Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available....Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.展开更多
Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available....Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.Methods:We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings,version 3.0(ACMG SF v3.0),list in the genomes of 57,933 Icelanders.We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database,the frequency of variants,and their associations with disease to create a manually curated set of actionable genotypes(variants).We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers.展开更多
How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable i...How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable insights by utilizing the power of cutting-edge algorithms and machine learning, empowering enterprises to make deft decisions quickly and efficiently. This article explores the idea of cognitive computing and AI in decision-making, emphasizing its function in converting unvalued data into valuable knowledge. It details the advantages of utilizing these technologies, such as greater productivity, accuracy, and efficiency. Businesses may use cognitive computing and AI to their advantage to obtain a competitive edge in today’s data-driven world by knowing their capabilities and possibilities [1].展开更多
Many companies like credit card, insurance, bank, retail industry require direct marketing. Data mining can help those institutes to set marketing goal. Data mining techniques have good prospects in their target audie...Many companies like credit card, insurance, bank, retail industry require direct marketing. Data mining can help those institutes to set marketing goal. Data mining techniques have good prospects in their target audiences and improve the likelihood of response. In this work we have investigated two data mining techniques: the Naive Bayes and the C4.5 decision tree algorithms. The goal of this work is to predict whether a client will subscribe a term deposit. We also made comparative study of performance of those two algorithms. Publicly available UCI data is used to train and test the performance of the algorithms. Besides, we extract actionable knowledge from decision tree that focuses to take interesting and important decision in business area.展开更多
Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available....Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.Methods:We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings,version 3.0(ACMG SF v3.0),list in the genomes of 57,933 Icelanders.We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database,the frequency of variants,and their associations with disease to create a manually curated set of actionable genotypes(variants).We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers.展开更多
Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available....Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.展开更多
The cybersecurity report provides unstructured actionable cyber threat intelligence(CTI)with detailed threat attack procedures and indicators of compromise(IOCs),e.g.,malware hash or URL(uniform resource locator)of co...The cybersecurity report provides unstructured actionable cyber threat intelligence(CTI)with detailed threat attack procedures and indicators of compromise(IOCs),e.g.,malware hash or URL(uniform resource locator)of command and control server.The actionable CTI,integrated into intrusion detection systems,can not only prioritize the most urgent threats based on the campaign stages of attack vectors(i.e.,IOCs)but also take appropriate mitigation measures based on contextual information of the alerts.However,the dramatic growth in the number of cybersecurity reports makes it nearly impossible for security professionals to find an efficient way to use these massive amounts of threat intelligence.In this paper,we propose a trigger-enhanced actionable CTI discovery system(TriCTI)to portray a relationship between IOCs and campaign stages and generate actionable CTI from cybersecurity reports through natural language processing(NLP)technology.Specifically,we introduce the“campaign trigger”for an effective explanation of the campaign stages to improve the performance of the classification model.The campaign trigger phrases are the keywords in the sentence that imply the campaign stage.The trained final trigger vectors have similar space representations with the keywords in the unseen sentence and will help correct classification by increasing the weight of the keywords.We also meticulously devise a data augmentation specifically for cybersecurity training sets to cope with the challenge of the scarcity of annotation data sets.Compared with state-of-the-art text classification models,such as BERT,the trigger-enhanced classification model has better performance with accuracy(86.99%)and F1 score(87.02%).We run TriCTI on more than 29k cybersecurity reports,from which we automatically and efficiently collect 113,543 actionable CTI.In particular,we verify the actionability of discovered CTI by using large-scale field data from VirusTotal(VT).The results demonstrate that the threat intelligence provided by VT lacks a part of the threat context for IOCs,such as the Actions on Objectives campaign stage.As a comparison,our proposed method can completely identify the actionable CTI in all campaign stages.Accordingly,cyber threats can be identified and resisted at any campaign stage with the discovered actionable CTI.展开更多
