Miracle-dz/UniFAR-FTUs huggingface dataset:
String-Rewriting Grammars for Evolutionary Architectural Design

Evolutionary methods afford a productive and creative alternative design workflow. Crucial to success is the choice of formal representation of the problem. String-rewriting context-free grammars (CFGs) are one common option in evolutionary computation, but their suitability for design is not obvious. Here, a CFG-based evolutionary algorithm for design is presented. The process of meta-design is described, in which the CFG is created and then refined to produce an improved design language. CFGs are contrasted with another grammatical formalism better known in architectural design: Stiny's shape grammars. The advantages and disadvantages of the two types of grammars for design tasks are discussed.
Research Statement -benjamin Hutz Local Information Dynatomic Cycles

In Morton and Silverman [8], the authors give an upper bound on the possible primitive periods of periodic points for rational maps on P (and also automorphisms of P ). I generalize their main theorem to nondegenerate morphisms on smooth, irreducible projective varieties and provide a similar upper bound on primitive periods based on good reduction information for these more general dynamical systems.
Sosyal Bilgiler Dersinde Farklı İşbirlikli Öğrenme Yöntemlerinin Uygulamlarına İlişkin Öğrenci Görüşleri

Bu arastirmanin amaci, ortaokul 6. sinif sosyal bilgiler dersi ogretiminde farkli isbirlikli ogrenme yontemlerinin uygulamalarina iliskin ogrenci goruslerini tespit etmektir. Arastirmada nitel veri toplamada onemli bir veri toplama teknigi olan odak grup gorusme yontemi kullanilmistir. Arastirmada Demokrasinin Seruveni (DS) unitesi Erzurum ilinde bulunan Sabanci Ortaokulu’nda 3 farkli sinifta jigsaw, grup arastirmasi (GA) ve okuma-yazma-uygulama (OYU) yontemlerine uygun olarak 5 hafta sureyle islenmistir. Uygulamalar sona erdikten sonra ise her siniftan maksimum cesitlilik orneklemesine uygun olarak dusuk, orta ve yuksek duzeyde basarili olanlar arasindan secilen ogrencilerle odak grup gorusmeleri yapilmistir. Her uc siniftan 10’ar ogrenci olmak uzere toplam 30 ogrenci bu gorusmelere katilmistir. Ogrencilerin ogrenme surecine yonelik goruslerini belirlemek amaciyla acik uclu sorulardan olusan Odak Grup Gorusme Formu kullanilmistir. Elde edilen nitel verilerin cozumlenmesinde ise icerik analizi yontemi kullanilmistir. Arastirmanin sonucunda genel itibariyle her 3 gruptaki ogrenciler kendilerine uygulanan isbirlikli yontem sayesinde konulari daha iyi ogrendiklerini, arkadaslik iliskilerinde pozitif yonde gelismeler oldugunu, bazi sosyal becerileri kazandiklarini belirtmislerdir. Bununla birlikte ogrenciler siniftaki gruplar arasinda odule ulasma arzusunun rekabete donusebildigini; bu durumun da ozellikle diger gruplarla olan arkadaslik iliskilerini olumsuz yonde etkileyebildigini ifade etmislerdir.
Scalable Video Streaming over Wimax Networks

The Multicast/Broadcast Service (MBS) feature of mobile WiMAX network is a promising technology for providing wireless multimedia, because it allows the delivery of multimedia content to large-scale user communities in a cost-efficient manner. In this thesis, we focus on two research problems in such networks: (i) maximizing the video quality and (ii) minimizing energy consumption for mobile receivers. We prove that these problems are NP-Complete, and propose constant factor approximation algorithms to solve them. Our algorithms intelligently select video layers from a scalable video stream to maximize video quality and construct burst transmission schedules that reduce receiver device energy consumption without sacrificing the video quality. Using extensive simulation and mathematical analysis we show that the proposed solution: (i) is efficient in terms of execution time, (ii) achieves high radio resource utilization, (iii) maximizes the received video quality, and (iv) minimizes the energy consumption for mobile receivers.
A kernel approach to learning a neuron model from spike train data

