Miracle-dz/UniFAR-FTUs huggingface dataset:
Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta

Appropriate bias is widely viewed as the key to efficient learning and generalization. I present a new algorithm, the Incremental Delta-Bar-Delta (IDBD) algorithm, for the learning of appropriate biases based on previous learning experience. The IDBD algorithm is developed for the case of a simple, linear learning system--the LMS or delta rule with a separate learning-rate parameter for each input. The IDBD algorithm adjusts the learning-rate parameters, which are an important form of bias for this system. Because bias in this approach is adapted based on previous learning experience, the appropriate test beds are drifting or non-stationary learning tasks. For particular tasks of this type, I show that the IDBD algorithm performs better than ordinary LMS and in fact finds the optimal learning rates. The IDBD algorithm extends and improves over prior work by Jacobs and by me in that it is fully incremental and has only a single free parameter. This paper also extends previous work by presenting a derivation of the IDBD algorithm as gradient descent in the space of learning-rate parameters. Finally, I offer a novel interpretation of the IDBD algorithm as an incremental form of hold-one-out cross validation.
Telepathology through the Internet

1 Holand U, Pedersen S. Quality requirements for telemedical services. Telektronlkk, Kjel/er, Televerkets Forskningsinstitutt 1993:1 2 Amstrong I, Haston W. Decision Support Systems in Remote Health Care. Aberdeen: RGIT Ltd, 1994 3 Southern Health Board. Greyscale Image Transfer System User Manual. Cork: Southern Health Board, 1994 4 PIT Telecom. ISDN. RapidImage Communication Offers Great Benefits to Doctor and Patient. Amsterdam: PIT Telecom Netherlands, 95-2408/ 07-93 5 Richardson R. Global telemedlcine practical applications. Linking Saudi Arabia to USA. In: Health, Information Society and Developing Countries. Amsterdam: IDS Press, 1995: 223-36 6 Aksellsen S, Eldsvlk AK, Folkow T. ISDN: new possibilities for telemedlcine. In: Telektranikk, Kjel/er, Televerkets Forskningsinstitutt 1993:1
Action classification in still images using human eye movements

Despite recent advances in computer vision, image categorization aimed at recognizing the semantic category of an image such as scene, objects or actions remains one of the most challenging tasks in the field. However, human gaze behavior can be harnessed to recognize different classes of actions for automated image understanding. To quantify the spatio-temporal information in gaze we use segments in each image (person, upper-body, lower-body, context) and derive gaze features, which include: number of transitions between segment pairs, avg/max of fixation-density map per segment, dwell time per segment, and a measure of when fixations were made on the person versus the context. We evaluate our gaze features on a subset of images from the challenging PASCAL VOC 2012 Action Classes dataset, while visual features using a Convolutional Neural Network are obtained as a baseline. Two support vector machine classifiers are trained, one with the gaze features and the other with the visual features. Although the baseline classifier outperforms the gaze classifier for classification of 10 actions, analysis of classification results over reveals four behaviorally meaningful action groups where classes within each group are often confused by the gaze classifier. When classifiers are retrained to discriminate between these groups, the performance of the gaze classifier improves significantly relative to the baseline. Furthermore, combining gaze and the baseline outperforms both gaze alone and the baseline alone, suggesting both are contributing to the classification decision and illustrating how gaze can improve state of the art methods of automated action classification.
Conformal Flattening by Curvature Prescription and Metric Scaling

We present an efficient method to conformally parameterize 3D mesh data sets to the plane. The idea behind our method is to concentrate all the 3D curvature at a small number of select mesh vertices, called cone singularities, and then cut the mesh through those singular vertices to obtain disk topology. The singular vertices are chosen automatically. As opposed to most previous methods, our flattening process involves only the solution of linear systems of Poisson equations, thus is very efficient. Our method is shown to be faster than existing methods, yet generates parameterizations having comparable quasi‐conformal distortion.
Imaging , Diagnosis , Prognosis Stromal LRP 1 in Lung Adenocarcinoma Predicts Clinical Outcome

