Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse methods for hyperspectral unmixing and image fusion

In recent years, the substantial increase in the number of spectral channels in optical remote sensing sensors allows more detailed spectroscopic analysis of objects on the Earth surface. Modern hyperspectral sensors are able to sample the sunlight reflected from a target on the ground with hundreds of adjacent narrow spectral channels. However, the increased spectral resolution comes at the price of a lower spatial resolution, e.g. the forthcoming German hyperspectral sensor Environmental Mapping and Analysis Program (EnMAP) which will have 244 spectral channels and a pixel size on ground as large as 30 m $\times$ 30 m. The main aim of this thesis is dealing with the problem of reduced spatial resolution in hyperspectral sensors. This is addressed first as an unmixing problem, i.e., extraction and quantification of the spectra of pure materials mixed in a single pixel, and second as a resolution enhancement problem based on fusion of multispectral and hyperspectral imagery. This thesis proposes novel methods for hyperspectral unmixing using sparse approximation techniques and external spectral dictionaries, which unlike traditional least squares-based methods, do not require pure material spectrum selection step and are thus able to simultaneously estimate the underlying active materials along with their respective abundances. However, in previous works it has been shown that these methods suffer from some drawbacks, mainly from the intra dictionary coherence. To improve the performance of sparse spectral unmixing, the use of derivative transformation and a novel two step group unmixing algorithm are proposed. Additionally, the spatial homogeneity of abundance vectors by introducing a multi-look model for spectral unmixing is exploited. % Based on the above findings, a new method for fusion of hyperspectral images with higher spatial resolution multispectral images is proposed. The algorithm exploits the spectral information of the hyperspectral image and the spatial information from the multispectral image by means of sparse spectral unmixing to form a new high spatial and spectral resolution hyperspectral image. The introduced method is robust when applied to highly mixed scenarios as it relies on external spectral dictionaries. Both the proposed sparse spectral unmixing algorithms as well as the resolution enhancement approach are evaluated quantitatively and qualitatively. Algorithms developed in this thesis are significantly faster and yield better or similar results to state-of-the-art methods.
A Case of Ocular Angiostrongyliasis with Molecular Identification of the Species in Vietnam

A 23-year-old female residing in a village of Cao Bang Province, North Vietnam, visited the Hospital of Hanoi Medical University in July 2013. She felt dim eyes and a bulge-sticking pain in her left eye for some days before visiting the hospital. In the hospital, a clinical examination, an eye endoscopy, and an operation were carried out. A nematode specimen was collected from the eye of this patient. The body of this worm was thin and long and measured 22.0×0.3 mm. It was morphologically suggested as an immature female worm of Angiostrongylus cantonensis. By a molecular method using 18S rRNA gene, this nematode was confirmed as A. cantonensis. This is the first molecular study for identification of A. cantonensis in Vietnam.
Serum Levels of Advanced Glycosylation End Products in Diabetic Nephropathy

Background/Aims: Advanced glycosylation end products (AGEs) are important pathogenetic factors underlying diabetic complications. Recently, a highly reliable new enzyme-linked immunosorbent assay for these metabolites has been established. We used the assay to correlate AGEs in serum with renal function categories and histopathology in patients with diabetic nephropathy. Methods: Type 2 diabetic patients (n = 71) and healthy control subjects (n = 35) were studied. The diabetic subjects were divided into two groups: normal renal function and chronic renal failure not requiring dialysis. In renal biopsy specimens from 22 diabetic subjects with a normal renal function, the severity of glomerular lesions was assessed morphometrically in terms of the ratio of the area of periodic acid-Schiff stained mesangium to total glomerular area. Results: The serum AGE concentrations were higher in both undialyzed diabetic groups, especially in those with renal failure, than in the controls. The serum AGE concentrations increased with the severity of glomerular lesions (morphometric ratio under 15%, 2.85 ± 0.73 mU/ml; 15–24%, 4.01 ± 0.71 mU/ml; 25% or more, 5.12 ± 0.64 mU/ml). Conclusions: The serum AGE levels measured by the new enzyme-linked immunosorbent assay reflected the severity of glomerulopathy, and, therefore, it may be a clinically useful tool for assessing diabetic renal complications.
Refinement of SDBC Business Process Models Using ISDL