A spiking neuron is a principal component of the brain and the nervous system. Understanding the characteristics of a single neuron as well as the interactions of a population of neurons is essential to neuroscience. At the micro-level, neurons are very complex devices that control the flow of ions in and out of the membrane. However an abstracted view of the neuron sees it as a mechanism which receives electrical signals from other neurons as input and produces and transmits electrical signals to other neurons. Much work has been done to model the neuron at varying levels of complexity in order to explain its dynamics. Competitions exist which compare the accuracy of submitted neurons models. Here we propose a methodology which learns an equivalent mathematical mapping from input spike trains to the output spike train by only considering the timing of all afferent(incoming) and efferent(outgoing) spikes within a bounded finite past. This is done by instantiating a classiffication problem which uses kernels to dichotomize input spike trains which cause the neuron to generate a spike from those that do not cause the neuron to generate a spike. The kernel used is one that has been generated from a dictionary of functions which are similar to those used in existing neuron models. By using an intuitive dictionary, we produce a kernel which is tailored to the problem of learning spiking neuron models. By the representer theorem we know that only a finite number of training data points will be needed to produce the classification solution. By considering the number of data points used to produce the solution, we are able to assess the complexity of the modeled neuron. Those neurons which need more spike time inputs to reproduce their behavior could be considered more complex than those which need fewer spike time inputs for the given kernel.
1 Is the Food And Drug Administration Safe And Effective ?

Their e-mail addresses Are <t-philipson@uchicago.edu> and <ericsun@uchicago.edu >, respectively. 2 In virtually all developed countries and many undeveloped ones as well, regulatory authorities provide public oversight of the safety and efficacy of many medical products and foods. In the United States, such oversight is conducted by the Food and Drug Administration (FDA), which regulates drugs, medical devices, biologics (products made from living organisms, like vaccines and blood products), cosmetics, radiation-emitting electronic products, veterinary products, and foods. The FDA regulates all food products except meat and poultry, which are regulated by the United States Department of Agriculture, although the FDA regulates game meats. According to the FDA, the products it regulates account for more than one-fifth of U.S. consumer spending. In the area of medical products, the agency is responsible for determining whether marketed products are both safe and effective before and after they have been marketed. Compared to many other regulatory agencies, relatively little research has been done by economists on the efficiency tradeoffs involved with the FDA, although existing analyses Schwartzman (1976). It is somewhat ironic to conjecture that if a product application was supplied to the FDA with the scant amount of analysis or evidence that currently exists on the efficiency or performance of the policies of the agency itself, such an application would clearly be rejected on the basis of insufficient analysis or evidence. In this paper we discuss and summarize in a non-technical manner recent research on the FDA that sheds new light on whether the policies of the agency itself are safe and effective. Although the discussion is specific to the FDA, some of this research could potentially apply to other areas of regulation as well, such as e.g. transportation. 3 We begin with some background on the statutes and regulations that govern the Food and Drug Administration. We then stress two static and dynamic issues that seem fundamental to the efficiency of the FDA. The static issue concerns the potential inefficiency of the duality of product safety laws when such functions are performed not only by the FDA but also by the private sector in a complimentary way through product liability law. Put another way, what is the rationale for using product liability and the FDA to regulate drug safety? While intuitively it may seem that two systems must be better than one in ensuring drug safety, it is important to remember that each …
Chapter 6: Discussion

