LLukas22/scidocs huggingface dataset:
Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial—Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial

BACKGROUND
The lowering of cholesterol concentrations in individuals at high risk of cardiovascular disease improves outcome. No study, however, has assessed benefits of cholesterol lowering in the primary prevention of coronary heart disease (CHD) in hypertensive patients who are not conventionally deemed dyslipidaemic.


METHODS
Of 19342 hypertensive patients (aged 40-79 years with at least three other cardiovascular risk factors) randomised to one of two antihypertensive regimens in the Anglo-Scandinavian Cardiac Outcomes Trial, 10305 with non-fasting total cholesterol concentrations 6.5 mmol/L or less were randomly assigned additional atorvastatin 10 mg or placebo. These patients formed the lipid-lowering arm of the study. We planned follow-up for an average of 5 years, the primary endpoint being non-fatal myocardial infarction and fatal CHD. Data were analysed by intention to treat.


FINDINGS
Treatment was stopped after a median follow-up of 3.3 years. By that time, 100 primary events had occurred in the atorvastatin group compared with 154 events in the placebo group (hazard ratio 0.64 [95% CI 0.50-0.83], p=0.0005). This benefit emerged in the first year of follow-up. There was no significant heterogeneity among prespecified subgroups. Fatal and non-fatal stroke (89 atorvastatin vs 121 placebo, 0.73 [0.56-0.96], p=0.024), total cardiovascular events (389 vs 486, 0.79 [0.69-0.90], p=0.0005), and total coronary events (178 vs 247, 0.71 [0.59-0.86], p=0.0005) were also significantly lowered. There were 185 deaths in the atorvastatin group and 212 in the placebo group (0.87 [0.71-1.06], p=0.16). Atorvastatin lowered total serum cholesterol by about 1.3 mmol/L compared with placebo at 12 months, and by 1.1 mmol/L after 3 years of follow-up.


INTERPRETATION
The reductions in major cardiovascular events with atorvastatin are large, given the short follow-up time. These findings may have implications for future lipid-lowering guidelines.
Takagi-Sugeno Fuzzy Control of Induction Motor

This paper deals with the synthesis of fuzzy state feedback controller of induction motor with optimal performance. First, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy controller is designed to stabilise the induction motor and guaranteed a minimum disturbance attenuation level for the closed-loop system. The gains of fuzzy control are obtained by solving a set of Linear Matrix Inequality (LMI). Finally, simulation results are given to demonstrate the controller’s effectiveness. Keywords—Rejection disturbance, fuzzy modelling, open-loop control, Fuzzy feedback controller, fuzzy observer, Linear Matrix Inequality (LMI)
A Randomised Controlled Trial to Reduce Sedentary Time in Young Adults at Risk of Type 2 Diabetes Mellitus: Project STAND (Sedentary Time ANd Diabetes)

AIMS
Type 2 diabetes mellitus (T2DM), a serious and prevalent chronic disease, is traditionally associated with older age. However, due to the rising rates of obesity and sedentary lifestyles, it is increasingly being diagnosed in the younger population. Sedentary (sitting) behaviour has been shown to be associated with greater risk of cardio-metabolic health outcomes, including T2DM. Little is known about effective interventions to reduce sedentary behaviour in younger adults at risk of T2DM. We aimed to investigate, through a randomised controlled trial (RCT) design, whether a group-based structured education workshop focused on sitting reduction, with self-monitoring, reduced sitting time.


METHODS
Adults aged 18-40 years who were either overweight (with an additional risk factor for T2DM) or obese were recruited for the Sedentary Time ANd Diabetes (STAND) RCT. The intervention programme comprised of a 3-hour group-based structured education workshop, use of a self-monitoring tool, and follow-up motivational phone call. Data were collected at three time points: baseline, 3 and 12 months after baseline. The primary outcome measure was accelerometer-assessed sedentary behaviour after 12 months. Secondary outcomes included other objective (activPAL) and self-reported measures of sedentary behaviour and physical activity, and biochemical, anthropometric, and psycho-social variables.


RESULTS
187 individuals (69% female; mean age 33 years; mean BMI 35 kg/m2) were randomised to intervention and control groups. 12 month data, when analysed using intention-to-treat analysis (ITT) and per-protocol analyses, showed no significant difference in the primary outcome variable, nor in the majority of the secondary outcome measures.


CONCLUSIONS
A structured education intervention designed to reduce sitting in young adults at risk of T2DM was not successful in changing behaviour at 12 months. Lack of change may be due to the brief nature of such an intervention and lack of focus on environmental change. Moreover, some participants reported a focus on physical activity rather than reductions in sitting per se. The habitual nature of sedentary behaviour means that behaviour change is challenging.


