Miracle-dz/UniFAR-FTUs huggingface dataset:
An Investigation into the Factors Governing Drug Absorption and Food Effect Prediction Based on Data Mining Methodology

Drug absorption is a complex process governed by a number of interrelated physicochemical, biopharmaceutical, and pharmacokinetic factors. In order to explore complex relationships among these factors, multivariate exploratory analysis was performed on the dataset of drugs with diverse bioperformance. The investigated dataset included subset of drugs for which bioequivalence between solid dosage form and oral solution has been reported, and subset of drugs described in the literature as low solubility/low permeability compounds. Discriminatory power of hierarchical clustering on principal components was somewhat higher when applied on the data subsets of drugs with similar bioperformance, while analysis of the integrated dataset indicated existence of two groups of drugs with the boundaries reflected in Peff value of approximately 2 × 10−4 cm/s and Fa and Fm values higher than 85% and 50%, respectively. Majority of the investigated drugs within the integrated dataset were grouped within their initial subset indicating that overall drug bioperformance is closely related to its physicochemical, biopharmaceutical and pharmacokinetic properties. Classification models constructed using the random forest (RF) and support vector machine with polynomial kernel function were able to predict food effect based on drug dose/solubility ratio (D/S), effective permeability (Peff), percent of dose metabolized (Fm), and elimination half-life (τ1/2). Although both models performed well during training and testing, only RF kept satisfying performance when applied on the external dataset (kappa value > 0.4). The results obtained indicate that data mining can be employed as useful tool in biopharmaceutical drug characterization which merits further investigation.
Impact of acoustic enviornment on work in open-plan offices across job characteristics

© Proceedings of the 26th International Congress on Sound and Vibration, ICSV 2019. All rights reserved. This study aims to investigate the impacts of acoustic environment on the relationship between job characteristics and job satisfaction. Acoustic measurements and questionnaire surveys were conducted in open-plan offices in the UK and Korea. Background noise levels were recorded for 8 hours in each office and speech transmission index (STI) and sound pressure levels were measured for quantifying the single number quantities in ISO 3382-3. A total of 324 employees from 12 offices completed a questionnaire survey. The questionnaire included questions assessing noise disturbances and speech privacy, as well as job satisfaction and job characteristics. The result confirmed the strong impacts of job characteristics on self-rated job satisfaction. Background noise levels during working hours and reverberation time were negatively associated with job satisfaction; however, there were little influences of speech privacy and noise disturbance on job satisfaction. It was also observed that speech privacy, noise disturbance, background noise level, and cultural difference (Korea and UK) had moderating effects on the relationship between job characteristics and job satisfaction. In particular, greater speech privacy and lower background noise level increased the impacts of job characteristics on job satisfaction
The Application of a Falls Risk Index

This study examined the prospective use of a falls risk index. The research question was: To what extent do the intrinsic factors identified in the Tinetti et al. falls risk index predict which patients are likely to experience a fall. Hogue's ecological model of falls in late life provided a conceptual framework for the study. Direct observation was used to collect baseline data from a convenience/purposive sample of 26 male patients in a midwest nursing home care unit with a rehabilitation focus. Patients were then assigned to one of three risk groups: yes-fall, 30% chance of fall, no-fall. Reports of patient falls were reviewed during the following four months. Data were analyzed by discriminant analysis and frequency tables. Actual occurrences were demonstrated to be consistent with predicted occurrences in the frequency tabulation, and 23/26 Participants were classified correctly by discriminant analysis. There are several considerations in the interpretation of this data: (1) over half the sample was in the predicted middle—risk group (30% chance of falls) which has limited clinical usefulness, (2) the discriminant analysis equation was developed from study data, and (3) no variable contributed significantly to risk of falling in the stepwise entrance of variables analysis. Nonetheless, predictability of the extremes (yes-fall or no-fall) using reproducible scales to evaluate risk factors was demonstrated, and may be useful clinically as well as in other studies of patient falls. I give permission to the College of Nursing, SDSU to publish this abstract in a collection of abstracts from master's projects and theses.
ePubWU Institutional Repository

