Miracle-dz/UniFAR-FTUs huggingface dataset:
A reliability study of an instrument for measuring general practitioner consultation skills: the LIV-MAAS scale.

OBJECTIVE To evaluate the reliability of a new tool, the LIV-MAAS, in assessing consultation competence in UK general practice. DESIGN These were pilot studies, with small numbers of participants. Videoed general practitioner (GP) consultations were analysed by trained lay and professional raters, using the LIV-MAAS. The inter-rater reliabilities were assessed. Four videos were assessed by five raters in a pilot study. After this, 71 consultations from eight doctors were assessed by sets of three raters. MAIN MEASURES Inter-rater reliabilities and inter-consultation reliabilities. RESULTS For the pilot study, the estimated inter-rater reliability ranged from 0.69 (one rater) to 0.91 (five raters). For the main study, the estimated inter-rater reliability for the LIV-MAAS checklist using two raters was 0.71, and using three raters it was 0.78. Mean differences in reliability within each series of nine consultations were 0.20 (three raters) and 0.42 (two raters). CONCLUSIONS As a measure of 'consultation competence', administered by trained raters (medical or lay) to real GP consultations, the LIV-MAAS instrument shows adequate reliability and stability but would benefit from considerable shortening. Further development of the LIV-MAAS and testing with larger samples are required.
Computational Analysis of Muscular Dystrophy Sub-types Using a Novel Integrative Scheme

To construct biologically interpretable features and facilitate Muscular Dystrophy (MD) sub-types classification, we propose a novel integrative scheme utilizing PPI network, functional gene sets information, and mRNA profiling. The workflow of the proposed scheme includes three major steps: First, by combining protein–protein interaction network structure and gene co-expression relationship into new distance metric, we apply affinity propagation clustering to build gene sub-networks. Secondly, we further incorporate functional gene sets knowledge to complement the physical interaction information. Finally, based on constructed sub-network and gene set features, we apply multi-class support vector machine (MSVM) for MD sub-type classification, and highlight the biomarkers contributing to the sub-type prediction. The experimental results show that our scheme could construct sub-networks that are more relevant to MD than those constructed by conventional approach. Furthermore, our integrative strategy substantially improved the prediction accuracy, especially for those hard-to-classify sub-types.
Operating System Support for Augmented Reality Applications

Augmented reality (AR) takes natural user input (NUI), such as gestures, voice, and eye gaze, and produces digital visual overlays on top of reality seen by a user. Today, multiple shipping AR applications exist, most notably titles for the Microsoft Kinect and smartphone applications such as Layar, Wikitude, and Junaio. Despite this activity, little attention has been paid to operating system support for AR applications. Instead, each AR application today does its own sensing and rendering, with the help of user-level libraries like OpenCV or the Microsoft Kinect SDK. In this paper, we explore how operating systems should evolve to support AR applications. Because AR applications work with fundamentally new inputs and outputs, an OS that supports AR applications needs to re-think the input and display abstractions exposed to applications. Unlike mouse and keyboard, which form explicit, separate channels for user input, NUI requires continuous sensing of the real-world environment, which often has sensitive data mixed with user input. Hence, the OS input abstractions must ensure that user privacy is not violated, and the OS must provide a fine-grained permission system for access to recognized objects like a user's face and skeleton. In addition, because visual outputs of AR applications mix real-world and virtual objects, the synthetic window abstraction in traditional GUIs is no longer viable, and OSes must rethink the display abstractions and their management. We discuss research directions for solving these and other issues and building an OS that let multiple applications share one (augmented) reality.
The challenges of exposure assessment in health studies of Gulf War veterans

