Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Study of Acyclovir Microencapsulation by Novel Solvent Evaporation-Matrix Erosion and Spray Drying Techniques

Designing and evaluating a multiparticulate controlled release dosage form, to increase the efficacy of acyclovir (a selective antiherpes agent). Spray drying technique for microsphere production is compared with novel solvent evaporation-matrix erosion technique for variable drug loading in different concentration of ethyl cellulose. The microspheres were characterized for physicochemical properties. The microspheres sizes were ranged from 7-25 μm. The spray dried microspheres had better encapsulation efficiency (up to 91%) compared to that of novel solvent evaporation-matrix erosion technique microspheres. Scanning electron microscopy confirmed spherical geometry due to high crosslinking density. Differential scanning calorimetry, Fouriertransform infrared spectroscopy and x-ray diffraction studies showed chemical stability and intactness of entrapped drug in the microspheres. In vitro release of acyclovir from spray dried microspheres continued for longer period compared to novel solvent evaporation-matrix erosion method. Overall, the release studies depended on the concentration of ethyl cellulose, extent of drug loading, and the technique used to prepare microspheres. Thus, marked retardation of drug release may provide a useful effective anti-retroviral drug therapy.
Dispositions in the twenty-first century school library profession

Within the school library profession there is an emerging focus on dispositions, defined as "a tendency to exhibit frequently, consciously, and voluntarily a pattern of behavior that is directed to a broad goal" (Katz, 1993). Directed focus groups of practicing school librarians were asked to articulate their vision for school libraries of the future. Data from these groups informed development of six dispositional continua to guide both school library education and school librarianship in the 21stcentury.This study clarifies the dispositions needed by school librarians in the future.
Modelling energy demand from higher education institutions using a hybrid panel model : a case study of the UK

Among the various sustainability goals of higher education institutions (HEIs), reducing energy use and carbon emissions are particularly important. However, not much is known about energy demand from the higher education sector – especially since there is a lack of robust models of energy demand in this sector. This paper, the first to utilize a panel dataset and advanced panel econometric techniques in order to model energy use in higher education, investigates variations in energy use between HEIs (cross-sectional analysis), and also changes in energy use over time (temporal analysis), using the UK as a case study. We argue that panel dataset and methods are more useful for understanding growth (and reduction) in energy use within the HE sector than the methods used within previous cross-sectional studies. Results show that, over time and also across the sector, energy consumption in the HEIs increases with increases in income and floor space, but at a slower rate. As HEIs grow overall (in terms of income, floor space, student and staff number) over time, they become more 'energy efficient' (using less energy per unit of area, population or income), indicating economies of scale in the temporal dimension. Results also show that after controlling for income and size, research intensive HEIs consume more energy. We also find a small but statistically significant effect of energy prices on energy consumption, as might be expected. Simulation using the model parameters for an example scenario suggests that energy consumption will continue to increase unless there is a significant change in the policies driving income growth and spatial expansion in the HE sector in the UK.
Estimation of the parameters of fish stock dynamics from catch-at-age data and indices of abundance: can natural and fishing mortality be separated?

Models for fluctuations in size of fish stocks must include parameters that describe expected dynamics, as well as stochastic influences. In addition, reliable population projections also require assessments about the uncertainties in estimates of vital parameters. Here we develop an age-structured model of population dynamics based on catch-at-age data and indices of abundance in which the natural and fishing mortality are separated in a Bayesian state–space model. Markov chain Monte Carlo methods are used to fit the model to the data. The model is fitted to a data set of 19 years for Northeast Arctic cod (Gadus morhua). By simulations of the fitted model we show that the model captures the dynamical pattern of natural mortality adequately, whereas the absolute size of natural mortality is difficult to estimate. Access to long time series of high-quality data are necessary for obtaining precise estimates of all the parameters in the model, but some parameters cannot be estimated without including some pr.
Batch Normalized Deep Boltzmann Machines

