Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Inflation on Indirect Real Estate Investments in Nigeria

The study aims at investigating the impact of inflation on securitized real estate investments in Nigeria with a view to providing information to aid real estate investors in making informed investment decisions. The time frame for the study covers between 2007 and 2016. All the securitized real estate investments including both REITs and non REITs were used in the study. The population for the study comprised of all securitized real estate companies in Nigeria namely Skye Shelter Fund REITs, Union Home REITs, UPDC REITs and UACN properties. Data for the study were collected from the databases of the securitized real estate companies covering the study period. The data collected comprised of share prices and dividends of the respective companies as well as inflation rates obtained from the Nigerian Bureau of Statistics (NBS). The data were analyzed by means of both descriptive statistical tools such as frequencies, mean scores and percentages; and inferential statistical tools such as correlation and regression models. The study revealed that the inflation-hedging performance of securitized real estate in Nigeria provided a partial hedge against inflation (with beta 0.071). It was recommended that real estate investors consider including REITs in their investment portfolios to so as to protect their investment funds from erosion by inflation.
Health literacy, cognitive ability and self-reported diabetes in the English Longitudinal Study of Ageing

To examine the association of health literacy and cognitive ability with risk of diabetes.Research Design and Methods: Participants were 8,669 English Longitudinal Study of Ageing participants (mean age 66.7 years, SD 9.7) who completed health literacy and cognitive ability tests at wave 2 (2004-2005), and who answered a self-reported question on whether a doctor had ever diagnosed them with diabetes. Logistic regression was used to examine the cross-sectional associations of health literacy and cognitive ability with diabetes status. In those without diabetes at wave 2, Cox regression was used to test the associations of health literacy and cognitive ability with risk of diabetes over a median of 9.5 years follow-up (n=6,961). Adequate (compared to limited) health literacy (OR 0.72, 95% CI 0.61-0.84) and higher cognitive ability (OR per 1 SD 0.73, CI 0.67-0.80) were both associated with lower odds of self-reported diabetes. Adequate health literacy (HR 0.64; CI 0.53-0.77) and higher cognitive ability (HR 0.77, CI 0.69-0.85) were also associated with lower risk of self-reporting diabetes during follow-up. When both health literacy and cognitive ability were added to the same model, these associations were slightly attenuated. Additional adjustment for health behaviours, education and social class attenuated associations further, and neither health literacy nor cognitive ability were significantly associated with diabetes.Adequate health literacy and better cognitive ability were associated with reduced risk of diabetes. These associations were independent of each other, but not of other health- and socioeconomic-related variables.
A platform for data handling, analysis and evaluation of environmental engineering issues and simulation control

Computer clusters are getting more and more employed for highly demanding computational tasks in environmental engineering, as the new parallel computing technologies are improving steadily and have attained a high standard. Nevertheless, for a task to execute in a cluster, it needs to be written following paradigms of parallelism, which is not necessarily dominated by the implementer of a specific problem, such as analysis of meteorological data, simulation of pollution dispersion among many others. Therefore, the aim of this work is to develop a computer platform capable of parallelizing, manipulating, analyzing and evaluating meteorological observational data and controlling simulation. Task specific features can be added to the platform through plugins, rendering it flexible and extensible for a large range of tasks. A simple plugin was created to validate and evaluate the functionality of the platform with satisfactory results. The test application considers a simple function to carry out the calculation of the four statistical moments (mean, variance, skewness and kurtosis) of a given variable in a given time scale. Despite its simplicity, this plugin can already be used for exploring the relevance of some variables in order to use this information in a procedure for data reduction.
Regulatory T Cells in Health and Disease

CD4 T cells are commonly divided into regulatory T (Treg) cells and conventional T helper (Th) cells. Th cells control adaptive immunity against pathogens and cancer by activating other effector immune cells. Treg cells are defined as CD4 T cells in charge of suppressing potentially deleterious activities of Th cells. Suggested functions for Treg cells include: prevention of autoimmune diseases by maintaining self-tolerance; suppression of allergy, asthma and pathogeninduced immunopathology; feto-maternal tolerance; and oral tolerance. Identification of Treg cells remains problematic, because accumulating evidence suggests that all the presently-used Treg markers (CD25, CTLA-4, GITR, LAG-3, CD127 and Foxp3) represent general T-cell activation markers, rather than being truly Treg-specific. Treg-cell activation is antigen-specific, which implies that suppressive activities of Treg cells are antigen-dependent. The classification of Treg cells as a separate lineage remains controversial because the ability to suppress is not an exclusive Treg property. Suppressive activities attributed to Treg cells may in reality, at least in some experimental settings, be exerted by conventional Th cell subsets, such as Th1, Th2, Th17 and T follicular (Tfh) cells. Recent reports have also demonstrated that Foxp3 Treg cells may differentiate in vivo into conventional effector Th cells, with or without concomitant down regulation of Foxp3
Corporate Innovation, Likelihood to be Acquired, and Takeover Premiums

