Miracle-dz/UniFAR-FTUs huggingface dataset:
Variability of prasugrel antiplatelet effect in patients with acute coronary syndrome

Background. Many reports have demonstrated excessive variability in response to clopidogrel, the most commonly used P2Y12 receptor antagonist. Clopidogrel resistant patients are at increased risk of cardiovascular (CV) events. Prasugrel is a new P2Y12 inhibitor that provides greater and faster platelet inhibition and reduces CV events more effectively than clopidogrel. The aim of this study was to evaluate the variability and efficacy of prasugrel antiplatelet activity in patients presenting with acute coronary syndrome (ACS). Materials and methods. The study was designed as a prospective, single-center, non-randomized, observational trial. Platelet reactivity (PR) was assessed with the VeryfyNow assay three times during hospitalization in forty-two patients undergoing percutaneous coronary intervention (PCI) for ACS and treated with standard doses of prasugrel. Results. Platelet aggregation with prasugrel displayed relatively high variability. The platelet aggregation was lowest on the 3rd day of the treatment at 4 p.m. and was significantly different from the measurements obtained on the 3rd and 4th day in the morning (6.0 v. 8.5 U; p = 0.0005 and 6.0 v. 36.5 U; p < 0.00001, respectively), with the latter two differing significantly from each other (p = 0.002). All participants were successfully treated with prasugrel achieving PR < 208 PRU in each measurement, whereas 42.9–80.9% (depending on sampling point) of patients presented very low platelet activity. The subgroups of stable and persistent low PR included a higher percentage of active smokers (73.3 v. 40.7%; p = 0.04 and 80.0 v. 43.8%; p = 0.04, respectively). Conclusions. Prasugrel treatment is associated with high variability of PR. Nonetheless, prasugrel is a highly effective antiplatelet drug. Active smoking may predispose to strong and stable on-prasugrel platelet inhibition.
Ultrasound Imaging for the Medial Branches of the Superior Cluneal Nerve: Optimal Visibility at the “Fatty Tunnel”

In recent years, the role-play of superior cluneal nerve (SCN) as regards pain and disability in specific subsets of low back pain patients is becoming better understood. Herewith, the diagnosis of SCN entrapment based solely on physical examination is quite challenging in clinical practice. As such, a finding of sono-Tinel at the level of the osteo-fibrous tunnel (i.e. between the bony groove of the posterior iliac crest and the thoracolumbar fascia) coupled with a positive nerve block is often required to confirm the involvement of SCN.
Challenges in Operationalising Predictive Analytics

The phenomenon of big data has brought home the importance of predictive analytics as a technology and statistical technique critical to taking the sting out of the big data mayhem. Although predictive analytics has been around for some time, the benefits of predictive analytics have only recently been appreciated due largely to the phenomenon of big data. This new-found appreciation of predictive analytics is coupled with a desire by many corporate organisations not only to inform strategic business decisions with evidence, but also to predict future trends with a high level of confidence. While many organisations are able to use predictive analytics technology with greater success, the outcome for some organisations has been less than successful. This paper argues that predictive analytics can only achieve so much when organisations and their analytics teams consider the main challenges in predictive analytics projects. The paper suggests a number of measures that analytics teams can take to address the challenges of predictive analytics. The paper concludes that although some machine learning algorithms based on artificial intelligence are increasingly being used to address aspects of the challenges of predictive analytics but with ever present danger of lurking variables or unknown factors, there is no sustainable alternative to good data quality assurance.
The State of the Art

The rapidly developing relationship between tourism and creativity, arguably heralds a ‘creative turn’ in tourism studies. Creativity has been employed to transform traditional cultural tourism, shifting from tangible heritage towards more intangible culture and greater involvement with the everyday life of the destination. The emergence of ‘creative tourism’ reflects the growing integration between tourism and different placemaking strategies, including promotion of the creative industries, creative cities and the ‘creative class’. Creative tourism is also arguably an escape route from the serial reproduction of mass cultural tourism, offering more flexible and authentic experiences which can be co-created between host and tourist. However the gathering critique also highlights the potential dangers of creative hype and commodification of everyday life.
Summer pruning in table grape

This paper reviews cultural practices to improve fruit quality in table grape during vegetative and reproductive seasons. Summer pruning in table grape (Vitis vinifera L.) has more effects than winter pruning, above all with regard to plant productivity and final number of bunches for harvesting. Thinning is one of the most cultural technique and it consists in the elimination of vegetative or reproductive organs in excess. Other summer canopy management techniques include leaf removal, fruit shoots positioning, shoot trimming and girdling.
A Dual-band Electromagnetic Energy Harvesting Surface

We present a dual-band electromagnetic energy harvesting surface that is designed for absorbing electromagnetic energy in the GSM-1800 and Wi-Fi bands. The unit cell of the periodic structure incorporates two bow-tie dipoles and a resistive load demonstrating excellent absorption characteristics with minimal dielectric losses. We also demonstrate how the proposed surface can increase the rectenna phsyical area and the collected power per rectifier, leading to viable energy harvesting applications in low power density environments.
Learning programs and teaching techniques to enhance oral health literacy or patient-centred communication for healthcare providers: A systematic review.

