Miracle-dz/UniFAR-FTUs huggingface dataset:
Refining Economic Diversification Strategies for Real Estate Portfolios

Diversification of real estate portfolios has historically been accomplished by utilizing a geographic and/or property-type strategy. More recently, a number of economically based diversification categories have been proposed by industry researchers (see Hartzell, Shulman and Wurtzebach, 1987 and Wurtzebach, 1988). This study tests the efficiency of the existing geographic and geographic/economic strategies currently in the literature against an economically based diversification strategy using straightforward government SIC code categories. The three strategies used include: the NCREIF four geographic regions; the Solomon Brothers eight regions (a combination of economics and geography); and a purely economic grouping of the 316 MSAs in the United States using the nine major government SIC code categories. This study finds that the addition of economic underpinnings to a geographically constrained model, as developed by Hartzell et al. (1987) creates a higher risk/return efficient frontier than the purely geographic NCREIF diversification model. However, shedding geography altogether and diversifying along purely economic lines provides an even better efficient frontier during real estate cycle recovery and growth periods. This new strategy provides the real estate portfolio manager with the opportunity to increase risk-adjusted returns with a strategy that is easily understood and applied.
Predicting Stock Prices Using Polynomial Classifiers: The Case of Dubai Financial Market

Predicting stock price movements is a challenging task for academicians and practitioners. In particular, forecasting price movements in emerging markets seems to be more elusive because they are usually more volatile often accompa-nied by thin trading-volumes and they are susceptible to more manipulation compared to mature markets. Technical analysis of stocks and commodities has become a science on its own; quantitative methods and techniques have been applied by many practitioners to forecast price movements. Lagging and sometimes leading technical indicators pro-vide rich quantitative tools for traders and investors in their attempt to gain advantage when making investment or trading decisions. Artificial Neural Networks (ANN) have been used widely in predicting stock prices because of their capability in capturing the non-linearity that often exists in price movements. Recently, Polynomial Classifiers (PC) have been applied to various recognition and classification application and showed favorable results in terms of recog-nition rates and computational complexity as compared to ANN. In this paper, we present two prediction models for predicting securities’ prices. The first model was developed using back propagation feed forward neural networks. The second model was developed using polynomial classifiers (PC), as a first time application for PC to be used in stock prices prediction. The inputs to both models were identical, and both models were trained and tested on the same data. The study was conducted on Dubai Financial Market as an emerging market and applied to two of the market’s leading stocks. In general, both models achieved very good results in terms of mean absolute error percentage. Both models show an average error around 1.5% predicting the next day price, an average error of 2.5% when predicting second day price, and an average error of 4% when predicted the third day price.
Spirituality, quality of life and the dialysis patient.

standardized questionnaires, which permit the rapid screening of large cohorts of patients. These questionnaires explore various domains, such as those delineated by the SF-36, Beck Depression Inventory, etc. These studies often document the impact of the medical illness on the patients’ perception of their quality of life. Moreover, the impact of quality of life domains on medical outcomes, as well as the relationships between these various domains have been noted. However, developing strategies to improve various quality of life domains has proved to be difficult. For example, although depression is documented as the most common psychological problem encountered in ESRD patients, few studies have looked at specific treatment strategies to improve the depressive symptoms of these patients [13]. And, studies that have developed strategies to treat depression have emphasized the difficulties encountered in employing successful algorithms [13]. No studies have documented that addressing or treating quality of life problems improves patient outcomes. Nevertheless, it is now recommended by K/DOQI that quality of life issues be monitored on an ongoing basis in ESRD patients [14]. The purpose of this monitoring is to define and document the quality of life status of the patient, hopefully identify therapies that can improve the patients’ quality of life, and ultimately improve patient outcomes. Spirituality has been considered by some investigators to be an important arena to focus on in assessing the quality of life of patients. Several questionnaires have been developed to more closely examine the spirituality of patients [2–7,15,16]. These questionnaires permit an assessment to be made of an individual’s spiritual perceptions and distinguish
Bounds for sparse planar and volume arrays

This paper improves and extends bounds on the numbers of sensors, redundancies, and holes for sparse linear arrays to sparse planar and volume arrays. As an application, the efficiency of regular planar and volume arrays with redundancies but no holes is deduced. Also, examples of new redundancy and hole square arrays, found by exhaustive computer search, are given.
Evaluation of the anti-arthritic activity of the hydroethanolic leaf extract of Alchornea cordifolia in rats.

