Miracle-dz/UniFAR-FTUs huggingface dataset:
The management of mycetoma.

Mycetoma is a chronic specific granulomatous subcutaneous inflammatory disease. It is caused by true fungi or by bacteria, and hence it is usually classified as eumycetoma and actinomycetoma, respectively. It is a serious health problem in many tropical and subtropical areas, and has many medical, social and economical impacts. The treatment of mycetoma depends mainly on its etiological agent and the extent of the disease. Actinomycetoma is amenable to medical treatment by antibiotics and antimicrobial agents, while the medical treatment of eumycetoma by various antifungals is inadequate and disappointing. Combined medical and surgical treatment is the gold standard in eumycetoma. In general, the current treatment for mycetoma is unsatisfactory, it needs a long duration to affect cure, has many side effects, has a high relapse rate and is expensive for patients and health authorities. Controlled clinical trials for novel antibiotics and antifungals are needed for the management of mycetoma patients.
Credit card fraud detection by dynamic incremental semi-supervised fuzzy clustering

The problem of credit card fraud detection is approached by a semi-supervised classification task on a data stream. The DISSFCM algorithm is applied, which is based on Dynamic Incremental Semi-Supervised Fuzzy C-Means that processes data grouped in small-size chunks. Experimental results on a real-world dataset of credit card transactions show that DISSFCM has comparable results with some fully-supervised stream data classification methods, also in presence of a high percentage of unlabeled data.
A Convolutional Neural Network with Non-Local Module for Speech Enhancement

Convolution neural networks (CNNs) are achieving increasing attention for the speech enhancement task recently. However, the convolutional operations only process a local neighborhood (several nearest neighboring neurons) at a time across either space or time direction. The long-range dependencies can only be captured when the convolutional operations are applied recursively, but the problems of computationally inefficient and optimization difficulties are introduced. Inspired by the recent impressive performance of the non-local module in many computer vision tasks, we propose a convolutional neural network with non-local module for speech enhancement in this paper. The non-local operations are capable of capturing the global information in the frequency domain through passing information between distant time-frequency units. The non-local operations are able to set the dimension of the input as an arbitrary value, which results in the easy integration with our proposed network framework. Experimental results demonstrate that the proposed method not only improves the computational efficiency significantly but also outperforms the competing methods in terms of objective speech intelligibility and quality metrics.
Improving existing VPN through Software Deﬁned Networking

This is to certify that the thesis prepared by Goytom Mebratu , entitled Improving existing VPN through Software Deﬁned Networking and submitted in partial fulﬁllment of the requirements for the degree of Master of Science Telecommunication Engineering complies with the regulations of the University and meets the accepted standards with respect to originality and quality.
Level of driver involvement in trucks human-machine interfaces design : effects on usability, distraction and acceptance

The design process of trucks human-machine interfaces has been adapted to address human factors and road safety issues. It is now widely accepted that user involvement in the design process is valuable. Currently in industry, users are mainly involved in the stages of analysis and evaluation of concepts, the latter being defined by professionals. However, the literature in other fields reports benefits of a broader form of user involvement: participatory design. In this design process, users are involved all along products development, and particularly during concepts design. Participatory design would allow better access to users' needs, expectations, and tacit knowledge. The objective of this project is to study how the level of drivers’ involvement in the design process impacts the usability, distraction and acceptance of trucks human-machine interfaces. After a preliminary analysis of the context of use, three instrument cluster design processes were conducted in parallel using a tactile equipment. The outcomes of these three processes, differing in level of user involvement, were evaluated and compared in a driving simulator experiment. The results do not enable to demonstrate that participatory design has a significant impact on usability, distraction and acceptance. This thesis concludes with recommendations to practitioners and research perspectives.
Dynamic Relationship Between Imports and Economic Growth in Pakistan

This research paper examines the causal relationship between imports and economic growth along with the impact of economic growth on imports in the perspective of Pakistan using the Granger causality test and simple regression test. The research aims to evaluate the relationship between the respective variables by using the data for a period of 40 years from 1975 to 2014. The result revealed that there is a causal relationship between imports and economic growth and found the evidence of bi-directional causality between imports and economic growth in Pakistan. Similarly, the result showed that there is a significant causal relationship between economic growth and imports in Pakistan. On the basis of Granger’s causality test, the positive and significant relationship between the respective variables reflects that imports of capital goods such as machinery group, chemicals, equipment, etc. translate in to the economic productivity and growth along with the imports of consumer goods that also contributes towards the export oriented productivity indirectly. For further research, the right mix of the categories and products should be examined to accelerate the pace of economic growth through imports in Pakistan. Keywords: Import, Economic Growth, Granger Causality, Bi-directional, Causal Relationship DOI : 10.7176/JESD/10-10-08 Publication date :May 31 st 2019
80/20 Rule partially explains 7+/-2 law: general system-based analysis