A variety of exposures have been investigated in Gulf War veterans' health studies. These have most commonly been by self-report in a postal questionnaire but modelling and bio-monitoring have also been employed. Exposure assessment is difficult to do well in studies of any workplace environment. It is made more difficult in Gulf War studies where there are a number and variety of possible exposures, no agreed metrics for individual exposures and few contemporary records associating the exposure with an individual. In some studies, the exposure assessment was carried out some years after the war and in the context of media interest. Several studies have examined different ways to test the accuracy of exposure reporting in Gulf War cohorts. There is some evidence from Gulf War studies that self-reported exposures were subject to recall bias but it is difficult to assess the extent. Occupational exposure-assessment methodology can provide insights into the exposure-assessment process and how to do it well. This is discussed in the context of the Gulf War studies. Alternative exposure-assessment methodologies are presented, although these may not be suitable for widespread use in veteran studies. Due to the poor quality of and accessibility of objective military exposure records, self-assessed exposure questionnaires are likely to remain the main instrument for assessing the exposure for a large number of veterans. If this is to be the case, then validation methods with more objective methods need to be included in future study designs.
Dose-escalating and pharmacological study of oxaliplatin in adult cancer patients with impaired renal function: a National Cancer Institute Organ Dysfunction Working Group Study.

PURPOSE This study was undertaken to determine the toxicities, pharmacokinetics, and maximum tolerated doses of oxaliplatin in patients with renal impairment and to develop formal guidelines for oxaliplatin dosing in this patient population. PATIENTS AND METHODS Thirty-seven adult cancer patients with variable renal function received intravenous oxaliplatin at 60 to 130 mg/m2 every 3 weeks. Patients were stratified by 24-hour creatinine clearance (CrCL) into four cohorts: group A (controls, CrCL > or =60 mL/min), group B (mild dysfunction, CrCL 40 to 59 mL/min), group C (moderate dysfunction, CrCL 20 to 39 mL/min), and group D (severe dysfunction, CrCL <20 mL/min). Doses were escalated in cohorts of three patients, and urine and plasma ultrafiltrates were assayed for platinum concentrations. RESULTS No dose-limiting toxicities were observed in any patient group during the first cycle of therapy. Escalation of oxaliplatin to the maximum dose of 130 mg/m2 was well tolerated in all patient groups with a CrCL > or =20 mL/min (groups A, B, and C). Pharmacokinetic analysis showed that patients with decreased CrCL had a corresponding decrease in the clearance of plasma ultrafiltrable platinum (r2 = 0.765). However, oxaliplatin-induced side effects were not more common or severe in patients with mild to moderate renal dysfunction, despite the decrease in ultrafiltrable platinum clearance. CONCLUSION Oxaliplatin at 130 mg/m2 every 3 weeks is well tolerated by patients with mild to moderate degrees of renal dysfunction. These data strongly support the recommendation that dose reductions of single-agent oxaliplatin are not necessary in patients with a CrCL greater than 20 mL/min.
Design and Testing of a Wireless Portable Carbon Nanotube-Based Chemical Sensor System

The design and preliminary testing results of a wireless portable carbon nanotube-based chemical sensor system are presented in this paper. The overall sensor system consists of a chemical sensor module, a microcontroller-based data acquisition module, a multiplexer and constant current source module, and a wireless communication module. The chemical sensor module is based on use of an interdigited electrode (IDE) configuration. A layer of single-walled carbon nanotubes (SWNTs) is laid on the IDE electrodes. Chemical sensing is based on detection of changes in the conductivity of the SWNT network. The system has 32 channels of chemical sensing elements. It is self-contained and portable, and wirelessly transmits measurement data to a PC via an 802.11b wireless LAN. Preliminary results on chemical detection and chemical selectivity are described.
Property-Rights Regimes and Natural Resources: A Conceptual Analysis

The term "common-property resource" is an example of a term repeatedly used to refer to property owned by a government or by no one. It is also used for property owned by a community of resource users. Such usage leads to confusion in scientific study and policy analysis. In this paper we develop a conceptual schema for arraying property-rights regimes that distinguishes among diverse bundles of rights ranging from authorized user, to claimant, to proprietor, and to owner. We apply this conceptual schema to analyze findings from a variety of empirical settings including the Maine lobster industry.
In Vivo Imaging and Quantification of Carbonic Anhydrase IX Expression as an Endogenous Biomarker of Tumor Hypoxia

