Miracle-dz/UniFAR-FTUs huggingface dataset:
Brand Management, Competitiveness and Business Performance in Mexican Small Service Businesses

Brand management is considered in the current marketing literature as one of the most important business strategies, not only by researchers and academics but also by professionals in the field of marketing, which can allow the growth in the level of competitiveness of small service enterprises, as well as have a significant increase in their level of business performance. Moreover, brand management has usually focused on big transnational enterprises and there are relatively few investigations that have focused on small firms. There are even less research papers that have made emphasis in small service businesses. Therefore, with a sample of 150 small service businesses, the aim of this empirical research is the analysis and discussion of brand management at the level of competitiveness and business performance in small service businesses in a country with an emerging economy, which is the case of Mexico. The results obtained show that brand management has positive, significant effects in the level of competitiveness and the level of business performance.
Probabilistic Streaming Tensor Decomposition

Tensor decomposition is a fundamental tool for multiway data analysis. While most decomposition algorithms operate a collection of static data and perform batch processes, many applications produce data in a streaming manner — every time a subset of entries are generated, and previously seen entries cannot be revisited. In such scenarios, traditional decomposition approaches will be inappropriate, because they cannot provide timely updates when new data come in, and they need to access the whole dataset many times for batch optimization. To address this issue, we propose POST, a PrObabilistic Streaming Tensor decomposition algorithm, which enables real-time updates and predictions upon receiving new tensor entries, and supports dynamic growth of all the modes. Compared with the state-of-the-art streaming decomposition approach MAST, POST is more flexible in that it can handle arbitrary orders of streaming entries, and hence is more widely applicable. In addition, as a Bayesian inference algorithm, POST can quantify the uncertainty of the latent embeddings via their posterior distributions, and the confidence levels of the missing entry value predictions. On several real-world datasets, POST exhibits better or comparable predictive performance than MAST and other static decomposition algorithms.
Estimating the Effect of School Quality on Mortality in the Presence of Migration: Evidence from the Jim Crow South

How does school quality affect health amid multiple behavioral responses? The Rosenwald schools transformed school quality for rural southern African Americans in the early 1900s. Research shows that the schools made black migration northward more likely and that the Great Migration shortened life expectancy for these migrants. Besides the hypothesized health-enhancing effects of school quality, negative health effects might also occur through migration. We disentangle behavioral mechanisms and find complete exposure to the Rosenwald schools increased life expectancy by 2–3 months; a more naive approach finds no relationship. Results are robust to heterogeneous treatment effects and various measurement issues.
Foraging animals create fertile patches in an Australian desert shrubland

Fertile patches are created and maintained by a combination of physical and biologically-mediated processes including soil disturbance by animals. We examined the creation of fertile patches by 4 vertebrates, the greater bilby Macrotis lagotis, burrowing bettong Bettongia lesueur, European rabbit Oryctolagus cuniculus, and Gould's sand goanna Varanus gouldii within dunes, ecotones, and swales in a dunefield in arid South Australia. These animals all create pits when foraging for subterranean food resources. We hypothesized that 1) the effect of pits on litter capture would vary among landscapes and animal species, 2) larger pits would trap more litter and seed, 3) pits would contain more viable seed than the surrounding matrix, and 4) the effect of pits on soil chemistry would vary among animal species, and be greater in landscapes with more finely textured soils. We found that litter was restricted almost exclusively to the pits, and was greater in pits with larger openings. Litter capture was greater in ecotones and dunes than in swales. A total of 1307 seedlings from 46 genera germinated from litter samples taken from the pits, but no seedlings emerged from samples taken from soil surrounding the pits. Foraging pits contained significantly higher levels of total C and N than surrounding soil, and total C and N concentrations were greatest in swales and lowest in dunes. Pits contained ca 55% more mineralisable N that surface soils, and pits constructed by bilbies and bettongs contained half the concentration of mineralisable N as those of rabbits and goannas. Concentrations of mineral N and mineralisable N were also greatest in the swales. Our results demonstrate the importance of animal-created pits as nutrient sinks and sites for seedling establishment, and suggest that changes in the composition of arid zone vertebrates may have resulted in profound changes to nutrient and soil dynamics in arid Australia.
Caulogenesis and Chlorophyll Content in STEVIA REBAUDIANA ( BERT ) Bertoni by Using Glutamine in the Culture Medium

Incorporation of Glutamine in MS medium significantly enhanced direct shoot bud induction from nodal explants from juvenile plants of S. rebaudiana. Shoot bud induction medium was supplemented with BAP (2.5mgl) and IAA (2.5mgl) When the concentration of Glutamine in the induction medium 100mgL. There was significant increase in percentage response along with healthy, well developed with dark green broader leaves. Here was remarkable increase in total biomass and chlorophyll content at 100mgl Level in the medium. During the proliferation stage, also presence of Glutamine in the medium favored increase in shoots bud number per explants.
Craniomaxillofacial Bone Engineering by Scaffolds Loaded with Stem Cells: A Systematic Review