Although amazing progress has been made in ma- chine learning to achieve high generalization accuracy and ef- ficiency, there is still very limited work on deriving meaning- ful decision-making actions from the result...Although amazing progress has been made in ma- chine learning to achieve high generalization accuracy and ef- ficiency, there is still very limited work on deriving meaning- ful decision-making actions from the resulting models. How- ever, in many applications such as advertisement, recommen- dation systems, social networks, customer relationship man- agement, and clinical prediction, the users need not only ac- curate prediction, but also suggestions on actions to achieve a desirable goal （e.g., high ads hit rates） or avert an unde- sirable predicted result （e.g., clinical deterioration）. Existing works for extracting such actionability are few and limited to simple models such as a decision tree. The dilemma is that those models with high accuracy are often more complex and harder to extract actionability from. In this paper, we propose an effective method to extract ac- tionable knowledge from additive tree models （ATMs）, one of the most widely used and best off-the-shelf classifiers. We rigorously formulate the optimal actionable planning （OAP） problem for a given ATM, which is to extract an action- able plan for a given input so that it can achieve a desirable output while maximizing the net profit. Based on a state space graph formulation, we first propose an optimal heuris- tic search method which intends to find an optimal solution. Then, we also present a sub-optimal heuristic search with an admissible and consistent heuristic function which can re- markably improve the efficiency of the algorithm. Our exper- imental results demonstrate the effectiveness and efficiency of the proposed algorithms on several real datasets in the application domain of personal credit and banking.展开更多
"Give me 10 youths,and I will shake the world,"declared Soekarno,Indonesia's founding president.The sentiment might have been idealistic,but not false.History has never been driven by comfort,nor shaped ..."Give me 10 youths,and I will shake the world,"declared Soekarno,Indonesia's founding president.The sentiment might have been idealistic,but not false.History has never been driven by comfort,nor shaped solely by inheritance.Its most significant turning points have emerged from those with youth,conviction,and courage ingrained in them.Progress starts when young people not only dream but also take action.Sometimes,the boldest move is not to run towards the glow of cities,but to turn back-to one's soil,roots,and forgotten homeand help them flourish.展开更多
Deep learning has undeniably sharpened our ability to forecast risk in neuropsychiatry[1].Yet the very success of prediction has exposed a deeper limitation:we are still remarkably uncertain about which levers to pull...Deep learning has undeniably sharpened our ability to forecast risk in neuropsychiatry[1].Yet the very success of prediction has exposed a deeper limitation:we are still remarkably uncertain about which levers to pull to change patient trajectories[2].Accurate risk scores that cannot be translated into credible actions leave clinicians where they began,testing symptomatic fixes and hoping for the best.If we want to move beyond this impasse,the next step is not simply to train larger models,but to rethink what we ask of them.展开更多
Plant bacterial diseases cause significant harm to agricultural production because of their frequent,intermittent and regional outbreaks.Currently,chemical control is still a more effective method for bacterial diseas...Plant bacterial diseases cause significant harm to agricultural production because of their frequent,intermittent and regional outbreaks.Currently,chemical control is still a more effective method for bacterial disease.To develop new,efficient and safe antibacterial agrochemicals,we summarize the research progress of compounds with antibacterial activities in the past ten years,classify them according to their active skeletons,and discuss their structure-activity relationships and mechanisms of action.Finally,the development trend of antibacterial agrochemicals was prospected.This review provides valuable information for the development of antibacterial agrochemicals.展开更多
Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between...Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).展开更多
