Miracle-dz/UniFAR-FTUs huggingface dataset:
Turbidity in Apalachicola Bay, Florida from Landsat 5 TM and Field Data: Seasonal Patterns and Response to Extreme Events

Synoptic monitoring of estuaries, some of the most bio-diverse and productive environments on Earth, is essential to study small-scale water dynamics and its role on spatiotemporal variation in water quality important to indigenous marine species and surrounding human settlements. We present a detailed study of turbidity, an optical index of water quality, in Apalachicola Bay, Florida (USA) using historical in situ measurements and Landsat 5 TM data archive acquired from 2004 to 2011. Data mining techniques such as time-series decomposition, principal component analysis, and classification tree-based models were utilized to decipher time-series for examining variations in physical forcings, and their effects on diurnal and seasonal variability in turbidity in Apalachicola Bay. Statistical analysis showed that the bay is highly dynamic in nature, both diurnally and seasonally, and its water quality (e.g., turbidity) is largely driven by interactions of different physical forcings such as river discharge, wind speed, tides, and precipitation. River discharge and wind speed are the most influential forcings on the eastern side of river mouth, whereas all physical forcings were relatively important to the western side close to the major inlet, the West Pass. A bootstrap-optimized and atmospheric-corrected single-band empirical relationship (Turbidity (NTU) = 6568.23 × (Reflectance (Band 3))1.95; R2 = 0.77 ± 0.06, range = 0.50–0.91, N = 50) is proposed with seasonal thresholds for its application in various seasons. The validation of this relationship yielded R2 = 0.70 ± 0.15 (range = −0.96–0.97; N = 38; RMSE = 7.78 ± 2.59 NTU; Bias (%) = −8.70 ± 11.48). Complex interactions of physical forcings and their effects on water dynamics have been discussed in detail using Landsat 5 TM-based turbidity maps during major events between 2004 and 2011. Promising results of the single-band turbidity algorithm with Landsat 8 OLI imagery suggest its potential for long-term monitoring of water turbidity in a shallow water estuary such as Apalachicola Bay.
Reliability measurement of mass storage system for onboard instrumentation

Advances in spaceborne vehicular technology have made possible the long-life duration of the mission in harsh cosmic environments. Reliability and data integrity are the commonly emphasized requirements of spaceborne solid-state mass storage systems, because faults due to the harsh cosmic environments, such as extreme radiation, can be experienced throughout the mission. Acceptable dependability for these instruments has been achieved by using redundancy and repair. Reconfiguration (repair) of memory arrays using spare memory lines is the most common technique for reliability enhancement of memories with faults. Faulty cells in memory arrays are known to show spatial locality. This physical phenomenon is referred to as fault clustering . This paper initially investigates a quadrat-based fault model for memory arrays under clustered faults to establish a reliable foundation of measurement. Then, lifelong dependability of a fault-tolerant spaceborne memory system with hierarchical active redundancy, which consists of spare columns in each memory module and redundant memory modules, is measured in terms of the reliability (i.e., the conditional probability that the system performs correctly throughout the mission) and mean-time-to-failure (i.e., the expected time that a system will operate before it fails). Finally, minimal column redundancy search technique for the fault-tolerant memory system is proposed and verified through a series of parametric simulations. Thereby, design and fabrication of cost-effective and highly reliable fault-tolerant onboard mass storage system can be realized for dependable instrumentation.
Prediction Factors of Recurrent Ischemic Events in One Year after Minor Stroke

