Miracle-dz/UniFAR-FTUs huggingface dataset:
A qualitative study of the role of Australian general practitioners in the surgical management of obesity

General practitioners (GPs) are increasingly managing patients with class 2 and 3 obesity (body mass index [BMI] > 35 and 40 kg/m2, respectively). Bariatric surgery is considered for patients with class 2 obesity and comorbidities or class 3 obesity where sustained weight loss using non‐surgical interventions has not been achieved. In Australia, GPs facilitate access to surgery through referral processes, but the nature of GP involvement in bariatric pre‐ and post‐surgery care is currently unclear. This qualitative study involved 10 in‐depth interviews with GPs and 20 interviews with adults who had all undergone laparoscopic adjustable gastric banding (LAGB) for weight management in Tasmania, Australia. Interviews were transcribed and analysed thematically. Referrals for bariatric surgery commonly occurred at the patient's request or to manage comorbidity. Consistent with previous studies, for GPs, referral patterns were influenced by previous case experience and patients’ financial considerations. Accessibility of surgery was also a consideration. Post‐surgery, there was a lack of clarity about the role of GPs, with patients generally preferring the surgical team to manage the LAGB. In bariatric surgery, patient preference for surgery, access and comorbidity are key drivers for referral and post‐surgical monitoring and support. Greater role clarity and enhanced collaboration between surgeons, GPs and patients following surgery is likely to enhance the experience and outcomes for patients.
Stimulus familiarity modulates functional connectivity of the perirhinal cortex and anterior hippocampus during visual discrimination of faces and objects

Recent research suggests that the medial temporal lobe (MTL) is involved in perception as well as in declarative memory. Amnesic patients with focal MTL lesions and semantic dementia patients showed perceptual deficits when discriminating faces and objects. Interestingly, these two patient groups showed different profiles of impairment for familiar and unfamiliar stimuli. For MTL amnesics, the use of familiar relative to unfamiliar stimuli improved discrimination performance. By contrast, patients with semantic dementia—a neurodegenerative condition associated with anterolateral temporal lobe damage—showed no such facilitation from familiar stimuli. Given that the two patient groups had highly overlapping patterns of damage to the perirhinal cortex, hippocampus, and temporal pole, the neuroanatomical substrates underlying their performance discrepancy were unclear. Here, we addressed this question with a multivariate reanalysis of the data presented by Barense et al. (2011), using functional connectivity to examine how stimulus familiarity affected the broader networks with which the perirhinal cortex, hippocampus, and temporal poles interact. In this study, healthy participants were scanned while they performed an odd-one-out perceptual task involving familiar and novel faces or objects. Seed-based analyses revealed that functional connectivity of the right perirhinal cortex and right anterior hippocampus was modulated by the degree of stimulus familiarity. For familiar relative to unfamiliar faces and objects, both right perirhinal cortex and right anterior hippocampus showed enhanced functional correlations with anterior/lateral temporal cortex, temporal pole, and medial/lateral parietal cortex. These findings suggest that in order to benefit from stimulus familiarity, it is necessary to engage not only the perirhinal cortex and hippocampus, but also a network of regions known to represent semantic information.
Online Graph Completion: Multivariate Signal Recovery in Computer Vision

The adoption of human-in-the-loop paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e.g., human supervision) and the underlying inference algorithms are closely interwined. While classical work in active learning provides effective solutions when the learning module involves classification and regression tasks, many practical issues such as partially observed measurements, financial constraints and even additional distributional or structural aspects of the data typically fall outside the scope of this treatment. For instance, with sequential acquisition of partial measurements of data that manifest as a matrix (or tensor), novel strategies for completion (or collaborative filtering) of the remaining entries have only been studied recently. Motivated by vision problems where we seek to annotate a large dataset of images via a crowdsourced platform or alternatively, complement results from a state-of-the-art object detector using human feedback, we study the completion problem defined on graphs, where requests for additional measurements must be made sequentially. We design the optimization model in the Fourier domain of the graph describing how ideas based on adaptive submodularity provide algorithms that work well in practice. On a large set of images collected from Imgur, we see promising results on images that are otherwise difficult to categorize. We also show applications to an experimental design problem in neuroimaging.
Correct Architecture Refinement

