Miracle-dz/UniFAR-FTUs huggingface dataset:
SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization

In the era of big data, it is often the rare categories that are of great interest in many high-impact applications, ranging from financial fraud detection in online transaction networks to emerging trend detection in social networks, from network intrusion detection in computer networks to fault detection in manufacturing. As a result, rare category characterization becomes a fundamental learning task, which aims to accurately characterize the rare categories given limited label information. The unique challenge of rare category characterization, i.e., the non-separability nature of the rare categories from the majority classes, together with the availability of the multi-modal representation of the examples, poses a new research question: how can we learn a salient rare category oriented embedding representation such that the rare examples are well separated from the majority class examples in the embedding space, which facilitates the follow-up rare category characterization? To address this question, inspired by the family of curriculum learning that simulates the cognitive mechanism of human beings, we propose a self-paced framework named SPARC that gradually learns the rare category oriented network representation and the characterization model in a mutually beneficial way by shifting from the 'easy' concept to the target 'difficult' one, in order to facilitate more reliable label propagation to the large number of unlabeled examples. The experimental results on various real data demonstrate that our proposed SPARC algorithm: (1) shows a significant improvement over state-of-the-art graph embedding methods on representing the rare categories that are non-separable from the majority classes; (2) outperforms the existing methods on rare category characterization tasks.
Provision of frequency control by a BESS in combination with flexible units

The inherent energy constraints of a Battery Energy Storage System (BESS) limit its ability to participate extensively in frequency reserve markets. This limitation can be addressed by operating the battery alongside distributed, controllable loads and generators in the form of a Virtual Power Plant (VPP). In this paper, a detailed MPC approach was developed to simulate the operation and cost of a VPP combined with a BESS providing primary and secondary frequency reserve. Unit types including photovoltaic arrays, hydropower, combined heat and power and controllable loads were modeled. Two case studies are presented to validate the model, examining the technical and economic feasibility of a VPP under various operating scenarios, with different battery configurations. A techno-economic optimum is determined. Additionally, the relative value of different unit types is quantified.
Margin Elimination Through Timing Error Detection in a Near-Threshold Enabled 32-bit Microcontroller in 40-nm CMOS

This paper presents a near-threshold operating voltage timing error detecting 32-bit microcontroller system. The lightweight in situ error detection and correction technique uses a soft-edge flip-flop combined with in-latch transition detection and a set-dominant error latch to detect data path transitions after the clock edge. Inherent error correction is achieved through time borrowing in soft-edge flip-flops. The technique is implemented in an ARM Cortex M0 microcontroller system in 40-nm CMOS, rendering the microcontroller “timing error aware. ” Automatic critical path analysis results in an optimized timing error detection window and sparse flip-flop replacement. An autonomous dynamic voltage scaling (DVS) loop facilitates automatic operation at the point of first failure. The M0 system operates down to 290 mV and achieves 11–18 pJ/cycle core energy consumption in a 5–30 MHz frequency ranges. The architecture profits optimally from ULV operation at frequencies <10 MHz, where intra-die variations are significant.
Graph-based anomaly detection for smart cities: A survey

With increasing size, the problems a city faces (e.g., air pollution, traffic congestion or high energy consumption) increase, but so does the amount of implicitly available data. In order to leverage this data for smarter problem solutions, local authorities and businesses require sophisticated analysis preprocessing techniques. Recent work proposes modeling urban data as a graph and applying graph-based anomaly detection, which is traditionally used for fraud and intrusion detection. This demonstrates that a successful application of anomaly detection to selected sources of urban data is possible, but lacks an evaluation of the general applicability. In this survey, we discuss several homogeneous and heterogeneous graph models for urban data and suitable detection approaches.
Energia natural afluente monthly forecasting using an Artificial Neural Networks MLPs

This work presents an Artificial Neural Network multilayer perceptron model for the prediction of Energia Natural Afluente, the model is based on a cross-validation and learning method, where groups of neurons compete when the network receives a new input. The knowledge of the future behavior of the inflow flows is of vital importance to optimize the planning of the operation in hydrothermal systems to know the possible states of the future inflows, as well as the intrinsic probabilities of event, even helps the generation, distribution and commercialization companies to position in the electricity market in order to optimize their financial returns, betting on unlikely events in the “less trained” eyes. The ability of the artificial neural network models to approximate is as good as the configurations of their training, being able to lead the network to an excessive adjustment of the data, losing the capacity of generalization and compromising the prediction errors, therefore this is an element in defining the best parameters until the network is validated. The performance and acuity of the model was tested against the historical database that was used in the training of the network. The results showed that it is possible to use Artificial Neural Networks to make predictions of future affluent natural energy, and may even be applied to portfolio optimization methods for companies that commercialize electric energy in the Brazilian electricity market.
Low-cost IGBT driver for single-phase full-bridge converter

