Miracle-dz/UniFAR-FTUs huggingface dataset:
Demasking the impact of microfinance

We reconsider data from a randomized control trial study in India. The data reveal the impact of a microloan program. We extend the often used randomized impact evaluation and di¤erence-in-di¤erence approach by quantile regression and the consideration of the quantile treatment effects. The use of additional, more advanced, evaluation methods allows a more detailed consideration of borrowers at the lower and at the upper end of the wealth distribution. We find a strong negative and signi.cant time-trend. Furthermore, we observe a negative impact of the provi- sion of microfinance loans such that the overall impact is even more negative. This is particularly well seen for entrepreneurs in the lower and in the higher quantiles. As we learn that poor entrepreneurs use microloans for consumption, we doubt that micro.nance is the right instrument for them. The data suggest that providing microloans for average entrepreneurs, who can hire very poor entrepreneurs, might be an effective solution for that dilemma.
Measuring Distributional Effects of Fiscal Reforms

The purpose of this paper is to provide an overview of how to analyse the distributional effects of fiscal reforms. Thereby, distributional effects shall be differentiated by four subconcepts, i.e. 1. ) the traditional concept of inequality, 2. ) the rather novel concept of polarisation, 3. ) the concept of progression in taxation, and 4. ) the concepts of income poverty and richness. The concept of inequality and the concept of income poverty are the by far most widely applied concepts in empirical analyses, probably since they appear to be the most transparent ones in their structure as well as the most controversial ones in political affairs. However, the concepts of richness, polarisation and progression in taxation shall additionally be subject of this analysis, since they appear to be useful devices on the course of analysing cause and effect of the other two concepts.
Hidden Markov Model for Emotion Detection in Speech

This paper seeks to classify speech inputs into emotion labels. Emotions are key to effective communication and their accurate detection in speech gives way to numerous applications that improve human computer interaction, leading to advancements in various other fields. In order to achieve this, a Gaussian Hidden Markov Model (HMM) is used, to take into account the temporal nature of the speech signals. A Gradient boosting machine using decision trees approach has also been tried and has shown to have achieved a high accuracy of 84.4%. The ”Emotional Prosody Speech database”, which consists of ”acted” speech samples was used for training.
Hong Kong Monsoon , Orography , and Human Influence on Asian Rainfall

Ocean’s role in the seasonal monsoon rainfall over the Asian continent is revealed using recent high-resolution spacebased data. The balance of continental rainfall with moisture advected from the ocean is discussed. Temporal variation of rainfall in China and Indochina was found to be in phase and agree approximately in magnitude with moisture advection from the Indian Ocean but out of phase with those from the Pacific. During the onset of summer monsoon, moisture advected out of Indian into the Bay of Bengal occurs earlier than the moisture advected into the subcontinent from the Arabian Sea. Geographic distribution of rain is found to be governed by local orography, and narrow mountains anchor local rain and convection. Possible effect of orographic rain by urban pollution is suggested.
Improving Congestion Window Growth in Large Bandwidth Delay Product Networks

TCP performance degrades significantly when used over networks with a large bandwidth delay product. This is primarily due to the exponential and linear congestion window growth algorithms employed by Jacobson based TCP variants. In this paper we present a logarithmic window growth algorithm that is based on bandwidth estimation, allowing it to perform well regardless of the network bandwidth delay product. Implementation details are presented for this algorithm, along with results achieved via simulation.
Type-2 Fuzzy Cerebellar Model Articulation Controller-Based Learning Rate Adjustment for Blind Source Separation

Blind source separation (BSS) is a technique for recovering a set of source signals without a priori information on the transformation matrix or the probability distributions of source signals. Based on separation results of outputs, this paper proposes the interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC)-based learning rate adjustment for the BSS. The adopted T2FCMAC system has the ability of generating the proper learning rate by using the inputs of second- and higher order correlation coefficients of output components. In addition, to enhance the performance of the T2FCMAC-based learning rate approach, the T2FCMAC system is optimized by particle swarm optimization (PSO) algorithm by the performance index of second-order correlation measure. Simulation and comparison results are introduced to show the effectiveness and performance of the proposed approach.
Fast antenna characterization via a sparse spherical multipole expansion

