Miracle-dz/UniFAR-FTUs huggingface dataset:
Poverty and Wellbeing Impacts of Microfinance: What Do We Know?

Over the last 35 years, microfinance has been generally regarded as an effective policy tool in the fight against poverty. Yet, the question of whether access to credit leads to poverty reduction and improved wellbeing remains open. To address this question, we conduct a systematic review of the quantitative literature of microfinance’s impacts in the developing world, and develop a theory of change that links inputs to impacts on several welfare outcomes. Overall, we find that the limited comparability of outcomes and the heterogeneity of microfinance-lending technologies, together with a considerable variation in socio-economic conditions and contexts in which impact studies have been conducted, render the interpretation and generalization of findings intricate. Our results indicate that, at best, microfinance induces short-term dynamism in the financial life of the poor; however, we do not find compelling evidence that this dynamism leads to increases in income, consumption, human capital and assets, and, ultimately, a reduction in poverty
View-based 3D object recognition using wavelet multiscale singular-value decomposition and support vector machine

In this paper, a novel view-based 3D object recognition method is proposed, which consists of three steps. First, employing wavelet transform to decompose view images of the object into different frequency sub-images. Second, for each sub-image, the features are extracted using singular-value decomposition (SVD) approach, and the features extracted from sub-images are combined to construct the feature vector of the original image. Third, the feature vector is fed into the support vector machine (SVM) to classify the objects. Experimental results show that the proposed method is effective.
DecentralizedDataFusionwith InverseCovariance Intersection

In distributed and decentralized state estimation systems, fusion methods are employed to systematically combine multiple estimates of the state into a single, more accurate estimate. An often encountered problem in the fusion process relates to unknown common information that is shared by the estimates to be fused and is responsible for correlations. If the correlation structure is unknown to the fusion method, conservative strategies are typically pursued. As such, the parameterization introduced by the ellipsoidal intersection method has been a novel approach to describe unknown correlations, though suitable values for these parameters with proven consistency have not been identified yet. In this article, an extension of ellipsoidal intersection is proposed that guarantees consistent fusion results in the presence of unknown common information. The bound used by the novel approach corresponds to computing an outer ellipsoidal bound on the intersection of inverse covariance ellipsoids. As a major advantage of this inverse covariance intersection method, fusion results prove to be more accurate than those provided by the well-known covariance intersection method.
An edge based image steganography with compression and encryption

Security of secret data has been a major issue of concern from ancient time. Steganography and cryptography are the two techniques which are used to reduce the security threat. Cryptography is an art of converting secret message in other than human readable form. Steganography is an art of hiding the existence of secret message. These techniques are required to protect the data theft over rapidly growing network. To achieve this there is a need of such a system which is very less susceptible to human visual system. In this paper a new technique is going to be introducing for data transmission over an unsecure channel. In this paper secret data is compressed first using LZW algorithm before embedding it behind any cover media. Data is compressed to reduce its size. After compression data encryption is performed to increase the security. Encryption is performed with the help of a key which make it difficult to get the secret message even if the existence of the secret message is reveled. Now the edge of secret message is detected by using canny edge detector and then embedded secret data is stored there with the help of a hash function. Proposed technique is implemented in MATLAB and key strength of this project is its huge data hiding capacity and least distortion in Stego image. This technique is applied over various images and the results show least distortion in altered image.
An incentive mechanism for Peer-to-Peer video streaming

Increase in the number of audiences interested in watching live events through the internet has become a challenge for traditional client-server approaches. In fact, supporting manifold audiences requires that broadcasters allocate more bandwidth. P2P networks for live streaming allow the users to support video dissemination by contributing their resources. Consequently, P2P networks are effective and scalable alternative for video streaming in the network. Since the performance of a P2P streaming system is dependent on the contribution of the group members, free riding is one of the main challenges of such systems. Free riders are some selfish peers that do not upload any data to other peers while downloading from the network. Therefore, designing incentive mechanisms for P2P streaming systems is essential. In this paper we designed and proposed an incentive mechanism for mesh based P2P video streaming. The proposed approach includes two parts. In the first part, the contribution of the peers in the network is measured and maintained in a distributed fashion, and in the second part, differentiated service is provided for the peers based on their contribution. We simulated the proposed approach and the results show the efficiency of the proposed mechanism in improving the overall quality of the perceived video in the group.
Hardware-Supported Transactional Memory

