Miracle-dz/UniFAR-FTUs huggingface dataset:
Key Issues in Mobile Health and Implications for New Zealand

mHealth or mobile health describes the use of mobile communications devices for health-related purposes. There is much interest in mHealth internationally at this time; including interest in interventions developed in New Zealand/by New Zealanders. A recent research project examined the key issues in the implementation of mHealth and the current opportunities to address those issues in the U.S. The key mHealth issues are outlined here under the themes of policy and regulation, the wireless environment, the health system, current mHealth initiatives in practice and research. This paper examines how these issues may apply in New Zealand and the current opportunities to address them. This information may be useful to those embarking on mHealth developments in New Zealand and may help to inform the inclusion of mobile capabilities within the NZ Health IT infrastructure.
DISLOCATIONS, GRAIN BOUNDARIES AND FOCAL CONICS IN SMECTICS A

Simple geometrical considerations predict 3 types of tilt grain boundaries in smec- tics A : curvature of the layers, arrays of dislocations and focal domains of equal eccentricity. These 3 possibilities are shown to exist in CBOOA (shear experiment). Their energies are discussed in terms of a simple model.
Morphometrics indicates giant Ordovician macluritid gastropods switched life habit during ontogeny

Abstract Paleontologists have long speculated that the bizarre, giant Ordovician gastropods Maclurites Le Sueur, 1818 and Maclurina Ulrich and Scofield, 1897 lived more like suspension-feeding oysters than typical algivorous snails. Geometric and eigenshape morphometrics demonstrate the plausibility of this lifestyle, but with a twist. The apertures of these gastropods were small ellipsoids when young, transitioning rapidly to polygonal morphologies at maturity, with angulations (sinuses) occurring in regions associated with development of mature ctenidia (gills) and enhanced stability on the seafloor. Combined with knowledge of extant suspension-feeding gastropods and functional and phylogenetic analysis of the anatomy of other fossil relatives, this ontogenetic pattern suggests these snails began life as typical mobile algae-grazers, but switched to sedentary suspension-feeders as they aged.
A measurement study on multi-path TCP with multiple cellular carriers on high speed rails

Recent advances in high speed rails (HSRs) are propelling the need for acceptable network service in high speed mobility environments. However, previous studies show that the performance of traditional single-path transmission degrades significantly during high speed mobility due to frequent handoff. Multi-path transmission with multiple carriers is a promising way to enhance the performance, because at any time, there is possibly at least one path not suffering a handoff. In this paper, for the first time, we measure multi-path TCP (MPTCP) with two cellular carriers on HSRs with a peak speed of 310km/h. We find a significant difference in handoff time between the two carriers. Moreover, we observe that MPTCP can provide much better performance than TCP in the poorer of the two paths. This indicates that MPTCP's robustness to handoff is much higher than TCP's. However, the efficiency of MPTCP is far from satisfactory. MPTCP performs worse than TCP in the better path most of the time. We find that the low efficiency can be attributed to poor adaptability to frequent handoff by MPTCP's key operations in sub-flow establishment, congestion control and scheduling. Finally, we discuss possible directions for improving MPTCP for such scenarios.
Quantifying year around changes in a humpback whale ( Megaptera novaeangliae ) song sound using multivariate statistics and artificial neural networks

v Introduction . 1 Materials and methods . 5 Data collection . 5 Extraction of acoustic parameters . 6 Multivariate statistics . 8 Back propagation neural network . 11 Results . 15 Extraction of acoustic parameters . 15 Multivariate statistics . 15 Back propagation neural network . 20 Discussion . 21 Extraction of acoustic parameters . 21 Multivariate statistics . 23 Back propagation neural network . 25 References . 29 Appendix A: Figures and Tables . 34 Appendix B: Matlab scripts for the extraction of acoustic parameters and neural network implementation . 48
Combining complementary kernels in complex visual categorization