Objective: The concept of tissue engineering holds huge promise for thefuture treatment of osseous defects. For bone tissue engineering, stem cells are applied on supporting scaffolds under controlled stimulation with growth factors. Scaffolds are provisional matrices for bone growth providing a specific environment for tissue development and favoring cellular attachment, growth and differentiation. To date, ceramics, polymers, and composite scaffolds have been widely used for bone tissue engineering in various in-vitro and animal studies. The objective of this article was to review the advances in jaw bone engineering from a scaffold material point of view. Methods: A review of literature was carried out by using Medline database and searching topics like "craniomaxillofacial tissue engineering", "bone regeneration", "scaffold", "oral surgery", "stem cell+ scaffold", "xenograft" and "allograft". Animal and human studies evaluating repair of craniomaxillofacial defects with scaffold and stem cells, were considered in this study. Results: A total of 64 studies were evaluated. Conclusion: Based on the results of this literature review, although autogenous bone grafting has remained the preferred strategy for treatment of bone defects, rapid prototyping (RP) techniques do offer great opportunities to generate suitable scaffolds for bone tissue engineering in near future.
Game theory based multi criteria decision making problem under uncertainty: a case study on Indian Tea Industry

The long-term evolution of multi agent multi criteria decision making (MCDM) and to obtain sustainable decision a novel methodology is proposed based on evolutionary game theory. In this paper multi agent MCDM is represented as an evolutionary game and the evolutionary strategies are defined as sustainable decisions. Here we consider the problem of decision making in Indian Tea Industry. The agents in this game are essentially Indian Tea Estate owner and Indian Tea board. The replicator dynamics of the evolutionary game are studied to obtain evolutionary strategies which could be defined as sustainable strategies. The multi agent MCDM in Indian Tea Industry is considered under different socio-political and Corporate Social Responsibility scenario and groups of Indian Tea Industry. Again, the impacts of imprecision and market volatility on the outcome of some strategies (decisions) are studied. In this paper the imprecision on the impact of the strategies are modelled as fuzzy numbers whereas the market volatility is taken into account as white noise. Hence the MCDM problem for Indian Tea Industry is modelled as a hybrid evolutionary game. The probabilities of strategies are obtained by solving hybrid evolutionary game and could be represented as a Dempster-Shafer belief structure. The simulation results facilitate the Decision Makers to choose the strategies (decisions) under different type of uncertainty.
HIV-1 resistance profile in plasma and peripheral blood lymphocytes in a group of naive patients

Transmitted HIV-1 drug resistance (TDR) is a persisting problem, even though the prevalence of primary resis- tance may remain stable or start to decline. Proviral DNA detectable in peripheral blood mononuclear cells (PBMCs) is a reservoir of drug resistant viral variants and could be an alternative marker to viral RNA for the detection of drug resis- tance mutations. The aim of this study was to compare the HIV-1 resistance profile between plasma viral RNA and proviral DNA in a group of untreated patients. Thirty-one HIV-1 seropositive patients without prior ARV treatment were included in the study. The presence of non-polymorphic drug resistance mutations was identified in 10 cases in proviral DNA and in 11 cases in plasma according to different scoring systems. Our results show a similar resistance profile between plasma RNA and proviral DNA, but with some discordances present. The sequencing of proviral DNA could provide useful ad- ditional information with regard to primary resistance.
Vers un modèle dynamique de l ’ attention visuelle d ’ un opérateur humain Towards a dynamic model of human visual attention

Une idée pour améliorer la conception, le diagnostic d’interfaces homme-machine est de pouvoir disposer d’un modèle cognitif d’un opérateur humain (par exemple d’un pilote d’avion). Un tel modèle peut également apporter des moyens pour assister en ligne un opérateur humain en anticipant l’apparition de ses erreurs et en aidant à les corriger. Dans le cadre de cette problématique, une étape consiste à définir un modèle dynamique de l’attention visuelle, dans la mesure où l’activité de traitement de l’information visuelle est particulièrement sollicitée dans les interactions hommes-machines (exemple : surveillance des paramètres avions).
2D Material Microcavity Light Emitters: To Lase or Not to Lase?

