Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Inhibitors of V-ATPase Pumps in Yeast by HTS Flow Cytometry

Fluorescence intensity of the pH-sensitive carboxyfluorescein derivative BCECF was monitored by high throughput flow cytometry in living yeast cells. We measured fluorescence intensity of BCECF trapped in yeast vacuoles, acidic compartments equivalent to lysosomes where V-ATPases are abundant. Because V-ATPases maintain a low pH in the vacuolar lumen, V-ATPase inhibition by concanamycin A alkalinized the vacuole and increased BCECF fluorescence. Likewise, V-ATPase deficient mutant cells had greater fluorescence intensity than wild-type cells. Thus, we detected an increase of fluorescence intensity after short-term and long-term inhibition of V-ATPase function. We used yeast cells loaded with BCECF to screen a small chemical library of structurally diverse compounds in order to identify V-ATPase inhibitors. One compound, disulfiram, enhanced BCECF fluorescence intensity (although to a degree beyond anticipated for pH changes alone in the mutant cells). Once confirmed by dose response assays (EC50=26 μM), we verified V-ATPase inhibition by disulfiram in secondary assays which measured ATP hydrolysis in vacuolar membranes. The inhibitory action of disulfiram against V-ATPase pumps revealed a novel effect previously unknown for this compound. Because V-ATPases are highly conserved, new inhibitors identified could be used as research and therapeutic tools in cancer, viral infections, and other diseases where V-ATPases are involved.
Genetic Relationship Among 36 Genotypes of Ceiba pentandra (L.) as Revealed by RAPD and ISSR Markers

Ceiba pentandra (L.) Gaertn (trade name Ceiba) of the family Bombacaceae is an important multi-purpose tree species in Ghana and demand for it is rising daily. As a result, it has been included as one of the species for the National Forest Plantation Development Programme of Ghana as part of the efforts towards its restoration. Seedlings for the programme are being raised from seed collected from the wild without regard for their genetic quality and its future adverse effects. The absence of adequate information on the genetic diversity within the species therefore serves as a potential threat to its long term sustainable management and efficient genetic conversation. The phylogenetic relationships of 36 genotypes of C. pentandra from natural range of the species in five ecological zones (populations) of Ghana were therefore analyzed using 10 polymerase chain reaction (PCR) markers (5 random amplified polymorphic DNAs (RAPDs) and 5 inter simple sequence repeats (ISSRs)). The principal component analysis (PcoA) defined by axis 1 and 2 accounted for 67.15% of the variation observed. Cluster analysis using GeneStat Discovery showed that, 14 (38.89%), 21 (58.33%) and 4 (11.11%) of the accessions had a coefficient of similarity of 1 from the RAPD, ISSR and the combined RAPD and ISSR polymorphism respectively. The most distantly related accessions from the RAPD polymorphism analysis were BAW 1 and KON 8 with a similarity coefficient of 0.06 whereas those from the ISSR polymorphism were BAW 10 and ASE 1 with 21% similarity between them. Similarly, BUF 1 and KUE 1 were the most dissimilar accessions from the combined RAPD and ISSR fragments analysis with a similarity coefficient of 0.23. Nine (25%) accessions with high degree of dissimilarity between them were identified in the study. These accessions could serve as good candidates for conservation as seed trees and in breeding programs of C. pentandra in Ghana. Implications of the findings for effective management of the genetic resources of the species were also discussed.
Brand Equity in the Australian domestic beef market

Branding remains in a fairly nascent state within the Australian domestic beef market. Several brands have begun to emerge in recent years including Certified Angus, 1824, Hereford Prime, Stockyard Beef and Diamantina. However, these primarily cater for restaurant rather than household trade. This contrasts with other countries, such as the US, where branded beef makes up a large proportion of the domestic market. Using random parameter logit models we examine the willingness of consumers to pay for one type of branded beef, as well specific beef attributes, in a regional area of NSW. We find that there is evidence that segments of the population would be willing to pay for branded beef. The value of the brand is related to several sociodemographic characteristics, as well as attitudinal variables.
Calendar Anomalies: Do REITs Behave Like Stocks?