TRIAL REGISTRATION
Controlled-Trials.com ISRCTN08434554.
EEG-based estimation of mental fatigue by using KPCA-HMM and complexity parameters

Two complexity parameters of EEG, i.e. approximate entropy (ApEn) and Kolmogorov complexity (Kc) are utilized to characterize the complexity and irregularity of EEG data under the different mental fatigue states. Then the kernel principal component analysis (KPCA) and Hidden Markov Model (HMM) are combined to differentiate two mental fatigue states. The KPCA algorithm is employed to extract nonlinear features from the complexity parameters of EEG and improve the generalization performance of HMM. The investigation suggests that ApEn and Kc can effectively describe the dynamic complexity of EEG, which is strongly correlated with mental fatigue. Both complexity parameters are significantly decreased (P < 0.005) as the mental fatigue level increases. These complexity parameters may be used as the indices of the mental fatigue level. Moreover, the joint KPCA–HMM method can effectively reduce the dimensionality of the feature vectors, accelerate the classification speed and achieve higher classification accuracy (84%) of mental fatigue. Hence KPCA–HMM could be a promising model for the estimation of mental fatigue. Crown Copyright 2010 Published by Elsevier Ltd. All rights reserved.
Output Analysis for Simulations

We discuss methods for statistically analyzing the output from stochastic discrete-event or Monte Carlo simulations. Terminating and steady-state simulations are considered.
Microbiological Assessment and Monitoring of Environmental Pollutants

Individuals and governments have shown a great concern about the quality of the environment. Many governmental and non-governmental organisations are committed to activities that will reduce the effects of pollution of air, soil and water. Pollution does not only affect man, but also has grave effects on domestic livestock, wildlife, climate, forests and crops. Pollution management therefore needs to be prioritised by all governments.
Smart traffic analytics in the semantic web with STAR-CITY: Scenarios, system and lessons learned in Dublin City

This paper gives a high-level presentation of STAR-CITY, a system supporting semantic traffic analytics and reasoning for city. STAR-CITY, which integrates (human and machine-based) sensor data using variety of formats, velocities and volumes, has been designed to provide insight on historical and real-time traffic conditions, all supporting efficient urban planning. Our system demonstrates how the severity of road traffic congestion can be smoothly analyzed, diagnosed, explored and predicted using semantic web technologies. Our prototype of semantics-aware traffic analytics and reasoning, illustrated and experimented in Dublin Ireland, but also tested in Bologna Italy, Miami USA and Rio Brazil works and scales efficiently with real, historical together with live and heterogeneous stream data. This paper highlights the lessons learned from deploying and using a system in Dublin City based on Semantic Web technologies. c © 2011 Published by Elsevier Ltd.
A Study Into The Effects Of eLearning On Higher Education

The Internet is a technological development that has the potential to change not only the way society retains and accesses knowledge but also to transform and restructure traditional models of higher education, particularly the delivery and interaction in and with course materials and associated resources. Utilising the Internet to deliver eLearning initiatives has created expectations both in the business market and in higher education institutions. Indeed, eLearning has enabled universities to expand on their current geographical reach, to capitalise on new prospective students and to establish themselves as global educational providers. This paper examines the issues surrounding the implementation of eLearning into higher education, including the structure and delivery of higher education, the implications to both students and lecturers and the global impact on society. This journal article is available in Journal of University Teaching & Learning Practice: http://ro.uow.edu.au/jutlp/vol2/iss1/3 Journa l o f Un ivers i t y Teach ing and Learn ing Prac t i ce A Study Into The Effects Of eLearning On Higher Education
Long-term outcomes of a multidisciplinary cognitive behavioural programme for coping with chronic neuropathic spinal cord injury pain.

OBJECTIVE
To explore the long-term outcomes of CONECSI (COping with NEuropathiC Spinal cord Injury pain), a multidisciplinary cognitive behavioural treatment programme in persons with spinal cord injury.


DESIGN
Long-term follow-up pre-post-intervention design.


SUBJECTS
A total of 29 subjects with a spinal cord injury and chronic neuropathic pain from 4 Dutch rehabilitation centres.


METHODS
Primary outcomes were pain intensity and pain-related disability (Chronic Pain Grade questionnaire). Secondary outcomes were mood (Hospital Anxiety and Depression Scale), participation in activities (Utrecht Activities List), and life satisfaction (Life Satisfaction Questionnaire). Random coefficient analysis was used for the analyses of measurements before (t1), immediate post-intervention (t2), and 6 (t3), 9 (t4), and 12 (t5) months follow-up.


