Miracle-dz/UniFAR-FTUs huggingface dataset:
Current Account Adjustments and I ntegration in West Africa

In this paper, we seek to understand three main issues: first, what are the longand short-run determinants of current account balances in West Africa; second, is there a sustainable path for the current account position that is consistent with regional integration; and if yes, what has been the process of adjustment towards such a path. We address these questions by first identifying the longterm determinants of the current account, and then using the results to calculate the equilibrium sustainable targets for the current account in the region. After accounting for short-run disequilibrium adjustment processes, we show how far apart each ECOWAS country is from the regionally sustainable path. The key findings are as follows: (i) the determinants of current account dynamics differ depending on the time horizon of analysis; (ii) the real exchange rate, fiscal policy, trade openness, investment, and income levels are the key determinants in the short run; (iii) there is considerable variation by country in the deviation of each countries' current account position from the regionally sustainable equilibrium path. Some implications for policy are highlighted. Rights and Permissions All rights reserved. The text and data in this publication may be reproduced as long as the source is cited. Reproduction for commercial purposes is forbidden. The WPS disseminates the findings of work in progress, preliminary research results, and development experience and lessons, to encourage the exchange of ideas and innovative thinking among researchers, development practitioners, policy makers, and donors. The findings, interpretations, and conclusions expressed in the Bank’s WPS are entirely those of the author(s) and do not necessarily represent the view of the African Development Bank Group, its Board of Directors, or the countries they represent. Working Papers are available online at https://www.afdb.org/en/documents/publications/working-paper-series/ Produced by Macroeconomics Policy, Forecasting, and Research Department Coordinator Adeleke O. Salami This paper is the product of the Vice-Presidency for Economic Governance and Knowledge Management. It is part of a larger effort by the African Development Bank to promote knowledge and learning, share ideas, provide open access to its research, and make a contribution to development policy. The papers featured in the Working Paper Series (WPS) are those considered to have a bearing on the mission of AfDB, its strategic objectives of Inclusive and Green Growth, and its High-5 priority areas—to Power Africa, Feed Africa, Industrialize Africa, Integrate Africa and Improve Living Conditions of Africans. The authors may be contacted at workingpaper@afdb.org. Correct citation: Chuku, C. , J. Atan, F. Obioesio, and K. Onye (2017), Current Account Adjustments and Integration in Africa, Working Paper Series N° 287, African Development Bank, Abidjan, Côte d’Ivoire. Current Account Adjustments and Integration in West Africa Chuku Chuku, Johnson Atan, Felix Obioesio, and Kenneth Onye JEL Codes: F32, F41, C33
Characterization of ethyl acetate and methanol extracts of Commiphora myrrha and evaluating in vitro anti-diabetic and anti-obesity activities

Diabetes mellitus is a clinical syndrome characterized by hyperglycemia. Reduction of gastrointestinal glucose absorption through the inhibition of carbohydrate digesting enzymes is one of in-vitro anti-diabetic therapeutic approach. This study aimed to evaluate the in-vitro anti-diabetic and anti-obesity activities of ethyl acetate and methanol extracts of Commiphora myrrha oleo-gum as well as identification of the bioactive compounds. Commiphora myrrha was extracted with methanol and ethyl acetate. The two extracts were used to evaluate their α-amylase, α-glucosidase and pancreatic lipase inhibitory activities. Identification of the bioactive compounds in ethyl acetate was analysed by GC-MS gas chromatograph. The results showed that the ethyl acetate extract had a stronger inhibitory activity on α-amylase (IC50=54.60Âµg/ml) and α-glucosidase (IC50=58.7Âµg/ml) than methanol extract on α-amylase (IC50=124.01Âµg/ml) and α-glucosidase (IC50= 191.2Âµg/ml). Also, ethyl acetate extract had a promising inhibitory effect on pancreatic lipase (IC50= 107.8Âµg/ml) than methanol extract (IC50= 498.1Âµg/ml). Gas chromatography - mass spectrometry analysis of the ethyl acetate extract identified 31 compounds. Among them nobiletin (50.26%), metaproterenol (orciprenaline) (14.99%), morantel (8.86%) and tricetin (3.38%) were the main compounds. These findings proved that Commiphora myrrha has anti-diabetic and anti-obesity inhibition activity may be due to the bioactive compounds with interesting medicinal properties.
Should Corporate Bond Trading Be Centralized?