This paper analyses the role of the spatial structure of migrant networks in the location decision of migrants to the European Union at the regional level. Using a random parameters logit specification, a significant positive effect of migrant networks in neighbouring regions on migrants’ location decisions is found. Although this spatial spillover effect is smaller than the effect of networks in the host regions, omitting to control for this spatial dependence results in a 40% overestimation of the effect of regional migrant networks on the location decision of newly arriving migrants.
The Effect of Thermal Care Workshop on EMS Staff Readiness in managing Accidental Hypothermia in Trauma Patients

Background: Hypothermia is a common complication in trauma patients. Studies show that the management of hypothermia in trauma patients in the pre-hospital phase may be underestimated. Objectives: The purpose of this study was to evaluate the effect of thermal care workshop on the staff readiness to manage hypothermia in trauma patients. Methods: This quasi-experimental study utilized convenience sampling after obtaining the approval of the Research Ethics Committee and involved 60 qualified EMS staff who were divided into two groups including: intervention group (30 technicians) and control group (30 technicians). The intervention group received the treatment in the form of a workshop. Nonetheless, the control group did not receive any educational intervention. The data were collected before, immediately after and 45 days after the workshop to determine EMS staff readiness using a validated researcher-made questionnaire. In this study, the significance level was 0.5. Results: There was a significant difference between the posttest results of the control group and the intervention group (p<0.001). Moreover, in the intervention group, there were significant differences between the pretest results and the two posttest results (p<0.001). Finally, the readiness gained after the workshop lasted for 45 days. Conclusion: The thermal care workshop enhanced the readiness of emergency medical personnel. The generalization of the results of this study is restricted due to the fact that random selection and random assignment of participants were not possible in the present study. It is recommended that more robust studies be designed to evaluate, prevent and manage hypothermia in trauma patients in the pre-hospital phase.
TABLE OF CONTENTS Thiol group functionalization of mesoporous SiO2 SBA-15 using supercritical CO2

Chemical modification of mesoporous SiO2 SBA-15 with thiol groups was performed using mercaptopropyltrimethoxysilane (MPTMS) dissolved in supercritical CO2 (scCO2). Thiol groups serve as adsorbents for the selective removal of contaminant metal cations and in catalysis. Functionalization was carried out in scCO2 at temperatures ranging from 40 to 150 oC and pressures from 15.0 to 29.0 MPa. For comparison purposes, the reaction was also performed in toluene at 80 and 110 oC. As opposed to toluene, scCO2 is considered a green solvent. Grafting of the thiol groups was confirmed by FTIR spectroscopy, thermogravimetric analysis (TGA) and elemental analysis. Grafting density and surface coverage of the materials modified using scCO2 increased with temperature, CO2 density, time and stirring and varied from 1.3 to 4.4 mmol g -1 and from 1.3 to 4.0 molecules nm -2 , respectively. On the other hand, surface area and pore size decreased as grafting density increased. At temperatures of 80 oC or higher, the pore size remained constant, suggesting the formation of a compact monolayer. Modification at higher temperatures led to larger grafting densities but very low surface areas. Assuming total hydrolysis and condensation of the precursor, the optimum grafting density and surface coverage of 2.3 mmol g -1 and 2.4 molecules nm -2 , respectively, were obtained in scCO2 at 80 oC and 25.0 MPa for 4 h. Grafting densities of the samples prepared in toluene were by far much lower than those obtained using scCO2 at lower temperatures and shorter times, which demonstrates the advantages of CO2 as a green functionalization medium.
Learning Data-Driven Objectives to Optimize Interactive Systems