Aiming at aligning business process modeling and software specification, the SDBC approach considers a multi-viewpoint modeling where static, dynamic, and data business process aspect models have to be mapped adequately to corresponding static, dynamic, and data software specification aspect models. Next to that, the approach considers also a business process modeling viewpoint which concerns real-life communication and coordination issues, such as meanings, intentions, negotiations, commitments, and obligations. Hence, in order to adequately align communication and dynamic aspect models, SDBC should use at least two modeling techniques. However, the transformation between two techniques unnecessarily complicates the modeling process. Next to that, different techniques use different modeling formalisms whose reflection sometimes causes limitations. For this reason, we explore in the current paper the value which the (modeling) language ISDL could bring to SDBC in the alignment of communication and behavioral (dynamic) business process aspect models; ISDL can usefully refine dynamic process models. Thus, it is feasible to expect that ISDL can complement the SDBC approach, allowing refinement of dynamic business process aspect models, by adding communication and coordination actions. Furthermore, SDBC could benefit from ISDL-related methods assessing whether a realized refinement conforms to the original process model. Our studies in the paper are supported by an illustrative example.
In vivo regulation of alternative pre-mRNA splicing by the Clk1 protein kinase

Controlled expression of cellular and viral genes through alternative precursor messenger RNA (pre-mRNA) splicing requires serine/arginine-rich (SR) proteins. The Clk1 kinase, which phosphorylates SR proteins, is regulated through alternative splicing of the Clk1 pre-mRNA, yielding mRNAs encoding catalytically active and truncated inactive polypeptides (Clk1 and Clk1T, respectively). We present evidence that Clk1 and Clk1T proteins regulate the splicing of Clk1 and adenovirus pre-mRNAs in vivo. The peptide domain encoded by the alternatively spliced exon of Clk1 is essential for the regulatory activity of the Clk1 kinase. This is the first direct demonstration of an in vivo link between alternative splicing and protein kinase activity.
A novel approach for intelligent pre-crash threat assessment systems

Compared to the state-of-the-art on integrated safety systems, earlier activated safety systems can further reduce the risk of suffering a major injury. Activation of such systems prior to a collision can be realized by analysing measurements of exteroceptive sensors (pre-crash data). An algorithm for estimating collisions in real-time using fused measurements of a video camera, a laser range finder (LRF), and ego vehicle motion sensors is presented. The threat posed by the actual driving situation is assessed by calculating a certain risk value, which is determined by combining the collision probability and crash severity estimations in a comprehensive way. A scale model vehicle is introduced to capture characteristics of the proposed system experimentally. First test runs show that the object width measurement is very accurate (absolute error of 5%) and the maximum time to collision (TTC) estimation error is around 17% about 300ms before the impact. Comparing different obstacles and impact scenarios (e.g. small overlap vs. full frontal collision), the calculated risk is a promising new measure to early discriminate crash types.
Positive Outcomes Enhance Incidental Learning for Both Younger and Older Adults

