Miracle-dz/UniFAR-FTUs huggingface dataset:
Does donepezil treatment slow the progression of hippocampal atrophy in patients with Alzheimer's disease?

OBJECTIVE The only approved pharmacological approach for the symptomatic treatment of Alzheimer's disease in Japan is the use of a cholinesterase inhibitor, donepezil hydrochloride. Recent in vivo and in vitro studies raise the possibility that cholinesterase inhibitors can slow the progression of Alzheimer's disease. The purpose of the present study was to determine whether donepezil has a neuroprotective effect in Alzheimer's disease by using the rate of hippocampal atrophy as a surrogate marker of disease progression. METHOD In a prospective cohort study, 54 patients with Alzheimer's disease who received donepezil treatment and 93 control patients with Alzheimer's disease who never received anti-Alzheimer drugs underwent magnetic resonance imaging (MRI) twice at a 1-year interval. The annual rate of hippocampal atrophy of each subject was determined by using an MRI-based volumetric technique. Background characteristics, age, sex, disease duration, education, MRI interval, apolipoprotein E (APOE) genotype, and baseline Alzheimer's Disease Assessment Scale score were comparable between the treated and control groups. RESULTS The mean annual rate of hippocampal volume loss among the treated patients (mean=3.82%, SD=2.84%) was significantly smaller than that among the control patients (mean=5.04%, SD=2.54%). Upon analysis of covariance, where those confounding variables (age, sex, disease duration, education, MRI interval, APOE genotype, and baseline Alzheimer's Disease Assessment Scale score) were entered into the model as covariates, the effect of donepezil treatment on hippocampal atrophy remained significant. CONCLUSIONS Donepezil treatment slows the progression of hippocampal atrophy, suggesting a neuroprotective effect of donepezil in Alzheimer's disease.
A three-level MOSFET inverter for low-power drives

This paper proposes operating a three-level neutral-point-clamped (NPC) inverter using a two-level pulsewidth-modulation method. This allows for the clamping diodes to be rated at a fraction of the main switches due to their low average current requirement. The use of a bootstrap charge pump as a low-cost method to obtain the isolated gate drive power supplies is extended for use with the NPC topology. Using this control method and circuits, an inverter based on high-volume, low-cost, low-voltage power MOSFETs is experimentally demonstrated as a possible economic alternative to an insulated-gate-bipolar-transistor-based drive for 120-Vrms-supplied systems.
Optimal Network Alignment with Graphlet Degree Vectors

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.
How to Steal a Dog

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A method for feature extraction and classification of marine radar images

There are ship images (target) and non-ship images (noise) on radar images. In order to obtain other ship information from radar images, it is necessary to select and acquire ship images on radar images. Ship images are selected and acquired by navigation officers based on their observation skill and experience. The future purpose of this study is to automatically detect ship images on the radar. Therefore, in this paper, we propose the method for dividing ship images from non-ship images by the image processing and the cluster analysis using radar raster images. Many image feature points were extracted by the image processing using radar raster images. As a result of the cluster analysis using these image feature points, it is possible to detect about 99.8% ship images from radar raster images. However, there were many cases that non-ship images were classed as ship images. Therefore, the accuracy rate of cluster analysis results in this study was about 83%. In other words, it was possible to fairly determine about 83% images in this study.
Discovering Near-Optimal Communication Network for Modular Robots

