Miracle-dz/UniFAR-FTUs huggingface dataset:
Oral‐motor dysfunction in children who fail to thrive: organic or non‐organic?

Forty‐seven children with non‐organic failure to thrive (NOFT) were identified from a whole‐population survey of children's growth and development. A significant proportion (N=17) of these 47 children were found to have oral‐motor dysfunction (OMD) identified using a previously validated assessment tool. NOFT children with OMD and those with normal oral‐motor function (N=30) were compared in order to ascertain whether there were any neurodevelopmental differences which might explain this finding. We hypothesized that children with OMD might have a subtle neurodevelopmental disorder. Few psychosocial variables discriminated the two groups. However, cognitive stimulation within the home and cognitive‐growth fostering during mealtimes was much poorer for children with OMD. Some evidence has suggested that NOFT children with OMD may be‘biologically’more vulnerable from birth. We suggest that the continued use of the term‘non‐organic’to describe failure to thrive in such children is questionable and requires redefining.
Generating Engagement on the Make Healthy Normal Campaign Facebook Page: Analysis of Facebook Analytics

Background Facebook is increasingly being used as part of mass media campaigns in public health, including the Make Healthy Normal (MHN) campaign in New South Wales, Australia. Therefore, it is important to understand what role Facebook can play in mass media campaigns and how best to use it to augment or amplify campaign effects. However, few studies have explored this. Objective This study aimed to investigate usage of and engagement with the MHN Facebook page and to identify influential factors in driving engagement with the page. Methods We examined both post-level and page-level analytic data from Facebook from the campaign’s launch in June 2015 to September 2017. For post-level data, we conducted a series of negative binomial regressions with four different outcome measures (likes, shares, comments, post consumers), including some characteristics of Facebook posts as predictors. We also conducted time series analyses to examine associations between page-level outcomes (new page likes or “fans” and number of engaged users) and different measures of exposure to the page (number of unique users reached and total count of impressions) and to television advertising. Results Of the 392 posts reviewed, 20.7% (n=81) received a paid boost and 58.9% (n=231) were photo posts. We found that posts that received a paid boost reached significantly more users and subsequently received significantly more engagement than organic (unpaid) posts (P<.001). After adjusting for reach, we found the effect of being paid was incremental for all outcome measures for photos and links, but not videos. There were also associations between day of the week and time of post and engagement, with Mondays generally receiving less engagement and posts on a Friday and those made between 8 AM and 5 PM receiving more. At the page level, our time series analyses found that organic impressions predicted a higher number of new fans and engaged users, compared to paid impressions, especially for women. We also found no association between television advertising and engagement with the Facebook page. Conclusions Our study shows that paying for posts is important for increasing their reach, but that page administrators should look to maximize organic reach because it is associated with significantly higher engagement. Once reach is accounted for, video posts do not benefit from being paid, unlike the other post types. This suggests that page administrators should carefully consider how they use videos as part of a Facebook campaign. Additionally, the lack of association between television advertising and engagement suggests that future campaigns consider how best to link different channels to amplify effects. These results highlight the need for ongoing evaluation of Facebook pages if administrators are to maximize engagement.
Alteration of SLP 2-like immunolabeling in mitochondria signifies early cellular damage in developing and adult mouse brain

