Miracle-dz/UniFAR-FTUs huggingface dataset:
Review and Recommendations for Zero-Inflated Count Regression Modeling of Dental Caries Indices in Epidemiological Studies

Over the past 5–10 years, zero-inflated (ZI) count regression models have been increasingly applied to the analysis of dental caries indices (e.g. DMFT, dfms). The main reason for that is linked to the broad decline in children’s caries experience, such that dmf and DMF indices more frequently generate low or even zero counts. This article specifically reviews the application of ZI Poisson and ZI negative binomial regression models to dental caries, with emphasis on the description of the models and the interpretation of fitted model results given the study goals. The review finds that interpretations provided in the published caries research are often imprecise or inadvertently misleading, particularly with respect to failing to discriminate between inference for the class of susceptible persons defined by such models and inference for the sampled population in terms of overall exposure effects. Recommendations are provided to enhance the use as well as the interpretation and reporting of results of count regression models when applied to epidemiological studies of dental caries.
Joint Inference for Bilingual Semantic Role Labeling

We show that jointly performing semantic role labeling (SRL) on bitext can improve SRL results on both sides. In our approach, we use monolingual SRL systems to produce argument candidates for predicates in bitext at first. Then, we simultaneously generate SRL results for two sides of bitext using our joint inference model. Our model prefers the bilingual SRL result that is not only reasonable on each side of bitext, but also has more consistent argument structures between two sides. To evaluate the consistency between two argument structures, we also formulate a log-linear model to compute the probability of aligning two arguments. We have experimented with our model on Chinese-English parallel Prop-Bank data. Using our joint inference model, F1 scores of SRL results on Chinese and English text achieve 79.53% and 77.87% respectively, which are 1.52 and 1.74 points higher than the results of baseline monolingual SRL combination systems respectively.
Reasoning about context and engineering context-aware agents

A context-aware agent adapts to its human user’s context—a snapshot of the user’s environment, actions, and interactions. Engineering such agents is nontrivial. A contextaware agent must (1) capture its user’s mental model of context—a high-level concern centered on meaning, and (2) learn to recognize contexts from sensor data—a low-level concern centered on devices and infrastructure. This thesis develops: Xipho: an agent-oriented methodology that assists a developer in systematically modeling a context-aware agent via cognitive constructs, and Platys: a middleware that (1) elicits a subjective context model for each user, (2) learns the context model from sensor data, and (3) shares the user’s context across multiple agents in a privacy-preserving manner.
Successful Physician-Hospital Integration in Rural Areas

Objectives. During the 1990s hospitals competed to acquire physician practices. Those competitive bidding wars could have pushed the price of practices beyond the value obtained by gaining influence over physicians. This paper examines how hospital location and competition for physician practices affects the profitability of physician-hospital integration in rural areas. Materials and Methods. Eight years of data covering 338 rural hospitals are used to test whether the acquisition of physician practices is more successful in more isolated, uncompetitive rural markets than in competitive rural markets. A hospital without a competitor within a 15-mile radius is deemed to operate in an uncompetitive market. Success is measured by shifts in admissions, lengths of stay, and overall profitability following the acquisition of a physician practice. Results. Hospitals in uncompetitive rural markets that acquired practices showed decreased lengths of stay and increased admissions with no reduction in profitability. Hospitals in more competitive rural markets that acquired practices showed a decrease in profitability. Conclusions. Integration was a more profitable strategy for isolated rural hospitals than for hospitals with nearby competitors. Although further research is needed to determine if these results are due to the affect of competition on the cost of acquiring and operating practices, isolated rural hospitals should be open to the prospect of acquiring physician practices. Hospitals in competitive markets should be cautious about entering bidding wars for physician practices.
Estimating and Testing Models with Many Treatment Levels and Limited Instruments