A method is presented for the stepwise refinement of an abstract architecture into a relatively correct lower-level architecture that is intended to implement it. A refinement step involves the application of a predefined refinement pattern that provides a routine solution to a standard architectural design problem. A pattern contains an abstract architecture schema and a more detailed schema intended to implement it. The two schemas usually contain very different architectural concepts (from different architectural styles). Once a refinement pattern is proven correct, instances of it can be used without proof in developing specific architectures. Individual refinements are compositional, permitting incremental development and local reasoning. A special correctness criterion is defined for the domain of software architecture, as well as an accompanying proof technique. A useful syntactic form of correct composition is defined. The main points are illustrated by means of familiar architectures for a compiler. A prototype implementation of the method has been used successfully in a real application. >
Generating Semantic Information for Virtual Environments

In order to build virtual humans with pleasing interactions in virtual scenarios, a consistent representation of all relevant relations and information is required. For virtual scenarios, this equates to having a meaningful (semantic) understanding of the objects and virtual agent performable actions in the scenario. The process of creating semantics for rich virtual environments is a tedious and time consuming endeavor, such that only the most pertinent pieces of information are added to the most used objects in the scene. This has the effect of decreasing realism as only a few objects can be acted upon. Furthermore, authoring relations by hand does not guarantee consistent semantics, which can also erode realism. We discuss the need and progress in automating semantic generation for objects and actions in virtual scenarios. We provide special consideration for semantics connecting objects to actions, known as operational information. We also examine the need for automated methods to generate domain specific knowledge such that a virtual environment is not overburdened by semantic information but instead finds a balance of relations.
mailVis: Visualizing emailbox for re-finding emails

We present the design and implementation of mailVis, an interactive visual interface for email boxes that facilitates re-finding of emails. Email re-finding tasks can be challenging, involving scanning of many emails and modifying the query as the search progresses. We designed mailVis for such tasks in which the user would benefit from having memory clues and multiple options to direct the search. During the design process, we devised a novel interaction technique, filter swipe, that combines filtering and selection into one action for rapidly skimming individual items in a data set.
Involvement of the "I" domain of LFA-1 in selective binding to ligands ICAM-1 and ICAM-3

To analyze the binding requirements of LFA-1 for its two most homologous ligands, ICAM-1 and ICAM-3, we compared the effects of various LFA-1 activation regimes and a panel of anti-LFA-1 mAbs in T cell binding assays to ICAM-1 or ICAM-3 coated on plastic. These studies demonstrated that T cell binding to ICAM-3 was inducible both from the exterior of the cell by Mn2+ and from the interior by an agonist of the "inside-out" signaling pathway. T cells bound both ICAM ligands with comparable avidity. A screen of 29 anti-LFA-1 mAbs led to the identification of two mAbs specific for the alpha subunit of LFA-1 which selectively blocked adhesion of T cells to ICAM-3 but not ICAM-1. These two mAbs, YTH81.5 and 122.2A5, exhibited identical blocking properties in a more defined adhesion assay using LFA-1 transfected COS cells binding to immobilized ligand. Blocking was not due to a steric interference between anti-LFA-1 mAbs and N-linked carbohydrate residues present on ICAM-3 but not ICAM-1. The epitopes of mAbs YTH81.5 and 122.2A5 were shown to map to the I domain of the LFA-1 alpha subunit. A third I domain mAb, MEM-83, has been previously reported to uniquely activate LFA-1 to bind ICAM-1 (Landis, R. C., R. I. Bennett, and N. Hogg. 1993. J. Cell Biol. 120:1519-1527). We now show that mAb MEM-83 is not able to stimulate binding of T cells to ICAM-3 over a wide concentration range. Failure to induce ICAM-3 binding by mAb MEM-83 was not due to a blockade of the ICAM-3 binding site on LFA-1. This study has demonstrated that two sets of functionally distinct mAbs recognizing epitopes in the I domain of LFA-1 are able to exert differential effects on the binding of LFA-1 to its ligands ICAM-1, and ICAM-3. These results suggest for the first time that LFA-1 is capable of binding these two highly homologous ligands in a selective manner and that the I domain plays a role in this process.
Correlation of expression of the actin filament‐bundling protein espin with stereociliary bundle formation in the developing inner ear

