Miracle-dz/UniFAR-FTUs huggingface dataset:
Koncepcja uproszczonego modelowania relacji "Użytkowanie terenu - zanieczyszczenie wód" w małych zlewniach górskich

The paper deals with modelling the relationship between the quality of surface waters and land use in small mountain catchments. Much easier and often more practical is to create simplified models that consider only selected hydrologic and infrastructural factors. The land use factor W which is a weighed average of quantified types of land use has been estimated to calculate the concentration of some pollutants in surface waters. A strong correlation has been found between the character of land use in the catchment and nutrients in surface waters. The concentration of natural components in surface waters (e.g. Ca, Mg and SO 4 ) has not, however, correlated with the type of land use. Simple models are very practical to calculate approximate concentrations based only on the land use structure.
Comparison of mechanical, biological and chemical methods for controlling Black cherry (Prunus serotina) in Flanders (Belgium)

Large scale application of black cherry (Prunus serotina Ehrh.) in forestry and the typical ecological characteristics of the species resulted in its dominance of the shrublayer in homogeneous pine forests on poor sandy soils in Flanders. For reasons of nature conservation Flemish forest policy and management tries to transform these forests into more natural and structural deciduous forests. Controlling Black cherry is seen as a major condition for succes in this matter. In this study the lethal effect of mechanical, biological and chemical control methods was tested using an experimental block design. The methods consisted of girdling and felling with periodical removal of new sprouts, stump and stem treatment with mycoherbicide based on the Silverleaf disease fungus (Chondrostereum purpureum Pouzar), leaf and stump treatment with the herbicide glyphosate and stem treatments with the same herbicide using different techniques like the Hack & Squirt method, the EZject Capsule Injection System and the Silvaxe Tree Injector. The results indicated that a proper comparison can only be made after evaluation in the second autumn after treatment at the earliest. All chemical control methods, except one (Silvaxe Tree Injector System), showed a significant higher proportional mortality than mechanical and biological control methods. No statistical proof was found of a seasonal influence on mortality for the chemical methods. Application of the Hack & Squirt method and the EZject Capsule Injection System in summertime resulted in a significantly higher proportional mortality than leaf treatment and stump treatment in autumn. Lethal doses of glyphosate for different dbh-classes were calculated resulting in easy to use application procedures for stem treatment. The high lethal effect of the Hack & Squirt method confirmed their practical value. No significant seasonal influence on mortality nor any significant impact of mycoherbicide concentration was found for the biological stump treatments. Stem treatment with mycoherbicide proved inappropriate. The best season for girdling appears to be springtime while additional test indicate that wintertime could be even more appropriate. The lowest Significant proportional mortality for girdling and felling with one additional removal of sprouts was found in summertime. A high variability in proportional mortality was detected for the mechanical methods and in a lesser degree for the biological methods, sometimes approximating or even equaling the mortality rate of chemical methods. If environmental considerations have to be taken into account or if chemical control is legally forbidden (e.g. forest reserves in Flanders) biological stump treatment and girdling offer a valuable alternative. Their variable mortality can lead to unpredictable results though.
Sampling directed graphs with random walks

Despite recent efforts to characterize complex networks such as citation graphs or online social networks (OSNs), little attention has been given to developing tools that can be used to characterize directed graphs in the wild, where no pre-processed data is available. The presence of hidden incoming edges but observable outgoing edges poses a challenge to characterize large directed graphs through crawling, as existing sampling methods cannot cope with hidden incoming links. The driving principle behind our random walk (RW) sampling method is to construct, in real-time, an undirected graph from the directed graph such that the random walk on the directed graph is consistent with one on the undirected graph. We then use the RW on the undirected graph to estimate the outdegree distribution. Our algorithm accurately estimates outdegree distributions of a variety of real world graphs. We also study the hardness of indegree distribution estimation when indegrees are latent (i.e., incoming links are only observed as outgoing edges). We observe that, in the same scenarios, indegree distribution estimates are highly innacurate unless the directed graph is highly symmetrical.
Shared genetic variance between obesity and white matter integrity in Mexican Americans

Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N = 761, 58% females, ages 18–81 years; 41.3 ± 14.5) from the Genetics of Brain Structure and Function Study. Shared genetic variance was calculated between measures of adiposity [(body mass index (BMI; kg/m2) and waist circumference (WC; in)] and whole-brain and regional measurements of cerebral white matter integrity (fractional anisotropy). Whole-brain average and regional fractional anisotropy values for 10 major white matter tracts were calculated from high angular resolution diffusion tensor imaging data (DTI; 1.7 × 1.7 × 3 mm; 55 directions). Additive genetic factors explained intersubject variance in BMI (heritability, h2 = 0.58), WC (h2 = 0.57), and FA (h2 = 0.49). FA shared significant portions of genetic variance with BMI in the genu (ρG = −0.25), body (ρG = −0.30), and splenium (ρG = −0.26) of the corpus callosum, internal capsule (ρG = −0.29), and thalamic radiation (ρG = −0.31) (all p's = 0.043). The strongest evidence of shared variance was between BMI/WC and FA in the superior fronto-occipital fasciculus (ρG = −0.39, p = 0.020; ρG = −0.39, p = 0.030), which highlights region-specific variation in neural correlates of obesity. This may suggest that increase in obesity and reduced white matter integrity share common genetic risk factors.
Attribute selection for fault location recognition in transmission lines

After a severe disturbance due to an insulation failure in a transmission line, the precise fault location is a critical problem for the maintenance crew. In order to avoid further economical and social costs, fault diagnosis has to be performed as soon as possible. Fault diagnosis has been a major area of investigation among power system problems and intelligent system applications. Several approaches have been proposed for solving this problem. This paper advocates the application of support vector machines for mapping the relationship between electrical signals and fault locations in transmission lines. The significance of voltages and currents is analyzed using steady-state and electromagnetic transient information, i.e., two ways of feeding the fault location models are compared. The tests consider different operating and fault conditions, including different types of fault, a variety of fault impedances, fault angles, line loading, equivalent system impedances, and fault locations
An in-depth analysis of stochastic Kronecker graphs

Graph analysis is playing an increasingly important role in science and industry. Due to numerous limitations in sharing real-world graphs, models for generating massive graphs are critical for developing better algorithms. In this article, we analyze the stochastic Kronecker graph model (SKG), which is the foundation of the Graph500 supercomputer benchmark due to its favorable properties and easy parallelization. Our goal is to provide a deeper understanding of the parameters and properties of this model so that its functionality as a benchmark is increased. We develop a rigorous mathematical analysis that shows this model cannot generate a power-law distribution or even a lognormal distribution. However, we formalize an enhanced version of the SKG model that uses random noise for smoothing. We prove both in theory and in practice that this enhancement leads to a lognormal distribution. Additionally, we provide a precise analysis of isolated vertices, showing that the graphs that are produced by SKG might be quite different than intended. For example, between 50% and 75% of the vertices in the Graph500 benchmarks will be isolated. Finally, we show that this model tends to produce extremely small core numbers (compared to most social networks and other real graphs) for common parameter choices.
SCURVY IN CAPYBARAS BRED IN CAPTIVITY IN ARGENTINE

In order to determine if the absence of vitamin C in the diet of capybaras (Hydrochoerus hydrochaeris) causes scurvy, a group of seven young individuals were fed food pellets without ascorbic acid, while another group of eight individuals received the same food with 1 g of ascorbic acid per animal per day. Animals in the first group developed signs of scurvy-like gingivitis, breaking of the incisors and death of one animal. Clinical signs appeared between 25 and 104 days from the beginning of the trial in all individuals. Growth rates of individuals deprived of vitamin C was considerably less than those observed in the control group. Deficiency of ascorbic acid had a severe effect on reproduction of another population of captive capybaras. We found that the decrease in ascorbic acid content in the diet affected pregnancy, especially during the first stages. The results obtained suggest that it is necessary to supply a suitable quantity of vitamin C in the diet of this species in captivity.
Image-Based Measurement of Alveoli Volume Expansion in an Animal Model of a Diseased Lung