History has never been driven by comfort,nor shaped solely by inheritance.Its most significant turning points have emerged from those with youth,conviction and courage ingrained in them.Progress starts when young peop...History has never been driven by comfort,nor shaped solely by inheritance.Its most significant turning points have emerged from those with youth,conviction and courage ingrained in them.Progress starts when young people not only dream but also take action.Sometimes,the boldest move is not to run towards the glow of cities,but to turn back-to one’s soil,roots and forgotten home-and help it to flourish.展开更多
Europe is grappling with a colossal textile waste problem.Over 125 million tonnes of raw materials are devoured by the global industry each year,yet a mere fraction-less than 1%-of these fibres originate from recycled...Europe is grappling with a colossal textile waste problem.Over 125 million tonnes of raw materials are devoured by the global industry each year,yet a mere fraction-less than 1%-of these fibres originate from recycled textiles.The majority faces an unsustainable fate in landfills,incinerators,or is exported.A pivotal new report by Systemiq,"The Textile Recycling Breakthrough,"offers both a stark assessment and a strategic roadmap:Europe has the potential to amplify polyester textile recycling nearly tenfold by 2035,but this hinges on immediate,decisive action from policymakers and the industry.展开更多
The combination of Daphnes Cortex(DC)and Liquorice Root(LR),two traditional Chinese medicinal herbs,has shown significant therapeutic effects on rheumatoid arthritis(RA),but its synergistic mechanism of action remains...The combination of Daphnes Cortex(DC)and Liquorice Root(LR),two traditional Chinese medicinal herbs,has shown significant therapeutic effects on rheumatoid arthritis(RA),but its synergistic mechanism of action remains to be elucidated.Employing a network pharmacology and molecular docking approach,this study systematically investigated the synergistic mechanism of the herb pair DC and LR in RA treatment.Active components and their corresponding targets were retrieved from the TCMSP database and relevant literature,and RA-related targets were collected from established disease databases.A total of 73 overlapping targets between DC-LR and RA were identified,among which core targets such as AKT1,TNF,and CASP3 were highlighted.GO and KEGG enrichment analyses revealed that these targets are involved in biological processes such as oxidative stress response and cell migration,and are significantly enriched in key pathways including HIF-1,TNF,and PI3K-Akt signaling pathways.Compatibility analysis further revealed that the combination of DC and LR may enhance therapeutic effects through synergistic regulation of shared targets and complementary modulation of upstream and downstream pathway components.Molecular docking confirmed strong binding affinities between core active components and key targets.This study provides a multi-dimensional“component-target-pathway”perspective on the potential synergistic anti-RA mechanism of the DC-LR herb pair,offering a theoretical basis for further experimental validation and clinical application.展开更多
[Objectives]To investigate the efficacy and potential mechanism of the topical preparation Jineijin-Shanzha Patch(composed of Galli Gigerii Endothelium Corneum and Crataegi Fructus)in improving functional dyspepsia(FD...[Objectives]To investigate the efficacy and potential mechanism of the topical preparation Jineijin-Shanzha Patch(composed of Galli Gigerii Endothelium Corneum and Crataegi Fructus)in improving functional dyspepsia(FD)based on network pharmacology.[Methods]Firstly,we reviewed the existing research progress on each constituent drug of the Jineijin Shanzha Patch for FD improvement.Following this,identified overlapping genes were utilized to construct both a"Drug-Active Component-FD Target"network and a Protein-Protein Interaction(PPI)network specific to the patch.In addition,Gene Ontology(GO)analysis was carried out.[Results]We identified that the 13 herbs in the Jineijin Shanzha Patch are mainly used for food stagnation,qi stagnation,and spleen deficiency.Screening revealed 43 active patch components,1414 FD-related targets,and 284 shared targets between them.The PPI network analysis further identified the top 10 core targets from these shared targets.From the"Drug-Active Component-FD Target"network,we identified the core elements.These included the herbal components Vignae Semen(from Liushenqu),Crataegi Fructus,and Pseudostellariae Radix;the active components quercetin,genistein,and apigenin;and the key targets CASP3,BCL2,and CASP9.GO analysis of the 284 overlapping targets indicated that the Jineijin Shanzha Patch may exert its therapeutic effects via regulation of biological processes such as the response to lipopolysaccharide,response to bacterium-derived molecules,and regulation of the apoptotic signaling pathway.[Conclusions]The main active components of the Jineijin Shanzha Patch(quercetin,genistein,and apigenin)may improve FD by modulating signaling pathways such as the response to lipopolysaccharide,response to bacterium-derived molecules,and regulation of the apoptotic signaling pathway,thereby acting on key targets including CASP3,BCL2,and CASP9.展开更多
