Miracle-dz/UniFAR-FTUs huggingface dataset:
Design Ratio-Memory Cellular Neural Network (RMCNN) in CMOS Circuit Used in Association-Memory Applications for 0.25 mm Silicon Technology

Abstract: The paper is proposed the Ratio-Memory Cellular Neural Network (RMCNN) that structure with the self-feedback and the modified Hebbian learning algorithm. The learnable RMCNN architecture was designed and realized in CMOS technology for associative memory neural network applications. The exemplar patterns can be learned and correctly recognized the output patterns for the proposed system. Only self-output pixel value in A template and B template weights are updated by the nearest neighboring five elements for all test input exemplar patterns. The learned ratio weights of the B template are generated that the catch weights are performed the summation of absolute coefficients operation to enhance the feature of recognized pattern. Simulation results express that the system can be learned some exemplar patterns with noise and recognized the correctly pattern. The 9×9 RMCNN structure with self-feedback and the modified Hebbian learning algorithm is implemented and verified in the CMOS circuits for TSMC 0.25 μm 1P5M VLSI technology. The proposed RMCNN have more learning and recognition capability for the variant exemplar patterns in the auto-associative memory neural system applications.
Human perception-based image segmentation using optimising of colour quantisation

This study presents an advanced histogram-based image segmentation method that enhances image segmentation quality, while greatly reducing the computational complexity. Unlike existing histogram-based methods, the authors optimise the size of bins in the colour histogram by using human perception-based colour quantisation and the clustering centroids are selected effectively without using a complex process. Additionally, an over-segmentation removal technique based on connected-component labelling is employed. This improves the segmentation quality by connectivity analysis. A comparison between the experimental results on the Berkeley Segmentation Dataset by the proposed method and the benchmark methods demonstrated that the proposed method enhanced the segmentation quality by improving the Probabilistic Rand Index and the Segmentation Covering values compared with those of the benchmark methods. The computation time using the proposed method is reduced by up to 91.63% compared with the computation time using benchmark methods.
The development of vestibular system and related functions in mammals: impact of gravity

This chapter reviews the knowledge about the adaptation to Earth gravity during the development of mammals. The impact of early exposure to altered gravity is evaluated at the level of the functions related to the vestibular system, including postural control, homeostatic regulation, and spatial memory. The hypothesis of critical periods in the adaptation to gravity is discussed. Demonstrating a critical period requires removing the gravity stimulus during delimited time windows, what is impossible to do on Earth surface. The surgical destruction of the vestibular apparatus, and the use of mice strains with defective graviceptors have provided useful information on the consequences of missing gravity perception, and the possible compensatory mechanisms, but transitory suppression of the stimulus can only be operated during spatial flight. The rare studies on rat pups housed on board of space shuttle significantly contributed to this problem, but the use of hypergravity environment, produced by means of chronic centrifugation, is the only available tool when repeated experiments must be carried out on Earth. Even though hypergravity is sometimes considered as a mirror situation to microgravity, the two situations cannot be confused because a gravitational force is still present. The theoretical considerations that validate the paradigm of hypergravity to evaluate critical periods are discussed. The question of adaption of graviceptor is questioned from an evolutionary point of view. It is possible that graviception is hardwired, because life on Earth has evolved under the constant pressure of gravity. The rapid acquisition of motor programming by precocial mammals in minutes after birth is consistent with this hypothesis, but the slow development of motor skills in altricial species and the plasticity of vestibular perception in adults suggest that gravity experience is required for the tuning of graviceptors. The possible reasons for this dichotomy are discussed.
Cilostazol attenuates kainic acid-induced hippocampal cell death

Cilostazol is a selective inhibitor of type 3 phosphodiesterase (PDE3) and has been widely used as an antiplatelet agent. Cilostazol mediates this activity through effects on the cyclic adenosine monophosphate (cAMP) signaling cascade. Recently, it has attracted attention as a neuroprotective agent. However, little is known about cilostazol's effect on excitotoxicity induced neuronal cell death. Therefore, this study evaluated the neuroprotective effect of cilostazol treatment against hippocampal neuronal damage in a mouse model of kainic acid (KA)-induced neuronal loss. Cilostazol pretreatment reduced KA-induced seizure scores and hippocampal neuron death. In addition, cilostazol pretreatment increased cAMP response element-binding protein (CREB) phosphorylation and decreased neuroinflammation. These observations suggest that cilostazol may have beneficial therapeutic effects on seizure activity and other neurological diseases associated with excitotoxicity.
RSK Activation of Translation Factor eIF4B Drives Abnormal Increases of Laminin γ2 and MYC Protein during Neoplastic Progression to Squamous Cell Carcinoma