This study addresses the unsettled question of whether REITs behave similarly to stocks with respect to calendar anomalies. We determine the magnitudes of several types of calendar anomalies for both the REIT and stock market index returns in 22 countries between 1990 and 2012. In general, our evidence shows that the calendar effects are not universal across countries and that REITs behave differently from their stock counterparts in a number of countries. The difference in behavior is especially evident around the turn of the month where REITs exhibit significantly higher returns than general stocks in the global sample as well as in 7 of the 22 countries examined. This result may be possibly linked to the higher level of institutional ownership in REITs than stocks in their corresponding market during the period examined.
Forest Cover Dynamics in South East Asia Evidenced from MODISData

Land cover data sets are essentially spatial representation of our earth’s surface, categorised into units like forests, grasslands etc. The availability of satellite platform based land cover classification products have largely advantaged mapping of changes in land cover revealing patterns and trends. Such studies are gaining importance in environmental risk assessment studies. Forest area is depleting fast giving way to expansion of agriculture and commercial plantations in South East Asia. In this study we attempt to map the dynamics of land cover between 2001 and 2012 in South East Asia using the Global Land Cover data product of Moderate Resolution Imaging Spectroradiometer (MODIS) platform using statistical and spatial methods. We found evidences of large scale forest conversion but the overall sum of changes was insignificant for the region in general. The suitability of MODIS against other platforms like Landsat for land cover change assessment and the opportunities for multivariate analysis is also discussed.
Performance Analysis of Multilevel Spatial Modulation OFDM Technique ( MLSM-MIMO )

Multiple–Input-Multiple-Output (MIMO) techniques are the key technology for next generation wireless communication standards, since it provides improved performance with bandwidth efficiency. The applications such as high speed internet, multimedia data transmission, and medical telemetry data which include images need high data rate transmission. The need for wideband channel and the scarcity of the available wireless spectrum are the main driving forces believed the development of new technologies such as adaptive coding techniques, STC, UWB, MCM and OFDM for the future generation wireless communication standards. MIMO-OFDM is a powerful combination and has already been adopted in many of the wireless standards to enhance system capacity. The main problem with these systems is increasing in computational complexity. Multilevel coding and multistage decoding has been proposed as a solution. In this paper MLSTTC-OFDM and MLSM-OFDM have been proposed and analyzed over frequency selective fast and slow fading channels. Simulation results show that MLSM-OFDM outperforms MLSTTC-OFDM over correlated fast and slow fading frequency selective channel conditions with 40% less computations. AMS Subject Classification: 94 Information and Communication, Circuits
Optimality conditions applied to free-time multi-burn optimal orbital transfers

While the Pontryagin Maximum Principle can be used to calculate candidate extremals for optimal orbital transfer problems, these candidates cannot be guaranteed to be at least locally optimal unless sufficient optimality conditions are satisfied. In this paper, through constructing a parameterized family of extremals around a reference extremal, some second-order necessary and sufficient conditions for the strong-local optimality of the free-time multi-burn fuel-optimal transfer are established under certain regularity assumptions. Moreover, the numerical procedure for computing these optimality conditions is presented. Finally, two medium-thrust fuel-optimal trajectories with different number of burn arcs for a typical orbital transfer problem are computed and the local optimality of the two computed trajectories are tested thanks to the second-order optimality conditions established in this paper.
Equatorial Ionospheric Electric Fields During the November 2004 Magnetic Storm

[1] We use radar measurements from the Jicamarca Radio Observatory, magnetometer observations from the Pacific sector and ionosonde data from Brazil to study equatorial ionospheric electric fields during the November 2004 geomagnetic storm. Our data show very large eastward and westward daytime electrojet current perturbations with lifetimes of about an hour (indicative of undershielding and overshielding prompt penetration electric fields) in the Pacific equatorial region during the November 7 main phase of the storm, when the southward IMF, the solar wind and reconnection electric fields, and the polar cap potential drops had very large and nearly steady values. This result is inconsistent with the recent suggestion that solar wind electric fields penetrate without attenuation into the equatorial ionosphere for several hours during storm main phase. The largest daytime prompt penetration electric fields (about 3 mV/m) ever observed over Jicamarca occurred during the November 9 storm main phase, when large equatorial electrojet current and drift perturbations were also present in the Pacific and Brazilian equatorial regions. The rise and decay times of these equatorial electric fields were about 20 min longer than of the corresponding solar wind electric fields. The ratios of prompt penetration electric fields and corresponding solar wind electric field changes were highly variable even during the day, and had largest values near dawn. Also, the prompt penetration electric fields did not show polar cap potential drop saturation effects. Our results clearly highlight that the relationships of prompt penetration and solar wind electric fields, and polar cap potentials are far more complex than implied by simple proportionality factors.
An Intelligent Decision Support System for SMED and Its Application in Textile Industry

