Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Arctic Coastal land covers with polarimetric SAR data

Increased rates of permafrost degradation and erosion along Arctic coastlines are anticipated, as a result of changing climatic conditions. To characterize and quantify rates of change, baselines in terms of the land cover types present and the physical location of the land-water interface, need to be established. Earth observation data provides a logistical alternative to conventional mapping approaches, while Synthetic Aperture Radar (SAR) systems are particularly well suited to this application since images can be acquired through cloud cover and in the low lighting conditions observed during Arctic winters. The focus of this study will be to assess the potential of dual pol TerraSAR-X and quad-pol Radarsat-2 imagery for land cover mapping, using complimentary datasets acquired over two study areas in the southern Beaufort Sea, Northwest Territories, Canada. Novel polarimetric SAR processing techniques, including the extraction of Kennaugh matrix elements, have been used to generate inputs to the Maximum Likelihood Classifier. Results show good potential for general land cover mapping, and that overall accuracy increases when backscatter coefficients from both sensors are utilized (81.4% for eight classes), compared to TerraSAR-X HH/VV (68.9%) or Radarsat-2 HH/HV/VV (73.6%) alone. Similar accuracies were achieved using Kennaugh matrix elements, but slight decreases were observed when backscatter coefficients and Kennaugh matrix elements were combined.
Developmental risk factors distinguish violent sexual offending, violent non-sexual offending and versatile violent offending in adulthood

Abstract The continuity of developmental risk factors from childhood into adolescence to predict criminal adult offending has not been investigated. From a developmental and life-course perspective, the issue is of both theoretical and practical importance, as understanding the long-term impact of early life experiences on adult outcomes that carry forward across major developmental periods can assist clinicians with the identification of targets for early intervention and prevention. The aim of the present study was to examine the extent to which childhood and adolescent risk factors distinguish among three offender subgroups in a sample of adult male offenders. The results indicated that the groups were more clearly distinguished on adolescent risk factors, giving greater prominence to proximal than distal predictors. As well, from a dose-response perspective, the pure sex offenders showed the most adverse developmental history and were differentiated from both the versatile violent sex offenders and the violent non-sex offenders.
Maternal Substrate Utilization Programs the Development of the Metabolic Syndrome in Male Mice Exposed to High Fat In Utero

Studies were conducted to determine whether maternal substrate utilization during pregnancy affects fetal growth and predisposes offspring to metabolic disease. Female wild-type (WT) and glucose transporter 4 heterozygous mice (G4±, a model of altered peripheral substrate utilization) were fed high-fat diet (HFD, 35.5% fat) or control chow (C, 9.5% fat) for 2 wk before mating, throughout pregnancy and lactation (IU/L). WT HFD females exhibited increased serum nonesterified fatty acid and lactate levels and increased hepatic mRNA expression of peroxisome proliferator-activated receptor γ coactivator-1-β and SREBP-1c, consistent with increased lipogenesis. G4± HFD females exhibited enhanced lipid clearance, and exposure to HFD did not increase hepatic gene expression. HFD independent of maternal genotype decreased fetal growth and birth weight. WT offspring were weaned onto a low-fat diet (5.6% fat). Male offspring of WT mothers exposed to HFD exhibited “catch-up” growth accompanied by increased adiposity, impaired glucose tolerance, and insulin sensitivity. In contrast, male offspring of G4± HFD mothers did not exhibit any characteristics of metabolic syndrome. These data suggest that differences in maternal substrate utilization influence offspring metabolic phenotype.
Typical properties of winners and losers in discrete optimization

We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e. g. , all binary optimization problems defined by linear constraints and a linear objective function over (0,1)n. By parameterizing which constraints are of stochastic and which are of adversarial nature, we obtain a semi-random input model that enables us to do a general average-case analysis for a large class of optimization problems while at the same time taking care for the combinatorial structure of individual problems. Our analysis covers various probability distributions for the choice of the stochastic numbers and includes smoothed analysis with Gaussian and other kinds of perturbation models as a special case. In fact, we can exactly characterize the smoothed complexity of optimization problems in terms of their random worst-case complexity.A binary optimization problem has a polynomial smoothed complexity if and only if it has a pseudopolynomial complexity. Our analysis is centered around structural properties of binary optimization problems, called winner, loser, and feasibility gaps. We show, when the coefficients of the objective function and/or some of the constraints are stochastic, then there usually exist a polynomial n-Ω(1) gap between the best and the second best solution as well as a polynomial slack to the boundary of the constraints. Similar to the condition number for linear programming, these gaps describe the sensitivity of the optimal solution to slight perturbations of the input and can be used to bound the necessary accuracy as well as the complexity for solving an instance. We exploit the gaps in form of an adaptive rounding scheme increasing the accuracy of calculation until the optimal solution is found. The strength of our techniques is illustrated by applications to various NP-hard optimization problems from mathematical programming, network design, and scheduling for which we obtain the the first algorithms with polynomial average-case/smoothed complexity.
Management information system for pollution sources census based on GIS