The 80/20 rule and the 7 ± 2 law are examples of difficult to explain empirical facts. According to the 80/20 rule, in each activity, 20% of the people contribute to the 80% of the results. The 7± 2 law means that we divide objects into 7 ± 2 groups – i.e., into 5 to 9 groups. In this paper, we show that there is a relation between these two facts: namely, we show that, because of the 80/20 rule, the number of classes cannot be smaller than 5. Thus, the 80/20 rule explains the lower bound (5) on the 7 ± 2 law. 1 Formulation of the Problem Difficult-to-explain empirical facts. There are several difficult-to-explain empirical facts. • For example, there is a ubiquitous 80/20 rule, according to which, in each human activity, 80% of the results come from 20% of the participants. For example, 20% of the people own 80% of all the wealth, 20% of researchers publish 80% of all the papers, etc.; see, e.g., [1, 2] and references therein. • There is a known phenomenon in psychology called a 7 ± 2 law (see, e.g., [4, 5]), according to which each person usually classifies everything into a certain number of classes C; depending on the person, this number ranges from 7 − 2 = 5 to 7 + 2 = 9 classes.
Multi-Resolution Face Recognition : The Behaviors of Local Binary Pattern at Different Frequency Bands

This paper presents an analysis of the recognition performance of LBP at different frequency bands to exploit their discriminative information. The work presented in this paper is part of an investigation about which aspects of a face contribute to automated face recognition. Multi-resolution analysis, by means of wavelet transform, is commonly used to explore the features of an image. The each step of wavelet transform decomposes an image recursively into four frequency bands: approximation, horizontal, vertical, and diagonal band. The approximation band is a down sampled version of the original image. Whereas, the other bands are detail bands that contain detail information of the image in horizontal, vertical, and diagonal directions. The noise is more dominant in these bands. The information contained in the detail bands is more related to high frequency-components and local structures such as edges. In order to analyze the impact of the various bands, we performed classiﬁcation experiments on them. For the A-bands, that contain the global information of the facial image, we used PCA/LDA classiﬁers. For the detail bands, that contain local structures, we used LBP.
Reliability Assessment of Distribution Network and Electric Vehicle Considering Quasi-Dynamic Traffic Flow and Vehicle-to-Grid

With the increasing number of electric vehicles and the emergence of vehicle-to-grid technology, electric vehicles have become distributed loads and power sources with random movement characteristics in the distribution network. In order to evaluate the reliability of the distribution network incorporating electric vehicles, firstly, this paper uses the trip chain theory to describe the travel of electric vehicles. Based on the static traffic flow distribution, a high efficiency quasi-dynamic travel simulation method is proposed to consider the influence of traffic congestion on the path selection. Then, the simulation time advancement of the Monte Carlo method is improved, which makes the reliability assessment of the distribution network containing a large amount of electric vehicles’ charging and discharging behaviors realizable. Finally, the practicality of the method is verified by the modified IEEE-RBTS Bus-6 test system. The effects of electric vehicles penetration, discharging threshold, and battery capacity on reliability of both distribution networks and electric vehicles are studied.
The labour supply of native and immigrant mothers in Norway

This paper investigates the determinants of the labour supply of first-time mothers in Norway. By considering three groups of women—native Norwegian women, women who migrated from OECD countries and Asian-African women—we study the variation in their labour supply. Given that the women were working before childbirth, we do not find significant differences in the labour supply of the three groups of women. Our results illustrate that after the birth of a child, university education increases the probability of career continuity for natives, as well as for the two groups of immigrants, although women who remain attached to the labour market earn a lower income after childbirth. However, the negative effect of childbirth on earned income for career-oriented women has no association with the level of their education. Our results indicate a negative change in earned income for lower- as well as higher-educated native and immigrant women given that they stay in the labour market after childbirth. We also study the probability of entering the labour force after childbirth for women who were not working before childbirth. Here we find that immigrant women from Asia and Africa behave differently compared with natives and OECD immigrants. Our results illustrate that higher-educated native as well as immigrant mothers from OECD countries tend to enter the labour market within two years after childbirth even though they were previously not working. On the other hand, in labour market entry for Asian-African immigrants, it is the husbands’ income that plays a significant role and has a negative effect on their labour supply.
Nursing care in pediatric respiratory disease

