Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials

Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment randomized trial (SMART) is an experimental design that can provide high-quality evidence for constructing optimal DTRs. In a conventional SMART, participants are randomized to available treatments at multiple stages with balanced randomization probabilities. Despite its relative simplicity of implementation and desirable performance in comparing embedded DTRs, the conventional SMART faces inevitable ethical issues including assigning many participants to the empirically inferior treatment or the treatment they dislike, which might slow down the recruitment procedure and lead to higher attrition rates, ultimately leading to poor internal and external validities of the trial results. In this context, we propose a SMART under the Experiment-as-Market framework (SMART-EXAM), a novel SMART design that holds the potential to improve participants' welfare by incorporating their preferences and predicted treatment effects into the randomization procedure. We describe the steps of conducting a SMART-EXAM and evaluate its performance compared to the conventional SMART. The results indicate that the SMART-EXAM can improve the welfare of the participants enrolled in the trial, while also achieving a desirable ability to construct an optimal DTR when the experimental parameters are suitably specified. We finally illustrate the practical potential of the SMART-EXAM design using data from a SMART for children with attention-deficit/hyperactivity disorder (ADHD)

Multi-label prediction method for lithology, lithofacies and fluid classes based on data augmentation by cascade forest

Predicting the lithology, lithofacies and reservoir fluid classes of igneous rocks holds significant value in the domains of CO2 storage and reservoir evaluation. However, no precedent exists for research on the multi-label identification of igneous rocks. This study proposes a multi-label data augmented cascade forest method for the prediction of multilabel lithology, lithofacies and fluid using 9 conventional logging data features of cores collected from the eastern depression of the Liaohe Basin in northeastern China. Data augmentation is performed on an unbalanced multi-label training set using the multi-label synthetic minority over-sampling technique. Sample training is achieved by a multi-label cascade forest consisting of predictive clustering trees. These cascade structures possess adaptive feature selection and layer growth mechanisms. Given the necessity to focus on all possible outcomes and the generalization ability of the method, a simulated well model is built and then compared with 6 typical multi-label learning methods. The outperformance of this method in the evaluation metrics validates its superiority in terms of accuracy and generalization ability. The consistency of the predicted results and geological data of actual wells verifies the reliability of our method. Furthermore, the results show that it can be used as a reliable means of multi-label prediction of igneous lithology, lithofacies and reservoir fluids.Document Type: Original articleCited as: Han, R., Wang, Z., Guo, Y., Wang, X., A, R., Zhong, G. Multi-label prediction method for lithology, lithofacies and fluid classes based on data augmentation by cascade forest. Advances in Geo-Energy Research, 2023, 9(1): 25-37. https://doi.org/10.46690/ager.2023.07.0

Asymmetric double-winged multi-view clustering network for exploring Diverse and Consistent Information

In unsupervised scenarios, deep contrastive multi-view clustering (DCMVC) is becoming a hot research spot, which aims to mine the potential relationships between different views. Most existing DCMVC algorithms focus on exploring the consistency information for the deep semantic features, while ignoring the diverse information on shallow features. To fill this gap, we propose a novel multi-view clustering network termed CodingNet to explore the diverse and consistent information simultaneously in this paper. Specifically, instead of utilizing the conventional auto-encoder, we design an asymmetric structure network to extract shallow and deep features separately. Then, by aligning the similarity matrix on the shallow feature to the zero matrix, we ensure the diversity for the shallow features, thus offering a better description of multi-view data. Moreover, we propose a dual contrastive mechanism that maintains consistency for deep features at both view-feature and pseudo-label levels. Our framework's efficacy is validated through extensive experiments on six widely used benchmark datasets, outperforming most state-of-the-art multi-view clustering algorithms

A review of building occupants adaptive behavior in buildings of China

In order to realize the sustainable development of society, building energy consumption has become a global concern. In buildings, occupants adaptive behaviors that means how to use the buildings have an very important influence on the building energy use. The researches of occupants adaptive behaviors have been carried out for more than 30 years in Europe, including England, Switzerland, Denmark and so on. In past 10 years, many Chinese scholars also started to study on this field. This paper reviewed the articles of occupants adaptive behaviors in china and summerized the current development situations then discussed the proper development direction in the future that can give some advises and references for the future study

Geometrical and electrical modulation on the transport property of silicene constrictions

We study the electrical modulation of the transport properties of silicene constrictions with different geometrical structures by adopting the tight-binding model and non-equilibrium Green's function method. The band structure and transmission properties are discussed under the influence of the external electric field and potential energy. Especially, we investigate the effects of the position and width of the central scattering region on the conductance with increasing of Fermi energy. We find that the conductance significantly depends on the position and the width. Interestingly, the symmetrical structure of the central region can induce a resonance effect and significantly enlarge the system's conductance. Obviously, we obtain an effective method to adjust the transport property of the silicene heterojunctions. Correspondingly, we propose a novel two-channel structure with an excellent performance on the conductance compared to the one-channel structure with the same total width.Comment: 7 pages, 8 figure

Resilience Mediates the Relationship Between Social Support and Quality of Life in Patients With Primary Glaucoma

Objective: Glaucoma is a serious disease causing blindness, which seriously affects the quality of life of patients. Previous studies have reported that both resilience and social support play important roles in enhancing the quality of life of patients with some diseases. The purpose of this study is to investigate if resilience mediates the relationship between social support and quality of life in patients with primary glaucoma.Methods: We conducted a cross-sectional study with 120 patients with primary glaucoma in China. The Connor-Davidson Resilience Scale was used to measure resilience, and social support was measured by the Perceived Social Support Scale. The Glaucoma Quality of Life-15 questionnaire was used to measure quality of life.Results: There were significant positive correlations between all dimensions and total scores on the resilience, social support, and quality of life scales (p < 0.01). Both resilience and social support could predict these patients' quality of life. A bootstrap test showed that resilience had a partial mediating effect on the relationship between social support and quality of life (p < 0.05).Conclusion: Resilience mediates the relationship between social support and quality of life in primary glaucoma patients. This finding suggests that increasing resilience and social support can improve the quality of life of primary glaucoma patients in clinical practice

Preparation and In Vitro Evaluation of Tacrolimus-Loaded Ethosomes

The main objective of the present work was to prepare and assess dermal delivery of tacrolimus-loaded ethosomes versus classic liposomes. Both delivery systems were characterized for particle size, polydispersity index, and entrapment efficiency (EE), by dynamic laser diffraction and ultrafiltration or dialysis methods, respectively. The results indicated that presence of ethanol in the formulations affected the particle size. In addition, ultrafiltration method was selected to determine EE due to relatively short period as compared with dialysis method. Ethosomes exhibited a significant higher EE and amount of drug in dermis in contrast to classic liposomes suggesting that ethosomes with higher entrapment capacity prompted more amount of tacrolimus to permeate through stratum corneum and reach the target of atopic dermatitis (AD). Physical stability was very well for tacrolimus-loaded ethosomes under storage condition (4°C). Our results demonstrated that the ethosomal system might be a promising candidate for dermal delivery of tacrolimus for AD

Infection and Infertility

Infection is a multifactorial process, which can be induced by a virus, bacterium, or parasite. It may cause many diseases, including obesity, cancer, and infertility. In this chapter, we focus our attention on the association of infection and fertility alteration. Numerous studies have suggested that genetic polymorphisms influencing infection are associated with infertility. So we also review the genetic influence on infection and risk of infertility