Bag Of Words model [1] and Fisher Vectors [2] coupled with incorporated spatial information, such as the Spatial Pyramid Matching (SPM) [3] or the spatial Fisher vectors [4], proved to reach state of the art performances in many Image categorization tasks, e.g. the PASCAL VOC challenge [5]. However, image categorization remains a very challenging task because most descriptors present strong intra-class variabilities and inter-class correlations. Therefore, a natural way to improve categorization performances consists in designing efficient feature combination strategies. It is an important issue for both computer vision and machine learning communities, that has been extensively studied in the last decade. Multiple Kernel Learning (MKL) is appealing for that purpose, since it offers the possibility to jointly learn the weighting of the different channels (features and similarity kernels) and the classification function [6]. The goal is to find the optimal classification function f defined as follows: f(x) = ∑ i αiyi ∑ m βmkm(x,xi)−b where the variable to be optimized are both the α and the w. Efficient algorithms exist for solving the related optimization convex problem [7]. Recent works attempting at using MKL on image datasets for combining different channels [8, 9] use MKL optimization algorithms based on l1 norm to regularize the kernel weights, like SimpleMKL [7]. Since this leads to sparse solutions, most studies report that MKL is often outperformed by simple baseline methods (product or averaging) [8, 9]. However, especially in our Computer Vision context, the different kernels are generated from different visual modalities, most of them being informative and many of them being complementary (e.g. edge, color and texture). Therefore, we are not interested in performing kernel selection, but we aim at finding a proper weighting between them. There exists however l2 MKL optimization schemes [10] to solve the MKL problem, but except [11], there has been few attempt to apply these schemes on image databases to find a non-sparse combination of complementary descriptors.
Survivor syndrome : effects on middle managers in South Africa

The impact oforganisational downsizing on employees who remain has been the subject of intense research, particularly in the USA. The issue of so-called survivor syndrome is critically important in relation to productivity growth and the success of restructuring. However, current conceptualisation has been based largely on American research. There has been little data on downsizing in the South African context. The purpose of this article is to discuss the extent of survivor syndrome in organisations that have restructured and downsized in South Africa. We ask the questions: does downsizing inevitably result in high levels of survivor syndrome; which factors intensify and modify survivor syndrome; and is there a restructuring cycle? The database constitutes 421 South African organisations. JELM 12
Behavioral Operations Management

Behavioral Operations Management investigates new developments around behavioral components - "people issues" - in operations management (OM). While these "people issues" are not new, OM has not dealt with them in a serious or consistent manner until the last 10 years or so. What is new is the emergence of a set of methods and structured areas of study that allow researchers to study these issues within the OM paradigm. The authors provide a definition of Behavioral OM and survey a number of relevant behavioral issues and their applications to the existing OM research. Finally, the authors propose that culture studies in OM may represent a promising direction of future behavioral OM research.
The effect of biodiversity on tree productivity: from temperate to boreal forests

Aim An important issue regarding biodiversity concerns its influence on ecosystem functioning.Experimental work has led to the proposal of mechanisms such as niche complementarity.However,few attempts have been made to confirm these in natural systems, especially in forests. Furthermore, one of the most interesting unresolved questions is whether the effects of complementarity on ecosystem functioning (EF) decrease in favour of competitive exclusions over an increasing productivity gradient. Using records from permanent forest plots, we asked the following questions. (1) Is tree productivity positively related to diversity? (2) Does the effect of diversity increase in less productive forests? (3) What metric of diversity (e.g. functional or phylogenetic diversity) better relates to tree productivity? Location Temperate, mixed and boreal forests of eastern Canada. Methods Over 12,000 permanent forest plots, from temperate to boreal forests, were used to test our hypotheses in two steps. (1) Stepwise regressions were used to identify the best explanatory variables for tree productivity. (2) The selected climatic and environmental variables,as well as density and biodiversity indices,were included in a structural equation model where links (paths) between covarying variables are made explicit, making structural equation modelling the best tool to explore such complicated causal networks. Results This is the first large-scale demonstration of a strong, positive and significant effect of biodiversity on tree productivity with control for climatic and environmental conditions. Important differences were noted between the two forest biomes investigated. Main conclusions We show for the first time that complementarity may be less important in temperate forests growing in a more stable and productive environment where competitive exclusion is the most probable outcome of species interactions, whereas in the more stressful environment of boreal forests, beneficial interactions between species may be more important. The present work is also a framework for the analysis of large datasets in biodiversity‐ecosystem functioning (B-EF) research.
Oral Antidiabetic Drugs for Cats

