Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Flow Table Management Of Flow Entry In Openflow Switch/Router

— In OpenFlow switch, a limited number of row entries can be stored in the flow table, to the maximum of its capacity. Once its maximum capacity is reached, one has to remove one of the entries to accommodate the new entry. This paper proposes a mechanism to remove the entry from the flow table of OpenFlow switch, which uses the combination of less frequently used and least recently used. Removed entries are stored in a separate cache memory. Since OpenFlow switch has multiple row table, any one of the tables can be utilized for this approach. Instead of approaching the controller for every new packet, the entry can be looked up in the cache table. For inserting any new entry into the flow table, it will be searched in the flow table. If it is not found in the flow table called as table miss. Then it can be searched in the cache table. The experimental results show that the proposed approach gives an average performance improvement (in terms of table miss) of 13.87% and 13.88% against LRU and LFU. This approach reduces the frequent interaction between OpenFlow switch and the controller. The experimental results also show that proposed approach reduces the controller interaction by 17% and 15% more than LRU and LFU approaches.
Analysis Of Security Requirements In The Context Of Edge Computing

— Billions of objects are being connected to the internet which makes the internet of things reality. Connected devices exchange a huge amount of data that should be processed with low latency. Cloud computing processes data on a centralized way which involves several issues such as technical issues and a single point of failure. Fog and edge computing may be considered as complementary to cloud computing. However, considering the heterogeneity of IoT objects and the large number of connected devices, data security is a must. This paper investigates the security challenges of edge computing and unveils a security model that presents the security requirements with respect to the IoT challenges.
Zika and microcephaly: from the scientific discovery by Fiocruz to the institution’s Facebook

The theme zika/microcephaly was one of the most relevant subjects in the Brazilian national news in the summer of 2015/2016 and raised important issues to be considered by the fields of health communication and science communication, such as the validation of discourses by science, limitations of knowledge scientific, the rise of information of doubtful veracity and its consequences, among others (AGUIAR, ARAÚJO, 2016). As a public institution for research and health promotion, the Oswaldo Cruz Foundation (Fiocruz) played a prominent role in this scenario for its research and scientific results and, from a communication point of view, used its Facebook page for a more direct interaction with the population (despite his media advisory efforts and presence of the media-mediated institution).
Improved Black-Box Constructions of Composable Secure Computation

We close the gap between black-box and non-black-box constructions of composable secure multiparty computation in the plain model under the minimal assumption of semi-honest oblivious transfer. The notion of protocol composition we target is angel-based security, or more precisely, security with super-polynomial helpers. In this notion, both the simulator and the adversary are given access to an oracle called an angel that can perform some predeﬁned super-polynomial time task. Angel-based security maintains the attractive properties of the universal composition framework while providing meaningful security guarantees in complex environments without having to trust anyone. Angel-based security can be achieved using non-black-box constructions in max( R OT , e O (log n )) rounds where R OT is the round-complexity of semi-honest oblivious transfer. However, current best known black-box constructions under the same assumption require max( R OT , e O (log 2 n )) rounds. If R OT is a constant, the gap between non-black-box and black-box constructions can be a multiplicative factor log n . We close this gap by presenting a max( R OT , e O (log n )) round black-box construction. We achieve this result by constructing constant-round 1-1 CCA-secure commitments assuming only black-box access to one-way functions.
Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Are the Intraday Effects of Central Bank Intervention on Exchange Rate Spreads Asymmetric and State Dependent?

This paper investigates the intraday effects of unannounced foreign exchange intervention on bid-ask exchange rate spreads using official intraday intervention data provided by the Danish central bank. Our starting point is a simple theoretical model of the bid-ask spread which we use to formulate testable hypotheses regarding how unannounced intervention purchases and intervention sales influence the market asymmetrically. To test these hypotheses we estimate weighted least squares (WLS) time-series models of the intraday bid-ask spread. Our main result is that intervention purchases and sales both exert a significant influence on the exchange rate spread, but in opposite directions: intervention purchases of the smaller currency, on average, reduce the spread while intervention sales, on average, increase the spread. We also show that intervention only affects the exchange rate spread when the state of the market is not abnormally volatile. Our results are consistent with the notion that illiquidity arises when traders fear speculative pressure against the smaller currency and confirms the asymmetry hypothesis of our theoretical model. Danmarks Nationalbank. We thank Danmarks Nationalbank for providing the official intraday intervention data. The views in this paper are those of the authors and do not necessarily reflect the views of the Danmarks Nationalbank, the Federal Reserve Bank of Dallas or the Federal Reserve System.
Impact of endogenous canola phenolics on the oxidative stability of oil‐in‐water emulsions

