Miracle-dz/UniFAR-FTUs huggingface dataset:
Case based organizational memory for processing architecture based on measurement metadata

With the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this paper we present a summary of an case-based organizational memory ontology, which aims at contributing to the design of an organizational memory based on cases, so that it can be used to learn, reasoning, solve problems, and as support to better decision making as well. The objective of this Organizational Memory is to serve as base for the organizational knowledge exchange in a processing architecture specialized in the measurement and evaluation. One key aspect associated with the measurement process is that the measures must be consistent and comparable in any moment for making decisions properly. In this way, the processing architecture is based on the C-INCAMI framework (Context-Information Need, Concept model, Attribute, Metric and Indicator) to define the measurement projects. Additionally, the proposal architecture uses a big data repository to make available the data for consumption and to manage the Organizational Memory, which allows a feedback mechanism in relation with online processing. The relation between the data stream processing, the big data repository and the Organizational Memory will be shown. In order to illustrate its utility a practical case associated with the weather radar (WR) of the Experimental Agricultural Station (EAS) INTA Anguil (La Pampa State, Argentina) is shown. Also future trends and concluding remarks are outlined.
A Social Network Analysis on Blended Courses

The large-scale online management systems (e.g. Moodle), online web forums (e.g. Piazza), and online homework systems (e.g. WebAssign) have been widely used in the blended courses recently. Instructors can use these systems to deliver class content and materials. Students can communicate with the classmates, share the course materials, and discuss the course questions via the online forums. With the increased use of the online systems, a large amount of students' interaction data has been collected. This data can be used to analyze students' learning behaviors and predict students' learning outcomes. In this work, we collected students' interaction data in three different blended courses. We represented the data as directed graphs and investigated the correlation between the social graph properties and students' final grades. Our results showed that in all these classes, students who asked more answers and received more feedbacks on the forum tend to obtain higher grades. The significance of this work is that we can use the results to encourage students to participate more in forums to learn the class materials better; we can also build a predictive model based on the social metrics to show us low performing students early in the semester.
Associations Between Facial Emotion Recognition, Cognition and Alexithymia in Patients with Schizophrenia: Comparison of Photographic and Virtual Reality Presentations

Emotion recognition is known to be impaired in schizophrenia patients. Although cognitive deficits and symptomatology have been associated with this impairment there are other patient characteristics, such as alexithymia, which have not been widely explored. Emotion recognition is normally assessed by means of photographs, although they do not reproduce the dynamism of human expressions. Our group has designed and validated a virtual reality (VR) task to assess and subsequently train schizophrenia patients. The present study uses this VR task to evaluate the impaired recognition of facial affect in patients with schizophrenia and to examine its association with cognitive deficit and the patients' inability to express feelings. Thirty clinically stabilized outpatients with a well-established diagnosis of schizophrenia or schizoaffective disorder were assessed in neuropsychological, symptomatic and affective domains. They then performed the facial emotion recognition task. Statistical analyses revealed no significant differences between the two presentation conditions (photographs and VR) in terms of overall errors made. However, anger and fear were easier to recognize in VR than in photographs. Moreover, strong correlations were found between psychopathology and the errors made.
Accelerating the transformation of power systems Flexible Coal Evolution from Baseload to Peaking Plant

The experience cited in this paper is from a generating station with multiple units located in North America referred to here as the CGS plant. For commercial reasons, the station has not been identified. Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility —namely the ability to cycle on and off and run at lower output (below 40% of capacity)—requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context—namely, power market opportunities and composition of the generation fleet—will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates. Photo from iStock 72283000 2 Many power systems the world over are being reshaped by new economic and political landscapes, which have resulted in increased investments in renewable energy, distributed energy technologies, and natural gas. This transformation will likely yield a substantial reduction in coal-generated electricity. For example, to reduce greenhouse gas emissions, Ontario, Canada is phasing out the use of coal by the end of 2014. As power systems undertake this transition, questions remain about the fate of coal plants and how their operations may change in systems with increasing penetration levels of variable renewable energy, such as wind and solar. Future power systems may need more flexible generation resources. These resources can be characterized by the ability to cycle on and off and run at low minimum loads to …
Situated Multimodal Documents

The choices made by user in processing a set of documents is related, in a broad sense, to the sum of influences coming from the documents in the user situation, which does not include only physical or technical context parameters, but also the user goal and a set of personal components related to the user goal and to the effect on the user of the document. We use the term situated document to denote such influence. In this paper we propose a model for situated documents and propose a functional architecture for their management.
On the Convergence of Successive Linear Programming Algorithms