Neighbor-to-Neighbor (Inter-Module) communication between modules using methods such as infrared, radio and bus-type connection are critical component for global behavior coordination. However, this type of communication method does not necessarily provide the shortest possible routes between modules and not making use of Hidden Communication Shortcuts (HCS). A HCS is defined as a communication channel between two modules without involving any inter-module (nonHCS) communication. For example, instead of sending messages through all modules in a snake configuration, the head module can directly talk to the tail module through infra-red if they are physically close. This paper proposes a novel way to discover existing communication shortcuts distributedly and form a near-optimal network using these shortcuts to connect a set of given terminal modules based on inter-module communication. The size of the discovered network is at most two times larger than the optimal (minimal) ones. To make this approach more realistic, we assume that not all communication devices on the modules are turned on simultaneously and in fact no more than r modules are allowed to turn on devices for non inter-module communication at the same time to avoid interferences. Derived from a centralized network deployment approach of mobile robot network ANCHOR [7], this paper provides (1) a distributed algorithm for HCS discovery among modular robots (2) with adaptation to heterogeneity as long as the modular robots are connected at least with neighbor-toneighbor communication (3) a distributed approach to form a near-optimal network with at most two times the minimum number of modules (2-OPT) to activate their devices for HCS. We show that the convergence time on a balanced configuration is of a factor t, O( 2 t ), where n and t are the number of modules and terminal modules respectively, but it remains O(n) for the total number of activation and deactivation of devices for HCS. In simulation, we also show the improvement of convergence time as r increases.
Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error

Abstract We developed a global, 30-m resolution dataset of percent tree cover by rescaling the 250-m MOderate-resolution Imaging Spectroradiometer (MODIS) Vegetation Continuous Fields (VCF) Tree Cover layer using circa- 2000 and 2005 Landsat images, incorporating the MODIS Cropland Layer to improve accuracy in agricultural areas. Resulting Landsat-based estimates maintained consistency with the MODIS VCF in both epochs (RMSE =8.6% in 2000 and 11.9% in 2005), but showed improved accuracy in agricultural areas and increased discrimination of small forest patches. Against lidar measurements, the Landsat-based estimates exhibited accuracy slightly less than that of the MODIS VCF (RMSE=16.8% for MODIS-based vs. 17.4% for Landsat-based estimates), but RMSE of Landsat estimates was 3.3 percentage points lower than that of the MODIS data in an agricultural region. The Landsat data retained the saturation artifact of the MODIS VCF at greater than or equal to 80% tree cover but showed greater potential for removal of errors through calibration to lidar, with post-calibration RMSE of 9.4% compared to 13.5% in MODIS estimates. Provided for free download at the Global Land Cover Facility (GLCF) website (www.landcover.org), the 30-m resolution GLCF tree cover dataset is the highest-resolution multi-temporal depiction of Earth's tree cover available to the Earth science community.
Self-powered adaptive circuit sampling for a piezoelectric harvester

This paper proposes a low-cost true self-powered start-up and control circuitry for an envisaged system based on commercial vibration energy harvesting sources, that is oriented to structural health monitoring (SHM) applications. The proposed circuitry is quite simple and assures a battery less system just working with piezoelectrical generators. This architecture works looking for the maximum mechanical to electrical efficiency conversion, thanks to a continuous check of the open-load voltage at the piezoelectric generator, disconnecting it from the electronic circuitry, defining a true adaptive control unit. Also it is addressed the cold-start of the system. Initial experimental results are provided to verify its performance.
Mobile robot 6D pose estimation using a wireless localization network

Global navigation satellite systems (GNSS) are widely used for localization on Earth, but are not available on other planets, so that robotic planetary exploration missions need to use alternative methods for localization. This paper presents a wireless localization network (WLN) for estimating the 3D position and 3D orientation of a mobile robot. It consists of at least one reference 24 GHz radar node with known pose, and a mobile node on the robot. The reference nodes can determine the distance and both spatial angles to the mobile robot (thus locating it in 3D) using round-trip time of flight measurements and digital beamforming. We use an extended Kalman filter (EKF) to fuse these results with the readings from the mobile node, and an inclinometer to determine the complete 6D pose of the mobile robot. Measurements in a realistic scenario prove the feasibility of the proposed concept.
Towards coupled data assimilation : coupled covariance structures

CSIRO and the Bureau of Meteorology advise that the information contained in this publication comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO and the Bureau of Meteorology (including each of its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it. CAWCR Research Letters is an internal serial online publication aimed at communication of research carried out within CAWCR. It follows on from its predecessor BMRC Research Letters. Articles in CAWCR Research Letters are peer reviewed. For more information visit the CAWCR website.
Cyclic Stretch Enhances the Expression and Activity of Coronary Endothelium-Derived Hyperpolarizing Factor Synthase