Liver diseases remain a global health crisis,with limited safe therapeutic options.Cornus officinalis,a traditional medicinal-edible plant,has demonstrated significant hepatoprotective potential.This review systematic...Liver diseases remain a global health crisis,with limited safe therapeutic options.Cornus officinalis,a traditional medicinal-edible plant,has demonstrated significant hepatoprotective potential.This review systematically summarizes its liver-protective mechanisms and explores its potential as a functional food.Data were collected from scientific databases such as Pub Med,Science Direct,Elsevier,Google Scholar,and relevant literature.Key bioactive compounds—including iridoids,polyphenols,and polysaccharides—contribute to hepatoprotection by mitigating oxidative stress,inflammation,steatosis,apoptosis,and by regulating gut microbiota.As critical quality markers,iridoids exhibit suboptimal bioavailability,necessitating targeted technological interventions—nanoencapsulation for liver-specific delivery and microbial fermentation for controlled aglycone conversion are proposed to enhance their pharmacokinetic properties and bioactivity.Future research could adopt encapsulation and fermentation technologies for C.officinalis processing,aiming to develop targeted functional food products with enhanced bioactivity of its active components.This review,for the first time,establishes a“component-pathway-integration”model,providing a theoretical framework for evidence-based CO-derived functional food development and highlighting the need for further research on iridoid metabolic transformation to advance liver health management.展开更多
To maximize the profits of power grid operators(GOs),load aggregators(LAs)and electricity customers(ECs),this paper proposes a hierarchical demand response(HDR)framework that considers competing interaction based on m...To maximize the profits of power grid operators(GOs),load aggregators(LAs)and electricity customers(ECs),this paper proposes a hierarchical demand response(HDR)framework that considers competing interaction based on multiagent deep deterministic policy gradient(MaDDPG).The ECs are divided into conventional ECs and the electric vehicles(EVs)which are managed by ECs agent(ECA)and EV agent(EVA)to exploit the flexibility of the HDR framework.Thus,the HDR is a tri-layer model determined by five types of agents engaging in competing interaction to maximize their own profits.To address the limitations of mathematical expression and participation scale in the Stackelberg game within the HDR model,a dynamic interaction mechanism is adopted.Moreover,to tackle the HDR involving various entities,the MaDDPG develops multiple agents to simulation the dynamic competing interactions between each subject as well as solve the problem of continuous action control.Furthermore,MaDDPG adopts soft target update and priority experience replay method to ensure stable and effective training,and makes the exploration strategy comprehensive by using exploration noise.Simulation studies are conducted to verify the performance of the MaDDPG with dynamic interaction mechanism in dealing with multilayer multi-agent continuous action control,compared to the double deep Q network(DDQN),deep Q network(DQN)and dueling DQN.Additionally,comparisons among the proposed HDR with the price based DR(PBDR)and incentive based DR(IBDR)are analyzed to investigate the flexibility of the HDR.展开更多
Alcohol culture has a long history in China, often appearing in scenarios such as business banquets, social gatherings, and family parties. With the expansion of the drinking population, the health problems caused by ...Alcohol culture has a long history in China, often appearing in scenarios such as business banquets, social gatherings, and family parties. With the expansion of the drinking population, the health problems caused by alcohol consumption have attracted widespread social attention. Excessive drinking can lead to alcohol poisoning in mild cases, damage to the stomach and liver in severe cases, and even induce alcoholic hepatitis and pancreatitis. Against this background, finding raw materials containing anti-alcohol substances and developing products to replace traditional anti-alcohol drugs have become important directions in the development of food science and nutrition. Based on existing theoretical and empirical research results, this paper systematically explores the anti-alcohol value of mulberry juice from aspects such as its biological components, anti-alcohol mechanism, relevant experimental verification, and application prospects. It aims to promote the development of natural anti-alcohol products, provide references for accelerating human alcohol metabolism, alleviating post-drinking discomfort, and meeting people’s pursuit of a healthy life.展开更多
文摘Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.