Pollution sources census and monitoring is one of the most important work in environment protection and management, which means a lot to environment planning and macro-control. Firstly, this paper analyzes the characteristics of pollution source census data and points out the similarity and common problems of existent environment information systems. Then proceeds to build a pollution sources census oriented management information system based on GIS and spatial database, which combines pollution sources information acquire and management, intelligently query and index, spatial analysis and comprehensive application all together. Finally this paper introduces the specific application of pollution sources census management information system according to the requirements of environment management.
Measurement of platelet antibodies: where do we stand?

The immune pathogenesis of idiopathic thrombocytopenic purpura (ITP) is well established; however, the diagnostic criteria do not require identification of platelet autoantibodies. The abundance of methods devised for the measurement of platelet antibodies over the years provides evidence of the so‐far futile search for a reliable diagnostic assay. The latest generation of platelet antigen‐specific assays has widened the knowledge of autoimmune mechanisms in thrombocytopenia, but they still lack sufficient sensitivity to be a useful tool in the routine evaluation of thrombocytopenic patients.
Improving head-related impulse response measured in noisy environments with spatio-temporal frequency analysis

A new noise reduction method based on spatio-temporal frequency analysis is proposed that can be applied to head-related impulse response (HRIR), which is an impulse response between the sound source and the ear canal entrance. HRIR measurement is sometimes conducted in spaces which are not free fields, such as soundproof chambers with low reverberation. Conventional noise reduction methods such as synchronous averaging need multiple measurements under an identical measurement condition. However, taking many measurements requires much time, and subjects must be patient. Therefore, a noise reduction method which requires fewer measurements is needed. In our proposed method, noises are suppressed using a two-dimensional filter that is designed in the spatio-temporal frequency domain. Two experiments were conducted to improve the signal-to-noise ratio (SNR). The maximum SNR improvement achieved 1.28 dB, and the HRIRs measured in high reverberation were also improved, indicating that the proposed method effectively improved HRIRs without multiple measurements.
Synthesizing Combination Therapies for Evolutionary Dynamics of Disease for Nonlinear Pharmacodynamics

Our previous results proposed an iterative scalable algorithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model with linear pharmacodynamics. In this manuscript, we use piecewise linear approximations to model nonlinear drug effects. We leverage results from optimal controller synthesis for positive systems to formulate the feedback synthesis problem as an optimization problem that sequentially explores piecewise linear subsystems corresponding to higher and higher treatment dosages.
Biochemical and Structural Characterization of Amy1: An Alpha-Amylase from Cryptococcus flavus Expressed in Saccharomyces cerevisiae

An extracellular alpha-amylase (Amy1) whose gene from Cryptococcus flavus was previously expressed in Saccharomyces cerevisiae was purified to homogeneity (67 kDa) by ion-exchange and molecular exclusion chromatography. The enzyme was activated by NH(4) (+) and inhibited by Cu(+2) and Hg(+2). Significant biochemical and structural discrepancies between wild-type and recombinant α-amylase with respect to K(m) values, enzyme specificity, and secondary structure content were found. Far-UV CD spectra analysis at pH 7.0 revealed the high thermal stability of both proteins and the difference in folding pattern of Amy1 compared with wild-type amylase from C. flavus, which reflected in decrease (10-fold) of enzymatic activity of recombinant protein. Despite the differences, the highest activity of Amy1 towards soluble starch, amylopectin, and amylase, in contrast with the lowest activity of Amy1(w), points to this protein as being of paramount biotechnological importance with many applications ranging from food industry to the production of biofuels.
Project “anonymity and unobservability in the Internet”

It is a hard problem to achieve anonymity for real-time services in the Internet (e.g. Web access). All existing concepts fail when we assume a very strong attacker model (i.e. an attacker is able to observe all communication links). We also show that these attacks are real- world attacks. This paper outlines alternative models which mostly render these attacks useless. Our present work tries to increase the efficiency of these measures.
Knowledge sharing tools, practices and barriers in transnational clusters