Overexpression of the basement membrane protein Laminin γ2 (Lamγ2) is a feature of many epidermal and oral dysplasias and all invasive squamous cell carcinomas (SCCs). This abnormality has potential value as an immunohistochemical biomarker of premalignancy but its mechanism has remained unknown. We recently reported that Lamγ2 overexpression in culture is the result of deregulated translation controls and depends on the MAPK-RSK signaling cascade. Here we identify eIF4B as the RSK downstream effector responsible for elevated Lamγ2 as well as MYC protein in neoplastic epithelial cells. Premalignant dysplastic keratinocytes, SCC cells, and keratinocytes expressing the E6 oncoprotein of human papillomavirus (HPV) type 16 displayed MAPK-RSK and mTOR-S6K1 activation and overexpressed Lamγ2 and MYC in culture. Immunohistochemical staining of oral dysplasias and SCCs for distinct, RSK- and S6K1-specific S6 phosphorylation events revealed that their respective upstream pathways become hyperactive at the same time during neoplastic progression. However, pharmacologic kinase inhibitor studies in culture revealed that Lamγ2 and MYC overexpression depends on MAPK-RSK activity, independent of PI3K-mTOR-S6K1. eIF4B knockdown reduced Lamγ2 and MYC protein expression, consistent with the known requirement for eIF4B to translate mRNAs with long, complex 5′ untranslated regions (5′-UTRs). Accordingly, expression of a luciferase reporter construct preceded by the Lamγ2 5′-UTR proved to be RSK-dependent and mTOR-independent. These results demonstrate that RSK activation of eIF4B is causally linked to elevated Lamγ2 and MYC protein levels during neoplastic progression to invasive SCC. These findings have potential clinical significance for identifying premalignant lesions and for developing targeted drugs to treat SCC.
Numerical Terradynamic Simulation Group 7-2006 MODIS land cover and LAI Collection 4 product quality across nine sites in the western hemisphere

Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS products. We present an updated BigFoot project rotocol S for developing 25-m validation data layers over 49-km study areas. Results from comparisons of MODIS and BigFoot land cover and LA1 products at nine contrasting sites are reported. In terms of proportional coverage, MODIS and BigFoot land cover were in close agreement at six sites. The largest differences were at low tree cover evergreen needleleaf sites and at an Arctic tundra site where the MODIS product overestimated woody cover proportions. At low leaf biomass sites there was reasonable agreement between MODIS and BigFoot LA1 products, but there was not a particular MODIS LA1 algorithm pathway that consistently compared most favorably. At high leaf biomass sites, MODIS LA1 was generally overpredicted by a significant amount. For evergreen needleleaf sites, LA1 seasonality was exaggerated by MODIS. Our results suggest incremental improvement from Collection 3 to Collection 4 MODIS products, with some remaining problems that need to be addressed.
A Multi Objective Hybrid Differential Evolution Algorithm assisted Genetic Algorithm Approach for Optimal Reactive Power and Voltage Control

To provide a quality and secured power supply in all the load centres is a challenging task. Due to the increase in load and various emergency conditions the voltage level in load centres may vary beyond the acceptable level which leads to voltage collapse and increase the system losses. To maintain the voltage levels within the acceptable range in all load centres reactive power support is very essential. The control centres has to provide the optimal reactive power where ever necessary to prevent these critical situations. To provide the controllable amount of reactive power and voltage in the needy region efficient power flow analysis are required. Many traditional methods are available but it has limitations and converged in poor optimal solution. In this paper an effective hybrid Differential Evolution Algorithm assisted Genetic Algorithm approach with multi objective functions are considered. In this approach the best features of Differential Evolution Algorithm and Genetic Algorithm are combined together and developed. In IEEE 30bus the effectiveness and the superiority of this method is verified. asir_70@hotmail.com Keyword-Newton Raphson Power Flow, Genetic Algorithm, Differential Evolution, Volt Ampere Reactive, Voltage Stability Index
Balanced Energy Efficient Rectangular routing protocol for Underwater Wireless Sensor Networks

Modeling of Underwater Wireless Sensor Networks (UWSNs) with a goal of maximum network lifetime and throughput with minimum energy consumption is a quite difficult task because of limited battery power and harsh underwater environment. Balanced Energy Efficient Rectangular routing protocol (BEER) covers the maximum network area with the mobility of sinks and collects the data from sensor nodes in their transmission range using direct transmission. Sink movement maximizes the throughput and balanced the energy consumption. Simulation results verify that our scheme performs outstanding in terms of network lifetime, stability period and throughput with minimum energy consumption.
Making optical MEMS sensors more compact using organic light sources and detectors