Abstract Empirical researchers interested in the causal effect of the endogenous regressor often use instrumental variables. When few valid instruments are available, they typically estimate restricted specifications that impose uniform per unit treatment effects, even when these effects are likely to vary. We show that in these cases, ordinary least squares and instrumental variables estimators identify different weighted averages of all per unit effects, so the traditional Hausman test is uninformative about endogeneity. We develop a new exogeneity test that works even when the true model cannot be estimated using IV methods as long as a single valid instrument is available. We revisit three recent empirical examples to demonstrate the practical value of our test.
Data-Oriented Methods for Grapheme-to-Phoneme Conversion

It is traditionally assumed that various sources of linguistic knowledge and their interaction should be formalised in order to be able to convert words into their phonemic representations with reasonable accuracy. We show that using supervised learning techniques, based on a corpus of transcribed words, the same and even better performance can be achieved, without explicit modeling of linguistic knowledge.In this paper we present two instances of this approach. A first model implements a variant of instance-based learning, in which a weighed similarity metric and a database of prototypical exemplars are used to predict new mappings. In the second model, grapheme-to-phoneme mappings are looked up in a compressed text-to-speech lexicon (table lookup) enriched with default mappings. We compare performance and accuracy of these approaches to a connectionist (backpropagation) approach and to the linguistic knowledge-based approach.
Optimization of routing, network coding and scheduling in wireless multicast ad-hoc networks with topology compression

In this paper, we present new methodology and results for joint routing and link scheduling optimization in multicast wireless ad-hoc networks. The impact of multicast diversity on scheduling is controlled by using topology compression concept quantified through compressed multicast topology matrix. To define topology matrix, first a set of all possible multicast paths, including network coded paths, is identified. A subset of these paths with appropriate rates is chosen to maximize achievable throughput or throughput per sum of transmitting powers on the route, in a conflict free environment created by proper scheduling. Therefore this optimization provides two improvement gains, throughput gain from scheduling on a compressed network topology and the gain from mixed path selection optimizations with a careful compromise between the multicast diversity and network coding. Numerical results, as illustration, are presented for a simple wireless butterfly network. If just throughput regardless of power consumption is maximized, then depending on the system parameters both a network coded structure or a plain routing can be optimum. On the other hand if throughput per power is maximized, a mixed set of plain routing paths is the optimum solution.
Joint Optimization of Power and Filter-and-Forward Beamforming in Cognitive Networks with Frequency Selective Channels

In this paper, we propose a filter-and-forward (FF)beamforming strategy in the secondary relays for the one-way cognitive relay network with frequency selective fading channels. Our aim is to optimize the beamforming coefficients and the secondary transmitted power to maximize the SINR at the secondary destination, while satisfying the interference constraint on the primary network and the total relays' transmitted power restriction. To solve this problem, we propose a two-step iterative algorithm. Simulation results show that comparing the amplifyand-forward (AF) strategy, the filter-and-forward strategy (FF) can get higher SINR at the secondary destination by using the algorithm that we proposed.
Search, Explore and Navigate : Designing a Next Generation Knowledge Media Workbench

Information work is a demanding activity caused by the increasing complexity of today's information spaces. Besides, information workers are acting correspondingly to their creative workflow, which involves multifaceted characteristics like diverse activities, locations and environments. Although it is important to find solutions to specific aspects of information work (information-seeking, information-management, media-warehousing, etc.) our design approach - MedioVis 2.0 - tries to support the entire workflow in one coalescing Knowledge Media Workbench, showcased in the context of digital libraries. To achieve this goal, we apply the concept of zoomable user interfaces, different visualization techniques and investigate additional considerations to provide a satisfying user experience.
Optimal Tracking of Time-Varying Channels: A Frequency Domain Approach for Known and New Algorithms

