Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Medication History Accuracy Between Nurses and Pharmacy Personnel

Purpose: To evaluate the differences in medication history errors made by pharmacy technicians, students, and pharmacists compared to nurses at a community hospital. Methods: One hundred medication histories completed by either pharmacy or nursing staff were repeated and evaluated for errors by a fourth-year pharmacy student. The histories were analyzed for differences in the rate of errors per medication. Errors were categorized by their clinical significance, which was determined by a panel of pharmacists, pharmacy students, and nurses. Errors were further categorized by their origin as either prescription (Rx) or over the counter (OTC). The primary outcome was the difference in the rate of clinically significant errors per medication. Secondary outcomes included the differences in the rate of clinically insignificant errors, Rx errors, and OTC errors. Differences in the types of errors for Rx and OTC medications were also analyzed. Additionally, the number of patients with no errors was compared between both groups. Results: The pharmacy group had a lower clinically significant error rate per medication (0.03 vs 0.09; relative risk [RR] = 0.66; 95% confidence interval [CI]: 0.020-0.093; P = .003). For secondary outcomes, the pharmacy group had a lower total error rate (0.21 vs 0.36, RR = 0.58; 95% CI: 0.041-0.255; P = .007), Rx error rate (0.09 vs 0.27, RR = 0.44; 95% CI: 0.071-0.292; P = .002), and OTC error rate (0.24 vs 0.46; RR = 0.52; 95% CI: 0.057-0.382; P = .009) per medication. The pharmacy group completed 20% more medication histories without Rx errors (P = .045) and 25% more histories without OTC errors (P = .041). Conclusion: This study demonstrated that expanded use of pharmacy technicians and students improves the accuracy of medication histories in a community hospital.
Whose experience matters in the boardroom? the effects of experiential and vicarious learning on emerging market entry

Using an organizational learning perspective, we develop arguments about vicarious learning through board interlocks and its relation to experiential learning. Although it is well established that firms learn from board interlocks, little attention has focused on which types of interlocks are most consequential and why. We distinguish between the relative advantages of various tie attributes such as experience, authority, and credibility and argue that these distinctions lead to measureable differences in learning outcomes. We further demonstrate that whether vicarious learning substitutes or complements focal firm experiential learning depends upon the type of interlock involved. After accounting for the endogeneity of ties, we find support for our framework in a longitudinal analysis of foreign investments by German firms in emerging economies between 1990 and 2003.
E-commerce websites and online customer reviews in France: analysis of current strategies and suggestions for improvement

E-commerce distribution channel experiences a dramatic development nowadays. France witnessed a rapid growth rate of online sales in recent years and now ranks as the second largest market in Europe in terms of turnover. On E-commerce websites, customer review system is considered as an efficient tool of E-Word of Mouth, enabling users to write recommendations which will influence potential purchasers. This paper discusses the crucial factors of customer review system. Also, a tool to evaluate review system is elaborated with five criteria such as accessibility, quality, design, interaction and control. Ten case studies of French E-commerce firms are presented according to those criteria in qualitative study. Opinions from French customers are collected through online questionnaires in quantitative study. Researches made from supply (firms) and demand (customers) sides show that accessibility and quality are the main concerns for users and often weaknesses in current review systems. Also, the credibility of reviews is questioned by customers. Focusing on these aspects, the paper aims to give suggestions for designing an ideal customer review system to firms in French e-commerce industry.
Research on Influencing Factors of Perceived Risk in Online Shopping by Consumers

Applying data gained from questionnaire, through T Test for Independent Samples, one-way ANOVA and Pearson correlation analysis, the paper analyzed the influences of eight chosen factors on perceived risk by consumers in online shopping. This empirical study finds that friend recommendation, Internet purchasing experience and involvement have significantly negative effect on financial risk and overall risk; product knowledge has significantly negative impact on financial, psychological, and overall risks; and consumer’s attitude to risk has significantly positive effect on the all four types of risks and overall risk. And no significant correlation was found between perceived risk and gender, the average monthly expenditure and Internet experience.
Towards the low-dose characterization of beam sensitive nanostructures via implementation of sparse image acquisition in scanning transmission electron microscopy