Background The risk of a subsequent stroke following a minor stroke is high. However, there are no effective rating scales to predict recurrent stroke following a minor one. Therefore, we assessed the risk factors associated with recurrent ischemic stroke or transient ischemic attack (TIA) within one year of minor stroke onset in order to identify possible risk factors. Methods Eight hundred and sixty-three non-cardioembolic ischemic stroke patients in the Chinese IntraCranial AtheroSclerosis Study that presented with minor stroke, defined as an admission National Institutes of Health stroke scale (NIHSS) score of ≤3, were consecutively enrolled in our study. Clinical information and imaging features upon admission, and any recurrent ischemic stroke or TIA within one year was recorded. Cox regression was used to identify risk factors associated with recurrent ischemic stroke or TIA within the year following stroke onset. Results A total of 50 patients (6.1%) experienced recurrent ischemic stroke or TIA within one year of minor stroke onset. Multivariate Cox regression model identified lower admission NIHSS score (HR, 1.75; 95% CI, 1.32 to 2.33; P<0.0001), history of coronary heart disease (HR, 2.62; 95% CI, 1.17 to 5.86; P = 0.02), severe stenosis or occlusion of large cerebral artery (HR, 4.68; 95% CI, 1.87 to 11.7; P = 0.001), and multiple acute cerebral infarcts (HR, 2.61; 95% CI, 1.01 to 6.80; P = 0.05) as independent risk factors for recurrent ischemic stroke or TIA within one year. Conclusions Some minor stroke patients are at higher risk for recurrent ischemic stroke or TIA. Urgent and intensified therapy may be reasonable in these patients.
MatrixMiner: a red pill to architect informal product descriptions in the matrix

Domain analysts, product managers, or customers aim to capture the important features and differences among a set of related products. A case-by-case reviewing of each product description is a laborious and time-consuming task that fails to deliver a condensed view of a product line. This paper introduces MatrixMiner: a tool for automatically synthesizing product comparison matrices (PCMs) from a set of product descriptions written in natural language. MatrixMiner is capable of identifying and organizing features and values in a PCM – despite the informality and absence of structure in the textual descriptions of products. Our empirical results of products mined from BestBuy show that the synthesized PCMs exhibit numerous quantitative, comparable information. Users can exploit MatrixMiner to visualize the matrix through a Web editor and review, refine, or complement the cell values thanks to the traceability with the original product descriptions and technical specifications.
Solving Dynamic Controllability Problem of Multi-Agent Plans with Uncertainty Using Mixed Integer Linear Programming

Executing multi-agent missions requires managing the uncertainty about uncontrollable events. When communications are intermittent, it additionally requires for each agent to act only based on its local view of the problem, that is independently of events which are controlled or observed by the other agents. In this paper, we propose a new framework for dealing with such contexts, with a focus on mission plans involving temporal constraints. This framework, called Multi-agent Simple Temporal Network with Uncertainty (MaSTNU), is a combination between Multi-agent Simple Temporal Network (MaSTN) and Simple Temporal Network with Uncertainty (STNU). We define the dynamic controllability property for MaSTNU, and a method for computing offline valid execution strategies which are then dispatched between agents. This method is based on a mixed-integer linear programming formulation and can also be used to optimize criteria such as the temporal flexibility of multi-agent plans. 1
Factors Predictive of Survival After Percutaneous Endoscopic Gastrostomy in the Elderly: Is Dementia Really a Risk Factor?

OBJECTIVES:Outcomes, especially survival, after percutaneous endoscopic gastrostomy (PEG) in patients with dementia remain unclear. The aims of this study were to assess the impact of dementia on survival after PEG and to explore the risk factors in elderly patients.METHODS:A total of 311 consecutive Japanese patients who underwent PEG were enrolled in this retrospective cohort study. Dementia was defined according to the standard criteria. After the clinical characteristics of patients with and without dementia were compared, the Kaplan-Meier method and Cox proportional-hazards regression analysis were applied to analyze survival rates.RESULTS:Survival was not significantly different between the two groups. The 12-month survival rate of patients with dementia (N = 143) was 51%, and that of patients without dementia (N = 168) was 49%. More than 20% of patients with dementia lived more than 3 yr after PEG. The predictors of poor survival after PEG were previous subtotal gastrectomy (odds ratio [OR] 2.619, 95% confidence interval [CI] 1.367–5.019), serum albumin <2.8 g/dL (OR 2.081, 95% CI 1.490–2.905), age >80 yr (OR 1.721, 95% CI 1.234–2.399), chronic heart failure (OR 1.541, 95% CI 1.096–2.168), and male gender (OR 1.407, 95% CI 1.037–1.909). CONCLUSIONS:In our series, there was no evidence to support a poorer prognosis after PEG in elderly people with dementia compared with the cognitively preserved elderly. However, if patients are male or of advanced age, have a low serum albumin, chronic heart failure, or subtotal gastrectomy, physicians should inform families that a poor prognosis is expected before performing PEG.
Non-negative Matrix Factorization, Convexity and Isometry

