Miracle-dz/UniFAR-FTUs huggingface dataset:
A data-driven model for wind plant power optimization by yaw control

This paper presents a novel parametric model that will be used to optimize the yaw settings of wind turbines in a wind plant for improved electrical energy production of the whole wind plant. The model predicts the effective steady-state flow velocities at each turbine, as well as the resulting electrical energy productions, as a function of the axial induction and the yaw angle of the different rotors. The model has a limited number of parameters that are estimated based on data. Moreover, it is shown how this model can be used to optimize the yaw settings using a game-theoretic approach. In a case study we demonstrate that our novel parametric model fits the data generated by a high-fidelity computational fluid dynamics model of a small wind plant, and that the data-driven yaw optimization control has great potential to increase the wind plant's electrical energy production.
Three Essays on the Economics of Controlling Mobile-Source Episodic Air Pollution

Three Essays on the Economics of Controlling Mobile-Source Episodic Air Pollution by Ramjee Acharya, Doctor of Philosophy Utah State University, 2018 Major Professor: Dr. Arthur Caplan Department: Applied Economics For the first two essays we adopt Berry et al.’s (2015) disease-outbreak model to estimate the optimal preventative capital stock necessary to control episodic, wintertime air pollution in Cache County and the Wasatch Front, Utah, respectively. To calibrate the model we empirically estimate the endogenous background risk of elevated PM2.5 concentration levels controlling for a host of pertinent weather-related variables, including snowfall, snow depth, and humidity levels, as well as wind speed and temperature gradient between the respective valley floors and neighboring mountain peaks. This calibration exercise also entails empirical estimation of the hazard associated with PM2.5 concentrations breaching the 24-hour-averaged NAAQS (National Ambient Air Quality Standard) in each of these regions when controlling for the same weather variables and region-wide vehicle trip counts. Matlab simulations of the empirically calibrated model result in estimates of optimal preventative capital stocks ranging from $4.1 to $14.1 million in Cache County, and $133 million to $1.6 billion dollars in Wasatch Front. Annually
BF design in cognitive relay networks via support vector machines

In this paper, we address the problem of beamforming (BF) design in a cognitive relay network (CRN), where the cognitive network not only shares the spectrum with the primary one but also acts as a relay to assist the primary signal transmission. Considering that all of the wireless channels are subject to the correlated Rayleigh fading distribution, we first formulate a constrained optimization problem to minimize the total transmit power of the cognitive base station (CBS) with multiple antennas, while guaranteeing the quality-of-service (QoS) of the primary and secondary users and keeping the mutual interference below an acceptable level. Then, by adopting the available partial channel state information (CSI), and proposing an approximation method to relax the constraints, a support vector machine (SVM) based algorithm is presented to solve the optimization problem for the BF weight vectors. The benefit of the new approach is that the slow change of the partial CSI can be taken into account. Finally, computer simulation results are provided to confirm the superiority of the proposed BF design strategy.
Exploiting Unlabeled Text to Extract New Words of Different Semantic Transparency for Chinese Word Segmentation

This paper exploits unlabeled text data to improve new word identiﬁcation and Chinese word segmentation performance. Our contributions are twofold. First, for new words that lack semantic trans-parency, such as person, location, or transliteration names, we calculate association metrics of adjacent character segments on unlabeled data and encode this information as features. Second, we construct an internal dictionary by using an initial model to extract words from both the unlabeled training and test set to maintain balanced coverage on the training and test set. In comparison to the baseline model which only uses n -gram features, our approach increases new word recall up to 6.0%. Additionally, our approaches reduce segmentation errors up to 32.3%. Our system achieves state-of-the-art performance for both the closed and open tasks of the 2006 SIGHAN bakeoﬀ.
Report on the ad-hoc track of the INEX 2005 workshop

The INitiative for the Evaluation of XML retrieval (INEX) has, since 2002, been working towards the goal of establishing an infrastructure, in the form of a large XML test collection and appropriate scoring methods, for the evaluation of content-oriented XML retrieval systems. In 2005, 47 organizations registered to participate in INEX. Throughout the year a number of groups dropped out due to resource requirements, while 11 further groups joined. INEX 2005 concluded with a total of 41 active groups. In addition to the main ad-hoc retrieval track, six further research tracks were included in INEX 2005, each studying different aspects of XML information access: interactive, relevance feedback, heterogeneous, natural language processing, and two new tracks for 2005, multimedia and document mining tracks.
Mirinae: A peer-to-peer overlay network for large-scale content-based publish/subscribe systems

