Miracle-dz/UniFAR-FTUs huggingface dataset:
Internally Generated Error Signals in Monkey Frontal Eye Field during an Inferred Motion Task

An internal model for predictive saccades in frontal cortex was investigated by recording neurons in monkey frontal eye field (FEF) during an inferred motion task. Monkeys were trained to make saccades to the extrapolated position of a small moving target that was rendered temporarily invisible and whose trajectory was altered. On approximately two-thirds of the trials, monkeys made multiple saccades while the target was invisible. Primary saccades were correlated with extrapolated target position. Secondary saccades significantly reduced residual errors resulting from imperfect accuracy of the first saccade. These observations suggest that the second saccade was corrective. Because there was no visual feedback, corrective saccades could only be driven by an internally generated error signal. Neuronal activity in the frontal eye field was directionally tuned before both primary and secondary saccades. Separate subpopulations of cells encoded either saccade direction or direction error before the second saccade. These results suggest that FEF neurons encode the error after the first saccade, as well as the direction of the second saccade. Hence, FEF appears to contribute to detecting and correcting movement errors based on internally generated signals.
Reversible authentication watermark for image

(invertible, lossless) authentication draws much attention recently for its ability to restore the original image from marked image without any distortions upon verification. In this paper, we propose a reversible water-marking scheme for image authentication based on histogram modification in integer wavelet transform (IWT) domain. The proposed scheme has features: i) Reversibility, high embedding capacity, and good perceptual invisibility; ii) Tamper localiza-tion and discerning; iii) Detection without requiring explicit knowledge of the original image; iv) Verification before reconstruction of the original image, therefore computational requirements are reduced when reconstruction isn't needed. To our best knowledge, none of the reversible authentication schemes reported in the literature has all of the features. Those features make the proposed scheme practical, effective and appealing for strict content integrity authentication system. Experimental results demonstrate the feasibility and validity of the proposed scheme.
Design of a Permanent Magnet Synchronous Machine for the Hybrid Electric Vehicle

Abstract — Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine. Keywords — Design, Finite Element, Hybrid electric vehicle, Optimization, Permanent magnet synchronous machine. I. I NTRODUCTION ELECTION of traction machines for hybrid electric vehicles (HEVs) is important and needs to get enough attention. The major requirements of HEVs electric machines are as follows [1]: 1- High instant power and high power density 2- High torque at low speed and a high power at high speed 3- Wide speed range 4- Fast torque response 5- High efficiency over the wide speed and torque ranges 6- High efficiency for regenerative breaking 7- Reliability and robustness 8- Reasonable cost Different machines have been used in HEVs so far. Induction machines, permanent magnet machines, DC machines and switch reluctance machines are the most applicable machines [1, 2]. Induction machines are the most interesting machines for HEVs up to now. Whereas, permanent magnet synchronous machines (PMSMs) are the most capable competing with induction machines for the electric machines of HEVs. This is due to their many advantages including high efficiency, compactness, high power density, fast dynamics and high torque to inertia ratio. Interior permanent magnet (IPM) machines with extra features
Ontology searching and browsing at the Rat Genome Database

The Rat Genome Database (RGD) is the premier repository of rat genomic and genetic data and currently houses over 40 000 rat gene records, as well as human and mouse orthologs, 1857 rat and 1912 human quantitative trait loci (QTLs) and 2347 rat strains. Biological information curated for these data objects includes disease associations, phenotypes, pathways, molecular functions, biological processes and cellular components. RGD uses more than a dozen different ontologies to standardize annotation information for genes, QTLs and strains. That means a lot of time can be spent searching and browsing ontologies for the appropriate terms needed both for curating and mining the data. RGD has upgraded its ontology term search to make it more versatile and more robust. A term search result is connected to a term browser so the user can fine-tune the search by viewing parent and children terms. Most publicly available term browsers display a hierarchical organization of terms in an expandable tree format. RGD has replaced its old tree browser format with a ‘driller’ type of browser that allows quicker drilling up and down through the term branches, which has been confirmed by testing. The RGD ontology report pages have also been upgraded. Expanded functionality allows more choice in how annotations are displayed and what subsets of annotations are displayed. The new ontology search, browser and report features have been designed to enhance both manual data curation and manual data extraction. Database URL: http://rgd.mcw. edu/rgdweb/ontology/search.html
An assessment of natural radionuclides in water of Langat River estuary, Selangor

