Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Hand Gesture-based Assembly for Augmented Reality Applications

—This paper presents an Augmented Reality (AR) assembly system for the interactive assembly of 3D models of technical systems. We use a hand tracking and hand gesture recognition system to detect the interaction of the user. The Microsoft Kinect video camera is the basis. The Kinect observes both hands of a user and the interactions. Thus, a user can select, manipulate, and assemble 3D models of mechanical systems. The paper presents the AR system and the interaction techniques we utilize for the virtual assembly. The interaction techniques have been tested by a group of users. The test results are explained and show that the interaction techniques facilitate an intuitive assembly.
Advanced CFD & HT numerical modeling of solar tower receivers

This paper presents an advanced methodology for the detailed modeling of the heat transfer and fluid dynamics phenomena in solar tower receivers. It has been carried out in the framework of a more ambitious enterprise which aims at modeling all the complex heat transfer and fluid dynamics phenomena present in central solar receivers. The global model is composed of 4 submodels (heat conduction, two-phase flow, thermal radiation and natural convection) which are described. Results of the numerical model obtained so far are also presented and discussed ©2013 The Authors. Published by Elsevier Ltd. Selection and peer review by the scientific conference committee of SolarPACES 2013 under responsibility of PSE AG.
Application of Poisson Mixed Combined Models for Identifying Correlations of CD4 Count Progression in HIV Infected TB Patients During ART Treatment Period

CD4 count is used to measures the number CD4 cells in the blood mostly during ART treatment to know the risk progression of HIV in the HIV infected patients. This continuously measured CD4 count during the treatment period results longitudinal data having correlation and over dispersion effects. While modeling such data to identify associated factors of change in CD4 count to monitor the progression of HIV most of the study did not considered these two main effects. The main aim of this study was also to consider these two main effect to identify the risk factors CD4 count progression based on 239 HIV infected TB patients who were 18 years old and above taking ART treatment from $1^{st}$ September 2009 to $1^{st}$ July 2014 at Jimma University Specialize Hospital. The result of study showed Poisson normal Gamma combine model which handles correlation and over dispersion effects of CD4 count simultaneously was an appropriate fit of the data among different Poisson mixed combined models considered for the study based on Akaki information criteria (AIC)comparisons. The estimated model depicts linear time and it's interaction effect with functional status category group of the patients have positive effect whereas quadratic time has the negative effect on the progression of CD4 count. The model also showed baseline bedridden and ambulatory functional status group patients has lower average CD4 count measurements in comparison with working functional status group patients counterparts. Therefore, while modeling CD4 count correlation and over dispersion should be taken in to consideration since the CD4 count value was correlated due to repeated measurement and it's variance larger than mean leading to over dispersion. Being at bedridden, ambulatory functional status at baseline in comparison with working functional status group and having quadratic time effects were also the associated risk factors that lowers the CD4 count measurements of the patients during the ART treatment period at the study area.
Intersectoral linkages and Agricultural growth in Swaziland for the period 1971-2011

Agriculture plays an important role in the Swazi economy as it is the primary source of employment, livelihood and food security. The future success of the contribution of agriculture to economic growth depends largely on how agriculture stimulates growth of the other sectors and especially how the other sectors growth spills over and stimulates agricultural growth. Using bound test approach to cointergration, Granger causality and Impulse Response framework, the study therefore examined the interrelationships between agriculture and the rest of the sectors of the economy and their impact on economic growth over the period of 1971 to 2011 in Swaziland. The empirical results indicated that a long run relation exists among agriculture, the rest of the economy and overall economic growth. Granger causality analysis indicated that there is bidirectional causality between agriculture and economic growth, unidirectional causality between agriculture and services, running from services to agriculture and independence between agriculture and industry. The Impulse Response showed that contribution to GDP forecast error by the industry sector is the highest, followed by agriculture and service sectors. This study recommended that agriculture should be given more priority in order to grow the economy. Keywords: Agriculture growth, ARDL, Granger causality tests, Inter-sectoral linkages, UECM, Variance decomposition.
Identification of QTLs for pod and kernel traits in cultivated peanut by bulked segregant analysis