Purpose: LRP1 (low-density lipoprotein receptor–related protein 1) is a broadly expressed receptor that binds multiple extracellular ligands and participates in protein clearance. It is expressed in numerous cancers, but its role in lung cancer has not been characterized. Here, we investigate the relationship between LRP1 and lung cancer. Experimental Design: LRP1 mRNA levels were determined in lung tumors from several large, multicenter studies. LRP1 protein localization was determined by immunohistochemical analysis of lung tumor microarrays. Normal fibroblasts, fibroblasts treated with the LRP1 inhibitor RAP (receptor-associated protein), and Lrp1 null fibroblasts were cocultured with 3 independent lung cancer cell lines to investigate the role of LRP1 on tumor cell proliferation. Results: LRP1 mRNA levels are significantly decreased in lung tumors relative to nontumorous lung tissue. Lower expression of LRP1 in lung adenocarcinomas correlates with less favorable clinical outcome in a cohort of 439 patients. Immunohistochemical analysis shows that LRP1 is primarily expressed in stromal cells in 94/111 lung cancers, with very little protein found in cancer cells. A growth-suppressive function of mouse embryonic fibroblast (MEF) cells was observed in 3 lung cancer cell lines tested (H460, H2347, and HCC4006 cells); growth suppression was blocked by the LRP1 inhibitor RAP. Lrp1 deletion in fibroblasts reduced the ability of MEF cells to suppress tumor cell mitosis. In a validation set of adenocarcinomas, we confirmed a significant, positive correlation between both LRP1 mRNA and protein levels and favorable
Integrated remote sensing for urban forest changes monitoring

Drivers of global climate change and the increased frequency of extreme climate events may affect urban and periurban forest ecosystems more rapidly than natural forest ecosystems. Multi stressors of urban forest ecosystems include alterations in forest soils and to the diversity and composition of forest ecosystem, as well as higher temperatures during heat waves periods and increasing carbon dioxide content due to high traffic issue. Global conservation targets and management practices of urban forest ecosystems in Romania requires adequate novel monitoring methodology for monitoring the dynamics changing status. Ground-based measurements are valuable tools with limited spatial footprints. Multispectral and multitemporal satellite remote sensing data allow detailed information on forest structure and can deliver ecologically relevant, long-term datasets suitable of vegetation phenology for analyzing changes in periurban and urban forest ecosystem areas, structure and function at temporal and spatial scales relevant to forest dynamics monitoring. The aim of this paper was to evaluate and characterize forest changes for selected test area Cernica –Branesti in Ilfov county located in the Eastern part of Bucharest metropolitan region, Romania, where the climate and anthropogenic stressors endanger natural and economical values of forest environment. Based on time-series Landsat 5 TM, 7 ETM+, 8 OLI/TIRS, MODIS Terra/Aqua and Sentinel 2A satellite data have been investigated urban forest land cover and forest biophysical parameters (LST, NDVI/EVI and LAI) changes over 2000-2016 period of time. Accuracy of image processing results (spectral classification) was confirmed through in-situ spectroradiometrical analysis of reflectance spectra with portable GER 2600 spectroradiometer.
Calcineurin regulates endothelial barrier function by interaction with and dephosphorylation of myosin phosphatase.