Abstract We analyze the effect of a firm's innovation activities on its likelihood to be acquired and the takeover premium using a large sample of M&A transactions. We show that firms with larger innovation outputs and R&D investments are more likely to be acquired, receive unsolicited bids, and receive multiple bids. The takeover premium increases with the target firm's innovation output, and this positive relation is stronger when there are more competing bidders, when acquiring firms’ product markets are competitive, and when technological proximity is lower in the acquiring firms’ industry. Both the acquirer's cumulative abnormal return around the announcement date and post-acquisition operating performance are positively related to the target firm's innovation output and R&D spending.
Scene classification of multisource remote sensing data with two-stream densely connected convolutional neural network

Scene classification is a hot research topic in the geoscience and remote sensing (RS) community. Currently, the investigations conducted in RS domain mainly use single source data (e.g. multispectral imagery (MSI), hyperspectral imagery (HSI), or light detection and ranging (LiDAR), etc.). However, one of the RS data aforementioned merely provides one certain perspective of the complex scenes while the multisource data fusion can provide complementary and robust knowledge about the objects of interest. We aim at fusing the spectral– spatial information of the HSI and the spatial-elevation information of LiDAR data for scene classification. In this work, the densely connected convolutional neural network (DensNet), which connects all preceding layers to later layers in feed-forword manner, is employed to effectively extract and reuse heterogeneous features from HSI and LiDAR data. More specifically, a novel two-stream DensNet architecture is proposed, which builds an identical but separated DensNet stream for each data respectively. Then one of stream is utilized to extract the spectral-spatial features from HSI, the other is exploited to extract the spatial-elevation features of LiDAR data. Subsequently, the spectral–spatial–elevation features extracted in two streams are deeply fused within the fusion network which consists of two fully-connected layers for the final classification. Experimental results conducted on widely-used benchmark datasets show that the proposed architecture provides competitive performance in comparison with the state-of-the-art methods.
ARM-FPGA Implementation of a Partially Reconfigurable OFDM-MIMO Phy-Link

MIMO-OFDM systems are known for high data rate and lower bit error rate (BER) in wireless communication system. These systems helps to yield high data rate and spectral efficiency over multipath and fading channels. OFDM systems use varying modulation schemes and IFFT points based on data rate requirements and number of carriers. Similarly the MIMO system uses an $\mathbf{MxM}$ antenna array with M ranging from 2 to M. Based on the channel conditions and environment a particular combination can perform better with maximum throughput and minimum BER. This paper explores a software defined reconfigurable hardware for the realization of MIMO-OFDM systems and a physical layer link implemented in Xilinx FPGA with partial reconfiguration. The phy link involves a QPSK and a QAM modem with $\mathbf{2}\mathrm{x}\mathbf{2}$ and $\mathbf{4\mathrm{x}4}$ antenna array. Using Partial reconfiguration technique the user can switch between these two schemes in minimum time without configuring the entire FPGA which will take 2 to 3 minutes based on the application. The same hardware can be used for designing multiple combination of modulation, number of carries and antenna array with partial reconfiguration which helps to maintain same hardware and switching between the schemes.
Reabilitação estética de paciente com sorriso gengival: relato de caso clínico

The increase in patients’ demands for an aesthetic smile has been increasing in dental offices. The shape, color and arrangement of the anterior teeth and their relationship with soft tissues determine the aesthetics of the smile. Aim of this paper is to present a clinical protocol for an oral rehabilitation with gingival smile correction. After the selection of the case, a digital planning (DSD) was performed, after periodontal surgery for gingival smile correction. Preparations were made for crowns and ceramic facets, work molding, temporary, adjustments of the prosthetic pieces and cementation. We conclude that the association of periodontal and rehabilitative treatment, following a detailed preliminary planning for cases of complex aesthetic resolution, provided highly predictable, safe and esthetically natural results. UNITERMS: Gingival Smile; Prosthesis; Gingival
Analysis of Denial-of-Service Attack Vectors in Software-Defined Networks