Bulked segregant analysis was used to identify simple sequence repeat (SSR) markers associated with pod and kernel traits in cultivated peanut, to permit rapid selection of superior quality genotypes in the breeding program. SSR markers linked to pod and kernel traits were identified in two DNA pools (high and low), which were established using selected F 2:6 recombinant individuals resulting from a cultivated cross between a runner (Tamrun OL01) and a Spanish (BSS 56) peanut. To identify quantitative trait loci (QTLs) for pod and kernel-related traits, parents were screened initially with 112 SSR primer pairs. The survey revealed 8.9% polymorphism between parents. Of ten SSR primer pairs distinguishing the parents, five (PM375, PM36, PM45, pPGPseq8D9, and Ah-041) were associated with differences between bulks for seed length, pod length, number of pods per plant, 100-seed weight, maturity, or oil content. Association was confirmed by analysis of segregation among 88 F 2:6 individuals in the RIL population. Phenotypic means associated with markers for three traits differed by more than 40%, indicating the presence of QTLs with major effects for number of pods per plant, plant weight, and pod maturity. The SSR markers can be used for marker assisted selection for quality and yield improvement in peanut. To the best of our knowledge, this is the first report on the identification of SSR markers linked to pod - and kernel- related traits in cultivated peanut.
Analysis and Prediction of some Histone-derived Antimicrobial Peptides from Toads Duttaphrynus melanostictus and Phyrinoidis asper

Antimicrobial peptides in skin secretions of toads is a promising methods to combat a wide spectrum of bacteria. Histone H2A is a type of DNA-binding protein that acts as a precursor for several antimicrobial peptides. In toads (family Bufonidae) buforin I and buforin II are examples of antimicrobial peptides that derived from histone H2A. This study investigated the genetic diversity and phylogenetic analysis and in silico prediction of antimicrobial peptides derived from histone H2A of Duttaphrynus melanostictus and Phyrinoidis asper , which were collected from Bogor Agricultural University’s campus area. A new set of primers (Buf_fwd and Buf_rev) were designed by using PrimerBLAST, to amplify 393 nucleotides of the histone H2A gene that codes 131 amino acids. Haplotype diversity of both species are very low. Phylogenetic analysis shows the sample D. melanostictus and P. asper are separated to each other in two different clades. Several short predicted peptides from histone H2A show a potential as an antimicrobial peptides based on in silico prediction. Psychochemical characteristics and 3D structure of potent antimicrobial peptides are described.
Depression, Family Support, and Body Mass Index in Mexican Adolescents

The relationship between depressive symptomatology and elevated Body Mass Index (BMI), and between family support and low BMI is controversial. There are unanswered questions about the relationship between these three variables We tested the hypothesis that positive family support mediates the association between depression and bodyweight responsible for overweight and obesity in Mexican youth. We explored if family support correlated with depression and if depressive symptomatology correlated with obesity. Our results indicate that the relationship between depression and family support was significant (r = -0.44, p = 0.004). A significant relationship between depression and BMI was found only in women. When family support is included into the equation, the effect of depression on BMI disappeared. This observation indicates family support is a partial mediator between depression and obesity in adolescents. Our results are important and prompt an extended analysis of likely causative links between psychosocial parameters and health descriptors.
Construction of consistent ice core accumulation time series from large-scale meteorological data: development and description of a regression model for one North Greenland ice core

