Miracle-dz/UniFAR-FTUs huggingface dataset:
Localized Teacher Supply and Demand in Arkansas: An Exploration of the Supply and Demand of Teachers in Arkansas School Districts

There have been widespread reports of an impending teacher shortage crisis in the U.S. for more than 30 years. In the U.S., there are claims of a widespread national shortage while research indicates teacher shortages are specific to certain subjects and schools. Part of the reason for the conflicting accounts is how shortage is identified and what information is used to assess it. In this study, I test whether a uniform teacher shortage exists across the state of Arkansas. I hypothesize that, rather than a universal shortage, teacher shortages are more likely to occur in certain regions and subjects. I examine the characteristics of districts with the most favorable teaching supply and those with the greatest teaching need using descriptive and multivariate analysis of data collected from district surveys along with administrative data. In this study, “supply” is defined as the ratio of applications to vacancies and “need” is defined as the ratio of vacancies to full-time equivalent (FTE) certified classroom teachers. This is the third study to use applicants to identify teacher supply, and the first to assess teacher need or shortages in this way. Results indicate teacher supply and need are unequally distributed across the state; there is no uniform teacher shortage statewide. Regarding teacher supply, I find district size, region, and urbanicity appear to drive supply. Teacher supply is most favorable for large districts with student enrollments greater than 3,500, districts in the Northwest, and suburban and city districts. Regarding teacher need, I find urbanicity and region contribute most to need and the need appears greatest for districts in cities, and districts in the Central and Southeast regions. Teacher need does not appear to be significantly influenced by district educational success, teacher salary, or district growth. Looking at the relationship between teacher supply and need, I find three clear relationships. In the Central and Southeast regions, there is lower teacher supply and greater teacher need. In urban districts, there is both greater teacher supply and need. In higher poverty districts, there is significantly less teacher supply and more teacher need.
Effects of epigallocatechin-3-gallate on thermogenesis and mitochondrial biogenesis in brown adipose tissues of diet-induced obese mice

ABSTRACT Background: Epigallocatechin-3-gallate (EGCG) is the major polyphenol in green tea and has been considered a natural agent that can help to reduce the risk of obesity. Objective: The aim of this study was to investigate the effects of EGCG on thermogenesis and mitochondrial biogenesis in brown adipose tissue (BAT) of diet-induced obese mice. Methods: Male C57BL/6J mice were provided a high-fat diet for 8 weeks to induce obesity, following which they were divided into two groups: one on a high-fat control diet and the other on a 0.2% EGCG (w/w)-supplemented high-fat diet for another 8 weeks. Results: The EGCG-supplemented group showed decreased body weight gain, and plasma and liver lipids. EGCG-fed mice exhibited higher body temperature and mitochondrial DNA (mtDNA) content in BAT. The messenger RNA levels of genes related to thermogenesis and mitochondrial biogenesis in BAT were increased by EGCG. Moreover, adenosine monophosphate-activated protein kinase (AMPK) activity in BAT was stimulated by EGCG. Conclusions: The results suggest that EGCG may have anti-obesity properties through BAT thermogenesis and mitochondria biogenesis, which are partially associated with the regulation of genes related to thermogenesis and mitochondria biogenesis, and the increase in mtDNA replication and AMPK activation in BAT of diet-induced obese mice.
A Study on Distance-based Outlier Detection on Uncertain Data

