Miracle-dz/UniFAR-FTUs huggingface dataset:
DEVELOPMENT AND VALIDATION OF NOVEL RP-HPLC METHOD FOR SIMULTANEOUS ESTIMATION OF GABAPENTIN AND AMITRIPTYLINE HYDROCHLORIDE IN BULK AND PHARMACEUTICAL DOSAGE FORMS

Objective : To develop a novel, accurate, precise and linear reverse phase high performance liquid chromatographic (RP-HPLC) method for simultaneous quantitative estimation of gabapentin and amitriptyline hydrochloride in gabantip-at tablet and validate as per international conference on harmonization (ICH) guidelines and to perform the force degradation studies using the developed method. Methods : In the present work, good chromatographic separation was achieved isocratically using a shim-pack HPLC C18 column (4.6 x 250 mm, 5μm) and mobile phase consisting of 0.05 M potassium dihydrogen orthophosphate pH 2.1 adjusted with orthophosphoric acid and acetonitrile in the ratio (55:45), at flow rate 1 ml/min and column temperature (25 °C). The effluents obtained were monitored at 221 nm with the UV-visible detector. Results : The retention time of gabapentin and amitriptyline hydrochloride was found to be 1.959 min and 4.221 min respectively. The linearity of gabapentin was found in the range of 720-1680 ppm and that for amitriptyline hydrochloride was found to be 24-56 ppm. The correlation coefficient for gabapentin and amitriptyline hydrochloride were 0.999 and 0.9963 respectively. The high recovery values (98%-101%) indicate a satisfactory accuracy. The low percent relative standard deviation (% RSD) values in the precision study reveals that the method is precise. Conclusion : The developed method is novel, simple, precise, rapid, accurate and reproducible for simultaneous estimation of gabapentin and amitriptyline hydrochloride tablet dosage form. Hence the proposed method may find practical applications as a quality-control tool in the simultaneous analysis of the two drugs in combined dosage forms in quality-control laboratories.
MODULATION OF NEUROPLASTICITY IN HUMANS BY ADVANCED STIMULATION PROTOCOLS AND NEUROMODULATORS

The neuromodulator nicotine alters cognitive functions in animals and humans most likely by modification of brain plasticity. In the human brain, it alters plasticity induced by transcranial direct current stimulation (tDCS) and paired associative stimulation (PAS), probably by interference with calcium-dependent modulation of the glutamatergic system. We aimed to test this hypothesis further by exploring the impact of the  nicotinic receptor partial agonist varenicline, which has calcium channel properties, on focal and non-focal plasticity, induced by PAS and tDCS, respectively. We administered low (0.1mg), medium (0.3mg) and high (1.0mg) single doses of varenicline or placebo medication before PAS or tDCS on the left motor cortex of 25 healthy non-smoking individuals. Corticospinal excitability was monitored by single-pulse transcranial magnetic stimulation (TMS)-induced motor evoked potential (MEP) amplitudes up to 36 hours after plasticity induction. Whereas low-dose varenicline had no impact on stimulation-induced neuroplasticity, medium-dose varenicline preserved only focal excitatory plasticity. High-dose application preserved cathodal tDCS-induced excitability diminution and focal facilitatory plasticity induced by excitatory PAS, but abolished anodal tDCSand inhibitory CHAPTER 2 – ORIGINAL ARTICLES AND MANUSCRIPTS 37 PAS-induced changes in excitability. These results are comparable to the impact of nicotine receptor activation and might help to further explain the involvement of specific receptor subtypes in the nicotinic impact on neuroplasticity and cognitive functions in humans.
A New Broadband Microstrip Leaky – Wave Antenna