An empirical downscaling relationship is constructed which consistently estimates annual ice accumulation from large-scale meteorological data. The method by which the relationship was developed and the application of the method to one ice core are described. The statistical tech- nique is based on a stepwise multiple linear regression using yearly accumulation as the predictand and the principle components (PCs) of seasonally averaged large-scale atmospheric fields as predic- tors. In order to separate the accumulation variations related to circulation and thermodynamics, the first step involves the stream-function field as the predictor. In the second step, temperature PCs are related to the residuals between real ice accumulation and accumulation described by stream-func- tion PCs. One model is fitted for a North Greenland ice core. The atmospheric data are monthly NCEP Reanalysis data from 1948 to 1992. A statistical relationship is found which reproduces about 71.5% of local ice accumulation variability. The relationship involves 3 physically plausible stream- function patterns, representing a seasonal mean (May to August) over Greenland, the North Atlantic and North Europe, which describes 64% of variance. In the second step, an additional contribution of the temperature field to the explained variance of 7.5% is achieved. The temperature PCs represent the annual mean 700 hPa pattern covering the area from east Canada to east Greenland.
Optimising molecular dynamic potentials to dynamical structure factor data

This paper reports an algorithm and software for producing dynamical models of materials at the atomic scale using classical molecular dynamics simulation, but simultaneously refining the potential energy parameters based on experimentally determined dynamical and structural information such as the dynamical structure factor S(Q, ω). The software is called MDMC (Molecular Dynamics Monte Carlo) (https://github.com/MDMCproject) and the first pre-release version used in this work is https://doi.org/10.5281/zenodo.1068365. The algorithm follows from two previous very successful algorithms Reverse Monte Carlo (RMC) (McGreevy & Pusztai, 1988)(McGreevy, 2001) and Empirical Potential Structure Refinement (EPSR) (Soper, 1996) (Soper, 2007), though these are only used to produce structural models based on structural data. In this paper the algorithm is presented together with initial results for a model system, liquid argon, based on the data of (van Well, Verkerk, de Graaf, Suck, & Copley, 1985). Introduction Both RMC and EPSR have had a large impact on structural studies of disordered and amorphous materials. For recent reviews and works using these methods see for example: (Playford, Owen, Levin, & Tucker, 2014) (Bouty, 2014) (Soper & Edler, 2017). In RMC the atomic coordinates in a structural model, typically many thousands of atoms, are refined based on the difference between experimental structural data and that calculated from the model. Sequences of RMC configurations (models) have been used to explore dynamical aspects of structures (see e.g. McGreevy and Zetterström, 2003), for example diffusion pathways in crystalline ionic conductors, but still based on structural data. This approach has then been extended (RMCt) to fit to the dynamical structure factor (Gereben, Pusztai, & McGreevy, 2007) by assigning a time step between configurations and thus creating an analogue of a MD simulation. In EPSR an empirical potential is used in a Monte Carlo model to generate a structure and the potential parameters are refined based on the difference between experimental structural data and that calculated from the model. When the refinement has converged the potential can then be used on its own to create ensembles of structures. In principle the potential could also be used in a MD simulation to create dynamical models. However, it has been recognised for a long time that often a range of potentials can adequately reproduce the same set of structural data, whereas they might produce quite different results in terms of dynamics. Hence the use of the word ‘empirical’; the potential is purely used as a tool for generating a structural model.
A Context-Aware Framework for an Intelligent Mall based on Recommender System

IntelliSense technology used in various fields are constantly expanding from the depth and breadth. Currently, most of the academic research on intelligent sensing systems are in specific fields such as health care, environmental monitoring, smart home. And less in-depth and practical research for smart shopping environment. In this paper, we design a recommendation system based on intelligent business district. First we design the architecture of the system which is efficient and scalable. Then raise the concept of behavior context model to describe all the situation in the intelligent mall.
Coupled Ocean–Atmosphere Offshore Decay Scale of Cold SST Signals along Upwelling Eastern Boundaries

