LLukas22/scidocs huggingface dataset:
The development and psychometric properties of a new scale to measure mental
illness related stigma by health care providers: The opening minds scale for
Health Care Providers (OMS-HC)

BACKGROUND
Research on the attitudes of health care providers towards people with mental illness has repeatedly shown that they may be stigmatizing. Many scales used to measure attitudes towards people with mental illness that exist today are not adequate because they do not have items that relate specifically to the role of the health care provider.


METHODS
We developed and tested a new scale called the Opening Minds Scale for Health Care Providers (OMS-HC). After item-pool generation, stakeholder consultations and content validation, focus groups were held with 64 health care providers/trainees and six people with lived experience of mental illness to develop the scale. The OMS-HC was then tested with 787 health care providers/trainees across Canada to determine its psychometric properties.


RESULTS
The initial testing OMS-HC scale showed good internal consistency, Cronbach's alpha = 0.82 and satisfactory test-retest reliability, intraclass correlation = 0.66 (95% CI 0.54 to 0.75). The OMC-HC was only weakly correlated with social desirability, indicating that the social desirability bias was not likely to be a major determinant of OMS-HC scores. A factor analysis favoured a two-factor structure which accounted for 45% of the variance using 12 of the 20 items tested.


CONCLUSIONS
The OMS-HC provides a good starting point for further validation as well as a tool that could be used in the evaluation of programs aimed at reducing mental illness related stigma by health care providers. The OMS-HC incorporates various dimensions of stigma with a modest number of items that can be used with busy health care providers.
Clinical Relevance of Nontuberculous Mycobacteria Isolated from Sputum in a Gold Mining Workforce in South Africa: An Observational, Clinical Study

BACKGROUND
The clinical relevance of nontuberculous mycobacteria (NTM), detected by liquid more than solid culture in sputum specimens from a South African mining workforce, is uncertain. We aimed to describe the current spectrum and relevance of NTM in this population.


METHODS
An observational study including individuals with sputum NTM isolates, recruited at workforce tuberculosis screening and routine clinics. Symptom questionnaires were administered at the time of sputum collection and clinical records and chest radiographs reviewed retrospectively.


RESULTS
Of 232 individuals included (228 (98%) male, median age 44 years), M. gordonae (60 individuals), M. kansasii (50), and M. avium complex (MAC: 38) were the commonest species. Of 38 MAC isolates, only 2 (5.3%) were from smear-positive sputum specimens and 30/38 grew in liquid but not solid culture. MAC was especially prevalent among symptomatic, HIV-positive individuals. HIV prevalence was high: 57/74 (77%) among those tested. No differences were found in probability of death or medical separation by NTM species.


CONCLUSIONS
M. gordonae, M. kansasii, and MAC were the commonest NTM among miners with suspected tuberculosis, with most MAC from smear-negative specimens in liquid culture only. HIV testing and identification of key pathogenic NTM in this setting are essential to ensure optimal treatment.
Zero-day Malware Detection based on Supervised Learning Algorithms of API call Signatures

Zero-day or unknown malware are created using code obfuscation techniques that can modify the parent code to produce offspring copies which have the same functionality but with different signatures. Current techniques reported in literature lack the capability of detecting zero-day malware with the required accuracy and efficiency. In this paper, we have proposed and evaluated a novel method of employing several data mining techniques to detect and classify zero-day malware with high levels of accuracy and efficiency based on the frequency of Windows API calls. This paper describes the methodology employed for the collection of large data sets to train the classifiers, and analyses the performance results of the various data mining algorithms adopted for the study using a fully automated tool developed in this research to conduct the various experimental investigations and evaluation. Through the performance results of these algorithms from our experimental analysis, we are able to evaluate and discuss the advantages of one data mining algorithm over the other for accurately detecting zero-day malware successfully. The data mining framework employed in this research learns through analysing the behavior of existing malicious and benign codes in large datasets. We have employed robust classifiers, namely Naïve Bayes (NB) Algorithm, k−Nearest Neighbor (kNN) Algorithm, Sequential Minimal Optimization (SMO) Algorithm with 4 differents kernels (SMO Normalized PolyKernel, SMO – PolyKernel, SMO – Puk, and SMORadial Basis Function (RBF)), Backpropagation Neural Networks Algorithm, and J48 decision tree and have evaluated their performance. _____________________________ Copyright © 2011, Australian Computer Society, Inc. This paper appeared at the 9th Australasian Data Mining Conference (AusDM 2011), Ballarat, Australia. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 121, Peter Vamplew, Andrew Stranieri, Kok-Leong Ong, Peter Christen and Paul Kennedy, Eds. Reproduction for academic, not-for profit purposes permitted provided this text is included Overall, the automated data mining system implemented for this study has achieved high true positive (TP) rate of more than 98.5%, and low false positive (FP) rate of less than 0.025, which has not been achieved in literature so far. This is much higher than the required commercial acceptance level indicating that our novel technique is a major leap forward in detecting zero-day malware. This paper also offers future directions for researchers in exploring different aspects of obfuscations that are affecting the IT world today.
Clinical evaluation of propofol as sedative for endotracheal intubation in neonates.