RESULTS
The analyses showed significant improvements on pain intensity (t1-t2 and t1-t5) and pain-related disability (t1-t2, t1-t4, and t1-t5), anxiety and participation in activities (t1-t2, t1-t3, and t1-t5).


CONCLUSION
This exploratory study suggests that a multidisciplinary cognitive behavioural programme might have lasting improvements on pain intensity, pain-related disability, anxiety, and participation in activities in people with chronic neuropathic spinal cord injury pain and highlights the potential of such programmes.
The influence of insulin use on glycemic control: How well do adults follow prescriptions for insulin?

OBJECTIVE
The purposes of this study were to determine the relationship between insulin self-management and glycemic control and to identify patient characteristics associated with better control.


RESEARCH DESIGN AND METHODS
A Department of Veterans Affairs regional database was used to identify patients with diabetes on chronic insulin therapy (n = 6,222) with dose defined as number of units and doses. The rate of insulin use during a 2-year period was calculated using pharmacy data. Regression analyses were used 1) to predict compliance with prescribed insulin regimens using demographic variables, HbA1c levels, and a measure of diabetes management intensity and 2) to predict HbA1c levels using demographic variables and rates of insulin use.


RESULTS
Insulin use was 77.44 +/- 17% of prescribed amounts, including wastage; HbA1c levels were 7.98 +/- 1.66%. Concomitant oral hypoglycemic agent use (84.89 +/- 16%) was higher than insulin use (P < 0.0001) but correlated with insulin use (r = 0.189, P < 0.0001). Ordinary least-squares regression showed that race, HbA1c levels, and intensity of diabetes management were significant predictors of insulin use. Age, race, and insulin use were significant predictors of HbA1c levels.


CONCLUSIONS
Adults prescribed a specific insulin regimen averaged using 77% of prescribed doses, demonstrating good intention to follow the prescription. However, HbA1c higher than the recommended level suggested that the rate of insulin use, the prescribed regimen, or both were inadequate to achieve good glycemic control in patients with long-term insulin use.
Cooperative manipulation and transportation with aerial robots

In this paper we consider the problem of controlling multiple robots manipulating and transporting a payload in three dimensions via cables. We develop robot configurations that ensure static equilibrium of the payload at a desired pose while respecting constraints on the tension and provide analysis of payload stability for these configurations. We demonstrate our methods on a team of aerial robots via simulation and experimentation.
Blended Learning Improves Science Education

Blended learning is an emerging paradigm for science education but has not been rigorously assessed. We performed a randomized controlled trial of blended learning. We found that in-class problem solving improved exam performance, and video assignments increased attendance and satisfaction. This validates a new model for science communication and education.
Targeting children of substance-using parents with the community-based group intervention TRAMPOLINE: A randomised controlled trial - design, evaluation, recruitment issues

BACKGROUND
Children of substance-abusing parents are at risk for developing psychosocial development problems. In Germany it is estimated that approx. 2.65 million children are affected by parental substance abuse or dependence. Only ten percent of them receive treatment when parents are treated. To date, no evaluated programme for children from substance-affected families exists in Germany. The study described in this protocol is designed to test the effectiveness of the group programme TRAMPOLINE for children aged 8-12 years with at least one substance-abusing or -dependent caregiver. The intervention is specifically geared to issues and needs of children from substance-affected families.


METHODS/DESIGN
The effectiveness of the manualised nine-session group programme TRAMPOLINE is tested among N = 218 children from substance-affected families in a multicentre randomised controlled trial. Outpatient counselling facilities across the nation from different settings (rural/urban, Northern/Southern/Eastern/Western regions of the country) will deliver the interventions, as they hold the primary access to the target group in Germany. The control condition is a group programme with the same duration that is not addiction-specific. We expect that participants in the intervention condition will show a significant improvement in the use of adaptive coping strategies (in general and within the family) compared to the control condition as a direct result of the intervention. Data is collected shortly before and after as well as six months after the intervention.


DISCUSSION
In Germany, the study presented here is the first to develop and evaluate a programme for children of substance-abusing parents. Limitations and strengths are discussed with a special focus on recruitment challenges as they appear to be the most potent threat to feasibility in the difficult-to-access target group at hand (Trial registration: ISRCTN81470784).
The effects of background music on word processed writing

College students often listen to music while they use a computer. This experiment investigated whether background music disrupts their ability to word process  ̄uently and eectively. Forty-®ve psychology undergraduates wrote brief expository essays. Background music signi®cantly disrupted writing  ̄uency (words generated per minute controlling for typing speed and including those words deleted before the ®nal draft) even though no response to the music was required. Those with some musical training and high working memory span wrote better essays with longer sentences and were also more likely to pause at clause boundaries. Even unattended music places heavy demands on working memory and disrupts word processed writing. # 2001 Elsevier Science Ltd. All rights reserved.
Antimicrobial activity of natural products against Clostridium difficile in vitro.

