Intelligent Knowledge Beyond Data Mining: Influences of Habitual Domains

Data mining is a useful analytic method and has been increasingly used by organizations to gain insights from large-scale data. Prior studies of data mining have focused on developing automatic data mining models that belong to first-order data mining. Recently, researchers have called for more study of the second-order data mining process. Second-order data mining process is an important step to convert data mining results into intelligent knowledge, i.e., actionable knowledge. Specifically, second-order data mining refers to the post-stage of data mining projects in which humans collectively make judgments on data mining models’ performance. Understanding the second-order data mining process is valuable in addressing how data mining can be used best by organizations in order to achieve competitive advantages. Drawing on the theory of habitual domains, this study developed a conceptual model for understanding the impact of human cognition characteristics on second-order data mining. Results from a field survey study showed significant correlations between habitual domain characteristics, such as educational level and prior experience with data mining, and human judgments on classifiers’ performance

Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke

Importance It is uncertain whether intravenous methylprednisolone improves outcomes for patients with acute ischemic stroke due to large-vessel occlusion (LVO) undergoing endovascular thrombectomy. Objective To assess the efficacy and adverse events of adjunctive intravenous low-dose methylprednisolone to endovascular thrombectomy for acute ischemic stroke secondary to LVO. Design, Setting, and Participants This investigator-initiated, randomized, double-blind, placebo-controlled trial was implemented at 82 hospitals in China, enrolling 1680 patients with stroke and proximal intracranial LVO presenting within 24 hours of time last known to be well. Recruitment took place between February 9, 2022, and June 30, 2023, with a final follow-up on September 30, 2023.InterventionsEligible patients were randomly assigned to intravenous methylprednisolone (n = 839) at 2 mg/kg/d or placebo (n = 841) for 3 days adjunctive to endovascular thrombectomy. Main Outcomes and Measures The primary efficacy outcome was disability level at 90 days as measured by the overall distribution of the modified Rankin Scale scores (range, 0 [no symptoms] to 6 [death]). The primary safety outcomes included mortality at 90 days and the incidence of symptomatic intracranial hemorrhage within 48 hours. Results Among 1680 patients randomized (median age, 69 years; 727 female [43.3%]), 1673 (99.6%) completed the trial. The median 90-day modified Rankin Scale score was 3 (IQR, 1-5) in the methylprednisolone group vs 3 (IQR, 1-6) in the placebo group (adjusted generalized odds ratio for a lower level of disability, 1.10 [95% CI, 0.96-1.25]; P = .17). In the methylprednisolone group, there was a lower mortality rate (23.2% vs 28.5%; adjusted risk ratio, 0.84 [95% CI, 0.71-0.98]; P = .03) and a lower rate of symptomatic intracranial hemorrhage (8.6% vs 11.7%; adjusted risk ratio, 0.74 [95% CI, 0.55-0.99]; P = .04) compared with placebo. Conclusions and Relevance Among patients with acute ischemic stroke due to LVO undergoing endovascular thrombectomy, adjunctive methylprednisolone added to endovascular thrombectomy did not significantly improve the degree of overall disability.Trial RegistrationChiCTR.org.cn Identifier: ChiCTR210005172

A New Container Throughput Forecasting Paradigm under COVID-19

COVID-19 has imposed tremendously complex impacts on the container throughput of ports, which poses big challenges for traditional forecasting methods. This paper proposes a novel decomposition–ensemble forecasting method to forecast container throughput under the impact of major events. Combining this with change-point analysis and empirical mode decomposition (EMD), this paper uses the decomposition–ensemble methodology to build a throughput forecasting model. Firstly, EMD is used to decompose the sample data of port container throughput into multiple components. Secondly, fluctuation scale analysis is carried out to accurately capture the characteristics of the components. Subsequently, we tailor the forecasting model for every component based on the mode analysis. Finally, the forecasting results of all the components are combined into one aggregated output. To validate the proposed method, we apply it to a forecast of the container throughput of Shanghai port. The results show that the proposed forecasting model significantly outperforms its rivals, including EMD-SVR, SVR, and ARIMA

A New Container Throughput Forecasting Paradigm under COVID-19

COVID-19 has imposed tremendously complex impacts on the container throughput of ports, which poses big challenges for traditional forecasting methods. This paper proposes a novel decomposition–ensemble forecasting method to forecast container throughput under the impact of major events. Combining this with change-point analysis and empirical mode decomposition (EMD), this paper uses the decomposition–ensemble methodology to build a throughput forecasting model. Firstly, EMD is used to decompose the sample data of port container throughput into multiple components. Secondly, fluctuation scale analysis is carried out to accurately capture the characteristics of the components. Subsequently, we tailor the forecasting model for every component based on the mode analysis. Finally, the forecasting results of all the components are combined into one aggregated output. To validate the proposed method, we apply it to a forecast of the container throughput of Shanghai port. The results show that the proposed forecasting model significantly outperforms its rivals, including EMD-SVR, SVR, and ARIMA