Diabetes mellitus (DM) is commonly diagnosed in cats. In humans, treatment regimens for non–insulin-dependent DM include various combinations of dietary modification, exercise, insulin administration, and one or more oral antidiabetic drugs, which have been extensively evaluated in humans but not in cats. Glucose toxicity is a phenomenon of chronic hyperglycemia and must be understood before interpreting response to any antidiabetic therapy. This article provides a critical review of the oral antidiabetic drugs glipizide, metformin, troglitazone, and acarbose. Diabetes mellitus (DM) is a common endocrine disorder in cats. It is estimated to affect 1 in 300 cats, with both forms of the disease defined by the ability of pancreatic beta cells to secrete insulin. Type I DM is characterized by the destruction of insulin-producing beta cells in the islets of Langerhans. Type I DM is always insulin dependent; therefore, the treatment of choice is insulin. Type II DM is characterized by defects in glucose-stimulated insulin secretion by the pancreas and in peripheral tissue sensitivity to and use of insulin. Initially, type II DM is non–insulin-dependent because of the ability of beta cells to produce some insulin. However, the progression of disease usually results in insulin dependence. In humans, treatment options for type II DM include various combinations of dietary modification, exercise, and administration of one or more oral antidiabetic drugs with or without insulin. The treatment options for type II DM in cats are not as diverse as those for humans for the following reasons: n It is difficult to discern in cats whether DM is insulin dependent, and most cats are treated as insulin-dependent diabetics. n Diabetic cats with finicky appetites may be difficult to manage with dietary changes. n Oral antidiabetic drugs have not been extensively evaluated in cats. (Nevertheless, understanding their possible role in treating feline diabetics is important for veterinarians. Use of these drugs in cats may become more commonplace, and clients often have questions regarding their use.) CE Vol. 23, No. 7 July 2001 633 n Glipizide is the only antidiabetic agent whose mechanism of action is directed at the endocrine
Changes in susceptibility to pyriproxyfen, a JH mimic, during late larval and early pupal stages of Culex pipiens molestus

Effects of pyriproxyfen were investigated in 5 strains of Culex pipiens molestus containing an organophosphorus insecticide resistant strain and a low-level resistant strain against methoprene and pyrethroids. Pyriproxyfen showed potent JH mimic activity in all strains regardless of insecticide resistance. When the susceptibility to pyriproxyfen was examined during the fourth instar to early pupa by t hr immersion test method, the susceptibility changed markedly depending on the developmental stages. The maximum susceptibility appeared from the fourth day of the fourth instar to 30 min after pupation, and the susceptibility was very low before and after that period. The stage of maximum susceptibility to pyriproxyfen did not coincide with that to methoprene; from the third day of the fourth instar to pupation, suggesting the involvement of different factors in the mode of action. Results of injection test in early pupa indicated that decline in the JH mimic susceptibility mainly depends on the decrease of cellular sensitivity to the JH mimics in the pupa, not on the change in their permeability through the cuticle.
AWARD NUMBER: W81XWH-08-1-0508 TITLE: “The Isolation and Characterization of Human Prostate Cancer Stem Cells”

BACKGROUND—The field of prostate cancer has been stymied by the difficulty of cultivating patient-derived samples in the laboratory. In order to help circumvent this challenge, we sought to develop an in vitro assay of human prostate cancer initiation employing a prostate-associated mesenchymal feeder layer. METHODS—Rat seminal vesicle mesenchyme (rSVM) harvested from male neonatal rats was plated in 12-well plates and then irradiated with 30 Gy after ~75% confluence. Single-cell suspensions of two human non-adherent prostate cancer xenograft lines (TRPC and LAPC9) were then plated on irradiated rSVM. At 3–4 weeks, three-dimensional solid structures, termed glandoids, were harvested and analyzed or transplanted singly into the renal capsule of immunodeficient mice. Animals were assessed for tumor formation 8–12 weeks after engraftment. Finally, clonality assays were performed to determine whether glandoids usually arise from a single cell and are therefore clonal in origin. RESULTS—Glandoids form with reliable frequency (1/~300 plated cells), are constituted by relevant cell types (CK8+, CK5–, PSA+) and after implantation into immunocompromised mice, give rise to tumors that recapitulate original xenograft histology and cell composition; defining a glandoid as a tumor-initiating unit. In addition, assessment of red fluorescent protein (RFP)labeled glandoids revealed either all red or non-red structures, with few areas of fusion, suggesting glandoids are clonal in origin. CONCLUSIONS—The above assay describes an adjunct technique to readily cultivate cells from prostate cancer xenografts in vitro and as such provides a platform on which tumor-initiating cell studies and high-throughput drug discovery may be performed.
Self-learning Monte Carlo method with Behler-Parrinello neural networks

We propose a general way to construct an effective Hamiltonian in the Self-learning Monte Carlo method (SLMC), which speeds up Monte Carlo simulations by training an effective model to propose uncorrelated configurations in the Markov chain. Its applications are, however, limited. This is because it is not obvious to find the explicit form of the effective Hamiltonians. Particularly, it is difficult to make trainable effective Hamiltonians including many-body interactions. In order to overcome this critical difficulty, we introduce the Behler-Parrinello neural networks (BPNNs) as "effective Hamiltonian'' without any prior knowledge, which is used to construct the potential-energy surfaces in interacting many particle systems for molecular dynamics. We combine SLMC with BPNN by focusing on a divisibility of Hamiltonian and propose how to construct the element-wise configurations. We apply it to quantum impurity models. We observed significant improvement of the acceptance ratio from 0.01 (the effective Hamiltonian with the explicit form) to 0.76 (BPNN). This drastic improvement implies that the BPNN effective Hamiltonian includes many body interaction, which is omitted in the effective Hamiltonian with the explicit forms. The BPNNs make SLMC more promising.
What is superresolution microscopy

