Optimal instance selection for improved decision tree

Instance selection plays an important role in improving scalability of data mining algorithms, but it can also be used to improve the quality of the data mining results. In this dissertation we present a new optimization-based approach for instance selection that uses a genetic algorithm (GA) to select a subset of instances to produce a simpler decision tree with acceptable accuracy. The resultant trees are likely to be easier to comprehend and interpret by the decision maker and hence more useful in practice. We present numerical results for several difficult test datasets that indicate that GA-based instance selection can often reduce the size of the decision tree by an order of magnitude while still maintaining good prediction accuracy. The results suggest that GA-based instance selection works best for low entropy datasets. With higher entropy, there will be less benefit from instance selection. A comparison between GA and other heuristic approaches such as Rmhc (Random Mutation Hill Climbing) and simple construction heuristic, indicates that GA is able to obtain a good solution with low computation cost even for some large datasets. One advantage of instance selection is that it is able to increase the average instances associated with the leaves of the decision trees to avoid overfitting, thus instance selection can be used as an effective alternative to prune decision trees. Finally, the analysis on the selected instances reveals that instance selection helps to reduce outliers, reduce missing values, and select the most useful instances for separating classes

Left ventricular remodeling following myocardial infarction revealed with a quantitative diffusion MRI tractography framework

A cardiac-tailored framework for 3D Diffusion Tensor MRI tractography is developed and used to characterize myofiber architecture in normal and remodeled myocardium. We show that myofibers in the subepicardium of the remote infarct zone become less oblique (more circumferential) as the heart dilates and remodels. This fiber realignment may play an important role in the loss of contractile function in the remote zone over time

Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models

Public large-scale text-to-image diffusion models, such as Stable Diffusion, have gained significant attention from the community. These models can be easily customized for new concepts using low-rank adaptations (LoRAs). However, the utilization of multiple concept LoRAs to jointly support multiple customized concepts presents a challenge. We refer to this scenario as decentralized multi-concept customization, which involves single-client concept tuning and center-node concept fusion. In this paper, we propose a new framework called Mix-of-Show that addresses the challenges of decentralized multi-concept customization, including concept conflicts resulting from existing single-client LoRA tuning and identity loss during model fusion. Mix-of-Show adopts an embedding-decomposed LoRA (ED-LoRA) for single-client tuning and gradient fusion for the center node to preserve the in-domain essence of single concepts and support theoretically limitless concept fusion. Additionally, we introduce regionally controllable sampling, which extends spatially controllable sampling (e.g., ControlNet and T2I-Adaptor) to address attribute binding and missing object problems in multi-concept sampling. Extensive experiments demonstrate that Mix-of-Show is capable of composing multiple customized concepts with high fidelity, including characters, objects, and scenes

Cryptic speciation of benthic Prorocentrum (Dinophyceae) species and their potential as ecological indicators

The response of marine ecosystems to rapid climate changes has been well recognized but not studied extensively. Benthic microalgae, in contrast to the phytoplankton that is able to be transported by currents, have limited dispersal ability and thus are a better ecological indicator to climate changes. Here we performed sampling in the Yellow Sea, the East China Sea and South China Sea and established twenty-six strains of benthic Prorocentrum for detailed morphological and molecular examinations. Five Prorocentrum species, including P. concavum, P. fukuyoi, P. mexicanum, P. tsawwassenense, and P. cf. sculptile, were identified. Both P. concavum and P. fukuyoi displayed marked intraspecific divergences in large subunit (LSU) ribosomal RNA gene sequences, corresponding to their geographical origins. In contrast, P. mexicanum strains shared identical LSU sequence. Prorocentrum tsawwassenense and P. cf. sculptile are not suitable ecological indicators as they were rarely observed. Prorocentrum mexicanum is not recommended either as it is present across the region. In contrast, P. concavum and P. fukuyoi have advantages as ecological indicators for climate changes in the Western Pacific as they comprise several ribotypes with differentiated biogeography. Toxin analysis was also performed on all five species except P. fukuyoi by liquid chromatography coupled to tandem mass spectrometry, but okadaic acid was not detectable