Effective optimization is essential for interactive systems to provide a satisfactory user experience. However, it is often challenging to find an objective to optimize for. Generally, such objectives are manually crafted and rarely capture complex user needs in an accurate manner. We propose an approach that infers the objective directly from observed user interactions. These inferences can be made regardless of prior knowledge and across different types of user behavior. We introduce interactive system optimization, a novel algorithm that uses these inferred objectives for optimization. Our main contribution is a new general principled approach to optimizing interactive systems using data-driven objectives. We demonstrate the high effectiveness of interactive system optimization over several simulations.
Comprehensive Perception Approach of Adoption: Experimenting Hybrid Chinese Maize Varieties in Benin

The probability of adoption of four Chinese Hybrid Varieties of maize is considered as a favorable perception for these varieties by actors. In order to understand the way of adoption, a panel of actors comprising producers, processors, traders, extension officers, local elected representatives and, above all, end-users, was used as enumerator to evaluate the behavior of those varieties in comparison to the reference maize varieties known as “local” in experiment plots during the vegetative, harvesting and processing phases. For each actor surveyed and for each introduced variety, the comparative index of appreciation (IA) was determined by the difference in perception scores with respect to each of the descriptors evaluated. The adoption of maize varieties within the sites surveyed was affected by the respondent’ social profile (title), the number of varieties already adopted by the respondent, respondent’s experience, age, educational background, membership to an association/organization and the site (research station). The estimation of adoption relative to probabilities (odds ratio) of each variety of maize from the binary logistic regression models revealed only one variety having more than one in two chances for being adopted. Unlike the adoption rate of maize varieties calculated after expensive dissemination efforts, the analysis of probabilities and determinants of adoption somewhat reduces research, pre-extension and extension efforts. The proposed approach allows for a flexible integration of research experiments and field extension concerns of the process of adoption by creating panels of stakeholders around research experiments on research stations.
Testing the feasibility of calculating stellar and gaseous true circular velocities from CALIF IFU data

Die Massenverteilung einer Galaxie bestimmt das Gravitationspotential, welches wiederum die geordnete Bewegung innerhalb der Galaxie definiert. Dadurch kann man von der Bewegung der Sterne und des Gases einer Galaxie Ruckschlusse auf die dunkle Materieverteilung gewinnen, wenn man die wahre Kreisgeschwindigkeit kennt. Die Daten wurden vom Team der CALIFA Studie als 3D Datenkuben zur Verfugung gestellt und mit einer Ellipsenfitmethode analysiert. Die Datenpunkte entlang der Ellipsen wurden Fouriertransformiert und die Koeffizienten in physikalisch aussagekraftige Parameter umgerechnet. Zwischen der beobachteten und der wahren Kreisgeschwindigkeit gibt es eine Differenz, welche durch eine asymmetrische Driftkorrektur mit Hilfe der Momente der stosfreien Boltzmanngleichung korrigiert wurde. Die wahre Kreisgeschwindigkeit der Sterne konnte problemlos aus den CALIFA Daten berechnet werden. Die Berechnungen der Gasdaten fuhrten allerdings nicht zu physikalisch brauchbaren Ergebnissen, was wohl auf die Qualitat der Daten zuruckzufuhren ist.
Influences of reasoning and achievement motivation on complex problem solving in a new microworld operationalization

Complex Problem Solving (CPS) can be defined as those psychological processes that enable a person to achieve goals under complex conditions, which are characterized by their complexity, connectivity, dynamics, lack of transparency, and polytely. Although many hypothesized influences have previously been tested concerning their relevance for the process of solving complex problems (e.g., general intelligence), results were often found to be rather heterogeneous. As this was found to be partially caused by fundamental differences between measurements of CPS, a new operationalization was used in the present study: Following the Microworld approach, CPS was assessed in the simulation game Cities: Skylines, as its aptitude as a Microworld could be justified from a theoretical perspective. A parameter for CPS performance was defined to investigate the following hypotheses: Both reasoning and achievement motivation were expected to be positively correlated to CPS performance. Furthermore, a gender difference favoring male participants was expected. Participants in the present study (N = 27) first provided demographic information, then subsequently completed a short test of reasoning and an objective personality test of achievement motivation, and finally were given a mission in a complex scenario implemented in Cities: Skylines. The results supported all three hypotheses, indicating significant small to moderate positive relationships of both reasoning and achievement motivation with CPS performance, and a significant gender difference favoring male participants in CPS performance. Furthermore, significant gender differences favoring males were also found for reasoning and achievement motivation. Results are discussed and the Microworld operationalization is evaluated.
Energy Poverty in Ecuador