Previous studies suggest that memory encoding is enhanced when people are anticipating a potential reward, consistent with the idea that dopaminergic systems that respond to motivationally relevant information also enhance memory for that information. In the current study, we examined how anticipating and receiving rewards versus losses affect incidental learning of information. In addition, we compared the modulatory effects of reward anticipation and outcome on memory for younger and older adults. Forty-two younger (aged 18–33 years) and 44 older (aged 66–92 years) adults played a game involving pressing a button as soon as they saw a target. Gain trials began with a cue that they would win $0.25 if they pressed the button fast enough, loss trials began with a cue that they would avoid losing $0.25 if they pressed the button fast enough, and no-outcome trials began with a cue indicating no monetary outcome. The target was a different photo-object on each trial (e.g., balloon, dolphin) and performance outcomes were displayed after the photo disappeared. Both younger and older adults recalled and recognized pictures from trials with positive outcomes (either rewarding or loss avoiding) better than from trials with negative outcomes. Positive outcomes were associated with not only enhanced memory for the picture just seen in that trial, but also with enhanced memory for the pictures shown in the next two trials. Although anticipating a reward also enhanced incidental memory, this effect was seen only in recognition memory of positive pictures and was a smaller effect than the outcome effect. The fact that older adults showed similar incidental memory effects of reward anticipation and outcome as younger adults suggests that reward–memory system interactions remain intact in older age.
Revenue-Optimized Webpage Recommendation

As a massive industry, display advertising delivers advertisers' marketing messages to attract customers throughbanners shown on webpages. For publishers, i.e. websites, display advertising is the most critical revenue source. Most existing webpage recommender systems suggest webpages based on user interests only. However, the articles of interest to specific users may not be profitable to publishers. Conversely, only recommending the most profitable articles may lose publishers' user base. To address this issue, we will conduct a series of investigations and design Revenue-Optimized Recommendation, aims to recommend users webpages that optimize interestingness and ad revenue.
Credibility as Signal: Predicting Evaluations of Credibility by a Signal-Based Model

In this paper we propose the model of signal for objects that are subject to evaluation by crowdsourcing. Such signal, constructed as probability of distribution using Normal Random Utility Model (NRUM), can be used to measure object's performance, create rankings or predict next evaluations. Our model is designed for monadic scale evaluations where evaluators can have different expertise or bias for using scale. Moreover, our model is constructed for situations where we can have a lot of missing evaluations or varying numbers of evaluations for each object and from each evaluator, typical for crowdsourcing data. We have built a model for medical Web pages credibility from real crowdsourcing data and have evaluated the model's predictive ability, proving its superiority to alternative prediction methods.
Physical Growth, Biological Age, and Nutritional Transitions of Adolescents Living at Moderate Altitudes in Peru

Background: Peru is experiencing a stage of nutritional transition where the principal characteristics are typical of countries undergoing development. Objectives: The objectives of this study were the following: (a) compare physical growth patterns with an international standard; (b) determine biological age; and (c) analyze the double nutritional burden of adolescents living at a moderate altitude in Peru. Design: Weight, standing height, and sitting height were measured in 551 adolescents of both sexes (12.0 to 17.9 years old) from an urban area of Arequipa, Peru (2328 m). Physical growth was compared with the international standard of the CDC-2000. Biological age was determined by using a non-invasive transversal technique based on years from age at peak height velocity (APHV). Nutritional state was determined by means of weight for age and height for age. Z scores were calculated using international standards from the CDC-2000. Results: Body weight for both sexes was similar to the CDC-2000 international standards. At all ages, the girls’ height (p < 0.05) was below the standards. However, the boys’ height (p < 0.05) was less at ages, 15, 16, and 17. Biological age showed up in girls at age 12.7 years and for boys at 15.2 years. Stunted growth (8.7% boys and 18.0% girls) and over weight (11.3% boys and 8.8% girls) occurred in both groups. A relationship existed in both sexes between the categories of weight for the age and stunted growth by sex. Conclusions: Adolescents living at a moderate altitude exhibited stunted linear growth and biological maturation. Furthermore, adolescents of both sexes showed the presence of the double nutritional burden (stunted growth and excessive weight).
Beyond the High-Performance Paradigm? An Analysis of Variation in Canadian Managerial Perceptions of Reform Programme Effectiveness