In this report, we describe a number of Hardware Transactional Memory (HTM) designs and their basic mechanisms used for better programmability and higher performance than conventional synchronization techniques based on locking. We compare the systems considering their programming model, hardware design challenges, transactional dataset constraints and forward progress guarantees. As high-speed networks emerge for the rack-scale systems [1], CPUs become a bottleneck and researchers start investigating optimistic concurrency control mechanisms to optimize different phases of the comprehensive distributed commit protocols [2]. To achieve high performance while maintaining strong data consistency in the system, we propose to leverage HTM design ideas to provide more efficient non-blocking operations on data objects stored in memory of different servers in a rack. Keywords—architecture support, hardware transactional memory, synchronization
Heteromultimeric TRPC 6-TRPC 7 Channels Contribute to Arginine Vasopressin-Induced Cation Current of A 7 r 5 Vascular Smooth Muscle Cells

The molecular identity of receptor-operated, nonselective cation channels (ROCs) of vascular smooth muscle (VSM) cells is not known for certain. Mammalian homologues of the Drosophila canonical transient receptor potential channels (TRPCs) are possible candidates. This study tested the hypothesis that heteromultimeric TRPC channels contribute to ROC current of A7r5 VSM cells activated by [Arg]-vasopressin. A7r5 cells expressed transcripts encoding TRPC1, TRPC4 , TRPC6, and TRPC7. TRPC4, TRPC6, and TRPC7 protein expression was confirmed by immunoblotting and association of TRPC6 with TRPC7, but not TRPC4 , was detected by coimmunoprecipitation. The amplitude of arginine vasopressin (AVP)-induced ROC current was suppressed by dominant-negative mutant TRPC6 (TRPC6) but not TRPC5 (TRPC5) mutant subunit expression. These data indicate a role for TRPC6and/or TRPC7-containing channels and rule a more complex subunit composition including TRPC1 and TRPC4. Increasing extracellular Ca concentration ([Ca ]o) from 0.05 to 1 mmol/L suppressed currents owing to native, TRPC7, and heteromultimeric TRPC6-TRPC7 channels, but not TRPC6 current, which was slightly enhanced. The relative changes in native and heteromultimeric TRPC6-TRPC7 current amplitudes for [Ca ]o between 0.01 and 1 mmol/L were identical, but the changes in homomultimeric TRPC6 and TRPC7 currents were significantly less and greater, respectively, compared with the native channels. Taken together, the data provide biochemical and functional evidence supporting the view that heteromultimeric TRPC6-TRPC7 channels contribute to receptor-activated, nonselective cation channels of A7r5 VSM cells. (Circ Res. 2006;98:1520-1527.)
Build fast, trade fast: FPGA-based high-frequency trading using high-level synthesis

High-Frequency Trading (HFT) systems require extremely low latency in response to market updates. This motivates the use of Field-Programmable Gate Arrays (FPGAs) to accelerate different system components such as the network stack, financial protocol parsing, order book handling and even custom trading algorithms. However, the long cycle of developing and verifying FPGA designs makes it challenging for HFT software developers to deploy such highly-dynamic systems, especially with their limited hardware design expertise. We present a complete highly-optimized infrastructure that implements low-latency system components in C++ using High-Level Synthesis (HLS). We also develop a framework that enables HFT algorithm developers to implement their trading algorithms in a high-level programming language and rapidly integrate it to the rest of the system. We implemented our HLS-based system on a Xilinx Kintex Ultrascale FPGA running at 156 MHz. Our on-board measurements show an end-to-end round-trip latency less than 870ns, which is comparable to that achieved by prior RTL-based implementations but requires reduced system development time and effort.
A photographic method for drop characterization 1 in agricultural sprinklers 2 by 3