Software-Defined Networking is a new emerging technology that is quickly gaining popularity amongst the largest corporations. However, this new networking paradigm has a centralized point of failure at the controller. With this choke point, it is imperative that it be designed with security at the forefront. This research aims to shed light on one of the possible ways that having a centralized point of failure in the network can provide malicious attackers an avenue to disrupt an entire enterprise network. Two experiments are performed. The first experiment confirms a vulnerability in a hardware switch discovered during this research. The second, to see if generating fake malicious software switches on the network is enough to inflate the Java Virtual Machine Heap to capacity and cause the controller to crash. These tests are conducted using enterprise grade servers and Software-Defined Networking enabled hardware switches. All trials conducted to confirm the discovered vulnerability resulted in a 100% success rate and revealed the cause of the vulnerability is due to the switch not following standards set forth by the Open Networking Foundation. The experiment performed to test the possibility of inflating the JVM Heap to capacity resulted in a 0% success rate. However, prolonged intermittent Denial-of-Service is achieved by causing the Garbage Collector to stop performing Young Generation Garbage Collections and to perform Full Garbage Collections exclusively. This transition to exclusive Full Garbage Collections is a result of the attack inflating the heap memory allocated to the Floodlight controller. The system reaches a point where the only way the Garbage Collector can keep the heap from running out of memory is by performing Full Garbage Collections. Moreover, the execution of Full Garbage Collections grew in both frequency and
In-Kernel Memory-Mapped I/O Device Emulation

Device emulation is a common necessity that arises at various steps of the development cycle, hardware migration, or reverse-engineering. While implementing the algorithms behind the device may be a nontrivial task by itself, connecting the emulator to an existing environment, such as drivers intended to work with the actual hardware, may be no less complex. Devices relying on memory-mapped input/output are of a particular interest, because unlike port-mapped input/output there is much less of a chance that the target platform provides a direct interface to intercept the transmissions. A well-known approach used in various virtual machine software is to put the entire operating system under a hypervisor and build the emulator externally. This may not be desirable for reasons like hypervisor complexity, performance loss, and additional requirements for the host hardware. In this paper we extend this approach to the kernel and explain how it may be possible to build the emulator by relying on the existing interfaces provided by an operating system. Given the common availability of an MMU unit as well as memory protection mechanisms, allowing the handling of page or segment traps at read or write access, we presume that a suggested technique of intercepting memory-mapped input/output could be implemented in a broad number of target platforms. To illustrate the specifics and show potential issues we provide the ways to simplify the implementation and optimize it in speed depending on the target capabilities, the protocol emulated, and the project requirements. As a working proof we created a SMC emulator for an x86 target, which makes use of this approach.
Réflexion à partir d’une étude comparative France-Japon sur l’articulation entre les aspirations professionnelles et les contextes sociétaux

Ce texte a pour objet de confronter, entre la France et le Japon, les perceptions qu’ont les employes de cette activite, du point de vue des conditions de travail et d’emploi, puis de comparer leurs choix de parcours professionnels qui se dessinent comme consequences de ces perceptions. Il s’agit, en l’occurrence, de s’interroger sur les determinants du choix de mobilite ou de stabilite que font les teleconseillers. Pour ce faire, nous les avons interroges, par questionnaire, sur leurs projets de parcours professionnel, en particulier sur leur intention de rester dans le CC au sein duquel ils travaillent ou de le quitter. La comparaison entre les deux pays se justifie, non seulement par son caractere heuristique -base meme de la science sociale-, mais aussi par une interrogation sur l’universalite du modele d’activite des CCs. Tant standardisee sur le plan des technologies, des modes operatoires et de la procedure organisationnelle comme chaine de montage, cette activite mobilise-t-elle de la meme maniere les ressources humaines dans les deux pays ? Ou le meme type de technologies est-il utilise differemment par les employes qui inventent diversement des astuces de contournement des contraintes ? L’usage des memes techniques entraine-t-il les memes effets ? Ce vieux debat sur le determinisme technologique meriterait aussi quelques elements de reponses dans un contexte renouvele de l’economie de services.
Seasonal radial growth of black pine (Pinus nigra Arnold) from Bosnia and Herzegovina, monitored by the pinning method and manual band dendrometers

Despite numerous dendroclimatological investigations into different tree species from Bosnia and Herzegovina, information is lacking on intra-annual wood formation patterns, which would help us to interpret the climate signal in tree rings better. Using the pinning method and manual band dendrometers, we investigated the seasonal dynamics of radial growth of black pine (Pinus nigra Arnold) trees in two successive growing seasons: 2011 and 2012. The up to 60-year-old trees grew in a stand at the base of a hill in the western, mountainous part of the Balkan Peninsula. The seasonal dynamics of wood formation and final number of cells differed between the studied years. Wood formation started in both years in early to mid-March. Differences were noticed in the wood production culmination; in 2011 it occurred at the end of May and beginning of June in 2012 and 2011, respectively. Xylem growth finished in 2012 in the middle of August and in 2011 in the middle of September. Based on the first derivative of the Gompertz function calculated rate of xylem growth was lowest in 2011. The dendrometers recorded a slow increment rate in spring, higher in summer and a decreasing rate again in the late summer in both growing seasons. In comparison with pinning, dendrometers showed a delay in the start of radial growth of up to 20 days in 2012. Additionally, dendrometers showed an increase in stem girth after the end of both growing seasons, when wood formation was already completed. Deviations between the two methods could be ascribed to the influence of water storage dynamics in the main stem and numerous structural processes in bark tissue, which are captured in dendrometer data. The influence of weather conditions on xylem phenology is also indicated by differences between the two studied years, although it is difficult to identify the influence of particular short-term weather events.
A REVIEW OF THE BALANCED SCORECARD IMPLEMENTATION IN HEALTH SECTOR ORGANIZATION