Training Deep Boltzmann Machines (DBMs) is a challenging task in deep generative model studies. The careless training usually leads to a divergence or a useless model. We discover that this phenomenon is due to the change of DBM layers’ input signals during model parameter updates, similar to other deterministic deep networks such as Convolutional Neural Networks (CNNs) or Recurrent Neural Networks (RNNs). The change of layers’ input distributions not only complicates the learning process but also causes redundant neurons that simply imitate the others’ behaviors. Although this phenomenon can be coped using batch normalization in deep learning, integrating this technique into the probabilistic network of DBMs is a challenging problem since it has to satisfy two conditions of energy function and conditional probabilities. In this paper, we introduce Batch Normalized Deep Boltzmann Machines (BNDBMs) that meet both aforementioned conditions and successfully combine batch normalization and DBMs into the same framework. However, unlike CNNs, due to the probabilistic nature of DBMs, training DBMs with batch normalization has some differences: i) fixing shift parameters β but learning scale parameters γ; ii) avoiding normalizing the first hidden layer and iii) maintaining multiple pairs of population means and variances per neuron rather than one pair in CNNs. We observe that our proposed BNDBMs can stabilize the input signals of network layers and facilitate the training process as well as improve the model quality. More interestingly, BNDBMs can be trained successfully without pretraining, which is usually a mandatory step in most existing DBMs. The experimental results in MNIST, Fashion-MNIST and Caltech 101 Silhouette datasets show that our BNDBMs outperform DBMs and centered DBMs in terms of feature representation and classification accuracy (3.98% and 5.84% average improvement for pretraining and no pretraining respectively).
Syddansk Universitet Effectiveness of the "Cancer Home-Life Intervention" on everyday activities and quality of life in people with advanced cancer living at home a randomised controlled trial and an economic evaluation

Background: During the past decade an increasing number of people live with advanced cancer mainly due to improved medical treatment. Research has shown that many people with advanced cancer have problems with everyday activities, which have negative impact on their quality of life, and that they spend a considerable part of their time at home. Still, research on interventions to support the performance of and participation in everyday activities is only scarcely available. Therefore, the occupational therapy-based “Cancer Home-Life Intervention” consisting of tailored adaptive interventions applied in the participant’s home environment was developed. The objective of this study is to examine the effectiveness and cost-effectiveness of the Cancer Home-Life Intervention compared to usual care on the performance of and participation in everyday activities and quality of life in people with advanced cancer living at home. Methods: The study is a randomised, controlled trial (RCT) including an economic evaluation. The required sample size of 272 adults living at home will be recruited from outpatient clinics at two Danish hospitals. They should be diagnosed with cancer; evaluated incurable by the responsible oncologist; and with a functional level 1–2 on the WHO performance scale. The primary outcome is the quality of performance of activities of daily living. Secondary outcomes are problems with prioritised everyday activities; autonomy and participation; and health-related quality of life. Participants are randomly assigned to: a) The Cancer Home-Life Intervention in addition to usual care, and b) Usual care alone. Discussion: The trial will show whether the Cancer Home-Life Intervention provides better support for people with advanced cancer living at home in performing and participating in everyday activities, and whether it contributes to their health-related quality of life. The economic evaluation alongside the RCT will show if the Cancer Home-Life Intervention is cost-effective. The trial will also show the acceptability of the intervention to the target group, and whether subgroups of participants will benefit more than others. Trial registration: ClinicalTrials.gov Identifier NCT02356627. Registered 02/02/2015.
Blindfolded vs. Informed Ultimatum Bargaining – A Theoretical and Experimental Analysis

Abstract This paper analyzes blindfolded vs. informed ultimatum bargaining where proposer and responder are both either uninformed or informed about the size of the pie. Considering the transition from one information setting to another suggests that more information induces lower (higher) price offers and acceptance thresholds when the pie is small (large). While our experimental data confirm this transition effect, risk aversion leads to diverging results in blindfolded ultimatum bargaining where task-independent strategies such as ‘equal sharing’ or the ‘golden mean’ are implemented more frequently.
Identification of genomic markers correlated with sensitivity in solid tumors to Dasatinib using sparse principal components

ABSTRACT Differential analysis techniques are commonly used to offer scientists a dimension reduction procedure and an interpretable gateway to variable selection, especially when confronting high-dimensional genomic data. Huang et al. used a gene expression profile of breast cancer cell lines to identify genomic markers which are highly correlated with in vitro sensitivity of a drug Dasatinib. They considered three statistical methods to identify differentially expressed genes and finally used the results from the intersection. But the statistical methods that are used in the paper are not sufficient to select the genomic markers. In this paper we used three alternative statistical methods to select a combined list of genomic markers and compared the genes that were proposed by Huang et al. We then proposed to use sparse principal component analysis (Sparse PCA) to identify a final list of genomic markers. The Sparse PCA incorporates correlation into account among the genes and helps to draw a successful genomic markers discovery. We present a new and a small set of genomic markers to separate out the groups of patients effectively who are sensitive to the drug Dasatinib. The analysis procedure will also encourage scientists in identifying genomic markers that can help to separate out two groups.
Reliability and Accuracy of Ball Speed During Different Strokes in Young Tennis Players