The vertebrate hair cell is named for its stereociliary bundle or hair bundle that protrudes from the cell's apical surface. Hair bundles mediate mechanosensitivity, and their highly organized structure plays a critical role in mechanoelectrical transduction and amplification. The prototypical hair bundle is composed of individual stereocilia, 50–300 in number, depending on the animal species and on the type of hair cell. The assembly of stereocilia, in particular, the formation during development of individual rows of stereocilia with descending length, has been analyzed in great morphological detail. Electron microscopic studies have demonstrated that stereocilia are filled with actin filaments that are rigidly cross‐linked. The growth of individual rows of stereocilia is associated with the addition of actin filaments and with progressively increasing numbers of cross‐bridges between actin filaments. Recently, a mutation in the actin filament‐bundling protein espin has been shown to underlie hair bundle degeneration in the deaf jerker mouse, subsequently leading to deafness. Our study was undertaken to investigate the appearance and developmental expression of espin in chicken inner ear sensory epithelia. We found that the onset of espin expression correlates with the initiation and growth of stereocilia bundles in vestibular and cochlear hair cells. Intense espin immunolabeling of stereocilia was colocalized with actin filament staining in all types of hair cells at all developmental stages and in adult animals. Our analysis of espin as a molecular marker for actin filament cross‐links in stereocilia is in full accordance with previous morphological studies and implicates espin as an important structural component of hair bundles from initiation of bundle assembly to mature chicken hair cells. J. Comp. Neurol. 468:125–134, 2004. © 2003 Wiley‐Liss, Inc.
An intergenic region between the tagSNP rs3793917 and rs11200638 in the HTRA1 gene indicates association with age-related macular degeneration.

PURPOSE There is still a debate as to whether the LOC387715 or HTRA1 genes represent the key significant association identified with age-related macular degeneration (AMD) on the long arm of chromosome 10, region 26. METHODS An Australian patient cohort was genotyped by using tagged single nucleotide polymorphisms (tSNPs) to identify a causal SNP within this region. RESULTS Multiple tSNPs across the region showed association with AMD with the tSNP rs3793917 (odds ratio [OR], 3.45; 95% confidence interval [CI], 2.36-5.05, P = 2.8 × 10(-13)) having the highest association with AMD. This tSNP occurred in the intergenic region between the LOC387715 and HTRA1 genes. A second tSNP rs2672587 (OR, 2.92; 95% CI, 2.04-4.17; P = 7.7 × 10(-11)) located in intron 1 of the HTRA1 gene had the second highest association with AMD. After logistic regression analysis, the only tSNP to survive covariate testing was rs3793917, which occurred in the same LD block as the HTRA1 promoter SNP rs11200638 (r(2) = 0.88, D' = 0.97). CONCLUSIONS The findings indicate that the intergenic region between the tSNP rs3793917 and the SNP rs11200638 in the HTRA1 gene is the most likely site explaining the significant association with AMD.
The Icelandic Healthcare Database and informed consent.

