Learning Personalized Risk Preferences for Recommendation

The rapid growth of e-commerce has made people accustomed to shopping online. Before making purchases on e-commerce websites, most consumers tend to rely on rating scores and review information to make purchase decisions. With this information, they can infer the quality of products to reduce the risk of purchase. Specifically, items with high rating scores and good reviews tend to be less risky, while items with low rating scores and bad reviews might be risky to purchase. On the other hand, the purchase behaviors will also be influenced by consumers' tolerance of risks, known as the risk attitudes. Economists have studied risk attitudes for decades. These studies reveal that people are not always rational enough when making decisions, and their risk attitudes may vary in different circumstances. Most existing works over recommendation systems do not consider users' risk attitudes in modeling, which may lead to inappropriate recommendations to users. For example, suggesting a risky item to a risk-averse person or a conservative item to a risk-seeking person may result in the reduction of user experience. In this paper, we propose a novel risk-aware recommendation framework that integrates machine learning and behavioral economics to uncover the risk mechanism behind users' purchasing behaviors. Concretely, we first develop statistical methods to estimate the risk distribution of each item and then draw the Nobel-award winning Prospect Theory into our model to learn how users choose from probabilistic alternatives that involve risks, where the probabilities of the outcomes are uncertain. Experiments on several e-commerce datasets demonstrate that our approach can achieve better performance than many classical recommendation approaches, and further analyses also verify the advantages of risk-aware recommendation beyond accuracy

An n-of-1 Trial Service in Clinical Practice: Testing the Effectiveness of Liuwei Dihuang Decoction for Kidney-Yin Deficiency Syndrome

Objective. To describe the clinical use of n-of-1 RCTs for kidney-Yin deficiency syndrome that is a traditional Chinese medicine syndrome in publicly clinical practice in China. Methods. Our study included patients with kidney-Yin deficiency syndrome, using a within-patient, randomized, double-blind, crossover comparison of Liuwei Dihuang decoction versus placebo. Outcome Measures. Primary outcome measures included number of individual completion rates, response rate, and post-n-of-1 RCTs decisions. Secondary measures were the whole group score of individual Likert scale, SF-36 questionnaire. Results. Fifty patients were recruited and 3 were not completed. Forty-seven patients completed 3 pairs of periods, 3 (6.38%) were responders, 28 (59.57%) were nonresponders, and 16 (34.05%) were possible responders. Doctors and patients used the trial results to making decision. Three responders stayed on the medication management, 28 nonresponders ceased the LDD, 7 patients of the 16 possible responders could not give clear decision, and the others kept the same medication station. Among the whole group, neither the individual Likert score nor the SF-36 showed any statistical differences between LDD and placebo. Discussion. More attention should be paid to choose experienced TCM doctor as investigator and keep the simulant same with test medication in n-of-1 RCTs of TCM and sufficiently biological half-life period of Chinese medicine compound

Dipeptidyl peptidase-4 inhibitors and risk of heart failure in type 2 diabetes : systematic review and meta-analysis of randomised and observational studies

Objectives To examine the association between dipeptidyl peptidase-4 (DPP-4) inhibitors and the risk of heart failure or hospital admission for heart failure in patients with type 2 diabetes. Design Systematic review and meta-analysis of randomised and observational studies. Data sources Medline, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov searched up to 25 June 2015, and communication with experts. Eligibility criteria Randomised controlled trials, non-randomised controlled trials, cohort studies, and case-control studies that compared DPP-4 inhibitors against placebo, lifestyle modification, or active antidiabetic drugs in adults with type 2 diabetes, and explicitly reported the outcome of heart failure or hospital admission for heart failure. Data collection and analysis Teams of paired reviewers independently screened for eligible studies, assessed risk of bias, and extracted data using standardised, pilot tested forms. Data from trials and observational studies were pooled separately; quality of evidence was assessed by the GRADE approach. Results Eligible studies included 43 trials (n=68 775) and 12 observational studies (nine cohort studies, three nested case-control studies; n=1 777 358). Pooling of 38 trials reporting heart failure provided low quality evidence for a possible similar risk of heart failure between DPP-4 inhibitor use versus control (42/15 701 v 33/12 591; odds ratio 0.97 (95% confidence interval 0.61 to 1.56); risk difference 2 fewer (19 fewer to 28 more) events per 1000 patients with type 2 diabetes over five years). The observational studies provided effect estimates generally consistent with trial findings, but with very low quality evidence. Pooling of the five trials reporting admission for heart failure provided moderate quality evidence for an increased risk in patients treated with DPP-4 inhibitors versus control (622/18 554 v 552/18 474; 1.13 (1.00 to 1.26); 8 more (0 more to 16 more)). The pooling of adjusted estimates from observational studies similarly suggested (with very low quality evidence) a possible increased risk of admission for heart failure (adjusted odds ratio 1.41, 95% confidence interval 0.95 to 2.09) in patients treated with DPP-4 inhibitors (exclusively sitagliptin) versus no use. Conclusions The relative effect of DPP-4 inhibitors on the risk of heart failure in patients with type 2 diabetes is uncertain, given the relatively short follow-up and low quality of evidence. Both randomised controlled trials and observational studies, however, suggest that these drugs may increase the risk of hospital admission for heart failure in those patients with existing cardiovascular diseases or multiple risk factors for vascular diseases, compared with no use