− This paper presents a novel design of a curve tapered leaky-wave antenna (LWA). An FDTD code was used to extract the propagation constant of a microstrip LWA and to run a simple algorithm to design its layout. A physical grounding structure along the length of the antenna allows the adoption of a simple feeding planar line and the reduction of sidelobes. Moreover, the proposed design of LWA has interesting performance both for its bandwidth, (up to 33% for VSWR< 2) and for its gain (more than 12 dBi peak power gain at 10.5 GHz), compared with conventional planar microstrip LWAs which work in the same frequency range but with narrower bandwidth (20% VSWR< 2) and peak power gain less than 10 dBi. A prototype of a LWA proposed, was made showing a good agreement between experimental and theoretical results.
Another Look at the Ho–Lee Bond Option Pricing Model

Bond option pricing models come in two forms: equilibrium models and arbitrage-free models. The former start from assumptions about the dynamic process that governs the evolution of the instantaneous short rate, which produces a theoretically consistent model of the whole term structure. But unfortunately, real-world bond prices do not follow the model perfectly, and many will appear to be mispriced. By contrast, the Ho–Lee model, the first arbitrage-free model, starts with the observed term structure and sets up a binomial structure that determines how it can evolve over time so that there are no riskless arbitrage profit opportunities embedded in the current or any possible future yield curves. But the original formulation of the Ho–Lee model has the unfortunate property that it is possible for interest rates to go negative or to grow without bound over time, neither of which is acceptable. In this article, the authors present a modified Ho–Lee specification that eliminates the problem by allowing the binomial probabilities to change over time while still maintaining the no-arbitrage restriction.
LEARNING FROM SKEWED DATA DISTRIBUTION WITH CLUSTER DISJUNCT HYBRID APPROACH

Research on the class imbalance learning problem has been mainly directed towards rigorous trial and error producers to adapt certain intermediate parameters so as to improve bias on the minority set. In this paper, we present a new hybrid framework by initially applying under-sampling on majority subset and then in later stage applying oversampling on improved subset by using the concept of cluster disjuncts. To verify the proof of concept we test the proposed algorithm with five benchmark algorithms on twelve UCI datasets using six evaluation metrics. We demonstrate that the proposed HYBRID algorithm is one of the effective solutions for addressing the class imbalance problem in most of the cases.
UvA-DARE ( Digital Academic Repository ) Institutional complexity and sustainable development in the EU electricity sector

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On the Effect of Labour Productivity on Growth: Endogenous Fluctuations and Complex Dynamics

This paper introduces a sigmoidal production function that considers production possible even when the only input is labour. The long-run behaviour of an economy described by the neoclassical Solow-type growth model with differential savings is investigated considering the technology presented. It is found that labour productivity influences the existence of boom and bust periods as well as the level of capital per capita in equilibrium.
Identification of dynamic models in complex networks with predictor error methods

This paper addresses the problem of obtaining an estimate of a particular module of interest that is embedded in a dynamic network with known interconnection structure. In this paper it is shown that there is considerable freedom as to which variables can be included as inputs to the predictor, while still obtaining consistent estimates of the particular module of interest. This freedom is encoded into sufficient conditions on the set of predictor inputs that allow for consistent identification of the module. The conditions can be used to design a sensor placement scheme, or to determine whether it is possible to obtain consistent estimates while refraining from measuring particular variables in the network. As identification methods the Direct and Two Stage Prediction-Error methods are considered. Algorithms are presented for checking the conditions using tools from graph theory.
Differentiation between fore and hind hoof dimensions in the horse ( Equus caballus )

Abstract. The aim of the study was to define differences between front and hind hooves in dimensions and proportions of the measurements in horses of various breeds. 77 mares four to thirteen years old of four breeds belonging to different origin types were evaluated: Purebred Arabian horses, halfbred Anglo-Arabian horses, primitive Polish Konik horses and Polish Cold-Blooded horses. The dimensions were measured after trimming. Means in particular groups and differences between fore and hind hooves were estimated with the least square analysis of variance performed separately in each breed. In the four breeds studied, the fore and hind hoof dimensions from the lateral view of the hoof capsule have come out to be similar. The toe to heel length ratio approximates 2 : 1 in both hooves. Viewed from the solar surface, the hind hoof is wider at the heel buttress relative to the fore hoof. The greatest difference between the fore and rear hooves occurs in the capsule width, hence while recording this parameter, it should be defined which foot it concerns. The hoof width is the most highly correlated with other dimensions, as well as the correlations between the fore and hind hooves in this parameter are the highest. The hoof capsule width is the most characteristic parameter of the hoof.
Towards a better comprehension of satisfaction with democracy