We analyze the global convergence properties of a class of penalty methods for nonlinear programming. These methods include successive linear programming approaches, and more specifically the SLP-EQP approach presented in [1]. Every iteration requires the solution of two trust region subproblems involving linear and quadratic models, respectively. The interaction between the trust regions of these subproblems requires careful consideration. It is shown under mild assumptions that there exist an accumulation point which is a critical point for the penalty function. ∗Department of Computer Science, University of Colorado, Boulder, CO 80309; richard@cs.colorado. edu. This author was supported by Air Force Office of Scientific Research grant F49620-00-1-0162, and Army Research Office Grant DAAG55-98-1-0176. †Computational Science and Engineering Department, Rutherford Appleton Laboratory, Chilton, Oxfordshire OX11 0QX, England, EU; n.gould@rl.ac. uk. This author was supported by EPSRC grant GR/R46641. ‡Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL 602083118; nocedal@ece.northwestern. edu. These authors were supported by National Science Foundation grants CCR-9987818, ATM-0086579 and CCR-0219438, and by Department of Energy grant DE-FG0287ER25047-A004.
Boosting for interactive man-made structure classification

We describe an interactive framework for man-made structure classification. Our system is able to help an image analyst to define a query that is adapted to various image and geographic contexts. It offers a GIS-like interface for visually selecting the training region samples and a fast and efficient sample description by histogram of oriented gradients and local binary patterns. To learn a discrimination rule in this feature space, our system relies on the online gradient-boost learning algorithm for which we defined a new family of loss functions. We chose non-convex loss-functions in order to be robust to mislabelling and proposed a generic way to incorporate prior information about the training data. We show it achieves better performances than other state-of-the-art machine-learning methods on various man-structure detection problems.
Commercial vehicle cabin with active air suspension for improved ride comfort

The damping of a common cabin of a commercial vehicle is realized with hydraulic based dampers integrated inside the air springs of the suspension. For the suspension proposed in this paper, the damping forces are generated by varying the mass of air inside the air spring volume. To achieve a high bandwidth of vibration suppression, the mass flow of compressed air is controlled using fast switching valves. To use the air spring actuator in a superimposed vibration control, a force controller was designed, based on a linearized air spring model. Using four force-controlled air springs in the suspension of a cabin, a superimposed vibration control can be designed, which reduces the cabin accelerations in the lifting, pitching and rolling degree of freedom. In case of large excitations the utilized skyhook damping has to be changed into a groundhook damping, which is done by an automated cross-fade. During road tests the meaningful capability of the hybrid vibration isolation concept is proofed by measurements.
Heme protein-induced chronic renal inflammation: suppressive effect of induced heme oxygenase-1.

BACKGROUND Heme oxygenase (HO) is the rate-limiting enzyme in the degradation of heme; its inducible isozyme, HO-1, protects against acute heme protein-induced nephrotoxicity and other forms of acute tissue injury. This study examines the induction of HO-1 in the kidney chronically inflamed by heme proteins and the functional significance of such an induction of HO-1. METHODS Studies were undertaken in a patient with chronic tubulointerstitial disease in the setting of paroxysmal nocturnal hemoglobinuria (PNH), in a rat model of chronic tubulointerstitial nephropathy caused by repetitive exposure to heme proteins, and in genetically engineered mice deficient in HO-1 (HO-1 -/-) in which hemoglobin was repetitively administered. RESULTS The kidney in PNH evinces robust induction of HO-1 in renal tubules in the setting of chronic inflammation. The heme protein-enriched urine from this patient, but not urine from a healthy control subject, induced expression of HO-1 in renal tubular epithelial cells (LLC-PK1 cells). A similar induction of HO-1 and related findings are recapitulated in a rat model of chronic inflammation induced by repetitive exposure to heme proteins. Additionally, in the rat, the administration of heme proteins induces monocyte chemoattractant protein (MCP-1). The functional significance of HO-1 so induced was uncovered in the HO-1 knockout mouse: Repeated administration of hemoglobin to HO-1 +/+ and HO-1 -/- mice led to intense interstitial cellular inflammation in HO-1 -/- mice accompanied by striking up-regulation of MCP-1 and activation of one of its stimulators, nuclear factor-kappaB (NF-kappaB). These findings were not observed in similarly treated HO-1 +/+ mice or in vehicle-treated HO-1 -/- and HO-1 +/+ mice. CONCLUSION We conclude that up-regulation of HO-1 occurs in the kidney in humans and rats repetitively exposed to heme proteins. Such up-regulation represents an anti-inflammatory response since the genetic deficiency of HO-1 markedly increases activation of NF-kappaB, MCP-1 expression, and tubulointerstitial cellular inflammation.
Exploiting local popularity to prune routing indices in peer-to-peer systems

