Miracle-dz/UniFAR-FTUs huggingface dataset:
Diversity in Spectral Learning for Natural Language Parsing

We describe an approach to create a diverse set of predictions with spectral learning of latent-variable PCFGs (L-PCFGs). Our approach works by creating multiple spectral models where noise is added to the underlying features in the training set before the estimation of each model. We describe three ways to decode with multiple models. In addition, we describe a simple variant of the spectral algorithm for L-PCFGs that is fast and leads to compact models. Our experiments for natural language parsing, for English and German, show that we get a significant improvement over baselines comparable to state of the art. For English, we achieve the F1 score of 90.18, and for German we achieve theF1 score of 83.38.
Fibrosis signature of anastomotic margins for predicting anastomotic stenosis in rectal cancer with neoadjuvant chemoradiotherapy and sphincter-preserving surgery

Abstract Background Radiation-induced colorectal fibrosis (RICF) is a common pathological alteration among patients with rectal cancer undergoing neoadjuvant chemoradiotherapy (nCRT). Anastomotic stenosis (AS) causes symptoms and negatively impacts patients’ quality of life and long-term survival. In this study, we aimed to evaluate the fibrosis signature of RICF and develop a nomogram to predict the risk of AS in patients with rectal cancer undergoing nCRT. Methods Overall, 335 pairs of proximal and distal margins were collected and randomly assigned at a 7:3 ratio to the training and testing cohorts. The RICF score was established to evaluate the fibrosis signature in the anastomotic margins. A nomogram based on the RICF score for AS was developed and evaluated by using the area under the curve, decision curve analysis, and the DeLong test. Results The training cohort included 235 patients (161 males [68.51%]; mean age, 59.61 years) with an occurrence rate of AS of 17.4%, whereas the testing cohort included 100 patients (72 males [72.00%]; mean age, 57.17 years) with an occurrence rate of AS of 11%. The RICF total score of proximal and distal margins was significantly associated with AS (odds ratio, 3.064; 95% confidence interval [CI], 2.200–4.268; P < 0.001). Multivariable analysis revealed that the RICF total score, neoadjuvant radiotherapy, and surgical approach were independent predictors for AS. The nomogram demonstrated good discrimination in the training cohort (area under the receiver-operating characteristic curve, 0.876; 95% CI, 0.816–0.937), with a sensitivity of 68.3% (95% CI, 51.9%–81.9%) and a specificity of 85.5% (95% CI, 78.7%–89.3%). Similar results were observed in the testing cohort. Conclusions This study results suggest that the RICF total score of anastomotic margins is an independent predictor for AS. The prediction model developed based on the RICF total score may be useful for individualized AS risk prediction in patients with rectal cancer undergoing nCRT and sphincter-preserving surgery.
The spring stiffness profile within a passive, full-leg exoskeleton affects lower-limb joint mechanics while hopping

Passive, full-leg exoskeletons that act in parallel with the legs can reduce the metabolic power of bouncing gaits like hopping. However, the magnitude of metabolic power reduction depends on the spring stiffness profile of the exoskeleton and is presumably affected by how users adapt their lower-limb joint mechanics. We determined the effects of using a passive, full-leg exoskeleton with degressive (DG), linear (LN) and progressive (PG) stiffness springs on lower-limb joint kinematics and kinetics during stationary, bilateral hopping at 2.4 Hz. We found that the use of a passive, full-leg exoskeleton primarily reduced the muscle-tendon units (MTUs) contribution to overall joint moment and power at the ankle, followed by the knee, due to the average exoskeleton moment arm around each joint. The greatest reductions occurred with DG springs, followed by LN and PG stiffness springs, probably due to differences in elastic energy return. Moreover, the relative distribution of positive joint power remained unchanged when using a passive, full-leg exoskeleton compared with unassisted hopping. Passive, full-leg exoskeletons simultaneously assist multiple lower-limb joints and future assistive devices should consider the effects of spring stiffness profile in their design.
Assessment of genetically modified maize DP202216 for food and feed uses, under Regulation (EC) No 1829/2003 (application EFSA‐GMO‐NL‐2019‐159)

