Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining overlapping community structures within grain property networks

Granular materials (e.g, geological materials, powders and grains) when subjected to shear or compression deform through grain rearrangements. The structural topology of the grains, or fabric, can be usefully represented as a complex (contact) network whereby network nodes correspond to individual grains and network links correspond to grain contacts. Properties of each node (e.g, degree) can be calculated and throughout deformation this results in time series akin to sensor measurements for each grain in the assembly. These signals can be processed and collated into a particle property network with a corresponding community structure summarizing the relationship between each signal. Different properties give rise to different networks each with their own community structures, i.e, each network possesses the same set of nodes but a different link structure. The overlapping structure of these property network communities is of interest. We describe how the overlapping communities within networks constructed from properties related to grain behaviour with respect to multiscale cyclic structures is consistent with a power law description. Furthermore this behaviour is exhibited across a suite of computer simulations of compression tests which hints at possible universal features in the mechanical response of granular materials.
Vers un calcul en temps réel de la dose dans un fantôme segmenté en mailles homogènes. (Towards a real time computation of the dose in a phantom segmented into homogeneous meshes)

La planification automatique des traitements de radiotherapie necessite un calcul tres rapide de la dose delivree au patient. Nous proposons de realiser ce calcul en segmentant le fantome du patient en mailles homogenes, et en associant aux mailles des projections vers des distributions precalculees en milieux homogenes, ainsi que des ponderations gerant les heterogeneites. Le calcul de dose se fait en deux etapes. La premiere etape concerne les mailles : les projections et ponderations y sont parametrees en fonction de criteres physiques et geometriques. La seconde etape concerne les voxels : la dose y est calculee en evaluant les fonctions prealablement associees a leur maille. Cette methode est tres rapide, notamment quand le nombre de points d'interet est limite (quelques centaines), les resultats etant dans ce cas obtenus en moins d'une seconde. Avec de telles performances, la planification automatique des traitements de radiotherapie devient parfaitement envisageable.
Hemoglobin A1c in Patients on Peritoneal Dialysis: How Should We Interpret It?

Almost half the patients on peritoneal dialysis are diabetic and glycemic control is essential to improve both patient and technique survival. Hemoglobin A1c (HbA1c) is widely used in the general population for diabetes diagnosis and monitoring as it highly correlates with blood glucose levels and outcomes. Its use has been extrapolated to the peritoneal dialysis population, despite HbA1c being commonly underestimated. In renal failure patients, HbA1c is influenced by variables affecting not only glycemia but also hemoglobin and the time of interaction between the two. Importantly, the impact of these variables differs in peritoneal dialysis compared to non‐dialysis chronic kidney disease and hemodialysis patients.
Effect of Mandatory IFRS Adoption on Cost of Debt in Turkey

The ultimate aim of financial reporting is the communication between companies and their stakeholders. To better serve this ultimate aim, International Accounting Standards Board (IASB) required all European Union listed companies to adopt International Financial Reporting Standards (IFRS) starting from January 1, 2005. Some of other emerging countries like Turkey also complied with this requirement. In this paper, whether mandatory adoption of IFRS in 2005 caused a decrease in average cost of debt of Turkish manufacturing firms or not is tested. A cross-section fixed effect panel model was employed for a data set of 138 companies and 646 firm-year observations between years 2002 and 2008. Results show that firms in the sample have a significantly lower cost of debt after adoption year. Moreover, while; firm size, current ratio, GDP growth and interest rates have a positive association with the cost of debt, tangibility and interest coverage have a negative effect on the cost of debt.
Adaptive Feedback Reduction for P-VQ in MU-MISO Downlink Precoding

In this study, an adaptive and variable-rate feedback reduction technique for partitioned vector quantization (P-VQ) in MU-MISO downlink precoding is proposed. Independent feed-back reduction is performed for both channel quality indicator (CQI) and channel direction indicator (CDI) over slowly-varying Rayleigh channel. The users adaptively reduce the feedback over-head for quantized channel state information (CSI) depending on the rate and direction of change in the correlated CQIs and CDIs. Simulation results show that the proposed scheme greatly lessens the communication overhead with very small performance loss and enhances the quantization efficiency.
Two salts of 5-sulfosalicylic acid and 3-aminopyridine.

