Miracle-dz/UniFAR-FTUs huggingface dataset:
Endoscopography : Deriving a 3 D Textured Surface from Endoscopic Video , Then Registration with CT

Endoscopy [1] enables high-resolution visualization of tissue texture and is a critical step in many clinical workflows, including diagnosis and treatment planning for cancers in the nasopharynx. However, an endoscopic video does not provide its information in 3D space, making it difficult to use in tumor localization, and it is inefficient to review. We present a new imaging approach that we call endoscopography. Endoscopography reconstructs a full 3D textured surface, which we call an endoscopogram, from an endoscopic video. This endoscopogram opens the door for novel 3D visualizations of patient anatomy derived solely from endoscopic data. It also allows information contained in the tissue texture in the endoscopogram to be transferred to 3D image such as CT through a surface-to-surface registration. In particular, through an interactive tool, the physician can draw directly on the endoscopogram surface to specify a tumor, which then can be automatically transferred to CT slices to aid tumor localization. We describe the sequence of methods we have designed to achieve this goal. Through evaluations on synthethic, phantom, and patient data, we demonstrate that our surface reconstruction method can obtain accurate results within millimeters of ground-truth, and our registration approach can handle tissue deformations and reconstruction inconsistencies across endoscopic video frames.
Assessment of Collaborative Problem Solving in Engineering Students Through Hands-On Simulations

Contribution: This article discusses the use of manufacturing simulation games to study collaborative problem-solving skills in engineering students. The simulation represents the mass production paradigm in which large quantities of identical products are produced. Empirical data is collected from the simulation to evaluate the skills engineering students used in solving the problem and their group effectiveness. Background: The use of simulation games to teach problem solving in design and manufacturing is an effective approach to convey concepts to students. Simulation games engage students in experiential and collaborative learning with fun elements. Research Questions: How does hands-on simulation engage students in collaborative problem solving? How does participation in collaborative problem solving affect group effectiveness? Methodology: This work presents a study of 37 university-level engineering students in the United States. Participants worked in groups completing the simulation game and responded to surveys on their various skills used. Findings: Participants utilized analytical, metacognitive, and thinking skills in their engagement, reported that the simulation games enhanced their understanding of manufacturing concepts and active collaboration improved problem-solving effectiveness.
Hyeongki Kim Dihedral angle prediction using generative adversarial networks

Several dihedral angles prediction methods were developed for protein structure prediction and their other applications. However, distribution of predicted angles would not be similar to that of real angles. To address this we employed generative adversarial networks (GAN) which showed promising results in image generation tasks. Generative adversarial networks are composed of two adversarially trained networks: a discriminator and a generator. A discriminator is trained to distinguish between samples from a dataset and generated samples while a generator is trained to generate realistic samples. Although the discriminator of GANs is trained to estimate density, the explicit density of the model is not tractable. On the other hand, noise-contrastive estimation (NCE) was introduced to estimate a normalization constant of an unnormalized statistical model and thus the density function. In this thesis, we introduce noise-contrastive estimation generative adversarial networks (NCE-GAN) which enables explicit density estimation of the generative adversarial networks by feeding noise samples from a known distribution, like noise-contrastive estimation, and adding a corresponding class for the discriminator. We analyzed the minibatch discrimination and new loss for the generator is proposed. We also propose residue-wise variants of auxiliary classifier GAN (AC-GAN) and Semi-supervised GAN to handle sequence information in a window. In our experiment, the conditional generative adversarial network (C-GAN), AC-GAN and Semi-supervised GAN were compared. And experiments done with improved conditions were invested. We identified a phenomenon of AC-GAN that distribution of its predicted angles is composed of unusual clusters. The distribution of the predicted angles of Semi-supervised GAN was most similar to the Ramachandran plot. We found that adding the output of the NCE as an additional input of the discriminator is helpful to stabilize the training of the GANs and to capture the detailed structures. However, using the newly proposed loss in the generator were only helpful in C-GAN and AC-GAN. Adding regression loss to the object of the generator and using predicted angles by regression loss only model as an additional input of the generator could improve the conditional generation performance of the C-GAN and AC-GAN.
The electronic ballot box : class, age and racial bias on the Internet.

