Miracle-dz/UniFAR-FTUs huggingface dataset:
A software-defined networking framework for IoT based on 6LoWPAN

The software defined networking framework facilitates flexible and reliable internet of things networks by moving the network intelligence to a centralized location while enabling low power wireless network in the edge. In this paper, we present SD-WSN6Lo, a novel software-defined wireless management solution for 6LoWPAN networks that aims to reduce the management complexity in WSN's. As an example of the technique, a simulation of controlling the power consumption of sensor nodes is presented. The results demonstrate improved energy consumption of approximately 15% on average per node compared to the baseline condition.
Improvement of the developmental competence of canine oocyte using caffeine supplementation during IVM at different maturation time

Summary The aim of the current study was to investigate the effect of caffeine supplementation during in vitro maturation (IVM) for different maturation times on the developmental potential of canine oocytes recovered from ovariohysterectomized bitches. The recovered cumulus–oocytes complexes were in vitro matured for 72 h. Here, 10 mM caffeine was added to the maturation medium for different incubation times (caffeine from 0–72 h maturation, caffeine for the first 24 h of maturation only, caffeine addition from 24 to 48 h maturation time, caffeine addition from 48 to 72 h maturation or in caffeine-free medium, control group). The matured oocytes were in vitro fertilized using frozen–thawed spermatozoa. The presumptive zygotes were in vitro cultured in synthetic oviductal fluid medium for 5 days. The results showed that both maturation and fertilization rates were significantly higher (P ˂ 0.05) using caffeine-treated medium for the first 24 h of maturation compared with the control and other two groups of caffeine treatment (from 24 to 48 h and from 48 to 72 h), whereas use of caffeine-treated medium for a 0–72 h incubation time did not affect these rates (P > 0.05). Interestingly, the matured oocytes in caffeine-supplemented medium for the first 24 h or from 0–72 h showed a significant (P ˂ 0.05) increase in the total number of cleaved embryos compared with the control group. In conclusion, supplementation of the maturation medium with 10 mM caffeine for the first 24 h of maturation or during the whole maturation time (0–72 h) improved nuclear maturation and subsequent embryo development preimplantation following in vitro fertilization.
Tracing a Route and Finding a Shortcut: The Working Memory, Motivational, and Personality Factors Involved

Wayfinding (WF) is the ability to move around efficiently and find the way from a starting point to a destination. It is a component of spatial navigation, a coordinate and goal-directed movement of one’s self through the environment. In the present study, the relationship between WF tasks (route tracing and shortcut finding) and individual factors were explored with the hypothesis that WF tasks would be predicted by different types of cognitive, affective, motivational variables, and personality factors. A group of 116 university students (88 F.) were conducted along a route in a virtual environment and then asked first to trace the same route again, and then to find a shortcut between the start and end points. Several instruments assessing visuospatial working memory, mental rotation ability, self-efficacy, spatial anxiety, positive attitude to exploring, and personality traits were administered. The results showed that a latent spatial ability factor (measured with the visuospatial working memory and mental rotations tests) – controlled for gender – predicted route-tracing performance, while self-report measures of anxiety, efficacy, and pleasure in exploring, and some personality traits were more likely to predict shortcut-finding performance. We concluded that both personality and cognitive abilities affect WF performance, but differently, depending on the requirements of the task.
OPTIMIZATION OF SODA PULPING PROCESS OF LIGNO-CELLULOSIC RESIDUES OF LEMON AND SOFIA GRASSES PRODUCED AFTER STEAM DISTILLATION

Sofia (Cymbopogon martini), and lemon (Cymbopogon flexuosus) grasses, are exclusively cultivated for extraction of important lemongrass and palma rosa oils. Lignocellulosic residue (LCR) of sofia and lemon grasses left after steam distillation can successfully be used for the production of chemical grade pulp. Steam distillation mitigates the problem of mass transfer, and facilitates the faster penetration of cooking liquor by leaching out a part of extraneous components. Sofia grass produces a pulp yield of 43.7% of kappa number 20 at an active alkali dose of 14% (as Na2O), maximum cooking temperature of 160 oC and cooking time 90 min. Likewise, lemon grass produces a pulp yield of 41.4% of kappa number 12.5 under the same conditions except temperature (150 oC) by a soda pulping process. Addition of 0.1% AQ at optimum cooking conditions reduces kappa number by 26 and 8% for sofia and lemon grasses with insignificant increase in pulp yield i.e. 0.2 and 0.4% for sofia and lemon grasses, respectively. The mechanical strength properties of lemon grass soda-AQ pulp are better than sofia grass. Bauer-McNett fiber classification further validates that +20 fractions are more (62.63%) in lemon grass than in sofia grass (42.72%).
Americas Conference on Information Systems ( AMCIS ) 8-2010 A Comparative Analysis of Persona Clustering Methods