The new trend is to avoid high-volume batch-and-queue manufacturing to produce small batches with short lead-time due to fluctuation in customer demands. However, producing more products at small batches results in more changeovers. Thus, a rapid changeover provides to be able to manufacture small quantities of the large diversity of customer demands. One of the most common method for changeover time reduction is Single Minute Exchange of Dies (SMED) which is a technique of Lean Manufacturing. The developed prototype intelligent SMED decision support methodology uses the expertise of different experts, professionals and scientific papers. Intelligent system approach for SMED has two main functions. First one is gathering data that the system asks some questions to the user to obtain the facts of the company and the second one is intelligent recommendations. According to “the facts” and “inference engine”, the system manages the SMED application and can give some suggestions. The methodology has forward chaining mechanism and 90 rules. One of the original aspects of the system is starting the methodology with the vision of the firm and strategy. If the strategy is proper for the firm, the system may continue, if not, suggest another strategy such as outsourcing or investment in production technology.
Attitudes Toward Homosexuals Among Youth in Multiethnic Brussels

This study examined attitudes toward lesbians and gay men (referred to in the literature as sexual prejudice ) in a sample of pupils from 70 secondary schools in Brussels. We used items measuring traditional and modern sexual prejudice and support for gay civil rights. We performed a multilevel linear multivariate response analysis to assess both the impact of individual characteristics and school influence on pupils’ attitudes. Controlling for sociodemographic variables, second-generation migrants had more prejudice toward homosexuals than pupils from the ethnic majority group. Identification with the receiving society and perception of group-level institutional discrimination, however, mediated the association between ethnic origin and homonegativity. In contrast to traditional sexual prejudice and gay civil rights issues, modern sexual prejudice items were less affected by individual sociodemographic variables. Modern sexual prejudice also remained rather stable across schools; however, schools did appear to affect civil rights issues and traditional sexual prejudice. This contribution sheds light on the relationship between ethnic origin and sexual prejudice and on the variation of several sexual prejudice dimensions across social groups and schools.
ESTIMATING THE ERROR CORRECTION MODEL FOR SUDANESE EXCHANGE RA

Dynamic analysis is vital issue in econometrics, hence we were applied it to model and estimate exchange rate. The study suggested four variables in explaining exchange rate movement, these variables covers the proxies of fiscal, monetary , and mixed policy. Furthermore GDP is introduced to reflect the overall performance of the economy. Some variables were stationary while others were not. Cointegration tests confirmed the existence of long run equilibrium relationship between exchange rate and the explanatory variables, hence the model was estimated by error correction model. The estimated coefficient were in combatable with economic and econometric theories. Monetary policy coefficients in short and long run proved the existence of J curve effect. Despite the multiplier of monetary policy was larger than that one of fiscal policy, the later policy was more effective than the former one in manipulation exchange rate.
Stable Lévy diffusion and related model fitting

A fractional advection-dispersion equation (fADE) has been advocated for heavytailed flows where the usual Brownian diffusion models fail. A stochastic differential equation (SDE) driven by a stable Lévy process gives a forward equation that matches the spacefractional advection-dispersion equation and thus gives the stochastic framework of particle tracking for heavy-tailed flows. For constant advection and dispersion coefficient functions, the solution to such SDE itself is a stable process and can be derived easily by least square parameter fitting from the observed flow concentration data. However, in a more generalized scenario, a closed form for the solution to a stable SDE may not exist. We propose a numerical method for solving/generating a stable SDE in a general set-up. The method incorporates a discretized finite volume scheme with the characteristic line to solve the fADE or the forward equation for the Markov process that solves the stable SDE. Then we use a numerical scheme to generate the solution to the governing SDE using the fADE solution. Also, often the functional form of the advection or dispersion coefficients are not known for a given plume concentration data to start with. We use a Levenberg–Marquardt (L-M) regularization method to estimate advection and dispersion coefficient function from the observed data (we present the case for a linear advection) and proceed with the SDE solution construction described above.
Design of Knowledge Acquisition Subsystem with Mining Association Rules from Big Data

Expert system has played an important role in human’s life for a long time. In order to establish an expert system, knowledge acquisition is the process which should be considered first. Regarding to this step, two of the most demanding requests are: how to discover the knowledge from a massive dataset, and how to organize them in a temporary database properly in order to be reviewed again. In this paper, we propose a design of a subsystem, which acquires the knowledge from Big Data sources and stores them following the rule form. Our work is conducted with the support of a data mining technique called association rules mining, which is executed through parallel distributed environments: given data under file form as input, outputs which includes rules representing knowledge with their corresponding certainty factor are gotten. Then all of these rules are stored in a relational database, which could be queried out by knowledge engineers to review them again before encoding them into the knowledge base. By the experiments with real dataset, it is confirmed that our proposed design could not only acquire the knowledge from Big Data source in an acceptable duration, but also handle well with the querying out situation when a lot of rules are gotten.
Using Google ’ s PageRank Algorithm to Identify Important Attributes of Genes

