Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between Medication Adherence, Self-consciousness, and Asthma Control and Severity among Patients with Asthma

controlling asthma severity and exacerbations among patients with asthma is very important. Adherence to therapy and self-consciousness factors could be responsible for this issue. Suboptimal adherence to asthma therapy is a major contributor to poor asthma outcomes. Self-conscious emotions can also prevent healing from traumatic events. People may delay or avoid medical care if they feel certain self-conscious emotions. Aim of the study: to determine the relationship between medication adherence, self-consciousness, and asthma control and severity among patients with asthma. Design: A descriptive correlational design was utilized. Setting: Outpatient Clinic of Chest Diseases, Main University Hospital, Alexandria, Egypt. Subjects: These comprised 90 patients with asthma attending the pre-mentioned health setting. Tools: Socio demographic characteristics and clinical data structured interview schedule, Modified Morisky Medication Adherence Scale, Assessment of Asthma Control and Severity scale, The Self-consciousness Scale. Results: 37.8% of the studied patients were medium adherents, while one third were low adherents, the majority of the studied patients had not controlled asthma, while the rest had a reasonably controlled asthma, the majority of patients had medium and simple continuous degrees of asthma severity, and they had low levels of self-consciousness as well as low levels of its subscales, there is no statistically significant relationship between degree of asthma severity and level of medication adherence; as well as between level of medication adherence and level of asthma control. There is a statistically significant negative relationship between degree of asthma severity and level of asthma control; as well as between degree of asthma severity and level of self-consciousness among patients with asthma. Conclusion: patients with asthma are medium and low adherents to medication, their asthma is not controlled and they had medium and simple degrees of asthma severity. Regardless of their illness, they had low levels of self-consciousness; as well as its subscales. High levels of asthma control and self-consciousness result in decrease severity of asthma. Patients having an increase in selfconsciousness have increase degrees of medication adherence as well as asthma control. Recommendations: Developing educational programs to promote medication adherence and self-management among patients with asthma, developing psycho-educational intervention programs that scope and address self-conscious emotions and investigate their effects on medication adherence among patients with asthma in Egypt, nurses and other health care professionals should make great emphasis on psychological, as well as physical aspects of patients with asthma as important factors that enhance medication adherence.
Quality Assessment of Cookies Produced from Composite Flour of Wheat, unripe Plantain and Moringa Leaf

The composite flour produced from blends of wheat, unripe plantain and moringa leaf were processed into cookies in the following ratios:100:0:0,50:45:5,35:55:10 and 45:50:5 respectively designated as W, WP45M, WP55M and WP50M. The chemical composition and sensory properties of cookies samples from the blends were determined. The cookies produced from the resultant blends were significantly (p<0.05) higher in protein (12.26%), ash (3.00%) and fibre (3.30%) than the control in protein (10.29%), ash (2.00%) and fibre (0.50%). Carbohydrate contents decreased with the addition of unripe plantain and moringa leaf. The cookies prepared using 35:55:10 blends had the higher vitamin A (6.90mg|100g) and vitamin C (7.89mg/100g) compared with the control. The sensory acceptability score showed the most accepted substitution level for making cookies was sample WP50M (45% wheat,50% unripe plantain and 5% moringa leaf). The study revealed importance of promoting the processing and utilization of lesser known local crops in baked product enrichment.
Reactive Power and Voltage Control of Nigerian Grid System Based on Artificial Bee Colony Algorithm

