S

As a new type of inorganic ductile semiconductor,silver sulfide(α-Ag_(2)S)has garnered a plethora of interests in recent years due to its promising applications in flexible electronics.However,the lack of detailed defect calculations and chemical intuition has largely hindered the optimization of material's performance.In this study,we systematically investigate the defect chemistry of extrinsic doping inα-Ag_(2)S using first-principles calculations.We computationally examine a broad suite of 17 dopants and find that all aliovalent elements have extremely low doping limits(<0.002%)in α-Ag_(2)S,rendering them ineffective in tuning the electron concentrations.In contrast,the isovalent elements Se and Te have relatively high doping limits,being consistent with the experimental observations.While the dopant Se or Te itself does not provide additional electrons,its introduction has a significant impact on the band gap,the band-edge position,and especially the formation energy of Ag interstitials,which effectively improve the electron concentrations by 2–3 orders of magnitudes.The size effects of Se and Te doping are responsible for the more favorable Ag interstitials in Ag_(2)S_(0.875)Se_(0.125) and Ag_(2)S_(0.875)Te_(0.125) with respect to pristine Ag2S.This work serves as a theoretical foundation for the rational design of Ag_(2)S-based functional materials.

A micro-crosslinked amphoteric hydrophobic association copolymer as high temperature-and salt-resistance fluid loss reducer for water-based drilling fluids

During ultradeep oil and gas drilling,fluid loss reducers are highly important for water-based drilling fluids,while preparing high temperature-and salt-resistance fluid loss reducers with excellent rheology and filtration performance remains a challenge.Herein,a micro-crosslinked amphoteric hydrophobic association copolymer(i.e.,DADC)was synthesized using N,N-dimethyl acrylamide,diallyl dimethyl ammonium chloride,2-acrylamido-2-methylpropane sulfonic acid,hydrophobic monomer,and pentaerythritol triallyl ether crosslinker.Due to the synergistic effects of hydrogen bonds,electrostatic interaction,hydrophobic association,and micro-crosslinking,the DADC copolymer exhibited outstanding temperature-and salt-resistance.The rheological experiments have shown that the DADC copolymer had excellent shear dilution performance and a certain degree of salt-responsive viscosity-increasing performance.The DADC copolymer could effectively adsorb on the surface of bentonite particles through electrostatic interaction and hydrogen bonds,which bring more negative charge to the bentonite,thus improving the hydration and dispersion of bentonite particles as well as the colloidal stability of the drilling fluids.Moreover,the drilling fluids constructed based on the DADC copolymer exhibited satisfactory rheological and filtration properties(FLHTHP=12 m L)after aging at high temperatures(up to200℃)and high salinity(saturated salt)environments.Therefore,this work provided new insights into designing and fabricating high-performance drilling fluid treatment agents,demonstrating good potential applications in deep and ultradeep drilling engineering.

MXenes: Versatile 2D materials with tailored surface chemistry and diverse applications

MXenes,the most recent addition to the 2D material family,have attracted significant attention owing to their distinctive characteristics,including high surface area,conductivity,surface characteristics,mechanical strength,etc.This review begins by presenting MXenes,providing insights into their structural characteristics,synthesis methods,and surface functional groups.The review covers a thorough analysis of MXene surface properties,including surface chemistry and termination group impacts.The properties of MXenes are influenced by their synthesis,which can be fluorine-based or fluorinedependent.Fluorine-based synthesis techniques involve etching with fluorine-based reagents,mainly including HF or LiF/HCl,while fluorine-free methods include electrochemical etching,chemical vapor deposition(CVD),alkaline etching,Lewis acid-based etching,etc.These techniques result in the emergence of functional groups such as-F,-O,-OH,-Cl,etc.on the MXenes surface,depending on the synthesis method used.Properties of MXenes,such as electrical conductivity,electronic properties,catalytic activity,magnetic properties,mechanical strength,and chemical and thermal stability,are examined,and the role of functional groups in determining these properties is explored.The review delves into the diverse applications of MXenes,encompassing supercapacitors,battery materials,hydrogen storage,fuel cells,electromagnetic interference(EMI) shielding,pollutant removal,water purification,flexible electronics,sensors,additive manufacturing,catalysis,biomedical and healthcare fields,etc.Finally,this article outlines the challenges and opportunities in the current and future development of MXenes research,addressing various aspects such as synthesis scalability,etching challenges,and multifunctionality,and exploring novel applications.The review concludes with future prospects and conclusions envisioning the impact of MXenes on future technologies and innovation.