Currently, there does not exist reliable MV treatment or protocols in critical care to treat acute respiratory diseases, and thus no proven way to optimise care to minimise the mortality, length of stay or cost. The overall approach of this research is to improve protocols by using appropriate computer models that take into account the essential lung mechanics. The aim of this research is to create an automated algorithm for tracking the boundary of individual or groups of alveoli, and to convert this into a pressure volume curve for three different types of alveoli. A technique called in vivo microscopy has been developed by Schiller et al which visualizes the inflation and deflation of individual alveoli in a surfactant deactivation model of lung injury in pigs. Three different types of alveoli were tracked using data from Schiller et al, type I, II and III. These types correspond to healthy alveoli, non-collapsing but partially diseased alveoli, and fully collapsing diseased alveoli respectively. The boundaries of all the alveoli that were tracked, compared well visually to the movies. Pressure versus Area curves were derived for both inflation and deflation, they captured the expected physiological behaviour, and were qualitatively similar to the quasi-static pressure area curves derived in Schiller et al, Quantitative differences are due to the dynamic effects of ventilation which were not investigated in Schiller et al.
Recommender systems for the conference paper assignment problem

We present a recommender systems approach to conference paper assignment, i.e., the task of assigning paper submissions to reviewers. We address both the modeling of reviewer-paper preferences (which can be cast as a learning problem) and the optimization of reviewing assignments to satisfy global conference criteria (which can be viewed as constraint satisfaction). Due to the paucity of preference data per reviewer or per paper (relative to other recommender systems applications) we show how we can integrate multiple sources of information to learn reviewer-paper preference models. Our models are evaluated not just in terms of prediction accuracy but in terms of end-assignment quality. Using a linear programming-based assignment optimization, we show how our approach better explores the space of unsupplied assignments to maximize the overall affinities of papers assigned to reviewers. We demonstrate our results on real reviewer bidding data from the IEEE ICDM 2007 conference.
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain

The Conjugate Gradient Method is the most prominent iterative method for solving sparse systems of linear equations. Unfortunately, many textbook treatments of the topic are written so that even their own authors would be mystified, if they bothered to read their own writing. For this reason, an understanding of the method has been reserved for the elite brilliant few who have painstakingly decoded the mumblings of their forebears. Nevertheless, the Conjugate Gradient Method is a composite of simple, elegant ideas that almost anyone can understand. Of course, a reader as intelligent as yourself will learn them almost effortlessly. The idea of quadratic forms is introduced and used to derive the methods of Steepest Descent, Conjugate Directions, and Conjugate Gradients. Eigenvectors are explained and used to examine the convergence of the Jacobi Method, Steepest Descent, and Conjugate Gradients. Other topics include preconditioning and the nonlinear Conjugate Gradient Method. I have taken pains to make this article easy to read. Sixty-two illustrations are provided. Dense prose is avoided. Concepts are explained in several different ways. Most equations are coupled with an intuitive interpretation.
Summarizing web forum threads based on a latent topic propagation process

With an increasingly amount of information in web forums, quick comprehension of threads in web forums has become a challenging research problem. To handle this issue, this paper investigates the task of Web Forum Thread Summarization (WFTS), aiming to give a brief statement of each thread that involving multiple dynamic topics. When applied to the task of WFTS, traditional summarization methods are cramped by topic dependencies, topic drifting and text sparseness. Consequently, we explore an unsupervised topic propagation model in this paper, the Post Propagation Model (PPM), to burst through these problems by simultaneously modeling the semantics and the reply relationship existing in each thread. Each post in PPM is considered as a mixture of topics, and a product of Dirichlet distributions in previous posts is employed to model each topic dependencies during the asynchronous discussion. Based on this model, the task of WFTS is accomplished by extracting most significant sentences in a thread. The experimental results on two different forum data sets show that WFTS based on the PPM outperforms several state-of-the-art summarization methods in terms of ROUGE metrics.
RF voltage limiters for passive differential UHF RFID front-ends in a 40 nm CMOS technology