Reliable spherical antenna characterization at high frequencies requires a considerable amount of time and often leads to the inefficient use of measurement facilities. The proposed method cuts the number of necessary samples for spherical antenna scans by 75% as compared to standard techniques, thus enabling significantly faster scan times without significant loss of accuracy. This is achieved by enforcing sparsity in the spherical multipole expansion through suitable translation and rotation operators. In this context, a novel and accurate method for phase center estimation is established which relies on a 1-norm minimization. Further, an iterative reconstruction algorithm is introduced which allows for reconstruction of undersampled measurement data in a successively optimized coordinate system. Validation using both synthetic and real measurement data demonstrates the capabilities of the proposed method.
Watermarking protocol for protecting user's right in content based image retrieval

Content based image retrieval (CBIR) is a technique to search for images relevant to the user's query from an image collection. In last decade, most attention has been paid to improve the retrieval performance. However, there is no significant effort to investigate the security concerning in CBIR. Under the query by example (QBE) paradigm, the user supplies an image as a query and the system returns a set of retrieved results. If the query image includes user's private information, an untrusted server provider of CBIR may distribute it illegally, which leads to the user's right problem. In this paper, we propose an interactive watermarking protocol to address this problem. A watermark is inserted into the query image by the user in encrypted domain without knowing the exact content. The server provider of CBIR will get the watermarked query image and uses it to perform image retrieval. In case where the user finds an unauthorized copy, a watermark in the unauthorized copy will be used as evidence to prove that the user's legal right is infringed by the server provider.
Genomic Selection Using Low-Density Marker Panels

Genomic selection (GS) using high-density single-nucleotide polymorphisms (SNPs) is promising to improve response to selection in populations that are under artificial selection. High-density SNP genotyping of all selection candidates each generation, however, may not be cost effective. Smaller panels with SNPs that show strong associations with phenotype can be used, but this may require separate SNPs for each trait and each population. As an alternative, we propose to use a panel of evenly spaced low-density SNPs across the genome to estimate genome-assisted breeding values of selection candidates in pedigreed populations. The principle of this approach is to utilize cosegregation information from low-density SNPs to track effects of high-density SNP alleles within families. Simulations were used to analyze the loss of accuracy of estimated breeding values from using evenly spaced and selected SNP panels compared to using all high-density SNPs in a Bayesian analysis. Forward stepwise selection and a Bayesian approach were used to select SNPs. Loss of accuracy was nearly independent of the number of simulated quantitative trait loci (QTL) with evenly spaced SNPs, but increased with number of QTL for the selected SNP panels. Loss of accuracy with evenly spaced SNPs increased steadily over generations but was constant when the smaller number individuals that are selected for breeding each generation were also genotyped using the high-density SNP panel. With equal numbers of low-density SNPs, panels with SNPs selected on the basis of the Bayesian approach had the smallest loss in accuracy for a single trait, but a panel with evenly spaced SNPs at 10 cM was only slightly worse, whereas a panel with SNPs selected by forward stepwise selection was inferior. Panels with evenly spaced SNPs can, however, be used across traits and populations and their performance is independent of the number of QTL affecting the trait and of the methods used to estimate effects in the training data and are, therefore, preferred for broad applications in pedigreed populations under artificial selection.
Exhaustive scanning approach to screen all the mitochondrial tRNA genes for mutations and its application to the investigation of 35 independent patients with mitochondrial disorders.

To gain a better understanding of the molecular basisof mitochondrial (mt) encephalomyopathies, a highly heterogeneous condition, we developed a denaturing gradient gel electrophoresis-based approach that allows rapid and exhaustive screening for mutations of all 22 mt tRNA-encoding genes and their flanking regions in large cohorts of patients. This method, that detects heteroplasmy (i.e. co-existence of mutant and wild-type mtDNA species in various ratios) directly, was applied to the investigation of 35 independent patients with a disease phenotype compatible with a mitochondrial encephalomyopathy. Twenty-five of the 35 patients investigated displayed a sequence variation in at least one tRNA gene. A total of 46 different sequence variations (41 point mutations, four short insertions and one short deletion), among which 20 are new, were characterized. Forty of them were present in a homoplasmic state, whereas six were heteroplasmic. Twenty-two were located in tRNA genes, among which 10 are new homoplasmic or heteroplasmic sequence variations; 24 were located in flanking regions (12 in mRNA-encoding genes, seven of them leading to missense sequence variations; two in rRNA genes; and 10 in non-coding regions). This study demonstrates (i) the high frequency of homoplasmic tRNA gene sequence variations in our patient sample, and (ii) the existence of several polymorphic sites in tRNA gene regions that may be helpful for defining haplogroups in different populations. It relies on a screening method that can now be applied easily to other population samples.
A Semantic Similarity Measure between Nouns based on the Structure of Wordnet