AbstractA simple analytic model is developed to represent the offshore decay of cold sea surface temperature (SST) signals that originate from wind-driven upwelling at a coastal boundary. The model couples an oceanic mixed layer to an atmospheric boundary layer through wind stress and air–sea heat exchange. The primary mechanism that controls SST is a balance between Ekman advection and air–sea exchange. The offshore penetration of the cold SST signal decays exponentially with a length scale that is the product of the ocean Ekman velocity and a time scale derived from the air–sea heat flux and the radiative balance in the atmospheric boundary layer. This cold SST signal imprints on the atmosphere in terms of both the boundary layer temperature and surface wind. Nonlinearities due to the feedback between SST and atmospheric wind, baroclinic instability, and thermal wind in the atmospheric boundary layer all slightly modify this linear theory. The decay scales diagnosed from two-dimensional and three-dimens.
Nambu-Goldstone mode in a rotating dilute Bose-Einstein condensate (8 pages)

The Nambu-Goldstone mode (NGM), associated with vortex nucleation in a harmonically confined, two-dimensional dilute Bose-Einstein condensate is studied. We argue, based on exact diagonalization calculations, that the NGM manifests in the lowest-lying envelope of the quasidegenerate spectrum that emerges as the vortex is about to enter the condensate. The quasidegenerate states constitute a series of octupole-mode branches that originate primarily from pairwise repulsive interactions between octupole excitations and are distinguished by the number of admixed quadrupolar excitations. As the vortex approaches the center of the condensate and the system's axisymmetry is restored, the NGM becomes massive due to its coupling to higher rotational bands. We clarify the mechanism of this mass acquisition by using a newly developed projection-operator method.
Molecular Disks in Radio Galaxies: The pathway to ALMA

Context. It has recently been proposed that the jets of low-luminosity radio galaxies are powered by direct accretion of the hot phase of the IGM onto the central black hole. Cold gas remains a plausible alternative fuel supply, however. The most compelling evidence that cold gas plays a role in fueling radio galaxies is that dust is detected more commonly and/or in larger quantities in (elliptical) radio galaxies compared with radio-quiet elliptical galaxies. On the other hand, only small numbers of radio galaxies have yet been detected in CO (and even fewer imaged), and whether or not all radio galaxies have enough cold gas to fuel their jets remains an open question. If so, then the dynamics of the cold gas in the nuclei of radio galaxies may provide important clues to the fuelling mechanism. Aims. The only instrument capable of imaging the molecular component on scales relevant to the accretion process is ALMA, but very little is yet known about CO in southern radio galaxies. Our aim is to measure the CO content in a complete volume-limited sample of southern radio galaxies, in order to create a well-defined list of nearby targets to be imaged in the near future with ALMA. Methods. APEX has recently been equipped with a receiver (APEX-1) able to observe the 230 GHz waveband. This allows us to search for CO(2-1) line emission in our target galaxies. Results. Here we present the results for our first three southern targets, proposed for APEX-1 spectroscopy during science verification: NGC3557, IC4296 and NGC1399. The experiment was successful with two targets detected, and possible indications for a double-horned CO line profile, consistent with ordered rotation. These early results are encouraging, demonstrating that APEX can efficiently detect CO in nearby radio galaxies. We therefore plan to use APEX to obtain CO spectroscopy for all our southern targets.
Equal-weighted information criterion for model selection in univariate time series analysis

In model building, the model with appropriate number of parameters needs to be identified. Thus, a variety of information criteria have already been developed, each with a different background to handle this challenge. The mostly used information criteria are the Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), and Hannan and Quinn Information Criterion (HQ). However, available literature and the preliminary analysis done by authors indicated that when selecting the appropriate model, these information criteria usually lacked uniformity. Thus, in this study, an information criterion that serves as a unifier to the three commonly used criteria; AIC, SIC and HQ is proposed. The penalties of these three information criteria are considered as a linear function. Simulations were conducted on the performance of the proposed information criterion (PIC) together with the three conventional information criteria using nine models and seven different sample sizes. The results revealed that the proposed information criterion (PIC) performed better than the AIC, SIC and HQ with respect to the overall performance in choosing the true model. The performance of PIC increased as sample size increased. However, PIC turns to under fit, when the true model is not selected. When sample size is large, PIC is asymptotically robust with respect to single processes, Autoregressive (AR) and Moving Average (MA). Thus, the proposed information criterion is recommended when selecting the order of a univariate time series. Tropical Agricultural Research Vol. 26 (2): 303 – 316 (2015)
International Laboratory Comparison of Influenza Microneutralization Assays for A ( H 1 N 1 ) pdm 09 , A ( H 3 N 2 ) , and A ( H 5 N 1 ) Influenza Viruses by CONSISE