This Article is brought to you for free and open access by ThinkIR: The University of Louisville's Institutional Repository. It has been accepted for inclusion in Faculty Scholarship by an authorized administrator of ThinkIR: The University of Louisville's Institutional Repository. For more information, please contact thinkir@louisville.edu. Original Publication Information This article was originally published in American Review of Politics, volume 28, in 2007.
An artificial neural network for redundant robot inverse kinematics computation

Title of Thesis : An Artificial Neural Network for Redundant Robot Inverse Kinematics Computation Name of Candidate : Wibawa Utama, Master of Science, 1990. Thesis Directed By : Dr. Edwin S. H. Hou, Assistant Professor Department of Electrical & Computer Engineering A redundant manipulator can be defined as a manipulator that has more degrees of freedom than necessary to determine the position and orientation of the end effector. Such a manipulator has dexterity, flexibility, and the ability to maneuver in presence of obstacles. One important and necessary step in utilizing a redundant robot is to relate the joint coordinates of the manipulator with the position and orientation of the end-effector. This specification is termed as the direct kinematics problem and can be where x is a vector representing the position and orientation of the end-effector, q is the joint vector, and f is a continuous non-linear function defined by the design of the manipulator. The inverse kinematics problem can be stated as: Given a position and orientation of the end-effector, determine the joint vector that specifies this position For non-trivial designs, f' cannot be expressed analytically. This paper presents a solution to the inverse kinematics problem for a redundant robot based on multilayer feed-forward artificial neural network.
Ferrian saponite from the Santa Monica Mountains (California, U.S.A., Earth): Characterization as an analog for clay minerals on Mars with application to Yellowknife Bay in Gale Crater

Abstract Ferrian saponite from the eastern Santa Monica Mountain, near Griffith Park (Los Angeles, California), was investigated as a mineralogical analog to smectites discovered on Mars by the CheMin X-ray diffraction instrument onboard the Mars Science Laboratory (MSL) rover. The martian clay minerals occur in sediment of basaltic composition and have 02l diffraction bands peaking at 4.59 Å, consistent with tri-octahedral smectites. The Griffith saponite occurs in basalts as pseudomorphs after olivine and mesostasis glass and as fillings of vesicles and cracks and has 02l diffraction bands at that same position. We obtained chemical compositions (by electron microprobe), X-ray diffraction patterns with a lab version of the CheMin instrument, Mössbauer spectra, and visible and near-IR reflectance (VNIR) spectra on several samples from that locality. The Griffith saponite is magnesian, Mg/(Mg+SFe) = 65-70%, lacks tetrahedral Fe3+ and octahedral Al3+, and has Fe3+/SFe from 64 to 93%. Its chemical composition is consistent with a fully tri-octahedral smectite, but the abundance of Fe3+ gives a nominal excess charge of +1 to +2 per formula unit. The excess charge is likely compensated by substitution of O2- for OH-, causing distortion of octahedral sites as inferred from Mössbauer spectra. We hypothesize that the Griffith saponite was initially deposited with all its iron as Fe2+ and was oxidized later. X‑ray diffraction shows a sharp 001 peak at 15 Å, 00l peaks, and a 02l diffraction band at the same position (4.59 Å) and shape as those of the martian samples, indicating that the martian saponite is not fully oxidized. VNIR spectra of the Griffith saponite show distinct absorptions at 1.40, 1.90, 2.30-2.32, and 2.40 mm, arising from H2O and hydroxyl groups in various settings. The position of the ~2.31 mm spectral feature varies systematically with the redox state of the octahedrally coordinated Fe. This correlation may permit surface oxidation state to be inferred (in some cases) from VNIR spectra of Mars obtained from orbit, and, in any case, ferrian saponite is a viable assignment for spectral detections in the range 2.30-2.32 mm.
Asymptotic representations of shifted quantum affine algebras from critical K-theory