文摘Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.Methods:We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings,version 3.0(ACMG SF v3.0),list in the genomes of 57,933 Icelanders.We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database,the frequency of variants,and their associations with disease to create a manually curated set of actionable genotypes(variants).We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers.
文摘How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable insights by utilizing the power of cutting-edge algorithms and machine learning, empowering enterprises to make deft decisions quickly and efficiently. This article explores the idea of cognitive computing and AI in decision-making, emphasizing its function in converting unvalued data into valuable knowledge. It details the advantages of utilizing these technologies, such as greater productivity, accuracy, and efficiency. Businesses may use cognitive computing and AI to their advantage to obtain a competitive edge in today’s data-driven world by knowing their capabilities and possibilities [1].
文摘Many companies like credit card, insurance, bank, retail industry require direct marketing. Data mining can help those institutes to set marketing goal. Data mining techniques have good prospects in their target audiences and improve the likelihood of response. In this work we have investigated two data mining techniques: the Naive Bayes and the C4.5 decision tree algorithms. The goal of this work is to predict whether a client will subscribe a term deposit. We also made comparative study of performance of those two algorithms. Publicly available UCI data is used to train and test the performance of the algorithms. Besides, we extract actionable knowledge from decision tree that focuses to take interesting and important decision in business area.
文摘Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.Methods:We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings,version 3.0(ACMG SF v3.0),list in the genomes of 57,933 Icelanders.We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database,the frequency of variants,and their associations with disease to create a manually curated set of actionable genotypes(variants).We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers.
文摘Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.
基金Our research was supported by the National Key Research and Development Program of China(Nos.2019QY1301,2018YFB0805005,2018YFC0824801).
文摘The cybersecurity report provides unstructured actionable cyber threat intelligence(CTI)with detailed threat attack procedures and indicators of compromise(IOCs),e.g.,malware hash or URL(uniform resource locator)of command and control server.The actionable CTI,integrated into intrusion detection systems,can not only prioritize the most urgent threats based on the campaign stages of attack vectors(i.e.,IOCs)but also take appropriate mitigation measures based on contextual information of the alerts.However,the dramatic growth in the number of cybersecurity reports makes it nearly impossible for security professionals to find an efficient way to use these massive amounts of threat intelligence.In this paper,we propose a trigger-enhanced actionable CTI discovery system(TriCTI)to portray a relationship between IOCs and campaign stages and generate actionable CTI from cybersecurity reports through natural language processing(NLP)technology.Specifically,we introduce the“campaign trigger”for an effective explanation of the campaign stages to improve the performance of the classification model.The campaign trigger phrases are the keywords in the sentence that imply the campaign stage.The trained final trigger vectors have similar space representations with the keywords in the unseen sentence and will help correct classification by increasing the weight of the keywords.We also meticulously devise a data augmentation specifically for cybersecurity training sets to cope with the challenge of the scarcity of annotation data sets.Compared with state-of-the-art text classification models,such as BERT,the trigger-enhanced classification model has better performance with accuracy(86.99%)and F1 score(87.02%).We run TriCTI on more than 29k cybersecurity reports,from which we automatically and efficiently collect 113,543 actionable CTI.In particular,we verify the actionability of discovered CTI by using large-scale field data from VirusTotal(VT).The results demonstrate that the threat intelligence provided by VT lacks a part of the threat context for IOCs,such as the Actions on Objectives campaign stage.As a comparison,our proposed method can completely identify the actionable CTI in all campaign stages.Accordingly,cyber threats can be identified and resisted at any campaign stage with the discovered actionable CTI.