Distribution and dynamics of niche and interspecific association of dominant phytoplankton species in the Feiyun River basin,Zhejiang,China

To investigate the dominant species and interspecific association in the phytoplankton community of the Feiyun River basin in Zhejiang Province,East China,the main stream and the Shanxi Zhaoshandu Reservoir in the downstream were chosen as the study area,for which 22 sampling sites were designated.Sampling was conducted in September 2021,January,May,and July 2022.Phytoplankton species were identified from both quantitative samples and in-vivo observations.Phytoplankton was quantified by direct counting.Results show that there were 98 species belonging to 6 phyla and 78 genera.In addition,to clarify the niches of the dominant phytoplankton species and their interspecific association,the dominance index was calculated,and a comprehensive analysis was conducted including niche width,niche overlap value,ecological response rate,overall association,chi-square test,and the stability.The phytoplankton community exhibited characteristics of a Cyanobacteria-Chlorophyta-Diatom type community,showing higher diversity in spring and lower diversity in summer.Among 11 dominants phytoplankton species from 3 phyla,both frequency and dominance degree varied seasonally,of which Microcystis sp.was the dominant species in Spring,Autumn,and Winter.The niche widths of the dominant species ranged from 0.234 to 0.933,and were categorized into three groups.The niche overlap values of the 11 dominant species ranged from 0.359 to 0.959,exhibiting significant seasonal differences-highest in winter followed by autumn,spring,and summer in turn.The overall correlation among dominant species in all four seasons revealed a non-significant negative association,resulting in an unstable community structure.A significant portion(84.2%)of species pairs displayed positive associations,suggesting a successional pattern where Diatoms dominated while other dominant species shared resources and space.Despite this pattern,stability measurements indicated that the dominant species community remained unstable.Therefore,careful monitoring is recommended for potential water environment issues arising from abnormal proliferation of dominant species in the watershed during winter.This research built a theoretical foundation with a data support to the early warning of eutrophication and provided a reference for water resources management in similar watersheds along the eastern coast of China.

THAPE: A Tunable Hybrid Associative Predictive Engine Approach for Enhancing Rule Interpretability in Association Rule Learning for the Retail Sector

Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.

Strengthening Active Aging through Older People’s Association and Economic Activity of the Older People in Nepal

Aging is a natural lifelong process ending in death. Many older people are living in poverty. Older people are generally considered dependent on others as they grow older. The purpose of this article is to explore the entrepreneurship activities of Nepalese older adults. Data for this study were collected from the project Help Age International (HAI) implemented in Nepal. Qualitative data observations and interviews were used to collect data. The findings of this study show the formation of the Older People’s Association (OPA) has supported many older people to participate outside the home in various social activities. Moreover, regular deposits through OPAs offer little help. OPAs support older people in their need of financial support to implement minor entrepreneurship. Older people who received support were pleased and were actively involved in their activities and also regularly deposited money in them. Subsequently, older people’s participation in social activities has increased and also helped to lower elderly abuse, loneliness, and depression. Local governments should promote such activities which will help with healthy aging.