BACKGROUND Different decoctions of Alchornea cordifolia leaves are used by Yoruba herbalists (Southwest Nigeria) for the local treatment of ulcers, rheumatic pains, febrile convulsions, and for enhancing physical performance. MATERIALS AND METHODS In this study, the anti-arthritic effect of 100 - 400 mg/kg/day of the hydroethanolic leaf extract of Alchornea cordifolia (HEAC) was investigated in Complete Freund's Adjuvant (CFA)-induced arthritic rats as a way of evaluating its efficacy in the local management of arthritis. In addition, the effects of HEAC on liver and renal function parameters as well as its effect on the antioxidant enzyme system were investigated. Arthritis was induced using 0.1 ml of 10 mg/ml of Complete Freund's Adjuvant (CFA) following 1 h oral pretreatment and 8(th) day post-arthritic induction with 100, 200 and 400 mg/kg/day of HEAC and 3 mg/kg/day of celecoxib as the reference drug. The anti-arthritic activity of HEAC was assessed based on the ability of HEAC to alter the paw edema diameter, body weight, full blood count, renal and liver function markers, glycoprotein, lysosomal enzymes and possible antioxidant potential in the arthritic rats. RESULTS Oral pretreatment with 100, 200, and 400 mg/kg/day of HEAC produced significant (p<0.001, p<0.05 and p<0.01) reductions in the paw edema diameter in a non-dose dependent fashion in ACF-induced arthritic rats with the 100 mg/kg/day of HEAC producing the most significant anti-arthritic effect. Similarly, HEAC increased hepatic GSH levels, CAT and SOD activities suggesting possible antioxidant mechanism for its anti-arthritic effect. CONCLUSION Overall, results of this study lend credence to the folkloric use of water decoction of Alchornea cordifolia leaves against rheumatoid arthritis. However, further pharmacological investigations would be required at isolating and determining the active anti-arthritic molecule(s) in HEAC in the nearest future.
A hybrid feature selection rule measure and its application to systematic review

Systematic review is the scientific process that provides reliable answers to a particular research question. There is a significant shift from using manual human approach to decision support tools that provides a semi-automated screening phase by reducing the required time and effort. Text classification is useful in determining the statistical significance level of association rules to reduce workload in the systematic review. Several approaches to generate a Rule set for rule based classifiers were proposed in the literature. In this paper, we show that statistic as well as semantic measures of a rule can be combined and effectively computed as a hybrid feature selection rule measure (HFSRM). Moreover, we propose a new algorithm called Rules7-hybrid feature selection (Rules7-HFSRM) by combining the classical algorithm Rules7 and the HFSRM and then used it on the systematic review problem. Our results show that our algorithm significantly outperforms the state-of-the-art benchmark algorithms in the systematic review context.
Netgram: Visualizing Communities in Evolving Networks