This paper aims to identify the presence of energy poverty in Ecuador. Three indicators proposed by the European Union Energy Poverty Observatory (EPOV) are used to construct a multidimensional energy poverty index (MEPI) based on measure conditions associated with energy poverty, in areas related to delays in the payment of electricity bills, disproportionate expenses, hidden energy poverty, and the 10% Boardman (1991) rule. The information comes from the Ecuatorian Life Conditions Survey. The results show that energy poverty is present in Ecuadorian households, at the national level, and just as these indicators have restrictions, advantages and disadvantages, which demand decisions about the choice of their use.
A Web Browsing Traffic Model for Simulation: Measurement and Analysis

The simulation of packet switched networks depends on accurate workload models to serve as input for network models. We derive a workload model for data traffic generated by an individual browsing the web. The parameters of the model characterize user, web browser software, and web server software behaviour, independently of underlying network characteristics such as latency and throughput, which differ between network sites. We measured data on a campus network by capturing packet traces of IP, TCP and HTTP header data. The data were processed by extracting datasets for the model parameters from the data. The approach of obtaining datasets for parameters is novel as a heuristic algorithm was used to achieve this. The parameter datasets were analyzed by using visual techniques and goodness-of-fit measures for deriving analytic distributions. The workload model will be implemented as a traffic generating module in a network simulator. Traffic generated by the model will be validated by analyzing burstiness and self-similarity characteristics of the traffic, as well as comparing it to independently measured traffic. This paper presents our work up to date, which includes the definition of our workload model, the measurement and processing of web traffic data and initial findings from our statistical analysis of the data .
Reinstatement of Plagiochila sect. Abietinae

The classification of the speciose leafy liverwort genus Plagiochila into species and sections is still in a preliminary state. Based on phylogenetic analyses of a dataset comprising nuclear ITS and chloroplast rps4 and rbcL sequences, we reject an earlier proposed synonymy of the Asian-Australasian Plagiochila sect. Abietinae and the pantropical P. sect. Vagae. A monophyletic sect. Abietinae is recognised, containing a clade with five accessions of P. abietina sister to a single accession of P. hampeana. This Abietinae clade nests in a larger Plagiochila clade which also retrieves monophyletic sects. Fruticosae, Trabeculatae, Peculiares, Plagiochila and Poeltiae. Plagiochila sect. Vagae is placed sister to P. sect. Africanae. Two P. abietina accessions from Australia form a sister relationship with a clade comprising three P. abietina accessions from the Fiji Islands. Based on the example of P. patula, we discuss the benefits of including type or topotype specimens in revisionary studies considering molecular and morphological evidence. Barcoding / integrative taxonomy / Jungermanniales / liverwort / Lophocoleineae / Plagiochila sect. Vagae
Spectral Mixture Kernel Approximation Using Reparameterized Random Fourier Feature