基金This work was supported in part by China Postdoctoral Science Foundation （2013M531527）, the Fundamental Research Funds for the Central Universities （0110000037）, the National Natural Science Foun- dation of China （Grant Nos. 61502412, 61033009, and 61175057）, Natural Science Foundation of the Jiangsu Province （BK20150459）, Natural Science Foundation of the Jiangsu Higher Education Institutions （15KJB520036）, National Science Foundation, United States （IIS-0534699, IIS-0713109, CNS-1017701）, and a Microsoft Research New Faculty Fellowship.
文摘Although amazing progress has been made in ma- chine learning to achieve high generalization accuracy and ef- ficiency, there is still very limited work on deriving meaning- ful decision-making actions from the resulting models. How- ever, in many applications such as advertisement, recommen- dation systems, social networks, customer relationship man- agement, and clinical prediction, the users need not only ac- curate prediction, but also suggestions on actions to achieve a desirable goal （e.g., high ads hit rates） or avert an unde- sirable predicted result （e.g., clinical deterioration）. Existing works for extracting such actionability are few and limited to simple models such as a decision tree. The dilemma is that those models with high accuracy are often more complex and harder to extract actionability from. In this paper, we propose an effective method to extract ac- tionable knowledge from additive tree models （ATMs）, one of the most widely used and best off-the-shelf classifiers. We rigorously formulate the optimal actionable planning （OAP） problem for a given ATM, which is to extract an action- able plan for a given input so that it can achieve a desirable output while maximizing the net profit. Based on a state space graph formulation, we first propose an optimal heuris- tic search method which intends to find an optimal solution. Then, we also present a sub-optimal heuristic search with an admissible and consistent heuristic function which can re- markably improve the efficiency of the algorithm. Our exper- imental results demonstrate the effectiveness and efficiency of the proposed algorithms on several real datasets in the application domain of personal credit and banking.
文摘"Give me 10 youths,and I will shake the world,"declared Soekarno,Indonesia's founding president.The sentiment might have been idealistic,but not false.History has never been driven by comfort,nor shaped solely by inheritance.Its most significant turning points have emerged from those with youth,conviction,and courage ingrained in them.Progress starts when young people not only dream but also take action.Sometimes,the boldest move is not to run towards the glow of cities,but to turn back-to one's soil,roots,and forgotten homeand help them flourish.
文摘Deep learning has undeniably sharpened our ability to forecast risk in neuropsychiatry[1].Yet the very success of prediction has exposed a deeper limitation:we are still remarkably uncertain about which levers to pull to change patient trajectories[2].Accurate risk scores that cannot be translated into credible actions leave clinicians where they began,testing symptomatic fixes and hoping for the best.If we want to move beyond this impasse,the next step is not simply to train larger models,but to rethink what we ask of them.
基金The financial support from the National Natural Science Foundation of China (No.31972290)National Key Research and Development Program of China (No.2022YFD1700300)。
文摘Plant bacterial diseases cause significant harm to agricultural production because of their frequent,intermittent and regional outbreaks.Currently,chemical control is still a more effective method for bacterial disease.To develop new,efficient and safe antibacterial agrochemicals,we summarize the research progress of compounds with antibacterial activities in the past ten years,classify them according to their active skeletons,and discuss their structure-activity relationships and mechanisms of action.Finally,the development trend of antibacterial agrochemicals was prospected.This review provides valuable information for the development of antibacterial agrochemicals.
基金J.YANG was supported by funding from the National Natural Science Foundation of China(Grant Nos.42475022,42261144671)the National Key R&D Program of China(Project No.2024YFC3013100)+2 种基金the Fundamental Research Funds for the Central UniversitiesM.LU was supported by the Otto Poon Centre of Climate Resilience and Sustainability at HKUST and the Hong Kong Research Grant Committee(Project No.16300424)Data processing and storage were supported by the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab).
文摘Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).