Endothelium-derived hyperpolarizing factor (EDHF) mediates NO/prostacyclin-independent relaxation in the coronary circulation. Because hemodynamic stimuli modulate endothelial gene expression and because coronary arteries are subjected to pronounced variations in vessel distension, we determined the effects of cyclic stretch on the expression and activity of the coronary EDHF synthase/cytochrome P450 (CYP) 2C8/9. In cultured porcine coronary and human umbilical vein endothelial cells, acute application of cyclic stretch (6%, 1 Hz, 10 minutes) elicited the generation of 8,9-epoxyeicosatrienoic acid (EET), 11,12-EET, and 14,15-EET. Prolonged stretch (4 to 36 hours) increased the expression of CYP 2C mRNA and protein 5- to 10-fold and was accompanied by a 4- to 8-fold increase in EET generation. A corresponding increase in CYP 2C mRNA and protein was also observed in pressurized segments of porcine coronary artery perfused under pulsatile conditions (8%, 1 Hz) for 6 hours. Although in cultured endothelial cells, cyclic stretch elicited the rapid activation of tyrosine kinases as well as Akt and the p38 mitogen-activated protein kinase, the mechanism by which cyclic stretch induces the expression of CYP 2C could not be elucidated, because inhibitors of these pathways induced CYP 2C expression in cells maintained under static conditions. These results have identified coronary EDHF synthase/CYP 2C as a novel mechanosensitive gene product in native and cultured endothelial cells. Because this enzyme generates both EETs and superoxide anions, this finding has wide-reaching implications for vascular homeostasis in conditions of manifest endothelial dysfunction.
A new kernel function to extract non linear interval type features using symbolic kernel Fisher discriminant method with application to face recognition

In this paper we propose to use a new RBF kernel function to extract non linear interval type features using symbolic kernel Fisher discriminant analysis (symbolic KFD) for face recognition. The kernel based methods are a powerful paradigm; they are not favorable to deal with the challenge of large datasets of faces. We propose to scale up training task based on the interval data concept. Our investigation aims at extending kernel Fisher discriminant analysis (KFD) to interval data using new RBF kernel function. We adapt the symbolic KFD to extract interval type non linear discriminating features, which are robust due to varying facial expression, view point and illumination. In the classification phase, we employed Euclidean distance with minimum distance classifier. The new algorithm has been successfully tested using three databases, namely, ORL database, Yale Face database and Yale Face database B. The experimental results show that symbolic KFD with new RBF kernel function outperforms other discriminant analysis based algorithms.
A versatile path planning algorithm with behavioural control using FPGA based robots

The versatile solution to path planning of multi robots for industrial based services are presented in this paper. The authors are motivated to solve the challenges of multi robots path planning issues. The hardware based amenable algorithm for optimal path planning of multi robot with behavioural control is developed. The heuristic approach based leader follower method is incorporated between robots for behavioural control. The robots were able to navigate in both static and dynamic conditions by using the modified M* based obstacle avoidance mechanism with CORDIC module. This is validated by implementation of algorithm on Spartan 6 FPGAs (XC6SLX45 CSG324C).
Ubicomp'13 sencity workshop: sensing festivals as cities

In order to sense the mood of a city, we propose first looking at festivals. In festivals such as Glastonbury or Burning Man we see temporary cities where the inhabitants are engaged afresh with their environment and each other. Our position is that not only are there direct equivalences between larger festivals and cities, but in festivals the phenomena are often exaggerated, and the driving impulses often exploratory. These characteristics well suit research into sensing and intervening in the urban experience. To this end, we have built a corpus of sensor and social media data around a 18,000 attendee music festival and are developing ways of analysing and communicating it.
The Hα Luminosity Function and Star Formation Rate at z ~ 0.2