Carbonic anhydrase IX (CA IX) is a transmembrane protein that has been shown to be greatly upregulated under conditions of hypoxia in many tumor cell lines. Tumor hypoxia is associated with impaired efficacy of cancer therapies making CA IX a valuable target for preclinical and diagnostic imaging. We have developed a quantitative in vivo optical imaging method for detection of CA IX as a marker of tumor hypoxia based on a near-infrared (NIR) fluorescent derivative of the CA IX inhibitor acetazolamide (AZ). The agent (HS680) showed single digit nanomolar inhibition of CA IX as well as selectivity over other CA isoforms and demonstrated up to 25-fold upregulation of fluorescent CA IX signal in hypoxic versus normoxic cells, which could be blocked by 60%–70% with unlabeled AZ. CA IX negative cell lines (HCT-116 and MDA-MB-231), as well as a non-binding control agent on CA IX positive cells, showed low fluorescent signal under both conditions. In vivo FMT imaging showed tumor accumulation and excellent tumor definition from 6–24 hours. In vivo selectivity was confirmed by pretreatment of the mice with unlabeled AZ resulting in >65% signal inhibition. HS680 tumor signal was further upregulated >2X in tumors by maintaining tumor-bearing mice in a low oxygen (8%) atmosphere. Importantly, intravenously injected HS680 signal was co-localized specifically with both CA IX antibody and pimonidazole (Pimo), and was located away from non-hypoxic regions indicated by a Hoechst stain. Thus, we have established a spatial correlation of fluorescence signal obtained by non-invasive, tomographic imaging of HS680 with regions of hypoxia and CA IX expression. These results illustrate the potential of HS680 and combined with FMT imaging to non-invasively quantify CA IX expression as a hypoxia biomarker, crucial to the study of the underlying biology of hypoxic tumors and the development and monitoring of novel anti-cancer therapies.
How effective are ‘headspace’ youth mental health services?

Australian & New Zealand Journal of Psychiatry, 49(10) There is a high prevalence of mental disorders in Australian youth, but many of those affected do not seek professional help. In response to this treatment gap, the Australian government set up a National Youth Mental Health Foundation, ‘headspace’, in 2006. This initiative involved the setting up of an initial 10 enhanced primary care services for young people aged 12–15 years, offering early intervention for mental health and substance use problems, as well as physical health care and vocational services. These services were designed to be ‘youth-friendly’ and to overcome the stigma attached to traditional services. They also aimed to break down the age divide between adolescent and adult services. This headspace model has been enthusiastically supported by successive Australian governments, with the number of headspace centres funded due to expand to 100 by 2016. Other countries have also begun to adopt the model. However, it is important to note that this expansion has occurred in the absence of any evidence that headspace services are actually effective in improving youth mental health. While there have been descriptive studies of headspace clients, outcome data have been lacking until recently. It is therefore very welcome to see the publication of two papers by an evaluation team working for headspace (Rickwood et al., 2015a, 2015b), which give the most comprehensive data to date. What was found?
High Strain Rate Superplasticity in Ceramics

In order to attempt to industrial applications of superplastic forming, the present authors have investigated to design high strain rate superplastic zirconia ceramics. Very recently we found a new ceramic with high strain rate superplasticity (HSRS). A new ceramic, ZrO 2 (3Y)-2mol%CaO-2mol%TiO 2 were examined at deformation temperatures (T) between 1350° and 1450°C and at strain rate (e) from 10 -5 to 10 -2 s - and exhibited elongations of more than 400% even at T=1400°C and e=1.11 × 10 -2 s -1 . The present paper reports superplastic behaviors in ZrO 2 (3Y), ZrO 2 (3Y)-CaO and ZrO 2 (3Y)-CaO-TiO 2 systems and discusses the roles of dopants of CaO and TiO 2 .
An Application Framework for Controlling an Avatar in a Desktop-Based Virtual Environment via a Software SSVEP BrainComputer Interface