Demography and Socio-Economic Aspects on Irrigated Smallholder Agricultural Enterprises and Their Association with the Cultivation of Maize (Zea mays L.) as a Selected Field Crop

The purpose of this study is to correlate demography and socio-economic aspects at Irrigated Smallholder Agricultural Enterprises and their association with the Cultivation of Maize in order to determine its positive impacts at irrigated smallholders’ agricultural entrepreneurs’ household. Chi-square test was used as descriptive analysis method. The Fischer Exact tests were employed to test demography (gender, age, education, and income) in winter and summer production season of irrigated smallholder agricultural enterprises and their association with the cultivation of selected field crop (i.e. maize). The results show that gender results were not being statistically significant, as measured by the Phi measure of effect size, φ = 0.149, p = 0.011, and φ = 0.05, p = 0.392 in summer. As far as age is concern, it appears to be a statistically significant association between cultivating maize and age in winter, φ = 0.046, p = 0.730 in winter and φ = 0.172, p = 0.013. Education winter result not being statistically significant, the effect size showed a weak association, as measured by the Phi measure of effect size, φ = 0.112, p = 0.305 and φ = 0.035, p = 0.948 in summer. Income result not being statistically significant, as measured by the Phi measure of effect size, φ = 0.049, p = 0.399 and φ = 0.081, p = 0.166 in summer. In conclusion, the study shows that the development of best management practices must be based on a comprehensive analysis of the livelihoods and irrigated smallholder agricultural enterprise farming styles of participating irrigated smallholder agricultural entrepreneurs.

Epistasis-aware genome-wide association studies provide insights into the efficient breeding of high-yield and high-quality rice

Marker-assisted selection(MAS)and genomic selection(GS)breeding have greatly improved the efficiency of rice breeding.Due to the influences of epistasis and gene pleiotropy,ensuring the actual breeding effect of MAS and GS is still a difficult challenge to overcome.In this study,113 indica rice varieties(V)and their 565 testcross hybrids(TC)were used as the materials to investigate the genetic basis of 12 quality traits and nine agronomic traits.The original traits and general combining ability of the parents,as well as the original traits and midparent heterosis of TC,were subjected to genome-wide association analysis.In total,381 primary significantly associated loci(SAL)and 1,759 secondary SALs that had epistatic interactions with these primary SALs were detected.Among these loci,322 candidate genes located within or nearby the SALs were screened,204 of which were cloned genes.A total of 39 MAS molecular modules that are beneficial for trait improvement were identified by pyramiding the superior haplotypes of candidate genes and desirable epistatic alleles of the secondary SALs.All the SALs were used to construct genetic networks,in which 91 pleiotropic loci were investigated.Additionally,we estimated the accuracy of genomic prediction in the parent V and TC by incorporating either no SALs,primary SALs,secondary SALs or epistatic effect SALs as covariates.Although the prediction accuracies of the four models were generally not significantly different in the TC dataset,the incorporation of primary SALs,secondary SALs,and epistatic effect SALs significantly improved the prediction accuracies of 5(26%),3(16%),and 11(58%)traits in the V dataset,respectively.These results suggested that SALs and epistatic effect SALs identified based on an additive genotype can provide considerable predictive power for the parental lines.They also provide insights into the genetic basis of complex traits and valuable information for molecular breeding in rice.

Discharge plasma for prebiotic chemistry: Pathways to life’s building blocks

Discharge plasmas, recognized as unique platforms for investigating the origins of chemical life, have garnered extensive interest for their potential to simulate prebiotic conditions. This paper embarks on a comprehensive overview of recent advancements in the plasma-enabled synthesis of life’s building blocks, charting the complex environmental parameters believed to have surrounded life’s inception. This discussion elaborates on the fundamental mechanisms of discharge plasmas and their likely role in fostering conditions necessary for the origin of life on early Earth. We consider a variety of chemical reactions facilitated by plasma, specifically the synthesis of vital organic molecules - amino acids, nucleobases, sugars, and lipids. Further, we delve into the impact of plasmas on prebiotic chemical evolution. We expect this review to open new horizons for future investigations in plasma-related prebiotic chemistry that could offer valuable insights for unraveling the mysteries of life's origin.