Uncertain data management, querying and mining have become important because the majority of real world data is accompanied with uncertainty these days. Uncertainty in data is often caused by the deficiency in underlying data collecting equipments or sometimes manually introduced to preserve data privacy. The uncertainty information in the data is useful and can be used to improve the quality of the underlying results. Therefore in this dissertation, three problems are being solved related to outlier detection on uncertain data. 1) Distancebased outlier detection on uncertain data: In this research, we give a novel definition of distance-based outliers on uncertain data. Since the distance probability computation is expensive, a cell-based approach is proposed to index the dataset objects and to speed up the outlier detection process. The cell-based approach identifies and prunes the cells containing only inliers based on its bounds on outlier score (#D-neighbors). Similarly it can also detect the cells containing only outliers. 2) Topk outlier detection on uncertain data: In this work, a topk distance-based outlier detection approach is presented. In order to detect top-k outliers from uncertain data efficiently, we propose a data structure, populated-cells list (PC-list). Using the PC-list, the top-k outlier detection algorithm needs to consider only a fraction of the dataset objects and hence quickly identifies candidate objects for the top-k outliers. 3) Continuous outlier detection on uncertain data streams: In this part of the dissertation, a distance-based approach is proposed to detect outliers continuously from a set of uncertain objects’ states that are originated synchronously from a group of data sources (e.g., sensors in WSN). A set of objects’ states at a timestamp is called a state set. Usually, the duration between two consecutive timestamps is very short and the state of all the objects may not change much in this duration. Therefore, to eliminate the unnecessary computation at every timestamp, an incremental approach of outlier detection is proposed which makes use of outlier detection results obtained from the previous timestamp to detect outliers in the current timestamp. Finally, extensive experimental evaluations on real and synthetic datasets are presented for each of the proposed outlier detection approaches, to prove their accuracy, efficiency and scalability.
Spectral variation constrained power spectral density estimation for wideband spectrum sensing

In this paper, a novel power spectrum density (PSD) estimation approach is proposed for accurate and efficient wideband spectrum sensing in Cognitive Radio (CR) systems. Based on the observed signal from a wideband receiver, the goal of determining the fluctuation-free signal PSD is formulated as a constrained Bayesian estimation problem, subject to spectral variation constraints between neighboring spectral frequencies. The extracted signal PSD obtained using the proposed approach can then used in the energy detection process to make informed decisions with regards to the identification of free spectrum resources for opportunistic access by the CR. Experimental results using Monte Carlo simulations and real terrestrial digital TV (DTV) signal acquisitions show that the proposed approach allows for accurate PSD computation using wideband receivers under unknown noise and fluctuation conditions. Therefore, there is great potential for integrating the proposed method into existing energy detection methods for more accurate and efficient wideband spectrum sensing in CR systems under unknown noise and channel conditions.
Detecteur a ondes de lamb de la position d'un stylet

A partir de la mesure du temps de vol d'un paquet d'ondes se propageant dans une plaque de verre, il est possible connaissant la vitesse du paquet d'ondes, de calculer la position de l'emetteur par rapport a un recepteur. Ce principe est applique pour calculer a une cadence de 1000 points par seconde, les coordonnees cartesiennes (x,y) d'un stylet, muni d'une source ultrasonore engendrant des modes de lamb dans la plaque. Les problemes de mesure lies a l'inclinaison ou a la rotation du stylet sont evites, soit en combinant un mode de precession de la pointe du stylet avec la detection differentielle du mode s#0 de lamb, grace a des recepteurs piezoelectriques colles sur les chants opposes de la plaque, soit en combinant une vibration axiale de la pointe avec la detection directe ou differentielle du mode a#0 de lamb. Dans le cas d'une detection differentielle, le fonctionnement du stylet peut etre asynchrone par rapport au systeme et ne necessite aucun cable de connexion si l'on place dans le tube du stylet un generateur d'impulsions alimente par une petite source d'energie. La precision du dispositif est limitee par le phenomene de diffraction. Le phenomene est cependant compense et la precision accrue dans la region centrale de la plaque, dans le cas d'une detection differentielle
Study of Pressure-Sensitive Materials for Floor Sensor Networks

This paper presents a comparative study of pressure-sensitive sensor materials being suitable for monitoring purposes in pressure mapping sensor networks. Four sensor materials working on piezoresistive, piezoelectric, quasi-piezoelectric and capacitive principle have been discussed including the built-up, the working principle, the manufacturing and the most important properties. Additionally, the electromechanical models of the sensor elements have been introduced and verified by comparing the modelled and measured sensor characteristics. The studied materials were compared and evaluated using a decision matrix with respect to the applicability as a thin and flexible pressure sensor unit in a competitive large-area floor sensor network.
Pitfalls in MR measurement of tissue blood flow with intravascular tracers: Which mean transit time?

