An iterative initial-points refinement algorithm for categorical data clustering

The original k-means clustering algorithm is designed to work primarily on numeric data sets. This prohibits the algorithm from being directly applied to categorical data clustering in many data mining applications. The k-modes algorithm [Z. Huang, Clustering large data sets with mixed numeric and categorical value, in: Proceedings of the First Pacific Asia Knowledge Discovery and Data Mining Conference. World Scientific, Singapore, 1997, pp. 21–34] extended the k-means paradigm to cluster categorical data by using a frequency-based method to update the cluster modes versus the k-means fashion of minimizing a numerically valued cost. However, as is the case with most data clustering algorithms, the algorithm requires a pre-setting or random selection of initial points (modes) of the clusters. The differences on the initial points often lead to considerable distinct cluster results. In this paper we present an experimental study on applying Bradley and Fayyad\u27s iterative initial-point refinement algorithm to the k-modes clustering to improve the accurate and repetitiveness of the clustering results [cf. P. Bradley, U. Fayyad, Refining initial points for k-mean clustering, in: Proceedings of the 15th International Conference on Machine Learning, Morgan Kaufmann, Los Altos, CA, 1998]. Experiments show that the k-modes clustering algorithm using refined initial points leads to higher precision results much more reliably than the random selection method without refinement, thus making the refinement process applicable to many data mining applications with categorical data

Natural manganese ores for efficient removal of organic pollutants via catalytic peroxymonosulfate-based advanced oxidation processes

Peroxymonosulfate-based advanced oxidation processes (PMS-AOPs) for in situ persistent organic pollutant (POP) remediation in aqueous solutions can be a promising technology. However, this technology is constrained by its high toxicity and cost of metal oxide and non-metal catalysts for PMS activation. Here, we investigated the catalytic performance of a widely available natural mineral, manganese ore (MO), for PMS activation. A series of natural MO samples in an aqueous solution were prepared via the Fenton-like reaction. The samples\u27 crystalline structure, surface morphology, textural properties, and other surface characteristics of the selected MO were systematically characterized. The effects of PMS concentration and process parameters on the degradation performance of four chosen model pollutants, that is, phenol, tetrabromobisphenol A (TBBPA), rhodamine B (RhB), and methylene blue (MB), were evaluated. The experimental results showed that natural MO increased catalytic activity and enhanced the PMS oxidation processes, with 98%, 90%, and 75% removal efficiencies on phenol, TBBPA, and RhB, respectively, within 1.5 h. The reduction in the initial pH solution from 10 to 7 and the increase in temperature from 15 to 45°C enhanced the MB degradation rate (decolorization) by 55 and 46%, respectively, within 2 h. During the PMS activation process, SO4−, OH, and 1O2 species were generated, but only SO4− and OH radicals with strong oxidative potentials contributed to the catalytic degradation. The dissolved metals from the experiments were found well within the limit of drinking water standards, verifying that the MO + PMS catalytic system is suitable for commercial applications. This work provides insights into the development potential and prospects of using natural minerals for PMS activation and POP degradation, which can accelerate their industrial applications

Experimental Evaluation of Water Control for Continuous Packer in Buried Hill Fractured Gas Reservoir: A Case Study of HZ 26-6 Condensate Gas Field

AbstractAlthough research into water control completion techniques is now relatively mature, there are still difficulties in controlling water in fractured gas reservoirs in the sea. Unlike oil reservoirs, submerged gas reservoir development still faces some problems. To explore the water control mechanism of buried hill fractured gas reservoir, based on the parameters of well HZ26-6-2 in HZ 26-6 condensate gas field, the water control experiment of the continuous packer in the bottom water gas reservoir was completed through the design of experimental parameters, the design of buried hill fractured formation, and the process design of continuous packer. Studies have shown that the continuous packer water control technology delays the water coning rate and makes the water propulsion more uniform. The water breakthrough time and gas production are slightly different for different fractured gas reservoirs, and the network fracture model has a short gas recovery period and fast gas production speed. Continuous packer water control can improve natural gas recovery by 14.3% in fractured gas reservoir. Based on fracture dredging ability, sand accumulation and filling degree, and drilling and production strategy, the influencing factors of horizontal well water control effect in buried hill fractured gas reservoir are discussed and summarized. The research results are aimed at establishing a development model of water control for buried hill gas reservoirs and providing good technical support for rational and scientific water control of horizontal Wells in offshore condensate gas fields. The findings of this study can help for a better understanding of water control of horizontal wells in offshore condensate gas fields