In this paper, we developed a systematic frequency domain approach to analyze adaptive tracking algorithms for fast time-varying channels. The analysis is performed with the help of two new concepts, a tracking filter and a tracking error filter, which are used to calculate the mean square identification error (MSIE). First, we analyze existing algorithms, the least mean squares (LMS) algorithm, the exponential windowed recursive least squares (EW-RLS) algorithm and the rectangular windowed recursive least squares (RW-RLS) algorithm. The equivalence of the three algorithms is demonstrated by employing the frequency domain method. A unified expression for the MSIE of all three algorithms is derived. Secondly, we use the frequency domain analysis method to develop an optimal windowed recursive least squares (OW-RLS) algorithm. We derive the expression for the MSIE of an arbitrary windowed RLS algorithm and optimize the window shape to minimize the MSIE. Compared with an exponential window having an optimized forgetting factor, an optimal window results in a significant improvement in the h MSIE. Thirdly, we propose two types of robust windows, the average robust window and the minimax robust window. The RLS algorithms designed with these windows have near-optimal performance, but do not require detailed statistics of the channel. >
SmartFarm : Improving Agriculture Sustainability Using Modern Information Technology

In this paper, we overview our ongoing work on an open source, hybrid cloud approach to agriculture analytics for enabling sustainable farming practices. SmartFarm integrates disparate environmental sensor technologies into an on-farm, private cloud software infrastructure that provides farmers with a secure, easy to use, low-cost data analysis system. SmartFarm couples data from external cloud sources (weather predictions, satellite imagery, state and national datasets, etc) with farm-local statistics, provides an interface into which custom analytics apps can be plugged, and ensures that all private data remain under the control of farmers.
Screening for carcinoma in situ in the contralateral testicle in patients with testicular cancer: a population-based study.

BACKGROUND Screening programmes for contralateral carcinoma in situ (CIS) testis in patients with unilateral germ-cell cancer (GCC) have never been evaluated. We investigated the effect of screening for contralateral CIS in a large nation-wide, population-based study. PATIENTS AND METHODS A contralateral single-site biopsy was offered to 4130 patients in whom GCC had been diagnosed in 1984-2007 (screened cohort); 462 patients in whom GCC was diagnosed in 1984-1988 comprised the unscreened cohort. Cases with CIS were offered radiotherapy. Initially CIS-negative biopsies in patients with metachronous GCC were revised according to today's standards. Risk for metachronous GCC was estimated using cumulative incidence and the Cox proportional hazards model. RESULTS In the screened cohort, contralateral CIS was found in 181 (4.4%) patients. The cumulative incidence of metachronous GCC after 20 years was 1.9% in the screened cohort and 3.1% in the unscreened cohort (P = 0.097), hazard ratio (HR) for the unscreened cohort: 1.59 (P = 0.144). Expert revision with contemporary methodology of CIS-negative biopsy samples from patients with metachronous cancer revealed CIS in 17 out of 45 (38%) cases. Decreased risks for metachronous GCC were related to older age at diagnosis (HR 0.52 per 10 years, P < 0.001) and chemotherapy (HR 0.35, P = 0.002). Limitations include the small number of patients in the unscreened cohort and the retrospective study design. CONCLUSIONS Our evaluation of a national population-based screening programme for contralateral CIS in patients with testicular cancer showed no significant difference in the risk for metachronous GCC between a screened and an unscreened cohort. Single-site biopsy including modern immunohistochemistry does not identify all cases of CIS.
Speech-Recognition Interfaces for Music Information Retrieval: 'Speech Completion' and 'Speech Spotter'

This paper describes music information retrieval (MIR) systems featuring automatic speech recognition. Although various interfaces for MIR have been proposed, speech-recognition interfaces suitable for retrieving musical pieces have not been studied. We propose two different speech-recognition interfaces for MIR, speech completion and speech spotter, and describe two MIR-based hands-free jukebox systems that enable a user to retrieve and play back a musical piece by saying its title or the artist’s name. The first is a music-retrieval system with the speech-completion interface that is suitable for music stores and car-driving situations. When a user can remember only part of the name of a musical piece or an artist and utters only a remembered fragment, the system helps the user recall and enter the name by completing the fragment. The second is a background-music playback system with the speech-spotter interface that can enrich human-human conversation. When a user is talking to another person, the system allows the user to enter voice commands for music-playback control by spotting a special voice-command utterance in face-to-face or telephone conversations. Our experimental results from use of these systems have demonstrated the effectiveness of the speech-completion and speech-spotter interfaces.
Semantic trajectory compression: Representing urban movement in a nutshell