Modern information technology is rapidly changing how new knowledge is discovered in most fields of science, including medicine. This technology offers interesting possibilities in the development of methods to understand diseases better, but it also presents new ethical challenges. The new technology offers the possibility of mining large data sets for knowledge, without a priori hypotheses, by systematically juxtaposing various data in the search for the best fit. This kind of pure combinatorial analysis may be particularly powerful in the case of the common diseases, most of which are complex and have remained beyond the reach of the classic hypothesis-driven .
Overlapped-shaking: A local authentication method for mobile applications

Mobile applications become increasingly popular currently. Both authentication and privacy are very important for mobile applications. A promising approach for local authentication is to match the acceleration sensor samples of the two candidate smart phones. However, the acceleration sensor on the smart phones sample at different rates and the starting phases are not aligned. This paper presents a new local authentication method for mobile applications called Overlapped-shaking. Overlapped-shaking is a background service for smart phones which can measure the similarities between two shaking patterns. We design a new acceleration samples matching method called SAM, which can handle the data in different sample rates and offset at the beginning. We implement a demonstration of Overlapped-shaking service on Android smart phones. Test results show that our approach works very well for acceleration-based smart phone authentications.
EVIDENCE SUPPORTING A COGNITIVE MODEL OF DEPRESSION IN PARKINSON’S DISEASE

The objective of this study was to explore the possibility that depression in Parkinson disease (PD) arises from an illness-related vulnerability to negative emotional stimuli. The Color-Word and Emotional Stroop tasks were performed by 27 nondepressed patients with PD and 27 healthy volunteers. Patients with PD showed greater interference to the sad words of the Emotional Stroop than did control patients, despite similar performances to the controls on the neutral and Color-Word Stroop tasks. Nondepressed patients with PD may have attentional mechanisms that are vulnerable to negative stimuli. This vulnerability might arise out of a common involvement of anterior cingulate regions in both selective attention and mood regulation , and could in turn predispose to cognitive distortions that may lead to depression.
Cardiovascular Risk Factors Associated With Insulin Resistance Cluster in Families With Early-Onset Coronary Heart Disease

Coronary heart disease (CHD) is a multifactorial disease caused by environmental and genetic factors. CHD clusters in families, but it is not known whether susceptibility to early-onset CHD is associated with the clustering of cardiovascular risk factors. Therefore, we determined the levels of cardiovascular risk factors among siblings with and without severe early-onset CHD drawn from 101 Finnish families. Probands with CHD, compared with their siblings without CHD, had, respectively, higher 2-hour insulin levels (475.7 versus 331.8 pmol/L, P =0.011) and 2-hour insulin areas (796.2 versus 640.4 pmol/L per hour, P =0.031) in an oral glucose tolerance test, lower high density lipoprotein cholesterol levels (1.22 versus 1.42 mmol/L, P =0.001), higher total triglyceride levels (1.91 versus 1.68 mmol/L, P =0.018), higher very low density lipoprotein triglyceride levels (1.25 versus 1.06 mmol/L, P =0.011), and higher fibrinogen levels (3.8 versus 3.4 g/L, P = 0.008). No significant differences were found in cardiovascular risk factors between affected siblings and probands with CHD. Environmental or lifestyle factors did not differ between siblings with or without early-onset CHD. We conclude that cardiovascular risk factors associated with the insulin resistance syndrome (hyperinsulinemia, low high density lipoprotein cholesterol, high total and very low density lipoprotein triglycerides, and high fibrinogen) are likely to contribute indirectly to early-onset CHD.
Response to ‘Can indirect non‐invasive markers or models replace liver biopsy?’

lizing serum markers, imaging tests and genetic studies has not achieved sufficient acceptance yet and hence biopsy is still considered the only valid and gold standard for patients with CHB or hepatitis C on duration, planning and effectiveness of treatment (2). In fact, although the model developed in the current article has significantly high sensitivity and specificity, that should not be overlooked; 122 of 301 (41%) in all patients still need liver biopsy to make treatment decision. Utilization of both indirect and direct markers (Procollagen type 1 and type III, type IV collagen, hyaluronic acid, laminin, matrix metalloproteinases, etc.) in combination may reduce the need for biopsy in studies investigating such models (3). In conclusion, liver biopsy is still gold standard and to reduce real sense of the need for liver biopsy, more studies that have combined utilization of direct and indirect markers in developed models even with high sensitivity and specificity are needed.
Continuum tree asymptotics of discrete fragmentations and applications to phylogenetic models