Several approaches for computing semantic similarity and relatedness measures between terms have been developed. This paper proposes a new semantic similarity measure between two nodes concentrating on nouns as well as their hypernym/hyponym relationships based on the structure of Wordnet. In particular, the similarity of two given nouns depends not only on their positions but also on their relevancy connections in the hierarchy. We evaluate our measure and the other ones on dataset of Miller-Charles and then compute the correlation coefficients to the human judgments. The experimental results show that our method outperforms edge-counting methods.
Stroke-Based Chinese Character Completion

In this paper, we propose a method for completing the Chinese character in the image of Inscription rubbings or Chinese calligraphy that is corrupted by fissure and dirt. The method aim at completing the Chinese character from single image based only on the information the image contains. In our approach, for completing the corrupted image with Chinese characters, the structure of the Chinese characters is analyzed firstly using a modified stroke extraction method. All the contours of undamaged Chinese characters in the image are extracted and decomposed into a plausible set of strokes for reducing the problems by the strokes crossing or touching. Then, the structure of the characters in the missing regions is recovered by finding the similarity characters or similarity strokes though a partial contour matching method. Finally, we complete the image use the method with structure propagation, but the curves are not specified by user and are the contour of damaged characters we have recovered.
High density oligonucleotide array analysis of interferon-α2a sensitivity and transcriptional response in melanoma cells

Interferon alpha (IFN-α) represents an adjuvant therapy of proven effectiveness in increasing disease-free interval and survival in subgroups of melanoma patients. Since high doses of cytokine are required, the treatment is often accompanied by toxic side effects. Furthermore, naturally occurring insensitivity to IFN-α may hamper its therapeutic efficacy. Clinical, molecular or immunological markers enabling the selection of potential responders have not been identified so far. To explore the molecular basis of IFN-α responsiveness, we analysed the expression pattern of about 7000 genes in IFN-α sensitive and resistant cell lines and we compared the transcription profiles of cells cultured in the presence or absence of the cytokine using high-density oligonucleotide arrays. Melanoma cell lines were screened for their sensitivity to proliferation inhibition and HLA class I induction upon IFN-α treatment by standard 3H-thymidine incorporation and flow-cytometry. The study of 4 sensitive and 2 resistant cell lines allowed the identification of 4 genes (RCC1, IFI16, hox2 and h19) preferentially transcribed in sensitive cells and 2 (SHB and PKC-ζ) preferentially expressed in resistant cells. IFN-α stimulation resulted in the expression of a panel of 19 known inducible genes in sensitive but not in resistant cells. Moreover a group of 30 novel IFN-α inducible genes was identified. These data may provide a useful basis to develop diagnostic tools to select potential IFN-α responders eligible for treatment, while avoiding unnecessary toxicity to non-responders. Furthermore, by extending the knowledge of the polymorphic effects of IFN-α on gene expression, they offer novel clues to the study of its pleiotropic toxicity. © 2001 Cancer Research Campaign http://www.bjcancer. com
On Timing and Frequency Offset Estimation for OFDM Systems

A new training symbol weighted by the PN sequence was designed and an efficient timing and frequency offset estimation scheme for orthogonal frequency division multiplexing systems was proposed. The timing synchronization is accomplished by using the piecewise symmetric conjugate of the primitive training symbol and the good autocorrelation of the PN weighted factor. After the time synchronization is finished, the PN weighted factor is removed and the renewed training symbol is used to estimate the frequency offset. Compared with conventional schemes, the proposed scheme can achieve a significantly smaller mean square error and provide a wider frequency acquisition range.
Constrained One-Bit Transform for Low Complexity Block Motion Estimation

One-bit transform (1BT)- and two-bit transform (2BT)-based block motion estimation (ME) schemes have been proposed in the literature to reduce the computational complexity of the ME process by enabling simple Boolean ex-or matching of lower bit depth representations of image frames. Recently a multiplication-free 1BT (MF-1BT) has been proposed to facilitate 1BT to be carried out with integer arithmetic using addition and shifts only. Thresholding schemes are typically used in order to construct the lower bit depth representations utilized in 1BT and 2BT. In our experience we have observed that one problem with such schemes is that pixel values that lie on directly opposite sides of the threshold are categorized into separate classes and are, therefore, counted as a nonmatch in the search process even if they are close in value. A constrained 1BT (C-1BT) that restricts pixels with values adjacent to the transform threshold during 1BT matching, counting them as a match regardless of their 1BT value, is proposed in this paper. It is shown that the proposed C-1BT approach improves the ME accuracy of 1BT-based ME and even outperforms 2BT-based ME at macroblock level
Hierarchical Error Diffusion