Proponents of the high-performance paradigm often argue that the variable success of new forms of work organization is explained primarily by a failure to implement them comprehensively and to adopt complementary HRM practices. This paper argues that these explanations are inadequate and develops an alternative, political economy approach which accounts more fully for how conflicts embedded in the employment relation limit the effectiveness of reforms. It draws on a unique longitudinal data set representing 78 Canadian workplaces to analyse the extent to which reform programme content, pre-existing HRM conditions and workplace context variables are associated with reform programme effectiveness. Copyright Blackwell Publishers Ltd/London School of Economics 2001.
Chymase Mediates Injury and Mitochondrial Damage in Cardiomyocytes during Acute Ischemia/Reperfusion in the Dog

Cardiac ischemia and reperfusion (I/R) injury occurs because the acute increase in oxidative/inflammatory stress during reperfusion culminates in the death of cardiomyocytes. Currently, there is no drug utilized clinically that attenuates I/R injury in patients. Previous studies have demonstrated degranulation of mast cell contents into the interstitium after I/R. Using a dog model of I/R, we tested the role of chymase, a mast cell protease, in cardiomyocyte injury using a specific oral chymase inhibitor (CI). 15 adult mongrel dogs had left anterior descending artery occlusion for 60 min and reperfusion for 100 minutes. 9 dogs received vehicle and 6 were pretreated with a specific CI. In vivo cardiac microdialysis demonstrated a 3-fold increase in interstitial fluid chymase activity in I/R region that was significantly decreased by CI. CI pretreatment significantly attenuated loss of laminin, focal adhesion complex disruption, and release of troponin I into the circulation. Microarray analysis identified an I/R induced 17-fold increase in nuclear receptor subfamily 4A1 (NR4A1) and significantly decreased by CI. NR4A1 normally resides in the nucleus but can induce cell death on migration to the cytoplasm. I/R caused significant increase in NR4A1 protein expression and cytoplasmic translocation, and mitochondrial degradation, which were decreased by CI. Immunohistochemistry also revealed a high concentration of chymase within cardiomyocytes after I/R. In vitro, chymase added to culture HL-1 cardiomyocytes entered the cytoplasm and nucleus in a dynamin-dependent fashion, and promoted cytoplasmic translocation of NR4A1 protein. shRNA knockdown of NR4A1 on pre-treatment of HL-1 cells with CI significantly decreased chymase-induced cell death and mitochondrial damage. These results suggest that the beneficial effects of an orally active CI during I/R are mediated in the cardiac interstitium as well as within the cardiomyocyte due to a heretofore-unrecognized chymase entry into cardiomyocytes.
Fault-Tolerant RFID Reader Localization Based on Passive RFID Tags

With the growing use of RFID-based devices, there are increasing attentions on utilizing RFID technology for localization. In this paper, we consider RFID reader localization which locates an object by attaching it with an RFID reader that communicates with passive RFID tags deployed in the environment. One difficulty in RFID reader localization is that frequent RFID faults can affect localization accuracy. More specifically, in a complex localization environment, metal, water, obstacles, etc., causes some tags to fail to communicate with the reader, and consequently the localization result may deviate from the real location. For permanent faults, existing localization approaches can tolerate only faults that occur at individual tags, by utilizing the redundant information from their neighboring tags. However, these approaches cannot handle permanent faults that occur at a group of neighboring tags in a region, which is referred to as regional permanent fault. They will suffer from serious localization errors if such kind of faults occurs. Moreover, existing work lacks quality measurement of localization results, hence the user may be not aware how serious the localization errors can be. In this paper, we propose an effective fault-tolerant RFID reader localization approach that can handle regional permanent fault, and provide quality measurement of localization results. Our approach is applied to both 2D and 3D localization applications. We further study the network localization problem where some objects know their locations and the other objects determine their locations by measuring the distances to their neighbors. Using the localization results and especially the quality information obtained by our approach, we solve the network localization problem with improved localization accuracy. Evaluation results show that our approach outperforms existing approaches in localization accuracy and can provide additional useful quality information.
Inference of Boolean Networks Using Sensitivity Regularization