In this paper we explore avenues for improving the reliability of dimensionality reduction methods such as Non-Negative Matrix Factorization (NMF) as interpretive exploratory data analysis tools. We first explore the difficulties of the optimization problem underlying NMF, showing for the first time that non-trivial NMF solutions always exist and that the optimization problem is actually convex, by using the theory of Completely Positive Factorization. We subsequently explore four novel approaches to finding globally-optimal NMF solutions using various ideas from convex optimization. We then develop a new method, isometric NMF (isoNMF), which preserves non-negativity while also providing an isometric embedding, simultaneously achieving two properties which are helpful for interpretation. Though it results in a more difficult optimization problem, we show experimentally that the resulting method is scalable and even achieves more compact spectra than standard NMF.
Disambiguating Highly Ambiguous Words

A word sense disambiguator that is able to distinguish among the many senses of common words that are found in general-purpose, broad-coverage lexicons would be useful. For example, experiments have shown that, given accurate sense disambiguation, the lexical relations encoded in lexicons such as WordNet can be exploited to improve the effectiveness of information retrieval systems. This paper describes a classifier whose accuracy may be sufficient for such a purpose. The classifier combines the output of a neural network that learns topical context with the output of a network that learns local context to distinguish among the senses of highly ambiguous words.The accuracy of the classifier is tested on three words, the noun line, the verb serve, and the adjective hard; the classifier has an average accuracy of 87%, 90%, and 81%, respectively, when forced to choose a sense for all test cases. When the classifier is not forced to choose a sense and is trained on a subset of the available senses, it rejects test cases containing unknown senses as well as test cases it would misclassify if forced to select a sense. Finally, when there are few labeled training examples available, we describe an extension of our training method that uses information extracted from unlabeled examples to improve classification accuracy.
Genome-wide association study identifies loci at ATF7IP and KLK2 associated with percentage of circulating free PSA.

BACKGROUND Percentage of free-to-total prostate-specific antigen (%fPSA) is an independent predictor of risk for prostate cancer among men with modestly elevated level of total PSA (tPSA) in blood. Physiological and pathological factors have been shown to influence the %fPSA value and diagnostic accuracy. MATERIALS/METHODS To evaluate genetic determinants of %fPSA, we conducted a genome-wide association study of serum %fPSA by genotyping 642,584 single nucleotide polymorphisms (SNPs) in 3192 men of European ancestry, each with a tPSA level of 2.5 to 10 ng/ml, that were recruited in the REduction by DUtasteride of Prostate Cancer Events study. Single nucleotide polymorphisms (SNPs) with P < 10(-5) were further evaluated among the controls of a population-based case-control study in Sweden (2899 prostate cancer cases and 1722 male controls), including 464 controls having tPSA levels of 2.5 to 10 ng/ml. RESULTS We identified two loci that were associated with %fPSA at a genome-wide significance level (P <5 x 10(-8)). The first associated SNP was rs3213764 (P = 6.45 x 10(-10)), a nonsynonymous variant (K530R) in the ATF7IP gene at 12p13. This variant was also nominally associated with tPSA (P = .015). The second locus was rs1354774 (P = 1.25 x 10(-12)), near KLK2 at 19q13, which was not associated with tPSA levels, and is separate from the rs17632542 locus at KLK3 that was previously associated with tPSA levels and prostate cancer risk. Neither rs3213764 nor rs1354774 was associated with prostate cancer risk or aggressiveness. CONCLUSIONS These findings demonstrate that genetic variants at ATF7IP and KLK2 contribute to the variance of %fPSA.
Towards automatic code generation for UAV mission planning using decision sensors