Mitochondria play a critical role in various pathways of regulated cell death. Here we propose a novel method for detection of initial derangement of mitochondria in degenerating and dying neuronal cells. The method is based on our recent finding that antibodies directed against the cannabinoid type 1 receptor (CB1) also bind the mitochondrial stomatin-like protein 2 (SLP2) that belongs to an inner mitochondrial membrane protein complex. It is well established that SLP2 regulates mitochondrial biogenesis and respiratory functions. We now show that anti-CB1 antibodies recognize conformational epitopes, but not linear amino acid sequence of SLP2. In addition we found that anti-CB1 serum mostly labels swollen mitochondria with early or advanced stages of pathology in mouse brain while other proteins of the complex may mask epitopes of SLP2 in the normal mitochondria. Although neurons and endothelial cells in healthy brains contain occasional immunopositive mitochondria detectable with anti-CB1 serum, their numbers increase significantly after hypoxic insults in parallel with signs of cellular damage. Moreover, use of electron microscopy suggests relocation of SLP2 from its normal functional position in the inner mitochondrial membrane into the mitochondrial matrix in pathological cells. Thus, SLP2like immunolabeling serves as an in situ histochemical target detecting early derangement of mitochondria. Anti-CB1 serum is crucial for this purpose because available anti-SLP2 antibodies do not provide selective labeling of mitochondria in the fixed tissue. This new detection method of mitochondrial dysfunction can benefit the in vitro research of human diseases and developmental disorders by enabling analysis in live animal models.
Generation of a Nanobody Targeting the Paraflagellar Rod Protein of Trypanosomes

Trypanosomes are protozoan parasites that cause diseases in humans and livestock for which no vaccines are available. Disease eradication requires sensitive diagnostic tools and efficient treatment strategies. Immunodiagnostics based on antigen detection are preferable to antibody detection because the latter cannot differentiate between active infection and cure. Classical monoclonal antibodies are inaccessible to cryptic epitopes (based on their size-150 kDa), costly to produce and require cold chain maintenance, a condition that is difficult to achieve in trypanosomiasis endemic regions, which are mostly rural. Nanobodies are recombinant, heat-stable, small-sized (15 kDa), antigen-specific, single-domain, variable fragments derived from heavy chain-only antibodies in camelids. Because of numerous advantages over classical antibodies, we investigated the use of nanobodies for the targeting of trypanosome-specific antigens and diagnostic potential. An alpaca was immunized using lysates of Trypanosoma evansi. Using phage display and bio-panning techniques, a cross-reactive nanobody (Nb392) targeting all trypanosome species and isolates tested was selected. Imunoblotting, immunofluorescence microscopy, immunoprecipitation and mass spectrometry assays were combined to identify the target recognized. Nb392 targets paraflagellar rod protein (PFR1) of T. evansi, T. brucei, T. congolense and T. vivax. Two different RNAi mutants with defective PFR assembly (PFR2RNAi and KIF9BRNAi) were used to confirm its specificity. In conclusion, using a complex protein mixture for alpaca immunization, we generated a highly specific nanobody (Nb392) that targets a conserved trypanosome protein, i.e., PFR1 in the flagella of trypanosomes. Nb392 is an excellent marker for the PFR and can be useful in the diagnosis of trypanosomiasis. In addition, as demonstrated, Nb392 can be a useful research or PFR protein isolation tool.
About the Influence of Illumination Models on Image Comprehension in Direct Volume Rendering

In this paper, we present a user study in which we have investigated the influence of seven state-of-the-art volumetric illumination models on the spatial perception of volume rendered images. Within the study, we have compared gradient-based shading with half angle slicing, directional occlusion shading, multidirectional occlusion shading, shadow volume propagation, spherical harmonic lighting as well as dynamic ambient occlusion. To evaluate these models, users had to solve three tasks relying on correct depth as well as size perception. Our motivation for these three tasks was to find relations between the used illumination model, user accuracy and the elapsed time. In an additional task, users had to subjectively judge the output of the tested models. After first reviewing the models and their features, we will introduce the individual tasks and discuss their results. We discovered statistically significant differences in the testing performance of the techniques. Based on these findings, we have analyzed the models and extracted those features which are possibly relevant for the improved spatial comprehension in a relational task. We believe that a combination of these distinctive features could pave the way for a novel illumination model, which would be optimized based on our findings.
Hyperactivity and its primary disorders in the childhood population