Measuring tissue blood flow with NMR imaging of intravascular tracers is more difficult than measurements of tissue blood volume. One major obstacle to the application of the Central Volume Principle is the direct measurement of the mean transit time. In this note, we demonstrate that mean transit time (MTT), which relates tissue blood volume to blood flow via the Central Volume Principle, is not the first moment of the concentration‐time curve for MR or CT imaging of purely intravascular tracers. However, while first moment methods cannot be used by themselves to determine absolute flow, we show that transit curves may provide a useful relative measure of flow, for example, by considering ratios of the first moments.
Successful treatment of cardiac sarcoidosis with infliximab.

To the Editor: The clinical presentation of cardiac sarcoidosis may include arrhythmias, pericardial or valvular disease, congestive heart failure, or ventricular aneurysms1. Cardiac sarcoidosis is regarded as an indication for corticosteroid therapy2. Immunosuppressive agents are often combined with corticosteroids to reduce adverse effects. Anti-tumor necrosis factor-α (anti-TNF-α) therapy has been used to treat refractory sarcoidosis3, and TNF-α expression has been documented at sites where sarcoid granulomas are observed, and plays a critical role in granuloma formation4. Thus, anti-TNF-α therapy should result in suppression of disease manifestation and progression. The use of infliximab in patients with cardiac sarcoidosis has been described…
Maternal plasma and breastmilk viral loads are associated with HIV‐1‐specific cellular immune responses among HIV‐1‐exposed, uninfected infants in Kenya

Infants exposed to maternal HIV‐1 provide an opportunity to assess correlates of HIV‐1‐specific interferon (IFN)‐γ responses and may be informative in the development of HIV‐1 vaccines. HIV‐1‐infected women with CD4 counts 200–500 cells/mm3 were randomized to short‐course zidovudine/nevirapine (ZDV/NVP) or highly active anti‐retroviral therapy (HAART) between 2003 and 2005. Maternal plasma and breastmilk HIV‐1 RNA and DNA were quantified during the first 6–12 months postpartum. HIV‐1 gag peptide‐stimulated enzyme‐linked immunospot (ELISPOT) assays were conducted in HIV‐1‐exposed, uninfected infants (EU), and correlates were determined using regression and generalized estimating equations. Among 47 EU infants, 21 (45%) had ≥1 positive ELISPOT result during follow‐up. Infants had a median response magnitude of 177 HIV‐1‐specific spot‐forming units (SFU)/106 peripheral blood mononuclear cells (PBMC) [interquartile range (IQR) = 117–287] directed against 2 (IQR = 1–3) gag peptide pools. The prevalence and magnitude of responses did not differ by maternal anti‐retroviral (ARV) randomization arm. Maternal plasma HIV‐1 RNA levels during pregnancy (P = 0·009) and breastmilk HIV‐1 DNA levels at 1 month (P = 0·02) were associated with a higher magnitude of infant HIV‐1‐specific ELISPOT responses at 1 month postpartum. During follow‐up, concurrent breastmilk HIV‐1 RNA and DNA (cell‐free virus and cell‐associated virus, respectively) each were associated positively with magnitude of infant HIV‐1‐specific responses (P = 0·01). Our data demonstrate the importance of antigenic exposure on the induction of infant HIV‐1‐specific cellular immune responses in the absence of infection.
Maximum similarity based feature matching and adaptive multiple kernel learning for object recognition