This paper presents a low-cost IGBT driver for single-phase full-bridge converter, including a dead time circuit. The IGBT model corresponds to GA75Ts120U from International Rectifier. It is important to highlight that, in essence, the IGBT driver was implemented with discrete components, which considerably decreases its cost in comparison to the similar circuits available in the market. Simulation- and experimental-results of the implemented converter are provided to evaluate the performance of the IGBT driver.
FOXP3 and miR-155 cooperate to control the invasive potential of human breast cancer cells by down regulating ZEB2 independently of ZEB1

Control of oncogenes, including ZEB1 and ZEB2, is a major checkpoint for preventing cancer, and loss of this control contributes to many cancers, including breast cancer. Thus tumour suppressors, such as FOXP3, which is mutated or lost in many cancer tissues, play an important role in maintaining normal tissue homeostasis. Here we show for the first time that ZEB2 is selectively down regulated by FOXP3 and also by the FOXP3 induced microRNA, miR-155. Interestingly, neither FOXP3 nor miR-155 directly altered the expression of ZEB1. In breast cancer cells repression of ZEB2, independently of ZEB1, resulted in reduced expression of a mesenchymal marker, Vimentin and reduced invasion. However, there was no de-repression of E-cadherin and migration was enhanced. Small interfering RNAs targeting ZEB2 suggest that this was a direct effect of ZEB2 and not FOXP3/miR-155. In normal human mammary epithelial cells, depletion of endogenous FOXP3 resulted in de-repression of ZEB2, accompanied by upregulated expression of vimentin, increased E-cadherin expression and cell morphological changes. We suggest that FOXP3 may help maintain normal breast epithelial characteristics through regulation of ZEB2, and loss of FOXP3 in breast cancer cells results in deregulation of ZEB2.
Citizenpedia: A human computation framework for the e-government domain

Human computation relies on crowds of people to perform large workloads, and in this work, we want to exploit this potential to improve the experience of e-government and the use of e-services. To that end we present the Citizenpedia, a human computation framework aimed at fostering citizens involvement in the public administration. The Citizenpedia is presented as a web application with two main tools: the Question Answering Engine, where citizens and civil servants can post and solve doubts about e-services and public administration, and the Collaborative Procedure Designer, where citizens can collaborate with civil servants in the definition and improvement of new administrative procedures and e-services. In this work we present several contributions: first, the design of the Citizenpedia concept, and then, its evaluation through a set of online surveys that were filled by 152 citizens and 63 civil servants from three different countries. The surveys served to successfully validate our design, and also to provide feedback on new features that were not taken into account in the first place. We finally present the software architecture of the Citizenpedia and provide the link to its source code.
Research on neural network control method with end point bias

Taking into account the existing neural network control method of large amount of calculation and application is not strong, in this paper, a complex neural network control structure is designed for the nonlinear and strong coupling system, which is coupled by the N sub neural network, at the same time, the paper proposes a neural network control method with end point bias. The method assigns different weights to each sub item of the mean variance objective function, so that the determination of neural network parameters is effectively biased towards the end point error value, so as to ensure the terminal stability of the system. Finally, the applicability of the proposed method is verified by a nonlinear strong coupling system with multiple inputs and multiple outputs, and the expected results are obtained.
Investigation of thorium utilization in accelerator driven systems

This article deals with the idea of using accelerator driven systems for thorium transmutation into the fissile material, which can be utilized in the accelerator driven systems and in thermal nuclear reactors. Thorium occurs on the Earth only in fertile isotope Th-232. It can be converted to fissile isotope U-233 by neutron capture and subsequent beta decay. The experimental part handles the data that were acquired by irradiation of four thorium samples in the field of secondary neutrons inside the QUINTA spallation set-up, which was irradiated by 660 MeV protons. Reaction rates for the different products were estimated using gamma-ray spectroscopy and activation techniques. Furthermore, Pa-233 production rates were also determined in all experimental samples. Pa-233 and fission production rates were calculated in all experimental samples using the MCNPX transport code and evaluated nuclear data for high-energy reactions. The experimental results are of a great importance for the future investigation of thorium in the accelerator driven system concept, validation of Monte Carlo-based calculation codes and validation of high-energy nuclear models.
Modeling and simulation of an offshore crane