OBJECTIVE To investigate the learning programs and teaching techniques used in interventions to enhance oral health literacy (OHL) or patient-centred communication (PCC) for healthcare providers. MATERIALS AND METHODS A systematic review of OHL and PCC were obtained from four electronic databases (PubMed, ScienceDirect, ProQuest, and Scopus) was undertaken. These searches covered the period from January 2008 to December 2017. The quality assessment tool was the Joanna Briggs Institute Critical Appraisal tool for systematic reviews of effectiveness. RESULTS The final review included nine studies among a total of 1,475 studies. They showed 3 learning programs (workshops, training, and community-based rotation) and 17 related teaching techniques to promote OHL and PCC. The most commonly-used learning programs to enhance OHL and PCC for healthcare providers were workshops and the teaching techniques included feedback and reflection. The intervention periods of the programs took 20 minutes to half a day. The three studies did not have a follow-up, while the rest showed a follow-up range of 2 months to 3 years. Interestingly, there was one study, which applied double follow-ups to show the effectiveness of the program. CONCLUSION Either workshops or training programs with a combination of teaching techniques were effective in terms of enhancing their OHL or PCC. The more frequent follow-up might increase the long-term effectiveness of the learning program.
Leveraging SMOTE in a Two-Layer Model for Prediction of Protein-Protein Interactions

The research of the mechanisms of infectious diseases between host and pathogens remains a hot topic. It takes stock of the interactions data between host and pathogens, including proteins and genomes, to facilitate the discoveries and prediction of underlying mechanisms. However, the incomplete protein-protein interactions data impediment the advances in this exploration and solicit the wet-lab experiments to examine and verify the latent interactions. Although there have been numerous studies trying to leverage the computational models, especially machine learning models, the performances of these models were not good enough to produce high-fidelity candidates of interactions data due to the nature of the protein-protein interactions data. In this paper, we propose a two-layer model for prediction of host-pathogen protein-protein interactions tackling the challenges affiliated to the feature representation algorithms and the imbalanced data. The two-layer model consists of two essential modules, which are XGBoost to reduce the imbalanced ratio of the data and SVM to improve the performance. SMOTE technology is incorporated as a key component in our model to alleviate the bias of imbalanced ratio. In this study, we have carefully collected proteins interactions data from public databases and built a dataset following the protocol with consensus of literature. A variety of models, including traditional models, models in major literature and our model, are verified on the datasets. Results demonstrate that our model significantly improve the performance comparing with the other state-of-the-art models.
Design of Multiphase Interleaved Equalization Circuit Based on Graph Theory

Lithium-ion batteries play an important role in large-scale energy storage systems. However, the power inconsistency of the battery packs restricts the developments of modern technologies in energy storage area. The motivation of the present study is to serve the growing needs of the energy balance for lithium-ion battery packs. The present study proposes a flexible multiphase interleaved converter for the energy equalization of a lithium battery pack with series configuration. Moreover, the graph theory is applied to the analysis of equalization circuits. It is intended to establish a unified standard for the comparison. The parameter of average efficiency is considered as an important indicator to evaluate the characteristics of the equilibrium system. The proposed method is verified by constructing a lithium-ion battery pack with the equalization circuit. It is observed that the proposed multiphase interleaved converter has flexible characteristics, while it has low energy loss compared with the conventional methods. It is found that the proposed method simplifies the complex equalization circuits into graphs and facilitates the comparison of the average efficiency of the system. It is concluded that this method is a feasible and powerful method for evaluating the battery equalization circuit. This approach can be applied for solving complex problems in other engineering applications.
Enhancing SMEs' Growth by Investing in Organizational Capital

Objective : The objective of this paper is to verify the relationship between the share of investments in organizational capital (OC) within the total amount of investments and key performance indicators of SMEs. Research, Design & Methods : Quantitative research based on the authorâ€™s theoretical model and was conducted on a group of 180 Polish SMEs with the use of a structured questionnaire. To verify the hypothesis measures of dispersion as well as correlation were used. Findings: The share of investments in OC vary at particular growth stages and the highest is in decline stage. Investigated firms invest mostly in 'brand' and 'IT systems'. Investing in OC seems to be important mostly for SMEs that are in the prime stage. In this stage the share of investments in OC is correlated with almost all performance indicators. It suggests that OC can be treated as a source of competitive advantage and firmsâ€™ performance. Implications & Recommendations: The appropriate share of investments in particular resources positively impact the effectiveness of decisions aimed at enhancing SMEs growth. Guidelines in what to invest help managers to plan their activities, especially while operating in a rapidly changing environment. Contribution & Value Added: The study contributes to the stream of research devoted to SME growth factors. Despite the fact that there already are publications on the impact of particular resources on organisationsâ€™ success or failure, complex studies, including those concerning Polish SMEs, are much needed.
Microbiological screening of street-vended groundnut cake, Kulikuli and natural spices for reducing microbial contamination in the food snack