AIM
To determine the effects of propofol for endotracheal intubation in neonates in daily clinical practice.


METHODS
We prospectively studied the pharmacodynamic effects of intravenous propofol administration in neonates who needed endotracheal intubation at the neonatal intensive care unit.


RESULTS
Propofol was used for 62 intubations in neonates with postmenstrual ages ranging from 24 + 3 weeks to 44 + 5 weeks and bodyweights ranging from 520 to 4380 g. A 2 mg/kg bodyweight propofol starting dose was sufficient in 37% of patients; additional propofol was needed less often on the first postnatal day. The mean amount of propofol used was 3.3 (±1.2) mg/kg. The success rate of intubation depended on the experience of the physician and was related to the total administered amount of propofol. Hypotension occurred in 39% of patients and occurred more often at the first postnatal day. In 15% of procedures, propofol mono therapy was insufficient.


CONCLUSION
This study shows that high doses of propofol are needed to reach effective sedation in neonates for intubation, with hypotension as a side effect in a considerable percentage of patients. Further research in newborn patients needs to identify optimal propofol doses and risk factors for hypotension.
Tailoring a successful project-based course - in which students learn to work in teams on the development of useful software products for real clients - to the needs and resource constraints of individual colleges and universities

Workshop Summary The purpose of this workshop is to present an in-depth overview of USC CS577, and to start the processes of: • eliciting from faculty at a variety of colleges and universities the different needs and resource constraints to which they would be subject were they to port CS577 to their home institutions • planning the types of adjustments that can be made to CS577 to meet various sets of constraints
A proof technique for parallel programs

Abstract In this paper we present a set of axioms and rules of inference for a parallel programming language with shared variables and synchronization statements. The important difference between our approach and that of Owicki and Gries (1976) is that our semantics does not contain anything similar to their ‘interference freedom’ check, resulting in a much greater isolation of the proofs of the individual processes than is possible in their system. We illustrate our proof technique with some simple examples.
VOLUNTARY CONTRIBUTIONS TO A PUBLIC GOOD: NON-NEUTRALITY RESULTS

We show that the well-known neutrality theorem (that a small redistribution of wealth does not affect the aggregate private provision of a public good) no longer holds if agents take into account the effect of their individual supply of the public good on the relative price of private goods. Copyright 2007 Blackwell Publishing Ltd
Throughput-delay trade-off in wireless networks

Gupta and Kumar (2000) introduced a random network model for studying the way throughput scales in a wireless network when the nodes are fixed, and showed that the throughput per source-destination pair is /spl otimes/(1//spl radic/nlogn). Grossglauser and Tse (2001) showed that when nodes are mobile it is possible to have a constant or /spl otimes/(1) throughput scaling per source-destination pair. The focus of this paper is on characterizing the delay and determining the throughput-delay trade-off in such fixed and mobile ad hoc networks. For the Gupta-Kumar fixed network model, we show that the optimal throughput-delay trade-off is given by D(n) = /spl otimes/(nT(n)), where T(n) and D(n) are the throughput and delay respectively. For the Grossglauser-Tse mobile network model, we show that the delay scales as /spl otimes/(n/sup 1/2//v(n)), where v(n) is the velocity of the mobile nodes. We then describe a scheme that achieves the optimal order of delay for any given throughput. The scheme varies (i) the number of hops, (ii) the transmission range and (iii) the degree of node mobility to achieve the optimal throughput-delay trade-off. The scheme produces a range of models that capture the Gupta-Kumar model at one extreme and the Grossglauser-Tse model at the other. In the course of our work, we recover previous results of Gupta and Kumar, and Grossglauser and Tse using simpler techniques, which might be of a separate interest.
Inhomogeneous Lattice Paths, Generalized Kostka Polynomials and A n −1 Supernomials

Inhomogeneous lattice paths are introduced as ordered sequences of rectangular Young tableaux thereby generalizing recent work on the Kostka polynomials by Nakayashiki and Yamada and by Lascoux, Leclerc and Thibon. Motivated by these works and by Kashiwara’s theory of crystal bases we define a statistic on paths yielding two novel classes of polynomials. One of these provides a generalization of the Kostka polynomials while the other, which we name the An−1 supernomial, is a q-deformation of the expansion coefficients of products of Schur polynomials. Many well-known results for Kostka polynomials are extended leading to representations of our polynomials in terms of a charge statistic on Littlewood–Richardson tableaux and in terms of fermionic configuration sums. Several identities for the generalized Kostka polynomials and the An−1 supernomials are proven or conjectured. Finally, a connection between the supernomials and Bailey’s lemma is made.
Exploring the validity of the continuum of resistance model for discriminating early from late and non-uptake of colorectal cancer screening: implications for the design of invitation and reminder letters.