Drugs affecting renin angiotensin system (RAS), the angiotensin receptor (ATR) blockers and angiotensin converting enzyme (ACE) inhibitors, have clinically been widely used as antihypertensive agents. Beside peripheral RAS which control blood pressure, a separate RAS exist in central nervous system (Wright et al., 1997) where it regulates numerous physiological and behavioral processes including cognitive function (Gard, 2002). In the recent years, it has been found that drugs affecting RAS i.e. ACE inhibitors and ATR blockers showed memory improvement in animals and human being ( Raghavendra et al., 1998; Fogari et al., 2004; Jenkins and Chai, 2007). Further, it has been found that angiotensin II (Ang II) is associated with disturbed cholinergic function (Barnes et al., 1989) and oxidative stress (Griendling et al., 1994), the important factors implicated in pathophysiology of dementia ( Pratico et al., 2002). Though, previous studies reported beneficial effects of ACE inhibition and ATR blockers in dementia using several models but its involvement in colchicine and AF64A induced impairment in memory function has not been investigated. Therefore, the present study explored role of central ACE and ATR by utilizing intracerebral (IC) colchicine and AF64A induced model of memory impairment in mice. The IC colchicine and AF64A induced dementia models were developed in mice and validated by using clinically used acetylcholinesterase inhibitor, donepezil. The RAS affecting drugs ACE inhibitor and ATR blockers were used as experimental pharmacological tools to explore involvement of RAS components in memory impairment. The effects of ACE inhibitor, perindopril, and selective blockers of AT1 receptor, candesartan was studied on memory function and associated factors like oxidative stress and cholinergic function in mice brain. These RAS affecting drugs were reported to cross blood brain barrier (Tota et al., 2009).
İşitme Engelli Üniversite Öğrencilerine Uygulanan ‘Tanımlama Yapma’ Stratejisinin İncelenmesi

Arastirmalar isiten ve isitme engelli bireylerin sozcuk dagarcigi gelisimi ve okudugunu anlamalari arasinda kuvvetli bir iliski oldugunu gostermektedir. Bununla birlikte bireylerin is yasantilarindaki basarilari icin mesleki terimleri ogrenmeleri buyuk onem tasimaktadir. Dengeli Okuma Yazma Ogretimi Yaklasimi’nin (DOYOY) sozcuk dagarcigi gelistirme ortami yaratmada yararli ve etkili oldugu gorulmustur. Bu makalede isitme engelli universite ogrencilere dogrudan sozcuk dagarcigi gelistirme stratejilerinden ‘Tanimlama Yapma’nin nasil gerceklestirildigi ve yapilan uygulamalarin ogrencilerin tanimlama yapma becerilerini nasil etkiledigi aktarilacaktir. Eylem arastirmasi olarak gerceklestirilen arastirma Anadolu Universitesi Engelliler Entegre Yuksekokul, Grafik bolumu birinci sinifta okuyan on isitme ogrenci ile gerceklestirilmistir. Arastirma verileri videoteyp kayitlari, gecerlik komitesi ses kayitlari ve toplanti tutanaklari, ders planlari ve yansitmali degerlendirmeler ve sozcuk dagarcigi duzeylerini belirleme amacli test sonuclarindan olusmaktadir. Dongusel olarak toplanan veriler arastirma surecinde ve sonunda cesitli analiz teknikleri ile analiz edilmistir. Veriler gecerlik komitesi tarafindan duzenli olarak incelenmistir. Arastirma bulgularina gore gerceklestirilen tanimlamalar, planlanmis veya ogrenciler ve arastirmacinin dogaclama olarak derse katkilariyla cesitlenmistir. Isitme engelli ogrencilerin DOYOY ile gerceklestirilen derslerle, tanim yapma becerisini gelistirdikleri gozlemlenmistir. Bu becerinin ogrencilerin okuma anlama becerilerinin gelisimini dolayli bir sekilde gelistirdigi dusunulmektedir. Bu bulgular arastirmadaki diger bulgular ve alan yazin isiginda tartisilmistir
An Efficient Method for Indian Vehicle License Plate Extraction and Character Segmentation

Automatic License Plate Identification (ALPI) has many applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints, etc.). In this paper, a smart, simple and efficient algorithm which is mainly designed for Indian license Plate Recognition is presented for vehicle's license plate recognition system. The proposed algorithm consists of three major parts: Extraction of plate region, segmentation of characters and recognition of plate characters. For extracting the Plate region, edge detection algorithm and vertical projection method are used. In segmentation part, filtering, thinning and vertical and horizontal projection are used. And finally, chain code concept with different parameter is used for recognition of the characters. The performance of the proposed algorithm has been tested on real images.
Impact of Mental Fatigue during Repetitive Exercises of a Visual P300 Speller