Atomically thin layers of transition metal dichalcogenides (TMDs) are of great interest to the photonics community because of their unique optical properties. For example, in conjunction with microring or photonic crystal microresonators, they readily form microcavity light emitters. A number of configurations are now presented that apparently meet the conditions for lasing, yet there is considerable debate in the community as to whether lasing is actually achieved. By employing a very comprehensive set of assessment criteria, herein is shown that none of the TMD devices meet all the conditions for lasing, despite some very convincing data being presented. These findings are examined in the context of microcavity lasers based on III–V gain materials. Applications of TMD light emitters in the areas of quantum information and biosensing are also discussed to highlight areas where lasing action is not necessarily required.
Series 8-6-2018 Robust Inference for the Stepped Wedge Design

Based on a permutation argument, we derive a closed form expression for an estimate of the treatment effect, along with its standard error, in a stepped wedge design. We show that these estimates are robust to mis-specification of both the mean and covariance structure of the underlying data-generating mechanism, thereby providing a robust approach to inference for the treatment effect in stepped wedge designs. We use simulations to evaluate the type I error and power of the proposed estimate and to compare the performance of the proposed estimate to the optimal estimate when the correct model specification is known. The limitations, possible extensions, and open problems regarding the method are discussed.
Speech signal denoising with wavelet-transforms and the mean opinion score characterizing the filtering quality

Speech signal processing is widely used to reduce noise impact in acquired data. During the last decades, wavelet-based filtering techniques are often applied in communication systems due to their advantages in signal denoising as compared with Fourier-based methods. In this study we consider applications of a 1-D double density complex wavelet transform (1D-DDCWT) and compare the results with the standard 1-D discrete wavelet-transform (1DDWT). The performances of the considered techniques are compared using the mean opinion score (MOS) being the primary metric for the quality of the processed signals. A two-dimensional extension of this approach can be used for effective image denoising.
Face Recognition for Newborns, Toddlers, and Pre-School Children: A Deep Learning Approach

Biometric recognition of newborns, toddlers, and pre-school children aims is an important research challenge with applications in identifying newborn swapping, missing kids, and disbursing benefits. In this research, we propose a representation learning algorithm to extract unique and invariant features from face images of newborns and toddlers, to design an efficient face recognition algorithm. Specifically, we propose a deep learning model which applies class-based penalties while learning the filters of a convolutional neural network. The proposed CNN architecture achieves a rank-1 identification accuracy of 62.7% for single gallery newborn face recognition and 85.1% for single gallery toddler face recognition, forming state-of-the-results for both the databases. Comparison with several existing algorithms also showcases the effectiveness of the proposed algorithm on both the databases.
Triplet Markov models and fast smoothing in switching systems

The aim of the paper is twofold. The first aim is to present a mini tutorial on « pairwise Markov models » (PMMs) and " triplet Markov models " (TMMs) which extend the popular " hidden Markov models " (HMMs). The originality of these extensions is due to the fact that the hidden data does not need to be Markov. More precisely, for X hidden data and Y observed ones, the originality of PMMs is that X does not need to be Markov, and the originality of TMMs is that even (X, Y) does not need to be Markov. In spite of these lacks of Markovianity fast processing methods, similar to those applied in HMMs or their other extensions, remain workable. The second goal is to present an original switching model approximation allowing fast smoothing. The method we propose, called " double filtering based smoothing " (DFBS), uses a particular TMM in which the pair (X, R), where R models switches, is not Markov. It is based on two filters, and uses a class of models, known as conditionally Gaussian observed Markov switching models (CGOMSMs), where exact fast filtering is feasible. The original model is approximated by two CGOMSMs in order to process the past data and the future data in direct and reverse order, respectively. Then state estimates produced by these two models are fused to provide a smoothing estimate. The DFBS is insensitive to the dimensions of the hidden and observation space and appears as an alternative to the classic particle smoothing in the situations where the latter cannot be applied due to its high processing cost.
Validity Threats in Quantitative Data Collection With Games: A Narrative Survey

Background. Games are increasingly used to collect scientific data. Some suggest that game features like high cognitive load may limit the inferences we can draw from such data, yet no systematic overview exists of potential validity threats of game-based methods. Aim. We present a narrative survey of documented and potential threats to validity in using games for quantitative data collection. Method. We combined an unsystematic bottom-up literature review with a systematic top-down application of standard validity threat typologies to games to arrive at a systematisation of game-characteristic validity threats. Results. We identify three game characteristics that potentially impact validity: Games are complex systems, impeding the predictable control and isolation of treatments. They are rich in unwanted variance and diversity. And their social framing can differ from and interact with the framing of research studies or non-game situations they are supposed to represent. The diversity of gamers and their differences to general populations bring further complications. Discussion and Conclusions. The wealth of potential validity threats in game-based research is met by a dearth of systematic methodological studies, leading us to outline several future research directions.
Numerical simulations of compressible Rayleigh–Taylor turbulence in stratified fluids