There is an increasing number of rapidly growing repositories capturing the movement of people in space-time. Movement trajectory compression becomes an ob- vious necessity for coping with such growing data volumes. This paper introduces the concept of semantic trajectory compression (STC). STC allows for substantially compressing trajectory data with acceptable information loss. It exploits that human urban mobility typically occurs in transportation networks that define a geographic context for the move- ment. In STC, a semantic representation of the trajectory that consists of reference points localized in a transportation network replaces raw, highly redundant position information (e.g., from GPS receivers). An experimental evaluation with real and synthetic trajectories demonstrates the power of STC in reducing trajectories to essential information and illus- trates how trajectories can be restored from compressed data. The paper discusses possible application areas of STC trajectories.
Grammars and cellular automata for evolving neural networks architectures

The class of feedforward neural networks trained with back-propagation admits a large variety of specific architectures applicable to approximation pattern tasks. Unfortunately, the architecture design is still a human expert job. In recent years, the interest to develop automatic methods to determine the architecture of the feedforward neural network has increased, most of them based on the evolutionary computation paradigm. From this approach, some perspectives can be considered: at one extreme, every connection and node of architecture can be specified in the chromosome representation using binary bits. This kind of representation scheme is called the direct encoding scheme. In order to reduce the length of the genotype and the search space, and to make the problem more scalable, indirect encoding schemes have been introduced. An indirect scheme under a constructive algorithm, on the other hand, starts with a minimal architecture and new levels, neurons and connections are added, step by step, via some sets of rules. The rules and/or some initial conditions are codified into a chromosome of a genetic algorithm. In this work, two indirect constructive encoding schemes based on grammars and cellular automata, respectively, are proposed to find the optimal architecture of a feedforward neural network.
TRIM28 is required by the mouse KRAB domain protein ZFP568 to control convergent extension and morphogenesis of extra-embryonic tissues

TRIM28 is a transcriptional regulator that is essential for embryonic development and is implicated in a variety of human diseases. The roles of TRIM28 in distinct biological processes are thought to depend on its interaction with factors that determine its DNA target specificity. However, functional evidence linking TRIM28 to specific co-factors is scarce. chatwo, a hypomorphic allele of Trim28, causes embryonic lethality and defects in convergent extension and morphogenesis of extra-embryonic tissues. These phenotypes are remarkably similar to those of mutants in the Krüppel-associated box (KRAB) zinc finger protein ZFP568, providing strong genetic evidence that ZFP568 and TRIM28 control morphogenesis through a common molecular mechanism. We determined that chatwo mutations decrease TRIM28 protein stability and repressive activity, disrupting both ZFP568-dependent and ZFP568-independent roles of TRIM28. These results, together with the analysis of embryos bearing a conditional inactivation of Trim28 in embryonic-derived tissues, revealed that TRIM28 is differentially required by ZFP568 and other factors during the early stages of mouse embryogenesis. In addition to uncovering novel roles of TRIM28 in convergent extension and morphogenesis of extra-embryonic tissues, our characterization of chatwo mutants demonstrates that KRAB domain proteins are essential to determine some of the biological functions of TRIM28.
Physiology and Pathology of Implantation in the Human and Nonhuman Primate

