Miracle-dz/UniFAR-FTUs huggingface dataset:
Polarimetric SAR speckle filtering and its implication for classification

This paper proposes a new approach in polarimetric synthetic aperture radar (SAR) speckle filtering. The new approach emphasizes preserving polarimetric properties and statistical correlation between channels, not introducing crosstalk, and not degrading the image quality. In the last decade, speckle reduction of polarimetric SAR imagery has been studied using several different approaches. All of these approaches exploited the degree of statistical independence between linear polarization channels. The preservation of polarimetric properties and statistical characteristics such as correlation between channels were not carefully addressed. To avoid crosstalk, each element of the covariance matrix must be filtered independently. This rules out current methods of polarimetric SAR filtering. To preserve the polarimetric signature, each element of the covariance matrix should be filtered in a way similar to multilook processing by averaging the covariance matrix of neighboring pixels. However, this must be done without the deficiency of smearing the edges, which degrades image quality and corrupts polarimetric properties. The proposed polarimetric SAR filter uses edge-aligned nonsquare windows and applies the local statistics filter. The impact of using this polarimetric speckle filtering on terrain classification is quite dramatic in boosting classification performance. Airborne polarimetric radar images are used for illustration.
Macrophage migration inhibitory factor in the nucleus of solitary tract decreases blood pressure in SHRs.

AIMS The macrophage migration inhibitory factor (MIF) is an intracellular inhibitor of the central nervous system actions of angiotensin II on blood pressure. Considering that angiotensin II actions at the nucleus of the solitary tract are important for the maintenance of hypertension in spontaneously hypertensive rats (SHRs), we tested if increased MIF expression in the nucleus of the solitary tract of SHR alters the baseline high blood pressure in these rats. METHODS AND RESULTS Eight-week-old SHRs or normotensive rats were microinjected with the vector AAV2-CBA-MIF into the nucleus of the solitary tract, resulting in MIF expression predominantly in neurons. Rats also underwent recordings of the mean arterial blood pressure (MAP) and heart rate (via telemetry devices implanted in the abdominal aorta), cardiac- and baroreflex function. Injections of AAV2-CBA-MIF into the nucleus of the solitary tract of SHRs produced significant decreases in the MAP, ranging from 10 to 20 mmHg, compared with age-matched SHRs that had received identical microinjections of the control vector AAV2-CBA-eGFP. This lowered MAP in SHRs was maintained through the end of the experiment at 31 days, and was associated with an improvement in baroreflex function to values observed in normotensive rats. In contrast to SHRs, similar increased MIF expression in the nucleus of the solitary tract of normotensive rats produced no changes in baseline MAP and baroreflex function. CONCLUSION These results indicate that an increased expression of MIF within the nucleus of the solitary tract neurons of SHRs lowers blood pressure and restores baroreflex function.
Multitrait indices to predict worm length and number in sheep with natural, mixed predominantly Teladorsagia circumcincta infection

SUMMARY Accurately identifying resistance to gastrointestinal nematode infections requires the ability to identify animals with low and high intensities of infection. The pathogenic effects of nematodes depend upon both the length and number of worms, neither of which can be measured in live animals. Indices that predict these quantities are urgently needed. Monthly fecal egg counts, bodyweights, IgA concentrations and pepsinogen concentrations were measured on Scottish Blackface sheep naturally infected with a mixture of nematodes, predominantly Teladorsagia circumcincta. Worm number and average worm length were available on over 500 necropsied lambs. We derived predictive indices for worm length and number using linear combinations of traits measured in live animals. The correlations between the prediction values and the observed values were 0·55 for worm length and 0·51 for worm number. These indices can be used to identify the most resistance and susceptible lambs.
Mapping replicational sites in the eucaryotic cell nucleus

We have used fluorescent microscopy to map DNA replication sites in the interphase cell nucleus after incorporation of biotinylated dUTP into permeabilized PtK-1 kangaroo kidney or 3T3 mouse fibroblast cells. Discrete replication granules were found distributed throughout the nuclear interior and along the periphery. Three distinct patterns of replication sites in relationship to chromatin domains in the cell nucleus and the period of S phase were detected and termed type I (early to mid S), type II (mid to late S) and type III (late S). Similar patterns were seen with in vivo replicated DNA using antibodies to 5-bromodeoxyuridine. Extraction of the permeabilized cells with DNase I and 0.2 M ammonium sulfate revealed a striking maintenance of these replication granules and their distinct intranuclear arrangements with the remaining nuclear matrix structures despite the removal of greater than 90% of the total nuclear DNA. The in situ prepared nuclear matrix structures also incorporated biotinylated dUTP into replication granules that were indistinguishable from those detected within the intact nucleus.
Gesture Recognition with the Leap Motion Controller