Optimal stock and capital reserve policies for emergency medical supplies against epidemic outbreaks

Killing tens of thousand of people and bringing tremendous loss, epidemics have been one of the most huge and urgent threats for all human kind. Given the abruptness of epidemic outbreaks, quick access to sufficient medical supplies is essential. Most existing research focuses on reserving physical stocks only, while some authors also consider reserving production capacity. This study is the first to consider capital reserves besides physical stocks, a practice that is for instance used in China. We characterize in closed form and graphically under what conditions a certain reserve policy (no reserves, safety stock only, capital reserve only, mixed reserves) is optimal. A key insight is that increased demand uncertainty sometimes leads to lower safety stock levels, although the combined reserves do increase. In such situations, to limit the risk of obsolescence, it is optimal to rely less on safety stocks and more on capital reserves

Dietary Methionine Increased the Growth Performances and Immune Function of Partridge Shank Broilers after Challenged with Coccidia

The present study investigated the effects of methionine (Met) on growth, immune function, and antioxidant capacity in partridge shank broilers, which were treated with either an anticoccidial drug or a coccidia vaccine. Chickens were fed five graded levels of Met (0.33%, 0.39%, 0.45%, 0.51%, or 0.57%) for 21 days in combination with the drug or vaccine. The results revealed that an optimal level of Met supplementation (1) increased ADFI (average daily feed intake), ADG (average daily gain), and F/G values (feed-to-gain ratio), indicating improved production; (2) increased OPG levels (oocysts per gram feces), intestinal lesion scores, bursa of Fabricius and thymus indexes, and sIgA content; (3) improved GSH-Px activities, and increased content levels of T-protein, albumin, and urea nitrogen. In addition, birds in the anticoccidial drug group had higher final weights, higher ADFI and ADG values, as well as lower F/G values, compared with birds in the vaccine group, indicating that coccidia vaccine reduces the performance of broilers. In conclusion, we found that an optimal level of dietary Met improved the production of partridge shank broilers, and this result might be related to immune function and antioxidant capacity. Optimal levels of digestible Met in terms of production performance (ADG and F/G) and immune function (sIgA in ileum mucosa) in partridge shank broilers (1–21 days) were found to be 0.418, 0.451, and 0.451 of diet, respectively, when birds were given anticoccidial drug treatment, with corresponding figures of 0.444, 0.455, and 0.452% when the coccidia vaccine was administered

Coffee and cancer risk: A meta-analysis of prospective observational studies

Meta-analyses on coffee and cancer incidence mainly restricted to limited cancers. We carried out a more comprehensive meta-analysis of cohort studies to explore association between coffee and most cancer types. We conducted comprehensive search and summarized relative risk (RR) and 95% confidence intervals for the highest versus lowest coffee intake and cancer using STATA12. We conducted dose-analysis if result suggested significant association. The publication bias was evaluated with begg’s and egger’s test. Finally, 105 individual prospective studies were included. Inverse associations were observed on oral, pharyngeal, colon, liver, prostate, endometrial cancer and melanoma, with RR 0.69 (95% CI = 0.48–0.99, I2 = 73.4%, P = 0.044), 0.87 (95% CI = 0.78–0.96, I2 = 28.4%, P = 0.007), 0.46 (95% CI = 0.37–0.57, I2 = 0%, P = 0), 0.89 (95% CI = 0.84–0.93, I2 = 30.3%, P = 0.003), 0.73 (95% CI = 0.67–0.80, I2 = 0%, P = 0) and 0.89 (95% CI = 0.80–0.99, I2 = 0%, P = 0.031) respectively. However, the relative risk for lung cancer is 2.18 (95% CI = 1.26–3.75, I2 = 63.3%, P = 0.005). The summary relative risk for increment of 2 cups of coffee were RR = 0.73, 95% CI = 0.67–0.79 for liver cancer, RR = 0.97, 95% CI = 0.96–0.98 for prostate cancer and RR = 0.88, 95% CI = 0.85–0.92 for endometrial cancer. Accordingly, coffee intake was associated with reduced risk of oral, pharynx, liver, colon, prostate, endometrial cancer and melanoma and increased lung cancer risk