Discussion of "Estimating Random Effects via Adjustment for Density Maximization" by C. Morris and R. Tang

Discussion of "Estimating Random Effects via Adjustment for Density Maximization" by C. Morris and R. Tang [arXiv:1108.3234]Comment: Published in at http://dx.doi.org/10.1214/11-STS349A the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Rejoinder

Rejoinder of "Estimating Random Effects via Adjustment for Density Maximization" by C. Morris and R. Tang [arXiv:1108.3234]Comment: Published in at http://dx.doi.org/10.1214/11-STS349REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Deep GrabCut for Object Selection

Most previous bounding-box-based segmentation methods assume the bounding box tightly covers the object of interest. However it is common that a rectangle input could be too large or too small. In this paper, we propose a novel segmentation approach that uses a rectangle as a soft constraint by transforming it into an Euclidean distance map. A convolutional encoder-decoder network is trained end-to-end by concatenating images with these distance maps as inputs and predicting the object masks as outputs. Our approach gets accurate segmentation results given sloppy rectangles while being general for both interactive segmentation and instance segmentation. We show our network extends to curve-based input without retraining. We further apply our network to instance-level semantic segmentation and resolve any overlap using a conditional random field. Experiments on benchmark datasets demonstrate the effectiveness of the proposed approaches.Comment: BMVC 201

Adversarial Robustness: Softmax versus Openmax

Deep neural networks (DNNs) provide state-of-the-art results on various tasks and are widely used in real world applications. However, it was discovered that machine learning models, including the best performing DNNs, suffer from a fundamental problem: they can unexpectedly and confidently misclassify examples formed by slightly perturbing otherwise correctly recognized inputs. Various approaches have been developed for efficiently generating these so-called adversarial examples, but those mostly rely on ascending the gradient of loss. In this paper, we introduce the novel logits optimized targeting system (LOTS) to directly manipulate deep features captured at the penultimate layer. Using LOTS, we analyze and compare the adversarial robustness of DNNs using the traditional Softmax layer with Openmax, which was designed to provide open set recognition by defining classes derived from deep representations, and is claimed to be more robust to adversarial perturbations. We demonstrate that Openmax provides less vulnerable systems than Softmax to traditional attacks, however, we show that it can be equally susceptible to more sophisticated adversarial generation techniques that directly work on deep representations.Comment: Accepted to British Machine Vision Conference (BMVC) 201

FMNL1 promotes growth and metastasis of breast cancer by inhibiting BRCA1 via upregulation of HMGA1

In the earlier published article, “Herbei Province” included in the affiliation of the second author is incorrect. “Chongqing” is a municipality directly under the Central Government and does not belong to "Hebei Province”. At the request of the author, the correct affiliation is provided above. New citation: Zhang Q, Yang H, Tang C, Wang Q, Ren L, Jia C, et al. FMNL1 promotes growth and metastasis of breast cancer by inhibiting BRCA1 via upregulation of HMGA1. Trop J Pharm Res 2021; 20(8):1559-1564 doi: 10.4314/tjpr.v20i8.2. Erratum: 2022; 21(8): 1807 doi: 10.4314/ tjpr.v 21i8.31 Earlier citation: Zhang Q, Yang H, Tang C, Wang Q, Ren L, Jia C, et al. FMNL1 promotes growth and metastasis of breast cancer by inhibiting BRCA1 via upregulation of HMGA1. Trop J Pharm Res 2021; 20(8):1559-1564 doi: 10.4314/tjpr.v20i8.

Automatic locking knee brace joint

This invention is an apparatus for controlling the pivotal movement of a knee brace comprising a tang-and-clevis joint that has been uniquely modified. Both the tang and the clevis have a set of teeth that, when engaged, can lock the tang and the clevis together. In addition, the tang is biased away from the clevis. Consequently, when there is no axial force (i.e., body weight) on the tang, the tang is free to pivot within the clevis. However, when an axial force is exerted on the tang, the tang is pushed into the clevis, both sets of teeth engage, and the tang and the clevis lock together

FGF23 metabolism, a new paradigm for chronic kidney disease

Introduction:  Fibroblast growth factor-23 (FGF23) is a major regulator of phosphate metabolism often elevated in genetic hypophosphataemic disorders and in chronic kidney disease. Recent studies have identified relationships between FGF23 and various markers of iron status including ferritin. New assays measuring the intact form of FGF23 have been released.  Objective:  To determine the relationship between ferritin and C-terminal and intact FGF23 concentrations in blood.  Method:  FGF23 concentrations were measured using the 2nd generation, two-site enzyme-linked immunosorbent assay for either C-terminal or intact FGF23 (Immutopics Inc., Ca, USA). Ferritin was measured on a COBAS 6000 (Roche Diagnostics). Assay accuracy and precision were monitored using kit controls supplied by the manufacturers.  Results:  We observe a weak negative correlation between measurements of C-terminal and intact FGF23 (Pearson’s rho=0.85 p<0.0001). We observed no statistically significant correlation of ferritin concentrations with either FGF23 C-terminal or intact. However high concentrations of ferritin were observed in samples showing low concentrations of C-terminal FGF23 (<140RU/mL) and intact FGF23 (<122pg/mL).  Conclusion:  Although not statistically significant, we observe a negative relationship between concentrations of ferritin and FGF23. High level of C-terminal FGF23 is found in patients with chronic kidney disease, especially in patients with end-stage renal disease usually regarded as a compensatory response to hyperphosphatemia or phosphate overload. We observed a cluster of patients with retention of both C-terminal and intact FGF23 associated with low levels of ferritin suggesting that metabolism and/or excretion of FGF23 in CDK patients might be an iron dependent mechanism

Volunteer Work, Informal Help, and Care among the 50+ in Europe: Further Evidence for 'Linked' Productive Activities at Older Ages

Objectives - Taking a cross-national comparative perspective, we investigate linkages between volunteer work, informal helping, and caring among Europeans aged 50 or older: Is the relationship between these activities characterized by complementarity or by substitution? Is there evidence for the existence of (unobserved) personality traits that foster engagement independent of a specific activity? Methods - Based on 27,305 personal interviews from the 2004 Survey of Health, Ageing and Retirement in Europe (SHARE), we estimate univariate and multivariate probit models, which allow us to analyze the interrelationship between different productive activities and the derterminants of individuals' engagement therein. Results - There is substantial variation in the participation in volunteering, helping, and caring between countries and regions. Independent of the general level of activity in a country, we find evidence for a complementary and interdependent relationship between all three activities. Discussion - Our findings not only suggest an important role of societal opportunity structures in elders' productive engagement, but they also support recent notions of the existence of a general motivation for engagement in productive activities, independent of a specific domain of activity. Thus, the study of motivations should be an important aspect of future research on productive aging.