: Reactive power and voltage control in electrical power system leads to simultaneous minimization of the real power losses and enhancement of voltage profiles at affected customers’ buses. To achieve these goals available generating units’ excitation systems, discrete tap positions of on-load tap changer of transformers are adjusted as well as switching of discrete doses of inductors and capacitors etc. at load buses. This is mixed integer non-linear optimization problem with the existence of multiple optimum solutions. Thus, there is a need to develop intelligent technology to achieve the global optimum solution. This paper presents the application of Artificial Bee Colony (ABC) Algorithm to solve the optimization problem using the above-mentioned control devices. The effectiveness of the developed algorithm has been demonstrated on standard IEEE 30 bus network and real 54-bus Nigeria 330kV grid system modelled in MATPOWER under three different loading scenarios. Simulation results on IEEE 30 bus revealed that the algorithm was able to achieve real power loss reduction of 0.9646%, 0.6384% and 6.01% while for 54-bus Nigeria 330kV grid system real power loss reduction of 9.497%, 7.45% and 10.12% was procured for 80%, 100% and 120% loading conditions respectively. For both system studies, the algorithm was able to eliminate the voltage limits violations. The approach was able to procure significant power loss reduction and eliminate the voltage limits violations by restoring them within limits. This thus leads to reduction in the cost of energy to the consumers and voltage profiles enhancement; hence improvement in the network power quality and voltage stability.
Computer guided Inferior Alveolar Nerve Block by a modified customized 3D-printed surgical guide: A proof of Concept

Background: Inferior alveolar nerve block (IANB) is essential for many surgical and endodontic procedures. It requires accurate needle placement due to its high failure rate. Purpose: The article was undertaken to assess the location of the targeted mandibular foramen and to present a proof of concept (PoC) of a novel customized modified surgical guide for blocking the inferior alveolar nerve. Materials and Methods: The location of this foramen was determined in 360 mandibular rami in 180 cone-beam computed tomography scans of the mandible from the premolar region of the opposite side. A novel customized 3D-printed implant surgical guide was modified after determining the suitable IANB needle direction on 3D images generated from digital dental model images and cone-beam computed tomography (CBCT) scans for 8 lower posterior implant cases. Results: The distance from the IANB targeted foramen to the premolar region of the opposite side could be measured in all CBCT scans and showed many variations. The CBCT-based analysis of the mandibular foramen location could be fused with digital dental images for the modification of the new device for IANB. The concept of determining the path of needle insertion for the design and fabrication of a modified 3D-printed surgical guide for IANB was found to be feasible. Conclusions: The location of the mandibular foramen could be determined in CBCT scans with its variations. A proof of concept (PoC) of a new customized device for IANB computer guided accurate needle penetration could be presented. The new modified 3D-printed guide may offer the advantages of more accurate IANB injection with an exact three-dimensional determination of the path of needle insertion. [Hamdy A. M. Marzook, Abeer A. Elgendy, Fawzy A. Ali. Computer guided Inferior Alveolar Nerve Block by a modified customized 3D-printed surgical guide: A proof of Concept. J Am Sci 2020;16(9):104-111]. ISSN 15451003 (print); ISSN 2375-7264 (online). http://www.jofamericanscience. org. 10. doi:10.7537/marsjas160920.10.
Trading in Fragmented Markets

In this paper we study competition between the London Stock Exchange (LSE) and multilateral trading facilities (MTFs) under the Markets in Financial Instruments Directive (MiFID) in FTSE 100 constituents. We find that despite the lack of price protection investors often execute at the best available price. This indicates that price competition is important for investors and that most investors are monitoring multiple markets. In cases where participants do not execute at the best price, we find that liquidity is in general higher and that trades are more informative. When comparing the market quality across trading venues we find remarkable differences. The LSE posts better terms of trade and is in general more liquid than any MTF. However, our results show that Chi-X, an MTF, contributes more to quote-based information discovery than the LSE but that trades on the LSE carry more private information than on MTFs. This is consistent with the theory, presented in Chowdhry and Nanda (1991), that more informed investors gravitate to the market with the highest liquidity and confirms some concerns regarding ’cream-skimming’. Finally, we find despite a high level of market fragmentation that the market for FTSE 100 constituents is relatively efficient. Email addresses: Ryan.Riordan@kit.edu (Ryan Riordan), Andreas.Storkenmaier@kit.edu (Andreas Storkenmaier), Martin.Wagener@kit.edu (Martin Wagener), Christof.Weinhardt@kit.edu (Christof Weinhardt) Ryan Riordan is a post doctoral researcher at the School of Economics and Business Engineering at the Karlsruhe Institute of Technology, Germany. Andreas Storkenmaier is a Ph.D. student at the Graduate School Information and Market Engineering at the School of Economics and Business Engineering, Karlsruhe Institute of Technology, Germany funded by the Deutsche Forschungsgemeinschaft (German Research Foundation). Martin Wagener (corresponding author) is a Ph.D. student at the School of Economics and Business Engineering at the Karlsruhe Institute of Technology, Germany in co-operation with the Stuttgart Stock Exchange, Germany. Christof Weinhardt is a professor at the School of Economics and Business Engineering at the Karlsruhe Institute of Technology, Germany.
Journal of Applied Structural Equation Modeling RELATIVE IMPORTANCE OF WATER QUALITY PARAMETERS ON FISH GROWTH USING PLS REGRESSION