Content-based publish/subscribe systems provide a useful alternative to traditional address-based communication due to their ability to decouple communication between participants. It has remained a challenge to design a scalable overlay supporting the complexity of content-based networks, while satisfying the desirable properties large distributed systems should have. This paper presents the design of Mirinae, a new structured peer-to-peer overlay mesh based on the interests of peers. Given an event, Mirinae provides a flexible and efficient dissemination tree minimizing the participation of non-matching nodes. We also present a novel ID space transformation mechanism for balancing routing load of peers even with highly skewed data, which is typical of the real world. Mirinae can be used as a substrate for content-search and range query in other important distributed applications.
Online Writer-Independent Character Recognition Using a Novel Relational Context Representation

Transforming handwriting into digital text and recognition of handwritten patterns opens a vast scope of application opportunities from searching for handwritten notes and document management to causing actions by writing symbols. Despite receiving a great attention, a massive number of applications, and a huge research effort, recognition of handwritten text has not still reached a desired efficiency and is an active area of research. One of the most important factors that makes handwriting recognition a challenging task is the huge variety of writing styles which can not be captured efficiently through available classification methods using current feature descriptors. Our approach to gain performance in online character recognition is to design more representative features for handwritten character representation in order to tackle the huge inter-class variability problem and increase recognition accuracy. The representation can also be used in recognition of other online planar patterns. The experimental results show that proposed representation with SVM classifier outperforms best reported recognition rates for Arabic characters in a writer-independent system.
Conserved ‘Hypothetical’ Proteins: New Hints and New Puzzles

Conserved hypothetical proteins, i.e. conserved proteins whose functions are still unknown, pose a challenge not just to functional genomics but also to general biology. For many conserved proteins, computational analysis provides only a general prediction of biochemical function; their exact biological functions have to be established through direct experimentation. In the few cases when this has been accomplished, the results were remarkable, revealing the deoxyxylulose pathway and a new essential enzyme, the ITP pyrophosphatase. Comparative genome analysis is also instrumental in illuminating unsolved problems in biology, e.g. the mechanism of FtsZ-independent cell division in Chlamydia, Ureaplasma and Aeropyrum or the role of uncharacterized conserved domains in signal transduction.
First-principles quantum dynamics for fermions: Application to molecular dissociation

We demonstrate that the quantum dynamics of a many-body Fermi-Bose system can be simulated using a Gaussian phase-space representation method. In particular, we consider the application of the mixed fermion-boson model to ultracold quantum gases and simulate the dynamics of dissociation of a Bose-Einstein condensate of bosonic dimers into pairs of fermionic atoms. We quantify deviations of atom-atom pair correlations from Wick's factorization scheme, and show that atom-molecule and molecule-molecule correlations grow with time, in clear departures from pairing mean-field theories. As a first-principles approach, the method provides benchmarking of approximate approaches and can be used to validate dynamical probes for characterizing strongly correlated phases of fermionic systems.
Resilient user interface level tests

About 60% of the software development cost for online applications is related to developing user interfaces commonly used by the end users to interact with those applications. Frequent small changes to user interfaces (UIs) however easily break about 70% of the test cases intended to mimic users' interactions. Fixing broken tests results in extra costs of maintenance while lessening the benefits of test automation. One of the biggest challenges in creating resilient UI level test cases is to identify and locate the elements of the UI in a way that small UI changes do not break the way in which an element was originally located. In this paper, we present our early efforts in creating a test development framework that makes test cases independent of the internal structure of the UIs, so that a change in the structure does not break any test as long as the functionalities validated in the test are not changed. Our approach is inspired by the way human interact with the UIs of online applications and how those interactions are described and communicated in natural language to others. Visual landmarks such as texts (via a perceptual activity) help end users to locate their points of interest during their interaction with the application in a way that is independent of the internal structure of application.
SPA: Symbolic Program Approximation for Scalable Path-sensitive Analysis

Symbolic execution is a static-analysis technique that has been used for applications such as test-input generation and change analysis. Symbolic execution’s path sensitivity makes scaling it difficult. Despite recent advances that reduce the number of paths to explore, the scalability problem remains. Moreover, there are applications that require the analysis of all paths in a program fragment, which exacerbate the scalability problem. In this paper, we present a new technique, called Symbolic Program Approximation (SPA), that performs an approximation of the symbolic execution of all paths between two program points by abstracting away certain symbolic subterms to make the symbolic analysis practical, at the cost of some precision. We discuss several applications of SPA, including testing of software changes and static invariant discovery. We also present a tool that implements SPA and an empirical evaluation on change analysis and testing that shows the applicability, effectiveness, and potential of our technique.
Unsupervised Sub-tree Alignment for Tree-to-Tree Translation