Asymptotic representations of shifted quantum affine algebras from critical K-theory Huaxin Liu In this thesis we explore the geometric representation theory of shifted quantum affine algebras A , using the critical K-theory of certain moduli spaces of infinite flags of quiver representations resembling the moduli of quasimaps to Nakajima quiver varieties. These critical K-theories become A -modules via the so-called critical R-matrix R, which generalizes the geometric R-matrix of Maulik, Okounkov, and Smirnov. In the asymptotic limit corresponding to taking infinite instead of finite flags, singularities appear in R and are responsible for the shift in A . The result is a geometric construction of interesting infinite-dimensional modules in the category O of A , including e.g. the pre-fundamental modules previously introduced and studied algebraically by Hernandez and Jimbo. Following Nekrasov, we provide a very natural geometric definition of qq-characters for our asymptotic modules compatible with the pre-existing definition of q-characters. When A μ is the shifted quantum toroidal gl1 algebra, we construct asymptotic modules DTμ and PTμ whose combinatorics match those of (1-legged) vertices in Donaldson–Thomas and Pandharipande–Thomas theories. Such vertices control enumerative invariants of curves in toric 3-folds, and finding relations between (equivariant, K-theoretic) DT and PT vertices with descendent insertions is a typical example of a wall-crossing problem. We prove a certain duality between our DTμ and PTμ modules which, upon taking q-/qq-characters, provides one such wall-crossing relation.
Risk factors associated with extended-spectrum b-lactamase-producing organisms at a tertiary care hospital

Methods: A case–control study of 119 patients with ESBL organisms and 132 patients with non-ESBL organisms was conducted. Demographics, co-morbidities, device utilization and antibiotic use were analysed for all patients and infected patients only (cases = 75, controls = 83). Both exposure and degree of exposure (in grams) to antibiotics were included. A dot blot hybridization technique was used to identify genes in plasmid extracts from the ESBL organisms.
Glial and Neural Response in Short-term Human Retinal Detachment

sected RPE from a melanoma specimen was used as a control. The quantitative real-time PCR was performed using the forward primer IS6 (5 AGGCGAACCCTGCCCAG-3 ) and reverse pr imer IS7 (5 GATCGCTGATCCGGCCA-3 ), whichamplifieda122–basepair fragment of the IS6110 multicopy element (GenBank accession No. X52471). The standard DNA used was 10 ng to 10 pg of M tuberculosis genomic DNA (Colorado State University). The amount of the test sample product was interpolated from the standard curve of cycle threshold values generated from known starting concentrations of standard M tuberculosis DNA. An average of 3 different runs revealed about 1.7 10 bacterial genomes in the RPE layer. The controls were negative for DNA amplification (Figure 2).
Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions

Bayesian model is constructed to estimate the missing data of capital stock, and the impact of three industrial structures on the tertiary industry is discussed. The results show that: the maximum MC error with missing data on capital stock estimated by Bayesian is 0.4963, the maximum MC error of production function estimated by Bayesian stratation is 0.3276, the standard deviation is 0.0890 and the accuracy is high; from 1993 to 2018, the sum of capital output elasticity and labor output elasticity in the tertiary industry in Yunnan Province was greater than 1, and the scale compensation was increasing; the level of technological progress, the growth rate of all factors, the elasticity of capital output and the elasticity of labor output were all close to stable, and the ranges of changes were 0.2714-0.3252, -0.0680-0.0390, 0.5615-0.5858 and 0.4522-0.4784, respectively; the elasticity of capital output was greater than that of labor force output, and the tertiary industry in Yunnan Province was more dependent on the elasticity of capital output.
Predictive Control of Hydronic Floor Heating Systems using Neural Networks and Genetic Algorithms