Groundnut ( Arachis hypogea ) and its popular derivative snack-product, kulikuli are particularly prone to contamination by a wide variety of toxigenic microorganisms due to its high nutritive content. Peanuts are rich in calories and contain many nutrients, minerals, antioxidants, and vitamins that are essential for optimum health. Samples were collected from five selected sites within the Mowe market, Ogun State, South-West Nigeria from two experimental blocks and compared for microbial quality with laboratory-prepared samples treated with plant-derived natural spices. Aliquots of diluents of the treatments were inoculated in duplicates onto Eosin Methylene Blue (EMB) agar and Potato dextrose agar (PDA) to screen for coliform bacteria and fungi respectively to obtain the total colony count (TCC). The bacterial species isolated from the market samples include Serratia fonticola , Proteus vulgaris , while Morganella morganii and Proteus vulgaris were isolated from laboratory samples. Conversely, Rhizopus nigricans , Penicilium nigricans , Mucor hiemalis , Alternaria alternata and Aspergillus niger are the fungal organisms isolated from the market and laboratory samples. The result of the total bacterial count (TBC, cfu/ml) show that the market samples displayed the highest TBC when compared with laboratory-prepared samples treated with natural spices, even better than the preservative chemical (sodium benzoate) treated samples. The cinnamon treated samples showed the lowest TBC values. The results confirmed that treating kulikuli with spices may reduce the effect of toxigenic organisms associated with this food product. © 2016 International Formulae Group. All rights reserved. Keywords: Enterotoxigenic, Aflatoxin, kulikuli , Natural spices, Enterobacteriacae
Competence-Based Evolution of Contractual R&D Relationships

This research addresses the mutual evolution of competencies and interorganisational relationships, by using a longitudinal case study approach. The empirical phenomena that we investigate involve the professional research and development services offered by VTT Electronics, the contract research organisation. Within this context, we are interested in the relationships of one of the focal research groups of the organisation. Examples will be provided by the research and development of fault diagnosis systems, computers embedded in various kinds of electronic products designed for real-time condition monitoring. The evolution of the research and development relationships in the field of fault diagnosis between VTT Electronics and its research partners and customers will be analysed from the late eighties to the present date. The analysis, mainly based on written case data, addresses both the basic characteristics of fault diagnosis competence and the effect of their changes on the relationships of the focal organisation. Finally, some empirical, theoretical and managerial implications of our analysis will be presented.
Effect of different processing methods of pigeon pea (Cajanus cajan) on growth performance, carcass traits, and blood biochemical and hematological parametersof broiler chickens

Muhammad ARIF, Abdur REHMAN, Muhammad SAEED, Mohamed Ezzat Abd EL-HACK, Mahmoud ALAGAWANY, Haider ABBAS, Muhammad Asif ARIAN, Sarfaraz Ali FAZLANI, Abbasi Imtiaz HUSSAIN, Tugay AYASAN* Department of Animal Sciences, University College of Agriculture, University of Sargodha, Sargodha, Pakistan College of Animal Sciences, Northwest A&F University, Yangling, P.R. China Department of Poultry, Faculty of Agriculture, Zagazig University, Zagazig, Egypt College of Animal Sciences and Technology, Agriculture University, Beijing, PR China East Mediterranean Agricultural Research Institute, Adana, Turkey
Innovative System Indicators for Islamic Tourism Using C-PEST Factors

Islamic tourism is seen from a different perspective as compared to the conventional tourism, such as economic, cultural and religious. The qualitative research design has been incorporated to assess the innovative system indicators through systematic analysis. Basically, it is an exploratory study of the Competitive-Political, Economic, Social and Technological (C-PEST) factors that were conducted through three phases to understand current and potential Islamic tourism market in the tourism industry. The preliminary stage involves a comprehensive literature review taken as a foundation of Islamic tourism concept, theories and principles from the Holy Quran, Hadith, and tourism reports. Phase two (2) and three (3) involves the field survey with tourists and interviews with key informants from tourism suppliers.
Reproducibility of Embroidered Electromagnetically Coupled Wearable Patch Antennas