Given any regularly varying dislocation measure, we identify a natural self-similar fragmentation tree as scaling limit of discrete fragmentation trees with unit edge lengths. As an application, we obtain continuum random tree limits of Aldous's beta-splitting models and Ford's alpha models for phylogenetic trees. This confirms in a strong way that the whole trees grow at the same speed as the mean height of a randomly chosen leaf.
Identification of MicroRNA-Like Molecules Derived from the Antigenome RNA of Hepatitis C Virus: A Bioinformatics Approach

MicroRNAs (miRNAs) are small, noncoding RNA molecules that play important roles in the regulation of gene expression of the cell. Recent studies have described cytoplasmic RNA virus genome- derived miRNAs. Moreover, miRNAs have also been encountered in the reverse strand of the viral mRNA, revealing the presence of miRNAs in replication intermediaries. In order to get insight into the possible role of Hepatitis C Virus (HCV) antigenome in relation to miRNA coding, we computationally identified potential miRNAs on the antigenome of HCV reference strain H77. By utilizing a series of bioinformatics tools, we identified a miRNA present in the antigenomeof HCV H77 strain. This miRNA maps in the 5’non-translated region (5’UTR) of the HCV genome and is found to be conserved among HCV genotypes and sub-types. In silico target prediction generated 17 cellular genes. These potential targets are involved in apoptosis as well as immune response pathways, suggesting that they could play a role in the pathogenesis caused by viral infection. The results of these studies revealed the presence of a viral miRNA in the negative-sense RNA strand used as a replication template for the HCV genome, as observed for other RNA viruses.
The Recognition of Handwritten Digits Based on BP Neural Network and the Implementation on Android

Offline handwriting recognition has become one of the hottest directions in the field of image processing and pattern recognition. It can transform any handwriting to plain text file and has been widely used in cheque recognition, mail sorting, reading aid for the blind and so on. In this paper, we attempt to recognize handwritten digits with feature extraction by Back Propagation(BP) neural network. The MNIST database of handwritten digits is applied to train and test the neural network. In addition, we introduce the Principal Component Analysis (PCA) for feature extraction which can improve the performance of the neural network and immensely shorten the training time. On the other hand, we make comparison of the recognition rate among three methods: neural network method, thirteen features method and Fisher discriminant analysis method. Finally, we succeed in porting these algorithms to Android.
Parallel leap: large-scale maximal pattern mining in a distributed environment

When computationally feasible, mining extremely large databases produces tremendously large numbers of frequent patterns. In many cases, it is impractical to mine those datasets due to their sheer size; not only the extent of the existing patterns, but mainly the magnitude of the search space. Many approaches have been suggested such as sequential mining for maximal patterns or searching for all frequent patterns in parallel. So far, those approaches are still not genuinely effective to mine extremely large datasets. In this work we propose a method that combines both strategies efficiently, i.e. mining in parallel for the set of maximal patterns which, to the best of our knowledge, has never been proposed efficiently before. Using this approach we could mine significantly large datasets; with sizes never reported in the literature before. We are able to effectively discover frequent patterns in a database made of billion transactions using a 32 processors cluster in less than 2 hours
A security-aware refactoring tool for Java programs

Refactoring is a useful practice in developing and maintaining software since it improves the design of existing code without changing its external behavior. Therefore, contemporary integrated development environments tend to include refactoring tools that support automatic transformations of source code. Unfortunately, some of the popular refactoring transformations make existing code vulnerable although they improve its maintainability. The existence of vulnerable code is still a serious issue for many software systems. This paper describes a tool with support for a new class of refactoring concerning software security, which is built as an Eclipse plug-in. It helps programmers to easily know the adverse impact of code changes on security vulnerabilities in the application of refactoring, and provides them with a chance to determine if they could accept or should cancel the applied refactoring. Consequently, they feel safe to improve the maintainability of existing code without missing security vulnerabilities newly inserted into the code. To evaluate the capability of this tool, we made an experiment with it. The experimental results show the usefulness of the tool and also reveal several remaining issues to be tackled.