: This paper presents the use a neural network and a micro genetic algorithm to optimize future set-points in existing hydronic ﬂoor heating systems for improved energy eﬃciency. The neural network can be trained to predict the impact of changes in set-points on future room temperatures. Additionally, weather disturbances such as solar heat gain can be anticipated and compensated for, while taking into account the slow dynamics of the ﬂoor. Together with a genetic algorithm, they provide a way to search for optimal future set-point sequences, when convexity and continuity in the solution space is not guaranteed. Evaluation of the performance of multiple neural networks is performed, using diﬀerent levels of information, and optimization results are presented on a detailed house simulation model.
How do Economic Circumstances Determine Preferences? Evidence from Long-run Panel Data

Preferences for redistribution and social spending are correlated with income and unemployment risk, but it is unclear how these relationships come about. I build a theory emphasizing that only large changes in economic circumstances provide the information and motivation needed for people to change their preferences. Stable long-run preferences are shaped mainly by early socialization, which includes economic and ideological influences from the family, and early labor market experiences. Enduring shocks, low intergenerational mobility and the tendency of left-wing parents to be poorer generate correlations between circumstances and preferences. Because preferences are stable, greater inequality may not increase aggregate support for redistribution. Support is found for the theory with panel data from Switzerland, using a range of empirical tests.
Carrying out contract successfully ends up with an IT Outsourcing failure : Relationship Management Cases of IT Outsourcing in a Cross-Cultural Context

IT outsourcing is a serious option available to modern managers today. An emerging trend is the focus on relationship management. In a global economy cross-cultural differences may add to the complexity of fostering a relationship. This study examines cross-cultural relationship management in IT outsourcing. Due to the exploratory nature of this study, the researcher investigates two IT outsourcing cases within one Chinese organization. One vendor has a western cultural background and the other a Chinese cultural background. The result shows that cultural differences influence the fostering of a relationship. Some practical implications could be generated to manage offshore IT outsourcing.
Using Computer Vision To Gain Health Insights from Social Media by Aritro Biswas

In this thesis, I developed machine learning methods that would support tools for gaining health insights from social media images. On the one hand, I have helped create a dataset for food image segmentation and a segmentation network for this task, a task that is very relevant for understanding the nutritional content of food from images. I also explored the flip side of the issue, and helped design an interface that users can use to explore food recipes in machine learning-driven ways. On the other hand, I helped create a dataset and model for classifying types of disasters given images of natural or manmade disasters. Thesis Supervisor: Antonio Torralba Title: Professor
Crop Rotation: An Approach to Save Irrigation Water under Water Scarcity in Egypt

Crop rotation is an agricultural management practice that could save on the applied irrigation water. The objectives of this paper were: (i) to calculate water requirements for a prevailing crop rotation in old land, new land and salt affected soil, in addition to sugarcane rotation in South Egypt; (ii) to suggest water saving rotations, calculate its water requirements and the saved irrigation water. Water requirements were calculated using BISm model. The results indicated that the proposed rotation in old land, the saved irrigation water amount could reach 1095, 1331 and 1546 m 3 /ha in Lower, Middle and Upper Egypt, respectively as a result of cultivation on raised beds and intercropping (produce two crops with the same amount of water). In calcareous soil, 3160 m 3 /ha could be saved if the proposed rotation was used. The proposed rotation in sandy soil can save low amount of water, i.e. 53, 67 and 152 m 3 /ha in Lower, Middle and Upper Egypt, respectively. In salt affected soil, 3426 m 3 /ha can be saved under the proposed rotation. The saved amount of irrigation water under proposed sugarcane rotations was 3596 and 7609 m 3 /ha for spring and autumn rotations, respectively. Thus, crop rotation and intercropping can help in solving food insecurity problem through increase land productivity. Furthermore, it can save a sum of irrigation water and increase water productivity. These saved irrigation water amounts can be used to cultivate new areas and reduce food gap.
Effects of Design Parameters on Fuel Economy and Output Power in an Automotive Thermoelectric Generator