The reproducibility of electromagnetically coupled wearable patch antennas was experimentally investigated in terms of the measurements for electromagnetically fed embroidered patch antennas. The stability of resonant frequency, bandwidth, gain, and radiation pattern were all assessed in the 2-GHz band in a sample of embroidered patch antennas fabricated on felt with conductive yarn. Results revealed that the electromagnetically coupled patch antennas demonstrated outstanding reproducibility even when embroidered on a mechanically flexible felt substrate.
Interactive comment on “Vertical profiles of sub-micron aerosol single scattering albedo over Indian region immediately before monsoon onset and during its development: Research from the SWAAMI field campaign” by Mohanan R. Manoj et al

At the outset, we thank the reviewer for the observation that “overall, the present work appears to be a scientifically sound exploration of this topic” and also recognizing that “Aerosol-monsoon interactions over South Asia is a very active research topic for which many open questions remain. ” We fully agree with this. However, while thankfully acknowledging the reviewer’s overall appreciation of our paper; we disagree to some of
Analysis of Phase Discretization Influence on the Monochromatic Aberrations of Focusing Metasurface Based on Generalized Rayleigh-Sommerfeld Diffraction Theory

In this paper, we discuss the effect of phase discretization on the monochromatic aberrations of a planar focusing metasurface. A series of focusing metasurfaces with constant aperture and different numerical aperture (NA) are synthesized by availably discrete phase distributions instead of the ideally continuous phase maps. Under normal and oblique illumination of a Gaussian plane-wave, their diffraction field patterns are computed by the generalized Rayleigh-Sommerfeld diffraction integral. The focusing parameters describing the beam shape and the Strehl ratio quantifying the aberrations are then extracted from numerical results and comparatively analyzed. It is demonstrated that the flat metasurface with increasing phase levels can obtain better focus yet miserably more Strehl ratio decrement for increasing incident angles and NA implying worse Comatic aberrations.
Fault Detection System Using Machine Learning on Geothermal Power Plant

Geothermal power plants are a renewable clean energy source with great potential that Indonesia has. The manual fault detection system at the critical machine is one of the problems in the operation of geothermal power plants in Indonesia. Vulnerable errors in determining engine conditions and delays in knowing alerts are two major problems that arise. The application of machine learning algorithms in making fault detection models has been used in various industries and objects. This research is the application of machine learning algorithms to create fault detection classification models on critical engines of geothermal power plants. The algorithm used is the basic classifier and ensemble classifier to compare which algorithms produce the best classification indicators of classifications. This research can provide insight into the geothermal power plant industry in Indonesia to overcome existing fault detection system by utilizing sensor data using machine learning algorithm.
Alpha Suppression and Symmetry Training for Generalized Anxiety Symptoms

ABSTRACT Introduction. Twenty-eight anxious adults were assessed for frontal lobe alpha asymmetry, a brain state associated with depression and anxiety. Fifteen of the 28 exhibited significant asymmetry and 12 agreed to participate in a biofeedback program addressed at reducing frontal alpha asymmetry. Method. The program consisted of earlobe temperature biofeedback (ETB) and two forms of neurofeedback, alpha suppression and alpha symmetry training. Individuals were instructed to warm their right earlobe for six sessions, and half succeeded, though success was not required to advance to the next stage of training. For subsequent EEG training, two anterior sites were selected on the basis of poor alpha coherence. Individuals were trained to reduce alpha magnitude at these sites by 10% for 30 min or more, which took from 6 to 16 sessions to achieve. Once successful with alpha suppression, individuals were trained to improve alpha symmetry between the sites by 15% for 30 min or more. Results. This feat took .
A New Trajectory-Planning Beetle Swarm Optimization Algorithm for Trajectory Planning of Robot Manipulators

Based on a heuristic optimization algorithm, this paper proposes a new algorithm named trajectory-planning beetle swarm optimization (TPBSO) algorithm for solving trajectory planning of robots, especially robot manipulators. Firstly, two specific manipulator trajectory planning problems are presented as the practical application of the algorithm, which are point-to-point planning and fixed-geometric-path planning. Then, in order to verify the effectiveness of the algorithm, this paper develops a control model and conducts numerical experiments on two planning tasks. Moreover, it compares with existing algorithms to show the superiority of our proposed algorithm. Finally, the results of numerical comparisons show that algorithm has a relatively faster computational speed and better control performance without increasing computational complexity.
Application of the Arrhenius Equation in Geotechnical Engineering

The reliable measurement of geotechnical properties in cold regions should account for their fluctuations with temperature. The objective of this paper is to introduce a chemical model based on the Arrhenius equation that can predict the properties of materials as their temperature changes. The model can monitor phases and reaction rates as they change with temperature. It has been already applied in the fields of geology, construction, chemistry, materials engineering, and food science. The application of the Arrhenius equation requires a reliable estimate of the activation energy. Therefore, this study also demonstrates several methods for evaluating activation energy in different contexts through summaries and reviews of previous research related to the Arrhenius equation. This paper may be of wide use in obtaining temperature-dependent parameters in geotechnical engineering.