The aim of this study was to evaluate the antioxidative effect of phenolics naturally present in canola seeds and meal. Individual phenolics were extracted from ground, defatted canola seeds, and meal. Fractionated extracts rich in sinapic acid, sinapine, or canolol as well as a non-fractionated extract were used. These extracts (100 and 350 µM) were evaluated as antioxidants in stripped canola oil-in-water (o/w) emulsion. For comparison, the antioxidative effect of phenolic standards for sinapic acid and sinapine (as sinapine thiocyanate) and butylated hydroxytoluene (BTH) as a positive control were also evaluated. The concentration of lipid hydroperoxides and selected volatiles measured at different time points was used to evaluate the antioxidative effect. Moreover, the properties of extracts and corresponding phenolic standards were evaluated in three different in vitro antioxidant assays. All extracts and standard antioxidants had radical scavenging activity and reducing power. The antioxidant standards and extracts inhibited lipid oxidation in the emulsions compared to no antioxidant added. At 100 µM the effectiveness of the extracts was as follows: sinapine>whole extract>sinapic acid>canolol>Con2 (no antioxidant). At 350 µM the ranking was as follows: canolol ≥ sinapine ≥ whole extract ≥ sinapic acid > Con2. Sinapine and sinapic acid extracts were more efficient antioxidants than the corresponding pure standards. However, the most efficient antioxidant in this study was BHT. The differences in effectiveness may be ascribed to mainly the different chain attached to the phenolic ring, which results in different polarity and thus different location in the emulsions. Practical applications: The result showed stronger antioxidant activity of canola extracts than phenolic standards. Therefore, these canola extracts can be used for protecting canola oil emulsion or other emulsions against lipid oxidation. However, the results indicate that the antioxidant activity of the extracts rich in sinapine and canolol had a concentration-sensitive effect. In order to get the best antioxidative effect, optimization of the concentration to be used for each specific application is necessary.
GRPW-MS: Geographic Routing a Mobile Sink in WSNs

In this paper we present an enhancement to the GRPW algorithm for wireless sensor networks. Performance of GRPW algorithm algorithm depends heavily on the immobile sink node position . This prediction can be hard to do. For that reason, we propose a modiﬁed algorithm that is able to adapt to the current situation in the network in which the sink node considered mobile. In this paper, in line with our previous efforts, we investigate the approach that makes use of a mobile sink for balancing the trafﬁc load and in turn improving network lifetime . Simulations were performed on GRPW as well as on the proposed Routing algorithm. The efﬁciency factors that were evaluated was total number of transmissions in the network and total delivery rate. The simulation results show that a the proposed Routing algorithm in some cases could outperform the existing algorithm. And in general the proposed Routing algorithm may perform reasonable well for a large number network setups.
Comprehensive Review Of Social Entrepreneurship: Developing The Conceptual Framework For Describing The Phenomenon Of Social New Venture Creation

This conceptual paper is comprehensive reviews of the related literature of the social entrepreneurship phenomenon. The study of entrepreneurship, especially in new venture creation, has gained the attention of previous researchers because of contribution to the development of the country towards GDP, job creation, innovation, and social values creation. This study is trying to develop the conceptual framework for describing the phenomenon of social entrepreneurship from various theoretical lenses. The study of social entrepreneurship is still premature, particularly the process of new venture creation. Therefore, the purpose of this paper is to critically review how four elements of Gartner theory that contribute to the emergence
Removal Of Malachite Green Dye By Peanut (Arachis Hypogaea) Shell Biochar: Optimisation Using Response Surface Methodology

