Construction of nested space-filling designs

New types of designs called nested space-filling designs have been proposed for conducting multiple computer experiments with different levels of accuracy. In this article, we develop several approaches to constructing such designs. The development of these methods also leads to the introduction of several new discrete mathematics concepts, including nested orthogonal arrays and nested difference matrices.Comment: Published in at http://dx.doi.org/10.1214/09-AOS690 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

A reinforced learning approach to optimal design under model uncertainty

Optimal designs are usually model-dependent and likely to be sub-optimal if the postulated model is not correctly specified. In practice, it is common that a researcher has a list of candidate models at hand and a design has to be found that is efficient for selecting the true model among the competing candidates and is also efficient (optimal, if possible) for estimating the parameters of the true model. In this article, we use a reinforced learning approach to address this problem. We develop a sequential algorithm, which generates a sequence of designs which have asymptotically, as the number of stages increases, the same efficiency for estimating the parameters in the true model as an optimal design if the true model would have correctly been specified in advance. A lower bound is established to quantify the relative efficiency between such a design and an optimal design for the true model in finite stages. Moreover, the resulting designs are also efficient for discriminating between the true model and other rival models from the candidate list. Some connections with other state-of-the-art algorithms for model discrimination and parameter estimation are discussed and the methodology is illustrated by a small simulation study

Interaction balance in symmetrical factorial designs with generalized minimum aberration

Abstract: In this paper, the issue of balance pattern of the interaction columns of a symmetrical design is considered according to orthogonal components system. The minimum interaction unbalance criterion is proposed for ranking and comparing s-level factorial designs, where s is any a prime or a prime power. It is further showed that the interaction unbalance pattern is just the generalized wordlength pattern defined b

Intracranial management of HER-2 overexpression breast cancer with extensive volume or symptomatic brain metastases

ObjectivesThis study aimed to evaluate the impact of high intracranial burden and symptomatic presentation of brain metastases on treatment outcomes in patients with HER-2 positive breast cancer. Through a retrospective analysis, we explored the intracranial responses following the application of HER-2 targeted therapy alone or in combination with other modalities and further elucidated the relationship between treatment efficacy, intracranial progression-free survival (PFS), overall survival (OS), and the burden of intracranial lesions and symptomatic presentations.MethodsA retrospective analysis was conducted on cases of HER-2 overexpressing breast cancer patients with brain metastases. Clinical records were reviewed to extract patient demographics, treatment modalities, and intracranial disease characteristics. Intracranial tumor burden was quantified at diagnosis and post-initial treatment. High intracranial tumor burden was defined as either total metastatic volume >15 cc, or the largest lesion >3 cm. Responses were assessed using established criteria. The correlation between intracranial disease parameters and intracranial progression-free survival (PFS) and overall survival (OS) was determined.ResultsThe study comprised 65 patients with HER-2 overexpression breast cancer and brain metastases. Symptomatic presentation was observed in 69.2% of patients at the diagnosis of brain metastases. Treatment with HER-2 target therapy alone or in combination with other modalities resulted in substantial intracranial responses, with 81.5% achieving at least a partial response at 3 months from therapy initiation. Median intracranial PFS and OS for patients with high intracranial burden were 9 and 22 months, respectively. Patients with high intracranial burden and symptomatic presentation at diagnosis demonstrated worse PFS and OS to those with lower burden and absence of symptoms (p < 0.05 for each).ConclusionsHer-2 overexpressing breast cancer and brain metastases face significant challenges, particularly those with high intracranial tumor burden, which correlates with poorer outcomes and higher incidence of leptomeningeal metastasis. Most patients responded positively to initial therapies, especially anti-HER-2 treatments combined with radiotherapy. Larger tumors necessitated more comprehensive treatment approaches, such as WBRT and SRS. Key factors influencing intracranial tumor control included the Ki-67 index, intracranial tumor burden, and continuous use of HER-2 targeted therapy post-diagnosis

Expert Consensus on Microtransplant for Acute Myeloid Leukemia in Elderly Patients -Report From the International Microtransplant Interest Group

Recent studies have shown that microtransplant (MST) could improve outcome of patients with elderly acute myeloid leukemia (EAML). To further standardize the MST therapy and improve outcomes in EAML patients, based on analysis of the literature on MST, especially MST with EAML from January 1st, 2011 to November 30th, 2022, the International Microtransplant Interest Group provides recommendations and considerations for MST in the treatment of EAML. Four major issues related to MST for treating EAML were addressed: therapeutic principle of MST (1), candidates for MST (2), induction chemotherapy regimens (3), and post-remission therapy based on MST (4). Others included donor screening, infusion of donor cells, laboratory examinations, and complications of treatment

An Automatic Tree Skeleton Extraction Approach Based on Multi-View Slicing Using Terrestrial LiDAR Scans Data

Effective 3D tree reconstruction based on point clouds from terrestrial Light Detection and Ranging (LiDAR) scans (TLS) has been widely recognized as a critical technology in forestry and ecology modeling. The major advantages of using TLS lie in its rapidly and automatically capturing tree information at millimeter level, providing massive high-density data. In addition, TLS 3D tree reconstruction allows for occlusions and complex structures from the derived point cloud of trees to be obtained. In this paper, an automatic tree skeleton extraction approach based on multi-view slicing is proposed to improve the TLS 3D tree reconstruction, which borrowed the idea from the medical imaging technology of X-ray computed tomography. Firstly, we extracted the precise trunk center and then cut the point cloud of the tree into slices. Next, the skeleton from each slice was generated using the kernel mean shift and principal component analysis algorithms. Accordingly, these isolated skeletons were smoothed and morphologically synthetized. Finally, the validation in point clouds of two trees acquired from multi-view TLS further demonstrated the potential of the proposed framework in efficiently dealing with TLS point cloud data