Partial least squares (PLS) is a multivariate dimension reduction technique which is not based on ordinary regression assumptions. The use of PLS regression in life sciences is still a novel concept despite having many scientific applications. This paper analyses the relative importance of physicochemical parameters on the growth of Oreochromis jipe using Oreochromis niloticus as a control. Modelling and the graphical display of the regression coefficients were performed using a suite of open access R-software packages. The modelling hypotheses were assessed using experimental data collected from 270 fingerlings cultured for the period of 84 days. The findings revealed that significant linear correlation exists between water quality variables and the mean body weight of both O. jipe and O. niloticus fish species. The study provides baseline information to assess the growth of O. jipe under aquaculture conditions; therefore, we recommend a further study to be conducted on several other predictor variables that can be measured under controlled aquaculture conditions.
Sequence Classification of Tweets with Transfer Learning via BERT in the Field of Disaster Management

Twitter is extensively used as an information-sharing platform during any kind of emergency like disasters etc. People tweet useful information about disaster-related events such as evacuations, volunteer need, help, warnings etc. This data is sometimes very useful for rescue teams, NGOs, military and various other government and private organisations who are tasked with responsibilities to save lives and provide volunteers. This data can also be used to analyze disaster behaviour. In this paper, we have collected labelled tweets from crisisLexT26 and crisisNLP and classiﬁed them into seven labels on the basis of information provided by them. The data was heavily skewed. So to improve the accuracy of classiﬁers, we have applied various techniques as a result of which we have created two datasets (Imbalanced and Balanced). We have compared the performance of various BERT-based models on these two datasets. For sequence classiﬁcation, a balanced dataset performs better than an imbalanced dataset. We can improve accuracy of classiﬁers to great extent by adopting good data preprocessing and data splitting techniques.
Simplified Laws of Similarity for Wind Turbine Rotors

Laws of similarity or scaling laws for the characteristics of a wind turbine rotor are of importance to the designer even during the initial design phase of a new wind turbine concept, but are still more so when the designer wants to make adjustments or modifications to a wind turbine, in order to improve the machine, optimize or adapt it to another wind climate than originally anticipated, or eventually redesign it by scaling up or down the rotor size. In the paper some esamples are shown to illustrate the principles, and equations for the laws of similarity are derived under simplified conditions such as neglecting the influence of the variation of the Reynolds Number. Some comments are presented on comparison of stall-and pitch-regulated wind turbines and on two speed operation. The optimization of a stall-regulated wind turbine to different wind climates by variation of the generator size is illustrated by examples. EDB descriptors: ADJUSTMENTS; DESIGN? DIMENSIONS; OPTIMIZATION; REYNOLDS NUMBER; ROTORS; WIND TURBINES. UDC 621.548 May 1984 Riso National Laboratory, DK-4000 Roskilde, Denmark ISBN 87-550-1007-5 ISSN 0418-6435 Riso Repro 1984 CONTENTS Page
Institutional Investor Type , Misvaluation , and Governance ∗