Social media and Web 2.0 technologies seem to be especially promising because of their open character and low barrier of adoption. The use of these technologies for knowledge sharing in organizational settings has been thoroughly examined and some positive effects have been found, but much less is known about how the social media tools could be effectively used in cross-organizational settings or in international cooperation. The aim of the study was to investigate what kind of knowledge sharing practices can be identified in international clusters; which tools are used for supporting the knowledge sharing in international networks and what kind of barriers the members perceive in their knowledge sharing processes within the network. The results indicated that communities are actively thinking about employing social technologies for knowledge sharing, but several barriers exists that hinder adoption. The study indicated that any tool could build the community sense and replace the face-to-face meetings in real life, but the technologies should be intertwined with real life communication and every community needs a facilitator who takes responsibilities for community building.
Applications of Multi-Resolution Neural Networks to Mammography

We have previously presented a coarse-to-fine hierarchical pyramid/ neural network (HPNN) architecture which combines multi-scale image processing techniques with neural networks. In this paper we present applications of this general architecture to two problems in mammographic Computer-Aided Diagnosis (CAD). The first application is the detection of microcalcifications. The coarse-to-fine HPNN was designed to learn large-scale context information for detecting small objects like microcalcifications. Receiver operating characteristic (ROC) analysis suggests that the hierarchical architecture improves detection performance of a well established CAD system by roughly 50%. The second application is to detect mammographic masses directly. Since masses are large, extended objects, the coarse-to-fine HPNN architecture is not suitable for this problem. Instead we construct a fine-to-coarse HPNN architecture which is designed to learn small-scale detail structure associated with the extended objects. Our initial results applying the fine-to-coarse HPNN to mass detection are encouraging, with detection performance improvements of about 36%. We conclude that the ability of the HPNN architecture to integrate information across scales, both coarse-to-fine and fine-to-coarse, makes it well suited for detecting objects which may have contextual clues or detail structure occurring at scales other than the natural scale of the object.
Congestion Control for WebRTC: Standardization Status and Open Issues

The WebRTC initiative has achieved impressive results in terms of the gained industrial interest, the penetration of the technology in end-user devices, and the ever growing community of developers. WebRTC is today supported by major mobile platforms and Internet browsers, allowing potentially billions of users to seamlessly establish real-time communication sessions. Among all the functionalities that must be implemented by WebRTC devices, congestion control is particularly important to ensure that the network operates properly while providing a satisfactory user experience. A working group that is focusing on this issue is the IETF RTP Media Congestion Avoidance Techniques (RMCAT), which aims at defining the requirements and designing congestion control algorithms to be used for the transport of real-time media flows over RTP. This article overviews the status of the standardization efforts that are taking place in the RMCAT working group. We discuss the choices involved in the design of media congestion control, the proposed algorithms, and the issues that are considered still open.
Elite: A Digital Dedicated Hardware System for Movement Analysis Via Real-Time TV Signal Processing

The system illustrated in this paper has been designed and developed particularly for automatic and reliable analysis of body movement in various conditions and environments. It is based on real-time processing of the TV images to recognize multiple passive markers and compute their coordinates. This performance is achieved by using a special algorithm allowing the recognition of markers only if their shape matches a predetermined "mask. " The main feature of the system is a two-level processing architecture, the first of which includes a dedicated peripheral fast processor for shape recognition (FPSR), designed and implemented by using fast VLSI chips. The second level consists of a general purpose computer and provides the overall system with high flexibility. The main characteristics are: no restriction on the number of markers, resolution of one part in 2500, and a 50 Hz sampling rate independent of the number of markers detected. The prototype has been fully developed, and preliminary results obtained from the analysis of several movements are illustrated.
Improving influx constant and ratio estimation in FDOPA brain PET analysis for Parkinson's disease.