Abstract Genetically modified maize DP202216 was developed to confer tolerance to glufosinate‐ammonium‐containing herbicides and to provide an opportunity for yield enhancement under field conditions. These properties were achieved by introducing the mo‐pat and zmm28 expression cassettes. The molecular characterisation data and bioinformatic analyses do not identify issues requiring food/feed safety assessment. None of the identified differences in the agronomic/phenotypic and compositional characteristics tested between maize DP202216 and its comparator needs further assessment, except for the levels of stearic acid (C18:0), which do not raise nutritional and safety concerns. The GMO Panel does not identify safety concerns regarding the toxicity and allergenicity of the PAT and ZMM28 proteins as expressed in maize DP202216, and finds no evidence that the genetic modification would change the overall allergenicity of maize DP202216. In the context of this application, the consumption of food and feed from maize DP202216 does not represent a nutritional concern in humans and animals. The GMO Panel concludes that maize DP202216 is as safe as the comparator and non‐GM reference varieties tested, and no post‐market monitoring of food/feed is considered necessary. In the case of accidental release of viable maize DP202216 grains into the environment, this would not raise environmental safety concerns. The post‐market environmental monitoring plan and reporting intervals are in line with the intended uses of maize DP202216. The GMO Panel concludes that maize DP202216 is as safe as its comparator and the tested non‐GM reference varieties with respect to potential effects on human and animal health and the environment.
Analyzing Polls and News Headlines Using Business Intelligence Techniques

Opinion and market research companies gather a substantial amount of polls data which can be combined with news headlines, for the corresponding time periods they are collected. These data are analyzed in order to answer specific (predefined) questions related to the situation of each time period. However, when these tasks are fulfilled, the collected data are archived and possibly the majority of them will remain unutilized for future research. In this paper, we argue that these „inactive‟ data can be further analyzed and hidden knowledge can be extracted. For this reason, we propose an appropriate framework based on modern Business Intelligence (BI) techniques. The innovation of the proposed framework is that it is able to reuse and analyze data that have been collected in the past and discover hidden knowledge, which can be utilized to bring profit in many ways. The basic scope of our framework is a) to supply knowledge on trends regarding specific politico-social and market issues and the way in which the situation of each period affect those trends, b) to predict the evolvement of trends according to the current situation or the formulation of emerging trends.
Identifying Clusters of Non-Farm Activity within Exclusive Farm Use Zones in the Northern Willamette Valley

This Thesis is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. For more information, please contact pdxscholar@pdx.edu. Recommended Citation Chun, Nicholas, "Identifying Clusters of Non-Farm Activity within Exclusive Farm Use Zones in the Northern Willamette Valley" (2017). Dissertations and Theses. Paper 3888.
Difficulties in emotion regulation and well-being in breast cancer

ABSTRACT Objective: Breast cancer is responsible for disruptive changes in women’s lives, causing them to experience diverse and intense negative emotions that can affect their perception of well-being. The present study aimed to characterize difficulties in emotion regulation (ER), according to Gratz and Roemer’s multidimensional assessment, in women with breast cancer and to relate them with General Well-Being and its different domains: Physical, Social/Familial, Emotional, and Functional. Method: Ninety-five Portuguese women with breast cancer aged between 32 and 75 years answered a sociodemographic and clinical questionnaire and the Portuguese versions of the Difficulties in Emotion Regulation Scale and the Functional Assessment of Cancer Therapy – General. Data were collected in an oncology public hospital. Results: In general, difficulties in ER presented negative correlations with General Well-Being and its domains. The multiple regression analysis findings indicated that two specific types of difficulties, Limited Access to ER Strategies and Lack of Emotional Clarity, play a significant role in predicting well-being, especially in the Emotional domain, which was most compromised in these patients. Conclusions: These difficulties should be approached within psycho-oncological interventions as they are essential contributors to improving emotional and general well-being and fostering psychological adaptation to breast cancer.
Spatial-mode selection based on channel mean feedback for a robust joint linear precoder and decoder MMSE design

The joint linear precoder and decoder minimum mean squared error (MMSE) design represents a low complexity yet powerful solution for spatial multiplexing MIMO systems. Its performance can be further boosted through optimally selecting the number of spatial streams to be used according to the available channel state information (CSI), so-called spatial-mode selection. The performance of both the latter MMSE design and the related spatial-mode selection criteria, however, critically depends on the availability of timely CSI at both transmitter and receiver. In practice, the latter assumption can be severely challenged, due to channel time variations that lead to imperfect CSI at the transmitter. State-of-the-art designs mistakenly use this imperfect CSI to design the linear precoder and rely on the receiver to reduce the induced degradation. We have alternatively proposed a robust Bayesian joint linear precoder and decoder solution that takes into account the uncertainty on the true channel, given the channel mean feedback at the transmitter. In this paper, we further improve the performance of our aforementioned robust design using a new spatial-mode selection criterion based on channel mean feedback. We also illustrate, via Monte-Carlo analysis, the robustness of the resulting improved design to channel time variations, which outperforms the state-of-the-art approach.
The development of non-destructive sampling methods of parchment skins for genetic species identification