Understanding citizens’ attitudes towards their political systems continues to be a matter of great importance in the beginning of the 21 st century. Traditional approaches used to assess these attitudes have proven to be limited and lead to erroneous conclusions. Using data from a pilot study conducted by the European Social Survey in the United Kingdom and Russia in late 2011, this article employs multiple items to offer a comprehensive analysis of citizens’ evaluations of the functioning of their democracies. Findings reveal deep citizen concern with economic performance. Other important conclusions are drawn at both the substantive and methodological levels.
Surveys and Econometricians When can surveys beat econometricians in forecasting inflation

We examine the forecasting power of surveys in dierent environments, countries with stable inflation and countries where inflation is more volatile. We test whether surveys forecast inflation better then the best out of sample VAR forecaster. We find a very clear pattern: surveys are better real time forecasters then a VAR in stable economies, and not in countries with a highly volatile inflation.
Electric charge catalysis by magnetic fields and a nontrivial holonomy

We describe a generic mechanism by which a system of Dirac fermions in thermal equilibrium acquires electric charge in an external magnetic field. To this end the fermions should have an additional quantum number, isospin, or color and should be subject to a second magnetic field, which distinguishes the isospin or color, as well as to a corresponding isospin chemical potential. The role of the latter can be also played by a nontrivial holonomy (Polyakov loop) along the Euclidean time direction. The charge is accumulated since the degeneracies of occupied lowest Landau levels for particles of positive isospin and antiparticles of negative isospin are different. We discuss two physical systems where this phenomenon can be realized. One is monolayer graphene, where the isospin is associated with two valleys in the Brillouin zone, and the strain-induced pseudomagnetic field acts differently on charge carriers in different valleys. Another is hot QCD, for which the relevant non-Abelian field configurations with both nonzero chromomagnetic field and a nontrivial Polyakov loop can be realized as calorons\char22{}topological solutions of Yang-Mills equations at finite temperature. The induced electric charge on the caloron field configuration is studied numerically. We argue that due to the fluctuations of holonomy, the external magnetic field should tend to suppress charge fluctuations in the quark-gluon plasma and estimate the importance of this effect for off-central heavy-ion collisions.
Promoting ecological restoration in France: issues and solutions

Ecological restoration has developed greatly over recent decades. Promoting harmonious relationships between scientists and practitioners, between restoration ecology and ecological restoration, is essential to improving restoration projects. These relationships are difficult to achieve at a global scale, although international action remains essential. Therefore, regional and national networks are attempting to take up the challenge. With several European countries planning to create their own network in the coming years, insights from current practice are helpful. Here, we (1) describe the context in which ecological restoration is developing in France and (2) present the French restoration network, Réseau d'Echanges et de Valorisation en Ecologie de la Restauration (REVER). Most public policies related to restoration in France are derived from European Union (EU) directives, such as those on water, ecological networks, biodiversity, and protected species and natural habitat. Restoration can also be undertaken through Environmental Impact Assessment (EIA) or subsequent to damage. Following the model of the International Society for Ecological Restoration, the French network for ecological restoration (REVER) aims at accompanying and promoting restoration by facilitating relationships between the various stakeholders: practitioners, scientists, site managers, etc. To encourage exchange of knowledge and experience, REVER manages a website, organizes workshops, and provides links with SER‐Europe and Society for Ecological Restoration International (SERI). This article provides information that will be of interest to other countries trying to meet the Aichi targets of the convention on biological diversity: the restoration of 15% of degraded ecosystems by 2020.
AN APPLICATION OF THE EXPERIMENTAL CHOICE MODEL TO ESTIMATE PREFERENCES FOR OUTDOOR RECREATION ATTRIBUTES IN TAMAN NEGARA MALAYSIA NATIONAL PARK