Real-world complex networks are dynamic in nature and change over time. The change is usually observed in the interactions within the network over time. Complex networks exhibit community like structures. A key feature of the dynamics of complex networks is the evolution of communities over time. Several methods have been proposed to detect and track the evolution of these groups over time. However, there is no generic tool which visualizes all the aspects of group evolution in dynamic networks including birth, death, splitting, merging, expansion, shrinkage and continuation of groups. In this paper, we propose Netgram: a tool for visualizing evolution of communities in time-evolving graphs. Netgram maintains evolution of communities over 2 consecutive time-stamps in tables which are used to create a query database using the sql outer-join operation. It uses a line-based visualization technique which adheres to certain design principles and aesthetic guidelines. Netgram uses a greedy solution to order the initial community information provided by the evolutionary clustering technique such that we have fewer line cross-overs in the visualization. This makes it easier to track the progress of individual communities in time evolving graphs. Netgram is a generic toolkit which can be used with any evolutionary community detection algorithm as illustrated in our experiments. We use Netgram for visualization of topic evolution in the NIPS conference over a period of 11 years and observe the emergence and merging of several disciplines in the field of information processing systems.
A geometric version of BGP reflection functors

Quiver Grassmannians and quiver flags are natural generalisations of usual Grassmannians and flags. They arise in the study of quiver representations and Hall algebras. In general, they are projective varieties which are neither smooth nor irreducible. We use a scheme theoretic approach to calculate their tangent space and to obtain a dimension estimate similar to one of Reineke. Using this we can show that if there is a generic representation, then these varieties are smooth and irreducible. If we additionally have a counting polynomial we deduce that their Euler characteristic is positive and that the counting polynomial evaluated at zero yields one. After having done so, we introduce a geometric version of BGP reflection functors which allows us to deduce an even stronger result about the constant coefficient of the counting polynomial. We use this to obtain an isomorphism between the Hall algebra at q=0 and Reineke's generic extension monoid in the Dynkin case.
Cross-functional integration and functional coordination in purchasing and supply management: Antecedents and effects on purchasing and firm performance

Purpose – The purpose of this paper is to develop a set of nine hypotheses linking four purchasing and supply management (PSM) practices directly to purchasing performance and indirectly to financial performance.Design/methodology/approach – The authors collected data in a global cross‐industry survey of 148 companies, combining primary interview and survey data with secondary data on firm performance, in order to minimize the impact of common method variance.Findings – Support was found for eight of the nine hypotheses. In particular, a positive impact was found of cross‐functional integration and functional coordination on purchasing performance, and of purchasing performance on firm performance. Both talent management and performance management have a positive impact on cross‐functional integration and functional coordination. Talent management also has a direct impact on purchasing performance, in contrast to performance management.Originality/value – The association of enhanced PSM maturity levels wi.
Understand Function of Location Entity Based on User Generated

Microblogging, as a commonly used form of social network, has become a popular data source for research. Some work relative to the understanding of locations and location inference are done based on microblogging platform by text data, time series data and graph mining on social relations. However, there is yet not many studies that demonstrate how to do modeling and understand the location entities within a scale of city based on such data sets. In the work, based on purely user generated content, a method that
Students’ Use of Social Media in Higher Education in Ghana

This study examined social media use among university students. An online survey was administered to a random sample of 311 sandwich students in the University of Education, Winneba in the 2012/13 academic year. The results revealed that majority of the students were aware of and use social media for a variety of reasons which included: connecting with old friends and family members, finding new friends, obtaining or sharing learning materials, receiving update of events, posting information and whiling away time. It was also found that students had concerns about joining or using social media which included concerns about personal privacy, limited computing skills, cost of Internet connectivity and time to use social media. The results of the study also indicated that students had positive views about the academic use of social media. Students believed that: it will be fun for their lecturers to use social media, their grades will be better if they could contact lecturers through social media and lecturers should hold some lecture hours on social media. Keywords: Social Media, Higher Education, Academic use of social media, Concerns about using social media
Switched fuzzy-PD control of contact forces in robotic micromanipulation of Drosophila larvae