WHO Collaborating Centre for Reference and Research on Influenza, Victorian Infectious Diseases Reference Laboratory, Peter Doherty Institute for Infection and Immunity, Melbourne, Australia; National Institute for Biological Standards and Control, Medicines and Healthcare Products Regulatory Agency, Potters Bar, Hertfordshire, United Kingdom; National Institute for Biological Standards and Control, Hertfordshire, United Kingdom; Centers for Disease Control and Prevention, Atlanta, Georgia, USA; School of Public Health, The University of Hong Kong, Pok Fu Lam, Hong Kong; Public Health England, London, United Kingdom; Norwegian Institute of Public Health, Oslo, Norway; World Health Organization, Geneva, Switzerland; Center for Global Health, Institut Pasteur, Paris, France
Corporate Finance and the (In)efficient Exercise of Real Options

This paper considers real options within a continuous-time corporate finance context. We analyze whether these real options are exercised effciently, and what the underlying sources of inefficiency are. In particular we consider the role of incomplete information, competition, search costs and financing constraints on investment decisions. We also analyze the stockholder-bondholder and the manager-stockholder agency problems, and their effect on a firm's investment and closure policies.
Relation of RAS Gene Polymorphisms with Impaired Glucose Tolerance in Patient with End Stage Renal Failure

Abstract Renin angiotensin system (RAS) is a system that is the role of renal hemodynamics, blood pressure and fluid electrolyte balance regulation with progression to end-stage renal disease (ESRD). Angiotensin II (AII),the main mediatör of this system, is thought to cause a functional impairment in insulin receptor and post receptor signaling pathways. Our aim; was to show the relation of angiotensin-converting enzyme (ACE), angiotensin II receptor type 1 (AT1 R) and angiotensinogen gene (AGT) polymorphisms, that cause genetic susceptibility to over activation of RAS, to glucose intolerance in patient with end stage renal failure. The study included one hundredth patients. Based on fasting plasma glucose values and oral glucose tolerance test second hours glucose values, patients were grouped as normal patients and patients with glucose intolerance [impaired fasting glycemia (IFG), impaired glucose tolerance (IGT) and diabetes mellitus (DM)]. Insulin resistance was calculated by HOMA-IR method and insülin sensitivity index was calculated by ISI-S method. ACE, AT1 R, AGT polymorphisms were detected by polymerase chain reaction (PCR) method. There was no statistically significant difference between distribution of ACE, AT1R and AGT genotypes and glucose intolerance groups, and insulin resistance. There was a statistically significant difference between MM and TT genotypes and average insulin resistance values (p < 0,04). We have obtained results suggesting a relation between ACE gene D allele and glucose intolerance in patients with end stage renal failure (p=0.06). Moreover, a relation has been shown between AGT gene T allele and insulin resistance (p=0.04).
IST and E-Business Strategy Development: An I-Space Perspective

IST strategic reorientation invariably involves large investments for organisations. Problematic development and implementation can have a major impact on an organisations future growth. With the development of the Internet, organisations now face yet another major strategic reorientation and IST strategy issue  the move to e-business. Ensuring effective reorientation is therefore a crucial element for success. This paper investigates IST strategy development within three UK-based organisations by analysing the information flows during the strategy development process. The I-space framework is used to map the evolution of information from the initial trigger to the embedding of new knowledge into the organisation. The results of this research illustrate that IST strategy development is a complex social process. Each of the three cases experienced different triggers for change and information flows. However, this is one study of three organisations and should be interpreted as such to provide the inspiration for further research.