Scanning transmission electron microscopy (STEM) has been successfully utilized to investigate atomic structure and chemistry of materials with atomic resolution. However, STEM’s focused electron probe with a high current density causes the electron beam damages including radiolysis and knock-on damage when the focused probe is exposed onto the electron-beam sensitive materials. Therefore, it is highly desirable to decrease the electron dose used in STEM for the investigation of biological/organic molecules, soft materials and nanomaterials in general. With the recent emergence of novel sparse signal processing theories, such as compressive sensing and model-based iterative reconstruction, possibilities of operating STEM under a sparse acquisition scheme to reduce the electron dose have been opened up. In this paper, we report our recent approach to implement a sparse acquisition in STEM mode executed by a random sparse-scan and a signal processing algorithm called model-based iterative reconstruction (MBIR). In this method, a small portion, such as 5% of randomly chosen unit sampling areas (i.e. electron probe positions), which corresponds to pixels of a STEM image, within the region of interest (ROI) of the specimen are scanned with an electron probe to obtain a sparse image. Sparse images are then reconstructed using the MBIR inpainting algorithm to produce an image of the specimen at the original resolution that is consistent with an image obtained using conventional scanning methods. Experimental results for down to 5% sampling show consistency with the full STEM image acquired by the conventional scanning method. Although, practical limitations of the conventional STEM instruments, such as internal delays of the STEM control electronics and the continuous electron gun emission, currently hinder to achieve the full potential of the sparse acquisition STEM in realizing the low dose imaging condition required for the investigation of beamsensitive materials, the results obtained in our experiments demonstrate the sparse acquisition STEM imaging is potentially capable of reducing the electron dose by at least 20 times expanding the frontiers of our characterization capabilities for investigation of biological/ organic molecules, polymers, soft materials and nanostructures in general. Measurement Science and Technology Towards the low-dose characterization of beam sensitive nanostructures via implementation of sparse image acquisition in scanning transmission electron microscopy
Solid Phase Enzyme Immunoassays for the Quantification of Serum Amyloid P (SAP) and Complement Component 3 (C3) Proteins in Acute-Phase Mouse Sera

Simple, reliable and sensitive enzyme immunoassays have been developed for the quantification of the mouse acute-phase SAP and C3 proteins. The ELISA systems were validated using sera from mice injected with S. dysenteriae endotoxin, and detected 500 pg protein/ml. The assays use 96-well microtitre plates permitting rapid processing of a large number of samples.
Fourier transform ion cyclotron resonance mass spectrometric analysis of the green fraction of soil humic acids.

RATIONALE The green fraction of soil humic acids (HAs), designated Pg, contains 4,9-dihydroxyperylene-3,10-quinone (DHPQ) as a chromophore. Although various naturally occurring DHPQ derivatives are known to occur and Pg-like absorption is observed in the UV-visible spectra of HAs from various types of soils worldwide, the chemical structure of Pg is still unknown. METHODS For a better understanding of the chemical composition of Pg, the pre-isolated (crude Pg) and purified Pg (G2) samples and three soil HAs with different degrees of humification were analyzed using negative-mode electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) at 12 Tesla. The Pg samples were characterized using H/C-O/C ratios and based on the type and magnitude of the molecular formulae having DHPQ or related compounds as a potential structure. RESULTS The H/C-O/C diagram indicated that most of the lipids, proteins, other aliphatics, and lignin-like components were removed, while condensed aromatic components were concentrated during the purification process of crude Pg to G2 using Sephadex G-50. More than 27 molecular formulae resembling DHPQ, DHPQ substituted with varying numbers of carboxyl and/or hydroxyl groups, and phenyl-DHPQ derivatives were identified in both Pg samples. The peak magnitudes of these formulae in G2 (accounting for 40% of the total assigned magnitude) were greater than that in the crude Pg (21%). Most of the 27 molecular formulae were also detected in the three soil HAs, suggesting a common existence of Pg-related compounds in various soil HAs. CONCLUSIONS The important molecular formulae of Pg components were estimated utilizing FTICRMS. Copyright © 2013 John Wiley & Sons, Ltd.
A Computer Program to Improve LR Tests for Generalized Linear Models

Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion distributions. Improved likelihood ratio tests for these models were developed by Cordeiro (1983)Cordeiro (1987). We present a simple R program source for calculating Bartlett corrections to improve likelihood ratio tests in these models. The program was tested on some special models, confirming all of the previously reported numerical results for the Bartlett corrections.
What’s New in Innovation? A Contribution to the Novelty of Innovation Management Approaches

This contribution analyzes two sides of managerial strategic decisions on innovation: first the choices regarding innovation modes, second the choices concerning innovation outcomes protection/accessibility (IP strategy). Literature on innovation management treats these aspects in a somehow separate way. It follows a lack of frameworks which take simultaneously into account these two sides of innovation strategy. We develop a framework based on a set of components of the double managerial choice. The framework reflects a configurational approach to the strategic combinations on both innovation modes and outcomes. It provides guidelines to support strategic decision making. The set of factors highlights the hybrid nature of innovation models and shows the limitations of strategic decision making based on discrete dimensions: open versus closed and collective versus private outcomes.
Support Vector Learning for Gender Classification Using Audio and Visual Cues