Malachite green is a common dyeing agent used in various industries although it had brought detrimental effect towards the ecosystem. Thus, removal of MG from wastewater is crucial to prevent environmental pollution. In this study, malachite green removal using peanut shell biochar was being investigated. The experiments were designed in two methods: classical and optimization by response surface methodology with the employment of central composite design. Three parameters that involved in the study are contact time, pH and initial dye concentration. Based on central composite design, quadratic model was suggested for both responses which are malachite green removal and adsorption capacity. Analysis of variance (ANOVA) was applied in this study to identify the parameters that influence significantly towards the responses. The quadratic model obtained for both of the response proved that actual values were in good agreement with the predicted values with R2 value of 0.98 for malachite green removal and R2 value of 0.9794 for adsorption capacity. The optimum conditions predicted by respond surface methodology for malachite green removal was 97.33% at desirability of 1 with the conditions of 29.71 minutes contact time, pH 7.4 and initial dye concentration of 35.18 mg/L. At the meanwhile, the optimum conditions for adsorption capacity was 91.982 mg/g at desirability of 0.991 with the conditions of 30 minutes contact time, pH 8 and initial dye concentration of 60 mg/L.
Nanostructure of Amorphous Materials Using Electron Cross-Correlation Analysis

The microscopic knowledge of structures of materials is mainly based on information gained from the diffraction of photons, electrons or neutrons. These techniques allow the determination of the structure of most, even complex, crystalline materials. Also defects in crystalline material can be analyzed with high precision. Advanced HRTEM allows the determination of the positions of atom columns with pm accuracy. In contrast, for disordered matter the only accessible structural information (by standard diffraction) is the distribution function of distances between pairs of atoms, the so-called pair distribution function [1]. The reason for the missing bond angle information is the implicit ensemble and time average, which is involved in diffraction, based on a chaotic source. Ensemble averaging can be avoided if the coherence volume of a partially coherent electron beam (or X-ray beam) is equal to the illuminated sample volume. In this case all photons scatter in phase. By forming higher order correlation functions it is possible to access and classify the otherwise hidden local bond-orientational order as well as the medium-range order (MRO) in disordered matter. Bond-angle information requires the correlation of at least three different “molecules” in the sample. Fluctuation electron microscopy (FEM) as well as X-ray cross correlation analysis (XCCA) investigate the higher order correlations. FEM is most suited to study the MRO in glasses [2, 3]. Recently, XCCA experiments evidenced the existence of icosahedral symmetries in colloidal glasses [4]. In this paper the concept of XCCA will be applied to FEM. This should allow the testing of local symmetries, e.g., in metallic glasses.The mechanical properties of metallic glasses (MG) are largely dependent on their nanoscale structural ordering. Many studies have been completed on the short-range order of metallic glasses, indicating a preference for icosahedral-type short-range order. However, the prevalent nanostructure present at medium range length scales in most metallic glasses remains a debate. Cu-Zr binary metallic glasses are good glass formers over a large composition range and serve as a useful model system to study medium-range structural order in metallic glasses. The Cu-Zr MGs are predicted to be comprised of networks of icosahedra, with the highest concentration of interconnected icosahedra occurring at Cu65Zr35 [5]. However, other studies have shown evidence of planar-type ordering [2] related to the FCC structure of copper.
ASSESSING DAIRY CATTLE HEALTH WORLDWIDE

There is a large variation in the health status of dairy cattle worldwide. This variation on the one hand is partly due to differences in the occurrence or recurrence of diseases which are epidemic in nature. Examples are FMD, brucellosis, tuberculosis, and tick-borne diseases like anaplasmosis, cowdriosis, theileriosis (Preston & Jongejan, 1999). A lack of prevention and control programs for such diseases or failures in such programs contribute to these differences. Lack of control and control failures may be caused by e.g. political, geographical, wildlife-related, financial and socioeconomic limitations. They may be further hampered by certain dairy cattle husbandry practices like transhumane, subsistence or community farming, while high cattle densities (sometimes in conjunction with high density of other livestock) will contribute to a potentially rapid spread of highly contagious diseases, once introduced into an area.
Learning Causal Networks via Additive Faithfulness

In this paper we introduce a statistical model, called additively faithful directed acyclic graph (AFDAG), for causal learning from observational data. Our approach is based on additive conditional independence (ACI), a recently proposed three-way statistical relation that shares many similarities with conditional independence but without resorting to multi-dimensional kernels. This distinct feature strikes a balance between a parametric model and a fully nonparametric model, which makes the proposed model attractive for handling large networks. We develop an estimator for AFDAG based on a linear operator that characterizes ACI, and establish the consistency and convergence rates of this estimator, as well as the uniform consistency of the estimated DAG. Moreover, we introduce a modiﬁed PC-algorithm to implement the estimating procedure eﬃciently, so that its complexity is determined by the level of sparseness rather than the dimension of the network. Through simulation studies we show that our method outperforms existing methods when commonly assumed conditions such as Gaussian or Gaussian copula distributions do not hold. Finally, the usefulness of AFDAG formulation is demonstrated through an application to a proteomics data set.
Appraising the Research Trend of Energy Utilization Problem in Cellular Network