This paper shows that centralizing the US corporate bond market would yield large gains in efficiency. By studying two markets where corporate bonds are successfully traded on central limit order books, I estimate that the transaction costs of US corporate bonds would decrease by 70% on average if trading migrated from over-the-counter markets to limit order markets. To study the social value of reforming the corporate bond market, I build a parsimonious model of centralized and decentralized trading. The model implies that the optimal market structure can be determined by appropriately scaling the transaction costs associated with each market structure. Estimating the scaling factors reveals that a centralized market structure would be optimal for 91% of the bonds studied. For the average bond, moving to limit order markets would generate a social surplus equal to 1.28% of total par value. Large bond issues with low credit ratings and long time to maturity would benefit the most.
Adaptive Lifelong Learning for Visual Recognition

Whereas my PhD thesis studied transfer learning with Gaussian process models [8] and random decision forests [9], my current main research topic is lifelong learning of visual concepts. In particular, I have worked on aspects of adaptation [6, 10] (model sharing, learning from different but related datasets), active learning [3, 7] (selecting unlabeled examples which are likely beneficial when being labeled by an annotator), novelty detection [1] (determining whether an example belongs to an unknown category), and finegrained recognition [11, 4, 2] (discriminating very similar categories). Learning with non-iid. data has been always part of my research on domain adaptation, where I search for handy solutions applicable to some of the large-scale learning problems we have in vision. One example is the MMDT (max-margin domain transforms) method presented in [6], which jointly learns classifier parameters as well as a linear transformation that maps labeled examples of one dataset to the feature space of another but related labeled dataset. The method itself is a straightforward extension of standard one-vs-all SVMs and can be used in large-scale scenarios [10]. Recently, people have boosted the performance on nearly all vision datasets and tasks by using a feature representation learned with high complexity models (e.g. CNNs) on large-scale datasets, such as ImageNet. This strategy can be seen as non-iid. learning with two related but different datasets (ImageNet and another vision data set). In a recent publication, we brought this concept to an extreme by using pre-trained CNN models for object part discovery [11].
ANISOTROPIC HYPER-ELASTIC FINITE ELEMENT BASED UPON GENERALIZED STRAIN

This paper presents the mathematical formulation of a finite element model based on the stress-strain constitutive equations derived for anisotropic hyper-elastic materials using logarithmic strain. Assuming a constitutive equation for the specific internal energy the equation governing the Cauchy stress is derived. The dependence of third-order elastic constants on the choice of strain measure is shown. Using the finite element method the equilibrium equation is integrated in the current configuration. Differentiation of the residuum vector, which is a nonlinear function of displacements leads to a complex analytical expression for the tangent stiffness matrix. The particular terms of it are discussed. The paper presents also a numerical example, which demonstrates how nonlinear elasticity together with dislocations induce the surface tension observed in thin layers of crystalline monostructures. Paweł Dłużewski, Grzegorz Jurczak, Horacio Ant́unez
Crystal structure, optical and electrical characteristics of rutile TiO 2 nanocrystallite-based photoanodes doped with GeO 2

The effect of germanium dioxide, GeO 2 doping on dye-sensitized solar cell (DSSC) TiO 2 nanocrystallite photoanodes with composition (TiO 2 – ( GeO 2 ) x : 0 ≤ x ≤ 0 . 3 wt%) has been studied. The pure sample and GeO 2 -doped samples have been synthesized by a conventional solid-state reaction method and analysed by means of X-ray diffraction, scanning electron microscopy, energy dispersive X-ray and ultraviolet–visible spectroscopy techniques. The photovoltaic characteristics of the prepared samples have been studied by employing J – V measurements. The pattern of XRD depicted that the dominating phase in the sample with x = 0 is a rutile tetragonal phase with the P 4 2 / mnm space group. An increase in GeO 2 concentration leads to an appearance and rise of another hexagonal phase structure of α -GeO 2 with the P 3 2 21 space group. Data obtained from the UV–visible spectroscopy measurements reﬂect that the optical energy gap ( E optical ) increases with increasing GeO 2 content, while the optical refractive index decreases. J – V photovoltaic characteristics conﬁrm that the DSSCs doped with low-concentration doping, x = 0 . 05 and 0.1 of GeO 2 have higher values for conversion efﬁciency ( η ), ﬁll factor and short circuit current density ( J sc ) compared with samples with high-concentration doping ( x = 0 . 2 and 0.3) of GeO 2 . The present results showed that TiO 2 – ( GeO 2 ) x ( x = 0 . 05 and 0.1 wt%) ﬁlms are potential candidates for optical ﬁlter materials and optoelectrical and photo-conversion
Development of Robust Automated Scoring Models Using Adversarial Input for Oral Proficiency Assessment

In this study, we developed an automated scoring model for an oral proficiency test eliciting spontaneous speech from nonnative speakers of English. In a large-scale oral proficiency test, a small number of responses may have atypical characteristics that make it difficult even for state-of-the-art automated scoring models to assign fair scores. The oral proficiency test in this study consisted of questions asking about content in materials provided to the test takers, and the atypical responses frequently had serious content abnormalities. In order to develop an automated scoring system that is robust to these atypical responses, we first developed a set of content features to capture content abnormalities. Next, we trained scoring models using the augmented training dataset, including synthetic atypical responses. Compared to the baseline scoring model, the new model showed comparable performance in scoring normal responses, while it assigned fairer scores for authentic atypical responses extracted from operational test administrations.
A Computational Framework for Visual Perception of Inertial Affordances