Hyperactivity is a word that is easily misunderstood. To some it means merely overactivity, to others excitability, yet again, as in this article, it can refer to a quality of behaviour which is characterised by inattention, restlessness and impatience or impulsiveness. Different interpretations of the term cause confusion in epidemiological studies. Although a common practice in the last decade has been to combine rating scales or criteria so that a syndrome of hyperactivity including at least inattention and overactivity is appraised, earlier work did not necessarily do so. Both features are necessary, the restlessness seen in hyperactive children is genuine motor overactivity, not simply excessive off-task behaviour (Porrino et ai, 1983; Taylor et al., 1991). Some studies also include features such as aggressive behaviour or emotional lability. The adoption of operational criteria for the diagnoses of the principal disorders of hyperactivity: attention deficit disorder (DSM-III), attention deficit/hyperactivity disorder (DSM-IV) and hyperkinetic disorder (ICD-10) has or will lead to greater consensus but the conceptual grounds for creating such disorder categories vary with time and culture. The earlier American conceptualisation of hyperactive child or hyperactive reaction of childhood be-
On the Security of reCAPTCHA

CAPTCHAs are a popular method for stopping automated attacks and to reduce spam on websites. The idea is to use a puzzle, that only a human being can solve, but not automated programs. Particularly text CAPTCHAs, that ask a user to decipher distorted text in an image, are widely deployed on websites and users are accustomed to this type of CAPTCHA. reCAPTCHA is one of the biggest provider of text based CAPTCHA technology and is said to be one of the most secure. Current optical character recognition methods, especially traditional segmentation methods, work unreliably on distorted words from reCAPTCHA. In this bachelor thesis, the security of reCAPTCHA is analyzed in the presence of a custom automated solver capable of holistic word recognition. Specialized preprocessing is needed for one of reCAPTCHA’s recent variants, and proposed on the basis of a machine learning algorithm. Existing object recognition methods are modified and extended to work fast in a search space of about 22’000 words. It is experimentally shown that this method works well with all recent variants of reCAPTCHA’s challenges and achieves non-trivial recognition rates.
Effective Diagnosis of Routing Disruptions from End Systems

Internet routing events are known to introduce severe disruption to applications. So far effective diagnosis of routing events has relied on proprietary ISP data feeds, resulting in limited ISP-centric views not easily accessible by customers or other ISPs. In this work, we propose a novel approach to diagnosing significant routing events associated with any large networks from the perspective of end systems. Our approach is based on scalable, collaborative probing launched from end systems and does not require proprietary data from ISPs. Using a greedy scheme for event correlation and cause inference, we can diagnose both interdomain and intradomain routing events. Unlike existing methods based on passive route monitoring, our approach can also measure the impact of routing events on end-to-end network performance. We demonstrate the effectiveness of our approach by studying five large ISPs over four months. We validate its accuracy by comparing with the existing ISP-centric method and also with events reported on NANOG mailing lists. Our work is the first to scalably and accurately diagnose routing events associated with large networks entirely from end systems.
Cholesterol-binding site of the influenza M2 protein in lipid bilayers from solid-state NMR