The need for more sustainable mobility promoted research into the use of waste heat to reduce emissions and fuel consumption. As such, thermoelectric generation is a promising technique thanks to its robustness and simplicity. Automotive thermoelectric generators (ATEGs) are installed in the tailpipe and convert heat directly into electricity. Previous works on ATEGs mainly focused on extracting the maximum amount of electrical power. However, the back pressure caused by the ATEG heavily influences fuel consumption. Here, an ATEG numerical model was first validated with experimental data and then applied to investigate the effects that modifying the main ATEG design parameters had on both fuel economy and output power. The cooling flow rate and the geometrical dimensions of the heat exchanger on the hot side and the cold side of the ATEG were varied. The design that produced the maximum output power differed from that which maximized fuel economy. Back pressure was the most limiting factor in attaining fuel savings. Back pressure values lower than 5 mbar led to a < 0.2% increase in fuel consumption. In the ATEG design analyzed here, the generation of electrical output power reduced fuel consumption by a maximum of 0.5%.
Some but not all dispreferred turn markers help to interpret scalar terms in polite contexts

In polite contexts, people find it difficult to perceive whether they can derive scalar inferences from what others say (e.g., does “some people hated your idea” mean that not everyone hated it? ). Because this uncertainty can lead to costly misunderstandings, it is important to identify the cues people can rely on to solve their interpretative problem. In this article, we consider two such cues: Making a long Pause before the statement, and prefacing the statement with Well. Data from eight experiments show that Pauses are more effective than Wells as cues to scalar inferences in polite contexts—because they appear to give a specific signal to switch expectations in the direction of bad news, whereas Well appears to give a generic signal to make extra processing effort. We consider the applied value of these findings for human–human and human–machine interaction, as well as their implications for the study of reasoning and discourse.
Title Studies on Expression of Aldehyde Dehydrogenase in Normal andCancerous Tissues of Thyroids

Recently published articles have reported the controversial data regarding expression of aldehyde dehydrogenase isozyme 1A1 (ALDH1A1), a potential candidate marker for normal and cancer stem cells (CSCs), in thyroid tissues. These data prompted us to re-evaluate expression of ALDH1A1 in normal and cancerous thyroid tissues by two different means. The first method was immunohistochemistry with two different anti-ALDH1A1 antibodies from distinct companies. Following validating the integrity of these two antibodies by western blotting with ALDH-expressing and -non-expressing cancer cell lines and immunohistochemistry with breast and colon tissues, we here demonstrated significant and comparable expression of ALDH1A1 in both normal and cancerous thyroid tissues with both antibodies. Next, relative expression levels of ALDH isozymes were evaluated by reverse transcription-polymerase chain reaction (RT-PCR), revealing that ALDH1A1 was the most highly expressed isozyme followed by ALDH9A1 and relative expression patterns of isozymes were very similar in normal and cancerous tissues. All these data demonstrate that thyroid cells of normal and cancer origins do express ALDH1A1 and to a lesser extent 9A1. Further study will be necessary to study functional significance of ALDH1A1 in the function and behaviors of thyroid normal and cancer stem cells.
The Secular and Cyclic Determinants of Capitalization Rates: The Role of Property Fundamentals, Macroeconomic Factors, and “Structural Changes”

In this article, the authors revisit many studies that have attempted to explain the determinants of real estate capitalization rates. Two new innovations are introduced. First, the authors identify two macroeconomic factors, in addition to risk-free Treasury rates, that greatly impact cap rates—the general corporate risk premium operating in the economy and the amount of debt (liquidity) available. The addition of these factors greatly adds to the ability of previous models to explain the secular fall of cap rates in the last decade and their recent rise. Second, the authors search for “structural” shifts in the cap rate using innovative tests, including a large number of macroeconomic factors. The tests identify two distinct periods that the authors label as “investor sentiment. ” A period of negative sentiment was identified from 1991 to 1996 and a period of positive sentiment was identified from 2002 to 2007. Methodologically, the analysis uses a large and robust quarterly panel dataset of 30 U.S. metropolitan areas from 1980 Q1 through 2007 Q4. The authors compare the models using traditional measures of within-sample fit, as well as how the models behave in in-sample backtest forecasts.