Routing in unstructured peer-to-peer systems relies either on broadcasting (also called flooding) or on routing indices. An approach using routing indices is only scalable if the routing indices are of manageable size. In this paper, we present a strategy to prune routing indices based on popularity of resources. Routing indices maintain routing information for queries to the most popular resources, leaving queries to other resources to be routed randomly. The popularity of resources at each node of a network is learnt by each routing index, by means of a replacement strategy. We compare the performance of the local popularity method against that of the global popularity method in pruning routing indices in both static and dynamic environments. We compare the effectiveness and the efficiency of two standard replacement strategies: least frequently used (LFU) and least recently used (LRU). Our results confirm the efficiency and effectiveness of pruning routing indices based on the local popularity of resources in unstructured peer-to-peer networks.
A novel wireless vibrotactile display device for representing 3DOF force feedback in teleoperation

A vibrotactile display is one of possible methods to supersede force-feedback in teleoperation task. It can apply to an existing teleoperation system such as a master interface which is based on a vision sensor to provide reliable contact force. A novel wireless vibrotactile display device which can perform independently and can be used by constituting a vibrotactile array has been developed in this paper. In addition, it is applied to an existing retargeting system which can sense the position of the human wrist and the hand motions including the fingers using the CyberGlove and a magnetic sensor to implement a bi-lateral teleoperation system. Therefore, a new modified force-feedback method using vibrotactile display in telemanipulation is suggested in this research. With this system, an operator can manipulate a teleoperated robotic arm and a robotic hand without any difficulties, and it also can prevent an object or a slave robot from being damaged. Experimental results show distinguishability of vibrational cueing patterns and the improvement of the performance in telemanipulation.
Cyclin A down-regulation in TGFbeta1-arrested follicular lymphoma cells.

Transforming growth factor beta1 (TGFbeta1) induces growth arrest in many cell types, including B lymphocytes. We examined the effect of TGF on cell cycle progression of a non-Hodgkin lymphoma cell line of follicular lymphoma subtype (FL). After 48 h of TGFbeta1 (10 ng/ml) treatment, a significantly increased number of DoHH2 cells was retained in G(0)/G(1) phase. We examined the level of cell cycle components, cyclins, cyclin-dependent kinases (cdk), and their inhibitors. We found that the expression of cyclin A and p21(WAF1) molecules was primarily modulated by TGFbeta1 treatment while the expression of other regulatory components, like cyclins D, cyclin E, cdk2, cdk4, and cdk6 or p15(INK4B), p16(INK4A), and p27(KIP1) was not significantly affected. We further examined expression and activity of CREB/ATF family members to examine their roles in cyclin A inhibition. The binding activity of CREB-1 and ATF-2 to the CRE region of the cyclin A promoter was almost completely abolished due to the treatment. The total level of CREB-1, ATF-2, and ATF-3 was notably reduced. Moreover, CREB-1 was dephosphorylated due to the treatment as revealed by immunoblotting. We assume that down-regulation of cyclin A was mediated by the absence of CREB/ATF activation dimers. The profound effect on the ATF family of transcription factors indicates the complexity of TGFbeta1 action on FL B malignant cells.
Carbon: Chlorophyll Ratios and Net Primary Productivity of Subarctic Pacific Surface Waters Derived From Autonomous Shipboard Sensors