AIMS
To investigate the antimicrobial activity of various natural products against Clostridium difficile in vitro.


METHODS AND RESULTS
The antibacterial activity of 20 natural products was determined by the agar well diffusion and broth microdilution assays against four C. difficile strains, three comparator organisms and four gastrointestinal commensal organisms. Of the raw natural products, garlic juice had the highest activity. The most active processed products were peppermint oil and the four pure compounds trans-cinnamaldehyde, allicin, menthol and zingerone. Furthermore, Bacteroides species had similar susceptibility to C. difficile to most natural products; however, Lactobacillus casei was less susceptible. The combined effect of natural products with vancomycin or metronidazole was determined using the conventional checkerboard titration method and the fractional inhibitory concentration index was calculated. The results showed a possible synergism between trans-cinnamaldehyde and vancomycin and partial synergy between trans-cinnamaldehyde and metronidazole.


CONCLUSIONS
The study indicates a range of antimicrobial activity of natural products against C. difficile and suggests that they may be useful as alternative or complementary treatments for C. difficile infection (CDI), particularly as most are able to be given orally.


SIGNIFICANCE AND IMPACT OF THE STUDY
This study encourages further investigation of natural products for treatment of CDI.
Cloud Computing : Empirical Studies in Higher Education

The advent of cloud computing (CC) in recent years has attracted substantial interest from various institutions, especially higher education institutions, which wish to consider the advantages of its features. Many universities have migrated from traditional forms of teaching to electronic learning services, and they rely upon information and communication technology services. The usage of CC in educational environments provides many benefits, such as low-cost services for academics and students. The expanded use of CC comes with significant adoption challenges. Understanding the position of higher education institutions with respect to CC adoption is an essential research area. This paper investigated the current state of CC adoption in the higher education sector in order to enrich the research in this area of interest. Existing limitations and knowledge gaps in current empirical studies are identified. Moreover, suggested areas for further researches will be highlighted for the benefit of other researchers who are interesting in this topic. These researches encourage institutions of education especially in higher education to adopted cloud computing technology. Keywords—Cloud computing; education system; e-learning; information and communication technology (ICT)
Development of a Self-Tuned Neuro-Fuzzy Controller for Induction Motor Drives

In this paper, a novel adaptive neuro-fuzzy (NF)-based speed control of an induction motor (IM) is presented. The proposed NF controller (NFC) incorporates fuzzy logic laws with a five-layer artificial neural network scheme. In this controller, only three membership functions are used for each input for low computational burden, which will be suitable for real-time implementation. Furthermore, for the proposed NFC, an improved self-tuning method is developed based on the knowledge of intelligent algorithms and high-performance requirements of motor drives. The main task of the tuning method is to adjust the parameters of the fuzzy logic controller (FLC) in order to minimize the square of the error between actual and reference outputs. A complete model for indirect field-oriented control of IM incorporating the proposed NFC is developed. The performance of the proposed NFC-based IM drive is investigated extensively both in simulation and in experiment at different operating conditions. In order to prove the superiority of the proposed NFC, the results for the proposed controller are also compared to those obtained by conventional proportional-integral (PI) and FLC controllers. The proposed NFC-based IM drive is found to be more robust as compared to conventional PI and FLC controllers and, hence, suitable for high-performance industrial drive applications.
Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry

Reliable prediction of sales can improve the quality of business strategy. In this research, fuzzy logic and artificial neural network are integrated into the fuzzy back-propagation network (FBPN) for sales forecasting in Printed Circuit Board (PCB) industry. The fuzzy back propagation network is constructed to incorporate production-control expert judgments in enhancing the model’s performance. Parameters chosen as inputs to the FBPN are no longer considered as of equal importance, but some sales managers and production control experts are requested to express their opinions about the importance of each input parameter in predicting the sales with linguistic terms, which can be converted into pre-specified fuzzy numbers. The proposed system is evaluated through the real world data provided by a printed circuit board company and experimental results indicate that the Fuzzy back-propagation approach outperforms other three different forecasting models in MAPE measures. q 2005 Elsevier Ltd. All rights reserved.