Miracle-dz/UniFAR-FTUs huggingface dataset:
AUTOMATIC ROAD EXTRACTION BY INTEGRATED ANALYSIS OF IMAGES AND GIS DATA

Accurate 3D road network is a vital component of GIS for many applications, including traffic management, monitoring, city modeling, and visualization. This paper presents a practical system for automated 3D road network reconstruction by integrated processing of color image data and information from existing digital spatial databases. Starting from the existing database, the road attributes and the approximated road geometry are derived. Guided by this knowledge, various features including 3D straight edges, road regions, shadows, roadmarks and zebra crossings are extracted by the developed algorithms. The system then uses and fuses these features, existing information to generate and group road primitives to extract the roads. The key of the system is the use of knowledge as much as possible to increase success rate and reliability of the results, working in 2D images and 3D object space, and use of 2D and 3D interaction when needed. Another advantage of the developed system is that it can correctly and reliably handle problematic areas caused by shadows and occlusions. To complete the road network reconstruction, an efficient approach for road junction modeling has also been developed. The system was originally developed to process stereo images, but it has been modified to work also with orthoimages, thus making it applicable to sensors of unknown geometry. The system has been implemented as a stand-alone software package, and has been tested on a large number of images with different landscape. In this paper, various parts of the developed system are discussed, and the results of our system in the tests conducted independently by our project partner are presented together with the system performance evaluation.
On Exploration of Classifier Ensemble Synergism in Pedestrian Detection

A single feature extractor-classifier is not usually able to deal with the diversity of multiple image scenarios. Therefore, integration of features and classifiers can bring benefits to cope with this problem, particularly when the parts are carefully chosen and synergistically combined. In this paper, we address the problem of pedestrian detection by a novel ensemble method. Initially, histograms of oriented gradients (HOGs) and local receptive fields (LRFs), which are provided by a convolutional neural network, have been both classified by multilayer perceptrons (MLPs) and support vector machines (SVMs). A diversity measure is used to refine the initial set of feature extractors and classifiers. A final classifier ensemble was then structured by an HOG and an LRF as features, classified by two SVMs and one MLP. We have analyzed the following two classes of fusion methods of combining the outputs of the component classifiers: (1) majority vote and (2) fuzzy integral. The first part of the performance evaluation consisted of running the final proposed ensemble over the DaimlerChrysler cropwise data set, which was also artificially modified to simulate sunny and shadowy illumination conditions, which is typical of outdoor scenarios. Then, a window-wise study has been performed over a collected video sequence. Experiments have highlighted a state-of-the-art classification system, performing consistently better than the component classifiers and other methods.
Occurrence and Breaking of Extreme Waves in Deep Water . A Stochastic Approach Revisit

The occurrence of extreme waves in deep sea waters, and their breaking, is examined with the aid of a pdf model of joint amplitudes and frequencies. New wave breaking considerations allow kinematic, dynamic and maximum average slope concepts to be unified in a single breaking criterion that allows the more accurate determination of the limiting amplitudes that extreme waves can reach, incorporating the influence of nonlinearity of the wave field and the premature wave breaking concept. The probability of extreme wave occurrence does not significantly depend on the sea spectrum bandwidth. The breaking probability of extreme waves increases with the inverse wave age, but its dependence on the latter parameter weakens, as the limiting crest height criterion is stiffened. The right variation of sea surface kurtosis, and of the Benjamin Fier Index, with the (inverse) wave age and their lower than unity values reconfirms their relation to the extreme wave occurrence.
Empirical Analysis of Georgian Trade Pattern: Gravity Model

This paper investigates and analyzes the Georgia's data of trade, export and import. The data cover the periods from 2000 to 2011 using the panel data gravity model of trade. For this purpose the large country sample and long time series and a balanced data have been used. The findings through results of analysis revealed that Georgia's trade is positively determined by the size of the economies, GDP per capita, and common history found to be significant factors influencing Georgia's trade pattern. The results also confirm the hypothesis that foreign direct investment (FDI) is positively correlated with trade.
Securing Compliance: A Principled Approach

Bargaining, negotiation and civil penalty sanctions together constitute central techniques used by regulators in securing compliance with the law. This book is a timely exploration of these practices, constructing a principled framework for evaluating their legitimacy and thereby drawing into sharper focus the importance of the constitutional principles in regulatory compliance. Although Australian competition law provides the focal point of the book, its analysis and critique is equally applicable to other competition law regimes and to other areas of business regulation. While there are numerous empirical studies of regulatory enforcement, this book introduces a normative dimension to the debate by seeking to identify whether there are certain principled and ethical limits that inform and circumscribe the limits of legitimate enforcement practice. It is likely to be of interest to scholars in the fields of public law, criminology, economics, and regulation, and may also be of considerable assistance to legal practitioners in providing a principled, legal foundation from which to draw in their dealings with regulators.
Use of Empirically Derived Source‐Destination Models to Map Regional Conservation Corridors