We present the results of our numerical simulations of the Rayleigh–Taylor turbulence, performed using a recently proposed (Sbragaglia et al 2009 J. Fluid Mech. 628 299, Scagliarini et al 2010 Phys. Fluids 22 055101) lattice Boltzmann method that can describe consistently a thermal compressible flow subjected to an external forcing. The method allowed us to study the system in both the nearly Boussinesq regime and the strongly compressible regime. Moreover, we show that when the stratification is important, the presence of the adiabatic gradient causes the arrest of the mixing process.
PREDICTING ACCEPTANCE AND USE BEHAVIOR OF CONSUMERTOWARD INDIHOME SERVICES BY USING EXTENDED UTAUT MODEL (A Case Study in Bandung)

: Telkom as the only state-owned telecommunications enterprise also a leading telecommunication company in Indonesia which provides fixed line or cable line try to seek an opportunity from another potential market to generate their profit. While the mobile migration result in unfavorable situation for traditional market, however industry statistics show an upward trend from other key ICT indicator subscriptions, which in this case is Triple Play services named IndiHome. Unfortunately, the factors that affecting consumers on using IndiHome Services are still not clearly observed. Analyzing factors that affect the behavior intention and usage behavior of consumers toward the adoption of IndiHome Services is needed. This research intends to analyze factors that affect the behavioral intention and use behavior of consumers toward the adoption of IndiHome Services in Bandung, based on Unified Theory of Acceptance and Use of Technology 2. The results reveals, factors that influencing the Behavioral Intention on the adoption of IndiHome services in Bandung sequentially starting from the greatest influence are Habit, Hedonic Motivation, Social Influence, Performance Expectancy, Price Value and Facilitating Condition as 82.3%. While the influence of Habit and Behavioral Intention on Use Behavior as 7%.
Endogenous Technology and Climate Change

This paper studies the implications of the event of climate change for an economy that is characterized by an endogenous growth framework. The technological change is driven by the accumulation of knowledge that increases the efficiency of a renewable energy sector, leading to a reduction of the alternate fossil fuel energy use. A decentralized equilibrium is defined, and by comparing with the social planner solution an optimal carbon tax is obtained. This environmental policy accounts for the externality imposed by a rising temperature that is the result of the generation of pollution from the fossil fuel consumption, and that damages the output of the overall economy.
Bipedal Robotic Walking on Flat-Ground, Up-Slope and Rough Terrain with Human-Inspired Hybrid Zero Dynamics

The thesis shows how to achieve bipedal robotic walking on flat-ground, up-slope and rough terrain by using Human-Inspired control. We begin by considering human walking data and find outputs (or virtual constraints) that, when calculated from the human data, are described by simple functions of time (termed canonical walking functions). Formally, we construct a torque controller, through model inversion, that drives the outputs of the robot to the outputs of the human as represented by the canonical walking function; while these functions fit the human data well, they do not apriori guarantee robotic walking (due to do the physical differences between humans and robots). An optimization problem is presented that determines the best fit of the canonical walking function to the human data, while guaranteeing walking for a specific bipedal robot; in addition, constraints can be added that guarantee physically realizable walking. We consider a physical bipedal robot, AMBER, and considering the special property of the motors used in the robot, i.e., low leakage inductance, we approximate the motor model and use the formal controllers that satisfy the constraints and translate into an efficient voltage-based controller that can be directly implemented on AMBER. The end result is walking on flat-ground and up-slope which is not just human-like, but also amazingly robust. Having obtained walking on specific well defined terrains separately, rough terrain walking is achieved by dynamically changing the extended canonical walking functions (ECWF) that the robot outputs should track at every step. The state of the robot, after every non-stance foot strike, is actively sensed and the new CWF is constructed to ensure Hybrid Zero Dynamics is respected in the next step. Finally, the technique developed is tried on different terrains in simulation and in AMBER showing how the walking gait morphs depending on the terrain.
Microscopic X-ray Imaging Techniques Applied to Mineral Systems and Catalyst Particles

J.F. W. MOSSELMANS , C.I. PEARCE, W.R. BOWER, R.A.D. PATTRICK, S.W. T. PRICE, A.M. BEALE, A.P. SIMS, and L. BARRIO Science Division, Diamond Light Source, Harwell Campus, Didcot, Oxon OX11 ODE, UK School of Chemistry and Dalton Nuclear Institute, University of Manchester, Manchester M13 9PL, UK School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester M13 9PL, UK UK Catalysis Hub, Research Complex at Harwell, Harwell Campus, Didcot OX11 0FA, UK Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK Velocys Technologies Ltd., 115e Olympic Avenue, Milton Park, Abingdon OX14 4SA, UK e-mail: fred.mosselmans@diamond.ac. uk