5-Sulfosalicylic acid (5-SSA) and 3-aminopyridine (3-APy) crystallize in the same solvent system, resulting in two kinds of 1:1 proton-transfer organic adduct, namely 3-aminopyridinium 3-carboxy-4-hydroxybenzenesulfonate monohydrate, C(5)H(7)N(2)(+). C(7)H(5)O(6)S(-). H(2)O or 3-APy.5-SSA.H(2)O, (I), and the anhydrous adduct, C(5)H(7)N(2)(+). C(7)H(5)O(6)S(-) or 3-APy.5-SSA, (II). Both compounds have extensively hydrogen-bonded three-dimensional layered polymer structures, with interlayer homo- and heterogeneous pi-pi interactions in (I) and (II), respectively.
Vacuum‐Assisted Closure: A New Method for Wound Control and Treatment: Clinical Experience

Despite numerous advances, chronic and other difficult-to-man-age wounds continue to be a treatment challenge. Presented is a new subatmospheric pressure technique: vacuum-assisted closure (The V.A.C.). The V.A. C. technique entails placing an open-cell foam dressing into the wound cavity and applying a controlled subatmospheric pressure (125 mmHg below ambient pressure). Three hundred wounds were treated: 175 chronic wounds, 94 subacute wounds, and 31 acute wounds. Two hundred ninety-six wounds responded favorably to subatmospheric pressure treatment, with an increased rate of granulation tissue formation. Wounds were treated until completely closed, were covered with a split-thickness skin graft, or a flap was rotated into the healthy, granulating wound bed. The technique removes chronic edema, leading to increased localized blood flow, and the applied forces result in the enhanced formation of granulation tissue. Vacuum-assisted closure is an extremely efficacious modality for treating chronic and difficult wounds.
CASW : Context Aware Sliding Window for Frequent Itemset Mining over Data Streams

In recent years, advances in both hardware and software technologies coupled with high-speed data generation leads data streams and data stream mining. Data generation has been much faster in data stream applications and score of data is generated in quick turnaround time. Hence it becomes obvious to perform mining, data on arrival that is usually termed as data stream mining. General frequent pattern mining methods are envisaging limitations and do not support in responding to a massive quantum of data being streamed. In order to address such limitations, data mining researchers have focused on methods for conducting more efficient and effective mining tasks by scanning a database only once. As a process of evolution, sliding window model that perform mining operations focusing on updating accumulated parts over data streams, are proposed. It is hard to consider all of the frequent patterns in data stream environment as generated patterns were remarkably increasing as data streams get extended continuously. Hence, methods for efficiently compressing patterns that are generated are essential to address the limitations. Considering the challenges and shortcoming in the earlier solutions, in this paper, focus is on incremental mining of frequent patterns from the window and a solution of CASW (Context Aware Sliding Window) is proposed. There are well defined boundaries for frequent and infrequent patterns for specific patterns. In this research article, we adapt usage of window size change for 184 V. Sidda Reddy, T.V. Rao and A.Govardhn representing conceptual drift in the information stream. An experimental study carried out on the model depicts significant developments and has affirmed that the algorithm has been designed with a more efficient system than that of existing solution.
Linear dispersion codes

Multiple-antenna systems that operate at high rates require simple yet effective space-time transmission schemes to handle the large traffic volume in real time. At rates of tens of bits/sec/Hz, V-BLAST, where every antenna transmits its own independent substream of data, has been shown to have good performance and simple encoding and decoding. Yet V-BLAST suffers from its inability to work with fewer receive antennas than transmit antennas. Furthermore, because V-BLAST transmits independent data streams on its antennas there is no built-in spatial coding to guard against deep fades from any given transmit antenna. On the other hand, there are many previously-proposed space-time codes that have good fading resistance and simple decoding, but these codes generally have poor performance at high data rates or with many antennas. We propose a high-rate coding scheme that can handle any configuration of transmit and receive antennas and that subsumes both V-BLAST and many proposed space-time block codes as special cases. The scheme transmits substreams of data in linear combinations over space and time. The codes are designed to optimize the mutual information between the transmitted and received signals. Because of their linear structure, the codes retain the decoding simplicity of V-BLAST, and because of their information theoretic optimality, they possess many coding advantages. We give examples of the codes and show that their performance is generally superior to earlier proposed methods over a wide range of rates and SNRs.
Two challenges of Software Networking: Name-based Forwarding and Table Verification. (Deux défis des Réseaux Logiciels : Relayage par le Nom et Vérification des Tables)

Cette these aborde des problemes lies a deux aspects majeurs de l'evolution d'Internet : l'aspect«comportemental», qui correspond aux nouvelles interactions entre les utilisateurs et le reseau, et l'aspect «structurel», lie aux changements d'Internet d'un point de vue architectural.Le manuscrit est compose d'un chapitre introductif qui donne les grandes lignes de recherche de ce travail de these, suivi d'un chapitre consacre a la description de l'etat de l'art sur les deux aspects mentionnes ci-dessus. Parmi les solutions proposees par la communaute scientifique pour s'adapter a l'evolution d'Internet, deux nouveaux paradigmes reseaux sont particulierement decrits : Information- Centric Networking (ICN) et Software-Defined Networking (SDN). La these continue avec la proposition de «Caesar», un dispositif reseau, inspire par ICN, capable de gerer la distribution de contenus a partir de primitives de routage basees sur le nom des donnees et non les adresses des serveurs. Caesar est presente dans deux chapitres, qui decrivent l'architecture et deux des principaux modules : le relayage et la gestion de la tracabilite des requetes.La suite du manuscrit decrit un outil mathematique pour la detection efficace de boucles dans un reseau SDN d'un point de vue theorique. Les ameliorations de l'algorithme propose par rapport a l'etat de l'art sont discutees. „,La these se conclue par un resume des principaux resultats obtenus et une presentation des travaux en cours et futurs.
Excretion of endogenous and exogenous purine derivatives in sheep : effect of increased concentrate intake