Background: Several studies reported that performance measurement using balanced scorecard is better than using traditional performance measurements . Balanced scorecard approach has been used in many health service sectors, both profit and non-profit, including hospitals, health service system, center for mental health, pharmacy services and health insurance company. This study aims to review the balanced scorecard implementation in health sector organization of the published literature from 2012 to 2019. Methods: This study was used literature review method by collecting data of the Balanced Scorecard in the health care sector and draws on the 6 years of published literature to January 2019. The literature were found from a search on Google Scholar as well as Thomson Reuters Web of Knowledge. The search terms were used “Balanced Scorecard”, “Health Balanced Scorecard” and “BSC” on English language only. The papers were classified by topics, research settings and research methods and data analysis techniques. Results: From 1465 papers were examined, 12 pieces of literature met inclusion criteria. From 12 pieces of literature have been reviewed, were used case study research method, eleven papers with qualitative research and one paper using the Delphi method. Based on 12 papers found that The balanced scorecard in health sector organization has been implemented in ICO, primary health care, hematology department, hospitals, home care nursing, health facilities, health systems, nutritional therapy company and clinical nutrition. Moreover, the Balanced Scorecard approach was used for health service budgeting, developing key performance indicators, improving hospital performance, assessing the baseline status, as an indicator in conducting evaluations. Conclusion: This study found that several studies consistently proved that Balanced scorecard is essential for performance and evaluation measurement in the health sector.
Stimulants of Profitability of Non-Bank Financial Institutions: Evidence from Bangladesh

Financial institutions both Bank and Non-Bank play a significant role in the economy of a country. Like other developing countries Beside the Banking industry necessarily of Non-Bank financial institutions cannot overlook in Bangladesh. This study inspects the profitability of firms in the Non-Banking Financial Institutions (NBFIs) diligence of Bangladesh. Financial Enactment of a financial organization fundamentally depends on its some key financial factors. Specially operating efficiency is main inducing factor which is designed through operating income. Besides it capital Structure combination of equity and liability, term deposit, total asset considerably affect the profitability of any NBFI company. In addition operating expense also upsets the profitability though that is not statistically significant. Different Statistical procedures such as correlation matrix, multiple regressions have been used to determine the associations between variables. And before doing regression analysis normality distribution test has been accomplished by One-Sample KolmogorovSmirnov Test. This research is an effort to find out the statistically significant key stimulants variable and their level of impact over net profit.
Small is beautiful but scalable is better. Scalable Marketing Decision Support Systems for Big Data calculations in CRM

«Small is beautiful» is often used to praise small, appropriate technologies that are believed to empower people more, and is opposed to "bigger is better". It is the title of a highly successful book on economics that reached millions (1973, 1999). E.F Schumacher, the author who took this phrase from his teacher L. Kohr, was interested not in smallness but in appropriateness of scale as a challenge to the 'too big to fail' showing premonition concerning the bank crisis we witnessed recently. Scalability is the capability of a system to grow or to handle a growing amount of work. It is analogous with economic scalability of a company implying that the underlying business model offers the potential for economic growth within the company. In IT, scalability is influenced by many factors, ranging from syntax details to component abstraction constructs, among which a subtle combination of object-oriented and functional programming is the most relevant. It is probably best embodied in a relatively new computer language called Scala. While objectorientation is immensely successful since the sixties, functional programming enjoyed less “glamour”. By exaggerating a bit, its usefulness became obvious with the advent of the “MapReduce” approach which has revolutionized and democratized BigData solutions and is fundamentally a functional programing concept. For marketing managers who often feel shipwrecked in a see of data “Data, data everywhere and not a byte to use”, scalable Marketing Decision Support Systems (MDSS) can help transpose the often “small and beautiful” models, that have already been developed or used in marketing science, to new BigData problems. In our paper we address this challenge by introducing scalable MDSS based upon open-source solutions as the recent Apache Spark BigData solution written in Scala that takes MapReduce to the next level by flexibly chaining richer functional expressions as Directed Acyclic Graphs (DAGs) and introducing Resilient Distributed Datasets (RDDs) that make calculations up to 100 times faster. Applications to customer data base predictive modeling will be developed and performance gains will be tested.