This paper presents a reusable, highly configurable application framework that seamlessly integrates SSVEP stimuli within a desktop-based virtual environment (VE) on standard PC equipment. Steady-state visual evoked potentials (SSVEPs) are brain signals that offer excellent information transfer rates (ITR) within braincomputer interface (BCI) systems while requiring only minimal training. Generating SSVEP stimuli in a VE allows for an easier implementation of motivating training paradigms and more realistic simulations of real-world applications. EEG measurements on seven healthy subjects within three scenarios (Button, Slalom, and Apartment) showed that moving and static software generated SSVEP stimuli flickering at frequencies of up to 29 Hz proved suitable to elicit SSVEPs. This research direction could lead to vastly improved immersive VEs that allow both disabled and healthy users to seamlessly communicate or interact through an intuitive, natural, and friendly interface.
Standardized Cannabis sativa extract attenuates tau and stathmin gene expression in the melanoma cell line

Objective(s): Metastasis is the main cause of death in patients with melanoma. Cannabis-based medicines are effective adjunctive drugs in cancer patients. Tau and Stathmin proteins are the key proteins in cancer metastasis. Here we have investigated the effect of a standardized Cannabis sativa extract on cell migration and Tau and Stathmin gene expression in the melanoma cell line. Materials and Methods: In the treatment group, melanoma (B1617) was treated 48 hr with various concentrations of standardized C. sativa extract. Cells with no treatment were considered as the control group, then study was followed by Quantitative RT-Real Time PCR assay. Relative gene expression was calculated by the ΔΔct method. Migration assay was used to evaluate cancer metastasis. Results: Tau and stathmin gene expression was significantly decreased compared to the control group. Cell migration was also significantly reduced compared to controls. Conclusion: C. sativa decreased tau and stathmin gene expression and cancer metastasis. The results may have some clinical relevance for the use of cannabis-based medicines in patients with metastatic melanoma.
Software Defined Networking for community network testbeds

Wireless Community Networks have received increasing attention the latest years. In an effort to set the cornerstone for an internet without central authorities and monopolies, network engineers throughout the world have started creating community networks. To enhance this effort, Community-lab, a wireless community networks testbed, was created which allows researchers to experiment with new protocols and applications in a realistic environment. Nevertheless, this testbed does not offer the ability to perform L2 experiments. To address this gap, we developed a platform that allows Community-Lab researchers to perform L2 experiments. Moreover, we decided to reach our goal using Software Defined Networking(SDN) techniques, due to the attention they received lately and their promise for a complete networking solution. Overall, we propose an architecture that allows researchers to perform L2 experiments in a generic community networks testbed. To prove the feasibility of our architecture we implemented it for Community-Lab using the OpenFlow SDN protocol, enabling researchers to manage their L2 topology of their experiment.
Developing Antibacterial Vaccines in Genomics and Proteomics Era

Infectious diseases are the greatest cause of global morbidity and mortality. About half of this burden is caused by pathogenic bacteria. One of the most effective ways to prevent infectious diseases is to use vaccines. Limitations in the traditional approaches may be one of the reasons why vaccines are yet not available against some infectious bacterial agents. Recent advancements in high‐throughput ‘omics’ technologies and the availability of complete genome sequences of microbial pathogens and multiple isolates of the same species have dramatically changed the time frame and scope for identifying novel vaccine candidates. At present, 582 microbial genomes have been sequenced and sequencing of 1733 is in progress. There are more than 50 bacterial species for which the genome sequence is available for three or more isolates. Development of tools for in silico analysis has led to the identification of novel virulence genes, metabolic pathways and cell surface proteins that represent potential new targets for anti‐microbial drug and vaccine strategies. In this review, we provide an overview of the ‘omics’‐based techniques that can be used to advance and accelerate the discovery of vaccine candidates against extracellular bacterial pathogens. By citing specific examples, we discuss how high‐throughput molecular profiling techniques, such as genomics, transcriptomics and proteomics have contributed to the discovery of novel vaccine candidates. We end by contemplating on the emerging technologies that are likely to have a high impact on the field of vaccinology in the near future.
Multi-Human Dialogue Understanding for Assisting Artifact-Producing Meetings