Abstract This study aimed to examine the relationship between anthropometric and sport level (SL) variables and both ball speed and accuracy in young male competitive tennis players. A secondary aim of this study was to analyze the possible differences in ball speed and accuracy between players of different competitive levels. A total of 85 players (age: 14.7±2.4 years; height: 1.65±0.12 m; body weight: 56.3±13.4 kg) were divided into five groups according to their positions in the ranking list. To measure stroke performances, the goal was to hit 20 balls at the maximum possible speed inside the court, with the opportunity of hitting a maximum of 30 balls for each groundstroke and 40 for serve. Accuracy was calculated by dividing the number of balls inside the default surface by the total number of hits. The ball speed showed high reliability for all three strokes assessed. The ball speed progressively increased as SL increased for all strokes, whereas accuracy remained unchanged across SL groups. All independent variables presented significant relationships (r=0.59–0.85, p<0.05–0.001) with ball speed for all strokes. However, after applying partial correlations these relationships decreased substantially (r=0.02–0.51). The accuracy showed significant relationships with SL only in the serve (r=0.31, p<0.05) and backhand (r=0.26, p<0.05) strokes. In conclusion, the results of the present study suggest that tennis performance depends on increasing ball speed while maintaining a relatively stable level of accuracy.
The determination of financial structure: the incentive-signalling approach

The Modigliani-Miller theorem on the irrelevancy of financial structure implicitly assumes that the market possesses full information about the activities of firms. If managers possess inside information, however, then the choice of a managerial incentive schedule and of a financial structure signals information to the market, and in competitive equilibrium the inferences drawn from the signals will be validated. One empirical implication of this theory is that in a cross section, the values of firms will rise with leverage, since increasing leverage increases the market's perception of value.
Spread and interaction of Pepino mosaic virus ( PepMV ) and Pythium aphanidermatum in a closed nutrient solution recirculation system : effects on tomato growth and yield

D. Schwarz*, U. Beuch, M. Bandte, A. Fakhro, C. Büttner and C. Obermeier Institute of Vegetable and Ornamental Crops, Großbeeren ⁄ Erfurt e.V. , Theodor Echtermeyer Weg 1, D-14979 Großbeeren, Germany; Section Phytomedicine, Department of Crop and Animal Sciences, Faculty of Agriculture and Horticulture, Humboldt University Berlin, , Lentzeallee 55-57, D-14195 Berlin, Germany; Swedish University of Agricultural Sciences, Genetic Centre PO Box 7080, S-75007 Uppsala, Sweden; and Department of Plant Breeding, Justus Liebig University Giessen, Heinrich-Buff-Ring 26-32, D-35392 Giessen, Germany
Technical Note: Rabbit welfare during electrical stunning and slaughter at a commercial abattoir

A total of 1020 crossbreed rabbits were individually examined to evaluate their welfare during electric stunning and slaughter in a commercial abattoir. Stunning (the position of electrodes and repetition of applications of current) and sticking (the position, length and depth of the cut) procedures were checked. The rabbits were monitored behaviourally from the application of the current to death. The stunning system was incorrectly applied one hundred and ten times (10.8%). Three rabbits failed to be stunned and were still conscious at sticking. Eighteen rabbits recovered before the onset of death, as shown by their corneal reflex and in a few cases, vocalization (n=3) and head movement (n=1) were observed. Corneal reflex seemed to be the best indicator of recovery at the abattoir.
Effect of Stages of Maturity on Nutritive Value of Some Range Herbage Species in Low-Rainfall Woodland Savanna Southern Darfur, Sudan

Nine samples of range herbage species were collected within the grazing season using 0.5 × 0.5 m quadrate as from three weeks initial pasture growth established in June across throughout up to December (two seasons), to examine the effects of age on the trend of some chemical compositions and energy changes. Analysis of variance indicated that the chemical composition of grassland from 3 weeks of age, to 12 weeks of age across to 27 weeks of age was affected by the grass age, where the metabolizable energy contents were 15.85, 13.11 and 12.36 MJ/Kg/DM respectively. Hemi-celluloses and cellulose content showed a significant difference increase (P < 0.05) throughout the grazing season as grass age increases. The results also revealed that the Organic Matter (OM), Crude Protein (CP) and Metabolizable Energy (ME MJ/Kg DM) were significantly (P < 0.05) tended to be high at the beginning of growing season (mid July) (91.05%, 3.8% and 8.77 MJ respectively), then increased towards the mid of grazing season (mid September) and reduced towards the end of the grazing season (mid December).
Design of a Multi-Arm Surgical Robotic System for Dexterous Manipulation