An estuary is an area that has a free connection with the open sea and it is a dynamic semi-enclosed coastal bodies. Ex-mining, aquaculture and industrial areas in Selangor are the sources of pollutants discharged into the estuary water. Radionuclides are considered as pollutants to the estuary water. Gamma radiations emitted by natural radionuclides through their decaying process may give impact to human. The radiological effect of natural radionuclides which are 226Ra, 228Ra, 40K, 238U and 232Th, were explored by determining the respective activity concentrations in filtered water along the Langat estuary, Selangor. Meanwhile, in- situ water quality parameters such as temperature, dissolve oxygen (DO), salinity, total suspended solid (TSS), pH and turbidity were measured by using YSI portable multi probes meter. The activity concentration of 226Ra, 228Ra and 40K were determined by using gamma-ray spectrometry with high-purity germanium (HPGe) detector. The activity concentrations of 226Ra, 228Ra and 40K in samples are in the range of 0.17 - 0.67 Bq/L, 0.16 - 0.97 Bq/L and 1.22 - 5.57 Bq/L respectively. On the other hand, the concentrations of uranium-238 and thorium-232 were determined by using Energy Dispersive X-ray Fluorescence Spectrometry (EDXRF). The thorium concentrations are between 0.17 ppm to 0.28 ppm and uranium concentrations were 0.25 ppm to 0.31 ppm. The results show activity concentrations of radionuclides are slightly high near the river estuary. The Radium Equivalent, Absorbed Dose Rate, External Hazard Index, and Annual Effective Dose of 226Ra, 228Ra and 40K are also studied.An estuary is an area that has a free connection with the open sea and it is a dynamic semi-enclosed coastal bodies. Ex-mining, aquaculture and industrial areas in Selangor are the sources of pollutants discharged into the estuary water. Radionuclides are considered as pollutants to the estuary water. Gamma radiations emitted by natural radionuclides through their decaying process may give impact to human. The radiological effect of natural radionuclides which are 226Ra, 228Ra, 40K, 238U and 232Th, were explored by determining the respective activity concentrations in filtered water along the Langat estuary, Selangor. Meanwhile, in- situ water quality parameters such as temperature, dissolve oxygen (DO), salinity, total suspended solid (TSS), pH and turbidity were measured by using YSI portable multi probes meter. The activity concentration of 226Ra, 228Ra and 40K were determined by using gamma-ray spectrometry with high-purity germanium (HPGe) detector. The activity concentrations of 226Ra, 228Ra and 40K.
Climatic and basin factors affecting the flood frequency curve: PART I – A simple sensitivity analysis based on the continuous simulation approach

Abstract. Regionalized and at-site flood frequency curves exhibit considerable variability in their shapes, but the factors controlling the variability (other than sampling effects) are not well understood. An application of the Monte Carlo simulation-based derived distribution approach is presented in this two-part paper to explore the influence of climate, described by simulated rainfall and evapotranspiration time series, and basin factors on the flood frequency curve (ffc). The sensitivity analysis conducted in the paper should not be interpreted as reflecting possible climate changes, but the results can provide an indication of the changes to which the flood frequency curve might be sensitive. A single site Neyman Scott point process model of rainfall, with convective and stratiform cells (Cowpertwait, 1994; 1995), has been employed to generate synthetic rainfall inputs to a rainfall runoff model. The time series of the potential evapotranspiration (ETp) demand has been represented through an AR(n) model with seasonal component, while a simplified version of the ARNO rainfall-runoff model (Todini, 1996) has been employed to simulate the continuous discharge time series. All these models have been parameterised in a realistic manner using observed data and results from previous applications, to obtain ‘reference’ parameter sets for a synthetic case study. Subsequently, perturbations to the model parameters have been made one-at-a-time and the sensitivities of the generated annual maximum rainfall and flood frequency curves (unstandardised, and standardised by the mean) have been assessed. Overall, the sensitivity analysis described in this paper suggests that the soil moisture regime, and, in particular, the probability distribution of soil moisture content at the storm arrival time, can be considered as a unifying link between the perturbations to the several parameters and their effects on the standardised and unstandardised ffcs, thus revealing the physical mechanism through which their influence is exercised. However, perturbations to the parameters of the linear routing component affect only the unstandardised ffc. In Franchini et al. (2000), the sensitivity analysis of the model parameters has been assessed through an analysis of variance (ANOVA) of the results obtained from a formal experimental design, where all the parameters are allowed to vary simultaneously, thus providing deeper insight into the interactions between the different factors. This approach allows a wider range of climatic and basin conditions to be analysed and reinforces the results presented in this paper, which provide valuable new insight into the climatic and basin factors controlling the ffc. Keywords: stochastic rainfall model; rainfall runoff model; simulation; derived distribution; flood frequency; sensitivity analysis
Prion Protein-mediated Toxicity of Amyloid-β Oligomers Requires Lipid Rafts and the Transmembrane LRP1*