Force sensing and control are of paramount importance in robotic micromanipulation. A contact force regulator capable of accurately applying mechanical stimuli to a live Drosophila larva could greatly facilitate mechanobiology research on Drosophila and may eventually lead to novel discoveries in mechanotransduction of neuron circuitry. In this paper, we present a novel contact force scheme implemented in an automated Drosophila larvae micromanipulation system, featuring a switched fuzzy-PD controller and a noise-insensitive extended high gain observer. The switched fuzzy-PD controller inherits the fast convergence from fuzzy controller and overcomes the drawbacks (overshoot and oscillation) of a conventional fuzzy controller. The observer provides precise estimation to compensate for system modeling errors despite force measurement noise, which overcomes the disadvantage of traditional high gain observer. Force control experiments show that, compared to an conventional PID controller, this new controller-observer scheme has significantly enhanced dynamic performance in terms of rising time, overshoot, and oscillation. The developed robotic system and the force control scheme will be applied to mechanical stimulation and fluorescence imaging of Drosophila larvae for identifying new mechanotransduction mechanisms.
Strong Formulations for Multi-Item Capacitated Lot Sizing

Multi-item capacitated lot-sizing problems are reformulated using a class of valid inequalities, which are facets for the single-item uncapacitated problem. Computational results using this reformulation are reported, and problems with up to 20 items and 13 periods have been solved to optimality using a commercial mixed integer code. We also show how the valid inequalities can easily be generated as part of a cutting plane algorithm, and suggest a further class of inequalities that is useful for single-item capacitated problems.
A gazdasági növekedés és a pénzügyi közvetítés mélysége [Economic growth and the depth of financial mediation]

A tanulmany a gazdasagi novekedes es a penzugyi kozvetites melysege kozotti kapcsolatot tekinti at, kulonos figyelmet szentelve harom kozep-kelet-europai felzarkozo gazdasagra, Magyarorszagra, Csehorszagra es Lengyelorszagra. Az elmult tiz evben megszaporodtak azok a publikaciok, amelyek a gazdasagi novekedes es a penzugyi rendszerek sajatossagai kozotti kapcsolatot elemzik. A szakirodalomban egyre altalanosabban elfogadotta valt az a nezet, hogy a gazdasagi novekedes es a penzugyi kozvetites melysege szoros es kozvetlen kapcsolatban all egymassal. Sőt, tobb kutatasi eredmeny azt igazolja, hogy a penzugyi kozvetites melysege a jovőbeli gazdasagi novekedest jol előrejelző valtozo. E ket tenyező kozotti kapcsolat kerdeskore kulonosen fontos a kozep-kelet-europai felzarkozo gazdasagok eseteben, ahol a penzugyi kozvetites szintje a fejlett orszagokhoz viszonyitva nagyon alacsony. A szerző kiindulo allitasa az, hogy ezekben az orszagokban a felzarkozast elősegitő gazdasagi novekedesnek szuksegszerűen egyutt kell jarnia a penzugyi kozvetites szignifikans melyulesevel. Ha ez nem tortenik meg, az szamottevően fekezheti a gazdasagi novekedes hosszabb tavu trendjet. Ezert a fenntarthato gazdasagi novekedest tamogato gazdasagpolitikanak olyannak kell lennie, amely elősegiti (vagy legalabbis semmikeppen sem hatraltatja) a penzugyek gazdasagban betoltott szerepenek novekedeset, a penzugyi kozvetites melyuleset. Journal of Economic Literature (JEL) kod: O16, G20, G28.
Extraction of Semantic Floor Plans from 3D Point Cloud Maps

3D mapping is increasingly important for mobile robotics in general and for safety, security and rescue robotics (SSRR) in particular as complex environments must but captured in this domain. But it is hard to visualize 3D data in a simple way, e.g. to print maps for first responders, or to use it in standard robotics algorithms, e.g., for path planning. This paper describes a new approach to extract standard planar maps from large scale 3D maps in a very fast manner. In doing so, the approach can detect multiple floors, e.g., in a multi-story building or in a pancake collapse, and segment the 3D map accordingly. To each floor or level, a planar map is assigned, which is augmented by semantic information, especially with respect to traversability. Experiments are presented that are based on 3D maps generated in the large scale environments of USARsim, a high fidelity robot simulator. It is shown that the approach is very fast. The total processing of a complete 3D map takes just a few hundred milliseconds, leading to a proper extraction of floor plans to each of which semantic maps are assigned.
Licensed under Creative Commons Attribution Cc by Privacy Preserving Data Sharing with Cp-abe