by 3 Salvador, R. , Bautista-Capetillo, C. , 4 Burguete, J., Zapata, N. , Serreta, A. Playán, E. 5 6 ABSTRACT 7 The characterization of drops resulting from impact sprinkler irrigation has been 8 addressed by a number of techniques. In this paper, a new technique based on low-speed 9 photography (1/100 s) is presented and validated. The technique permits to directly 10 measure drop diameter, velocity and angle. The photographic technique was applied to 11 the characterization of drops resulting from an isolated sprinkler equipped with a 12 4.8 mm nozzle and operating at a pressure of 200 kPa. Sprinkler performance was 13 characterized from photographs of 1,464 drops taken at distances ranging from 1.5 to 14 12.5 m. It was possible to analyze separately the drops emitted by the main jet and those 15 emitted by the impact arm. The proposed technique does not require specific equipment, 16 although it is labour intensive. 17 18 19
A study of isolation and identification of non -albicans Candida species from clinically suspected cases of vulvovaginitis

The list of opportunistic fungi causing serious life threatening infection increases every year, and without question the single most important cause of opportunistic mycoses worldwide remains Candida species. The candida species are yeastlike fungi, ubiquitous in nature and are the component of normal flora of human beings. Candidiasis is the most common fungal infection affecting man, caused by a member of the genus Candida. Infections due to Candida species have increased dramatically in recent years and are of particular importance because of the rising number of immunocompromised patients, as it causes opportunistic infections in them. Although Candida albicans remains the most common cause of human Candidiasis, the frequency of infection attributed to other members of the genus is increasing . This is primarily due to increase in number of atrisk individuals, particularly those with impaired immunity such as transplant ISSN: 2319-7706 Volume 3 Number 12 (2014) pp. 147-159 http://www.ijcmas. com
On the Performance Evaluation of Vehicular PKI Protocol for V2X Communications Security

Cooperative Intelligent Transportation Systems (CITS) is an ongoing technology that will change our driving experience in the near future. In such systems, vehicles and Road-Side Units (RSU) cooperate by broadcasting V2X messages over the vehicular network (802.11p). Safety applications use these data to detect dangerous situations on time and avoid them. The security of V2X communications is based on the use of a vehicular Public Key Infrastructure (PKI) that delivers digital certificates to vehicles and RSU. Vehicles frequently change their certificate in order to make tracking more difficult and thus preserve drivers privacy. In this paper, we evaluate the performance of our PKI regarding the reloading of certificates by comparing two communication profiles (with and without V2X security). We developed a Proofof- Concept (PoC) with real implementation of the PKI protocol and the embedded system. The obtained results show that the end-to-end latency between a requesting vehicle and the PKI is non-negligible. We then discuss and propose optimizations that can be done to improve the performance of the system.
Building Evaluation Datasets for Consumer-Oriented Information Retrieval

Common people often experience difficulties in accessing relevant, correct, accurate and understandable health information online. Developing search techniques that aid these information needs is challenging. In this paper we present the datasets created by CLEF eHealth Lab from 2013-2015 for evaluation of search solutions to support common people finding health information online. Specifically, the CLEF eHealth information retrieval (IR) task of this Lab has provided the research community with benchmarks for evaluating consumer-centered health information retrieval, thus fostering research and development aimed to address this challenging problem. Given consumer queries, the goal of the task is to retrieve relevant documents from the provided collection of web pages. The shared datasets provide a large health web crawl, queries representing people’s real world information needs, and relevance assessment judgements for the queries.
INPUT ACOUSTIC IMPEDANCE OF THE AUDITORY SYSTEM MEASUREMENTS