文摘History has never been driven by comfort,nor shaped solely by inheritance.Its most significant turning points have emerged from those with youth,conviction and courage ingrained in them.Progress starts when young people not only dream but also take action.Sometimes,the boldest move is not to run towards the glow of cities,but to turn back-to one’s soil,roots and forgotten home-and help it to flourish.
文摘Europe is grappling with a colossal textile waste problem.Over 125 million tonnes of raw materials are devoured by the global industry each year,yet a mere fraction-less than 1%-of these fibres originate from recycled textiles.The majority faces an unsustainable fate in landfills,incinerators,or is exported.A pivotal new report by Systemiq,"The Textile Recycling Breakthrough,"offers both a stark assessment and a strategic roadmap:Europe has the potential to amplify polyester textile recycling nearly tenfold by 2035,but this hinges on immediate,decisive action from policymakers and the industry.
基金supported by National Training Program of Innovation and Entrepreneurship for Undergraduates(202510163044).
文摘The combination of Daphnes Cortex(DC)and Liquorice Root(LR),two traditional Chinese medicinal herbs,has shown significant therapeutic effects on rheumatoid arthritis(RA),but its synergistic mechanism of action remains to be elucidated.Employing a network pharmacology and molecular docking approach,this study systematically investigated the synergistic mechanism of the herb pair DC and LR in RA treatment.Active components and their corresponding targets were retrieved from the TCMSP database and relevant literature,and RA-related targets were collected from established disease databases.A total of 73 overlapping targets between DC-LR and RA were identified,among which core targets such as AKT1,TNF,and CASP3 were highlighted.GO and KEGG enrichment analyses revealed that these targets are involved in biological processes such as oxidative stress response and cell migration,and are significantly enriched in key pathways including HIF-1,TNF,and PI3K-Akt signaling pathways.Compatibility analysis further revealed that the combination of DC and LR may enhance therapeutic effects through synergistic regulation of shared targets and complementary modulation of upstream and downstream pathway components.Molecular docking confirmed strong binding affinities between core active components and key targets.This study provides a multi-dimensional“component-target-pathway”perspective on the potential synergistic anti-RA mechanism of the DC-LR herb pair,offering a theoretical basis for further experimental validation and clinical application.
基金Supported by Putuo District Science and Technology R&D Platform Project,Shanghai(2024QX04).
文摘[Objectives]To investigate the efficacy and potential mechanism of the topical preparation Jineijin-Shanzha Patch(composed of Galli Gigerii Endothelium Corneum and Crataegi Fructus)in improving functional dyspepsia(FD)based on network pharmacology.[Methods]Firstly,we reviewed the existing research progress on each constituent drug of the Jineijin Shanzha Patch for FD improvement.Following this,identified overlapping genes were utilized to construct both a"Drug-Active Component-FD Target"network and a Protein-Protein Interaction(PPI)network specific to the patch.In addition,Gene Ontology(GO)analysis was carried out.[Results]We identified that the 13 herbs in the Jineijin Shanzha Patch are mainly used for food stagnation,qi stagnation,and spleen deficiency.Screening revealed 43 active patch components,1414 FD-related targets,and 284 shared targets between them.The PPI network analysis further identified the top 10 core targets from these shared targets.From the"Drug-Active Component-FD Target"network,we identified the core elements.These included the herbal components Vignae Semen(from Liushenqu),Crataegi Fructus,and Pseudostellariae Radix;the active components quercetin,genistein,and apigenin;and the key targets CASP3,BCL2,and CASP9.GO analysis of the 284 overlapping targets indicated that the Jineijin Shanzha Patch may exert its therapeutic effects via regulation of biological processes such as the response to lipopolysaccharide,response to bacterium-derived molecules,and regulation of the apoptotic signaling pathway.[Conclusions]The main active components of the Jineijin Shanzha Patch(quercetin,genistein,and apigenin)may improve FD by modulating signaling pathways such as the response to lipopolysaccharide,response to bacterium-derived molecules,and regulation of the apoptotic signaling pathway,thereby acting on key targets including CASP3,BCL2,and CASP9.