Vibration and displacement sensors need to be compact for many applications in automation or consumer electronics, and microelectromechanical structures are a convenient way to implement such sensors. For these MEMS devices, optical readout methods have proven to be superior to capacitive or piezoresistive strategies in terms of sensitivity as well as noise and interference immunity, however the integration of light sources and detectors is not easily possible. This paper presents an approach to use organic optoelectronic devices for the readout. OLED and OPD (organic photo detector) are structured on the glass substrate and cover encapsulating the MEMS devices, allowing for a tightly integrated sensor based on vertical light flux modulation by a horizontally moving proof mass. The paper describes the principle sensor structure as well as the fabrication of suitable organic devices. First test results show that the approach is feasible.
Unraveling the cellular and molecular mechanisms of repetitive magnetic stimulation

Despite numerous clinical studies, which have investigated the therapeutic potential of repetitive transcranial magnetic stimulation (rTMS) in various brain diseases, our knowledge of the cellular and molecular mechanisms underlying rTMS-based therapies remains limited. Thus, a deeper understanding of rTMS-induced neural plasticity is required to optimize current treatment protocols. Studies in small animals or appropriate in vitro preparations (including models of brain diseases) provide highly useful experimental approaches in this context. State-of-the-art electrophysiological and live-cell imaging techniques that are well established in basic neuroscience can help answering some of the major questions in the field, such as (i) which neural structures are activated during TMS, (ii) how does rTMS induce Hebbian plasticity, and (iii) are other forms of plasticity (e.g., metaplasticity, structural plasticity) induced by rTMS? We argue that data gained from these studies will support the development of more effective and specific applications of rTMS in clinical practice.
Échange de Connaissances entre Utilisateurs et Agents Autonomes dans les EVFC

Cet article propose une approche innovante de la gestion et de l'echange de connaissances entre utilisateurs et agents autonomes dans les Environnements Virtuels de Formation Collaboratifs. Afin de faciliter a la fois le dialogue et la realisation de taches collaboratives au sein d'une equipe pouvant etre composee d'utilisateurs et d'agents autonomes, nous introduisons une entite commune a ces derniers : le Shell. Cette entite regroupe la gestion des connaissances et le controle du mannequin qui lui est attache. Les agents autonomes, bases sur une architecture nommee C-BDI, exploitent les connaissances du Shell auquel ils sont lies afin d'alimenter leur processus de prise de decision et d'enrichir leur dialogue, base sur une approche Information-State. Les utilisateurs peuvent egalement acceder aux connaissances de leur Shell respectif a travers une in- terface utilisateur.
1-Point RANSAC for extended Kalman filtering: Application to real-time structure from motion and visual odometry

Random sample consensus (RANSAC) has become one of the most successful techniques for robust estimation from a data set that may contain outliers. It works by constructing model hypotheses from random minimal data subsets and evaluating their validity from the support of the whole data. In this paper we present a novel combination of RANSAC plus extended Kalman filter (EKF) that uses the available prior probabilistic information from the EKF in the RANSAC model hypothesize stage. This allows the minimal sample size to be reduced to one, resulting in large computational savings without the loss of discriminative power. 1-Point RANSAC is shown to outperform both in accuracy and computational cost the joint compatibility branch and bound (JCBB) algorithm, a gold-standard technique for spurious rejection within the EKF framework. Two visual estimation scenarios are used in the experiments: first, six-degree-of-freedom (DOF) motion estimation from a monocular sequence (structure from motion). Here, a new method for benchmarking six-DOF visual estimation algorithms based on the use of high-resolution images is presented, validated, and used to show the superiority of 1-point RANSAC. Second, we demonstrate long-term robot trajectory estimation combining monocular vision and wheel odometry (visual odometry). Here, a comparison against global positioning system shows an accuracy comparable to state-of-the-art visual odometry methods. © 2010 Wiley Periodicals, Inc.
Trypanosoma cruzi Infection Induces a Global Host Cell Response in Cardiomyocytes

ABSTRACT Chagas' disease, caused by the hemoflagellate protozoan Trypanosoma cruzi, affects millions of people in South and Central America. Chronic chagasic cardiomyopathy, the most devastating manifestation of this disease, occurs in approximately one-third of infected individuals. Events associated with the parasite's tropism for and invasion of cardiomyocytes have been the focus of intense investigation in recent years. In the present study, we use murine microarrays to investigate the cellular response caused by invasion of primary murine cardiomyocytes by T. cruzi trypomastigotes. These studies identified 353 murine genes that were differentially expressed during the early stages of invasion and infection of these cells. Genes associated with the immune response, inflammation, cytoskeleton organization, cell-cell and cell-matrix interactions, apoptosis, cell cycle, and oxidative stress are among those affected during the infection. Our data indicate that T. cruzi induces broad modulations of the host cell machinery in ways that provide insight into how the parasite survives, replicates, and persists in the infected host and ultimately defines the clinical outcome of the infection.
A Knapsack Problem Approach for Optimal Allocation of Maintenance Resources on Electric Power Distribution Networks