The dependency of the cellular or mobile network is increasing exponentially with the growth of dynamic demands of the mobile users globally. There is a huge trade-off between the energy consumption and service enhancement in present and upcoming future cellular network services and technologies. In order to cater up extensive coverage area, the energy required by the base station and its associated components needs to expend a good amount of energy. This paper has identified a problem of energy consumption over the usage of the cellular network, which the massive numbers of increasing mobile users are facing at present. Therefore, this paper performs a thorough investigation about the contribution being made by the prior researchers pertaining to address energy problems along with investigating of the existing research trends. The findings of the paper will highlights the techniques adopted by them and will also showcase the associated research gap from the existing studies.
What are you retiring for? Health consequences in early aging country

Using Russia Longitudinal Monitoring Survey (RLMS-HSE) data from 1994 to 2013, this study investigates the impact of retirement on health in Russia. The Russian case is remarkable due to relatively low life expectancy and low retirement age. Assessing the effect of retirement on health is challenging because causality also runs in the opposite direction as poor health could lead to earlier retirement. The baseline identification strategy is based on the instrumental variables method that helps to overcome the endogeneity problem. To instrument retirement, I use the eligible retirement age that varies for different categories of employees. I also apply data on retirement expectations from previous waves of the panel and spouse’s labor market participation as additional instrumental variables. The results show significant health-reducing effects of retirement. This effect is observed only for full retirees and does not exist for those who move into part-time retirement. The result is robust to applying different health measures and adjusting for attrition bias. The effect of retirement on health is most significant for males, highly educated, married individuals, those living in urban area, and individuals with low initial health level. JEL Codes: J26, J14, I10
Review on Neural Networks for Face Recognition

— Face recognition becomes more important in our daily life for various purposes like securing important and personal data, security for a restricted area, for banking purpose and other online applications. Neural network plays a major role in face recognition. In case of face recognition, neural networks were used for different stages like feature extraction, prediction and classification individually as well as for both. After neural network, convolutional neural network was developed and now it is deep convolutional neural network which makes face recognition very simple and easier. This paper gives the detailed survey on neural networks and its contribution to face recognition in various researches since neural network to current deep neural network
83-96 Carmichael Sum 09.indd

The navy of Athens during the democratic period (ca. 480–322 BCE) was largely financed and managed by wealthy citizens who undertook a public service, or liturgy, to maintain a warship for a year. With reference to a model of decisions made by the citizens eligible to undertake the liturgy, the author argues that the successive reforms to the institution were designed in ways and introduced at times to preserve its potential both to raise revenue and to remain popular. The first and second reforms performed these tasks by increasing the incentives for the citizens most willing to spend their money to undertake the liturgy; the third did so by reducing free riding.
Surgery and Guillain-Barré Syndrome: A Single-Center Retrospective Study Focused on Clinical and Electrophysiological Subtypes

Background Surgery-related Guillain-Barré syndrome (GBS) is often underestimated and sometimes difficult to diagnose. This study aimed to elucidate the clinical features and electrophysiological subtypes of post-surgical GBS. Methods We retrospectively reviewed 17 patients who developed post-surgical GBS after a recent surgery between 2015 and 2019. Clinical characteristics, electrophysiological examinations, lumbar puncture results and prognosis were assessed. As controls, we selected 66 patients hospitalized with non-surgical GBS. Results The median duration from the surgery to the onset of GBS symptoms was 16.0 days. The main types of surgeries preceding GBS were orthopedic, gastrointestinal and neurosurgery. Symmetrical distal limbs weakness was present in all 17 post-surgical GBS patients. The incidence of respiratory failure, autonomic dysfunction and muscle atrophy in post-surgical GBS patients was significantly higher than that in non-surgical GBS patients. Hughes Functional Grading Scale (HFGS) scores were also higher in the post-surgical GBS group both at the time of peak disease and 6 months after discharge. Electrophysiological studies revealed significant motor amplitudes reduction with relative preserved nerve conduction velocities and distal latencies, suggesting axonal subtypes of GBS. Conclusion GBS should be considered in patients with rapidly progressive muscle weakness after surgery. Such patients often exhibit axonal subtypes of GBS with severe motor dysfunction, high risk of respiratory failure, and poor prognosis.