Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison and Improvement of Different Access Methods in Femtocell Networks

A variety of wide band wireless systems have been pushed towards their limits in order to meet growing interest for high data rate in wireless communications.In particular, the limit due to the spectrum scarcity forces communication systems to utilize the spectrum resource at maximum efficiency level. One of the methods that allow effective spectrum employing is to cover multiple systems over same spectrum source by allowing bearable interference to occur between them. Femtocells have been recently introduced as a remedy to spectrum scarcity and coverage problems in current cellular structures. Femtocells are personal use base stations and they share the spectrum in a way that they can coexist with the macrocell. This thesis provides a critical reviews of different access methods in femtocell networks and further introduces improvements related to these access methods. Simulation results validate capacity improvement of proposed techniques compared to the existing access methods.
Subject- and behavior-specific signatures extracted from fMRI data using whole-brain effective connectivity

The idea of fMRI-based personalized medicine is emerging to characterize brain disorders at the patient level and to develop tailored therapeutic protocols. A main limitation in this direction, as well as with fundamental studies of brain function, is the variability observed in fMRI data. In practice, such measurements exhibit a mixture of session-to-session variability with subject- and condition-related information. Disentangling these contributions is crucial for real-life applications where only a few sessions per subject are available. The present study aims to define a new reliable standard for the extraction of signatures from fMRI data. These signatures correspond to subnetworks of directed interactions between brain regions (typically 100 covering the whole brain) supporting the subject and condition identification for single fMRI sessions. The key is to step from functional connectivity to effective connectivity, which is estimated using a whole-brain dynamic model. Our method shows that as few as 4 sessions per subject are sufficient to perfectly identify more than 40 other sessions of 6 subjects. We also demonstrate the good generalization capability for 30 subjects. Using another dataset with resting state and movie viewing, we show that the two extracted signatures correspond to distinct subnetworks, suggesting some sort of orthogonality. Our results set solid foundations to follow longitudinally a subject’s condition from fMRI data.
Child health problems in Ethiopia

1. Global situation or child health The world population is growing at an alarming rate and particularly so in the developing nations. Over 80% of the world's children live in the developing world (1) where child mortality and morbidity rates are the highest. Each year about 14 million under-five children die from malnutrition and infection, i.e. , 40,000 daily or 2000 per hour, of which 98 % occur in the developing countries (1). The main causes of mortality in these countries are diarrhoeal diseases, pneumonia, perinatal and neonatal problems, measles, neonatal tetanus and malaria (Table 1), over 60% of which are preventable at low cost in these countries (2). In 1980, an estimated five million children under 5 years of age, died as a consequence of diarrhoeal disease (3). After the introduction of ORT, a quarter-century ago, over one million young lives are now being saved a year . Still over two million under-five children in the world's poorest neighborhoods die necessarily every year of diarrhoeal diseases (4) . Acute respiratory infections (ARI) are also major causes of mortality among children in developing countries accounting for over four million deaths per year (4). In 1980 dlere were 2.5 million dead1s due to measles but now this is reduced to just over one million a year; and the non-fatal cases have also been reduced. Over the same
The Impact of the Retirement Slowdown on the U.S. Youth Labor Market