Abstract: The ability of populations to be connected across large landscapes via dispersal is critical to long‐term viability for many species. One means to mitigate population isolation is the protection of movement corridors among habitat patches. Nevertheless, the utility of small, narrow, linear features as habitat corridors has been hotly debated. Here, we argue that analysis of movement across continuously resistant landscapes allows a shift to a broader consideration of how landscape patterns influence connectivity at scales relevant to conservation. We further argue that this change in scale and definition of the connectivity problem improves one's ability to find solutions and may help resolve long‐standing disputes regarding scale and definition of movement corridors and their importance to population connectivity. We used a new method that combines empirically derived landscape‐resistance maps and least‐cost path analysis between multiple source and destination locations to assess habitat isolation and identify corridors and barriers to organism movement. Specifically, we used a genetically based landscape resistance model for American black bears (Ursus americanus) to identify major movement corridors and barriers to population connectivity between Yellowstone National Park and the Canadian border. Even though western Montana and northern Idaho contain abundant public lands and the largest wilderness areas in the contiguous United States, moving from the Canadian border to Yellowstone Park along those paths indicated by modeled gene flow required bears to cross at least 6 potential barriers. Our methods are generic and can be applied to virtually any species for which reliable maps of landscape resistance can be developed.
Personality subtypes in eating disorders: validation of a classification in a naturalistic sample.

BACKGROUND Research has identified three personality subtypes in patients with eating disorders: emotionally dysregulated, constricted and high-functioning/perfectionistic. AIMS To see whether the subtypes are distinguished in ways indicative of valid classification, notably in patterns of adaptive functioning, comorbidity, treatment response and therapeutic interventions. METHOD A random sample of experienced clinicians provided data on 145 patients with bulimic symptoms, including data on eating disorder symptoms, DSM-IV comorbidity, personality pathology, treatment response and treatment interventions. RESULTS Patients categorised as dysregulated had the poorest functioning, most comorbidity and worst outcome, followed by patients in the constricted and high-functioning groups. The three subtypes elicited different therapeutic interventions and accounted for substantial incremental variance in outcome, holding constant the severity of eating disorder symptoms and presence of other Axis I disorders. CONCLUSIONS The data provide accumulating evidence for the validity of three personality subtypes in patients with eating disorders.
Optimum Currency Area Theory: A Framework for Discussion about Monetary Integration

The optimum currency area (OCA) theory tries to answer an almost prohibitively difficult question: what is the optimal number of currencies to be used in one region. The difficulty of the question leads to a low operational precision of OCA theory. Therefore, we argue that the OCA theory is a framework for discussion about monetary integration. We summarize theoretical issues from the classical contributions to the OCA literature in the 1960s to the modern “endogenous view”. A short survey of empirical studies on the OCA theory in the connection with the EMU and the Czech Republic is presented. Finally, we calculate OCA-indexes for the Czech Republic, EU, Germany and Portugal. The index predicts exchange rates variability from the view of traditional OCA criteria and asseses benefit-cost ratio of implementing common currency for a pair of the countries. We compare the structural similarity of the Czech Republic and Portugal to the German economy and find that the Czech economy is closer. The results are reversed when the EU economy is considered as a benchmark country.
The Leavitt path algebras of arbitrary graphs

We extend the notion of the Leavitt path algebra of a graph to include all directed graphs. We show how various ring-theoretic properties of these more general structures relate to the corresponding properties of Leavitt path algebras of row-finite graphs. Specifically, we identify those graphs for which the corresponding Leavitt path algebra is simple; purely infinite simple; exchange; and semiprime. In our final result, we show that all Leavitt path algebras have zero Jacobson radical.
Association of BMI Category Change with TB Treatment Mortality in HIV-Positive Smear-Negative and Extrapulmonary TB Patients in Myanmar and Zimbabwe