Identification and validation of PCSK9 as a prognostic and immune-related influencing factor in tumorigenesis: a pan-cancer analysis

IntroductionProprotein convertase subtilisin/kexin-9 (PCSK9) has been primarily studied in the cardiovascular field however, its role in cancer pathophysiology remains incompletely defined. Recently, a pivotal role for PCSK9 in cancer immunotherapy was proposed based on the finding that PCSK9 inhibition was associated with enhancing the antigen presentation efficacy of target programmed cell death-1 (PD-1). Herein, we provide results of a comprehensive pan-cancer analysis of PCSK9 that assessed its prognostic and immunological functions in cancer.MethodsUsing a variety of available online cancer-related databases including TIMER, cBioPortal, and GEPIA, we identified the abnormal expression of PCSK9 and its potential clinical associations in diverse cancer types including liver, brain and lung. We also validated its role in progression-free survival (PFS) and immune infiltration in neuroblastoma.ResultsOverall, the pan-cancer survival analysis revealed an association between dysregulated PCSK9 and poor clinical outcomes in various cancer types. Specifically, PCSK9 was extensively genetically altered across most cancer types and was consistently found in different tumor types and substages when compared with adjacent normal tissues. Thus, aberrant DNA methylation may be responsible for PCSK9 expression in many cancer types. Focusing on liver hepatocellular carcinoma (LIHC), we found that PCSK9 expression correlated with clinicopathological characteristics following stratified prognostic analyses. PCSK9 expression was significantly associated with immune infiltrate since specific markers of CD8+ T cells, macrophage polarization, and exhausted T cells exhibited different PCSK9-related immune infiltration patterns in LIHC and lung squamous cell carcinoma. In addition, PCSK9 was connected with resistance of drugs such as erlotinib and docetaxel. Finally, we validated PCSK9 expression in clinical neuroblastoma samples and concluded that PCSK9 appeared to correlate with a poor PFS and natural killer cell infiltration in neuroblastoma patients.ConclusionPCSK9 could serve as a robust prognostic pan-cancer biomarker given its correlation with immune infiltrates in different cancer types, thus potentially highlighting a new direction for targeted clinical therapy of cancers

Has the Carbon Trading Pilot Market Improved Enterprises’ Export Green-Sophistication in China?

This study empirically examined the effect of a carbon trading pilot market on export green-sophistication of Chinese listed enterprises by adopting a difference-in-difference method. Findings show that a carbon trading pilot market can improve enterprises’ export green-sophistication after using robustness tests to overcome endogeneity. The impact mechanism test shows that a carbon trading pilot market can improve export green-sophistication by increasing green technology innovation. Further research on the system design of carbon trading pilot markets shows that the greater the total carbon quota allocation, the larger the reduction in the trading volume of Chinese certified emissions. Furthermore, the weaker the punishment for an enterprise’s default in the pilot areas, the less favorable it is for enterprises to improve their export green-sophistication. Compared with the grandfather and historical intensity methods, benchmarking used in the allocation of carbon quotas is conducive to the improvement of the export green-sophistication of enterprises

Has the Carbon Trading Pilot Market Improved Enterprises’ Export Green-Sophistication in China?