The planning of an autonomous mission for UAVs requires more than the description of the points to be visited along the trajectory by which a certain task must be performed. However, the way in which such missions are planned does not provide conditions for the aircraft or the ground control system to find alternative ways of carrying out the mission, in the event of a risk or other situation different from what was initially planned. In this sense, this paper makes use of a complementary description of the trajectory of a UAV, specifying it through the Discrete Events Systems (DES) framework. Furthermore, it makes use of sensor information to identify situations of risk and, from this, to systematically carry out changes in the mission initially programmed in the aircraft in order to avoid undesired situations.
XRCC1 Arg399Gln Polymorphism Confers Risk of Breast Cancer in American Population: A Meta-Analysis of 10846 Cases and 11723 Controls

Background In the X-ray repair cross-complementing group 1 (XRCC1) gene, a polymorphism, Arg399Gln (rs25487), has been shown to change neoconservative amino acid and thus result in alternation of DNA repair capacity. Numerous studies have investigated the association between Arg399Gln and breast cancer risk in the American population, but yielding inconsistent results. This study aimed to clarify the role of this polymorphism in susceptibility to breast cancer. Methods Literatures were searched in multiple databases including PubMed, Springer Link, Ovid, EBSCO and ScienceDirect databases up to April 2013. A comprehensive meta-analysis was conducted to estimate the overall odds ratio (OR), by integrating data from 18 case control studies of 10846 cases and 11723 controls in the American population. Results Overall, significant association was observed between the Arg399Gln polymorphism and breast cancer risk under the random-effects model (OR for dominant model = 1.12, 95% CI: 1.02–1.24, P heterogeneity = 0.003; OR for additive model = 1.07, 95% CI: 1.01–1.14, P heterogeneity = 0.017). Further sensitivity analysis supported the robust stability of this current result by showing similar ORs before and after removal of a single study. Conclusions This meta-analysis suggests that the XRCC1 Arg399Gln polymorphism may significantly contribute to susceptibility of breast cancer in the American population.
Influence of peripheral iridectomy on intravitreous penetration of topical nipradilol

Purpose. Penetration of drug from the anterior chamber to the vitreous is substantial in aphakic eyes, but negligible in normal phakic eyes. The purpose of this study is to investigate the effect of the presence of peripheral iridectomy (PI) which bypasses iris-lens diaphragm on the drug penetration from the anterior chamber to the vitreous. Methods. Twelve Japanese White rabbits underwent PI in a randomly chosen eye and the same procedures except removal of the peripheral iris in the contralateral eye. Nine weeks after the procedure, topical instillation of 20µl of 1% nipradilol into the both eyes was repeated three times at five-minute intervals, and two hours later the animals were sacrificed and the both eyes were enucleated. Concentrations of nipradilol in the aqueous and vitreous were determined using a high-performance liquid chromatography. Results. The concentrations of nipradilol were significantly greater in the eyes with PI than those in the contralateral control eyes in the aqueous (5636 ± 1688 vs 2835 ± 663 ng/g, mean ± standard error, n = 12, p = 0.0028) and in the anterior vitreous (11.9 ± 2.5 vs 5.6 ± 1.0 ng/g, p = 0.0047), while not in the posterior vitreous or in the posterior retina-choroid. The ratios of the nipradilol concentrations in the anterior or posterior vitreous to that in the aqueous were not significantly different between the both eyes. Conclusions. The presence of PI had little effect on the penetration of topically instilled nipradilol from the anterior chamber to vitreous.
The geography of children: some ethical and methodological considerations for project and dissertation work

With the 'cultural turn' in geography children have been positioned on the geographical agenda. There is an evident and growing interest amongst undergraduates in the geography of children as a topic for project work and dissertation study. This seems an appropriate time to consider a series of related ethical and methodological issues which are important when working with children. The paper is organised into four parts. First, discussion focuses on the background which has given rise to a growing expectation that social (geographical) investigation should be with children rather than on or for children. These ideas are presented in order to encourage students and their supervisors to think about their work from the perspective of children. Second, a set of ethical issues to do with working with children are discussed. Third, examples of good methodological practice when working with children are presented. Lastly, a range of provocative issues to do with geographers studying children are examined. Throu.
Optimizing return-set size for requirements satisfaction and cognitive load