Objective The HIV epidemic has increased the proportion of patients with smear-negative and extrapulmonary tuberculosis (TB) diagnoses, with related higher rates of poor TB treatment outcomes. Unlike in smear-positive pulmonary TB, no interim markers of TB treatment progress are systematically used to identify individuals most at risk of mortality. The objective of this study was to assess the association of body mass index (BMI) change at 1 month (±15 days) from TB treatment start with mortality among HIV-positive individuals with smear-negative and extrapulmonary TB. Methods and Findings A retrospective cohort study of adult HIV-positive new TB patients in Médecins Sans Frontières (MSF) treatment programmes in Myanmar and Zimbabwe was conducted using Cox proportional hazards regression to estimate the association between BMI category change and mortality. A cohort of 1090 TB patients (605 smear-negative and 485 extrapulmonary) was followed during TB treatment with mortality rate of 28.9 per 100 person-years. In multivariable analyses, remaining severely underweight or moving to a lower BMI category increased mortality (adjusted hazard ratio 4.05, 95% confidence interval 2.77–5.91, p<0.001) compared with remaining in the same or moving to a higher BMI category. Conclusions We found a strong association between BMI category change during the first month of TB treatment and mortality. BMI category change could be used to identify individuals most at risk of mortality during TB treatment among smear-negative and extrapulmonary patients.
Democracy, Accountability, and Representation: Accountability and Authority: Toward a Theory of Political Accountability

We take it for granted that modern government must be democratic in the sense of deriving its authority directly or indirectly from the people. But democratic governments differ greatly in producing policies that are responsive to the popular will. In part, this variation may be traced to the diverse representational structures of various democratic governments. Electoral institutions are employed not only to choose good public officials, but as mechanisms to hold incumbents accountable to the public, and, in these ways, they may make policies more or less responsive to public wishes. Accountability is, on this view, a property of institutional structures, whereas responsiveness is a consequence of interaction within such structures. Put another way, responsiveness is a measure of how much accountability an institutional structure permits. Of course, responsiveness is not an unmitigated virtue. Most of us want government to be responsive when it comes to matters like building roads and universities, establishing a system of welfare and social security, and deciding how protective we will be of natural resources. What government should do in these cases is not a matter of justice or morality but depends on what cooperative projects citizens wish to undertake. But in the administration of programs in which the dispensing of justice is concerned, and perhaps in the case of managing monetary policy, popular responsiveness is not so attractive. We may want our judges to be accountable to someone in order to ensure that they are not venal or partisan but not because we wish their decisions to respond to popular preferences.
An efficient online system of concept based association rules mining

This paper presents a new text mining system for extracting association rules based on concepts from online textual documents. The system is called developed extracting association rules from textual documents. The mathematical formula of weighting schema is used for labeling the documents automatically and its named fuzzy weighting schema. A new algorithm is proposed for generating association rules based on concepts and it used a data structure of hash table for the mining process. The experiments are applied on a collection of scientific documents that selected from MEDLINE for breast cancer treatments and side effects. The performance of proposed system is compared with the previous Apriori-concept system for the execution time and the evaluation of the extracted association rules. The results show that the number of extracted association rules in the proposed system is always less than that in Apriori-concept system. Moreover, the execution time of proposed system is much better than Apriori-concept system in all cases.
Clinical study on local application of low-dose insulin for promoting wound healing after operation for deep burns

Transplanted free skin flaps are often needed to treat deep burns; their survival, however, is less than optimal. This study examined whether local low-dose insulin injections can promote flap survival and wound healing after surgery. A total of 165 patients who underwent free skin flap transplantation for simple deep burns were enrolled in the study and divided into 5 groups of 33 patients each: Blank control group (no local subcutaneous drug injections), saline control group (saline injections), low-dose insulin group (0.5 units regular insulin injections), medium-dose group (1.0 units regular insulin injections) and high-dose group (2.0 units regular insulin injections). Wound healing and flap survival conditions were assessed and compared among groups. The best wound healing rate found was that of the low-dose insulin injection group where all the parameters measured improved significantly: The healing time was shorter; the blood flow volume, the flap survival, the number of fibroblasts and new vessels increased; the re-epithelialization occurred faster; the infiltration of inflammatory cells was reduced; the expression levels of heat shock protein-90, vascular endothelial growth factor, transforming growth factor-β and interleukin-1 were higher; and the plasma glucose levels only fluctuated slightly. The results clearly demonstrate that a local low-dose insulin regime after flap transplantation can accelerate the healing time and improve the surgical outcome without exerting detrimental secondary effects on the glucose plasma level of deep burn patients.
Pearl's Calculus of Intervention Is Complete