In this paper, we investigate the effect that mental fatigue during repetitive exercises of a visual P300 Speller has on the P300 component, in terms of accuracy, amplitude, latency, signal morphology, and overall signal quality. This work is part of a larger EEG based project and is based on the P300 speller BCI (oddball) paradigm and the xDAWN algorithm, with eight healthy subjects; while using a non-invasive Brain-Computer Interface (BCI) based on low fidelity electroencephalographic (EEG) equipment. Herein, eight channels through the initial task (6 minutes), additional tasks (50 minutes) and final task (6 minutes) states, recorded the subjects’ signal. Our results show that the accuracy was best for the initial task (IT) at 100%, followed closely by the final task (FT) at 98%. In addition, our ANOVA analysis showed that the amplitude exhibited a statistical significance between IT and FT, while the latency did not indicate any statistical difference. This paper provides initial results into the practicability of the aforementioned P300 speller methodology and lowcost equipment to be used repetitively and continually and the effect thereof on accuracy and signal characteristics. Our aim is to assess the effect of prolonged usage and exposure to the aforementioned methodology and equipment, with the aim of broadening its use in a real-world context.
Anthropogenic N deposition and the fate of 15 NO

Human activity has substantially increased atmospheric NO 3 deposition in many regions of the Earth, which could lead to the N saturation of terrestrial ecosystems. Sugar maple (Acer saccharum Marsh.) dominated northern hardwood forests in the Upper Great Lakes region may be particularly sensitive to chronic NO 3 deposition, because relatively moderate experimental increases (three times ambient) have resulted in substantial N leaching over a relatively short duration (5–7 years). Although microbial immobilization is an initial sink (i.e., within 1–2 days) for anthropogenic NO 3 in this ecosystem, we have an incomplete understanding of the processes controlling the longer-term (i.e., after 1 year) retention and flow of anthropogenic N. Our objectives were to determine: (i) whether chronic NO 3 additions have altered the N content of major ecosystem pools, and (ii) the longer-term fate of NO 3 in plots receiving chronic NO 3 addition. We addressed these objectives using a field experiment in which three northern hardwood plots receive ambient atmospheric N deposition (ca. 0.9 g N m 2 year ) and three plots which receive ambient plus experimental N deposition (3.0 g NO3 -N m 2 year ). Chronic NO 3 deposition significantly increased the N concentration and content (g N/m ) of canopy leaves, which contained 72% more N than the control treatment. However, chronic NO 3 deposition did not significantly alter the biomass, N concentration or N content of any other ecosystem pool. The largest portion of N recovered after 1 year occurred in overstory leaves and branches (10%). In contrast, we recovered virtually none of the isotope in soil organic matter (SOM), indicating that SOM was not a sink for anthropogenic NO 3 over a 1 year duration. Our results indicate that anthropogenic NO 3 initially assimilated by the microbial community is released into soil solution where it is subsequently taken up by overstory trees and allocated to the canopy. Anthropogenic N appears to be incorporated into SOM only after it is returned to the forest floor and soil via leaf litter fall. Shortand long-term isotope tracing studies provided very different results and illustrate the need to understand the physiological processes controlling the flow of anthropogenic N in terrestrial ecosystems and the specific time steps over which
Energy Series: Estimating appliance and home electronic energy use

Virginia Cooperative Extension programs and employment are open to all, regardless of race, color, national origin, sex, religion, age, disability, political beliefs, sexual orientation, or marital or family status. An equal opportunity/affirmative action employer. Issued in furtherance of Cooperative Extension work, Virginia Polytechnic Institute and State University, Virginia State University, and the U.S. Department of Agriculture cooperating. Mark A. McCann, Director, Virginia Cooperative Extension, Virginia Tech, Blacksburg; Alma C. Hobbs, Administrator, 1890 Extension Program, Virginia State, Petersburg. ENERGY SERIES: Estimating Appliance and Home Electronic Energy Use
Evaluation of changes in choroidal thickness and the choroidal vascularity index after hemodialysis in patients with end-stage renal disease by using swept-source optical coherence tomography

