Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Shared Memory for NoC-based MPSoCs Tales

The architecture of anMPSoCmay be composed of elements such as: PEs, memory elements and a communication infrastructure.According to [1], one of the most critical components that determine the success of an MPSoC is its memory system. This assertion justifies itself by the fact that applications might spend several cycles waiting for the conclusion of a given memory operation. One approach to decrease the gap of speed between processing elements and memory elements, a solution commonly applied in high-end microprocessors is the use of static memories and the concept of memory hierarchy. In general-purpose systems, there usually exist four levels of memory: level 1 cache, level 2 cache, main memory and secondary memory. Cache memories can provide an acceptable data rate to feed the processor, maximizing the number of instructions that are executed in a certain period. Caches work as temporary, fast access memories that prevent the processors to sit idle while waiting for an instruction or data from slower memories. Another interesting point in the use of caches is the possibility of reducing energy consumption. As most memory accesses are done locally at the cache, transferring data on a bus/network-on-chip from slower memories are avoided. Despite the advantages, some problems related to the use of cache memories must be addressed. According to [2], data residing in a cache bank located near to the processor could be accessed much faster than data that reside in a bank physically farther from the processor. The nearest processor’s cache bank, in a 16-megabyte, on-chip L2 cache, built in a 50-nanometer process technology, could be accessed in 4 cycles, while an access to the farthest cache bank might take 47 cycles. This difference is caused due to wire latency. Therefore, as the manufacturing technology advances, the number of cycles to retrieve data from further cache banks increases. Additionally, the use of cache memories in MPSoCs creates the problem of cache incoherence. To avoid incoherence, a cache coherence protocol must be implemented.
Home Automation with IQRF Wireless Communication Platform : A Case Study

This paper describes a new wireless communication platform IQRF. In the paper is description of main features of the platform, available communication modules, gateways to other wired and wireless communication system, and development tools. The paper also describes a case study focused on IQRF Smart house concept. IQRF platform was designed and developed especially for home automation and
Vibration Analysis of a Vertical Axis Wind Turbine Blade

The motivation for this project arose from an expected vibration source of a small-scale vertical axis wind turbine currently undergoing field-testing. The turbine consists of three 3 metre long vertically aligned blades each fixed to the central shaft by two horizontal arms and separated from one another by an angle of θ=120o. The blade profile is a NACA 0015 with a chord length of 0.4 metres fixed at zero angle of attack to the support arms. The turbine optimally operates at a blade-tip speed ratio (the ratio of the blade rotational velocity to the ambient wind velocity) of 1.6. As the blades turn about the central shaft, they encounter an incident wind that is composed of the ambient wind and the wind due to rotation (Fig. 1). This incident wind results in lift and drag forces on the blades resulting in both a thrust force and a radial force on the turbine arms. Note: In this paper, lift is defined as the force perpendicular to Uwind, and drag is defined as the force parallel to Uwind.
Simultaneous unsupervised and supervised classification modeling for clustering , model selection and dimensionality reduction

In the unsupervised classification field, the choice of the number of clusters and the lack of assessment and interpretability of the final partition by means of inferential tools denotes an important limitation that could negatively influence the reliability of the final results. In this work, we propose to combine unsupervised classification with supervised methods in order to enhance the assessment and interpretation of the obtained partition, to identify the correct number of clusters and to select the variables that better contribute to define the groups structure in the data. An application on real data is presented in order to better clarify the utility of the proposed approach. Abstract Nella classificazione non supervisionata, la scelta a priori del numero ottimale di gruppi da considerare e la mancanza di interpretazioni inferenziali, rappresenta un grosso limite per questi modelli. In questo lavoro, proponiamo la combinazione di modelli di classificazione non-supervisionata e supervisionata per identificare il numero ottimale di gruppi da considerare, selezionando le variabili che incidono in modo significativo sulla partizione trovata. E’ prevista un’applicazione su dati reali.
In Search of Peace of Mind : Who Exactly Utilize Financial Advice ?