Contributors ix Preface xiii Acknowledgments xv Reviewers xvi 1 Pediatric pulmonary anatomy and physiology 3 Neal Nakra, MD, FAAP, FCCP 2 Pediatric respiratory health history and physical assessment 38 Concettina Tolomeo, DNP, APRN, FNP-BC, AE-C 3 Principles of lung therapeutics 51 Kathryn Blake, PharmD, BCPS, FCCP 4 Neonatal lung disease: Apnea of prematurity and bronchopulmonary dysplasia 85 Pnina Weiss, MD, and Concettina Tolomeo, DNP, APRN, FNP-BC, AE-C 5 Lower airway disease 110 Julie Honey, MSN, CPNP, and Michael Bye, MD, FAAP, FCCP 6 Upper airway disorders 132 Wendy S. L. Mackey, MSN, APRN-BC, CORLN, Melissa M. Dziedzic, MSN, CPNP, CORLN, and Lisa M. Gagnon, MSN, CPNP 7 Asthma 188 Concettina Tolomeo, DNP, APRN, FNP-BC, AE-C, Dawn Baker, MSN, CPNP, CCRC, and Pnina Weiss, MD 8 Cystic fi brosis 221 Antoinette Gardner, RN, MEd, CCRC, AE-C, and Kimberly Jones, MD 9 Obstructive sleep apnea 247 Linda Niemiec, MSN, RN, CPNP, and Lewis J. Kass, MD 10 Primary ciliary dyskinesia and bronchiectasis 269 Rosalynn Bravo-Cavoli, BS, MS, APRN, CPNP, AE-C, and Anita Bhandari, MD 11 Acute respiratory problems 286 Marcia Winston, MSN, CPNP, AE-C, and Catherine Kier, MD Index 314
Expressive Wearables: Practices-Oriented Codesign for New Forms of Social Mobile Technology

Self-expression is a vital practice for a functioning social life. Wearables have become expressive everyday products, while studies showed how physical collocation can be an opportunity for social technology. This article identifies a perspective for future design of wearables as an extension of the body in its social context: designing for diversity in expression with respect to social boundaries. The collected literature demonstrates the development of new forms of expressive wearables that challenges norms of dress and three groups of participatory methods enable re-search into everyday life practices. The two initial studies—inquiring into everyday life and exploring the wearable design for new practices—exemplify these methods and point a way forward with a focus for design on distinct practices of self-expression.
THE CLINICO-GENETIC STUDY OF SCHIZOPHRENIA

Although progress has been realized in some areas of psychiatric geneticsin the study of mental deficiency, in particularsome investigators think that the genetic study of schizophrenia has reached its limit inasmuch as a pathognomony peculiar to this disorder has not yet been found. They believe that further development awaits elucidation of the biochemical aspects of schizophrenia. I am not opposed to this view. However, it should be noted that many of the pessimists, though brilliant in human genetics, are not directly engaged in the practice of clinical psychiatry. For the clinical psychiatrist there are still many problems that require the aid of genetic research, even though the pathogenesis of schizophrenia is still not completely known. Continuing study of schizophrenia from the aspect of clinical genetics is therefore warranted.
Openness and Growth

The policy by China and India to open their markets to international trade has been touted as the reason for their phenomenal growth. This paper investigates the impact of opening up the China and Indian economy on economic growth in these countries using new panel data sets for both the national economies and the regional economies of China. The policy change to a more liberalized economy is explicitly identified using instrumental variables. The results provide support that export growth does have a positive and statistically significant effect on economic growth in these countries. However, the growth rates of these countries are export and FDI inelastic, in the sense that a one percentage point increase in growth rate of export or FDI will have a less than one percentage point increase in economic growth rate of these countries. In the case of the Chinese regions, the presence of export processing zones may exert positive effect on the regional growth rate but the increase in regional growth is even more export inelastic than at the national level. The results dispel the popular view that adopting a policy of more openness in the economy has a “multiplier” effect on economic growth. Of the two phases of liberalization in both countries, the second stage is statistically significant. One possible reason is that the scale of liberalization is greater in the second phase. Additionally, increasing the number of SEZs has very negligible effect on economic growth. Taken together, these results suggest that what contributes to greater growth is a greater scale of liberalization, rather than increasing the number of SEZs. The author is grateful to Yothin Jinjarak and Jinyu for their suggestions, particularly on the sources of the data. He would also like to thank seminar participants at Nanyang Technological University for their comments and suggestions. The usual caveat applies.
Data Mining for Description and Prediction of Antibiotic Treated Healthcare-Associated Infections