The inference of genetic regulatory networks from global measurements of gene expressions is an important problem in computational biology. Recent studies suggest that such dynamical molecular systems are poised at a critical phase transition between an ordered and a disordered phase, affording the ability to balance stability and adaptability while coordinating complex macroscopic behavior. We investigate whether incorporating this dynamical system-wide property as an assumption in the inference process is beneficial in terms of reducing the inference error of the designed network. Using Boolean networks, for which there are well-defined notions of ordered, critical, and chaotic dynamical regimes as well as well-studied inference procedures, we analyze the expected inference error relative to deviations in the networks' dynamical regimes from the assumption of criticality. We demonstrate that taking criticality into account via a penalty term in the inference procedure improves the accuracy of prediction both in terms of state transitions and network wiring, particularly for small sample sizes.
The Brown Bear and the American Eagle of Reading Research: Steven A. Stahl and Michael Pressley Remembered

This essay reviews the contribution to reading research of two scholars who died young, Steven Stahl and Michael Pressley, whose work is reflected in, respectively, Reading Research at Work: Foundations of Effective Practice, edited by Katherine A. Dougherty Stahl and Michael C. McKenna, and Shaping Literacy Achievement: Research We Have, Research We Need, edited by Michael Pressley and colleagues. Both books attempt an overview of research in reading in light of the report of the U.S. National Reading Panel (NRP). The Stahl volume focuses particularly on the NRP themes of teaching phonics, developing fluency and vocabulary, and comprehension. The Pressley volume focuses on themes the NRP did not review, including preschool literacy, home-school literacies, adolescent literacy, and content area reading. Both books deal in depth with the development of reading comprehension, and each is, in its own way, very successful.
Semi-autonomous data enrichment based on cross-task labelling of missing targets for holistic speech analysis

In this work, we propose a novel approach for large-scale data enrichment, with the aim to address a major shortcoming of current research in computational paralinguistics, namely, looking at speaker attributes in isolation although strong interdependencies between them exist. The scarcity of multi-target databases, in which instances are labelled for different kinds of speaker characteristics, compounds this problem. The core idea of our work is to join existing data resources into one single holistic database with a multi-dimensional label space by using semi-supervised learning techniques to predict missing labels. In the proposed new Cross-Task Labelling (CTL) method, a model is first trained on the labelled training set of the selected databases for each individual task. Then, the trained classifiers are used for the crosslabelling of databases among each other. To exemplify the effectiveness of the `CTL' method, we evaluated it for likability, personality, and emotion recognition as representative tasks from the INTERSPEECH Computational Paralinguistics ChallengE (ComParE) series. The results show that `CTL' lays the foundation for holistic speech analysis by semi-autonomously annotating the existing databases, and expanding the multi-target label space at the same time, while achieving higher accuracy as the baseline performance of the challenges.
TRANSFORMATIONS ON REGULAR NONDOMINATED COTERIES AND THEIR APPLICATIONS

A coterie under an underlying set U is a family of subsets of U such that every pair of subsets has at least one element in common, but neither is a subset of the other. A coterie C under U is said to be nondominated (ND) if there is no other coterie D under U such that, for every Q ∈ C, there exists Q ∈ D satisfying Q ⊆ Q. We introduce the operation σ which transforms a ND coterie to another ND coterie. A regular coterie is a natural generalization of a vote-assignable coterie. We show that any regular ND coterie C can be transformed to any other regular ND coterie D by judiciously applying the σ operation to C at most |C| + |D| − 2 times. As another application of the σ operation, we present an incrementally polynomial-time algorithm for generating all regular ND coteries. We then introduce the concept of a g-regular functional as a generalization of availability. We show how to construct an optimum coterie C with respect to a g-regular functional in O(n3|C|) time, where n = |U |. Finally, we discuss the structures of optimum coteries with respect to a g-regular functional.