Parchment, the skins of animals prepared for use as writing surfaces, offers a valuable source of genetic information. Many have clearly defined provenance, allowing for the genetic findings to be evaluated in temporal and spatial context. While these documents can yield evidence of the animal sources, the DNA contained within these aged skins is often damaged and fragmented. Previously, genetic studies targeting parchment have used destructive sampling techniques and so the development and validation of non-destructive sampling methods would expand opportunities and facilitate testing of more precious documents, especially those with historical significance. Here we present genetic data obtained by non-destructive sampling of eight parchments spanning the 15th century to the modern day. We define a workflow for enriching the mitochondrial genome (mtGenome), generating next-generation sequencing reads to permit species identification, and providing interpretation guidance. Using sample replication, comparisons to destructively sampled controls, and by establishing authentication criteria, we were able to confidently assign full/near full mtGenome sequences to 56.3% of non-destructively sampled parchments, each with greater than 90% of the mtGenome reference covered. Six of eight parchments passed all four established thresholds with at least one non-destructive sample, highlighting promise for future studies.
Centralize or distribute? A techno-economic study to design a low-cost cloud radio access network

Cloud radio access network (CRAN) has been proposed as a promising evolution of mobile network architecture where baseband processing functions of a base station are split/decoupled from the radio unit (RU) and centralized. However, rigid bandwidth and latency requirements are incurred by fronthaul, i.e., transport link, which connects RU to the central cloud. Therefore, new functional splits are discussed for CRAN with dual-site processing, which we call Hybrid-RAN (H-RAN), where some functions remain distributed while others are centralized. In this work, from a perspective of minimizing the total cost of ownership (TCO) for H-RAN, we present a techno-economic study to find the optimal functional splits for a base station (BS), with a given configuration. A configuration of a BS represents frequency layers, carrier bandwidths, and MIMO schemes, associated with different frequency bands. For each functional split, we present a model to calculate the requirement of computational resources and fronthaul bandwidth. We formulate a TCO minimization model using constraint programming. Numerical results show that the optimal functional split depends on BS configuration, fiber ownership, and data transmission direction. H-RAN with optimal functional split can achieve lower TCO than both classical Distributed RAN and CRAN.
20 years of neuromuscular electrical stimulation in COPD

Although a lung disease, COPD is also associated with extrapulmonary manifestations including, among others, limb muscle dysfunction. Limb muscle dysfunction is a key systemic consequence of COPD that impacts patients' physical activity, exercise tolerance, quality of life and survival. Deconditioning is the main mechanism underlying the development of limb muscle dysfunction in COPD, which can be partially improved with exercise. However, some patients may not be able to tolerate exercise because of incapacitating breathlessness or unwillingness to undertake whole-body exercise. Alternative training modalities that do not give rise to dyspnoea, such as neuromuscular electrical stimulation (NMES), are urged. Over the past 20 years, NMES in COPD has presented conflicting conclusions in meta-analysis. In this review, we try to understand the reason for this result by analysing possible biases and factors that brought conflicting conclusions. We discuss the population (the intervention group, but also the control group), the outcome measures, the frequency of stimulation, the rehabilitation protocol (i.e. NMES alone versus standard care/rehabilitation or NMES plus conventional exercise training versus conventional exercise training alone or NMES versus sham treatment) and the trial design. The main reason for this discrepancy is the lack of dedicated guidelines for NMES. Further research is urged to determine the optimal parameters for an NMES programme. Despite this, NMES appears to be an effective means of enhancing quadriceps strength and exercise capacity in COPD with the potential to break the vicious circle induced by the disease and COPD patients’ lifestyle.
Plant-based diets in patients with chronic kidney disease

Abstract Dietary protein restriction has been considered to be a nutritional-related strategy to reduce risk for end-stage kidney disease among patients with non-dialysis-dependent chronic kidney disease (CKD). However, there is insufficient evidence to recommend a particular type of protein to slow down the CKD progression. Recently, various plant-based diets could demonstrate some additional benefits such as a blood pressure-lowering effect, a reduction of metabolic acidosis as well as hyperphosphatemia, and gut-derived uremic toxins. Furthermore, the former concerns about the risk of undernutrition and hyperkalemia observed with plant-based diets may be inconsistent in real clinical practice. In this review, we summarize the current evidence of the proposed pleiotropic effects of plant-based diets and their associations with clinical outcomes among pre-dialysis CKD patients.
Theory of the hypervolume indicator: optimal μ-distributions and the choice of the reference point