This article presents a probabilistic sub-tree alignment model and its application to tree-to-tree machine translation. Unlike previous work, we do not resort to surface heuristics or expensive annotated data, but instead derive an unsupervised model to infer the syntactic correspondence between two languages. More importantly, the developed model is syntactically-motivated and does not rely on word alignments. As a by-product, our model outputs a sub-tree alignment matrix encoding a large number of diverse alignments between syntactic structures, from which machine translation systems can efficiently extract translation rules that are often filtered out due to the errors in 1-best alignment. Experimental results show that the proposed approach outperforms three state-of-the-art baseline approaches in both alignment accuracy and grammar quality. When applied to machine translation, our approach yields a +1.0 BLEU improvement and a -0.9 TER reduction on the NIST machine translation evaluation corpora. With tree binarization and fuzzy decoding, it even outperforms a state-of-the-art hierarchical phrase-based system.
The Effect of Oral L-glutamine on the Healing of Second-degree Burns in Mice.

UNLABELLED ﻿﻿﻿﻿﻿ ﻿Background. The effect of oral L-glutamine on wound healing in two groups of mice with superficial second-degree burns was evaluated. METHODS Thirty (30) male mice were included and randomly divided into two groups. First, the mice underwent general anesthesia, then an iron plate heated to 80˚C was placed on each animal's skin for 1 second to create a second-degree burn injury. The test group mice received glutamine powder (1 g/kg/day) dissolved in water; the control group did not receive this supplementation. The variables were weight, burn wound surface area (cm3), wound contraction, and wound healing percentage on days 7, 10, 13, 16, 19, and 22. Serum levels of albumin, urea, and creatinine were assayed on days 1 and 22. RESULTS There was no significant difference between the groups regarding weight or serum albumin, urea, and creatinine levels. However, mean wound contraction was significant between the groups on days 7, 10, 13, 16, 19, and 22. Complete wound healing (100%) was achieved on day 22 in the test group compared to 71% healing in the control group. CONCLUSION A significant and positive effect of oral glutamine on burn wound healing was found. However, further research is necessary in order to understand which stage of the healing process glutamine supplementation affected ﻿﻿﻿.
Association of the Cyclin D 1 A 870 G Polymorphism With Advanced Colorectal Cancer

CYCLIN D1 (CCND1) IS A KEY regulatory protein of the cell cycle, promoting the transition through the restriction point in the G1 phase beyond which the cell is committed to divide. Overexpression of the CCND1 gene, which has been shown to occur in 30% to 50% of breast and colorectal cancers, has been associated with increased cell proliferation and poor prognosis for a number of human malignancies, including colorectal cancer. A common adenine-to-guanine (A/G) substitution at nucleotide 870 in the conserved splice donor region of exon 4 has been shown to modulate splicing of CCND1 messenger RNA. The G allele preferentially splices transcript a, whereas the A allele mainly splices transcript b, which encodes a protein with a longer half-life. The A allele has been associated with poor prognosis for several cancers and with increased risk of colorectal cancer in hereditary nonpolyposis colorectal cancer families, as well as in 2 small hospital-based casecontrol studies. Because the A allele is common and may preferentially affect progression, it is important to further clarify its association with colorectal cancer, a neoplasm that is particularly difficult to cure once it has spread outside the intestines. We investigated the association of the CCND1 870A allele with colorectal cancer in a population-based case-control study originally conducted to test gene-diet interactions in the multiethnic population of Hawaii.
Remote Sensing Retrieval Study of the Surface Kinetic Parameters in the Yangtze Estuary and Its Adjacent Waters

Wind and current are significant parameters in the hydrodynamic processes, making a significant effect on the expansion of the Yangtze (Changjiang River) Diluted Water, sedi ment transport, resuspension and shelf circulation in the Yangtze Estuary. They are indis - pensable as input parameters in the numerical simulation of these phenomena. Synthetic aperture radar (SAR) can acquire data with different resolutions (down to 1 m) and cov - erage (up to 400 km) over a site during day or night time under all weather conditions, being capable of providing ocean surface kinetic parameters with high resolution. SAR images were collected to verify and improve the validity of wind direction retrieval by 2D fast Fourier transformation (FFT) method, wind speed by CMOD4 model and current by Doppler frequency method. These SAR-retrieved wind and current results were analyzed and assessed against in situ data and corresponding numerically simulated surface wind and current fields. Comparisons to the in situ and simulations show that 1) SAR can mea sure sea surface wind fields with a high resolution at sub-km scales and provide a pow - erful complement to conventional wind measurement techniques. 2) The Doppler shift anomaly measurements from SAR images are able to capture quantitative surface currents, thus are helpful to reveal the multi-scale upper layer dynamics around the East China Sea.
Estimated Dietary Polyphenol Intake and Major Food and Beverage Sources among Elderly Japanese