This paper develops a distinctive class of color error diffusion algorithm, called hierarchical error diffusion (HED). It aims to achieve perceptually pleasing color halftone through neither conventional joint quantization nor interchannel error diffusion. Instead, it explicitly controls three critical factors sequentially to yield high-quality color halftone: dot-overlapping control, dot-positioning control, and dot-coloring control. A specific implementation of HED is presented with the objective of minimum brightness variation rendering (MBVR). First, an optimal color transform is derived for dot-overlapping control to achieve minimum brightness variation color density (MBVCD). Then, the embedded monochrome error diffusion is employed in dot-positioning control. By sequentially thresholding the elements in partial density sum vector, better dot-positioning is encouraged for more visible color dots. The ldquoblue noiserdquo characteristics of dot-positioning from the monochrome error diffusion are inherited by the color halftone. The simple density priority strategy is applied in dot-coloring control. The pixel color error is diffused channel-independently with a single error filter in halftone dot color space. A comparison with the state-of-the-art color error diffusion algorithms demonstrates excellent halftone quality of HED, while without the typical artifacts of vector error diffusion. Evidence also shows that HED is closer to achieve MBVR than the minimum brightness variation quantization (MBVQ) color diffusion algorithm proposed in.
Concepts, methods and techniques in adaptive control

This tutorial paper looks back at almost 50 years of adaptive control trying to establish how much more we need to be able to offer the industrial community an adaptive controller which will be used and referred to with the same ease as existing PID controllers. Since the first commercial adaptive controller, significant progress in the design and analysis of these controllers has been achieved. Various forms of adaptive controllers are now readily available targeting a significant range of industries from process to aerospace. A general overview of adaptive control will allow the reader to place on the map several industrial architectures for such controllers, all with the aim of bridging the gap between academic and industrial views of the topic. Such a presentation of design and analysis tools currently opens a more philosophical question "Has the critical mass in adaptive control been reached? ".
Design and impedance estimation of a biologically inspired flexible mechanical transmission with exponential elastic characteristic

Nonlinear elasticity of transmission is indispensable in any passively variable stiffness mechanism. However, it remains obscure how to decide a desired nonlinear force-displacement function. On the other hand biological muscular actions are associated with stiffness/impedance variation in a wide range as demanded by everyday tasks. This paper addresses the issue of designing a nonlinear elastic transmission, where the elastic behaviour is obtained from the passive properties of biological muscle, which happens to be an exponential one, leading to existence of linearity between stiffness and force. In general, with passive damping, the transmission behaves as a mechanical impedance element, to be used in variable impedance actuation. Knowledge of the varying impedance is required to operate the transmission reliably. An off-line calibrated model can only be approximate and erroneous with noisy sensors and changing characteristics of the passive elements with time and environmental condition. This article implements an Extended Kalman Filter algorithm for on-line estimation of stiffness and impedance of such a damped series-elastic transmission. The underlined principle in stiffness-force affine relation is exploited favourably in stiffness estimation with reduced complexity. The effectiveness of the proposed estimator is examined through experiments on the mechanical transmission designed using the biological principle.
Nucleotidyl transferase assisted DNA labeling with different click chemistries

Here, we present a simple, modular and efficient strategy that allows the 3′-terminal labeling of DNA, regardless of whether it has been chemically or enzymatically synthesized or isolated from natural sources. We first incorporate a range of modified nucleotides at the 3′-terminus, using terminal deoxynucleotidyl transferase. In the second step, we convert the incorporated nucleotides, using either of four highly efficient click chemistry-type reactions, namely copper-catalyzed azide-alkyne cycloaddition, strain-promoted azide-alkyne cycloaddition, Staudinger ligation or Diels-Alder reaction with inverse electron demand. Moreover, we create internal modifications, making use of either ligation or primer extension, after the nucleotidyl transferase step, prior to the click reaction. We further study the influence of linker variants on the reactivity of azides in different click reactions. We find that different click reactions exhibit distinct substrate preferences, a fact that is often overlooked, but should be considered when labeling oligonucleotides or other biomolecules with click chemistry. Finally, our findings allowed us to extend our previously published RNA labeling strategy to the use of a different copper-free click chemistry, namely the Staudinger ligation.