This paper presents a mathematical modeling of a crane system using robot modeling theory as well as the numerical simulation of the dynamics of a crane and a marine craft. The simulations are performed in SimulationX and Matlab Simulink. The simulation platform includes a SimulationX-model of the crane, a realistic model of a marine craft using the Marine Systems Simulator(MSS) and the hydrodynamic sea-keeping calculations (VERES program code). The simulation results show a very good picture of the dynamic behavior of the real crane in offshore environment and verify the validation and effectiveness of the presented modeling approach.
A linear time approach to detect wormhole tunnels in mobile adhoc networks using 3PAT and transmission radius (3PATw)

Security issues in Mobile Ad hoc Networks (MANETs) have become a huge concern over the past few years considering their applications and necessity. Wormhole tunneling is an attack which when brought to such a network can completely neutralize the communications taking place in the network. The objective of the paper is to enhance the security provided by the existing methodologies to thereby improve the performance of the network. The proposed algorithm combines a Black Hole detection behavior mechanism and a wormhole detection behavior mechanism to detect and prevent the vulnerabilities in the Mobile Ad hoc Network based on the way of behavior.
Special Issue on Controversies and Progress in IGF-1 and Aging Aging, Atherosclerosis, and IGF-1

Insulin-like growth factor 1 (IGF-1) is an endocrine and autocrine/paracrine growth factor that circulates at high levels in the plasma and is expressed in most cell types. IGF-1 has major effects on development, cell growth and differentiation, and tissue repair. Recent evidence indicates that IGF-1 reduces atherosclerosis burden and improves features of atherosclerotic plaque stability in animal models. Potential mechanisms for this atheroprotective effect include IGF-1–induced reduction in oxidative stress, cell apoptosis, proinflammatory signaling, and endothelial dysfunction. Aging is associated with increased vascular oxidative stress and vascular disease, suggesting that IGF-1 may exert salutary effects on vascular aging processes. In this review, we will provide a comprehensive update on IGF-1’s ability to modulate vascular oxidative stress and to limit atherogenesis and the vascular complications of aging. pathway supports cell survival and enhances endothelial nitric oxide synthase activity, thereby inducing vasodilation. The pathway is critical for proliferative responses, activation of cell
Software defined network: Future of networking

The digital world we live in has been lead by the evolution of Internet, which has created revolution. Today almost everything is connected and accessible from anywhere, everywhere. Unfortunately, the traditional IP network system is still complex, not easily manageable and difficult to reconfigure in case of any change or fault. Software Defined Networking (SDN) is an emerging paradigm separates the network's control logic from the underlying routers and switches, promoting logical centralization of network control and introducing the ability to program the network. It has become the focus in the current information and communication technology area because of its flexibility and programmability. SDN abstracts low-level network functionalities to simplify network management. The OpenFlow protocol implements the SDN concept by abstracting network elements. It offers flexible and scalable functionality for network by decoupling the network control from forwarding devices. SDN uses a REST API (Representational State Transfer) for communication between controller and another application.
Power smoothing control for the PMSG WECS based on the kinetic energy

Based on analyzing the traditional wind power smoothing control method using the rotor inertia, this paper proposes a new power smoothing control strategy based on the kinetic energy by adopting the low-pass filter. The model of the direct-drive permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) is built based on Matlab/Simulink. The proposed low-pass filter based kinetic energy control strategy is compared with the traditional strategy in the simulation. The simulation results validate the effectiveness of the proposed power smoothing method.
miR-202-5p inhibits the migration and invasion of osteosarcoma cells by targeting ROCK1