Gaussian Process (GP) has been widely used to model the complex input and output relationship of the data due to its expressive power (Rasmussen, 2004). Selecting a kernel to determine the structure of the covariance is a crucial factor governing the performance of GP model. Spectral Mixture (SM) kernel devised by Wilson (Wilson and Adams, 2013) can be one candidate kernel because SM kernel can approximate any stationary kernel. In spite of its expressive power, training SM kernel takes more time due to many SM kernel hyperparameters. This drawback would prevent this SM kernel from being widely applied to practical problems for a large volume of data. Generally, two approaches have been mainly studied for the scalability of GP model: inducing inputs method (Titsias, 2009; Hensman et al., 2013; Salimbeni et al., 2018) and sparse spectrum based on Random Fourier Feature (Lázaro-Gredilla et al., 2010; Gal and Turner, 2015; Hoang et al., 2017). In this paper, we propose SM kernel approximation method by Reparameterized Random Fourier Feature (R-RFF). Also, we develop the regularized sparse spectrum approximation for kernel learning. Specifically, we apply the reparameterization trick (Kingma and Welling, 2013) to Random Fourier Feature (Rahimi and Recht, 2008) in the sense of both general parameter and natural parameter. In the process, we develop a robust sampling algorithm to consider the number of spectral points dependent on the ratio of weight parameters of SM kernel. Based on developed SM kernel approximation, we propose a training method employing Stochastic Gradient Variational Bayes (SGVB) to regularized lower bound. This approach allows us to scalably train GP model using SM kernel based on a stochastic optimization framework.
Memristive properties in GaN HEMTs affected by deep-level traps

In this MSc Thesis we evaluate the channel current characteristics of a GaN High Electron Mobility Transistor (GaN HEMT) for its potential memristive characterisics. Using a Matlab implementation of the SRH physics model and several experimental pulsed I/V and sinusoidal excitation data, we demonstrate that GaN HEMT channels affected by deep level traps can indeed display the two fundamental memristive criteria: (i) A pinched hysteretic trajectory in the iDS/vDS phase plane when the device is excited by a sinusoidal stimulus, and (ii) a hysteresis area that is monotonic and vanishes for increasingly higher frequencies. Resumo Nesta dissertação de Mestrado nós avaliamos as caracteŕısticas da corrente do canal de um GaN High Electron Mobility Transistor (GaN HEMT) pelas suas caracteŕısticas memristivas. Utilizando uma implementação do modelo f́ısico de SRH em Matlab e diversas medidas experimentais pulsadas I-V e resultados de excitação sinusoidal, nós demonstramos que o canal de um GaN HEMT afectado por traps de ńıveis profundos pode, de facto, apresentar as duas caracteŕısticas fundamentais do critério de memristividade: (i) Uma trajectória com histerese comprimida no espaço de fase iDS/vDS quando o dispositivo é excitado por um est́ımulo sinusoidal, e (ii) uma histerese cuja área é monotónica e desvanece para frequências cada vez maiores.
The Influence of Prevention- versus Promotion-Focused Brand Slogans on Consumer Motivated Choices and Behaviors

Across four studies, I show that slogans that focus on the self-concept seem to produce predominantly negative effects on consumer motivated behavior, and this is especially true for prevention (versus promotion) slogans. In my studies, prevention slogans focused on the feared self, promotion slogans focused on the ideal self, and control slogans did not refer to the self-concept. I found reliable negative effects of prevention slogans within the financial (study 1A) and beauty goal domains (study 1B). I also provide evidence that the demotivating effects of prevention-focused slogans are at least partially attributed to consumer defensiveness. Past research suggests that people are more likely to experience anxiety after exposure to a feared, rather than ideal self. In the present research, I extend this finding by showing that prevention-focused slogans (i.e. focus on feared self) encouraged defensive coping, instead of directly addressing the source of the threat. Specifically, exposure to prevention slogans generated a higher likelihood to engage in fluid compensation, a tendency to redirect attention to an unrelated goal and engage in behaviors aligned with this alternate goal (study 3). Conversely, the motivational effects of promotion-focused slogans (i.e. focus on ideal self) demonstrated a more positive, but more subtle pattern of direct coping. Promotion slogans only motivated goal-congruent behaviors among people with high self-consciousness (study 2).