BACKGROUND
The continuum of resistance model contends that respondents lie at one end of a continuum and non-respondents at the other with respect to factors demonstrated to impact on screening participation.


PURPOSE
The aim of this study was to explore the validity of this model for the prediction of participation in colorectal cancer screening.


METHOD
People aged 50 to 74 years were asked to complete a survey (n = 1,250). Eligible respondents (n = 376, 30 %) were invited to complete a faecal occult blood test (FOBT). The cutoff period for the determination of participation rates was 12 weeks, with a reminder sent at 6 weeks.


RESULTS
FOBTs were returned by n = 196 people (132 within 6 weeks, 64 following a reminder). Participation was generally influenced by the same variables in both the first 6 weeks and the second 6 weeks, consistent with the continuum of resistance model. These variables were having known someone with bowel cancer and the social cognitive factor, perceptions of barriers to screening. There is a suggestion, however, that other factors may be differentially associated with early, late and non-participants.


CONCLUSION
Participation in screening appears somewhat consistent with the continuum of resistance model in that early and late participants respond to some of the same factors. This suggests that the same messages are relevant to early, late and non-screeners, but further consideration of what other factors may be influencing discrete stages of readiness to participate is necessary.
Improved isoflavonoid production in Pueraria candollei hairy root cultures using elicitation

The effect of abiotic and biotic elicitors (methyl jasmonate, chitosan, salicylic acid, Agrobacterium, and yeast extract) at various concentrations on total isoflavonoid accumulation was studied in the hairy root cultures of Pueraria candollei. All elicitors stimulated isoflavonoid production. Yeast extract (0.5 mg/ml) was the most efficient giving total isoflavonoids at 60 ± 1 mg/g dry wt, which was 4.5-fold higher than control hairy roots on day 3 of elicitation.
SE-AKA: A secure and efficient group authentication and key agreement protocol for LTE networks

To support Evolved Packet System (EPS) in the Long Term Evolution (LTE) networks, the 3rd Generation Partnership Project (3GPP) has proposed an authentication and key agreement (AKA) protocol, named EPS-AKA, which has become an emerging standard for fourth-generation (4G) wireless communications. However, due to the requirement of backward compatibility, EPS-AKA inevitably inherits some defects of its predecessor UMTS-AKA protocol that cannot resist several frequent attacks, i.e., redirection attack, man-in-the-middle attack, and DoS attack. Meanwhile, there are additional security issues associated with the EPS-AKA protocol, i.e., the lack of privacy-preservation and key forward/backward secrecy (KFS/KBS). In addition, there are new challenges with the emergence of groupbased communication scenarios in authentication. In this paper, we propose a secure and efficient AKA protocol, called SE-AKA, which can fit in with all of the group authentication scenarios in the LTE networks. Specifically, SE-AKA uses Elliptic Curve Diffie-Hellman (ECDH) to realize KFS/KBS, and it also adopts an asymmetric key cryptosystem to protect users’ privacy. For group authentication, it simplifies the whole authentication procedure by computing a group temporary key (GTK). Compared with other authentication protocols, SE-AKA cannot only provide strong security including privacy-preservation and KFS/KBS, but also provide a group authentication mechanism which can effectively authenticate group devices. Extensive security analysis and formal verification by using proverif have shown that the proposed SE-AKA is secure against various malicious attacks. In addition, elaborate performance evaluations in terms of communication, computational and storage overhead also demonstrates that SE-AKA is more efficient than those existing protocols. 2013 Elsevier B.V. All rights reserved.
Pain in the Achilles Region WITH HÅKAN ALFREDSON

A Achilles—the legendary warrior and hero of Homer’s Th e Iliad—died as a result of an arrow that pierced the midportion of his tendon, today’s patient with a painful presentation in this region usually has a good long-term prognosis.1 Nevertheless, runners have a 15 times greater risk of Achilles tendon rupture, and 30 times greater risk of tendinopathy than do sedentary controls.2 Th is chapter highlights clinically useful evidence-based treatments for pain in the Achilles region.3, 4
Simulation of Patients Flow in Multiple Healthcare Units using Process and Data Mining Techniques for Model Identification

INTRODUCTION
An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for combination of different techniques. The implementation of the proposed approach for simulation of the acute coronary syndrome (ACS) was developed and used in an experimental study.