The Leap Motion Controller is a small USB device that tracks hand and finger movements using infrared LEDs, allowing users to input gesture commands into an application in place of a mouse or keyboard. This creates the potential for developing a general gesture recognition system in 3D that can be easily set up by laypersons using a simple, commercially available device. To investigate the effectiveness of the Leap Motion controller for hand gesture recognition, we collected data from over 100 participants and then used this data to train a 3D recognition model based on convolutional neural networks, which can recognize 2D projections of the 3D space. This achieved an accuracy rate of 92.4% on held out data. We also describe preliminary work on incorporating time series gesture data using hidden Markov models, with the goal of detecting arbitrary start and stop points for gestures when continuously
A Transplant‐Specific Quality Initiative–Introducing TransQIP: A Joint Effort of the ASTS and ACS

In an attempt to improve surgical quality in the field of transplantation, the American College of Surgeons (ACS) and American Society of Transplant Surgeons have initiated a national quality improvement program in transplantation. This transplant‐specific quality improvement program, called TransQIP, has been built from the ground up by transplant surgeons and captures detailed information on donor and recipient factors as well as transplant‐specific outcomes. It is built upon the existing ACS/National Surgical Quality Improvement Program infrastructure and is designed to capture 100% of liver and kidney transplants performed at participating sites. TransQIP has completed its alpha pilot and will embark upon its beta phase at approximately 30 centers in the spring of 2017. Going forward, we anticipate TransQIP will help satisfy Centers for Medicare and Medicaid Services requirements for a quality improvement program, surgeon requirements for maintenance of certification, and qualify as a clinical practice improvement activity under the Merit‐Based Incentive Payment System. Most importantly, we believe TransQIP will provide insight into surgical outcomes in transplantation that will allow the field to provide better care to our patients.
Analysis of the Vaccine Potential of Plasmid DNA Encoding Nine Mycolactone Polyketide Synthase Domains in Mycobacterium ulcerans Infected Mice

There is no effective vaccine against Buruli ulcer. In experimental footpad infection of C57BL/6 mice with M. ulcerans, a prime-boost vaccination protocol using plasmid DNA encoding mycolyltransferase Ag85A of M. ulcerans and a homologous protein boost has shown significant, albeit transient protection, comparable to the one induced by M. bovis BCG. The mycolactone toxin is an obvious candidate for a vaccine, but by virtue of its chemical structure, this toxin is not immunogenic in itself. However, antibodies against some of the polyketide synthase domains involved in mycolactone synthesis, were found in Buruli ulcer patients and healthy controls from the same endemic region, suggesting that these domains are indeed immunogenic. Here we have analyzed the vaccine potential of nine polyketide synthase domains using a DNA prime/protein boost strategy. C57BL/6 mice were vaccinated against the following domains: acyl carrier protein 1, 2, and 3, acyltransferase (acetate) 1 and 2, acyltransferase (propionate), enoylreductase, ketoreductase A, and ketosynthase load module. As positive controls, mice were vaccinated with DNA encoding Ag85A or with M. bovis BCG. Strongest antigen specific antibodies could be detected in response to acyltransferase (propionate) and enoylreductase. Antigen-specific Th1 type cytokine responses (IL-2 or IFN-γ) were induced by vaccination against all antigens, and were strongest against acyltransferase (propionate). Finally, vaccination against acyltransferase (propionate) and enoylreductase conferred some protection against challenge with virulent M. ulcerans 1615. However, protection was weaker than the one conferred by vaccination with Ag85A or M. bovis BCG. Combinations of these polyketide synthase domains with the vaccine targeting Ag85A, of which the latter is involved in the integrity of the cell wall of the pathogen, and/or with live attenuated M. bovis BCG or mycolactone negative M. ulcerans may eventually lead to the development of an efficacious BU vaccine.
Individual Differences in Impulsivity Predict Anticipatory Eye Movements