Many studies have shown that microRNA regulates the development and treatment of osteosarcoma (OS). In many human cancer studies, the expression of microRNA-202 has been shown to be abnormal. The aim of the study was to examine the role of miR-202-5p in the occurrence and formation of OS. miR-202-5p and Rho-associated coiled-coil containing protein kinase 1 (ROCK1) levels were assessed using RT-qPCR in OS tissues and cell lines. The cell migrating and invasive abilities were detected by the Transwell assay in OS. Moreover, the relationship between miR-202-5p and ROCK1 was verified via luciferase reporter assay. The protein level of ROCK1 was identified by western blot analysis. Downregulation of miR-202-5p was identified in OS tissues and cell lines. In addition, the miR-202-5p overexpression had inhibitory action for cell migration and invasion in OS. Moreover, miR-202-5p directly targeted ROCK1 and negatively regulated its expression. Upregulation of ROCK1 had a carcinogenic effect in OS. Furthermore, the upregulation of ROCK1 restored the suppressive effect of miR-202-5p. miR-202-5p, in turn, weakened the abilities of cell migration and invasion in OS by inhibiting ROCK1 expression. As a result, miR-202-5p may be developed as a potential pathway in the reatment of OS.
Underwater wall climbing robot for nuclear pressure vessel inspection

The paper describes the development of an underwater teleoperated wall climbing robot that can carry another pipe crawler robot to nozzle openings inside a nuclear pressure vessel CPV). The wall climbing robot is positioned over each nozzle in the pressure vessel via teleoperation using visual feedback. The pipe crawler robot then transfers into the nozzle where it non-destructively tests circumferential welds located at a distance of 700mm from the inside walls of a pressure vessel. The results of trials with the robot in water tanks and a mock-up of the PV are presented. The paper describes the performance of the two underwater wall climbing robot prototypes, with emphasis on the design of a highly manoeuvrable robot and the performance of a special design of suction cups that have a low coefficient of friction and permit motion in cylindrical pressure vessels. Copyright © 2008 by World Scientific Publishing Co. Pte. Ltd.
Physiological and energetic correlates of en route mortality for abnormally early migrating adult sockeye salmon (Oncorhynchus nerka) in the Thompson River, British Columbia

Since 1995, large segments of the late-run sockeye salmon (Oncorhynchus nerka) stock complex from the Fraser River, British Columbia, Canada, have been initiating spawning migrations several weeks earlier than normal. Most aberrant migrants die before spawning. To evaluate the mechanisms underlying the mortality, we intercepted late- run sockeye salmon of the Adams-Shuswap stock complex halfway along their freshwater migration (i.e., in the Thompson River Canyon situated 270 km from the Fraser estuary), nonlethally assessed physiological and energetic status, and tracked individuals using gastrically inserted radio transmitters. Aberrant migrants that resumed their migra- tion but failed to reach the spawning grounds had lower gross somatic energy, higher average migration ground speeds, higher plasma osmolality, and higher levels of plasma reproductive hormones than those that reached the spawning grounds. Fish surgically fitted with electromyogram radio transmitters did not continue their migration and fell downstream. These fish displayed excessive bleeding during transmitter implantation, an unusual phenomenon that li- kely contributed to the fish's inability to resume migration. Blood clotting time decreased steadily throughout the mi- gration period. Collectively, these data implicate a combination of energy depletion, premature reproductive development, and blood loss from wounds as potential contributors to mortality in early migrating late-run sockeye. 1077
Seasonal Energetics and Condition of Bonefish from Different Subtropical Tidal Creeks in Eleuthera, the Bahamas

Abstract Body composition and fish health indices of bonefish Albula vulpes were investigated to elucidate the energy dynamics in poorly studied tropical tidal flat environments. In general, bonefish were composed of 72% water, 21% protein, 4% ash, and 3% lipids, which is consistent with the wet weight values of the majority of freshwater and marine fish studied to date. Significant inverse relationships between the water and lipid contents of whole-body, gonad, and liver tissues revealed that the percentage of water is a good indicator of the relative amount of stored energy in bonefish and may be used as a surrogate for lipid content in future studies. The liver was the main storage site for lipids, containing more than twice the fat in the whole body. While both abiotic (e.g., season and location) and biotic (e.g., sex and size) factors contributed to the predictive power of the general linear models generated for all constituent analyses, there were no significant differences in whole-body or liver lipid content between seasons, which may be explained by there being a consistent food supply year-round. There was, however, a significant relationship between lipid content and body size with respect to season. Lipid content decreased in the winter and increased in the summer with increasing body size, a trend that can be explained by the timing of the reproductive season in bonefish. Seasonal changes in the condition factor and gonadosomatic indices were also linked to the winter spawning season, with decreasing body condition and increasing gonad development in the winter. Observed site-specific differences in the lipid content and liver somatic indices of bonefish may be accounted for by local trophodynamics as well as subtle differences in life history strategies. The energy reserve and fish health index data collected in this study may provide a useful baseline for future comparative work and help elucidate fish energetics in dynamic tropical tidal flat systems.