With the recent adoption and diffusion of the data sharing paradigm in distributed systems such as online social networks or cloud computing, there have been increasing demands and concerns for distributed data security. One of the most challenging issues in data sharing systems is the enforcement of access policies and the support of policies updates. With the development of cryptography, the attribute-based encryption (ABE) draws widespread attention of the researchers in recent years. The ABE scheme, which belongs to the public key encryption mechanism, takes attributes as public key and associates them with the ciphertext or the user's secret key. It is an efficient way to solve open problems in access control scenarios, for example, how to provide data confidentiality and expressive access control at the same time. Ciphertext policy attribute-based encryption (CP-ABE) is becoming a promising cryptographic solution to this issue. It enables data owners to define their own access policies over user attributes and enforce the policies on the data to be distributed. Therefore, in this study, we propose a novel CP-ABE scheme for a data sharing system by exploiting the characteristic of the system architecture. The proposed scheme features the following achievements: 1) the key escrow problem could be solved by escrow-free key issuing protocol, which is constructed using the secure two-party computation between the key generation center and the data-storing center, and 2) fine-grained user revocation per each attribute could be done by proxy encryption which takes advantage of the selective attribute group key distribution on top of the ABE. The performance and security analyses indicate that the proposed scheme is efficient to securely manage the data distributed in the data sharing system. Module.
Diversity for Parallel Channels to Minimize the Average Distortion

The problem of transmitting a source across a parallel channel with random states only known at the decoder is considered. We focus on minimizing the average distortion. The general problem is unsolved. There are two commonly used architecture, namely source coding diversity and channel coding diversity, which exploit diversity through parallel channel coding or multiple description (MD) source coding. The performance depend on the channel model. Source coding diversity is better for on-off channel models, but for channels with a continuous range of quality, the channel coding diversity is better. In this paper, we provide a joint source-channel coding schemes and a separate coding scheme, both of which have advantage of both channel coding diversity and source coding diversity. Our schemes achieve strictly better performance than MD encoding with joint source-channel decoding introduced by Laneman, \emph{et al.} Finally, inspirited by Nair, {\emph{et al.}}, a better coding scheme combining superposition, Gelfand-Pinsker coding, Marton coding, and indirect decoding is given.
Loop Quantum Gravity Effects on the High Energy Cosmic Ray Spectrum

Recent observations on ultra high energy cosmic rays (those cosmic rays with energies greater than � 4×10 18 eV) suggest an abundant flux of incoming particles with energies above 1 ×10 20 eV. These observations violate the Greisen-Zatsepin-Kuzmin cutoff. To explain this anomaly we argue that quantum-gravitational effects may be playing a decisive role in the propagation of ultra high energy cosmic rays. We consider the loop quantum gravity approach and provide useful techniques to establish and analyze constraints on the loop quantum gravity parameters arising from observational data. In particular, we study the effects on the predicted spectrum for ultra high energy cosmic rays and conclude that is possible to reconcile observations.
SSA analysis of noise eliminated Transcranial Doppler Signals with IIR filters

Biomedical signals affected with noise, interferences and other undesired effects like as Transcranial Doppler (TCD) Signals. In this work, 10dB additive White gaussian noise added on simulated TCD signals. Noise elimination on the TCD signal noise elimination used with 4th degree of IIR filters, parameters are determined with artificial bee colony algorithm (ABC). After noise elimination, new TCD parameters are determined with Singular spectral analysis (SSA) for diagnosis for healthy and patients.