We present a Model Predictive Control approach to visual affordances. Under this framework, visual features are used to estimate the inertial parameters of internal models. These models are used to generate and update motor control policies. Finally, the accelerations observed while applying the control policies are used to refine the mapping between visual features and inertial model parameters. The proposed approach allows to generalize visual affordances to novel objects, and novel tasks. Computer simulations show that the proposed approach models results from existing behavioral experiments, suggests and makes predictions for new experiments, and is amenable for implementation in humanoid robots.
LMWH inhibits TNF-α and IL-6 in placental villous explants and its effects are attenuated by TLR4 / NF-κB p 65 blocking in JEG-3 cells

Preeclampsia (PE) leads to high perinatal mortality and morbidity due to hypertensive disorder and maternal inflammatory response of pregnancy. Studies demonstrated higher levels of TNF-α and IL-6 were observed in cases of PE. This research aims to explore the effects of low molecular weight heparin (LMWH) on TNF-α and IL-6 and its preliminary potential mechanism through TLR-4/NF-κB p65 pathway in placental villous explants and JEG-3 cells. Placental villous explants derived from patients with PE, spontaneous preterm labor and first trimester termination of pregnancy were cultured under normoxia and hypoxia conditions respectively. Then different concentrations of LMWH were added to explants in hypoxia group. In terms of gene target study, JEG-3 cells were transfected by SiRNA against TLR-4 and NF-κB p65 individually. Protein and mRNA levels of TNF-α and IL-6 were measured by western-blot and PCR. Immunohistochemistry staining was used to locate relative proteins in placental villous explants. Placental villous explants under hypoxia condition had similar upregulated levels of TNF-α and IL-6 with that in PE group, and this upregulation could be inhibited by LMWH with 2.5 μg/ml as the most effective concentration. TLR-4 and NF-κB p65 were both higher expressed in PE group than those in control group. Blocking of TLR-4 or NFκB p65 in JEG-3 cells could both lead to attenuation of anti-inflammatory properties of LMWH. The results suggested LMWH could inhibit inflammatory response in placenta villous explants by inhibiting TNF-α and IL-6 and the effects were possibly via TLR-4/NF-κB p65 pathway.
Unique fixed point results for pairs of mappings on complete metric spaces

In this article, we prove a coincidence point results for four pairs of mappings on four complete metric spaces. The obtained result generalize some well known fixed point results of literature such as Namdeo et al.[Thai Journal of Mathematics, 7(1) (2009), 129 – 135] and Gupta et al. [International Journal of Applied Physics and Mathematics, 2 (3), (2012), 169 – 171].
Word knowledge in six- to nine-month-old Norwegian infants? Not without additional frequency cues

The past 5 years have witnessed claims that infants as young as six months of age understand the meaning of several words. To reach this conclusion, researchers presented infants with pairs of pictures from distinct semantic domains and observed longer looks at an object upon hearing its name as compared with the name of the other object. However, these gaze patterns might indicate infants' sensibility to the word frequency and/or its contextual relatedness to the object regardless of a firm semantic understanding of this word. The current study attempted, first, to replicate, in Norwegian language, the results of recent studies showing that six- to nine-month-old English-learning infants understand the meaning of many common words. Second, it assessed the robustness of a ‘comprehension’ interpretation by dissociating semantic knowledge from confounded extra-linguistic cues via the manipulation of the contingency between words and objects. Our planned analyses revealed that Norwegian six- to nine-month-old infants did not understand the meaning of the words used in the study. Our exploratory analyses showed evidence of word comprehension at eight to nine months of age—rather than from six to seven months of age for English-learning infants—suggesting that there are cross-linguistic differences in the onset of word comprehension. In addition, our study revealed that eight- to nine-month-old infants cannot rely exclusively on single extra-linguistic cues to disambiguate between two items, thus suggesting the existence of early word-object mappings. However, these mappings are weak, as infants need additional cues (such as an imbalance in frequency of word use) to reveal word recognition. Our results suggest that the very onset of word comprehension is not based on the infants' knowledge of words per se. Rather, infants use a converging set of cues to identify referents, among which frequency is a robust (pre-semantic) cue that infants exploit to guide object disambiguation and, in turn, learn new words.
Functional divergence of bitter taste receptors in a nectar-feeding bird