基金funded by the Major Science and Technology Project of Henan Province(231100310200)the National Key Research and Development Program(2023YFF1103804).
文摘Liver diseases remain a global health crisis,with limited safe therapeutic options.Cornus officinalis,a traditional medicinal-edible plant,has demonstrated significant hepatoprotective potential.This review systematically summarizes its liver-protective mechanisms and explores its potential as a functional food.Data were collected from scientific databases such as Pub Med,Science Direct,Elsevier,Google Scholar,and relevant literature.Key bioactive compounds—including iridoids,polyphenols,and polysaccharides—contribute to hepatoprotection by mitigating oxidative stress,inflammation,steatosis,apoptosis,and by regulating gut microbiota.As critical quality markers,iridoids exhibit suboptimal bioavailability,necessitating targeted technological interventions—nanoencapsulation for liver-specific delivery and microbial fermentation for controlled aglycone conversion are proposed to enhance their pharmacokinetic properties and bioactivity.Future research could adopt encapsulation and fermentation technologies for C.officinalis processing,aiming to develop targeted functional food products with enhanced bioactivity of its active components.This review,for the first time,establishes a“component-pathway-integration”model,providing a theoretical framework for evidence-based CO-derived functional food development and highlighting the need for further research on iridoid metabolic transformation to advance liver health management.
基金supported by the National Natural Science Foundation of China(No.52477097)the GuangDong Basic and Applied Basic Research Foundation(2023A1515240014)the State Key Laboratory of Advanced Electromagnetic Technology(Grant No.AET 2024KF005).
文摘To maximize the profits of power grid operators(GOs),load aggregators(LAs)and electricity customers(ECs),this paper proposes a hierarchical demand response(HDR)framework that considers competing interaction based on multiagent deep deterministic policy gradient(MaDDPG).The ECs are divided into conventional ECs and the electric vehicles(EVs)which are managed by ECs agent(ECA)and EV agent(EVA)to exploit the flexibility of the HDR framework.Thus,the HDR is a tri-layer model determined by five types of agents engaging in competing interaction to maximize their own profits.To address the limitations of mathematical expression and participation scale in the Stackelberg game within the HDR model,a dynamic interaction mechanism is adopted.Moreover,to tackle the HDR involving various entities,the MaDDPG develops multiple agents to simulation the dynamic competing interactions between each subject as well as solve the problem of continuous action control.Furthermore,MaDDPG adopts soft target update and priority experience replay method to ensure stable and effective training,and makes the exploration strategy comprehensive by using exploration noise.Simulation studies are conducted to verify the performance of the MaDDPG with dynamic interaction mechanism in dealing with multilayer multi-agent continuous action control,compared to the double deep Q network(DDQN),deep Q network(DQN)and dueling DQN.Additionally,comparisons among the proposed HDR with the price based DR(PBDR)and incentive based DR(IBDR)are analyzed to investigate the flexibility of the HDR.
基金Key Scientific Research Project of Institutions of Higher Education in Henan Province(Project No.:23A550020)。
文摘Alcohol culture has a long history in China, often appearing in scenarios such as business banquets, social gatherings, and family parties. With the expansion of the drinking population, the health problems caused by alcohol consumption have attracted widespread social attention. Excessive drinking can lead to alcohol poisoning in mild cases, damage to the stomach and liver in severe cases, and even induce alcoholic hepatitis and pancreatitis. Against this background, finding raw materials containing anti-alcohol substances and developing products to replace traditional anti-alcohol drugs have become important directions in the development of food science and nutrition. Based on existing theoretical and empirical research results, this paper systematically explores the anti-alcohol value of mulberry juice from aspects such as its biological components, anti-alcohol mechanism, relevant experimental verification, and application prospects. It aims to promote the development of natural anti-alcohol products, provide references for accelerating human alcohol metabolism, alleviating post-drinking discomfort, and meeting people’s pursuit of a healthy life.