Employment among older Americans has sharply risen since the mid-1990s, particularly in high-skill jobs. How has this labor-supply increase affected other participants in the labor market, and new entrants in particular? Exploiting cross-commuting zone differences in age composition among the old driven in large part by historical birth patterns, this paper explores the impact of retirement trends on youth employment outcomes between 1980 and 2017. I find that in commuting zones where fewer older workers retire due to the initial age structure, the share of younger workers in high-skill jobs declines while the share of younger workers in low-skill jobs rises. Fewer retirements also lead to a rise in the share of younger workers who have higher educational attainment than their job typically requires, declining youth wages, and lower job mobility. Together, the results suggest that the retirement slowdown has contributed to stagnant early career outcomes in recent decades, explaining 30 percent of the rise in the share of younger workers in low-skill jobs between 1980 and 2017. JEL: J11, J21, J24, J26 ∗I thank Martha Bailey, Matthias Doepke, Jon Guryan, Lee Lockwood and Matt Notowidigdo for their guidance throughout this project. For helpful comments and discussions, I thank Lori Beaman, Dan Fetter, Ben Friedrich, Sasha Indarte, Seema Jayachandran, Cynthia Kinnan, Shariq Mohammed, Mel Stephens, as well as seminar participants at the Federal Reserve Bank of Dallas, NBER Labor Studies Fall Meeting, NBER Summer Institute, Northwestern University, Stockholm University, University of Michigan, and Washington University in St. Louis. I gratefully acknowledge financial support from the Alfred P. Sloan Foundation Pre-Doctoral Fellowship on the Economics of an Aging Workforce, awarded through the NBER. †Population Studies Center, University of Michigan, 426 Thompson St, Ann Arbor, MI 48106 (email: mohnen@umich.edu).
The importance of monitoring nurses' workplace satisfaction of nurses for the well-being of all employees in nursing

Introduction: Work is an important constituent of an individual’s life since the experience of work influences well-being and health. The well-being of employees is an important issue in the work environment. The aim was to examine the relationship between satisfaction in the workplace and the well-being of employees in nursing. Methods: Quantitative research based on a cross-sectional study was used, with 640 employees in nursing from eight Slovenian hospitals participating in the study. A structured survey questionnaire was administered. The relationship between psychological well-being and workplace satisfaction was analysed with correlation and linear regression analysis. Results: The workplace satisfaction (x = 3.69, s = 1.13) and well-being ( x=161.27, s = 55.19) of employees in nursing are at a middle level. With the correlation analysis we established that well-being statistically significantly correlates with workplace satisfaction (r = 0.611, p < 0.001). Workplace satisfaction explains 42 % of the total variability of well-being of employees in nursing. Discussion and conclusion: It is necessary for every health care organization to take care of its employees' workplace satisfaction and well-being. Health care organizations can be successful and achieve their organisational objectives if their employees are satisfied with their work and have a high level of well-being.
Assessment of Myocardial Viability After Acute ST- Elevated Myocardial Infarction Using Stress Speckle Tracking Echocardiography and Cardiac MRI

Background: Speckle-tracking echocardiography has emerged as a unique technique for accurately evaluating myocardial function by analyzing the motion of speckles identified. Speckle-tracking measured under stress may offer an opportunity to improve the detection of dynamic regional abnormalities and myocardial viability. Objective: The aim of the current study was to evaluate stress speckle tracking to detect myocardial viability in comparison to cardiac MRI in post-STEMI patients. Patients and methods: 74 patients were prospectively enrolled in 18-month’s study. Dobutamine stress echocardiography was performed 4 days post-infarction accompanied with automated functional imaging analysis of left ventricle during rest and then during low dose stress. All patients underwent a follow up stress echocardiography at 3 months with speckle tracking analysis. Cardiac MRI took place concomitantly at 4 days post-infarction and 3 months. Results: Investigating strain rate obtained with stress speckle tracking after revascularization predicted the extent of myocardial scar, determined by contrast-enhanced magnetic resonance imaging. A good correlation was found between the global strain and total infarct size (R 0.75, p< 0.001). Furthermore, a clear inverse relationship was found between the segmental strain and the transmural extent of infarction in each segment. Meanwhile it provided 81.82% sensitivity and 82.6% specificity to detect transmural from non-transmural infarction at a cut-off value of -10.15. Conclusion: Strain rate obtained from speckle tracking during stress is a novel method of detecting myocardial viability after STEMI. Moreover, it carries a promising role in post-myocardial infarction risk stratification with a reasonable prediction of reversible cardiac-related hospital re-admission.
Alzheimer’s Disease and Habitual Exercise: Relationship Mediated and Fostered by Vascular Risk Profiles?