Measuring middle ear input impedance is of fundamental importance both from the point of view of the basic research and from the point of view of clinical diagnosis [1]. As regards the first aspect, characterization of the “input / output” middle ear’s amplification factor is crucial for deconvolving inside otoacoustic signals cochlear transfer function from that of the middle ear. From a clinical point of view, it is essential for a correct diagnosis to be able to separate trasmissive problems, linked to the middle ear, from that caused by cochlear pathologies. The measure of input impedance of the middle ear can be carried out using a probe consisting of a miniaturized microphone and loudspeaker inserted into the ear canal. The technique described in the literature [2] [4] consists in modeling the system probe + inner ear as a Thevenin equivalent circuit in which the characteristics impedance and Thevenin pressure of the probe have been characterized using a calibration system. The calibration, namely the characterization of the Thevenin parameters of the probe, is carried out using waveguides of known length whose impedance is derived by mathematical modeling as a function of the geometric parameters [3]. The solution of a least-squares problem allows to obtain the best fitting of the Thevenin parameters of the probe. The same measure of input impedance of the middle ear may also be effected by means of an intensimetric probe able to simultaneously measure pressure and velocity inside the ear canal. In this work measures of input impedance of the middle ear are made with both techniques described above. In particular, for the velocity measures was used a Microflown anemometer miniaturized probe. The measurements obtained by the two independent techniques were systematically compared finding a satisfactory agreement.
Uncovering Neuronal Networks Defined by Consistent Between-Neuron Spike Timing from Neuronal Spike Recordings

Abstract It is widely assumed that distributed neuronal networks are fundamental to the functioning of the brain. Consistent spike timing between neurons is thought to be one of the key principles for the formation of these networks. This can involve synchronous spiking or spiking with time delays, forming spike sequences when the order of spiking is consistent. Finding networks defined by their sequence of time-shifted spikes, denoted here as spike timing networks, is a tremendous challenge. As neurons can participate in multiple spike sequences at multiple between-spike time delays, the possible complexity of networks is prohibitively large. We present a novel approach that is capable of (1) extracting spike timing networks regardless of their sequence complexity, and (2) that describes their spiking sequences with high temporal precision. We achieve this by decomposing frequency-transformed neuronal spiking into separate networks, characterizing each network’s spike sequence by a time delay per neuron, forming a spike sequence timeline. These networks provide a detailed template for an investigation of the experimental relevance of their spike sequences. Using simulated spike timing networks, we show network extraction is robust to spiking noise, spike timing jitter, and partial occurrences of the involved spike sequences. Using rat multineuron recordings, we demonstrate the approach is capable of revealing real spike timing networks with sub-millisecond temporal precision. By uncovering spike timing networks, the prevalence, structure, and function of complex spike sequences can be investigated in greater detail, allowing us to gain a better understanding of their role in neuronal functioning.
Synthesis, Crystal Structure and Water Vapor Adsorption Properties of a Porous Supramolecular Architecture

A new complex, [Cu4(HL)4(H2O)14] (1, H3L·HCl = 5-((4-carboxypiperidin-1-yl)methyl)isophthalic acid hydrochloride), has been prepared and characterized by single-crystal X-ray diffraction, elemental analysis, IR spectroscopy and powder X-ray diffraction (PXRD). The result of the X-ray diffraction analysis reveals that the complex crystallizes in monoclinic, space group C2/c and three unique Cu(II) atoms that are connected by partially deprotonated HL2− anion to form a cyclic structure. The rich hydrogen bonding and π-π non-covalent packing interactions extend cyclic units into a three-dimensional (3D) supramolecular polymer. Moreover, the thermogravimetric (TG) analysis and water vapor adsorption property of 1 were also discussed.
Effect of radial anisotropy on plasmonic optical properties of coated nanorods