Current and future information systems require a better understanding of the interactions between users and systems in order to improve system use, and ultimately, success. The use of personas as design tools is becoming more widespread as academicians and practitioners discover its benefits. This paper presents an empirical study comparing the performance of existing qualitative and quantitative clustering techniques at the task of identifying personas and grouping system users into those personas. A method based on Factor (Principal Component) Analysis outperforms two others using Latent Semantic Analysis and Multivariate Cluster Analysis.
Low Resolution Face Recognition in the Wild

Although face recognition systems have achieved impressive performance in recent years, the low-resolution face recognition (LRFR) task remains challenging, especially when the LR faces are captured under non-ideal conditions, as is common in surveillance-based applications. Faces captured in such conditions are often contaminated by blur, nonuniform lighting, and nonfrontal face pose. In this paper, we analyze face recognition techniques using data captured under low-quality conditions in the wild. We provide a comprehensive analysis of experimental results for two of the most important applications in real surveillance applications, and demonstrate practical approaches to handle both cases that show promising performance. The following three contributions are made: {\em (i)} we conduct experiments to evaluate super-resolution methods for low-resolution face recognition; {\em (ii)} we study face re-identification on various public face datasets including real surveillance and low-resolution subsets of large-scale datasets, present a baseline result for several deep learning based approaches, and improve them by introducing a GAN pre-training approach and fully convolutional architecture; and {\em (iii)} we explore low-resolution face identification by employing a state-of-the-art supervised discriminative learning approach. Evaluations are conducted on challenging portions of the SCFace and UCCSface datasets.
Effect of Various Surface Treatment on Repair Strength of Composite Resin

Statement of Problem: In some clinical situations, repair of composite restorations is treatment of choice. Improving the bond strength between one new and old composite usually requires increased surface roughness to promote mechanical interlocking since chemical bonding might not be adequate. Similarly, the treatment of a laboratory fabricated resin composite restoration involves the same procedures, and there is a need to create the strongest possible bond of a resin cement to a previously polymerized composite. Purpose: The aim of this study was to evaluate the effect of various surface treatments on the shear bond strength of repaired to aged composite resin. Materials and Methods : Eighty four cylindrical specimens of a composite resin were fabricated and stored in distilled water for 100 days prior to surface treatment. Surface treatment of old composite was done in 6 groups as follow: 1- Air abrasion with CoJet sand particles with micoretcher + silane + dentin bonding agent 2- Air abrasion with 50µm Al2O3 particles+ phosphoric acid+ silane+ dentin bonding agent 3- Air abrasion with 50µm Al2O3 particles + phosphoric acid + dentin bonding agent 4- Diamond bur + phosphoric acid + silane + dentin bonding agent 5- Diamond bur + phosphoric acid + dentin bonding agent 6- Diamond bur + phosphoric acid + composite activator + dentin bonding agent Then fresh composite resin was bonded to treated surfaces. Twelve specimens were also fabricated as control group with the same diameter but with the height twice as much as other specimens. All of the specimens were thermocycled prior to testing for shear bond strength. The bond strength data were analyzed statistically using one way ANOVA test, t test and Duncan's grouping test. Results: One-way ANOVA indicated no significant difference between 7 groups (P=0.059). One-way ANOVA indicated significant difference between the three diamond bur groups (P=0.036). Silane had a significant effect on the repair bond strength of diamond bur/silane group. There was no significant difference in the bond strength diamond bur/composite activator group and diamond bur/no silane group. Silane had no significant effect on the repair bond strength of air abrasion group. The lowest bond strength was for diamond bur/ composite activator group. Conclusion: The best surface treatment for repair of an aged composite restoration could be used of diamond bur with silane, air abrasion with or without silane or ceramic deposition with CoJet Sand system. Silanation is a necessary step in the repair of composite resin with the use of diamond bur but not with the use of air abrasion.
Individualization of music‐based rhythmic auditory cueing in Parkinson's disease