The present study examined the endogenous urinary excretion of purine derivatives (PD; allantoin, uric acid and xanthine plus hypoxanthine) in fed animals. Four Rasa Aragonesa ewes fitted with simple cannulas in the rumen and proximal duodenum were used. Animals were given a lucerne (Medicago sat iva) hay diet, as sole feed (A) or supplemented, respectively, with 220 (B), 400 (C), and 550 (D) g rolled barley grain/d following a 4 x 4 random factorial design. Duodenal flow of purine bases (PB) was determined by the dual-phase marker system. 15N was infused continuously into the rumen to label exogenous or microbial PB. Duodenal PB flow and urinary excretion of PD increased with digestible organic matter intake showing a constant recovery of duodenal PB. The isotope dilution of PD in urine samples confirmed the presence of an endogenous fraction, originating from tissues, that increased from 115.2 (SE 5.84) pmol/kg @ 75 for the basal diet to 304.2 (SE 7.6) pmol/kg @'75 at the highest level of duodenal PB.
Working together: understanding value co-creation processes in professional service delivery

The starting point for professional service firm is actively participate in clients’ value co-creation processes to create unique value for clients. While prior studies focused on the concept of value co-creation and specifically not examined the context of professional services, the existing body of knowledge lacks empirical data on value co-creation, and consequently, does not provide sufficient practical insights for the service providers. This study addresses this gap in the research and aims to extend the understanding of processes of value co-creation between professional service firm and its clients. A case study result reveals seven value co-creation processes specific in professional service context performed by the client, the provider or executed in client-provider encounter. Value co-creation benefit and the possibilities for enhancing value co-creation between professional service firm and its client were analysed also. DOI: http://dx.doi. org/10.5755/j01.ee. 29.1. 18436
Random forests on distance matrices for imaging genetics studies

Abstract We propose a non-parametric regression methodology, Random Forests on Distance Matrices (RFDM), for detecting genetic variants associated to quantitative phenotypes, obtained using neuroimaging techniques, representing the human brain’s structure or function. RFDM, which is an extension of decision forests, requires a distance matrix as the response that encodes all pair-wise phenotypic distances in the random sample. We discuss ways to learn such distances directly from the data using manifold learning techniques, and how to define such distances when the phenotypes are non-vectorial objects such as brain connectivity networks. We also describe an extension of RFDM to detect espistatic effects while keeping the computational complexity low. Extensive simulation results and an application to an imaging genetics study of Alzheimer’s Disease are presented and discussed.
From ownership to access: How the sharing economy is changing the consumer behavior

Promoting the principles of circular economy and the new business models advocated by the circular economy can represent a solution for a more prosperous society, less dependent on primary and energy resources and more environmentally friendly. The sharing economy, which primarily involves the transformation of traditional market behaviors into collaborative consumption models, that ensure a more efficient and sustainable use of resources, is part of the circular economy and has generated business models that are compatible with it. This article discusses the possibility for the sharing economy to bring about profound changes in consumer behavior towards products and services and to highlight the factors that drive consumers’ shift towards the sharing economy. For this purpose we developed and tested a model in which the change in consumer mindset has as the main direct determinants the satisfaction with the services of the sharing economy and the intention to access such products and services. The study uses data collected through a questionnaire, applied to a sample of 320 customers of Uber – a symbol of the sharing economy, and processed using structural equation modelling. Research results show that there are premises for switching to an access-based consumption model.
Correlation between growth and physical fitness of socially disadvantaged girls

The intention of this study was to investigate the relationship between growth and physical fitness of girls between the ages seven and 18. The girls (N=302) were randomly selected from six randomly selected schools in an informal settlement in the Western Cape. Twenty anthropometric measurements were taken on each participant. Some of the measurements included heights, girths, skinfolds and breadths. Skinfold measurements were further used to calculate body composition and somatotypes. The following physical fitness components were included for assessment: flexibility (sit-and-reach test); grip strength (hand grip dynamometer); leg power (standing long-jump); speed (50m-sprint test); and cardiovascular endurance (three-minute step test). The relationship between growth and fitness characteristics was determined by means of a stepwise discriminant analysis. The participants were divided into ‘under 13’ and ‘13 and older’ groups and were used to establish differences in the relationships between growth and fitness. The analysis showed the prominence of weight and height as predictors of fitness parameters, especially strength, speed and leg power.
Hormonal correlates of individual quality in a long-lived bird: a test of the ‘corticosterone–fitness hypothesis’