Surgical procedures are traditionally performed by two or more surgeons along with staff nurses: one serves as the primary surgeon and the other as his/her assistant. Introducing surgical robots into the operating room has significantly changed the dynamics of interaction between the surgeons and with the surgical site. In this paper, we design a surgical robotic system to support the collaborative operation of multiple surgeons. This Raven IV surgical robotic system has two pairs of articulated robotic arms with a spherical configuration, each arm holding an articulated surgical tool. It allows two surgeons to teleoperate the Raven IV system collaboratively from two remote sites. To optimize the mechanism design of the Raven IV system, we configure the link architecture of each robotic arm, along with the position and orientation of the four bases and the port placement with respect to the patient’s body. The optimization considers seven different parameters, which results in 2:3 10 system configurations. We optimize the common workspace and the manipulation dexterity of each robotic arm. We study here the effect of each individual parameter and conduct a brute force search to find the optimal set of parameters. The parameters for the optimized configuration result in an almost circular common workspace with a radius of 150 mm, accessible to all four arms. [DOI: 10.1115/1.4034143]
Hazards of antithrombotic therapy on hemodialysis patients with atrial fibrillation and high thromboembolic risk: A Taiwanese population-based cohort study

The benefit of antithrombotic therapy in hemodialysis (HD) patients with atrial fibrillation (AF) and high thromboembolic risk has not been proved. The purpose of this study was to examine the effects of antithrombotic therapy on HD patients with AF and high thromboembolic risk. We analysed the outcomes of 1,197 HD patients with AF having CHA2DS2-VASc scores ≥ 2 points by using data retrieved from the National Health Insurance Research Database between 1997 and 2008. Four groups of patients, namely aspirin, warfarin, aspirin combined with warfarin, and non-treatment groups, were compared. Between the treatment and non-treatment groups, multivariate Cox proportional analysis revealed no significant difference in the mortality. Among the treatment groups, the aspirin combined with warfarin group had a higher mortality than that of the aspirin group. No significant differences were observed among the four groups in the risks of haemorrhagic stroke, gastrointestinal bleeding, congestive heart failure, acute coronary syndrome, and peripheral arterial occlusive disease. However, the risk of ischemic stroke was significantly higher in the aspirin and the aspirin combined with warfarin groups than in the non-treatment group. In HD patients with AF and with high thromboembolic risks, the mortality rate was not significantly different between treatment groups and non-treatment group. However, the risk of ischemic stroke was significantly higher in aspirin and aspirin plus warfarin groups when compared with non-treatment group. Therefore, the usage of aspirin and warfarin in these patients should be meticulously evaluated.
Local Politics and Economic Geography: Information Aggregation and Polarization

type="main"> We consider information aggregation in national and local elections when voters are mobile and might sort themselves into local districts. Using a standard model of private information for voters in elections in combination with a new economic geography model, agglomeration occurs for economic reasons, whereas voter stratification occurs due to political preferences. When trade is more costly, people tend to agglomerate for economic reasons, resulting in full information equivalence in the political sector. Under free trade, people sort themselves into districts, most of which are polarized, resulting in no full information equivalence in these districts.
A Hybrid DBN and CRF Model for Spectral-Spatial Classification of Hyperspectral Images

Hyperspectral image classification plays an important role in remote sensing image analysis. Recent techniques have attempted to investigate the capabilities of deep learning approaches to tackle the hyperspectral image classification. This work shows how to further improve the hyperspectral image classification through using both a deep representation and contextual information. To implement this objective, this work proposes a new Conditional Random Field (CRF) model (named DBN-CRF) with the potentials defined over the deep features produced by a Deep Belief Network (DBN). The newly formulated DBN-CRF model takes advantage of the strength of DBNs in learning a good representation and the ability of CRFs to model contextual (spatial) information in both the observations and labels. Within a piecewise training framework, an efficient training method is proposed to train the whole DBN-CRF model end-to-end. This means that the parameters in DBN and CRF can be jointly trained and thus the proposed method can fully use the strength of both DBN and CRF. Moreover, in the proposed training method, the end-to-end training can be implemented with a standard back-propagation algorithm, avoiding the repeated inference usually involved in CRF training and thus is computationally efficient. Experiments on real-world hyperspectral data show that our method outperforms the most recent approaches in hyperspectral image classification.
User Evaluation of an Interactive Music Information Retrieval System

Music information retrieval (MIR) is a highly inter active process and MIR systems should support users’ interactions during the process. However, there are very few user-centered xperiments in evaluating interactive MIR systems. In this pape r, we present a user experiment with 32 participants evaluating two result presentation modes of a music mood recommendation s ystem for two music seeking tasks, using user-centered measur s. Preliminary results disclosed that the presentation modes made significant difference on some of the user-centered m asures and users may enjoy the less effective but more appeali ng mode.