The role of ferroptosis in virus infections

Regulated cell death (RCD) is a strategy employed by host cells to defend invasions of pathogens, such as viruses and bacteria. Ferroptosis is a type of RCD characterized by excessive accumulation of iron and lipid peroxidation. While ferroptosis is primarily considered as a mechanism associated with tumorigenesis, emerging evidence begin to suggest that it may play essential role during virus infections. Recent studies illustrated that activation of ferroptosis could either induce or prohibit various types of RCDs to facilitate virus replication or evade host surveillance. More experimental evidence has demonstrated how viruses regulate ferroptosis to influence replication, transmission, and pathogenesis. This review summarizes ferroptosis-related metabolism, including iron metabolism, lipid peroxidation, and antioxidant metabolism. Furthermore, we discuss the interplay between viral infections and host ferroptosis process, with a focus on the mechanism of how viruses exploit ferroptosis for its own replication. Understanding how ferroptosis impacts virus infection can offer valuable insights into the development of effective therapeutic strategies to combat virus infections

Clinical outcomes and risk factors of coronary artery aneurysms after successful percutaneous coronary intervention and drug-eluting stent implantation for chronic total occlusions

AbstractObjectiveThe study aimed to analyze the risk factors and long-term outcomes associated with coronary artery aneurysms (CAAs) after successful percutaneous coronary intervention (PCI) and drug-eluting stent (DES) implantation in patients with CTOs.BackgroundThere are sporadic data available on post-procedure CAAs after transcatheter revascularization for CTOs.Methods and resultsA total of 141 patients with 149 CTOs who underwent successful CTO-PCI and DES implantation with angiographic follow-up from 2004 to 2010 were included. Patients were divided into CAA group and non-CAA group according to the presence of CAAs in the follow-up angiography. The independent predictors and major adverse cardiac events (MACEs) including cardiac death, myocardial infarction (MI) and target-vessel revascularization (TVR) were compared between two groups. The incidence of CAAs was 11.4% (17/149) after index procedure. Multivariate analysis showed that age (OR: 0.925, CI 0.873–0.980, P = 0.008), ostial occlusion (OR: 6.715, CI 1.473–30.610, P = 0.014), the parallel wire technique (OR: 6.167, CI 1.709–22.259, P = 0.005) and DES length (OR: 1.030, CI 1.002–1.058, P = 0.036) were the independent predictors of CAAs after successful CTO-PCI and DES implantation. MACEs were similar between two groups (adjusted hazard ratio 0.670; 95% CI 0.160–2.808; P = 0.584) during the 5-year follow-up.ConclusionsThe independent predictors of CAAs after successful CTO-PCI and DES implantation are age, ostial occlusion, the parallel wire technique and DES length. CAAs after index procedure are not frequently associated with adverse clinical events under dual antiplatelet therapy. Further large clinical studies are warranted to explore the clinical implications of patients with this distinct new entity

Antagonistic effects of Talaromyces muroii TM28 against Fusarium crown rot of wheat caused by Fusarium pseudograminearum

Fusarium crown rot (FCR) caused by Fusarium pseudograminearum is a serious threat to wheat production worldwide. This study aimed to assess the effects of Talaromyces muroii strain TM28 isolated from root of Panax quinquefolius against F. pseudograminearum. The strain of TM28 inhibited mycelial growth of F. pseudograminearum by 87.8% at 72 h, its cell free fermentation filtrate had a strong antagonistic effect on mycelial growth and conidial germination of F. pseudograminearum by destroying the integrity of the cell membrane. In the greenhouse, TM28 significantly increased wheat fresh weight and height in the presence of pathogen Fp, it enhanced the antioxidant defense activity and ameliorated the negative effects of F. pseudograminearum, including disease severity and pathogen abundance in the rhizosphere soil, root and stem base of wheat. RNA-seq of F. pseudograminearum under TM28 antagonistic revealed 2,823 differentially expressed genes (DEGs). Most DEGs related to cell wall and cell membrane synthesis were significantly downregulated, the culture filtrate of TM28 affected the pathways of fatty acid synthesis, steroid synthesis, glycolysis, and the citrate acid cycle. T. muroii TM28 appears to have significant potential in controlling wheat Fusarium crown rot caused by F. pseudograminearum