The main objective of the study is to explore the applicability of the choice experiment method to reveal preferences of visitors. The preferences are related to the attributes of eco-tourism resources in Taman Negara Malaysia. Four alternative sets of combinations of attributes which included types of accommodation, congestion levels, permitted length of stay per permit and entrance fees are given to visitors to choose. The results of the analysis on the probability of choice function reveal that types of accommodation, indicated by differences in room rates, and congestion levels are the two significant factors influencing visitors preferences for the eco-tourism resources. The choice of types of accommodation facilities can be implied to the preferences for quality services and facilities. On the other hand, the congestion level is associated with lower entrance fee and costs of visits.
Verification of Leaf Area Index Retrieved by ICESAT-2 Photon-Counting Lidar with Airborne Lidar

Leaf area index (LAI) is a significant parameter controlling a lot of physical and biological processes related to vegetation on the Earth's surface. Previously, an LAI estimation model of ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2)/Atlas (Advanced Topographic Laser Altimeter System) has been established and the accuracy of ICESat-2 LAI has been evaluated using optical images. However, this model hasn't been tested with airborne data. To demonstrate the effectiveness of ICESat-2 LAI, this study applied the model to airborne LiDAR data in the Saihanba National Nature Reserve in the same season. Results showed that the coefficient of determination $(R^{2})$ of ICESat-2 LAI was 0.63 and the root mean square error (RMSE) is $1.03(n=26,\ p < 0.001)$, ICESat-2 has the inversion capability of LAI comparable to airborne lidar. These findings may help in promoting the LAI estimation model and broadening the application fields of the photon-counting LiDAR data.
FATTY ACID PROFILE AND NUTRITION VALUES OF THE MICROALGA ( THALASSIOSIRA PSEUDONANA ) USED IN WHITE SHRIMP CULTURE

The microalga Thalassiosira pseudonana is an important feed item in the aquaculture industry, especially for white leg shrimp production. This study examined the fatty acid composition and other chemical components of T. pseudonana cultivated as biomass for the production of shrimp seedlings with the aim to evaluate its nutritional values. For the investigation, the microalga was grown under optimal conditions and harvested during log and early stationary phase after 6–8 days of cultivation. Chemical analysis showed that the main organic components of the biomass were lipid (20.8 % of dry cell weight), protein (13.2 %), and carbohydrate (10.0 %). GC-MS analysis showed that the lipid fraction consisted of 42.5 % SFAs (hexadecanoic acid 38.1 % of total fatty acid), 15.0 % MUFAs, and 42.4 % PUFAs (EPA 16.4 % and DHA 1.7 %). Moreover, the T. pseudonana biomass was found to contain a large variety of minerals and micronutrients (mg/kg), such as I (55.10), Fe (222.74), Cu (1.96), Mn (3.11), Mg (2.52), Ca (0.97), and Co (< 0.10), while boron was undetectable. Importantly, the contents of heavy metals, such as Cd, Pb, As, and Hg were lower than required levels for aquaculture feed by Vietnamese standards. Thus, T. pseudonana is a quality feed with high nutritional values for aquaculture.
Federal Environmental Protection and the Distorted Search for Oil and Gas

The US federal government imposes costly environmental protection requirements for oil and gas operations on federally owned lands. This paper shows how these federal policies aected rms’s drilling location choices and the resulting production. I exploit a natural experiment where federal and non-federal land were exogenously assigned. Using data from Wyoming, I nd that revealed drilling and production outcomes are consistent with a model of search where costs are higher on federal land. I also nd that low costs on non-federal land decreased drilling on nearby federal land while providing positive information spillovers. I show that drilling and production results are not driven by alternative mechanisms like common pools or irregular leasing policies. Back-of-the-envelope estimates suggest that federal regulations cost about $17 million (2010 dollars) per well. Most recent version available at:
Anti-mycobacterial Effects of the Extract of Humulus japonicus