Infertility affects 10 to 15% of the general population, and although advances in assisted reproductive therapies have had a major input, pregnancy rates continue to be relatively low. This has lead to an increasing interest in understanding the interaction between the embryo and the endometrium during the window of implantation. Multiple experimental approaches have been used to evaluate the morphological, cellular, and molecular changes in the endometrium during the normal menstrual cycle and as a consequence of numerous benign gynecological diseases that contribute to infertility. Successful implantation requires interplay between the embryo and the endometrium during a very narrow window of time within the menstrual cycle. Given that there are limitations to evaluating this intricate dialog in the human, nonhuman primates serve as a valuable model by which to obtain insights into this critical period of uterine receptivity. Articles in this issue provide a comprehensive summary of approaches to understand the complex biology that is required for successful implantation, and the potential adverse consequences of ovarian hyperstimulation and benign gynecological diseases on uterine receptivity and embryo implantation.
Runtime identification of microprocessor energy saving opportunities

High power consumption and low energy efficiency have become significant impediments to future performance improvements in modern microprocessors. This paper contributes to the solution of these problems by presenting: linear regression models for power consumption and a detailed study of energy efficiency in a modern out-of-order superscalar microprocessor. These simple (2-input) yet accurate (2.6% error) models provide a valuable tool for identifying opportunities to apply power saving techniques such as clock throttling and dynamic voltage scaling (DVS). Also, future work in improving energy efficiency is motivated by a detailed analysis of SPEC CPU 2000 workloads. The vast majority of workloads are found to yield very low energy efficiency due to the frequency of level two (L2) cache misses and misspeculated instructions.
Quantitative Assessment of Seven Transmembrane Receptors (7TMRs) Oligomerization by Bioluminescence Resonance Energy Transfer (BRET) Technology

Seven transmembrane receptors (7TMRs; also designated as G-protein coupled receptors (GPCRs)) form the largest and evolutionarily well conserved family of cell-surface receptors, with more than 800 members identified in the human genome. 7TMRs are the targets both for a plethora of endogenous ligands (e.g. peptides, glycoproteins, lipids, amino acids, nucleotides, neurotransmitters, odorants, ions, and photons) and therapeutic drugs and transduce extracellular stimuli into intracellular responses mainly via coupling to guanine nucleotide binding proteins (G-proteins) (McGraw & Liggett, 2006).
Deprem Yaşayan ve Yaşamayan Okul öncesi Çocukların Davranışsal/Duygusal Sorunlarının Karşılaştırmalı Olarak İncelenmesi

Bu calismada, deprem yasayan ve yasamayan okul oncesi cocuklarin davranissal/duygusal sorunlari ogretmenlerden elde edilen bilgiler dogrultusunda cinsiyet ve anne ogrenim duzeyi degiskenlerine gore karsilastirmali olarak incelenmistir. Arastirmanin orneklemini, Sultandagi (Afyon) deprem bolgesinde okul oncesi egitim kurumlarina devam eden 210 cocuk (calisma grubu) ve Ankaraâda okul oncesi egitim kurumlarina devam eden 272 cocuk (kontrol grubu) olmak uzere toplam 482 cocuk olusturmustur. Veri toplama araci olarak âOgretmen Bilgi Formu - 11/2 â"5 yas (The Caregiver-Teacher Report Form for Ages 11/2 _ 5; C-TRF / 11/2 â"5)â ve âDemografik Bilgiler Ogretmen Formuâ kullanilmistir. Analiz sonuclari, deprem deneyiminin ve anne ogrenim duzeyi degiskeninin cocuklarin davranissal/duygusal problemlerinde anlamli bir farklilik yaratmadigini ortaya koymustur. Ancak, cinsiyetin deprem deneyiminden bagimsiz olarak orneklemdeki cocuklarin sorun davranislari uzerindeki temel etkisinin anlamli oldugu bulunmustur. Ogretmenler, erkek cocuklari somatik sorunlarda, kizlari ise dikkat sorunlarinda daha sorunlu olarak degerlendirdikleri tespit edilmistir.