This paper proposes a framework for determining the return-set size that optimizes the tradeoff between requirements satisfaction (the degree to which the customer's requirements are satisfied by the best inventory item presented to the customer) and cognitive load (the number of actions a customer must perform and the number of choices from which these are actions are selected). This framework is based on LCW (learning customer weights), a procedure for learning customer preferences represented as feature weights by observing customers' selections from return sets. An empirical evaluation on simulated customer behavior indicated that LCW's estimate of the mean preferences of a customer population improved as the number of customers increased, even for larger numbers of features of widely differing importance. This improvement in the estimate of mean customer preferences led to improved prediction of individual customer's rankings, irrespective of the extent of variation among customers and whether a single or multiple retrievals were permitted. The experimental results suggest that the return set that optimizes benefit may be smaller for customer populations with little variation than for customer populations with wide variation.
A high-performance hardware architecture of an image matching system based on the optimised SIFT algorithm

The Scale Invariant Feature Transform (SIFT) is one of the most popular matching algorithms in the field of computer vision. It takes over many other algorithms because features detected are fully invariant to image scaling and rotation, and are also shown to be robust to changes in 3D viewpoint, addition of noise, changes in illumination and a sustainable range of affine distortion. However, the computational complexity is high, which prevents it from achieving real-time. The aim of this project, therefore, is to develop a high-performance image matching system based on the optimised SIFT algorithm to perform real-time feature detection, description and matching. This thesis presents the stages of the development of the system. To reduce the computational complexity, an alternative to the grid layout of standard SIFT is proposed, which is termed as SRI-DASIY (Scale and Rotation Invariant DAISY). The SRI-DAISY achieves comparable performance with the standard SIFT descriptor, but is more efficient to be implemented using hardware, in terms of both computational complexity and memory usage. The design takes only 7.57 µs to generate a descriptor with a system frequency of 100 MHz, which is equivalent to approximately 132,100 descriptors per second and is of the highest throughput when compared with existing designs. Besides, a novel keypoint matching strategy is also presented in this thesis, which achieves higher precision than the widely applied distance ratio based matching and is computationally more efficient. All phases of the SIFT algorithm have been investigated, including feature detection, descriptor generation and descriptor matching. The characterisation of each individual part of the design is carried out and compared with the software simulation results. A fully stand-alone image matching system has been developed that consists of a CMOS camera front-end for image capture, a SIFT processing core embedded in a Field Programmable Logic Array (FPGA) device, and a USB back-end for data transfer. Experiments are conducted by using real-world images to verify the system performance. The system has been tested by integrating into two practical applications. The resulting image matching system eliminates the bottlenecks that limit the overall throughput of the system, and hence allowing the system to process images in real-time without interruption. The design can be modified to adapt to the applications processing images with higher resolution and is still able to achieve real-time.
Hessian-assisted supervoxel: structure-oriented voxel clustering and application to mediastinal lymph node detection from CT volumes

In this paper, we propose a novel supervoxel segmentation method designed for mediastinal lymph node by embedding Hessian-based feature extraction. Starting from a popular supervoxel segmentation method, SLIC, which computes supervoxels by minimising differences of intensity and distance, we overcome this method's limitation of merging neighboring regions with similar intensity by introducing Hessian-based feature analysis into the supervoxel formation. We call this structure-oriented voxel clustering, which allows more accurate division into distinct regions having blob-, line- or sheet-like structures. This way, different tissue types in chest CT volumes can be segmented individually, even if neighboring tissues have similar intensity or are of non- spherical extent. We demonstrate the performance of the Hessian-assisted supervoxel technique by applying it to mediastinal lymph node detection in 47 chest CT volumes, resulting in false positive reductions from lymph node candidate regions. 89 % of lymph nodes whose short axis is at least 10 mm could be detected with 5.9 false positives per case using our method, compared to our previous method having 83 % of detection rate with 6.4 false positives per case.