Alzheimer’s disease, the most frequent form of dementia that accounts for 50-70% of all cases, impairs memory and learning, precludes independent living, and poses psychological and financial strain on caregivers and the healthcare system. Since the first discovery from a patient of Alois Alzheimerin 1906, a century of vigorous research has established key pathological features, including the conspicuous neuro degeneration that preferentially target shippo campus and the deposition of cerebral amyloid plaques and neurofibrillary tangles. However, there have been no established strategies to treat Alzheimer’s disease, and the currently-identified risk factors for Alzheimer’s disease (i.e., aging and ApoE? 4 allele) are non-modifiable. As a large number of baby boomers will be facing elevated risks of developing Alzheimer’s disease in the near future, there is an ever increasing need to search for modifiable risk factors and to identify intervention strategies to attenuate and prevent the disease development.
Factors Associated with School Burnout in High School Students of South Punjab, Pakistan

The present study aimed to investigate the factors associated with school burn out among high school students in South Punjab. It was hypothesized that high achievement goals and achievement emotions negatively affect the school burnout among students. Data was collected from different high schools situated in Multan, Muzaffargarh, Bahawalpur and Rahim Yar Khan in South Punjab. The sample was consisted of 813 students from which 387 were females and 426 were males. The age range of participants was 14 to 16, with a mean age of 15.5 ± 0.85. The Achievement Goal Questionnaire, Achievement emotions Questionnaire (AEQ) and The Maslach Burnout Inventory–Student Survey were used as the data collection tools. Findings indicated that the investigated variables (i.e., students’ levels of school burnout, achievement goals, and achievement emotions) displayed the expected correlation patterns, with a negative association between high achievement goals, high achievement emotions and school burnout. Furthermore, these correlation patterns were confirmed for both female and male students. Findings revealed that females are higher in the level of performance approach, mastery approach, performance avoidance, class related emotions, learning related emotions and test emotions as compared to males and males are higher in emotional exhaustion, cynicism, and academic efficiency. Findings also indicate that on the family side students from nuclear family systems have higher in performance approach, performance avoidance and class related emotions whereas students from joint family system were higher in emotional exhaustion, cynicism, and academic efficiency. On the public and private school comparison results revealed that students from public schools have higher level of performance approach, mastery approach, class related emotions, learning related emotions and test emotions as compared to students of private schools.
To Reduce the Effects of Experimental Aflatoxicosis in Broiler Chicks Using Specific Egg Yolk Immunoglobulin (IgY)

Background : This experiment was conducted to evaluate the effects of the specific egg yolk immunoglobulin (IgY) on reducing the defects of experimental aflatoxicosis in broilers. Materials and Methods : In a completely randomized design, a total of 128 Ross 308 broiler chicks were used in 4 treatments, 4 replicates and 8 observations (chicks) for 42 days. Treatments were: 1) control; 2) diet containing 1 ppm aflatoxin B1; 3) diet contaminated with 1 ppm aflatoxin B1 + 0.75 % of egg yolk containing IgY; 4) diet contaminated with 1 ppm aflatoxin B1 + 1.5 % of egg yolk containing IgY. Results : The results showed that the use of aflatoxin containing diet significantly increased the feed conversion ratio, serum cholesterol concentration, serum gamma-glutamyl transferase (GGT), and aspartate aminotransferase (AST). Also, experimental aflatoxicosis resulted in reduced feed intake, weight gain, serum total protein and albumin concentrations (p<0.05); as well as the liver histopathologic lesions. IgY containing egg yolk (0.75% and 1.5%) added to the contaminated ration improved feed intake, weight gain and feed conversion ratio compared to treatment 2 (p<0.05). Compared to treatment 2, serum cholesterol concentration decreased while total protein concentration increased in treatments 3 and 4 (p<0.05). Liver tissue was approximately normal with mild effects on hepatocytes and mild cytoplasmic changes in chicks receiving treatments 3 and 4. Conclusion : It can be concluded that specific IgY is effective in reducing the defects of experimental aflatoxicosis as well as improving performance in broilers.
Automatic segmentation of spinal cord diffusion MR Images for disease location finding