We have measured the Hα + [N II] fluxes of the I-selected Canada-France Redshift Survey (CFRS) galaxies lying at a redshift z below 0.3 and hence derived the Hα luminosity function. The magnitude limits of the CFRS mean that only the galaxies with MB ≳ -21 mag were observed at these redshifts. We obtained a total Hα luminosity density of at least 1039.44±0.04 ergs s-1 Mpc-3 at a mean z = 0.2 for galaxies with rest-frame EW(Hα + [N II]) ≳ 10 Å. This is twice the value found in the local universe by Gallego et al. Our Hα star formation rate, derived from Madau, is higher than the UV observations at the same z, implying a UV dust extinction of ~1 mag. We found a strong correlation between the Hα luminosity and the absolute magnitude in the B band: M(BAB) = 46.7 - 1.6 log L(Hα). This work will serve as a basis of future studies of Hα luminosity distributions measured from optically selected spectroscopic surveys of the distant universe, and it will provide a better understanding of the physical processes responsible for the observed galaxy evolution.
Big Data Analytics on Aviation Social Media: The Case of China Southern Airlines on Sina Weibo

This study proposes a passenger value model based on a social media platform. Using the case of China Southern Airlines on Sina Weibo, this study illustrates how big social data analysis can help an airline company to understand better the passengers and improve customer relationship management. The objectives of this study are threefold: (1) developing a model of passengers' social media value, (2) discussing the possible application scenarios for the proposed model, (3) using sentiment analysis to study the case of China Southern Airlines on Sina Weibo, and illustrating Weibo users' attitudes toward China Southern Airlines. This study also discusses the practical implications for airlines to manage their social media platforms. With the combination of a passenger's social media value and passenger's other offline behavior information, we can establish a comprehensive profile for travelers.
Someato : characterizing and exploiting behavior and interests of users in social media ∗

Characterizing and understanding behavior and interests of social media members is crucial for enhancing several practical applications in this environment, such as target marketing or recommendation. Aiming to characterize and exploit such behavior and interests, this work proposes Someato, a novel online analytics tool. Besides a characterization methodology, Someato comprises a search and a recommender system. Its main goal is to discover information and people that each member potentially wants to find within a social media. A preliminary usage on a real social community evinces Someato’s analytics capability and intuitive scientific visualization over log data from social media.
Joint distribution and steerable filter based fast local feature description algorithm

We propose a new fast local feature description Algorithm, which called Multi-Resolution Wavelet Transform Descriptor (MRWD), in order to decrease the disadvantages of the scale invariant feature transform(SIFT), e.g. instable to illumination, slow speed and high dimensions ect. Firstly, we establish the joint distribution of normalized pixels' intensity and distance to eliminate the impact of lighting transform. Then, we achieved a steerable filter using the multi-scale feature of Haar wavelet, to reduce the computational complexity and dimension. Finally, generate the MRWD descriptor. The algorithm not only reduces the instability caused by illumination change, but also maintains a good robustness on the scale and rotation transform compared to the traditional distribution based local feature description algorithm. Meanwhile, MRWD is faster than SIFT in computational speed, and reduces the dimensions
Ending Global Poverty: A Guide to What Works

Extreme Poverty: The Cruelest Trap * Poverty Traps and the Experience of the Poor * The Keys to Capability: Eight Keys to Escaping Poverty Traps * Escaping the Cruel Trap of Poverty: How the Poor Can Gain the Keys to Capability * Health, Nutrition, and Population * Basic Education * Credit for Poverty Reduction, and Insuring Opportunity * Bottom Up Market Development: Assets and Access for the Poor * Entitlement to New Technologies and the Capability to Benefit from them* Sustaining the Environment for Ending Poverty * Social Inclusion and Human Rights for the Poor and Voiceless * Community Empowerment and Development * Innovations in Poverty Strategy * What You Can Do to Help * First Steps * Further Questions * Stepping Up * What Businesses Can Do * Some Closing Words: An End to Global Poverty