Significance Cholesterol is important for membrane protein function, but cholesterol-binding structures of membrane proteins are difficult to determine by X-ray crystallography and electron microscopy due to the small size and dynamic nature of cholesterol. We have developed a solid-state NMR approach to determine the cholesterol-binding structure of membrane proteins in lipid bilayers. Applied to the influenza M2 protein, the measured interatomic distances and cholesterol orientational angles indicate that cholesterol binds M2 in a substoichiometric fashion, flanking methyl-rich transmembrane (TM) residues near an amphipathic helix, without requiring a cholesterol recognition sequence motif, and this substoichiometric binding uniquely correlates with membrane curvature generation. These results give unprecedented insights into how cholesterol clusters M2 to the neck of the budding virus to mediate membrane scission. The influenza M2 protein not only forms a proton channel but also mediates membrane scission in a cholesterol-dependent manner to cause virus budding and release. The atomic interaction of cholesterol with M2, as with most eukaryotic membrane proteins, has long been elusive. We have now determined the cholesterol-binding site of the M2 protein in phospholipid bilayers using solid-state NMR spectroscopy. Chain-fluorinated cholesterol was used to measure cholesterol proximity to M2 while sterol-deuterated cholesterol was used to measure bound-cholesterol orientation in lipid bilayers. Carbon–fluorine distance measurements show that at a cholesterol concentration of 17 mol%, two cholesterol molecules bind each M2 tetramer. Cholesterol binds the C-terminal transmembrane (TM) residues, near an amphipathic helix, without requiring a cholesterol recognition sequence motif. Deuterium NMR spectra indicate that bound cholesterol is approximately parallel to the bilayer normal, with the rough face of the sterol rings apposed to methyl-rich TM residues. The distance- and orientation-restrained cholesterol-binding site structure shows that cholesterol is stabilized by hydrophobic interactions with the TM helix and polar and aromatic interactions with neighboring amphipathic helices. At the 1:2 binding stoichiometry, lipid 31P spectra show an isotropic peak indicative of high membrane curvature. This M2–cholesterol complex structure, together with previously observed M2 localization at phase boundaries, suggests that cholesterol mediates M2 clustering to the neck of the budding virus to cause the necessary curvature for membrane scission. The solid-state NMR approach developed here is generally applicable for elucidating the structural basis of cholesterol’s effects on membrane protein function.
Chronic idiopathic neutropenias and severe congenital neutropenia

Purpose of reviewChronic idiopathic and severe congenital neutropenias are rare disorders for which recent discoveries have highlighted mechanisms and consequences. Recent findingsAn inflammatory bone marrow milieu has been shown to be a major contributor to the pathophysiology of chronic idiopathic neutropenia. Activated T-lymphocytes with myelosuppressive properties and pro-apoptotic mediators, such as IFNγ, TNFα, Fas-ligand and TGFβ1 result in accelerated apoptosis of granulocytic progenitor cells. Decreased levels of the anti-inflammatory cytokine IL-10 further disturb the balance between survival and pro-apoptotic mediators in chronic idiopathic neutropenia. Mutations in the HAX1 gene are associated with most cases of recessive autosomal severe congenital neutropenia, while ELA2 mutations are found in most cases of autosomal dominant and sporadic cases. The role of HAX-1 protein as a regulatory step in apoptosis provides further evidence for severe congenital neutropenia as a disorder of programmed cell death. The preleukemic character of severe congenital neutropenia, particularly for patients with need for high granulocyte colony stimulating factor dosage, was recently emphasized. SummaryChronic idiopathic (or as recent data suggest, immunologic) and severe congenital neutropenias provide intriguing models for better understanding of regulation of myelopoiesis. Similarities and differences between the two disorders might help to dissect these regulatory events.
A Mobile Web Focused Search Engine Using Implicit Feedback

The diverse backgrounds of Web users lead to the notion of personalized search engines. Traditional search engines normally provide the same ranked search results to everyone. The concept of “one ranking fits all” of search engines is not effective, especially when the search is from a personal mobile device. This personalization can be achieved by a machine-learning algorithm, which learns from implicit feedback provided by the users in the form of clicks. This research provides personalized rankings based on this collected implicit feedback data by using support vector machines (SVM). The support vector machine builds a unique model according to the user-feedback data. Search results are ranked according to the unique model to meet each user‟s specific needs. The proposed system greatly improves the overall ranking quality of search results.
Computational Intelligence for Software Engineering (NII Shonan Meeting 2014-13)

his talk summarises a small number of projects that I have worked on that exploit heuristic search to produce human competitive software artefacts. These projects range from the automatic construction of rules deﬁning the core of an optimising compiler; the discovery of non-trivial recurrences from partial call trees; the evolution of navigation functions for robotic control; and the search for patches for software repair
Insights into the molecular determinants involved in cap recognition by the vaccinia virus D 10 decapping enzyme