In this thesis, we perform object recognition using (i) maximum similarity based feature matching, and (ii) adaptive multiple kernel learning. Images are likely more similar if they contain objects within the same categories, so how to measure image similarities correctly and efficiently is one of the critical issues for object recognition. We first propose to match features between two images so that their similarity is maximized, and employ support vector machines (SVMs) for recognition based on the maximum similarity matrix. Secondly, given several similarity matrices (kernels) created by different visual information in images, we propose a novel adaptive multiple kernel learning technique to generate an optimal kernel from all the kernels based on biconvex optimization. These two new approaches are tested on the most recent image benchmark datasets and their results are impressive, equalling or bettering the state-of-the-art results.
Four Ages of Understanding: The First Postmodern Survey of Philosophy from Ancient Times to the Turn of the Twenty-First Century

This book redraws the intellectual map and sets the agenda in philosophy for the next fifty or so years. By making the theory of signs the dominant theme in "Four Ages of Understanding", John Deely has produced a history of philosophy that is innovative, original, and complete. The first full-scale demonstration of the centrality of the theory of signs to the history of philosophy, "Four Ages of Understanding" provides a new vantage point from which to review and reinterpret the development of intellectual culture at the threshold of "globalization". Deely examines the whole movement of past developments in the history of philosophy in relation to the emergence of contemporary semiotics as the defining moment of Postmodernism. Beginning traditionally with the Pre-Socratic thinkers of early Greece, Deely gives an account of the development of the notion of signs and of the general philosophical problems and themes which give that notion a context through four ages: Ancient philosophy, covering initial Greek thought; the Latin age, philosophy in European civilization from Augustine in the 4th century to Poinsot in the 17th; the Modern period, beginning with Descartes and Locke; and the Postmodern period, beginning with Charles Sanders Peirce and continuing to the present. Reading the complete history of philosophy in light of the theory of the sign allows Deely to address the work of thinkers never before included in a general history, and in particular to overcome the gap between Ockham and Descartes which has characterized the standard treatments heretofore. One of the essential features of the book is the way in which it shows how the theme of signs opens a perspective for seeing the Latin Age from its beginning with Augustine to the work of Poinsot as an indigenous development and organic unity under which all the standard themes of ontology and epistemology find a new resolution and place. A magisterial general history of philosophy, Deely's book provides both a strong background to semiotics and a theoretical unity between philosophy's history and its immediate future. With "Four Ages of Understanding" Deely sets a new agenda for philosophy as a discipline entering the 21st century.
Enhanced piezoresistive sensing via synchronized oscillations in a mechanically coupled disk array

This paper presents the mechanical coupling of SOI disk resonators for synchronized oscillation of a resonator array. The synchronized array of disk resonators has the added enhancement of employing piezoresistive readout to boost electromechanical transconduction. Compared to a single disk resonator using capacitive readout, an array of two disks employing piezoresistive sensing provides a 18.2dB reduction in the insertion loss. In terms of quality factor (Q), rather than suffer a reduction as a result of the coupling, the coupled disk array even showed a doubling of Q relative to that of a single disk resonator (184,000 as compared to 95,000).
Genetic Algorithm - Survey Paper

paper provides an introduction of Genetic Algorithm, its basic functionality. The basic functionality of Genetic Algorithm include various steps such as selection, crossover, mutation. This paper also focuses on the comparison of Genetic Algorithm with other problem solving technique. The details of labs that basically concentrate on the research and development of Genetic Algorithm is also included. The details of labs include the various projects that are carried out on Genetic Algorithm. KeywordsCrossover, Mutation, problem-solving technique.
An examination of the electronic banking services in stanbic bank branch of Makerere University

xi CHAPTER ONE . 1 1.0. Introduction . 1 1.1. Background to the Study . 1 1.2. Statement of the Problem . 3 1.3. Purpose of the Study . 4 1.4. Objectives of the Study . 4 1.5. Research Questions . 4 1.6. Scope of the Study . 4 1.7. Significance of the Study . 5 CHAPTER TWO . 6 LITERATURE REVIEW . 6 2.0. Introduction . 6
Feature Learning Based Approach for Weed Classification Using High Resolution Aerial Images from a Digital Camera Mounted on a UAV