Healthcare-associated infections is the most common healthcare related injury and affect almost every tenth patient. With the purpose of reducing these infections Infektionsverktyget, The Anti-Infection Tool, was developed for registration and feedback of infection data. The tool is now used in all Swedish county councils resulting in a wealth of data. The purpose of this thesis was thus to investigate how data mining can be applied to describe patterns in this data and predict patient outcomes regarding healthcare-associated infections that need to be treated with antibiotics.Data mining was performed with Microsoft SQL Server 2008 in which models based on six different data mining algorithms with different parameter settings were developed. They used the attributes gender, age and previous diagnoses and medical actions as inputs and antibiotic treated healthcare-associated infection outcome as output. The predictive performance of the models was evaluated using 5-fold cross validation and macro averaged measures of recall, precision and F-measure. Patterns generated by selected models were extracted.Models based on the Naive Bayes algorithm showed the highest predictive capabilities with respect to recall and models based on the Decision Trees algorithm with low pruning had the highest precision. Although, none were considered to perform sufficiently well and several areas of improvement were identified. The most important factor in the inadequate performance is believed to be the relatively rare occurrences of infections in the dataset. Extracted patterns based on the Association Rules algorithm were considered the easiest to interpret. Patterns included clinically valid and invalid as well as trivial relationships.Future studies should be focused on further model improvements and gathering of more patient data. The idea is that data mining in Infektionsverktyget in the future could be used both to provide ideas for further medical research and to identify risk patients and prevent healthcare-associated infections in daily clinical work.
Multi-Relay Non-Orthogonal Multiple Access Network With Cache-Enabled Users

This paper investigates the multi-relay non-orthogonal multiple access (NOMA) networks with cache-enabled users, in which the source transmits superimposed signals to two users, assisted by <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> relays. We firstly analyze traditional cooperative-NOMA networks, and then discuss the cooperative-NOMA networks with cache-enabled users. Moreover, the analytical expression of outage probability for the proposed network is derived, as well as the asymptotic expression. According to the asymptotic outage probability, we obtain that the diversity order is equal to the amount of relays <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>. Furthermore, increasing the file hit probability can enhance the transmission performance of the system. Finally, numerical as well as simulation results are presented to validate our analysis.
Multi-actor modelling for MILP energy systems optimisation: application to collective self-consumption

The shape of an energy project depends on the available technologies but also on stakeholders’ decisions although most energy-support-decision tools only focus on technical issues. This article aims to propose a multi-actor modelling based on stakeholders’ objectives and constraints and to apply it on the optimisation model generation tool OMEGAlpes. This modelling aims to help stakeholders to formalise their constraints and objectives and to negotiate them in a multi- stakeholders design process. Two types of stakeholders involved in urban renewable energy project have been highlighted: operators and infrastructure regulators. This modelling has been applied to a simplified collective selfconsumption project.
DNA recovery from handwritten documents using a novel vacuum technique

Investigations of many crimes such as robberies, kidnappings, and terrorism are often associated with the recovery of a paper document which has been written by the perpetrator. Paper can provide a variety of forensic evidence such as DNA, latent fingermarks, and indented writing. The focus of this study was the collection of probative DNA profiles from the text region of a handwritten note through a vacuum suction device without altering or destroying the document. Collection of DNA evidence was carried out in two separate groups. The first group involved 11 volunteers providing a handwritten note sample with unwashed hands. The second group of DNA collection involved six volunteers providing handwritten notes before and immediately after a period of mild aerobic activity. After the collection of DNA evidence, 10 volunteers provided sebaceous and eccrine latent fingermarks placed onto separate paper documents and developed with magnetic fingerprint developer or 1,2 indanedione to observe any effects of the vacuum swabbing technique. A final step to the study was performed to observe the effects of the vacuum swab technique on indented writing which may be developed using Electrostatic Detection Apparatus (ESDA). Ten simulated robbery notes were impressed with overlay sheets and processed with the vacuum swab before being developed using the ESDA process. Approximately 80% of processed DNA samples produced potentially probative profiles. Quantities of recovered DNA in the single collection series ranged from 0.6-54.3 pg/μL. DNA quantities in the active series prior to the aerobic activity ranged from 3.1-55.8 pg/μL. DNA quantities in the active series post-activity ranged from 1.9 to 221.6 pg/μL. The vacuum swab technique did not destroy nor alter any of the observed fingermarks. Additionally, the vacuum swab technique did not interfere with any indented writing as observed through ESDA.
Women Leaders in National Politics

In recent years the number of women executives has increased globally, and academic focus on these actors has grown accordingly. While some of the earliest research offered descriptive analyses of women leaders, concentrating particularly on their career preparation or political inspirations, this has given way to more systematic assessments of topics including paths, powers, and impacts. Global methodical studies have been supplemented by similarly rigorous country case studies and regional analyses. These works offer quantitative examinations, rich qualitative investigations, and often a combination. Consequently, factors facilitating women’s rise to power and authorities exercised in their capacities as presidents and prime ministers are illuminated. Much more research, however, must be conducted to evaluate the myriad effects women in power exert on societies.