AIMS Calcineurin (CN) influences myosin phosphorylation and alters endothelial barrier function; however, the molecular mechanism is still obscure. Here we examine whether CN controls myosin phosphorylation via mediating the phosphorylation state of Thr696 in myosin phosphatase (MP) target subunit 1 (MYPT1), the phosphorylation site inhibitory to the catalytic activity of MP. METHODS AND RESULTS Exposure of bovine or human pulmonary artery endothelial cells (BPAECs or HPAECs) to the CN inhibitor cyclosporin A (CsA) induces a rise in intracellular Ca(2+) and increases the phosphorylation level of cofilin(Ser3) and MYPT1(Thr696) in a Ca(2+)-and Rho-kinase-dependent manner. An active catalytic fragment of CN overexpressed in tsA201 cells decreases endogenous MYPT-phospho-Thr696 (MYPT1(pThr696)) levels. Purified CN dephosphorylates (32)P-labelled MYPT1, suggesting direct action of CN on this substrate. Interaction of MYPT1 with CN is revealed by MYPT1 pull-down experiments and colocalization in both BPAECs and HPAECs as well as by surface plasmon resonance (SPR)-based binding studies. Stabilization of the MYPT1-CN complex occurs via the MYPT1(300PLIEST305) sequence similar to the CN substrate-docking PxIxIT-motif. Thrombin induces a transient increase of MYPT1(pThr696) in BPAECs, whereas its combination with CsA results in maintained phosphorylation levels of both MYPT1(pThr696) and myosin. These phosphorylation events might correlate with changes in endothelial permeability since CsA slows down the recovery from the thrombin-induced decrease of the transendothelial electrical resistance of the BPAEC monolayer. CONCLUSION CN may improve endothelial barrier function via inducing dephosphorylation of cofilin(pSer3) and by interaction with MYPT1 and activating MP through MYPT1(pThr696) dephosphorylation, thereby affecting actin polymerization and decreasing myosin phosphorylation.
Nelfinavir, an HIV-1 Protease Inhibitor, Induces Oxidative Stress–Mediated, Caspase-Independent Apoptosis in Leishmania Amastigotes

Background Visceral leishmaniasis has now emerged as an important opportunistic disease in patients coinfected with human immunodeficiency virus type-1 (HIV-1). Although the effectiveness of HIV-1 protease inhibitors, such as nelfinavir, in antiretroviral therapies is well documented, little is known of the impact of these drugs on Leishmania in coinfected individuals. Methodology and Principal Findings Here, we show that nelfinavir generates oxidative stress in the parasite, leading to altered physiological parameters such as an increase in the sub-G1 DNA content, nuclear DNA fragmentation and loss of mitochondrial potential, which are all characteristics of apoptosis. Pretreatment of axenic amastigotes with the caspase inhibitor z-VAD-fmk did not inhibit the increase in sub-G1 DNA content in nelfinavir-treated parasites, suggesting therefore that this antiviral agent does not kill Leishmania amastigotes in a caspase-dependent manner. Furthermore, we observed that the mitochondrial resident protein endonuclease G is involved. We also demonstrate that parasites overexpressing GSH1 (the rate limiting enzyme of glutathione biosynthesis) were more resistant to nelfinavir when compared to untransfected controls. Conclusions and Significance These data suggest that nelfinavir induces oxidative stress in Leishmania amastigotes, culminating in caspase-independent apoptosis, in which DNA is degraded by endonuclease G. This study provides a rationale for future, long-term design of new therapeutic strategies to test nelfinavir as a potential antileishmanial agent as well as for possible future use in Leishmania/HIV-1 coinfections.
Maximal Margin Local Preserving Median Fisher Discriminant Analysis for Face Recognition

Median Fisher Discriminator(MFD) used the class median vector is more effective than Linear discriminant analysis(LDA). However, MFD only captures global geometrical structure information of the data and ignores the geometrical structure information of local data point. In this paper, we introduce a linear approach, called Maximal Margin Local Preserving Median Fisher Discriminant Analysis (MMLPMFDA). MMLPMFDA models the geometrical structure and variability of the local neighborhoods by constructing two adjacency graphs over the training data, and then incorporates the geometry and variability into the objective function of the MFD. In order to solve the small sample size problem, the objective function in a form of the difference is adopted. Finally, experiments on the ORL, YALE and AR face databases show the effectiveness of the proposed approach.
Rule Induction Using a Reverse Polish Representation