METHODS
A combination of data, text, process mining techniques, and machine learning approaches for the analysis of electronic health records (EHRs) with discrete-event simulation (DES) and queueing theory for the simulation of patient flow was proposed. The performed analysis of EHRs for ACS patients enabled identification of several classes of clinical pathways (CPs) which were used to implement a more realistic simulation of the patient flow. The developed solution was implemented using Python libraries (SimPy, SciPy, and others).


RESULTS
The proposed approach enables more a realistic and detailed simulation of the patient flow within a group of related departments. An experimental study shows an improved simulation of patient length of stay for ACS patient flow obtained from EHRs in Almazov National Medical Research Centre in Saint Petersburg, Russia.


CONCLUSION
The proposed approach, methods, and solutions provide a conceptual, methodological, and programming framework for the implementation of a simulation of complex and diverse scenarios within a flow of patients for different purposes: decision making, training, management optimization, and others.
Optimal High Frequency Trading with limit and market orders

We propose a framework for studying optimal market making policies in a limit order book (LOB). The bid-ask spread of the LOB is modelled by a Markov chain with finite values, multiple of the tick size, and subordinated by the Poisson process of the tick-time clock. We consider a small agent who continuously submits limit buy/sell orders at best bid/ask quotes, and may also set limit orders at best bid (resp. ask) plus (resp. minus) a tick for getting the execution order priority, which is a crucial issue in high frequency trading. By trading with limit orders, the agent faces an execution risk since her orders are executed only when they meet counterpart market orders, which are modelled by Cox processes with intensities depending on the spread and on her limit prices. By holding non-zero positions on the risky asset, the agent is also subject to the inventory risk related to price volatility. Then the agent can also choose to trade with market orders, and therefore get immediate execution, but at a least favorable price because she has to cross the bid-ask spread. The objective of the market maker is to maximize her expected utility from revenue over a short term horizon by a tradeoff between limit and market orders, while controlling her inventory position. This is formulated as a mixed regime switching regular/impulse control problem that we characterize in terms of quasi-variational system by dynamic programming methods. In the case of a mean-variance criterion with martingale reference price or when the asset price follows a Levy process and with exponential utility criterion, the dynamic programming system can be reduced to a system of simple equations involving only the inventory and spread variables. Calibration procedures are derived for estimating the transition matrix and intensity parameters for the spread and for Cox processes modelling the execution of limit orders. Several computational tests are performed both on simulated and real data, and illustrate the impact and profit when considering execution priority in limit orders and market orders.
Automatic Patch Generation for Buffer Overflow Attacks

Control-hijacking attacks exploit vulnerabilities in network services to take control of them and eventually their underlying machines. Although much work has been done on detection and prevention of control-hijacking attacks, most of them did not address the problem of repairing the attacked network services so as to prevent the same attacks from recurring. Ideally, post-attack repair should consist of an attack signature generation component that creates a filtering rule for front-end firewall or intrusion prevention system to block the detected attack and its variants, and a patch generation component that creates a fix to permanently eliminate the vulnerabilities that the detected attack exploits. This paper describes the design, implementation and evaluation of a program transformation and execution trace analysis system called PASAN that can automatically instrument the source code of network service programs in such a way that it can detect control-hijacking attacks and automatically generate patches to seal the vulnerability being exploited by the detected attack. We have implemented the first PASAN prototype as a GNU C compiler extension that aims at stack- based buffer overflow attacks but could be easily generalized to accommodate other control-hijacking attacks. Testing this prototype with seven network daemon programs with known vulnerabilities show that the automatically generated patches can successfully fix the vulnerability. In addition, these patches are similar in their structure to those that are manually created. The run-time performance overhead of application programs instrumented by PASAN is between 10% and 23%, except two programs, whose CPU consumption is low.
Resource and non‐resource root competition effects of grasses on early‐ versus late‐successional trees

1 Centre d’étude de la forêt (CEF), Département des Sciences Biologiques, Université du Québec à Montréal, C.P. 8888, Succ. Centre-Ville, Montréal, Québec H3C 3P8, Canada; 2 Centre Tecnològic Forestal de Catalunya, Carretera St Llorenç de Morunys, km 2, 25280 Solsona, Spain; 3 Department of Soil Science, University of Saskatchewan, 51 Campus Drive, Saskatoon, Saskatchewan S7N 5A8, Canada; and 4 Centre d’étude de la forêt (CEF), Institut de recherche en biologie végétale, Département de Sciences Biologiques, Université de Montréal. 4101 East, Sherbrooke St., Montréal, Québec H1X 2B2, Canada