Using data from about 290,000 household investment accounts for 2005-2014, we provide a comprehensive analysis of the role of economic and demographic characteristics in determining the tendency to utilize financial advice. Our findings indicate that age, gender and family status are strongly associated with the tendency to use advice. Women, widowed and married couples are more likely to seek financial advice. In addition, while trading experience and occupational complexity are negatively correlated with the use of financial advice, a home bias is positively associated with doing so, implying that less sophisticated investors are more likely to utilize financial advice. The findings are robust under different distributions of the data. Finally, we also test how macroeconomic uncertainty, reflected by the VIX, affects the tendency to utilize financial advice. Our results demonstrate that higher levels of financial uncertainty are associated with less use of financial advice. This finding supports the avoidance of information theory.
Exploring Codata : The Relation to Object-Orientation

Functional languages are known to enjoy an elegant connection to logic: lambda-calculus corresponds to natural deduction. Unfortunately, the same cannot be said for object-oriented languages. Type systems have been designed to capture all the fancy features present in current object-oriented languages. We believe, however, that the logical foundation of object-orientation has not yet been fully explored. Our goal is to describe how objects arise naturally in logic. The dual of data, known as codata, can be seen as an object. Whereas data is constructed, codata specifies all the possible ways to use it. Analogously to an object defining a pair, a codata pair gives two methods for accessing the first and second components. To substantiate this approach we extend a basic language containing both data and codata with the essential object-oriented features of subtyping, classes, and inheritance. This suggests how the functional and objectoriented paradigms can embrace each other; the extended language also provides a suitable intermediate language for the compilation of the two programming paradigms.
A novel method of vertical axis wind turbine noise prediction

Vertical Axis Wind Turbines are becoming more commonplace in urban environments but to date there has not been much computational work done to quantify their noise outputs. The EU FP7 project: SWIP (New innovative solutions, components and tools for the integration of wind energy in urban and peri-urban areas) aims to deal with, and overcome, the main barriers that slow down the largescale deployment of small and medium size wind turbines. One of the outputs of the project is a novel, six bladed, vertical axis wind turbine rated at 2kW. This work aims to predict aeroacoustic noise generated by the SWIP vertical axis wind turbine by means of a novel noise prediction method. Due to the high computational cost of LES an approach is proposed in which ANSYS Fluent is used to determine the transient flow solution, using unsteady RANS calculation, on a 2D section of the wind turbine undergoing rotation. Acoustic signals are calculated by employing a MATLAB code which uses the CFD solution as input data into a semi-empirical solver based a number of airfoil noise prediction algorithms. The 2D CFD data is interpolated onto a 3D model of the turbine using a quasi-steady time stepping approach. An estimate of the aeroacoustic noise of the turbine is established and the sensitivity of the code to changes in time step and discretisation is considered.
Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy Dovepress

php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2019:12 191–198 Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy Dovepress
The effects of latent myofascial trigger points ( LTrPs ) in the scapular rotator muscles on the temporal sequence of muscle recruitment during loaded scapular plane elevation

It has been suggested that chronic shoulder pain is associated with altered timing in the onset of muscle activity of the scapular rotator muscles (Wadsworth and Bullock-Saxton, 1997). It is also understood that the scapula relies upon the appropriate action of the scapular rotator muscle group, which acts to dynamically stabilise the scapula and the glenoid during elevation of the arm, to perform its role in force transfer from the trunk to the upper limb (Kibler, 1998). However, it is not known whether a pain-free muscle dysfunction, such as latent myofascial trigger points (LTrPs), in the scapular rotator muscles affects the timing of scapular muscle activation during elevation in the scapular plane or subsequently, what effect this has on the timing of activation of muscles more distal in the kinetic chain of the upper limb.
Research on Constructing Effective Patent Early Warning Mechanism in Central Region of China

In this text, taking reviews on the research literature of the domestic academic circle on patent early warning mechanism , the foreign cases of effective patent early-warning mechanism are analyzed, patent the current work of early warning in central region is discussed, finally constructing a effective path of early warning mechanism patent suited for central area was studied, and putting forward the principle of establishing the patent early warning mechanism, the text puts forward establishing a patent early warning mechanism of effective mode.
OVERLAPPING DECOMPOSITIONS-BASED ROBUST DECENTRALIZED TABU SEARCH-OPTIMIZED FIXED STRUCTURE H ∞ FREQUENCY STABILIZER DESIGN IN INTERCONNECTED POWER SYSTEMS

As interconnected power systems are subjected to load disturbances with changing frequency in the vicinity of the inter-area oscillation mode, the system frequency may severely oscillate. To stabilize frequency oscillation, the dynamic power flow control devices can be exploited. This paper focuses on a new robust decentralized fixed structure H∞ frequency stabilizer design of power control devices based on overlapping decompositions. The tie-line between two interconnected systems can be treated as the overlapped variable so that the original system can be decomposed into two subsystems. The frequency stabilizer equipped with the power control device can be designed in each subsystem independently. The structure of frequency stabilizer is specified as the 2 -order lead/lag compensator. To augment the system robust stability, the multiplicative uncertainty is employed to represent all unstructured system uncertainties. As a result, the multiplicative stability margin (MSM) can be used to guarantee the system robust stability. The control parameters of frequency stabilizer are optimized by a tabu search, so that the desired damping ratio of the target inter-area mode and the highest MSM are achieved. Two examples of power flow devices, i.e., high-voltage direct current transmission system and superconducting magnetic energy storage, are used to show the high performance and robustness against load disturbances and system parameters variation.
Early Stage Assessment Report Akinwande