Passive differential UHF radiofrequency identification (RFID) front-ends may experience at high input power levels voltage amplitudes exceeding the maximum voltage ratings of the respective CMOS technology. The risk of damaging overvoltage stress increases significantly with circuits moving to technologies below the 100nm node. This work gives a discussion on characteristics of central building blocks of a UHF RFID frontend in a 40nm low-power CMOS technology under high-power conditions. The investigation reveals the limitations of front-ends without dedicated RF limiter structures. Thus, we present two stand-alone RF voltage limiter designs that mitigate overvoltage stress risks. Simulation results demonstrate the capability of the two RF limiter circuits to restrict the voltage amplitude to values of lower than 1.1V at an available power of 20 dBm.
Specific Reactions of Different Striatal Neuron Types in Morphology Induced by Quinolinic Acid in Rats

Huntington's disease (HD) is a neurological degenerative disease and quinolinic acid (QA) has been used to establish HD model in animals through the mechanism of excitotoxicity. Yet the specific pathological changes and the underlying mechanisms are not fully elucidated. We aimed to reveal the specific morphological changes of different striatal neurons in the HD model. Sprague-Dawley (SD) rats were subjected to unilaterally intrastriatal injections of QA to mimic the HD model. Behavioral tests, histochemical and immunhistochemical stainings as well as Western blots were applied in the present study. The results showed that QA-treated rats had obvious motor and cognitive impairments when compared with the control group. Immunohistochemical detection showed a great loss of NeuN+ neurons and Darpp32+ projection neurons in the transition zone in the QA group when compared with the control group. The numbers of parvalbumin (Parv)+ and neuropeptide Y (NPY)+ interneurons were both significantly reduced while those of calretinin (Cr)+ and choline acetyltransferase (ChAT)+ were not changed notably in the transition zone in the QA group when compared to the controls. Parv+, NPY+ and ChAT+ interneurons were not significantly increased in fiber density while Cr+ neurons displayed an obvious increase in fiber density in the transition zone in QA-treated rats. The varicosity densities of Parv+, Cr+ and NPY+ interneurons were all raised in the transition zone after QA treatment. In conclusion, the present study revealed that QA induced obvious behavioral changes as well as a general loss of striatal projection neurons and specific morphological changes in different striatal interneurons, which may help further explain the underlying mechanisms and the specific functions of various striatal neurons in the pathological process of HD.
The Use of an Infrared Eyetracker to Measure Fixation Stability

Purpose. To assess fixation stability in patients, a scanning laser ophthalmoscope (SLO) has typically been required. Disadvantages of this technique include the need for a fixed viewing distance and rigid head support. Some modern infrared eyetrackers do not have these constraints. The purpose of this study was to compare fixation stability measurements made with these instruments. Methods. Normal subjects were asked to fixate a 2.5° high cross while fixation was measured with a SLO and an infrared eyetracker. Bivariate contour ellipse areas were calculated. Results. There was a linear relationship between the bivariate contour ellipse areas measured using each instrument. Bivariate contour ellipse areas returned from the eyetracker were larger. There was no difference in test-retest variability between the instruments. Conclusions. The eyetracker indicates fixation to be less stable than the SLO does, perhaps because of eye movements to compensate for small head movements. Our eyetracker can be used to analyze fixation when viewing images at any distance, without the need for head immobilization. The eyetracker and the SLO complement each other in the investigation of visual behavior.
Stem Cell-Like Side Populations in Esophageal Cancer : A Source of Chemotherapy Resistance and Metastases