In this paper we present the dialogue-understanding components of an architecture for assisting multi-human conversations in artifact-producing meetings: meetings in which tangible products such as project planning charts are created. Novel aspects of our system include multimodal ambiguity resolution, modular ontology-driven artifact manipulation, and a meeting browser for use during and after meetings. We describe the software architecture and demonstrate the system using an example multimodal dialogue.
The Value of Active Mutual Fund Management: An Examination of the Stockholdings and Trades of Fund Managers

Abstract We investigate the value of active mutual fund management by examining the stockholdings and trades of mutual funds. We fine that stocks widely held by funds do not outperform other stocks. However, stocks purchased by funds have significantly higher returns than stocks they sell—this is true for large stocks as well as small stocks, and for value stocks as well as growth stocks. We find that growth-oriented funds exhibit better stock selection skills than income-oriented funds. Finally, we find only weak evidence that funds with the best past performance have better stock-picking skills than funds with the worst past performance.
A values-based dialogue strategy to build motivation for conversation with autonomous conversational robots

The goal of this study is to develop a humanoid robot that can conduct a continuous conversation with people. Spoken dialogue systems have recently been rapidly developed, but the existing systems are insufficient for continuous use because they fail to inspire the user's motivation to talk with them. This is because a user is unable to feel that a robot possesses its own intentions, and thus the robot must acquire its own values to convey its sense of intentionality to users through its spoken communications. This paper focuses on a dialogue strategy aimed at building people's motivation under the assumption that the robot has a values-based dialogue system. People's motivation can be influenced by the intentionality as well as by the affinity of the robot. We hypothesized that there is a good disagreement/agreement ratio in a conversation to efficiently balance people's feelings of intentionality and affinity. The result of a psychological experiment using an android robot partially supported our hypothesis.
Line Extraction from Unconstraint Handwritten Document Pages using Piece-wise Water-flow Technique

To extract the lines from multi-skewed document images of handwritten Bangla or Roman text, a novel technique is described here. In this paper, at first, the document image is partitioned into number of vertical fragments. Then a hypothetical water-flow technique is applied separately in each vertically fragmented portion of the document images, from both left and right sides of the said partition. After identifying the touching segments, separation of the same is done and finally the water-flow technique is applied on the overall document image. The stripes of areas left unwetted on the image frame are finally labelled for extraction of text lines. To test the developed technique, Bangla and Roman scripts are used and the performance of the technique, as observed experimentally, is 95.54% for the document images of the said scripts.
MAC Design for WiFi Infrastructure Networks: A Game-Theoretic Approach

In WiFi networks, mobile nodes compete for accessing a shared channel by means of a random access protocol called Distributed Coordination Function (DCF). Although this protocol is in principle fair, since all the stations have the same probability to transmit on the channel, it has been shown that unfair behaviors may emerge in actual networking scenarios because of non-standard configurations of the nodes. Due to the proliferation of open source drivers and programmable cards, enabling an easy customization of the channel access policies, we propose a game-theoretic analysis of random access schemes. We show that even when stations are selfish, efficient equilibria conditions can be reached when they are interested in both uploading and downloading traffic. We explore the utilization of the Access Point as an arbitrator for improving the global network performance. Finally, we propose and evaluate some simple DCF extensions for practically implementing our theoretical findings.