Estimating polyphenol intake contributes to the understanding of polyphenols’ health benefits. However, information about human polyphenol intake is scarce, especially in the elderly. This study aimed to estimate the dietary intake and major sources of polyphenols and to determine whether there is any relationship between polyphenol intake and micronutrient intake in healthy elderly Japanese. First, 610 subjects (569 men, 41 women; aged 67.3 ± 6.1 years) completed food frequency questionnaires. We then calculated their total polyphenol intake using our polyphenol content database. Their average total polyphenol intake was 1492 ± 665 mg/day, the greatest part of which was provided by beverages (79.1%). The daily polyphenol intake differed largely among individuals (183–4854 mg/day), also attributable mostly to beverage consumption. Coffee (43.2%) and green tea (26.6%) were the major sources of total polyphenol; the top 20 food items accounted for >90%. The polyphenol intake did not strongly correlate with the intake of any micronutrient, suggesting that polyphenols may exert health benefits independently of nutritional intake. The polyphenol intake in this elderly population was slightly higher than previous data in Japanese adults, and beverages such as coffee and green tea contributed highly to the intake.
POS Tagger Combinations on Hungarian Text

In this paper we will briefly survey the key results achieved so far in Hungarian POS tagging and show how classifier combination techniques can aid the POS taggers. Methods are evaluated on a manually annotated corpus containing 1.2 million words. POS tagger tests were performed on single-domain, multiple domain and cross-domain test settings, and, to improve the accuracy of the taggers, various combination rules were implemented. The results indicate that combination schemas (like the Boosting algorithm) are promising tools which can significantly degrade the classification errors, and produce a more effective tagger application.
Estimating Equivalent Kernels for Neural Networks: A Data Perturbation Approach

We describe the notion of "equivalent kernels" and suggest that this provides a framework for comparing different classes of regression models, including neural networks and both parametric and non-parametric statistical techniques. Unfortunately, standard techniques break down when faced with models, such as neural networks, in which there is more than one "layer" of adjustable parameters. We propose an algorithm which overcomes this limitation, estimating the equivalent kernels for neural network models using a data perturbation approach. Experimental results indicate that the networks do not use the maximum possible number of degrees of freedom, that these can be controlled using regularisation techniques and that the equivalent kernels learnt by the network vary both in "size" and in "shape" in different regions of the input space.
Common HLA Alleles Associated with Health, but Not with Facial Attractiveness

Three adaptive hypotheses have been proposed to explain the link between the human leucocyte antigen (HLA) genes, health measures and facial attractiveness: inbreeding avoidance, heterozygote advantage and frequency-dependent selection. This paper reports findings that support a new hypothesis relating HLA to health. We suggest a new method to quantify the level of heterozygosity. HLA heterozygosity did not significantly predict health measures in women, but allele frequency did. Women with more common HLA alleles reported fewer cold and flu bouts per year, fewer illnesses in the previous year and rated themselves healthier than women with rare alleles. To our knowledge, this is the first study to show a positive correlation between HLA allele frequency and general health measures. We propose that certain common HLA alleles confer resistance to prevalent pathogens. Nevertheless, neither HLA heterozygosity nor allele frequency significantly predicted how healthy or attractive men rated the female volunteers. Three non-mutually exclusive explanations are put forward to explain this finding.
Ambient noise tomography at the Oseberg oil and gas field, North sea

Recent studies show that the noise recorded by seismic sensors can be used to characterize the seismic structure in the area where the sensors are located. This is called ambient noise tomography. In this thesis, data from ocean bottom cables at the Oseberg oil and gas field was used to characterize the near-surface in an area used for waste disposal. 32 days of data was made available to us from Equinor (Statoil). By using interferometry, we created virtual sources by taking the cross-correlation between ambient noise recordings made at different stations. Through slowness-frequency analysis, the dispersion curves of surface waves were retrieved from the noise correlations, and inverted to explore the shear wave velocity with depth. The platform is a major source of noise in the area. Below 2 Hz, we have noise coming from all directions. Above 2 Hz, the main source is the platform. Since the array of stations is made mostly of 4 lines in line with the platform, both the noise coming from all directions and the noise coming from the platform was used. The ambient noise with frequencies up to 4 Hz was used for Green’s function retrieval, and we see that eight hours of data is sufficient for retrieving the Green’s functions. No major change with time was observed, and the Green’s functions along the 4 lines are very similar. The Love wave and the Scholte wave fundamental mode and overtone emerged from the cross-correlations of ambient noise. The Scholte wave fundamental mode was used for inversion, and a model of S-wave velocity with depth down to 3000 m was obtained. The velocity increases from 300 m/s at the sea bottom to about 1700 m/s at 3 km depth, similar to the results retrieved from other methods.