Gait dysfunctions in Parkinson's disease can be partly relieved by rhythmic auditory cueing. This consists in asking patients to walk with a rhythmic auditory stimulus such as a metronome or music. The effect on gait is visible immediately in terms of increased speed and stride length. Moreover, training programs based on rhythmic cueing can have long‐term benefits. The effect of rhythmic cueing, however, varies from one patient to the other. Patients’ response to the stimulation may depend on rhythmic abilities, often deteriorating with the disease. Relatively spared abilities to track the beat favor a positive response to rhythmic cueing. On the other hand, most patients with poor rhythmic abilities either do not respond to the cues or experience gait worsening when walking with cues. An individualized approach to rhythmic auditory cueing with music is proposed to cope with this variability in patients’ response. This approach calls for using assistive mobile technologies capable of delivering cues that adapt in real time to patients’ gait kinematics, thus affording step synchronization to the beat. Individualized rhythmic cueing can provide a safe and cost‐effective alternative to standard cueing that patients may want to use in their everyday lives.
FPGA-Accelerated for Constrained High Dispersal Network

In recent years, the Deep Neural Network (DNN) has been successfully used in image classification. Most of existing DNN often need to learn a very large set of parameters, which require a huge amount of computational resources and time to train these model parameters using the gradient descent and back-propagation procedure. To solve this issue, the PCANet has been developed for high efficient design and training of the DNN. Compared with traditional DNN, PCANet has simpler structure and better performance, which makes it attractive for hardware design. To overcome the limitations of PCANet and significantly improve its performance, we have proposed a novel model named Constrained High Dispersal Network (CHDNet) which is a variant of PCANet. In this paper, we implement the CHDNet on the Xilinx ZYNQ FPGA to ensure the instantaneity of the system with lower power than personal computer needed by taking advantage of the algorithmic parallelism and ZYNQ architecture. Our experimental results over two major datasets, the MNIST dataset for handwritten digits recognition, and the Extended Yale B dataset for face recognition, demonstrate that our model of implementation on FPGA is more than 15x faster than software implementation on PC (Intel i7-4720HQ, 2.6GHz).
Human capital information in management reports: An analysis of compliance with the characteristic of the relevance of disclosure

Purpose: The aim of this paper is to assess the compliance with the characteristic of the relevance of disclosure in Management Reports, particularly dealing with Human Capital (HC) information. Design/methodology/approach: We codify all instances where narratives of IBEX-35 stock index companies over a five year period in Spain comply with the recommendations for a “high quality” Management Commentary (MC) in terms of the relevance characteristic of the information disclosed (IASB, 2005). Findings: The analysis results show that a greater quantity of information about HC in terms of the number of pages devoted is not always indicative of higher quality in terms of relevance if we look for the application of IASB recommendations. Research limitations/implications: Further research could assess compliance with other qualitative characteristics required by other standards or guidances that were internationaly generaly accepted. Practical implications: Among the areas that require improvement in HC disclosures we highlight forward-looking information. Social implications: We propose that an internationally accepted agreement must be struck to unite all the efforts that are being made to improve narrative information in the MC section, and specifically with reference to HC. Originality/value: This work compiles the HC disclosures identified as best practices that may serve as a reference to other companies.
The prefrontal cortical endocannabinoid system modulates fear–pain interactions in a subregion‐specific manner

The emotional processing and coordination of top‐down responses to noxious and conditioned aversive stimuli involves the medial prefrontal cortex (mPFC). Evidence suggests that subregions of the mPFC [infralimbic (IfL), prelimbic (PrL) and anterior cingulate (ACC) cortices] differentially alter the expression of contextually induced fear and nociceptive behaviour. We investigated the role of the endocannabinoid system in the IfL, PrL and ACC in formalin‐evoked nociceptive behaviour, fear‐conditioned analgesia (FCA) and conditioned fear in the presence of nociceptive tone.
Smartphone Addiction and Interpersonal Competence of Nursing Students

Background: Interpersonal competence is an important capacity for nurses. Recently, the advent of smartphones has instigated considerable changes in daily life. Because smartphone has multiple functions, people tend to use them for numerous activities, often leading to addictive behavior. Methods: This cross-sectional study performed a detailed analysis of smartphone addiction subscales and social support related to interpersonal competence of nursing students. Overall, 324 college students were recruited at Catholic University in Seoul, Korea from Feb 2013 to Mar 2013. Participants completed a self-reported questionnaire, which included scales that measured smartphone addiction, social support, interpersonal competence, and general characteristics. Path analysis was used to evaluate structural relations between subscales of smartphone addictions, social support, and interpersonal competence. Results: The effect of cyberspace-oriented relationships and social support on interpersonal competence were 1.360 (P=.004) and 0.555 (P<.001), respectively. Conclusion: Cyberspace-oriented relationship, which is a smartphone addiction subscale, and social support were positively correlated with interpersonal competence of nursing students, while other smartphone addiction subscales were not related to nursing student interpersonal competence. Therefore, effective smartphone teaching methods be developed to enhance nursing student motivation
A revelation principle for obviously strategy-proof implementation