Background: Prion protein (PrPC) is a receptor for amyloid-β oligomers (AβOs). Results: AβO binding to PrPC and cytotoxicity require transmembrane LRP1 and are reduced by cholesterol depletion and AβO remodeling. Conclusion: Cellular binding and toxicity of AβOs are dependent on PrPC being localized in a raft-based complex. Significance: Remodeling AβOs and disrupting the prion-LRP1-raft interaction provide therapeutic targets for Alzheimer disease. Soluble oligomers of the amyloid-β (Aβ) peptide cause neurotoxicity, synaptic dysfunction, and memory impairments that underlie Alzheimer disease (AD). The cellular prion protein (PrPC) was recently identified as a high affinity neuronal receptor for Aβ oligomers. We report that fibrillar Aβ oligomers recognized by the OC antibody, which have been shown to correlate with the onset and severity of AD, bind preferentially to cells and neurons expressing PrPC. The binding of Aβ oligomers to cell surface PrPC, as well as their downstream activation of Fyn kinase, was dependent on the integrity of cholesterol-rich lipid rafts. In SH-SY5Y cells, fluorescence microscopy and co-localization with subcellular markers revealed that the Aβ oligomers co-internalized with PrPC, accumulated in endosomes, and subsequently trafficked to lysosomes. The cell surface binding, internalization, and downstream toxicity of Aβ oligomers was dependent on the transmembrane low density lipoprotein receptor-related protein-1 (LRP1). The binding of Aβ oligomers to cell surface PrPC impaired its ability to inhibit the activity of the β-secretase BACE1, which cleaves the amyloid precursor protein to produce Aβ. The green tea polyphenol (−)-epigallocatechin gallate and the red wine extract resveratrol both remodeled the fibrillar conformation of Aβ oligomers. The resulting nonfibrillar oligomers displayed significantly reduced binding to PrPC-expressing cells and were no longer cytotoxic. These data indicate that soluble, fibrillar Aβ oligomers bind to PrPC in a conformation-dependent manner and require the integrity of lipid rafts and the transmembrane LRP1 for their cytotoxicity, thus revealing potential targets to alleviate the neurotoxic properties of Aβ oligomers in AD.
EAI Endorsed Transactions Preprint F-ETX: a predictive link state estimator for mobile networks

Due to their inherent features, Mobile Ad Hoc Networks have proven their efficiency to exchange data between mobile nodes. The main issue in this type of a network is the delivery of data to a destination. Unfortunately, the mobility of nodes and the disturbances of the propagation channel lead to the increase of the loss rate, which undermines routing performances. To address this issue, routing protocols use link quality estimators as a metric. However, current estimators have been designed for static wireless sensor networks and are not suitable in case of mobility. In order to overcome this issue, a novel metric called Fast ETX is suggested, which gives a reliable and accurate link quality assessment. It is setup by four estimators which assess and predict the link state. In addition, we design a framework to integrate this multi-estimator metric into a routing protocol.
Application of a perfectly matched layer in seismic wavefield simulation with an irregular free surface

Recently, an effective and powerful approach for simulating seismic wave propagation in elastic media with an irregular free surface was proposed. However, in previous studies, researchers used the periodic condition and/or sponge boundary condition to attenuate artificial reflections at boundaries of a computational domain. As demonstrated in many literatures, either the periodic condition or sponge boundary condition is simple but much less effective than the well‐known perfectly matched layer boundary condition. In view of this, we intend to introduce a perfectly matched layer to simulate seismic wavefields in unbounded models with an irregular free surface. We first incorporate a perfectly matched layer into wave equations formulated in a frequency domain in Cartesian coordinates. We then transform them back into a time domain through inverse Fourier transformation. Afterwards, we use a boundary‐conforming grid and map a rectangular grid onto a curved one, which allows us to transform the equations and free surface boundary conditions from Cartesian coordinates to curvilinear coordinates. As numerical examples show, if free surface boundary conditions are imposed at the top border of a model, then it should also be incorporated into the perfectly matched layer imposed at the top‐left and top‐ right corners of a 2D model where the free surface boundary conditions and perfectly matched layer encounter; otherwise, reflections will occur at the intersections of the free surface and the perfectly matched layer, which is confirmed in this paper. So, by replacing normal second derivatives in wave equations in curvilinear coordinates with free surface boundary conditions, we successfully implement the free surface boundary conditions into the perfectly matched layer at the top‐left and top‐right corners of a 2D model at the surface. A number of numerical examples show that the perfectly matched layer constructed in this study is effective in simulating wave propagation in unbounded media and the algorithm for implementation of the perfectly matched layer and free surface boundary conditions is stable for long‐time wavefield simulation on models with an irregular free surface.
SkyAI: Highly modularized reinforcement learning library