Computer vision systems for monitoring people and collecting valuable demographic information in a social environment is an important research problem. It is expected that such a system will play an increasingly important role in enhancing user's experience and can significantly improve the intelligibility of a human computer interaction (HCI) system. For example, a robust gender classification system can provide a basis for passive surveillance and access to a smart building using demographic information or can provide valuable consumer statistics in a public place. The option of an audio cue in addition to the visual cue promises a robust solution with high accuracy and ease-of-use in human computer interaction systems. This paper investigates gender classification using Support Vector Machines (SVMs). The visual (thumbnail frontal face) and the audio (features from speech data) cues were considered for designing the classifier. Three different representations of the data, namely, raw data, principle component analysis (PCA) and non-negative matrix factorization (NMF) were used for the experimentation with visual signal. For speech, mel-cepstral coefficient and pitch were used for the experimentation. It was found that the best overall classification rates obtained using the SVM for the visual and speech data were 95.31% and 100%, respectively, on data set collected in laboratory environment. The performance of the SVM was compared with two simple classifiers namely, the nearest prototype neighbor and the k-nearest neighbor on all feature sets. It was found that the SVM outperformed the other two classifiers on all datasets. To further understand the robustness issues, the proposed approach has been applied on a large balanced (roughly equal distribution of gender, ethnicity and age group) data-base consisting of 8000 faces collected in real world environment. While, the results are very promising it indicates more to be done to make a statistically meaningful conclusion.
An obstacle avoidance method for mobile robots based on fuzzy decision-making

In this paper, an obstacle avoidance method for wheeled mobile robots is proposed, based on selection of the local target points of robot's movement called “via-points” which are defined in a navigation space, generated by taking into consideration a smooth robot motion. The proposed algorithm utilizes a fuzzy multi-attribute decision-making method in which three fuzzy goals are defined to achieve successful robot navigation by deciding the via-point the robot would proceed at each control step. Via-point is defined as the local target point of a robot's movement at each decision instance. Three fuzzy goals to achieve successful robot navigation are defined. At each decision step, a set of the candidates of a next via-point in a 2D navigation space is constructed by combining various heading angles and velocities. Given the fuzzy goals, the fuzzy decision making enables the robot to choose the best via-point among the candidates. An efficient scheme for local minimum recovery from trapped-in situation is also provided. A series of simulations has been performed to study the effects of associated navigation parameters on the navigation performances. The method has been implemented on an actual mobile robot and experimented in real environments. Results from a series of simulations and experiments conducted in real environments show the validity and effectiveness of the proposed navigation method.
The Impact of Information Technology on the Efficiency of Banks: (An Empirical Investigation from Pakistan)

Use of Information technologies (IT’s) is increasing day by day in banking industry all over the world. Investment in IT is helping the top level management in achieving their objectives and anticipated targets. This empirical study reveals the contribution and role of IT on the efficiency of bank and also explores the existence of relationship between the investment in IT and bank efficiency measures. The result shows that investment in information system is contributing towards increase market share, reducing operating cost, improved customer services and assisting the banks in introducing new products and services. These are the major benefits of investment in IT which are propelling many banks to invest in IT. That is the reason that most of the organizations in Pakistan are using the IT as competitive tool. The banks in Khyber Pukhtoon Khowa (KPK), a province of Pakistan are using IT to get competitive advantage as well.
Don’t understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures

An interesting aspect of structured prediction is the evaluation of an output structure against the gold standard. Especially in the loss-augmented setting, the need of finding the max-violating constraint has severely limited the expressivity of effective loss functions. In this paper, we trade off exact computation for enabling the use and study of more complex loss functions for coreference resolution. Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. The accurate model comparison on the standard CoNLL-2012 setting shows the benefit of more expressive loss functions.
Activity‐unrelated neural control of myogenic factors in a slow muscle