Packet switching is the more preferred strategy for communication in computer networks compared with the other popular circuit switching, due to its more efficient use of network resources. In circuit switching, a dedicated circuit in the network is first established between two nodes/hosts requiring a connection before communication begins. Because this circuit is maintained throughout the duration of the connection, network resources will be considered wasted during idle periods when messages are not being transmitted. Also, the dedicated circuit for the connection cannot be shared with other connections in the network. In a packetswitched network, messages are broken into smaller blocks called packets, which are routed independently through multiple intermediate nodes towards a destination node, where they are then re-assembled correctly into the original message. This approach allows for network resources to be shared by different connections, for example, in a first-come-first-serve manner.
he reliability of a composite biodiversity indicator in predicting bird pecies richness at different spatial scales

Several biodiversity features can be linked to landscape heterogeneity, that, in turn, can be informative for management and conservation purposes. Usually, the more the landscape is complex the more the biodiversity increases. Biodiversity indicators can be a useful tool to assess biodiversity status, in function of landscape heterogeneity. In this study, we developed a biodiversity indicator, based on Shannon diversity index and built from distribution maps of protected species. With such an approach, we seek to evaluate the feasibility of using a combination of target species as a surrogate for assessing the status of the whole bird community. Our approach was spread over multiple spatial scales, to determine which was the most informative. We selected four species protected by European regulation and generated a presence-absence map from species distribution modelling. We, therefore, used the FRAGSTATS biodiversity metric to calculate Shannon index for the overlapped presence-absence maps, at two spatial scales (500 m and 1000 m). Then, the relationships with the whole community was assessed through generalised least square models, at the spatial scale of 4 ha, 9 ha and 25 ha. Results showed that the higher rate of variability of community was explained by the biodiversity indicator at 1000 m scale. Indeed, the more informative spatial scale for the whole bird community was 9 ha. In addition, a pattern emerged about the relationships between biodiversity indicator and community richness, that is worth of further research. Our study demonstrates that the usefulness of surrogate species for biodiversity and community assessment can become clear only at a certain spatial scales. Indeed, they can be highly predictive of the whole community, and highly informative for conservation planning. Moreover, their use can optimize biodiversity monitoring and conservation, focusing on a small number of noteworthy species. © 2016 Elsevier Ltd. All rights reserved.
The melanoma associated antigen 1 ( MAGEA 1 ) protein stimulates the E 3 ubiquitin ligase activity of TRIM 31 within

http://sro.sussex. ac.uk Kozakova, Lucie, Vondrova, Lucie, Stejskal, Karel, Charalabous, Panagoula, Kolesar, Peter, Lehmann, Alan, Uldrijan, Stjepan, Sanderson, Christopher M, Zdrahal, Zbynek and Palecek, Jan J (2015) The melanoma-associated antigen 1 (MAGEA1) protein stimulates the E3 ubiquitinligase activity of TRIM31 within a TRIM31-MAGEA1-NSE4 complex. Cell Cycle, 14 (6). pp. 920930. ISSN 1538-4101
Motivation factors of adult learning

Motivation is the driver of adult learning. The paper reveals the importance and peculiarities of adults’ learning process. There has been analyzed the impact of external and internal factors on the efficiency of adult learning; various approaches to the typology of intrinsic motivation are presented. The author has also considered the components of motivational sphere (emotional aspect, the set aims, the ability to learn), which can significantly influence the level of adult learning motivation.
C Y ] 1 2 Fe b 20 16 An Empirical Study on Academic Commentary and Its Implications on Reading and Writing

The relationship between reading and writing (RRW) is one of the major themes in learning science. One of its obstacles is that it is difficult to define or measure the latent background knowledge of the individual. However, in an academic research setting, scholars are required to explicitly list their background knowledge in the citation sections of their manuscripts. This unique opportunity was taken advantage of to observe RRW, especially in the published academic commentary scenario. RRW was visualized under a proposed topic process model by using a state of the art version of latent Dirichlet allocation (LDA). The empirical study showed that the academic commentary is modulated both by its target paper and the author’s background knowledge. Although this conclusion was obtained in a unique environment, we suggest its implications can also shed light on other similar interesting areas, such as dialog and conversation, group discussion, and social media.
Circulating RANKL , Osteoprotegerin and Breast Cancer Risk in BRCA 1 and BRCA 2 Mutation Carriers