The hypervolume indicator is a set measure used in evolutionary multiobjective optimization to evaluate the performance of search algorithms and to guide the search. Multiobjective evolutionary algorithms using the hypervolume indicator transform multiobjective problems into single objective ones by searching for a finite set of solutions maximizing the corresponding hypervolume indicator. In this paper, we theoretically investigate how those optimal μ--distributions-finite sets of μ solutions maximizing the hypervolume indicator-are spread over the Pareto front of biobjective problems. This problem is of high importance for practical applications as these sets characterize the preferences that the hypervolume indicator encodes, i.e., which types of Pareto set approximations are favored. In particular, we tackle the question whether the hypervolume indicator is biased towards certain regions. For linear fronts we prove that the distribution is uniform with constant distance between two consecutive points. For general fronts where it is presumably impossible to characterize exactly the distribution, we derive a limit result when the number of points grows to infinity proving that the empirical density of points converges to a density proportional to the square root of the negative of the derivative of the front. Our analyses show that it is not the shape of the Pareto front but only its slope that determines how the points that maximize the hypervolume indicator are distributed. Experimental results illustrate that the limit density is a good approximation of the empirical density for small μ. Furthermore, we analyze the issue of where to place the reference point of the indicator such that the extremes of the front can be found if the hypervolume indicator is optimized. We derive an explicit lower bound (possibly infinite) ensuring the presence of the extremes in the optimal distribution. This result contradicts the common belief that the reference point has to be chosen close to the nadir point: for certain types of fronts, we show that no finite reference point allows to have the extremes in the optimal μ-distribution.
An efficient radiative transfer model for hyperspectral IR radiance simulation and applications under cloudy‐sky conditions

An efficient radiative transfer model has been developed for hyperspectral infrared radiance simulation under both clear‐ and cloudy‐sky conditions. The hyperspectral IR cloudy radiative transfer model (HIRTM) combines atmospheric transmittances due to molecular absorption and cloud absorption and scattering from cloud hydrometeors. An efficient analytical Jacobian methodology is also developed under both clear‐ and cloudy‐sky conditions, which is needed both to assimilate cloudy radiances directly into numerical weather prediction models and to retrieve atmospheric soundings and cloud properties simultaneously from cloudy radiance measurements. In comparing HIRTM and its analytical Jacobian with the community radiative transfer model (CRTM), our research has shown that HIRTM's Jacobian calculations are similar to those of CRTM. HIRTM and CRTM synthetic observations derived from model output are compared with corresponding real observations from Geostationary Operational Environmental Satellite 13 Imager observations, and both perform similarly under water clouds, while CRTM is colder than HIRTM for thick ice clouds.
Complete Nucleotide Sequence of a Citrobacter freundii Plasmid Carrying KPC-2 in a Unique Genetic Environment

ABSTRACT The complete and annotated nucleotide sequence of a 54,036-bp plasmid harboring a blaKPC-2 gene that is clonally present in Citrobacter isolates from different species is presented. The plasmid belongs to incompatibility group N (IncN) and harbors the class A carbapenemase KPC-2 in a unique genetic environment.
Models of animated rivers for the interactive exploration of landscapes. (Modèles de rivières animées pour l'exploration interactive de paysages)

Rivers are ubiquitous in nature, and thus are an important component of the visual simulation of nature scenes. In nature, rivers are dynamic, therefore animation of rivers is necessary in these visual simulation applications. However, animation of rivers is a challenging problem. It incorporates multi-scale surface details and flow motion, and many phenomena involved have complex underlying physical causes. River animation is particular difficult in emerging interactive applications like Google Earth or games, which allow users to explore a very large scene and observe rivers at a very small scale or a very large scale at any moment. Controlling the design of water simulations is another hard problem. The goal of this dissertation is to achieve real-time, scalable, and controllable river animation with a detailed and space-time continuous appearance. To achieve this goal, we break down the river animation problem into macro-, meso-, and micro-scale subproblems from coarse to fine. We propose appropriate models for each scale that capture relevant surface details and fluid motion. In the macro-scale, we propose a procedural method that can compute velocities of rivers with curved banks, branchings and islands on the fly. In themeso-scale, we propose an improved featured-based simulationmethod to generate the crests of the quasi-stationary waves that obstaclesmake. We also propose a method for constructing an adaptive and feature-aligned water surface according to the given wave crests. In the micro-scale, we propose the use of wave sprites, a sprite-based texture model, to represent advected details with stationary spectrum properties on flow surfaces. Armed with wave sprites and a dynamic adaptive sampling scheme, we can texture the surface of a very large or even unbounded river with scene-independent performance. In addition, we propose a Lagrangian texture advection method that has other applications beyond river animation. We demonstrate that combining our models in three scales helps us incorporate visually convincing animated rivers into a very large terrain in real-time interactive applications.
TO SEE OR NOT TO SEE: The Need for Attention to Perceive Changes in Scenes

When looking at a scene, observers feel that they see its entire structure in great detail and can immediately notice any changes in it. However, when brief blank fields are placed between alternating displays of an original and a modified scene, a striking failure of perception is induced: Identification of changes becomes extremely difficult, even when changes are large and made repeatedly. Identification is much faster when a verbal cue is provided, showing that poor visibility is not the cause of this difficulty. Identification is also faster for objects considered to be important in the scene. These results support the idea that observers never form a complete, detailed representation of their surroundings. In addition, the results indicate that attention is required to perceive change, and that in the absence of localized motion signals, attention is guided on the basis of high-level interest.