UNLABELLED PET studies using l-3,4-dihydroxy-6-(18)F-fluorophenylalanine have been applied to assess the diminished functionality of the striatum in patients with suspected Parkinson's disease. Two techniques for analyzing such studies are ratio methods and graphically computed influx constants. We propose a method for improving the consistency with which scans obtained by either of these techniques are analyzed. The method is based on a fully 3-dimensional analysis of the images. METHODS Fifty-one dynamically acquired datasets were corrected for motion before analysis. Regions of interest (ROIs) for the analysis were determined by manual affine registration to a standard template, using a separate transformation for each ROI. Indicator values for each ROI were computed by averaging the values of voxels having the highest activity within a specified proportion of the voxels in the ROI, to increase the robustness to perturbations in the ROI position. Sensitivity was analyzed by examining the variation in results obtained when the ROIs were translated by up to 6 mm. RESULTS We observed significant percentage differences in the computed influx constant before and after motion correction (mean variation +/- SD, -0.75% +/- 9.5% averaged over all regions of all patients). Our method was robust to placement of the cerebellum ROI, whereas a 2- dimensional analysis based on hand-drawn ROIs was associated with a 2- to 3-fold greater percentage variation in uptake for translations of 2 mm or more in ROI position. When we compared the 2 quantification techniques, our influx constants and ratios correlated at r(2) = 0.91, P < 0.0001. CONCLUSION Motion correction is an important step for computing reliable results in dynamic studies. The robustness of the results can be increased further by using standard normalized volumetric ROIs and by using the average value of a specified proportion of the voxels with the highest activity in the ROI as an indicator for that ROI. Influx constant values computed using our analysis technique closely correlated to values computed with ratio methods using this general approach.
Natural History and Magnetic Resonance Imaging Follow-up in 9 Sturge-Weber Syndrome Patients and Clinical Correlation

The natural history of Sturge-Weber Syndrome is variable where some patients have refractory epilepsy and persistent neurologic deficits while others do well. Also, evolution of MRI abnormalities is largely unknown. This long-term follow-up study tries to address these two issues. This retrospective and later prospective study followed 9 children with confirmed SWS. Clinical details of seizures, stroke-like episodes, neurologic and developmental deficits were ascertained specifically. Patients were divided into those with onset below or after 6 months of age for analysis. Disease was classified as active or inactive and correlations were made with the use of aspirin. All past, as well as prospectively acquired imaging was reviewed by two independent blinded neuroradiologists and the images were analysed as ictal (temporally related to seizure/stroke-like event) or interictal. Degree and extent of leptomeningeal enhancement was specifically looked for. Four boys and five girls were followed up for a mean of 6.1 years. Disease activity subsided in 8/9. Early-onset patients had a severe early course with significant residual deficits while late-onset patients did uniformly well. In 6 patients where aspirin was used, a stable course ensued. There was a significant increase in degree/extent of leptomeningeal enhancenment during an ictus which returned to the baseline in the interictal state in all 7 patients where both images were available. Focal cerebral atrophy worsened in early-onset cases. In conclusion, SWS patients with onset of seizures/stroke-like events before 6 months of age seem to do worse with a severe early course and persistent neurologic deficits. However the course stabilizes after 5 years of age in most. Late-onset SWS patients have a benign course. Aspirin use is associated with a stable course though further studies are needed. The leptomeningeal enhancement appears to increase during acute events before returning to baseline suggesting that extent of the disease is probably best judged during the interictal state.
Integrating Information

The case study reported here explores the processes involved in producing a written synthesis of three history texts and their possible relation to the characteristics of the texts produced and the degree of comprehension achieved following the task. The processes carried out by 10 final-year compulsory education students (15 and 16 years old) to produce their syntheses, including the integrations they verbalized while performing the task, were examined in detail with a double-analysis system. The results revealed a tendency for the students who engaged in more elaborative patterns to make more integrations and produce better texts. These students seemed to benefit more from the task in terms of comprehension. Conversely, the students who followed a more reproductive pattern by and large copied ideas from the source texts and achieved low levels of comprehension.
Special education for intellectual disability: current trends and perspectives

Purpose of review To inform readers of current issues in special education for individuals with intellectual disabilities and summarize recent research and opinion. Recent findings Two issues dominate special education for students with intellectual disabilities in the early 21st century. First, what should be taught to such students and who should teach them? Second, where should such students be taught – in ‘inclusive’ settings alongside normal peers or in special settings dedicated to their special needs? Research on teaching reading, arithmetic, and functional daily living skills to students with disabilities suggests the superiority of direct, systematic instruction. Universal design is often seen as supportive of inclusion. Inclusion has been seen as the central issue in special education but is gradually giving way to concern for what students learn. Summary Direct, systematic instruction in reading, arithmetic, and daily living skills is the most effective approach to teaching students with intellectual disabilities. Basic concepts and logic suggest that special and general education cannot be equivalent. We conclude that what students are taught should be put ahead of where they are taught. Our fundamental concern is that students with intellectual disabilities be respected and be taught all they can learn.