The properties of skeletal muscles are modulated by neural and nonneural factors, and the neural factors can be modulated by activity‐independent as well as activity‐dependent mechanisms. Given that daily activation of fast muscles is considerably less than of slow muscles, we hypothesized that the myogenic properties of the rat soleus (a slow muscle) would be more dependent on activity‐dependent than activity‐independent factors. Muscle mass, MyoD, and myogenin mRNA and protein levels, and satellite cell proliferation and differentiation rates (bromodeoxyuridine incorporation) were examined at 3, 14, and 28 days after either spinal cord isolation (SI, neuromuscular connectivity intact with minimal activation) or denervation (no neural influence). Soleus atrophy was similar in the SI and denervated groups at each time point, although increases in whole‐muscle expression of myogenin and, to a lesser degree, MyoD were lower (P < 0.05) in SI than denervated soleus muscles. Proliferation and differentiation of satellite cells, as well as mitotic activity of connective tissue cells, were lower (P < 0.05) in SI than denervated soleus muscles. In some instances, these changes were not observed until the later time points, i.e., 14 or 28 days. These results demonstrate that the motoneurons that innervate the slow soleus muscle have a significant modulatory influence on some muscle properties via mechanisms that are independent of activation. These activity‐independent modulatory influences, however, are less in the slow soleus than previously observed in fast muscles. Muscle Nerve, 2005
Methods and potentials of magnetic resonance imaging for monitoring radiofrequency hyperthermia in a hybrid system

Introduction: Non-invasive thermometry (NIT) is a valuable and probably indispensable tool for further development of radiofrequency (RF) hyperthermia. A hybridization of an MRI scanner with a hyperthermia system is necessary for a real-time NIT. The selection of the best thermographic method is difficult, because many parameters and attributes have to be considered. Methods: In the hybrid system (Siemens Symphony/BSD-2000-3D) the standard methods for NIT were tested such as T1, diffusion (ADC: apparent diffusion coefficient) and proton-resonance-frequency shift (PFS) method. A series of three-dimensional datasets was acquired with different gradient-echo sequences, diffusion-weighted EPI spin-echo sequences and calculated MR-temperatures in the software platform AMIRA-HyperPlan. In particular for the PFS-method, corrective methods were developed and tested with respect to drift and other disturbances. Experiments were performed in phantoms and the results compared with direct temperature measurements. Then the procedures were transferred to clinical applications in patients with larger tumours of the lower extremity or the pelvis. Results: Heating experiments and MR-thermography in a homogeneous cylindrical phantom give an excellent survey over the potentials of the methods. Under clinical conditions all these methods have difficulties due to motion, physiological changes, inhomogeneous composition and susceptibility variations in human tissues. The PFS-method is most stable in patients yielding reasonable MR temperature distributions and time curves for pelvic and lower extremity tumours over realistic treatment times of 60–90 min. Pooled data exist for rectal tumour recurrencies and soft tissue sarcomas. The fat tissue can be used for drift correction in these patients. T1 and diffusion-dependent methods appear less suitable for these patients. The standard methods have different sensitivities with respect to the various error sources. The advantages and pitfalls of every method are discussed with respect to the literature and illustrated by the phantom and patient measurements. Conclusions: MR-controlled RF hyperthermia in a hybrid system is well established in phantoms and already feasible for patients in the pelvic and lower extremity region. Under optimal conditions the temperature accuracy might be in the range of 0.5°C. However a variety of developments, especially sequences and post-processing modules, are still required for the clinical routine.
Absence of human astrovirus RNA in sewage and environmental samples

Over a period of several weeks during the summer of 1996, samples of sewage, sea water, river water, sand and silt were collected from a sewage works at Weston‐super‐Mare, England and from coastal areas nearby. A sensitive reverse‐transcriptase polymerase chain reaction (RT‐PCR) was used to search for human astrovirus (HAstV) RNA in concentrates of the samples. No evidence of astrovirus was found in any sample, which suggests that contamination with these viruses is not a problem in this area during the summer holiday season. Furthermore, the single case of astrovirus diarrhoea diagnosed in this laboratory in the summer occurred at the end of the sampling period, and not in the survey area. The primers used sometimes yielded a product two‐thirds the expected size but bearing no sequence homology with HAstV. The confirmation that poliovirus adsorbs to sand and silt shows that these materials might be able to concentrate other enteric viruses in water to a level which could be a threat to the health of people coming into contact with it.
Integrated Marketing Communications and Market Planning

Abstract This article links the integrated marketing communications (IMC) concept to the planning process in marketing. Following the current conceptualizations as a combination of various marketing communications tools, IMC strategy is applied to an established strategic market planning model named the Boston Consulting Group (BCG)'s growth-share matrix. Advertising, public relations, sales promotion, and direct marketing are defined as crucial elements for the core scheme. Alternative strategies for brands in different stages are identified from the product portfolio analysis. The view may also be thought of as the ongoing process of building and maintaining brand equity for consumers in the long-term period. Conceptual discussions are expected to help marketers think more strategically as they plan IMC programs for their products or services.