The Cross-Entropy Based Multi-Filter Ensemble Method for Gene Selection

The gene expression profile has the characteristics of a high dimension, low sample, and continuous type, and it is a great challenge to use gene expression profile data for the classification of tumor samples. This paper proposes a cross-entropy based multi-filter ensemble (CEMFE) method for microarray data classification. Firstly, multiple filters are used to select the microarray data in order to obtain a plurality of the pre-selected feature subsets with a different classification ability. The top N genes with the highest rank of each subset are integrated so as to form a new data set. Secondly, the cross-entropy algorithm is used to remove the redundant data in the data set. Finally, the wrapper method, which is based on forward feature selection, is used to select the best feature subset. The experimental results show that the proposed method is more efficient than other gene selection methods and that it can achieve a higher classification accuracy under fewer characteristic genes

The Cross-Entropy Based Multi-Filter Ensemble Method for Gene Selection

The gene expression profile has the characteristics of a high dimension, low sample, and continuous type, and it is a great challenge to use gene expression profile data for the classification of tumor samples. This paper proposes a cross-entropy based multi-filter ensemble (CEMFE) method for microarray data classification. Firstly, multiple filters are used to select the microarray data in order to obtain a plurality of the pre-selected feature subsets with a different classification ability. The top N genes with the highest rank of each subset are integrated so as to form a new data set. Secondly, the cross-entropy algorithm is used to remove the redundant data in the data set. Finally, the wrapper method, which is based on forward feature selection, is used to select the best feature subset. The experimental results show that the proposed method is more efficient than other gene selection methods and that it can achieve a higher classification accuracy under fewer characteristic genes

A high level of extra-pair paternity in the Chestnut Thrush (Turdus rubrocanus)

Extra-pair copulation (EPC) can potentially maximize individual reproductive fitness, and this process may involve sexual selection of male and female traits that reflect individual quality. Previous studies have implied that adult characteristics are associated with the probability of extra-pair paternity (EPP), but it differs between species. Moreover, there are relatively few examples of the adaptive rationale for females’ engagement in EPCs based on an examination of these more traditionally recorded traits, in combination with female flight-mediated traits such as wing length. We investigated whether EPP existed in the wild Chestnut Thrush (Turdus rubrocanus) population during three breeding seasons (2019–2021), and whether paternity was related to morphological traits of males and females. Eight highly variable microsatellite loci were used to identify paternity, and generalized linear mixed models were used to analyze the relationship between paternity and morphological traits. We found that EPP existed in the Chestnut Thrush. 53.3% (N ​= ​41/77) of the broods contained at least one extra-pair offspring (EPO), and 34.6% (N ​= ​72/208) of the nestlings were EPO. We also found that male wing length was negatively associated with the probability of EPP and the proportion of EPO. Female body length was positively related to the probability of EPP. Both female body condition and mass were negatively associated with the proportion of EPO. While other traits of male and female did not relate to the probability of EPP or the proportion of EPO. Extra-pair males had better body condition compared to the males they cuckolded. EPO did not differ from their half-siblings in terms of body size or body condition. The results suggest that body size and body condition were associated with EPP in the Chestnut Thrush. This study provides fundamental information for further studies on the evolution and maintenance of EPP in the Chestnut Thrush, and it is also useful for the comparison of EPP among Turdus species

Male vigilance and presence are important for foraging by female Chinese grouse in the pre-incubation period

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Soft song provokes stronger aggressive responses than broadcast song in the Plain Laughingthrush (Pterorhinus davidi)

Many bird species produce low-amplitude acoustic signals, known as soft songs, which are widely believed to function primarily in aggressive interactions. However, there are surprisingly few experimental studies that have examined whether soft songs are reliable signalling strategies for escalating aggressive interactions. Here, we investigate the functions of soft song in a colour-marked population of the Plain Laughingthrush Pterorhinus davidi, using playback experiments combined with specimen-based simulated territory intrusions. We found that playback of male soft song provoked quicker response and stronger aggressive intent by territorial pairs compared with playback of male broadcast song. Responses by territorial pairs to male soft song playback were significantly stronger compared with responses to broadcast song playback, with a greater number of flights over the speaker, more time spent within 1 m of the speaker and closer approaches to the speaker. Furthermore, closer approach with the production of soft song by focal males was the best predictor of aggressive intent in combined playback and specimen intrusion experiments. Our results suggest that male soft song is used as an aggressive signal in the Plain Laughingthrush, and represents the first evidence of such for a monogamous temperate duetting species