This paper is concerned with graphical criteria that can be used to solve the problem of identifying casual effects from nonexperimental data in a causal Bayesian network structure, i.e., a directed acyclic graph that represents causal relationships. We first review Pearl's work on this topic [Pearl, 1995], in which several useful graphical criteria are presented. Then we present a complete algorithm [Huang and Valtorta, 2006b] for the identifiability problem. By exploiting the completeness of this algorithm, we prove that the three basic do-calculus rules that Pearl presents are complete, in the sense that, if a causal effect is identifiable, there exists a sequence of applications of the rules of the do-calculus that transforms the causal effect formula into a formula that only includes observational quantities.
A Multi-Ontology Approach for Personal Information Management

The increasingly huge volume of personal information stored in a desktop computer is characterized by disparate models, unstructured contents, and implicit knowledge. Aiming at a semantic rich environment, a number of Semantic Desktop frameworks have been proposed, concentrating on different aspects, including organization, manipulation, and visualization of the data. In this paper, we propose a layered and semantic ontology-based framework for personal information management, and we discuss its annotations, associations, and navigation. We also discuss query processing in two cases: query rewriting in a single personal information application, PIA, and that between two PIAs.
CAM Use in Pediatric Neurology: An Exploration of Concurrent Use with Conventional Medicine

Background Previous studies have found that up to 60% of children with neurologic conditions have tried complementary and alternative medicine (CAM). Objective To assess the use of CAM among patients presenting to neurology clinics at two academic centers in Canada. Methods A survey instrument was developed to inquire about use of CAM products and therapies, including reasons for use, perceived helpfulness, and concurrent use with conventional medicine, and administered to patients or their parents/guardians at the Stollery Children's Hospital in Edmonton and the Children's Hospital of Eastern Ontario (CHEO) in Ottawa. Results Overall CAM use at the Stollery was 78%, compared to 48% at CHEO. The most common CAM products used were multi-vitamins (84%), vitamin C (37%), homeopathic remedies (24%), and fish oil/omega 3 s (22%). The most common CAM practices used were massage (47%), chiropractic (37%), faith healing (18%), aromatherapy (16%), homeopathy (16%), and relaxation (16%). Many patients used CAM products at the same time as conventional medicine but just over half (57%) discussed this concurrent use with their physician. Conclusion CAM use is common in pediatric neurology patients and most respondents felt that it was helpful, with few or no harms associated. However, this use is often undisclosed, increasing possibility of interactions with conventional drugs. We urge clinicians to inquire about CAM use during routine history taking at every patient visit. Parents would clearly like more information about CAM from their specialty clinics; such information would be easier to share if more primary data were available about the safety and effectiveness of commonly used therapies.
Depolarizing GABA Acts on Intrinsically Bursting Pyramidal Neurons to Drive Giant Depolarizing Potentials in the Immature Hippocampus

Spontaneous periodic network events are a characteristic feature of developing neuronal networks, and they are thought to play a crucial role in the maturation of neuronal circuits. In the immature hippocampus, these types of events are seen in intracellular recordings as giant depolarizing potentials (GDPs) during the stage of neuronal development when GABAA-mediated transmission is depolarizing. However, the precise mechanism how GABAergic transmission promotes GDP occurrence is not known. Using whole-cell, cell-attached, perforated-patch, and field-potential recordings in hippocampal slices, we demonstrate here that CA3 pyramidal neurons in the newborn rat generate intrinsic bursts when depolarized. Furthermore, the characteristic rhythmicity of GDP generation is not based on a temporally patterned output of the GABAergic interneuronal network. However, GABAergic depolarization plays a key role in promoting voltage-dependent, intrinsic pyramidal bursting activity. The present data indicate that glutamatergic CA3 neurons have an instructive, pacemaker role in the generation of GDPs, whereas both synaptic and tonic depolarizing GABAergic mechanisms exert a temporally nonpatterned, facilitatory action in the generation of these network events.
MORPHOLOGY AND LONGER DISTANCE DEPENDENCIES

This paper illustrates the advantages of laboratory research into SLA by describing two studies of acquisition of second language syntax. The first addresses the question of whether human morphological abilities can be understood in terms of associative processes or whether it is necessary to postulate rule-based symbol processing systems underlying these skills. We demonstrate that acquisition of L2 morphology shows frequency effects for both regular and irregular forms and that the acquisition course of learners' accuracy and reaction time can be accurately simulated by connectionist systems. The second concerns a bootstrapping account of SLA whereby processes of chunking in phonological memory underpin the acquisition of long-term memory for utterances and abstractions of grammatical regularities. It shows that phonological short-term memory is particularly important in the acquisition of long-distance dependencies. In both cases, it is argued that these aspects of SLA reflect associative learning processes. When SLA research is properly focused on acquisition, laboratory research allows investigation of the learners' exposure to evidence, their processes of perception and learning, and their resultant language representations.