In this paper, we discuss what is, what is not, and what is only sort of superresolution microscopy. We begin by considering optical resolution, first in terms of diffraction theory, then in terms of linear-systems theory, and finally in terms of techniques that use prior information, nonlinearity, and other tricks to improve resolution. This discussion reveals two classes of superresolution microscopy, “pseudo” and “true. ” The former improves images up to the diffraction limit, whereas the latter allows for substantial improvements beyond the diffraction limit. The two classes are distinguished by their scaling of resolution with photon counts. Understanding the limits to imaging resolution involves concepts that pertain to almost any measurement problem, implying a framework with applications beyond optics.
Triethyl Citrate (TEC) as a Dispersing Aid in Polylactic Acid/Chitin Nanocomposites Prepared via Liquid-Assisted Extrusion

The production of fully bio-based and biodegradable nanocomposites has gained attention during recent years due to environmental reasons; however, the production of these nanocomposites on the large-scale is challenging. Polylactic acid/chitin nanocrystal (PLA/ChNC) nanocomposites with triethyl citrate (TEC) at varied concentrations (2.5, 5.0, and 7.5 wt %) were prepared using liquid-assisted extrusion. The goal was to find the minimum amount of the TEC plasticizer needed to enhance the ChNC dispersion. The microscopy study showed that the dispersion and distribution of the ChNC into PLA improved with the increasing TEC content. Hence, the nanocomposite with the highest plasticizer content (7.5 wt %) showed the highest optical transparency and improved thermal and mechanical properties compared with its counterpart without the ChNC. Gel permeation chromatography confirmed that the water and ethanol used during the extrusion did not degrade PLA. Further, Fourier transform infrared spectroscopy showed improved interaction between PLA and ChNC through hydrogen bonding when TEC was added. All results confirmed that the plasticizer plays an important role as a dispersing aid in the processing of PLA/ChNC nanocomposites.
Conclave in the Tower of Babel: how peers review interdisciplinary research proposals

Peer review is a practice of research assessment where a researcher's work is evaluated by colleagues working in the same field on similar topics. Since interdisciplinary research is a new synthesis of expertise, the problem arises that peers in that sense do not exist. The aim of the paper is to show how under these conditions a specific institutional form of peer review counteracts the additional stress stemming from the interdisciplinarity of grant proposals and the multidisciplinary composition of the panel. The basis is an empirical study of networks of research groups belonging to different specialties. The key features of the procedure are the empowerment of applicants and the enforced inter-disciplinary learning of reviewers. The applicability of this procedure appears to be limited to areas where interdisciplinary research is common and where interdisciplinarity is only ‘moderate'. Copyright , Beech Tree Publishing.
From Coarse Attention to Fine-Grained Gaze: A Two-stage 3D Fully Convolutional Network for Predicting Eye Gaze in First Person Video

While predicting where people will look when viewing static scenes has been well-studied, a more challenging problem is to predict gaze within the ﬁrst-person, ego-centric ﬁeld of view as people go about daily life. This problem is difﬁcult because where a person looks depends not just on their visual surroundings, but also on the task they have in mind, their own internal state, their past gaze patterns and actions, and non-visual cues (e.g., sounds) that might attract their attention. Using data from head-mounted cameras and eye trackers that record people’s egocentric ﬁelds of view and gaze, we propose and learn a two-stage 3D fully convolutional network to predict gaze in each egocentric frame. The model estimates a coarse attention region in the ﬁrst stage, combining it with spatial and temporal features to predict a more precise gaze point in the second stage. We evaluate on a public dataset in which adults carry out speciﬁc tasks as well as on a new challenging dataset in which parents and toddlers freely interact with toys and each other, and demonstrate that our model outperforms state-of-the-art baselines.
Understanding Narrative and Embodied Interactions with "Present-at-Mind"

This workshop paper proposes the theoretical notion of "present-at-mind" as an extension of the Heideggarian categories of "present-at-hand" and "ready-to-hand". We argue that present-at-min d allows us to talk about the semantic and aestheti c qualities of embodied interaction, particularly within narrative contexts.