Association between Placental Malaria and Severe Pre-Eclampsia in Two University Hospitals of Yaounde City

Context: Pre-eclampsia and placental malaria, are two diseases that share pathophysiological similarities, such as placental ischemia, endothelial dysfunction and production of pro-inflammatory cytokines. Objective: The objective of our study was to investigate the association between placental malaria lesions and severe pre-eclampsia. Methodology: We conducted a prospective analytical cross-sectional study in two University Hospitals in the city of Yaounde (Yaounde Central Hospital and the Gynaecological Obstetrics and Paediatrics Hospital), and in the laboratory of the Centre Pasteur in Yaounde over an eight-month period (1st January 2021 – 1st September 2021). All patients with pre-eclampsia diagnosed according to the criteria of the International Society for the Study of Hypertension (ISSHP) and free of chronic metabolic or infectious pathology were included in this study. The patients were divided into two groups: group 1 (mild pre-eclampsia) and group 2: severe pre-eclampsia. Socio-demographic, clinical and histopathological characteristics specific to pre-eclampsia and placental malaria were investigated. Statistical analysis was performed with SPSS 23.0 software, Chi 2 was used to compare categorical variables, Student t-test was used to compare means, and logistic regression was used to assess the association between placental malaria lesions and PES. Results: The mean age of our study population was 29.93 ± 7.36 years versus 28.28 ± 7.18 years in patients with mild and severe pre-eclampsia respectively. Pre-eclampsia placental lesions (accelerated villous maturation, infarction) were significantly greater in patients with severe pre-eclampsia (p Conclusion: Placental malaria lesions were significantly associated with severe pre-eclampsia and increased the risk of developing severe pre-eclampsia placental lesions by a factor of 10.

Leveraging the potential of big genomic and phenotypic data for genome-wide association mapping in wheat

Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on Central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.Contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.

LQTTrack:Multi-Object Tracking by Focusing on Low-Quality Targets Association

Multi-object tracking(MOT)has seen rapid improvements in recent years.However,frequent occlusion remains a significant challenge in MOT,as it can cause targets to become smaller or disappear entirely,resulting in lowquality targets,leading to trajectory interruptions and reduced tracking performance.Different from some existing methods,which discarded the low-quality targets or ignored low-quality target attributes.LQTTrack,with a lowquality association strategy(LQA),is proposed to pay more attention to low-quality targets.In the association scheme of LQTTrack,firstly,multi-scale feature fusion of FPN(MSFF-FPN)is utilized to enrich the feature information and assist in subsequent data association.Secondly,the normalized Wasserstein distance(NWD)is integrated to replace the original Inter over Union(IoU),thus overcoming the limitations of the traditional IoUbased methods that are sensitive to low-quality targets with small sizes and enhancing the robustness of low-quality target tracking.Moreover,the third association stage is proposed to improve the matching between the current frame’s low-quality targets and previously interrupted trajectories from earlier frames to reduce the problem of track fragmentation or error tracking,thereby increasing the association success rate and improving overall multi-object tracking performance.Extensive experimental results demonstrate the competitive performance of LQTTrack on benchmark datasets(MOT17,MOT20,and DanceTrack).

Achieving asymmetric redox chemistry for oxygen evolution reaction through strong metal-support interactions

Water electrolysis poses a significant challenge for balancing catalytic activity and stability of oxygen evolution reaction(OER)electrocatalysts.In this study,we address this challenge by constructing asymmetric redox chemistry through elaborate surface OO–Ru–OH and bulk Ru–O–Ni/Fe coordination moieties within single-atom Ru-decorated defective NiFe LDH nanosheets(Ru@d-NiFe LDH)in conjunction with strong metal-support interactions(SMSI).Rigorous spectroscopic characterization and theoretical calculations indicate that single-atom Ru can delocalize the O 2p electrons on the surface and optimize d-electron configurations of metal atoms in bulk through SMSI.The^(18)O isotope labeling experiment based on operando differential electrochemical mass spectrometry(DEMS),chemical probe experiments,and theoretical calculations confirm the encouraged surface lattice oxygen,stabilized bulk lattice oxygen,and enhanced adsorption of oxygen-containing intermediates for bulk metals in Ru@d-NiFe LDH,leading to asymmetric redox chemistry for OER.The Ru@d-NiFe LDH electrocatalyst exhibits exceptional performance with an overpotential of 230 mV to achieve 10 mA cm^(−2)and maintains high robustness under industrial current density.This approach for achieving asymmetric redox chemistry through SMSI presents a new avenue for developing high-performance electrocatalysts and instills confidence in its industrial applicability.