The definitions of optimal preventive and corrective maintenance of electric power distribution networks can be seen as a special case of a knapsack problem. This paper proposes a dynamic programming approach to deal with this problem. The approach is developed for one or more years of planning horizon. Case studies compare the optimal dynamic programming approach with an heuristic method.
Evolution of structural properties of glass-mica-epoxy insulations along accelerated thermo-oxidative aging

The stator windings of large air-cooled rotating machines are insulated with mica-glass fabric impregnated with epoxy. These composites are submitted to thermal, mechanical and electrical stresses. A specific aging arrangement has been setup allowing artificial thermo-oxidative aging of dielectric samples thanks to the application of a dry O2 pressure at a controlled temperature. Two different materials are considered: a class H material, designed to sustain temperatures up to 180degC, and a high conductivity (HC) tape material, which is a class F insulation. The samples were followed in mass and DMA (dynamic mechanical analysis). Similar profiles of mass evolution with various temperature and oxygen pressure contribute to validate the artificial aging procedure. DMA allowed determining the glass transition temperature (Tg) of the epoxy resin and observing the evolution of the network density of the polymeric matrix along aging. Delaminations of a few tens mum thick were observed within the samples after aging. These characterizations allowed the comparison between both materials.
The methods to determine flat-band voltage VFB in semiconductor of a MOS structure

One of the most important parameters of the MOS (metal-oxide-semiconductor) structure is the flat-band voltage VFB in semiconductor. This voltage influences the threshold voltage VT, which is the fundamental parameter of any MOS device. Hence, the VFB voltage has a great practical importance and the precise and accurate determination of its value is very important.
Mathematical Comparison Methods to Assess Transfer Functions of Transformers to Detect Different Types of Mechanical Faults

The transfer function (TF) these days is a well-known method to detect different types of mechanical damage in power transformers. The most important mechanical faults mentioned by the authors and researchers, which are most likely to be detected using the TF and occur frequently in transformers, are disc-space variation, radial deformation, and axial displacement. These faults are investigated in this paper using three different similar-size test objects. Since the TF method is a comparative method and the measured results should be compared with the reference results, some mathematical methods are studied to compare different TFs. A complete fault detection, which means determining the type, location, and level of the faults by using TF analyses is the main aim of this paper.
Detail-preserving change detection from amplitude SAR images

This paper presents a modified version of the information-theoretic feature in [1] for change detection in multitemporal synthetic aperture radar (SAR) imagery. The proposed method is capable of capturing small-area structural changes between the two images, by maintaining at the same time the capability of rejecting statistical changes due to speckle patterns or co-registration inaccuracies. This improvement is obtained by bootstrapping the original procedure by means of an adaptive preliminary selection of potentially changed pixels driven by the logarithm of the pixel ratio. Experimental results have been carried out on true SAR images acquired by the COSMO-SkyMed constellation.
International Journal of Innovative Research in Computer and Communication Engineering Region of Interest Based Image Compression

The basic goal of region of interest (ROI) based compression for medical image is to enhance the compression efficiency for transmission and storage.Main goal of Region of interest(ROI) compression is to compressROI with supreme quality as compared to other region called Background. For an example, while compressing medical image the diagnostically important region should be compressed with better quality than background. Thus, the ROI area is compressed with less compression ratio and the background with the highest possible compression ratio in order to get overall better compression performance. As a part of ROI compression technique algorithm is developed using discrete cosine transform and Wavelet transform. A detailed analysis is carried out on the basis of parameters like compression ratio(CR),mean square error(MSE) and peak signal to noise ratio(PSNR). Advantage of ROI compression over conventional compression scheme is to improve quality of ROI with less value of MSE and PSNR. I. INTRODUCTION The aim of this paper is to propose an algorithm which compressesmedical images.It requires some specific portion as region of interest called ROI in which we have to maintain the image quality and other than ROI portion is called Background.The US medical images are used for diagnosis purpose so here good quality of ROI is required. Image compression is the application of data compression on digital images. The objective is to reduce redundancies of image data in order to able to store or transmit the data in an efficient form.The reduction in file size allows more images to be stored in a given amount of disk or memory.It is also reduction the time required for images to be sent over the Internet. It also reduction the time for downloaded from Web pages. The purpose of image compression is to achieve a very low bit rate representation [10]. In case of conventional compression schemes the equal loss of information will occur for whole image, as they are compressed with equal CR but in contextual compression schemes, the visual quality of important area (ROI) will be quite better due to less information loss of ROI as compared to back ground.