Dissemination weighted MR imaging may build the affectability and explicitness of MR imaging for certain pathologic states of the spinal rope yet is once in a while performed as a result of a few specialized issues. We consequently tried a novel stage explored turn reverberation dispersion weighted interleaved reverberation planar imaging arrangement in seven sound volunteers and six patients with intramedullary injuries. We performed dispersion weighted MR imaging of the spinal string with high spatial goals. Distinctive examples of dissemination irregularities saw in patient investigations bolster the conceivable symptomatic effect of dispersion weighted MR imaging for ailments of the spinal string. MR imaging has turned into the system of decision for imaging the spinal rope on account of a high affectability for pathologic intra medullary changes. In any case, the explicitness of anomalies oftentimes lingers behind when utilizing just regular MR arrangements. Dissemination weighted MR imaging guarantees to supply additional data in light of trademark changes of the clear dispersion coefficient, for example, those showed in intense ischemia, tumors, or sores related among numerous sclerosis. To date, the indicative commitment of dispersion weighted MR imaging has been concerted essentially in the cerebrum since dissemination weighted MR imaging of the spine is in detail every one the more requesting. Both the little size of the spinal rope and movement-initiated antiquities must be considered. We in this manner built up another examination strategy and tried its unwavering quality and potential for adding to the symptomatic workup of patients with spinal rope indications.
Retention in the First Programming Course: A Context Based Approach

Retention in the First Programming Course: A Context Based Approach Krishnendu Ghosh, Miami University Krishnendu Ghosh received his Ph.D. in Computer Science and Engineering in 2012 from University of Cincinnati and his masters degree in mathematics from University of Wisconsin-Milwaukee (2001). He is currently an Assistant Professor in the Computer and Information Technology Department at Miami University. His research interests include cyber security and formal verification. Michele D Dickey, Miami University Michele D. Dickey is a professor and program coordinator for the Instructional Design & Technology program in the Department of Educational Psychology at Miami University. Her research interests focus is on the intersection of technology and learning design. Prof. Laurena Werner, Miami University Laurena (a.k.a. Laurie) Werner is currently a retired and rehired Associate Professor in the Computer and Information Technology Department and an affiliate of the Computer Science and Software Engineering department at Miami University. She has been a member of the faculty since 1979. Her research interests are computer science pedagogy, and information assurance.
Federal Regulations and U.S. Energy Sector Output

A large body of literature finds that the energy sector is important to economic growth and development. The production of energy has negative environmental impacts, however, which has resulted in the sector being highly regulated. While several studies examine the effect of particular regulations on the energy sector, in this study we use the recently developed measure of regulation called RegData to estimate the impact of federal regulations on the energy sector. We employ a panel ARDL model to find an inverted Ushaped relationship between federal regulations and U.S. energy sector output. Federal regulations appear to increase energy sector outputs at low levels and then decline as regulations accumulate.
Contextual representation of documents, entities, and faces of people using a news corpus

A massive amount of unstructured data, in this information age, is composed of document collections. Examples include news articles, blog posts, scholarly publications, and reports generated by organizations as well as people. Many data mining and machine learning algorithms have been developed in the past decade to support text mining in many applications. Text mining applications cover a wide range of tasks spanning from personal information management — to organizational decision making, to disease control through epidemic prediction, and to intelligence analysis for national security. One bottleneck has been dominating data mining and machine learning theories for all these text mining applications — the quality of the outcomes of the algorithms depends on the quality of the representation of the documents. My research exploits imagery and textual content of documents to create high quality representations for documents, document tokens (e.g., names of people), and image snippets (e.g., faces of people in news images). My argument is that the utilization of both images and textual content of documents is crucial in generating a document representation because images within a document are included by the author(s) of the document to complement the textual content. In addition, visual objects found in the images of a document sometimes provide contextual information that might be missing in the textual content of the document. As an example, consider a document published this year that briefly describes a documentary that celebrates the life of Princess Diana. The textual content of the document does not contain the name Prince Charles or Queen Elizabeth. However, there is an image in the article that contains all three faces — Princess Diana, Prince Charles, and Queen Elizabeth — in the same photo. Inclusion of the image in the document representation will provide better features in this case because the image provides additional contextual information to enrich the content. My research focuses on incorporating such contextual information in representations in absence of annotated faces.
Aged streams: Time lags of nitrate, chloride and tritium assessed by Dynamic Groundwater Flow Tracking