Why the abnormal phenomena of D-band center theory exist?A new BASED theory for surface catalysis and chemistry

Since the D-band center theory was proposed,it has been widely used in the fields of surface chemistry by almost all researchers,due to its easy understanding,convenient operation and relative accuracy.However,with the continuous development of material systems and modification strategies,researchers have gradually found that D-band center theory is usually effective for large metal particle systems,but for small metal particle systems or semiconductors,such as single atom systems,the opposite conclusion to the D-band center theory is often obtained.To solve the issue above,here we propose a bonding and anti-bonding orbitals stable electron intensity difference(BASED)theory for surface chemistry.The newly-proposed BASED theory can not only successfully explain the abnormal phenomena of D-band center theory,but also exhibits a higher accuracy for prediction of adsorption energy and bond length of intermediates on active sites.Importantly,a new phenomenon of the spin transition state in the adsorption process is observed based on the BASED theory,where the active center atom usually yields an unstable high spin transition state to enhance its adsorption capability in the adsorption process of intermediates when their distance is about 2.5Å.In short,the BASED theory can be considered as a general principle to understand catalytic mechanism of intermediates on surfaces.

Genome-Wide Association Study of Cooked Rice Textural Attributes and Starch Physicochemical Properties in indica Rice

Rice cooking and eating qualities(CEQ)are mainly determined by cooked rice textural parameters and starch physicochemical properties.However,the genetic bases of grain texture and starch properties in rice have not been fully understood.We conducted a genome-wide association study for apparent amylose content(AAC),starch pasting viscosities,and cooked rice textural parameters using 279 indica rice accessions from the 3000 Rice Genome Project.We identified 26 QTLs in the whole population and detected single nucleotide polymorphisms(SNPs)with the lowest P-value at the Waxy(Wx)locus for all traits except pasting temperature and cohesiveness.Additionally,we detected significant SNPs at the SUBSTANDARD STARCH GRAIN6(SSG6)locus for AAC,setback(SB),hardness,adhesiveness,chewiness(CHEW),gumminess(GUM),and resilience.We subsequently divided the population using a SNP adjacent to the Waxy locus,and identified 23 QTLs and 12 QTLs in two sub-panels,WxT and WxA,respectively.In these sub-panels,SSG6 was also identified to be associated with pasting parameters,including peak viscosity,hot paste viscosity,cold paste viscosity,and consistency viscosity.Furthermore,a candidate gene encoding monosaccharide transporter 5(OsMST5)was identified to be associated with AAC,breakdown,SB,CHEW,and GUM.In total,39 QTLs were co-localized with known genes or previously reported QTLs.These identified genes and QTLs provide valuable information for genetic manipulation to improve rice CEQ.

Tree mycorrhizal associations determine how biodiversity,large trees,and environmental factors drive aboveground carbon stock in temperate forests