The development of low-cost unmanned aerial vehicles (UAVs) and light weight imaging sensors has resulted in significant interest in their use for remote sensing applications. While significant attention has been paid to the collection, calibration, registration and mosaicking of data collected from small UAVs, the interpretation of these data into semantically meaningful information can still be a laborious task. A standard data collection and classification work-flow requires significant manual effort for segment size tuning, feature selection and rule-based classifier design. In this paper, we propose an alternative learning-based approach using feature learning to minimise the manual effort required. We apply this system to the classification of invasive weed species. Small UAVs are suited to this application, as they can collect data at high spatial resolutions, which is essential for the classification of small or localised weed outbreaks. In this paper, we apply feature learning to generate a bank of image filters that allows for the extraction of features that discriminate between the weeds of interest and background objects. These features are pooled to summarise the image statistics and form the input to a texton-based linear classifier that classifies an image patch as weed or background. We evaluated our approach to weed classification on three weeds of significance in Australia: water hyacinth, tropical soda apple and serrated tussock. Our results showed that collecting images at 5–10 m resulted in the highest classifier accuracy, indicated by F1 scores of up to 94%.
Qualitative Content Analysis: A Case Study of a Malaysian Government Education Website

Content analysis is a set of qualitative methods utilized to analyse data from verbal, print or electronic communication channels. Text-based information from interviews, focus groups and open-ended survey questions can be evaluated using this method. This paper shall put forth the definition of qualitative content analysis and discuss the basic principles of its technique. The method for conducting qualitative content analysis research will then be outlined and explained. A case study of a Malaysian government education website is provided to demonstrate the application of the said method. The case study explores several critical success factors (CSFs) involved in the transfer of knowledge from the Government to targeted users via an education-based website. Fifteen interviews were conducted and 14 CSFs are identified and segregated into six thematic groups. This exercise shall provide practical guidance to the practitioners that are directly involved in the process. The identification and understanding of the CSFs would provide the much needed direction for the website administrators and content creators. They would have access to essential information that enable them to make strategic decisions related to their website’s content development and delivery activities. This would then enhanced their capacity to deliver the requisite knowledge to their targeted users.
Secondary metabolites by chemical screening. 20. Decarestrictines, a new family of inhibitors of cholesterol biosynthesis from Penicillium: III. Decarestrictines E to M.

Two novel natural niphimycin analogs, amycins A (5) and B (3) were isolated from the culture broth of the Streptomyces sp. DSM 3816 by chemical screening methods. In addition this strain produces the antibiotics niphimycin (4), elaiophylin (2) and nigericin (1). Fermentation, isolation, structure elucidation and biological activity of the amycins are described.
Fourteen-year follow-up of speech/language-impaired and control children: psychiatric outcome.

OBJECTIVE To examine the association between early childhood speech and language disorders and young adult psychiatric disorders. METHOD In a longitudinal community study conducted in the Ottawa-Carleton region of Ontario, Canada, interviewers administered structured psychiatric interviews to age 19 participants who were originally identified as speech-impaired only, language-impaired, or nonimpaired at age 5. The first stage of the study took place in 1982 when participants were 5 years old, and the latest stage of the study took place between 1995 and 1997 when participants had a mean age of 19 years. This report examines the association between early childhood speech/language status and young adult psychiatric outcome. RESULTS Children with early language impairment had significantly higher rates of anxiety disorder in young adulthood compared with nonimpaired children. The majority of participants with anxiety disorders had a diagnosis of social phobia. Trends were found toward associations between language impairment and overall and antisocial personality disorder rates. Males from the language-impaired group had significantly higher rates of antisocial personality disorder compared with males from the control group. Age of onset and comorbidity did not differ by speech/language status. The majority of participants with a disorder had more than one. CONCLUSIONS Results support the association between early childhood speech and language functioning and young adult psychiatric disorder over a 14-year period. This association underscores the importance of effective and early interventions.