It is often necessary to extract simple and understandable rules from databases containing inconsistent records and/or irrelevant fields. In this study we have assessed the feasibility of using a genetic programming (GP) approach to extract a single rule to describe such data. Instead of a tree structure we use a Reverse Polish (post-fix) representation. To assess the performance of the GP algorithm, it is compared to a steepest ascent hill climber algorithm and C5.0, a commercially available data mining algorithm (Quinlan, 1997). On the datasets used, the GP algorithm out-performs both C5.0 and a steepest ascent hill climber in the simplicity and, in most cases, the accuracy of the expressions produced.
Undamped Oscillations Generated by Hopf Bifurcations in Fractional-Order Recurrent Neural Networks With Caputo Derivative

In this paper, a fractional-order recurrent neural network is proposed and several topics related to the dynamics of such a network are investigated, such as the stability, Hopf bifurcations, and undamped oscillations. The stability domain of the trivial steady state is completely characterized with respect to network parameters and orders of the commensurate-order neural network. Based on the stability analysis, the critical values of the fractional order are identified, where Hopf bifurcations occur and a family of oscillations bifurcate from the trivial steady state. Then, the parametric range of undamped oscillations is also estimated and the frequency and amplitude of oscillations are determined analytically and numerically for such commensurate-order networks. Meanwhile, it is shown that the incommensurate-order neural network can also exhibit a Hopf bifurcation as the network parameter passes through a critical value which can be determined exactly. The frequency and amplitude of bifurcated oscillations are determined.
Intermediate disturbance and patterns of species richness

Abstract The intermediate disturbance hypothesis (IDH) predicts highest species diversity in environments experiencing intermediate intensity disturbance, after an intermediate timespan. Because many landscapes comprise mosaics with complex disturbance histories, the theory implies that each patch in those mosaics should have a distinct level of diversity reflecting the magnitude of disturbance and the time since it occurred. We model changing patterns of species richness across a landscape experiencing varied scenarios of simulated disturbance in order to predict first the variation of richness through time in individual patches, based on their disturbance histories, and then the changing patterns of richness across the landscape through time, representing the cumulative impact of changing richness within the individual patches. Model outputs show that individual landscape patches have highly variable species richness through time, with the trajectory reflecting the timing, intensity and sequence of disturbances. When the results are mapped across the landscape, the resulting temporal and spatial complexity reveals a distribution of biodiversity that is strikingly contingent on the details of disturbance history. These results illustrate the danger of generalization (in either data interpretation or management decisions), as IDH actually imposes a highly variable pattern of diversity.
Wireless wakeups revisited: energy management for voip over wi-fi smartphones

IP based telephony is rapidly gaining acceptance over traditional means of voice communication. Wireless LANs are also becoming ubiquitous due to their inherent ease of deployment and decreasing costs. In enterpriseWi-Fi environments, VoIP is a compelling application for devices such as smart phones with multiple wireless interfaces. However, the high energy consumption of Wi-Fi interfaces, especially when a device is idle,presents a significant barrier to the widespread adoption of VoIP over Wi-Fi.To address this issue, we present Cell2Notify, a practical and deployable energy management architecture that leverages the cellular radio on a smart phone to implement wakeup for the high-energy consumption Wi-Fi radio. We present detailed measurements of energy consumption on smart phone devices, and we show that Cell2Notify, can extend the battery lifetime of VoIPover Wi-Fi enabled smart phones by a factor of 1.7 to 6.4.
Endogenous Transfers in the Prisoner's Dilemma Game: An Experimental Test of Cooperation and Coordination

We study experimentally a two-stage compensation mechanism for promoting cooperation in prisonerâ€™s dilemma games. In stage 1, players simultaneously choose binding non-negative amounts to pay their counterparts for cooperating in a given prisonerâ€™s dilemma game, and then play the prisonerâ€™s dilemma game in stage 2 with knowledge of these amounts. For the asymmetric prisonerâ€™s dilemma games we consider, all payment pairs consistent with mutual cooperation in subgame-perfect equilibrium transform these prisonerâ€™s dilemma games into coordination games, with both mutual cooperation and mutual defection as Nash equilibria in the stage-2 game. We find considerable empirical support for the mechanism, as cooperation is much more common when these endogenous transfer payments are feasible. We identify patterns among transfer pairs that affect the likelihood of cooperation. Mutual cooperation is most likely when the payments are identical; it is also substantially more likely with payment pairs that bring the payoffs from mutual cooperation closer together than with payment pairs that cause them to diverge. There is substantial scope for this compensation mechanism to achieve beneficial social outcomes in commerce and in international affairs, and reason to be concerned about the ability of firms to design collusive agreements.
Design and analysis of IC power delivery with on-chip voltage regulation