<p>Groundwater connects the agricultural fields in a catchment with the drainage network and it therefore plays an important role in the pollution of surface waters. To study this transport mechanism, we derived dynamic groundwater travel time distributions from a distributed, transient 3D groundwater flow model using forward particle tracking. We then calculated in-stream concentrations by coupling the travel time distributions with input time-series of tritium and the agricultural tracers chloride and nitrate, representing the water quality of the groundwater recharge throughout the catchment. We tested this approach for a lowland stream in the Netherlands and found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained most of the long-term and seasonal variation in the measured stream nitrate concentrations. To study the observed lag in the breakthrough of agricultural solutes we performed a sensitivity analysis and found that the main contributors to such a time lag are the unsaturated zone, increased mean travel times and longer distances between agricultural fields and the drainage network. We found that the time between the application and effect of measures aimed to reduce in-stream concentrations depends on the combination of the input reduction rate and the mean travel time of the catchment. Furthermore, the location of agricultural fields in relation to the catchments&#8217; drainage network was found to be an important factor that largely governs the travel times of the agricultural pollutants. </p>
CLINICOHEMATOLOGICAL PROFILE OF ACUTE FEBRILE ILLNESS: EXPERIENCES IN A HOSPITAL CATERING TO SEMI-URBAN PEDIATRIC POPULATION OF DELHI

Rana Safia1, Mohd Tabish2, Jairajpuri S Zeeba3, Jetley Sujata4, Khetrapal Shaan1, Chandra Mohan Kumar5 From 1Assistant Professor, 3Associate Professor, 4Professor, Department of Pathology, 2MBBS Student, 5Professor, Department of Pediatrics, Hamdard Institute of Medical Sciences and Research, Jamia Hamdard, New Delhi, India Correspondence to: Dr. Zeeba S Jairajpuria, Department of Pathology, Hamdard Institute of Medical Sciences and Research, Jamia Hamdard, New Delhi 110 062, India. E-mail: jairajpurizs@gmail.com Received 10 July 2019 Initial Review 11 October 2019 Accepted 21 October
ANALYSIS OF THE CELL MEMBRANE FATTY ACIDS AND CHARACTERIZATION OF THE PSYCHROTOLERANT SERRATIA MARCESCENS HI6 ISOLATED FROM HOPAR (BUALTAR) GLACIER, PAKISTAN

In this study, the bacterial isolate HI6 was recovered from the ice of the Hopar (Bualtar) glacier, Karakoram Mountain Range, Pakistan. Isolate HI6 was identified as Serratia marcescens through microscopic and molecular analysis (16S rRNA sequencing). Serratia marcescens HI6 was analyzed for different physiological characteristics including temperature, pH and culture media. Serratia marcescens HI6 showed best growth at 25°C, on LB medium and pH 7. In addition, the Fatty acid methyl ester (FAME) was extracted and subjected to Fourier Transform infrared (FTIR) and Gas chromatography/mass spectroscopy (GC/MS) analysis. FTIR and GC/MS analysis has revealed that cell membrane of Serratia marcescens HI6 contains various types of fatty acids (FA). i–C16:1 (35.3% out of total cell membrane fatty acids) was found most predominantly followed by i–C15:1 (18.5%) and n-C16 (13.2%). Moreover, branched fatty acids (62%) including monounsaturated fatty acids (MUFA) (e.g. i– C15:1 and i–C16:1) and saturated fatty acids (SFA) were the dominant types of fatty acids in the cell membrane. A polyunsaturated fatty acid (PUFA), C18:2(cis–9) (known as linoleic acid) was also detected among analyzed fatty acids.