Biodiversity,large trees,and environmental conditions such as climate and soil have important effects on forest carbon stocks.However,recent studies in temperate forests suggest that the relative importance of these factors depends on tree mycorrhizal associations,whereby large-tree effects may be driven by ectomycorrhizal(EM)trees,diversity effects may be driven by arbuscular mycorrhizal(AM)trees,and environment effects may depend on differential climate and soil preferences of AM and EM trees.To test this hypothesis,we used forest-inventory data consisting of over 80,000 trees from 631 temperate-forest plots(30 m×30 m)across Northeast China to examine how biodiversity(species diversity and ecological uniqueness),large trees(top 1%of tree diameters),and environmental factors(climate and soil nutrients)differently regulate aboveground carbon stocks of AM trees,EM trees,and AM and EM trees combined(i.e.total aboveground carbon stock).We found that large trees had a positive effect on both AM and EM tree carbon stocks.However,biodiversity and environmental factors had opposite effects on AM vs.EM tree carbon stocks.Specifically,the two components of biodiversity had positive effects on AM tree carbon stocks,but negative effects on EM tree carbon stocks.Environmental heterogeneity(mean annual temperature and soil nutrients)also exhibited contrasting effects on AM and EM tree carbon stocks.Consequently,for the total carbon stock,the positive large-tree effect far surpasses the diversity and environment effect.This is mainly because when integrating AM and EM tree carbon stock into total carbon stock,the opposite diversity-effect(also environment-effect)on AM vs.EM tree carbon stock counteracts each other while the consistent positive large-tree effect on AM and EM tree carbon stock is amplified.In summary,this study emphasized a mycorrhizal viewpoint to better understand the determinants of overarching aboveground carbon profile across regional forests.

Genome-wide association study of seedling nitrogen-use efficiency-associated traits in common wheat(Triticum aestivum L.)

Nitrogen(N)fertilizer application is essential for crop-plant growth and development.Identifying genetic loci associated with N-use efficiency(NUE)could increase wheat yields and reduce environmental pollution caused by overfertilization.We subjected a panel of 389 wheat accessions to N and chlorate(a nitrate analog)treatments to identify quantitative trait loci(QTL)controlling NUE-associated traits at the wheat seedling stage.Genotyping the panel with a 660K single-nucleotide polymorphism(SNP)array,we identified 397 SNPs associated with N-sensitivity index and chlorate inhibition rate.These SNPs were merged into 49 QTL,of which eight were multi-environment stable QTL and 27 were located near previously reported QTL.A set of 135 candidate genes near the 49 QTL included TaBOX(F-box family protein)and TaERF(ethylene-responsive transcription factor).A Tabox mutant was more sensitive to low-N stress than the wild-type plant.We developed two functional markers for Hap 1,the favorable allele of TaBOX.

Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

Casual associations between blood metabolites and colon cancer

BACKGROUND Limited knowledge exists regarding the casual associations linking blood metabolites and the risk of developing colorectal cancer.AIM To investigate causal associations between blood metabolites and colon cancer.METHODS The study utilized a two-sample Mendelian randomization(MR)analysis to investigate the causal impact of 486 blood metabolites on colorectal cancer.The primary method of analysis used was the inverse variance weighted model.To further validate the results several sensitivity analyses were performed,including Cochran's Q test,MR-Egger intercept test,and MR robust adjusted profile score.These additional analyses were conducted to ensure the reliability and robustness of the findings.RESULTS After rigorous selection for genetic variation,486 blood metabolites were included in the MR analysis.We found Mannose[odds ratio(OR)=2.09(1.10-3.97),P=0.024],N-acetylglycine[OR=3.14(1.78-5.53),P=7.54×10^(-8)],X-11593-O-methylascorbate[OR=1.68(1.04-2.72),P=0.034],1-arachidonoylglycerophosphocholine[OR=4.23(2.51-7.12),P=6.35×10^(-8)]and 1-arachidonoylglycerophosphoethanolamine 4[OR=3.99(1.17-13.54),P=0.027]were positively causally associated with colorectal cancer,and we also found a negative causal relationship between Tyrosine[OR=0.08(0.01-0.63),P=0.014],Urate[OR=0.25(0.10-0.62),P=0.003],N-acetylglycine[0.73(0.54-0.98),P=0.033],X-12092[OR=0.89(0.81-0.99),P=0.028],Succinylcarnitine[OR=0.48(0.27-0.84),P=0.09]with colorectal cancer.A series of sensitivity analyses were performed to confirm the rigidity of the results.CONCLUSION This study showed a causal relationship between 10 blood metabolites and colorectal cancer,of which 5 blood metabolites were found to be causal for the development of colorectal cancer and were confirmed as risk factors.The other five blood metabolites are protective factors.