In our research, we have applied PageRank technology to identify important attributes of Genes. Google search engine uses this PageRank algorithm to assign a numerical weight of each webpage and cluster search results. We have found PageRank algorithm is a very effective method for selecting significant attributes for high-dimensional data; especially, gene expression data. Important genes can be used in clustering of gene expression data to get a better clustering using minimum time and space. Clustering of high-dimensional data requires lot of resources both in terms of time and memory space. Generally, some attributes are more important than others. We use yeast’s gene expression data from Stanford MicroArray Database. Four datasets are used each with approximate 4905 genes and 5 to 14 expression levels. We calculate the correlation matrix between these genes using their expression levels in various experiments. We have used Weka (data mining software in java) to generate and validate a naïve bayes classifier. We found that the data ranked with PageRank algorithm produces better classification than the raw data. The raw data used to build classifier can classify attributes at 48-50% accuracy while PageRanked data classify attributes at 62-64% accuracy.
Hyperchromatic Nucleus Segmentation on Breast Histopathological Images for Mitosis Detection

Breast cancer grading is the standard clinical practice for the prognosis and diagnosis of breast cancer development. The Nottingham Histological Grading (NHG) system is widely used in the breast cancer grading. In NHG system, the mitotic count based on histopathological images (i.e. microscopic slide examination) is one of the three criteria that define the overall grade. Image processing techniques such as segmentation could be utilised to detect mitotic cells. This study proposed a new approach to segment hyperchromatic nucleus on the histopathological images based on RGB and HSI colour spaces. The results show that the proposed segmentation technique could provide a promising result in segmenting hyperchromatic nucleus and preserving the ground truth (i.e. true mitotic cells).
On Risk Model with Dividends Payments Perturbed by a Brownian Motion – An Algorithmic Approach

Assume that an insurance company pays dividends to its shareholders whenever the surplus process is above a given threshold. In this paper we study the expected amount of dividends paid, and the expected time to ruin in the compound Poisson risk process perturbed by a Brownian motion. Two models are considered: In the first one the insurance company pays whatever amount exceeds a given level b as dividends to its shareholders. In the second model, the company starts to pay dividends at a given rate, smaller than the premium rate, whenever the surplus up-crosses the level b. The dividends are paid until the surplus down-crosses the level a, a < b . We assume that the claim sizes are phase-type distributed. In the analysis we apply the multidimensional Wald martingale, and the multidimensional Asmussesn and Kella martingale.
ISO 9001 as a standard of quality management in Poland and Czech Republic: an analysis based on the global data

It is vital to remember that there are numerous kinds of standards compliant with the ISO 9001 standard. ISO 9001 standard is one of many pro-quality solutions adopted in companies worldwide. Starting to apply pro-quality solutions in an organization, in particular the ISO 9001 standard implementation, is up to the decision making body. The analyses also show that the ISO 9001 standard meets the requirements of decisionmaking body. This trend is positive and continues to increase. Therefore, it is likely to forecast that the implementation dynamics will still be increasing in the near future.
Real-time pose and shape reconstruction of two interacting hands with a single depth camera

We present a novel method for real-time pose and shape reconstruction of two strongly interacting hands. Our approach is the first two-hand tracking solution that combines an extensive list of favorable properties, namely it is marker-less, uses a single consumer-level depth camera, runs in real time, handles inter- and intra-hand collisions, and automatically adjusts to the user's hand shape. In order to achieve this, we embed a recent parametric hand pose and shape model and a dense correspondence predictor based on a deep neural network into a suitable energy minimization framework. For training the correspondence prediction network, we synthesize a two-hand dataset based on physical simulations that includes both hand pose and shape annotations while at the same time avoiding inter-hand penetrations. To achieve real-time rates, we phrase the model fitting in terms of a nonlinear least-squares problem so that the energy can be optimized based on a highly efficient GPU-based Gauss-Newton optimizer. We show state-of-the-art results in scenes that exceed the complexity level demonstrated by previous work, including tight two-hand grasps, significant inter-hand occlusions, and gesture interaction.1
A Two-Stage Bayesian Network Approach for Robust Hand Trajectory Classification

In this paper, a hand gesture based approach is presented for the unidirectional information transfer from the human worker to the machine worker, designed for industrial applications. In order to allow high variance in respect of the location and orientation of the user relative to the RGB-D sensor, no detailed information about the finger setup is processed for the classification. For the recognition of various gestures, 3D hand trajectories are extracted and injected into a twostage probabilistic inference mechanism. In our approach, we use Hidden Markov Models to optimize the classification rate for intended gestures, and a Bayesian Network for the robust elimination of unintended gestures. We show how empirical and heuristic information about the stochastic process are combined and used for the probabilistic modeling, in order to improve the overall robustness of the classification. The evaluation of our approached showed that the two-stage scheme allows for a directed rejection strategy on the basis of heuristic driven restrictions, without the loss of classification performance.