Tuberculosis Research Section, National Institute of Allergy and Infectious Diseases, National Institutes of HealthAbstract The present study aimed to evaluate the in vitro antimycobacterial effects of hop plant, Humulus japonicus.Methanol extract of H. japonicus (MeOH extract) showed strong direct bactericidal effects against Mycobacteriumtuberculosis in vitro. Furthermore, the MeOH extract significantly inhibited M. tuberculosis growth in human macrophages.When five fractions obtained from MeOH extract were examined using the same methods, the hexane and ethyl acetatefractions showed bactericidal effects against M. tuberculosis in vitro, whereas the butanol and water fractions inhibited M.tuberculosis growth in macrophages. Because H. japonicus extract exhibited antimycobacterial activity against both free M.tuberculosis in culture medium and intracellular M. tuberculosis in human macrophages, this plant might be a goodcandidate for development of a new anti-tuberculosis drug.Keywords: Humulus japonicus, tuberculosis, bactericidal effect, macrophage
Telma Alves Veloso

Methods for the study of the functional connectivity in the brain have seen several developments over the last years, however not yet in a fully realized manner. Machine learning and complex network analysis are two promising techniques that together can help the process of better exploring functional connectivity for future clinical applications. Machine learning and pattern recognition algorithms are helpful for mining vast amounts of neural data with increasing precision of measures and also for detecting signals from an overwhelming noise component (Lemm, Blankertz, Dickhaus, & Müller, 2011). Complex network analysis, a subset of graph theory, is an approach that allows the quantitative assessment of network properties such as functional segregation, integration, resilience, and centrality (Rubinov & Sporns, 2010). These properties can be fed into classification algorithms as features. This is a new and complex approach that has no standard procedures defined, so the aim of this work is to explore the use of fMRI-derived complex network measures combined with machine learning algorithms in a clinical dataset. In order to do so, a set of classifiers is implemented on a feature dataset built with brain regional volumes and topological network measures that, in turn, were constructed based on functional connectivity data extracted from a resting-state functional MRI study. The set of classifiers includes the nearest neighbor, support vector machine, linear discriminant analysis and decision tree methods. A set of feature selection methods was also implemented before the classification tasks. Every possible combination of feature selection methods and classifiers was implemented and the performance was evaluated by a cross-validation procedure. Although the results achieved weren’t exceptionally good, the present work generated knowledge on how to implement this recent approach and allowed the conclusion that, for most cases, feature selection improves the performance of the classifier. The results also showed that the decision tree algorithm produces relatively good results without being associated with a feature selection method and that the SVM classifier, together with RFE feature selection method, produced results on the same level as other work done with a similar approach.
Real-time diffuse indirect illumination with virtual light meshes

Indirect illumination on a rendered scene can add a great deal to its visual quality, but it is also a costly operation. Therefore, a lot of research targets how to render indirect illumination in real-time. While powerful techniques for real-time indirect illumination currently exist, they provide only coarse-grained artistic control over the trade-off between quality and speed. We propose a Virtual Light Mesh to compute the scene’s diffuse indirect illumination, inspired by the use of other current auxiliary meshes such as Navigation Meshes and Collision Meshes. A Virtual Light Mesh (VLM) is a simplified mesh of polygonal lights used to approximate the light bounced by the real geometry. Together with the VLM, we design an acceleration data structure for efficient indirect illumination performance with a complex VLM. The use of VLM presents some positive properties: greater artistic control of the indirect illumination characteristics; the possibility of integration with existing techniques such as skeletal animation and procedural generation; and simple integration into existing asset production tools and pipelines. Our experimental results show that artist controlled indirect illumination is a viable alternative to existing methods.