Abstract To evaluate the effect of hemodialysis on choroidal thickness and the choroidal vascularity index (CVI) in patients with end-stage renal disease (ESRD) by using swept-source optical coherence tomography. Thirty-two eyes of 32 patients with ESRD undergoing hemodialysis were recruited prospectively. Detailed ophthalmologic examinations and swept-source optical coherence tomography were performed immediately before and after hemodialysis. Choroidal thickness maps were generated automatically by using built-in software. The CVI was calculated using binarized choroidal optical coherence tomography images. Systemic parameters such as body weight and blood pressure were also measured. The changes in systemic and ocular parameters during hemodialysis were evaluated. Subjects were divided into 2 groups (diabetes mellitus [DM] vs non-diabetes mellitus) for subgroup analysis. Total choroidal thickness showed a significant overall decrease after hemodialysis (−10.9 ± 14.0, P <.001). In the subgroup analysis, total choroidal thickness significantly decreased in both patients with DM (−11.3 ± 13.6, P = .004) and those without (−10.6 ± 14.9, P = .020), but the reduction of choroidal thickness was observed in more subfields in patients with DM than in those without. The CVI did not significantly change after hemodialysis (P = .717). No significant systemic and ocular factors affected the changes in total choroidal thicknesses. Choroidal thickness significantly decreased after hemodialysis in most subfields regardless of the presence of DM. Peri-hemodialysis choroidal changes could be considered in the management of patients with ESRD. Swept-source optical coherence tomography can provide ample and reliable quantitative data for monitoring ocular hemodynamic changes.
SYNOPSIS Name of the Candidate

We consider the broad framework of supervised learning, where one gets examples of objects together with some labels (such as tissue samples labeled as cancerous or non-cancerous, or images of handwritten characters labeled with the correct character in a-z), and the goal is to learn a prediction model which given a new object, makes an accurate prediction. The notion of accuracy depends on the learning problem under study and is measured by an evaluation metric of interest. A supervised learning algorithm is said to be statistically consistent or simply consistent if it returns an ‘optimal’ prediction model with respect to the desired evaluation metric in the limit of infinite data. Statistical consistency is a fundamental notion in supervised machine learning, and therefore the design of consistent algorithms for various learning problems is an important question. Consistency has been studied for certain specific multiclass learning problems and evaluation metrics, for example, binary classification with the 0-1 loss and F-measure [2, 29, 14, 11, 16]; multiclass classification with the 0-1 loss [28, 24]; ranking with pairwise disagreement (PD) and normalized discounted cumulative gain (NDCG) losses [7, 3, 21, 5]. However, the unifying theme in these problems is largely unexplored. In this thesis, we give the foundations of a unified framework for studying the problem of consistency for a general multiclass learning problem, thereby generalizing many known past results for specific learning problems. A majority of multiclass learning problems in practice use an evaluation metric based on a loss matrix (e.g. the fraction of wrongly classified instances is based on the 0-1 loss matrix), and most prevalent algorithms for such problems are surrogate minimizing algorithms, which are characterized by a surrogate loss (e.g. the support vector machine is a surrogate minimizing algorithm with the hinge surrogate loss). If the surrogate loss is convex, then the resulting surrogate minimizing algorithm can be framed as a convex optimization problem and be solved efficiently. In the first part of the thesis, we study calibrated surrogate losses which leads to a consistent surrogate minimizing algorithm for a given loss matrix. This is the largest and
Developing a Mathematics Module for Students with Intellectual Disability in Higher Education

Individuals with intellectual disability (ID) have largely been excluded from accessing all levels of education and participating in college life. Fortunately, academic institutions around the world are slowly beginning to examine how they can support equal citizenship of individuals with ID within their community. In Ireland, one university has recently accredited an innovative higher education programme for college students with intellectual disabilities. One of the emergent modules focuses on mathematics and recognises the importance of developing students’ numeracy skills in order to confidently navigate today’s society. Despite the increased emphasis on general mathematics education, the authors found there to be a dearth of research regarding the development of such a module for students with ID. This paper describes the design and development of the mathematics module and also details its piloting and evaluation with a cohort of students with ID who were enrolled in a higher education course in an Irish university.
A Quantized Riemann–Hilbert Problem in Donaldson–Thomas Theory

We introduce Riemann–Hilbert problems determined by the refined Donaldson–Thomas theory. They involve piecewise holomorphic maps from the complex plane to the group of automorphisms of a quantum torus algebra. We study the simplest case in detail and use the Barnes double gamma function to construct a solution.