We present optically derived estimates of phytoplankton carbon (Cphyto) and chlorophyll a concentration (Chl) across a wide range of productivity and hydrographic regimes in the Subarctic Pacific Ocean. Our high‐frequency measurements capture changes in Cphyto and Chl across regional gradients in macronutrient and micronutrient limitations and submesoscale hydrographic frontal zones. Throughout the majority of our survey region, carbon to chlorophyll ratios (Cphyto:Chl) ranged between 50 and 100. Lower values (10–20) were constrained to the highly productive coastal upwelling system along Vancouver Island, whereas higher estimated values (>200) were found directly off the southern British Columbia continental shelf. Further offshore, Cphyto:Chl was less variable, ranging from 50 to 80 in high nutrient low Chl waters in June and from 80 to 120 in the Gulf of Alaska in July. Much of the variability in Cphyto:Chl throughout the study region could be explained by mixed‐layer light levels (i.e., photoacclimation), with additional variability attributed to nutrient‐controlled changes in phytoplankton growth rates in some regions. Elevated Cphyto:Chl ratios resulting from apparent nutrient stress were found in areas of low macronutrient concentrations. In contrast, iron‐limited waters exhibited Cphyto:Chl ratios lower than predicted from the photoacclimation model. Applying the carbon‐based production model, we derived Cphyto and Chl‐based estimates of net primary productivity, which showed good coherence with independent 14C uptake measurements. Our results highlight the utility of ship‐board optical data to examine phytoplankton physiological ecology and productivity in surface marine waters.
Content Recommendation and Service Cost in P2P Systems

Recommendation systems and the performance of computer network systems have fundamental implications over each other. While recommendation systems impact system performance, the latter can be used to guide the former. In this paper, we study the interconnections between recommendation systems and the performance of the network. We propose an analytical model to capture the revenue and the cost to a content provider as a function of the quality of its recommendations and the cost to serve the content. The model is then used to suggest heuristics on how to recommend content accounting for service costs and user preferences.
Evaluation of the performance of TDR and capacitance techniques for soil moisture measurement

Though researchers have employed various techniques (gravimetric, electromagnetic, neutron scattering, heat pulse, micro-wave and optical remote sensing techniques) for soil moisture measurement, dielectric based techniques (Time Domain Reflectometry, TDR, and capacitance technique, CT) have gained much more popularity, mainly due to revolutionary developments in the field of electronics and data communication systems. However, suitability and relative performance of these techniques for moisture measurement of soils is a point of debate. Hence, in order to address this issue, extensive studies were conducted on the soils of entirely different characteristics, compacted at various compaction states (dry density and water content) by employing TDR and capacitance probes. Subsequently, the dielectric constant of the soil and its bulk electrical conductivity were obtained using these probes and compared against each other and that computed from Topp’s equation, which is a well-established relationship between the dielectric constant of the soil and its volumetric moisture content. An attempt was also made to correlate Ka values obtained from the dielectric techniques and Topp’s equation with that of Time Propagation (TP) mixing model, which incorporates in it the properties of the soil matrix as well. It has been observed that Ka-TDR matches well with the Ka-Topp and Ka-TP, while the best match has been observed between Ka-TDR and Ka- Topp as compared to the Ka-CT. As such, the study demonstrates, clearly, that Topp’s equation, which ignores the soil specific parameters, is capable of determining the soil moisture content appropriately . This study proposes an empirical equation which relates dielectric constants obtained from Topp's equation to those obtained from the TDR, capacitance technique and TP mixing model. Such a relationship can be further utilized for estimating the volumetric soil moisture content.
An Embedding of the BSS Model of Computation in Light Affine Lambda-Calculus

This paper brings together two lines of research: implicit characterization of complexity classes by Linear Logic (LL) on the one hand, and computation over an arbitrary ring in the Blum-Shub-Smale (BSS) model on the other. Given a fixed ring structure K we define an extension of Terui’s light affine lambda-calculus typed in LAL (Light Affine Logic) with a basic type for K. We show that this calculus captures the polynomial time function class FP(K): every typed term can be evaluated in polynomial time and conversely every polynomial time BSS machine over K can be simulated in this calculus.
Rapid Computation of I-vector

I-vector has been one of the state-of-the-art techniques in speaker recognition. The main computational load of the standard i-vector extraction is to evaluate the posterior covariance matrix, which is required in estimating the i-vector. This limits the potential use of i-vector on handheld devices and for large-scale cloud-based applications. Previous fast approaches focus on simplifying the posterior covariance computation. In this paper, we propose a method for rapid computation of i-vector which bypasses the need to evaluate a full posterior co-variance thereby speeds up the extraction process with minor impact on the recognition accuracy. This is achieved by the use of subspace-orthonormalizing prior and the uniform-occupancy assumption that we introduce in this paper. From the experiments conducted on the extended core task of NIST SRE’10, we obtained signiﬁcant speed-up with modest degradation in performance over the standard i-vector.