Nectar may contain many secondary metabolites that are commonly toxic and bitter-tasting. It has been hypothesized that such bitter-tasting secondary metabolites might keep the nectar exclusive to only a few pollinators. To test this hypothesis, we examined functional changes of bitter taste receptor genes (Tas2rs) in a species of nectar-feeding bird (Anna's hummingbird) by comparing these genes with those from two closely related insect-feeding species (chimney swift and chuck-will's widow). We previously identified a larger number of Tas2rs in the hummingbird than in its close insectivorous relatives. In the present study, we demonstrate higher sensitivity and new functions in the hummingbird Tas2r gene copies generated by a lineage-specific duplication, which has been shaped by positive selection. These results suggest that the bitter taste may lead to increased sensitivities and specialized abilities of the hummingbird to detect bitter-tasting nectar. Moreover, this study potentially supports the hypothesis that bitter-tasting nectar may have been specialized for some pollinators, thus enforcing plant–pollinator mutualism.
Surface Water Quality Evaluation Based on Bayesian Network

ABSTRACT Xie, X. ; Liu, Y. ; Luo, Y. , and Du, Q. , 2019. Surface water quality evaluation based on Bayesian network. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 54–60. Coconut Creek (Florida), ISSN 0749-0208. This study aimed to establish a new water quality evaluation method based on Bayesian network owing to the shortcomings that the connections between various indicators are not considered using the traditional evaluation method. It adopted a combination of mutual information and K2 search algorithm for network structure learning and applied the maximum likelihood estimation method for parameter learning. Considering the water quality in the Hongya section of the Qingyi River as an example, the correlation and quantitative expression of the indicators were obtained. The factors that directly affected the water quality grade were found to be permanganate index, ammonia nitrogen, and total nitrogen. The water quality grade was inferred based on the quantitative relationship between indicators and water quality category. After testing, the accuracy was found to be more than 83.3%, indicating that the Bayesian network method could be used for evaluating the water quality. The process of evaluation was simple and rapid, providing a reliable basis for quickly assessing the overall water quality of the river basin. Finally, according to the method, the associated missing indicators could be predicted, providing more complete hydrological data for water environment management.
Design of Electronic Microcontrol Interphone for Ocean-going Ship Based on Radio Frequency Filter

ABSTRACT Chen, J., 2019. Design of electronic microcontrol interphone for ocean-going ship based on radio frequency filter. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 935–940. Coconut Creek (Florida), ISSN 0749-0208. In order to improve the channel balance of ocean-going ship electronic micro-control system and the stability of intercom information transmission, it is necessary to design the ocean-going ship electronic microcontrol interphone. A design scheme of ocean-going ship electronic micro-control interphone based on radio frequency filter is proposed. The high-speed signal processing chip ADSP21160 processor system is used as the main control chip of ocean-going ship electronic micro-control interphone, and the overall design of ocean-going ship electronic micro-control interphone is carried out. The hardware module of the system includes the electronic micro-control transmission module, the micro-control signal amplification module, the signal detection module, the adaptive gain adjustment module, the modulation and demodulation module, the electronic micro-control intercom automatic control module and the output interface module. The input oceangoing ship electronic micro-control signal is amplified and filtered, the radio frequency filter is designed to filter the signal, the channel optimization control of ocean-going ship electronic control signal is carried out by using DSP, and the modulation and demodulation control of ocean-going ship electronic micro-control signal is carried out by using internal clock oscillator, and the optimization design of ocean-going ship electronic micro-control interphone is realized. The system test results show that the channel balance of electronic microcontrol intercom information transmission of ocean-going ships is good, the output error code is low, and the quality of electronic microcontrol intercom transmission of ocean-going ships is higher.
Assessment Method of the Economic Vulnerability of the Coastal Zone Based on the Analytic Hierarchy Process

ABSTRACT Wang, B. ; Nie, X. ; Li, Z. , and Fan, T. , 2019. Assessment method of the economic vulnerability of the coastal zone based on the analytic hierarchy process. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 798–803. Coconut Creek (Florida), ISSN 0749-0208. It is an important strategic measure to carry out the scientific concept of development and build a harmonious society to make great efforts to build a coastal economic uplift zone and cultivate a new economic growth pole. A coastal economic vulnerability assessment method based on analytic hierarchy process (AHP) is proposed. And combined with statistical data for empirical analysis. The statistical information model of coastal economic vulnerability assessment is constructed. According to the mining results of coastal economic vulnerability assessment information, the frequent itemsets association rules of coastal economic vulnerability assessment data are reconstructed, the correlation dimension characteristics of coastal economic vulnerability information are extracted, and the regular characteristics of coastal economic vulnerability assessment cross-correlation information fusion are analyzed. Taking this as the constraint condition, the correlation information mining evaluation of coastal economic vulnerability assessment is carried out, and the statistical analysis and robustness test of coastal economic vulnerability are carried out by using statistical feature analysis method. The simulation structure shows that the model has good accuracy and high confidence in coastal economic vulnerability assessment, and improves the quality of coastal economic vulnerability assessment.