BACKGROUND Many older adults in the US prefer to live independently for as long as they are able, despite the onset of conditions such as frailty and dementia. Solutions are needed to enable independent living, while enhancing safety and peace of mind for their families. Elderly patients are particularly at-risk for late assessment of cognitive changes. OBJECTIVES We predict early signs of il...

Multi-Instance Learning (MIL) deals with problems where each training example is a bag, and each bag contains a set of instances. Multi-instance representation is useful in many real world applications, because it is able to capture more structural information than traditional flat single-instance representation. However, it also brings new challenges. Specifically, the distance between data ob...

Antimony (SbIII) and miltefosine (MIL) are important drugs for the treatment of Leishmania parasite infections. The mitochondrion is likely to play a central role in SbIII and MIL induced cell death in this parasite. Enriched mitochondrial samples from Leishmania promastigotes selected step by step for in vitro resistance to SbIII and MIL were subjected to differential proteomic analysis. A sha...

BACKGROUND One-per-mil tumescent solution, which contains 0.2% lidocaine with 1:1,000,000 epinephrine, has been reported to be clinically effective for hand surgery under local anesthesia. However, it was lacking in its basic pharmacokinetics profile in regard to the onset of action (OOA) and duration of action (DOA). METHODS A randomized, double-blind study was conducted on 12 volunteers who...

Many real-world pattern recognition problems can be modeled using multiple-instance learning (MIL), where instances are grouped into bags, and each bag is assigned a label. State-of-the-art MIL methods provide a high level of performance when strong assumptions are made regarding the underlying data distributions, and the proportion of positive to negative instances in positive bags. In this pa...

Multiple Instance Learning (MIL) is a popular learning technique in various vision tasks including image classification. However, most existing MIL methods do not consider the problem of insufficient examples in the given target category. In this case, it is difficult for traditional MIL methods to build an accurate classifier due to the lack of training examples. Motivated by the empirical suc...

Fe-MIL-101-NH(2) was prepared by a novel method. The MOFs adhered well to SPPO via chemical bonds, and yielded the mixed-matrix Fe-MIL-101-NH(2)-SPPO membrane for use in fuel cells. The proton conductivity of the membranes was as high as 0.10 S cm(-1) at room temperature and 0.25 S cm(-1) at 90 °C.

Introduction: The lunar meteorites Miller Range 05035 (MIL) and Meteorite Hills 01210 (MET) were collected during the 2005 and 2001 ANSMET (Antarctic Meteorite Search) field seasons [1,2]. MET is a 22.8 g regolith breccia composed primarily of basaltic material [3-6]. MIL is a 142.2 g coarse-grained basalt [2]. The bulk composition, mineral assemblage, and texture of MIL is similar to lunar met...

In the supervised learning setting termed Multiple-Instance Learning (MIL), the examples are bags of instances, and the bag label is a function of the labels of its instances, typically a Boolean OR. The learner observes the bag labels but not the instance labels that generated them. MIL has numerous applications, and many heuristic algorithms have been used successfully on this problem. Howeve...