Semi-supervised Learning based on Distributionally Robust Optimization

We propose a novel method for semi-supervised learning (SSL) based on data-driven distributionally robust optimization (DRO) using optimal transport metrics. Our proposed method enhances generalization error by using the unlabeled data to restrict the support of the worst case distribution in our DRO formulation. We enable the implementation of our DRO formulation by proposing a stochastic gradient descent algorithm which allows to easily implement the training procedure. We demonstrate that our Semi-supervised DRO method is able to improve the generalization error over natural supervised procedures and state-of-the-art SSL estimators. Finally, we include a discussion on the large sample behavior of the optimal uncertainty region in the DRO formulation. Our discussion exposes important aspects such as the role of dimension reduction in SSL

Reproducible Increased Mg Incorporation and Large Hole Concentration in GaN Using Metal Modulated Epitaxy

The metal modulated epitaxy (MME) growth technique is reported as a reliable approach to obtain reproducible large hole concentrations in Mg-doped GaN grown by plasma-assisted molecular-beam epitaxy on c-plane sapphire substrates. An extremely Ga-rich flux was used, and modulated with the Mg source according to the MME growth technique. The shutter modulation approach of the MME technique allows optimal Mg surface coverage to build between MME cycles and Mg to incorporate at efficient levels in GaN films. The maximum sustained concentration of Mg obtained in GaN films using the MME technique was above 7 × 1020 cm-3, leading to a hole concentration as high as 4.5 × 1018 cm-3 at room temperature, with a mobility of 1.1 cm2 V-1 s-1 and a resistivity of 1.3 Ω cm. At 580 K, the corresponding values were 2.6 × 1019 cm-3, 1.2 cm2 V-1 s-1, and 0.21 Ω cm, respectively. Even under strong white light, the sample remained p-type with little change in the electrical parameters. © 2008 American Institute of Physics

Metal Modulation Epitaxy Growth for Extremely High Hole Concentrations Above 10(19) cm(-3) in GaN

The free hole carriers in GaN have been limited to concentrations in the low 1018 cm−3 range due to the deep activation energy, lower solubility, and compensation from defects, therefore, limiting doping efficiency to about 1%. Herein, we report an enhanced doping efficiency up to ~10% in GaN by a periodic doping, metal modulation epitaxy growth technique. The hole concentrations grown by periodically modulating Ga atoms and Mg dopants were over ~1.5 x 1019 cm−3. © 2008 American Institute of Physics

Breeding without Breeding: Is a Complete Pedigree Necessary for Efficient Breeding?

Complete pedigree information is a prerequisite for modern breeding and the ranking of parents and offspring for selection and deployment decisions. DNA fingerprinting and pedigree reconstruction can substitute for artificial matings, by allowing parentage delineation of naturally produced offspring. Here, we report on the efficacy of a breeding concept called “Breeding without Breeding” (BwB) that circumvents artificial matings, focusing instead on a subset of randomly sampled, maternally known but paternally unknown offspring to delineate their paternal parentage. We then generate the information needed to rank those offspring and their paternal parents, using a combination of complete (full-sib: FS) and incomplete (half-sib: HS) analyses of the constructed pedigrees. Using a random sample of wind-pollinated offspring from 15 females (seed donors), growing in a 41-parent western larch population, BwB is evaluated and compared to two commonly used testing methods that rely on either incomplete (maternal half-sib, open-pollinated: OP) or complete (FS) pedigree designs. BwB produced results superior to those from the incomplete design and virtually identical to those from the complete pedigree methods. The combined use of complete and incomplete pedigree information permitted evaluating all parents, both maternal and paternal, as well as all offspring, a result that could not have been accomplished with either the OP or FS methods alone. We also discuss the optimum experimental setting, in terms of the proportion of fingerprinted offspring, the size of the assembled maternal and paternal half-sib families, the role of external gene flow, and selfing, as well as the number of parents that could be realistically tested with BwB

An eHealth System Supporting Palliative Care for Patients with Non-Small Cell Lung Cancer: A Randomized Trial

BACKGROUND: In this study, the authors examined the effectiveness of an online support system (Comprehensive Health Enhancement Support System [CHESS]) versus the Internet in relieving physical symptom distress in patients with non-small cell lung cancer (NSCLC). METHODS: In total, 285 informal caregiver-patient dyads were assigned randomly to receive, for up to 25 months, standard care plus training on and access to either use of the Internet and a list of Internet sites about lung cancer (the Internet arm) or CHESS (the CHESS arm). Caregivers agreed to use CHESS or the Internet and to complete bimonthly surveys; for patients, these tasks were optional. The primary endpoint-patient symptom distress-was measured by caregiver reports using a modified Edmonton Symptom Assessment Scale. RESULTS: Caregivers in the CHESS arm consistently reported lower patient physical symptom distress than caregivers in the Internet arm. Significant differences were observed at 4 months (P = .031; Cohen d = .42) and at 6 months (P = .004; d = .61). Similar but marginally significant effects were observed at 2 months (P = .051; d = .39) and at 8 months (P = .061; d = .43). Exploratory analyses indicated that survival curves did not differ significantly between the arms (log-rank P = .172), although a survival difference in an exploratory subgroup analysis suggested an avenue for further study. CONCLUSIONS: The current results indicated that an online support system may reduce patient symptom distress. The effect on survival bears further investigation

Latent transforming growth factor binding protein 4 (LTBP4) is downregulated in mouse and human DCIS and mammary carcinomas

Transforming growth factor beta (TGF-) is able to inhibit the proliferation of epithelial cells and is involved in the carcinogenesis of mammary tumors. Three latent transforming growth factor- binding proteins (LTBPs) are known to modulate TGF- functions. The current study analyses the expression profiles of LTBP4, its isoforms LTBP1 and LTBP3, and TGF-1, TGF-2, TGF-3, and SMAD2, SMAD3 and SMAD4 in human and murine (WAP-TNP8) DCIS compared to invasive mammary tumors. Additionally mammary malignant (MCF7, Hs578T, MDA-MB361) and non malignant cell lines (Hs578BsT) were analysed. Microarray, q-PCR, immunoblot, immunohistochemistry and immunofluorescence were used. In comparison to non-malignant tissues (n = 5), LTBP4 was downregulated in all human and mouse DCIS (n = 9) and invasive mammary adenocarcinomas (n = 5) that were investigated. We also found decreased expression of bone morphogenic protein 4 (BMP4) and increased expression of its inhibitor gremlin (GREM1). Treatment of the mammary tumor cell line (Hs578T) with recombinant TGF-1 rescued BMP4 and GREM1 expression. We conclude that the lack of LTBP4-mediated targeting in malignant mammary tumor tissues may lead to a possible modification of TGF-1 and BMP bioavailability and function