Optimal instance selection for improved decision tree

Instance selection plays an important role in improving scalability of data mining algorithms, but it can also be used to improve the quality of the data mining results. In this dissertation we present a new optimization-based approach for instance selection that uses a genetic algorithm (GA) to select a subset of instances to produce a simpler decision tree with acceptable accuracy. The resultant trees are likely to be easier to comprehend and interpret by the decision maker and hence more useful in practice. We present numerical results for several difficult test datasets that indicate that GA-based instance selection can often reduce the size of the decision tree by an order of magnitude while still maintaining good prediction accuracy. The results suggest that GA-based instance selection works best for low entropy datasets. With higher entropy, there will be less benefit from instance selection. A comparison between GA and other heuristic approaches such as Rmhc (Random Mutation Hill Climbing) and simple construction heuristic, indicates that GA is able to obtain a good solution with low computation cost even for some large datasets. One advantage of instance selection is that it is able to increase the average instances associated with the leaves of the decision trees to avoid overfitting, thus instance selection can be used as an effective alternative to prune decision trees. Finally, the analysis on the selected instances reveals that instance selection helps to reduce outliers, reduce missing values, and select the most useful instances for separating classes.</p

Effects of Counter Tillage and Slope Gradient on Nutrient Losses on Sloping Farmland

Counter tillage is a typical cultivation practice on the Loess Plateau, which can influence the soil erosion process by intercepting runoff and increasing infiltration. However, few studies have investigated the mechanisms of nutrient losses associated with counter tillage. This study was conducted to reveal the effects of counter tillage and slope gradient on the soil nutrient loss mechanism on sloping farmland. In this study, the rainfall simulation was conducted with a rainfall intensity of 90 mm·h−1 and with five slope gradients (5.24%, 8.75%, 17.63%, 26.79%, 36.40%). The runoff plots involved the counter tillage (CT) and traditional plow (CK), in order to investigate the characteristics of soil erosion and available phosphorus (AP), ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) losses. The soil erosion characteristics included the time until runoff generation, RR (runoff rate), and SR (sediment rate); the nutrient loss characteristics included nutrient loss concentrations, nutrient loss and nutrient loss rate in runoff or sediment. The results indicated that the RR and SR with a slope gradient of 5.24~26.79% on CT decreased by 11.77~94.92% and 20.69~99.27%, respectively, compared with that of CK. As the slope gradient increased (36.40%), a break in the ridge occurred and the reduction in the RR and SR was weakened; this was likely to be close to that of the CK. Nutrient losses differed significantly between different slope gradients and tillage practices. Nutrient losses increased with an increasing slope gradient. The nutrient losses of AP, NH4+-N, and NO3−-N in runoff, with the slope gradient of 36.40%, increased 75.75%, 76.34%, 75.63%; meanwhile, in sediment, it increased 32.93, 30.70, 32.18 times, compared with the slope gradient of 5.24% on CT. The CT with the slope gradient of 5.24~26.79% had a good effect in controlling nutrient losses; however, for the slope gradient of 36.40%, the effects of CT in controlling nutrient losses decreased. The nutrient loss rate and RR or SR satisfied a linear positive correlation. The reduction benefits of nutrient losses on CT in runoff and sediment can reach 57.7% to 100% and 45.5% to 100%, respectively. In conclusion, CT is an effective tillage practice to control soil erosion and nutrient losses. This study can provide a reference for soil erosion and nutrient loss control on sloping farmland on the Loess Plateau