This paper introduces a software library of reinforcement learning (RL) methods, named SkyAI. SkyAI is a highly modularized RL library for real/simulated robots to learn behaviors. Our ultimate goal is to develop an artificial intelligence (AI) program with which the robots can learn to behave as their users' wish. In this paper, we describe the concepts, the requirements, and the current implementation of SkyAI. SkyAI provides two conflicting features: high execution-speed enough for real robot systems and high flexibility to design learning systems. We also demonstrate the applications to crawling tasks of both a humanoid robot in simulation and a real spider robot.
Application-aware latency monitoring for cloud tenants via CloudWatch+

A tenant hosted by a cloud platform typically runs a lot of applications, each of which not only has its own service capacity but also differs in revenue or business importance. Thus we argue that it is crucial for a cloud platform to provide fine-grained and application-aware performance monitoring for each tenant, rather than current monitors that can only handle overall metrics. In this paper, we propose CloudWatch+, a tool that focuses on detecting the latency of web-based applications. A cloud platform equipping with CloudWatch+ can automatically learn and distinguish web-based applications it is hosting, and detect latency anomalies for each application based on its own status. Our evaluation using the real data from a cloud platform with over 200 tenants demonstrates that the detection results of CloudWatch+ are more detailed than those of Amazon CloudWatch, which misses most alarms while some tenants' specific applications experience bad performance. Meanwhile, CloudWatch+ is also realtime and light-weight.
A calculus for access control in distributed systems

We study some of the concepts, protocols, and algorithms for access control in distributed systems, from a logical perspective. We account for how a principal may come to believe that another principal is making a request, either on his own or on someone else's behalf. We also provide a logical language for accesss control lists and theories for deciding whether requests should be granted.
LoVis: Local Pattern Visualization for Model Refinement

Linear models are commonly used to identify trends in data. While it is an easy task to build linear models using pre‐selected variables, it is challenging to select the best variables from a large number of alternatives. Most metrics for selecting variables are global in nature, and thus not useful for identifying local patterns. In this work, we present an integrated framework with visual representations that allows the user to incrementally build and verify models in three model spaces that support local pattern discovery and summarization: model complementarity, model diversity, and model representivity. Visual representations are designed and implemented for each of the model spaces. Our visualizations enable the discovery of complementary variables, i.e., those that perform well in modeling different subsets of data points. They also support the isolation of local models based on a diversity measure. Furthermore, the system integrates a hierarchical representation to identify the outlier local trends and the local trends that share similar directions in the model space. A case study on financial risk analysis is discussed, followed by a user study.
Placement of rechargeable routers based on proportional fairness in green mesh networks

Nowadays, the fast development of wireless mesh networks have led to a significant growth of energy consumption. Green mesh networks consisting of rechargeable routers supplied by renewable energy sources such as solar power have become a cost-effective alternative solution. In this paper, we study the rechargeable router placement problem and formulate it as an optimization problem to minimize the number of deployed routers while ensuring system Quality of Service (QoS) constraints, including users' traffic demand, routers' energy consumption, network failure rate and traffic fairness among users. To assign users to appropriate routers, we first propose two cell association algorithms, namely, Nearest Cell Association Algorithm (NCA) and Proportional Fairness cell Association Algorithm (PFCA). The former only considers the system level efficiency, which may cause unfairness among different users. The later tries to achieve a balance between the network performance and the user fairness. We then design two heuristic placement algorithms embedded with the proposed cell association methods to find approximate solutions for the rechargeable router placement problem. Simulation results show that compared with the optimal placement achieved by exhaustive search, ours can achieve good performance while with greatly reduced computation complexity. Furthermore, the proposed PFCA algorithm can guarantee user fairness with a increase of placement cost.
Comparison analysis of the global carbon dioxide concentration column derived from SCIAMACHY, AIRS, and GOSAT with surface station measurements

As a significant greenhouse gas, CO2 plays an important role in not only the formation of, but also in changes to, the Earth’s climate. A series of remote-sensing detectors have been launched into space to aid the understanding of sources and sinks of CO2. Although measurements from AIRS (Atmospheric Infrared Sounder), SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography), and GOSAT (Greenhouse Gases Observing Satellite) have been frequently used to retrieve atmospheric CO2 concentrations, there are no comprehensive comparison analyses between satellite data and ground data. In this article, the characteristics of the current common observing platforms and their product data are compared and analysed. Correlation coefficient, RMSD, and bias are used to evaluate the CO2 retrieved from satellite data. The results reveal that: SCIAMACHY has limitations in detecting CO2 over the ocean; GOSAT has the poorest coverage on a global scale but has a better capability to detect CO2 over the sea than SCIAMACHY; and AIRS can reflect the distribution and changes of CO2 very well. The differences in coverage and accuracy indicate the necessity to produce consistent products with improved spatial and temporal features and indicate a future development trend for instruments including higher spectral resolution, higher spatial resolution, wider coverage, shorter revisit periods, and higher signal to noise ratios.