Impulsivity is the tendency to act without forethought. It is a personality trait commonly used in the diagnosis of many psychiatric diseases. In clinical practice, impulsivity is estimated using written questionnaires. However, answers to questions might be subject to personal biases and misinterpretations. In order to alleviate this problem, eye movements could be used to study differences in decision processes related to impulsivity. Therefore, we investigated correlations between impulsivity scores obtained with a questionnaire in healthy subjects and characteristics of their anticipatory eye movements in a simple smooth pursuit task. Healthy subjects were asked to answer the UPPS questionnaire (Urgency Premeditation Perseverance and Sensation seeking Impulsive Behavior scale), which distinguishes four independent dimensions of impulsivity: Urgency, lack of Premeditation, lack of Perseverance, and Sensation seeking. The same subjects took part in an oculomotor task that consisted of pursuing a target that moved in a predictable direction. This task reliably evoked anticipatory saccades and smooth eye movements. We found that eye movement characteristics such as latency and velocity were significantly correlated with UPPS scores. The specific correlations between distinct UPPS factors and oculomotor anticipation parameters support the validity of the UPPS construct and corroborate neurobiological explanations for impulsivity. We suggest that the oculomotor approach of impulsivity put forth in the present study could help bridge the gap between psychiatry and physiology.
Multitask Agency, Modular Architecture, and Task Disaggregation in SaaS

We examine contract choices in the provision of "software-as-a-service" (SaaS), which is a business innovation that transforms information technology (IT) resources into a continuously provided service. We draw upon agency theory and modularity theory to propose that one of the central challenges in service disaggregation is that of knowledge interdependencies across client and provider organizations. The resulting lack of verifiability of certain tasks results in a multitask agency problem. Our key research questions involve (1) the suitability of high- versus low-powered incentives in SaaS contracts when the outsourced tasks involve business analytics that are difficult to verify, and (2) how such contract choices are affected by the modularity of interfaces between the client and the provider. Analysis of data collected from 154 providers of SaaS offering a range of IT services supports our contention that when contracting for business analytics characterized by knowledge interdependencies across clients and providers, incentives should be "low powered. " Modularity in the interfaces of the service provider increases the desirability of high-powered incentives in such situations. Our results are robust after accounting for endogeneity issues arising from unobserved matching between service providers and the nature of IT services outsourced by clients. With the increasing importance of information systems in services, this paper suggests that arm's-length relationships and high-powered incentives may be ineffective in incentivizing providers to perform on complex business analytic tasks, unless accompanied by the modularization of interfaces.
An Empirical Assessment of Semantic Interpretation

We introduce a framework for semantic interpretation in which dependency structures are mapped to conceptual representations based on a parsimonious set of interpretation schemata. Our focus is on the empirical evaluation of this approach to semantic interpretation, i.e., its quality in terms of recall and precision. Measurements are taken with respect to two real-world domains, viz. information technology test reports and medical finding reports.
A media monitoring solution

There are large amounts of information as video and audio not searchable. In a time where Business Intelligence is fundamental for all areas doing this kind of analysis only on text sources is a limiting factor. The use of large vocabulary speech recognition systems with increasing performance is giving rise to different applications. Despite the diversity, these applications share the extensive use of the contents of the transcription. In this paper we describe the results of a development project between a startup company and a research lab to build a full automatic system for monitoring TV and Radio channels. This system is composed by three main blocks: a recording block (records the selected channels in high and web streaming quality and broadcast to the next block), a processing block (generate metadata information) and a storage and accessing block (make available the metadata and videos). There is an optional block, the delivering, that could be customized according to the use and client needs. The processing block receives the video from the recording block time filtered by a scheduling interface. For that video the goal is to generate a full annotation with metadata describing the content and semantic information. This metadata make possible a filtering process for selective dissemination of information.
Detection of Power Quality Disturbances in Micro Grid Connected Power System

Micro Grid is a contracted distributed AC or DC network. Micro Grid resources are connected to the distributed linear as well as nonlinear loads through power electronics converter to provide an efficient, more reliable and quality power to the distributed loads with reduced co2 emission. Consequently makes full use of low cost generation resources and reduce waste. Interconnected Mode in the MG is connected to main grid either being absorbed by it or injecting some amount of power into the main system. Islanding Mode in the MG operates separately when upstream volt occurs in main grid network. Usage of power electronic interface converters, Integration of the renewable-resources based MG system to the main power system and nonlinear loads results in harmonics generation clutter the system reliability and other associated quality issues. Most of demanding users of electricity are suffering to a certain poor quality of electrical power. The excellent time-scaling resolution characteristic of WT used for detection of various power quality disturbances of integrating and islanding Micro Grid connected Distributed Generation systems. The WT plays important role in analysis, design and classification of discrete signal processing. The accuracy and reliability of classification techniques have assessed on signals contaminated with noise.
Fine-Grained Mining and Classification of Malicious Web Pages