Emerging evidence demonstrates the receptor activator of nuclear factor κB (RANK) signaling is of importance in BRCA-associated breast cancers. BRCA mutation carriers face a high lifetime risk of developing breast cancer and have been reported to have lower levels of osteoprotegerin (OPG) and RANK ligand (RANKL) compared to non-carriers. OPG has been associated with decreased breast cancer risk among mutation carriers in a small pilot study. Circulating RANKL has yet to be explored in this high-risk population. My thesis investigated the association between circulating OPG and RANKL and breast cancer risk in mutation carriers. There is a suggestive trend demonstrating an inverse association between circulating OPG and BRCA breast cancer risk. However, circulating RANKL levels are not predictive of BRCA breast cancer risk. OPG could be a novel biomarker for breast cancer risk among BRCA mutation carriers and may provide a novel target for chemoprevention.
Learning-Based Image Compression using Convolutional Autoencoder and Wavelet Decomposition

In this paper, a learning-based image compression method that employs wavelet decomposition as a preprocessing step is presented. The proposed convolutional autoencoder is trained end-to-end to yield a target bitrate smaller than 0.15 bits per pixel across the full CLIC2019 test set. Objective results show that the proposed model is able to outperform legacy JPEG compression, as well as a similar convolutional autoencoder that excludes the proposed preprocessing. The presented architecture shows that wavelet decomposition is beneficial in adjusting the frequency characteristics of the compressed image and helps increase the performance of learning-based image compression models.
HETEROGENEITY IN THE QUALITY-SATISFACTION-LOYALTY FRAMEWORK : A MULTI-GROUP ANALYSIS IN A BUSINESS-TO-BUSINESS BUYER NETWORK

Loyalty and satisfaction in business-to-business relationships benefits from a myriad of conceptualisations feeding the notion that securing buyer loyalty via customer satisfaction is critical for success. Equally as many studies have shown that the relationship between customer satisfaction and attitudinal loyalty is mediated by trust, commitment and the sharing of timeous and accurate information in the dyad. Far fewer studies have attempted to compare the results of these quality-satisfaction-loyalty models across different groups to account for heterogeneity across dyads. In this study we build on earlier work to empirically confirm the notion that relationship satisfaction leads to attitudinal loyalty and demonstrate that trust, commitment and information sharing mediates this relationship. We then compare the confirmed model across selected sources of heterogeneity originating from the variance in actors’ demographics and market characteristics. Our study employed a focal firm approach to consider a network of buyers in the South African Computer Aided Design (CAD) industry. Data was collected from 497 respondents and the empirical model was tested using variance based Structural Equation Modelling and Finite Mixture modelling. Our results show that the link between relationship satisfaction and attitudinal loyalty is fully mediated by trust and commitment. Our results also identify sources of heterogeneity based on gender, age, sector, managerial level and education. Beyond offering further support for the quality-satisfaction-loyalty causal chain, the study provides evidence of heterogeneity often characteristic of high context emerging markets. The findings provide researchers and practitioners with insights as to how dyadic relationship management practices may need to be altered for different groups and contexts.
Progressive Teacher-Student Learning for Early Action Prediction

The goal of early action prediction is to recognize actions from partially observed videos with incomplete action executions, which is quite different from action recognition. Predicting early actions is very challenging since the partially observed videos do not contain enough action information for recognition. In this paper, we aim at improving early action prediction by proposing a novel teacher-student learning framework. Our framework involves a teacher model for recognizing actions from full videos, a student model for predicting early actions from partial videos, and a teacher-student learning block for distilling progressive knowledge from teacher to student, crossing different tasks. Extensive experiments on three public action datasets show that the proposed progressive teacher-student learning framework can consistently improve performance of early action prediction model. We have also reported the state-of-the-art performances for early action prediction on all of these sets.
SPECIES RICHNESS AND COMPOSITION OF FERNS IN A FRAGMENT OF DENSE HUMID FOREST IN RIO GRANDE DO SUL , BRAZIL

A floristic survey of fern species was conducted in a fragment of Dense Humid Forest (29°24'59.23"S, 49°54'51.09"W) in Três Cachoeiras, RS, where life forms and substrate preferences were investigated. We found 37 species in 23 genera and 11 families, approximately 10% of Rio Grande do Sul’s fern species richness. Epiphytes were dominant, 14 of which were creeping. In addition, a 1ha plot in the study site was determined to compare its species richness and composition with same sized plots from different studies. In this plot we found 75% of the richness of the entire fragment. Considering this high concentration of species is recommended the inclusion of ferns, besides trees, when assessing alpha diversity for developing conservation plans for Atlantic Forest remnants. The occurrence of Cyathea corcovadensis (Raddi) Domin is highlighted, as it is an endangered species in the state.