We find that ownership by different institutional investor types has distinct implications for future firm (mis-)valuation and governance characteristics, with firms held by dedicated institutions displaying more favorable characteristics and posting better long-term performance. Dedicated institutional investors decrease future firm misvaluation relative to fundamentals, as well as the magnitude of this misvaluation. Transient institutional investors have the opposite effect. Using Regulation FD as an exogenous shock to information dissemination, we find evidence that these effects are due to the advantage dedicated institutions have in firm-specific analysis. We use propensity score matching to rule out institutional selfselection into misvalued firms. A decomposition of investor types by portfolio turnover and diversification suggests the valuation effect primarily comes from the turnover dimension. These results implies a more nuanced relationship of institutional ownership with firm value and corporate governance.
Thiol‐modified gold‐coated glass as an efficient hydrophobic substrate for drop coating deposition Raman (DCDR) technique

In this paper we report an easy and low-cost way to prepare a hydrophobic substrate for drop coating deposition Raman (DCDR) spectroscopy. This substrate is formed by a thiol-modified Au-coated glass and provides the Raman spectra with the same quality as the commercial Teflon-coated stainless steel substrate (SpectRIM™, Tienta Sciences, Inc.) for model molecular systems – albumin solution and liposome suspension. Gold layer, similarly to polished steel in the commercial substrate, served as a highly refractive layer strongly increasing the Raman signal. The main advantage of introduced substrate is that it is simple and a low-cost preparation easily manageable in every standard laboratory. Thus, it represents a promising alternative to commercial Teflon-coated stainless steel substrate. Copyright © 2016 John Wiley & Sons, Ltd.
Design and Development of Audio Data Transmission Using Visible Light Communication

The developments of technology have opened up new infrastructure in communication for transmitting audio data. This is evidenced by a large number of communication media, both wired and wireless. Hence, it raises new methods for sending audio data, one of which is using Visible Light Communication (VLC). VLC is a communication system for transmitting and receiving data using the visible light wave spectrum between 375 nm 780 nm. In this research, audio data communication utilizes the brightness of the LED light. The transmitter and receiver use an LED component as a transducer which is then sent to the data processing circuit. The data processing circuit is then sent to the audio amplifier circuit. From the test results, it can be shown that this system can transmit audio data. Based on the LED color test, Green produces the highest output voltage of 1.32 Volt. The angle limit that can be detected by the photodiode is at an angle of 70° with a measured voltage of 100mV and the resulting sound intensity of -32.541dB
CAM-D: A Description Method for Multi-Cloud Marketplace Application

Multi-cloud Marketplace facilitates to create adiverse ecosystem for cloud software and cloud resourceservices provided by many stakeholders. To leverage theadvantage of multi-cloud environment, cloud application couldbe a composition of software components which are able tobe distributed across various cloud providers. So the cloudapplication is therefore a complex system. Consequently, animportant key problem remained in research is to definemulti-cloud application in a particular form and to constructhis description. In this paper, we particularly focus ondeveloping a description method that can be taken to tacklethe lack of description for multi-cloud application by designingdescription templates for CAM which was developed in[1][2][3], called CAM-D. A completed application descriptioncan be synthesized from individual component descriptions.Our experimentation is expressed through the transformationof CAM-D template to TOSCA specification illustrated by casestudy. In addition, we also develop an flattening algorithm toassist in mapping to TOSCA.
Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