Measuring individual quality in vertebrates is difficult. Focusing on allostasis mechanisms may be useful because they are functionally involved in the ability of an individual to survive and reproduce in its environment. Thus, a rise in stress hormones levels (corticosterone) occurs when an organism has to cope with challenging environmental conditions. This has recently led to the proposal of the ‘cort–fitness hypothesis’, which suggests that elevated baseline corticosterone levels should be found in individuals of poor quality that have difficulty coping with their environment. We tested this hypothesis by comparing an integrative measure of individual quality to baseline corticosterone in black-browed albatrosses (Thalassarche melanophrys). We found that individual baseline corticosterone levels were related to individual quality and highly repeatable from one breeding season to the next. Importantly, this relationship was found in males, but not in females. Therefore, we suggest that the relationship between quality and baseline corticosterone levels may depend on the environmental and energetic constraints that individuals have to cope with.
Climb or Jump: Status-Based Seeding in User-Generated Content Networks

This article addresses seeding policies in user-generated content networks by challenging the role of influencers in a setting of unpaid endorsements. On such platforms, the content is generated by individuals and firms interested in self-promotion. The authors use data from a worldwide leading music platform to study unknown music creators who aim to increase exposure of their content by expanding their follower base through directing outbound activities to other users. The authors find that the responsiveness of seeding targets strongly declines with status difference; thus, unknown music creators (the majority) do not generally benefit at all from seeding influencers. Instead, they should gradually build their status by targeting low-status users rather than attempt to “jump” by targeting high-status ones. This research extends the seeding literature by introducing the concept of risk to dissemination dynamics in online communications, showing that unknown music creators do not seed specific status levels but rather choose a portfolio of seeding targets while solving a risk versus return trade-off. The authors discuss various managerial implications for optimal seeding in user-generated content networks.
Identification of spectral regions of the key components in the near infrared spectrum of wheat grain

NIR is gaining popularity in food industry as an analysis toll. The energy of infrared light may not be sufficient to induce transitions of valence electrons, instead, excites vibration and rotational motions in molecules. NIR spectra contains information about all the molecules containing hydrogen thereby enabling a humungous scope of organic compound analysis. NIRS is a non-destructive practical method with reliable reproducibility in results that can replace expensive, time-consuming and labor intensive methods that are in practice for customary validation in food industry. NIRS can be used efficiently for both qualitative and quantitative analysis of a component with little or no sample preparation. Its reliability has benchmarked a spot in food industries where the quality profile of ingredients employed like fat, moisture and protein to name a few, is critical. To decode a complex NIR spectra, consisting of many overlapping peaks, chemometric models were employed. The models were developed using carefully selected and representative samples which were analyzed by a standard reference analytical method. The spectral region contributing to the absorbance of NIR illustrates the presence of a specific functional groups, sometimes more than one wavelength region would contribute to a particular component. These are referred to as the fingerprint region of that particular component. Identifying the fingerprint region is the first step towards quantification of the components present in the sample. Wheat is an chief winter crop in the world. It is essential to understand the quality of wheat and segregate it based on its key components for different applications, this ensures an accomplished final product. Wheat key ingredients such as moisture, starch and protein were marked out from NIR Spectrum by identifying the corresponding functional group peak absorption values. This happens to be the first step towards building a prediction model.
Changes in aerobic power of men, ages 25-70 yr.

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak). The cross-sectional sample consisted of 1,499 healthy men ages 25-70 yr. The 156 men of the longitudinal sample were from the same population and examined twice, the mean time between tests was 4.1 (+/- 1.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill exercise test. The zero-order correlations between VO2peak and %fat (r = -0.62) and SR-PA (r = 0.58) were significantly (P < 0.05) higher that the age correlation (r = -0.45). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.46 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.79) showed that nearly 50% of this cross-sectional decline was due to %fat and SR-PA, adding these lifestyle variables to the multiple regression model reduced the age regression weight to -0.26 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results.
Convergence analysis of brain storm optimization algorithm

Brain storm optimization (BSO) algorithm is a new kind of swarm intelligence algorithm, which is inspired by collective behavior of human beings. In this paper, a Markov model for brain storm optimization algorithm is derived. The model gives the theoretical probability of the occurrence of each possible population as the number of generation count goes to infinity. Using the Markov model, the convergence of the brain storm optimization is analyzed.