Dye-effluxing side population (SP) cells can be resistant to chemotherapy and are thought to resemble cancer stem cells. We characterized the relevance of the SP subpopulation in esophageal cancer cell lines and their relation to chemotherapy resistance and metastasis. The SP subpopulation was detected using Hoechst 33342 staining in five esophageal cancer cell lines OE19, OE21, OE33, PT1590, and LN1590. CTx-resistant cell lines were developed after long-term exposure to 5-fluorouracil (5-FU) and cisplatin and validated by analysis of resistance markers, thymidylate synthase and ERCC1. While neither LN1590 nor PT1590 had detectable SP cells, OE19, OE21, and OE33 cells were found to contain varying levels of SP cells. With increasing duration of 5-FU or cisplatin therapy, the SP subpopulation substantially emerged in PT1590 and LN1590. OE19-SP cells displayed significant higher tumorigenicity than OE19non-SP (NSP) cells after subcutaneous tumor cell injection in vivo. SP cells isolated from OE19 and OE19/5-FUres were subsequently analyzed by an epithelial-to-mesenchymal transition (EMT) polymerase chain reaction array. Interestingly, the SP fraction of OE19/5-FUres showed a dramatic upregulation of EMT-related genes compared to the SP fraction of OE19. Our results provide evidence that (1) the proportion of SP cells is different in esophageal cancer, (2) SP cells exhibit stem cell properties and are associated to chemotherapy resistance, and (3) long-term CTx selects for SP cells with an upregulated EMT gene profile, which might be the source of systemic disease relapse. Further investigations are necessary to ideally target these EMT-associated SP cells in esophageal cancer.
On Gaussian random neuronal field model: Moment neuronal network approach

A novel model is proposed to describe the rich dynamics of spiking activities of leaky integrate-and-fire (LIF) neuronal networks via the moment neuronal network approach. Different from the existing neuronal field model (for example, Wilson-Cowan-Amari model) which only takes the first-order moment (mean firing rate) into considerations, we develop a Gaussian random field to qualitatively describe the spatio-temporal distribution of the first- and second-order moments: mean firing rate, variance or coefficient of variation (CV) equivalently, and the coefficient of correlation (CC), of spiking trains. By this neuronal field model, we find out that the firing rate response with respect to the input may be not sigmoidal or even monotonic if the inhibition is stronger than excitation, which leads fruitful dynamical behaviors, in comparison with the sigmoidal response. In addition, within this framework, we can analyse the synchronisation propagation in the LIF neuronal network. We use our Gaussian random field model to investigate how the three key factors: the ratio between inhibition and excitation, the size of synchronous cluster, and the background firing rate, decide the stability of a synfire chain.
Genome-Wide Identification of Expression Quantitative Trait Loci (eQTLs) in Human Heart

In recent years genome-wide association studies (GWAS) have uncovered numerous chromosomal loci associated with various electrocardiographic traits and cardiac arrhythmia predisposition. A considerable fraction of these loci lie within inter-genic regions. The underlying trait-associated variants likely reside in regulatory regions and exert their effect by modulating gene expression. Hence, the key to unraveling the molecular mechanisms underlying these cardiac traits is to interrogate variants for association with differential transcript abundance by expression quantitative trait locus (eQTL) analysis. In this study we conducted an eQTL analysis of human heart. For a total of 129 left ventricular samples that were collected from non-diseased human donor hearts, genome-wide transcript abundance and genotyping was determined using microarrays. Each of the 18,402 transcripts and 897,683 SNP genotypes that remained after pre-processing and stringent quality control were tested for eQTL effects. We identified 771 eQTLs, regulating 429 unique transcripts. Overlaying these eQTLs with cardiac GWAS loci identified novel candidates for studies aimed at elucidating the functional and transcriptional impact of these loci. Thus, this work provides for the first time a comprehensive eQTL map of human heart: a powerful and unique resource that enables systems genetics approaches for the study of cardiac traits.