Distributed on-chip voltage regulation offers an appealing solution to many power delivery challenges in modern chip designs. In-depth understanding of such power delivery networks (PDNs) that encompass large on-chip passive power grids and active on-chip and/or off-chip voltage regulators is hampered by high network complexity and the intricate interactions between a multitude of active regulators and the large passive network. In this paper, we discuss some of the key challenges and opportunities in designing power delivery networks with on-chip voltage regulation. We discuss important network simulation and design issues and present illustrative results to demonstrate the potential benefits resulted from holistic optimization of the power delivery network.
Symptom resolution in patients with Mycoplasma pneumoniae pneumonia.

BACKGROUND Mycoplasma pneumoniae generally causes pneumonia of mild to moderate severity in adults. However, little is known about the time course of the resolution of symptoms in this illness. OBJECTIVES To determine the time course of the resolution of symptoms in M pneumoniae pneumonia. METHODS The severity of fatigue, cough, dyspnea, sputum and pleuritic chest pain were self-scored and recorded daily for 14 days and on days 30 and 42. Each symptom was scored on a scale of 0 to 5. The sum of the five symptom scores had a range of 0 to 25 and was transformed into a value from zero to 100 by multiplying by four. RESULTS The mean composite symptom score for 76 patients was 59 (out of 100) at presentation, which declined to a score of 17 on day 14. Patients with a score of greater than 20 on day 14 had significantly higher scores throughout the course of the illness. Thirty-four per cent of those who were employed did not take time off work. CONCLUSIONS Most patients with M pneumoniae pneumonia had resolution of their symptoms within two weeks; however, 12.6% were still symptomatic at 42 days.
SnappyData: A Unified Cluster for Streaming, Transactions and Interactice Analytics

Many modern applications are a mixture of streaming, transactional and analytical workloads. However, traditional data platforms are each designed for supporting a speciﬁc type of workload. The lack of a single platform to support all these workloads has forced users to combine disparate products in custom ways. The common practice of stitching heterogeneous environments has caused enormous production woes by increasing complexity and the total cost of ownership. Tosupportthis class of applications, we present SnappyData as the ﬁrst uniﬁed engine capable of delivering analytics, transactions, and stream processing in a single integrated cluster. We build this hybrid engine by carefully marrying a big data computational engine ( Apache Spark ) with a scale-out transactional store ( Apache GemFire ). We study and address the challenges involved in building such a hybrid distributed system with two conﬂicting components designed on drastically different philosophies: one being a lineage-based computational model designed for high-throughput analytics, the other a consensus-and replication-based model designed for low-latency operations.
StereoSAR: a multi-static SAR mission concept to enhance Sentinel-1 capabilities for measuring ocean dynamics

We present a new mission concept, referred to as StereoSAR, with as primary aim to measure ocean surface currents at sub-mesoscales. To improve our understanding of the role surface currents play in a large variety of geophysical processes the mission will gather global measurements with high spatial and temporal resolution. A multi-static configuration based on a receive-only C-band dual polarimetric Synthetic Aperture Radar system working in synergy with Sentinel-1 is proposed. The Doppler Centroid Anomaly technique is used in order to measure Total Surface Current Velocity vectors by combining the mono-static observation and the squinted bi-static one. Simultaneous retrieval of Ocean Surface Wind Vectors and Ocean Swell Spectra is also performed. This paper presents an overview of the proposed mission concept and scenario. Some issues specific to multi-static Synthetic Aperture Radar are described and solutions offered. Finally, a preliminary performance assessment of the mission concept is included.