With the World Wide Web expanding continuously, more and more malicious web pages including phishing, malware and spamming spread rapidly, we are facing a great threat. The work of detecting malicious web pages and identifying their threat types has some shortcomings. In existing studies of malicious webpage detection, most are just for detecting a single attack type. In this paper, we extract a variety of webpage features and use machine learning algorithms to build an efficient classifier. By the classifier, we can detect malicious web pages and identify all the popular threat types. The features extracted in our method are derived from the HTML contents, the associated JavaScript code, and the corresponding URL. We collected 1000 benign web pages and 1500 malicious web pages as experimental data sets. The experimental results show that our method achieves a superior performance: the accuracy was over 95% in detecting malicious web pages and over 88% in identifying threat types.
On seeing forms

Presents a critical review of theories in perceptual psychology, placing special emphasis on the perception of visual forms. The author reviews the state of current theory on how we see forms and works to establish the logical and mathematical limits of reductionism and theory. His work suggests that some of the goals of cognitive, neurophysiological and computational theorists, while useful in certain contexts, cannot be used for valid statements of the inner workings of the perceptual system.
Goalgetter: Predicting Contrastive Accent in Data-to-speech Generation

This paper addresses the problem of predicting contrastive accent in spoken language generation. The common strategy of accenting`new' and deaccent-ingòld' information is not suucient to achieve correct accentuation; generation of contrastive accent is required as well. I will discuss a few approaches to the prediction of contrastive accent, and propose a practical solution which avoids the problems these approaches are faced with. These issues are discussed in the context of GoalGetter, a data-to-speech system which generates spoken reports of football matches on the basis of tabular information.
Dynamic Power Management Using Machine Learning

Dynamic power management (DPM) work proposed to date places inactive components into low power states using a single DPM policy. In contrast, we instead dynamically select among a set of DPM policies with a machine learning algorithm. We leverage the fact that different policies outperform each other under different workloads and devices. Our algorithm adapts to changes in workloads and guarantees quick convergence to the best performing policy for each workload. We performed experiments with a policy set representing state of the art DPM policies on a hard disk drive and a WLAN card. Our results show that our algorithm adapts really well with changing device and workload characteristics and achieves an overall performance comparable to the best performing policy at any point of time
A cluster-randomised controlled trial integrating a community-based water, sanitation and hygiene programme, with mass distribution of albendazole to reduce intestinal parasites in Timor-Leste: the WASH for WORMS research protocol

Introduction There is limited evidence demonstrating the benefits of community-based water, sanitation and hygiene (WASH) programmes on infections with soil-transmitted helminths (STH) and intestinal protozoa. Our study aims to contribute to that evidence base by investigating the effectiveness of combining two complementary approaches for control of STH: periodic mass administration of albendazole, and delivery of a community-based WASH programme. Methods and analysis WASH for WORMS is a cluster-randomised controlled trial to test the hypothesis that a community-based WASH intervention integrated with periodic mass distribution of albendazole will be more effective in reducing infections with STH and protozoa than mass deworming alone. All 18 participating rural communities in Timor-Leste receive mass chemotherapy every 6 months. Half the communities also receive the community-based WASH programme. Primary outcomes are the cumulative incidence of infection with STH. Secondary outcomes include the prevalence of protozoa; intensity of infection with STH; as well as morbidity indicators (anaemia, stunting and wasting). Each of the trial outcomes will be compared between control and intervention communities. End points will be measured 2 years after the first albendazole distribution; and midpoints are measured at 6 months intervals (12 months for haemoglobin and anthropometric indexes). Mixed-methods research will also be conducted in order to identify barriers and enablers associated with the acceptability and uptake of the WASH programme. Ethics and dissemination Ethics approval was obtained from the human ethics committees at the University of Queensland, Australian National University, Timorese Ministry of Health, and University of Melbourne. The results of the trial will be published in peer-reviewed journals presented at national and international conferences, and disseminated to relevant stakeholders in health and WASH programmes. This study is funded by a Partnership for Better Health—Project grant from the National Health and Research Council (NHMRC), Australia. Trial registration number ACTRN12614000680662; Pre-results
The Effect of Outliers in the Design of Data Gathering Tours

We consider the problem of designing a tour for a mobile element in data producing sensor networks. The tour is designed to visit a subset of the nodes, chosen for their centrality in the network. This way the sensors that are not visited by the mobile element will need to transmit their data wirelessly. This may require several hops and therefore may reduce the lifetime of the network. The most common optimization objective for these data gathering problems is to minimize the amount of wireless transmission. For networks with relatively uniform density of nodes, there are several heuristics that work well in practice. However, if there are nodes that are placed far from the central locations of the network, then most proposed algorithms will end up designing a tour that may be skewed towards the outlier nodes. In this work we quantify the effect of outliers in the design of data gathering tours in wireless networks, and propose the use of an algorithm from data mining to address this problem. We provide experimental evidence that the tour planning algorithms that takes into account outliers can significantly improve the solution.