Plasmonic optical properties in pairs of coated nanorods in near-field are investigated by finite element method. The coated nanorod is composed of a radically anisotropic dielectric core and a metallic shell. Numerical simulations show that for a finite radial permittivity εr, with the increase of the tangential permittivity εt, the position of the near-field intensity peak shifts to long wavelength along with the decrease in the magnitude. On the other hand, with increasing εr, the position of the intensity peak exhibits long-wavelength shift significantly, while keeping the maximal magnitude for isotropic case. Furthermore, a compensating effect for the decay of the intensity with the incearse of the gap width can be achieved by manipulate the anisotropy of the dielectric core.
Convolutional neural network based chart image classification

Charts are frequently embedded objects in digital documents and are used to convey a clear analysis of research results or commercial data trends. These charts are created through different means and may be represented by a variety of patterns such as column charts, line charts and pie charts. Chart recognition is as important as text recognition to automatically comprehend the knowledge within digital document. Chart recognition consists on identifying the chart type and decoding its visual contents into computer understandable values. Previous work in chart image identiﬁcation has relied on hand crafted features which often fails when dealing with a large amount of data that could contain signiﬁcant varieties and less common char types. Hence, as a ﬁrst step towards this goal, in this paper we propose to use a deep learning-based approach that automates the feature extraction step. We present an improved version of the LeNet [LeCu 89] convolutional neural network architecture for chart image classiﬁcation. We derive 11 classes of visualization (Scatter Plot, Column Chart, etc.) which we use to annotate 3377 chart images. Results show the efﬁciency of our proposed method with 89.5 % of accuracy rate.
GWU English TAC-KBP EL Diagnostic Task with Name Mention

This paper describes the entity linking system participating in the 2015 Knowledge Base Population (KBP) track at the Text Analysis Conference (TAC) by GWU’s Natural Language Processing (NLP) group (Care4Lang) in collaboration with the NLP consulting company Luki Labs. Our proposed system uses a supervised modeling approach with a feature set that targets the overlapping information between the query and the candidate entities from the KB. In addition, it uses an unsupervised approach to cluster the mentions that don’t have a reference in the KB. It is a first participation for both teams and the attained results are promising and encouraging for further research.
Effects of hydration on thermal expansion of forsterite, wadsleyite, and ringwoodite at ambient pressure

Abstract Single-crystal X-ray diffraction has been used to measure the thermal expansion coefficients of forsterite, wadsleyite, ringwoodite, and their hydrous forms at ambient pressure, from temperatures as low as 133 K to as high as 919 K. Second-order polynomial fitting to ln(V/V0) vs. T was applied to derive the expansion coefficients in the form of α = a1 × T + a0. The single crystal of anhydrous wadsleyite persisted up to 859 K. Hydrous forsterite was observed to dehydrate at 919 K, whereas hydrous wadsleyite started to dehydrate at 655 K. The crystal of ringwoodite with 0.20 wt% broke down at 911 K, and the two ringwoodite samples with 0.74 and 2.4 wt% H2O, were observed to break down with an irreversible unit-cell expansion at 808 and 606 K, respectively. From room temperature to high temperatures in this study, the mean thermal volume expansion coefficients are 36.4(5) and 38.1(9) × 10-6 K-1, respectively, for anhydrous and hydrous forsterite; 28.5(5) and 35.8(8) × 10-6 K-1, respectively, for the anhydrous and hydrous wadsleyite; 30.6(9), 35.2(15), and 34.9(7) × 10-6 K-1 for the samples of ringwoodite with 0.2, 0.74, and 2.4 wt% H2O, respectively. Thus, forsterite, wadsleyite, and ringwoodite all have larger thermal expansion coefficients in their hydrous forms than in their anhydrous forms.
Processing Principles of Ionosphere Passive Monitoring Data

Modern technologies allow to carry out passive monitoring of the iono-sphere with the possibility to track changes in ionospheric parameters with a high sampling rate and inﬂuence of these parameters on quality of navigation and spatial positioning. With the growth of the sampling frequency the amount of data being processed also increases. The article deals with the principles that have been selected to handle the large amounts of passive monitoring ionospheric data and software solution, which was developed on the basis of these principles.