This study empirically examined the effect of a carbon trading pilot market on export green-sophistication of Chinese listed enterprises by adopting a difference-in-difference method. Findings show that a carbon trading pilot market can improve enterprises’ export green-sophistication after using robustness tests to overcome endogeneity. The impact mechanism test shows that a carbon trading pilot market can improve export green-sophistication by increasing green technology innovation. Further research on the system design of carbon trading pilot markets shows that the greater the total carbon quota allocation, the larger the reduction in the trading volume of Chinese certified emissions. Furthermore, the weaker the punishment for an enterprise’s default in the pilot areas, the less favorable it is for enterprises to improve their export green-sophistication. Compared with the grandfather and historical intensity methods, benchmarking used in the allocation of carbon quotas is conducive to the improvement of the export green-sophistication of enterprises

Small world and stability analysis of industrial coupling symbiosis network of ecological industrial park of oil and gas resource cities

This paper analyzes the small cosmopolitan and stability of the industrial coupling symbiotic network of eco-industrial parks of oil and gas resource-based cities. Taking Daqing A Ecological Industrial Park as an example, we constructed the characteristic index system and calculated the topological parameters such as the agglomeration coefficient and the average shortest path length of the industrial coupling symbiotic network. Based on the complex network theory we analyzed the characteristics of the scaled world, constructed the adjacency matrix of material and information transfers between enterprises, drew the network topology diagram. We simulated the system analysis and analyzed the stability of the industrial coupling symbiotic network of the eco-industrial park using the network efficiency and node load and maximum connected subgraph. The analysis results are as follows: the small world degree δ of Daqing A Eco-industrial Park is 0.891, which indicates that the industrial coupled symbiotic network has strong small world characteristics; the average path is 1.268, and the agglomeration coefficient is 0.631. The probability of edge connection between two nodes in a symbiotic network is 63.1%, which has a relatively high degree of aggregation, indicating that energy and material exchanges are frequent among all enterprises in the network, the degree of network aggregation is high, and the dependence between nodes is high; when the tolerance parameter is 0 to 0.3, the network efficiency and the maximum connected subgraphs show a sharp change trend, indicating that the topology of the industrial coupling symbiotic network of the eco-industrial park changes drastically when the network is subjected to deliberate attacks. It is easy to cause the breakage of material flow and energy flow in the industrial park, which leads to the decline of the stability of the industrial coupling symbiotic network of the eco-industrial park

Clinical Analysis of Perioperative Outcomes on Neoadjuvant Hormone Therapy before Laparoscopic and Robot-Assisted Surgery for Localized High-Risk Prostate Cancer in a Chinese Cohort

Objective: To analyze the perioperative outcomes of neoadjuvant hormone therapy (NHT) before laparoscopic and robot-assisted surgery for localized high-risk prostate cancer in a Chinese cohort. Methods: The clinical data of 385 patients with localized high-risk prostate cancer who underwent radical prostatectomy (RP) in our hospital from January 2019 to June 2021 were analyzed retrospectively, including 168 patients with preoperative NHT and 217 patients with simple surgery. Clinical characteristics were compared in the above two groups, the laparoscopic RP (LRP) cohort (n = 234) and the robot-assisted laparoscopic radical prostatectomy (RALP) cohort (n = 151), respectively. Results: In the overall cohort, compared with the control group, the NHT group had a shorter operative time, less blood loss, a lower positive surgical margin rate, and a higher proportion of Gleason score (GS) downgrading after the operation (p p > 0.05). In the LRP cohort, it was found that the NHT group also had shorter operative time, less blood loss, lower positive surgical margin rate, a higher proportion of GS downgrading after the operation, and faster recovery of urinary control than the control group (p p p p > 0.05). Conclusions: NHT can lower the difficulty of surgery, reduce positive surgical margin rate, and help recovery in short-term urinary control in patients with high-risk prostate cancer after LRP. However, we do not have evidence on the benefit of NHT in high-risk PCa patients treated with RALP. For these patients, surgery can be performed as early as possible