Machine learning and deep learning algorithms are rapidly becoming integrated into everyday life. Whether it is in your face-ID to unlock your phone or the detection of deadly diseases like melanoma, neural networks have been traditionally designed to work in isolation to achieve amazing tasks once thought impossible by computers. However, these algorithms are trained to be able to solve extremely specific tasks. Models have to be rebuilt from scratch once the source and target domains change and the required task changes. Transfer learning is defined as a field that leverages learnings and weights from one task for related tasks. This process is quite smooth if one has enough data and the task is similar to the previous, already learnt task. However, research on when these two conditions are not met is scarce. The purpose of this research is to investigate how fine-tuning a pre-trained image classification model will affect accuracy for a binary image classification task. Image classification is widely used, and when only a small dataset is available, transfer learning becomes an important asset. Convolutional neural networks and the VGG-16 model trained on Imagenet will be used. Through this study, I am investigating whether there are specific trends in how fine-tuning affects accuracy when used for a small dataset which is dissimilar from Imagenet. This will allow for the beginning of investigating quantifiable methods to train a model when using Transfer Learning techniques.
Innovation Process Audit Model: A Case Study in an Electronics Company

Competitive advantage can be achieved through innovation. In order to ensure that the innovation process runs effectively, organization must conduct an audit. This research develops an innovation process audit model. The model is constructed by analyzing the impact of Technological Innovation Capabilities (TICs) on Technological Innovation Performances (TIPs). TICs are represented by eight independent variables which are Learning Capability, R&D Capability, Resource Allocation Capability, Manufacturing Capability, Marketing Capability, Organizational Capability, Strategic Planning Capability, and External Environment Capability. TIPs are represented by one dependent variable which is Product Performances. This innovation process audit model is validated using expert judgement in an electronics company then tested using forward stepwise regression. Based on the empirical testing, three TICs variables identified as the variables which influence TIPs. The three variables are Resource Allocation Capability, Manufacturing Capability, and External Environment Capability. The regression coefficient for the three variables are 0.765, 0.424, and 0.219 consecutively.
Manual of “The Robust LMI Parser” – Version 3.0

The ROLMIP (Robust LMI Parser), built to work under MATLAB jointly with YALMIP, is a toolbox aimed to ease the programming of Linear Matrix Inequality (LMI) relaxations for parameter-dependent LMIs with parameters lying in unit simplexes (or inside known intervals). Through simple commands, the user is able to deﬁne matrix polynomials, as well as to described the desired parameter-dependent LMI conditions in a easy way, considerably reducing the programming time. The main commands and deﬁnitions are thoroughly explained in this manual
An Enterprise Information System for retail companies’ internal inventory management

The last decade has witnessed a rapid development in Information Systems (IS), the application of information technologies in business processes. This project aims to develop an Enterprise Information System (EIS) which can improve retail companies’ daily activity coordination and inventory management. Transaction Processing Systems and Enterprise Applications will be constructed for data transfer between each branch and the central data warehouse of retail organizations. SQL, C++, HTML, and JavaScript codes will be used to implement the logic flow of sales record analysis and the login system. It is hoped that retail companies’ staff will find this system to be efficient and serviceable for checking stock levels and requesting product transfers.
Acid -Tolerant Rhizobia of Phaseolus vulgaris L. from the Intensively Cropped Soils of La Trinidad, Benguet, Philippines

The common bean (Phaseolus vulgaris L.) has long been intensively cultivated on the agricultural soils of La Trinidad, Benguet, Philippines. The soil of the site has become acidic (pH 5-6) because of chemical nitrogen fertilization at early stages of plant growth. The present study reports the diversity of rhizobia isolated from Benguet -Phaseolus and the selection of acid-tolerant strains that may have the potential for future inoculation trials. One hundred eighty nine (189) rhizobial strains were isolated from Phaseolus nodules and initially screened for acid tolerance in an unbuffered Glutamate Sucrose Minimal Medium (GSM) adjusted to pH 4.5. Further gnotobiotic evaluation of these strains based on symbiotic effectiveness and growth behavior at pH 4.5 yielded two most acid-tolerant strains (RG-136 and RG-137). Polyphasic characterization identified the most acid-tolerant strains as Rhizobium etli. 1Department of Biology, College of Science, University of the Philippines Baguio, Gov. Pack Road 2600, Baguio City, Philippines 2Institute of Biology, College of Science, University of the Philippines, Diliman, Quezon City 1101, Philippines