Decapping enzymes are required for the removal of the 50-end GpppN cap of mRNAs to allow their decay in cells. While many cap-binding proteins recognize the cap structure via the stacking of the methylated guanosine ring between two aromatic residues, the precise mechanism of cap recognition by decapping enzymes has yet to be determined. In order to get insights into the interaction of decapping enzymes with the cap structure, we studied the vaccinia virus D10 decapping enzyme as a model to investigate the important features for substrate recognition by the enzyme. We demonstrate that a number of chemically modified purines can competitively inhibit the decapping reaction, highlighting the molecular features of the cap structure that are required for recognition by the enzyme, such as the nature of the moiety at positions 2 and 6 of the guanine base. A 3D structural model of the D10 protein was generated which suggests amino acids implicated in cap binding. Consequently, we expressed 17 mutant proteins with amino acid substitutions in the active site of D10 and found that eight are critical for the decapping activity. These data underscore the functional features involved in the non-canonical cap-recognition by the vaccinia virus D10 decapping
Simulated variations in atmospheric CO 2 over a Wisconsin forest using a coupled ecosystem – atmosphere model

Ecosystem fluxes of energy, water, and CO2 result in spatial and temporal variations in atmospheric properties. In principle, these variations can be used to quantify the fluxes through inverse modelling of atmospheric transport, and can improve the understanding of processes and falsifiability of models. We investigated the influence of ecosystem fluxes on atmospheric CO2 in the vicinity of the WLEF-TV tower in Wisconsin using an ecophysiological model (Simple Biosphere, SiB2) coupled to an atmospheric model (Regional Atmospheric Modelling System). Model parameters were specified from satellite imagery and soil texture data. In a companion paper, simulated fluxes in the immediate tower vicinity have been compared to eddy covariance fluxes measured at the tower, with meteorology specified from tower sensors. Results were encouraging with respect to the ability of the model to capture observed diurnal cycles of fluxes. Here, the effects of fluxes in the tower footprint were also investigated by coupling SiB2 to a highresolution atmospheric simulation, so that the model physiology could affect the meteorological environment. These experiments were successful in reproducing observed fluxes and concentration gradients during the day and at night, but revealed problems during transitions at sunrise and sunset that appear to be related to the canopy radiation parameterization in SiB2.
Discovering Spatial Contexts for Traffic Flow Prediction with Sparse Representation Based Variable Selection

A new methodology based on sparse representation is proposed to detect the relevant sensors for traffic flow prediction at a given sensor. It performs remarkably better than the least square fitting and the local spatial context based methods. Some interesting phenomena have been observed in the experiments: (1) In general, hundreds of sensors distributed on the whole road network are relevant to a prediction task, which implies a much wider correlation range than what was assumed previously. (2) The number of relevant sensors is subject to the targeted sensor undergoing prediction due to location-specific network topology. (3) The spatial correlation scale increases with the increment of time lag while the performance degradation is less than that of the local spatial context based methods. As the scope of human mobility is subject to time lag, identifying the varying spatial context against time lag is crucial for prediction.
Offline and Online POMDP Solution Approaches for Roomba Navigation

This paper compares the implementation of three unique POMDP 1 solution methods to a common agent and operating environment. The 2 paper begins with a detailed introduction of the common environment 3 by describing the agent, a Roomba, its physical operating environ4 ment, a single room, and the resulting state, action, and observable 5 space. One offline and two online POMDP solution methods are 6 tested with an explanation of their implementation in relation to the 7 environment. QMDP is the offline solution method and POMCP 8 and POMCPOW are the two online solution methods implemented. 9 Solution method results are compared according to a performance 10 metric introduced in the paper. We find that QMDP is outperformed 11 by both POMCP and POMCPOW, while POMCPOW has a slightly 12 better performance measure than POMCP. 13