We prove that if a stochastic (social choice) rule has an obviously strategy-proof (OSP) implementation (Li, 2016), then it has such an implementation through a randomized round table mechanism, where the administrator randomly selects a game form in which the agents take turns making public announcements about their private information. When restricted to deterministic rules, our result improves upon other recent revelation principles by relaxing all recall requirements and by allowing all game trees compatible with normal forms (Alos-Ferrer and Ritzberger, 2016); we also establish robustness to player randomization using novel solution concepts involving mixed strategies and behavioral strategies. We use our result to provide a justification for ordinal mechanisms in the spirit of Carroll (2017), and we provide a simple characterization of the deterministic rules with OSP-implementations using deterministic round table mechanisms and ordinary strategy-proofness.
Intensity-based matching and registration for 3D correlative microscopy with large discrepancies

Correlative microscopy, especially light and electron microscopy (CLEM), enables the study of cells and subcellular elements in complementary ways, provided a reliable registration between images is efficiently achievable. We propose a general automatic registration method. Due to large discrepancies in appearance, field-of-view, resolution and position, a pre-alignment stage is required before any 3D fine registration stage. We define an intensity-based method for both stages, which leverages a common representation of the two involved image modalities. We report experimental results on different real datasets of 3D correlative microscopy, demonstrating time efficiency and overlay accuracy.
An Adaptive Batch-Orchestration Algorithm for the Heterogeneous GPU Cluster Environment in Distributed Deep Learning System

Training deep learning model is time consuming, so various researches have been conducted on accelerating the training speed through distributed processing. Data parallelism is one of the widely-used distributed training schemes, and various algorithms for the data parallelism have been studied. However, since most of studies assumed homogeneous computing environment, there is a problem that they do not consider a heterogeneous performance graphics processing unit (GPU) cluster environment. The heterogeneous performance environment leads to differences in computation time between GPU workers in the synchronous data parallelism. Due to the difference of the computation time of one iteration, the straggler problem that fast workers wait for the slowest worker makes training speed slow. Therefore, in this paper, we propose a batch-orchestration algorithm (BOA), reducing the training time by improving hardware efficiency in the heterogeneous performance GPU cluster. The proposed algorithm coordinates local mini-batch sizes for all workers to reduce the training iteration time. We confirmed that the proposed algorithm improves the performance by 23% over the synchronous SGD with one back-up worker when training ResNet-194 using 8 GPUs of three different types.
Subliminal Priming—State of the Art and Future Perspectives

The influence of subliminal priming (behavior outside of awareness) in humans is an interesting phenomenon and its understanding is crucial as it can impact behavior, choices, and actions. Given this, research about the impact of priming continues to be an area of investigative interest, and this paper provides a technical overview of research design strengths and issues in subliminal priming research. Efficient experiments and protocols, as well as associated electroencephalographic and eye movement data analyses, are discussed in detail. We highlight the strengths and weaknesses of different priming experiments that have measured affective (emotional) and cognitive responses. Finally, very recent approaches and findings are described to summarize and emphasize state-of-the-art methods and potential future directions in research marketing and other commercial applications.
Is there an optimal haematocrit for rainbow trout, Oncorhynchm mykiss (Walbaum)? An interpretation of recent data based on blood viscosity measurements

The viscosity of blood from rainbow trout was measured following manipulation of haematocrit by bleeding, hypoxia. exercise, and anaesthesia. Blood viscosity when measured at high shear rate (225 s 1) was proportional to haematocrit, but the dependence of viscosity on shear rate was far less for swollen erythrocytes from exercised and anaesthetized trout. Erythrocyte swelling was most marked in exercised and anaesthetized trout, and is a confounding factor when considering the effect of haematocrit on viscosity. The viscosity of blood with variable haematocrit, but constant mean cell Hb concentration, indicated that the relative oxygen transport capacity in trout was optimal at a haematocrit of 30%. Data from this, and earlier studies show that haematocrit in trout is variable and labile, yet none of the haematocrit values following manipulations are less than 85% of optimal. Optimal haematocrit is however, significantly higher than measured values from either cannulated or acutely venesected resting trout.
Impact of meteorological and geographical factors on the distribution of Phlebotomus chinensis in northwestern mainland China

Phlebotomine sandflies (Diptera: Phlebotomidae) are vectors of the zoonotic disease leishmaniasis. To better understand the distribution of phlebotomine sandflies in order to facilitate control of leishmaniasis transmission, the present study explored the impacts of climate and landscape on local abundances of Phlebotomus chinensis in northwestern mainland China. Identification records were used to create a geodatabase for the locations at which P. chinensis had been collected in the region, and a regional‐scale map was developed to show the distribution of P. chinensis. Location data and data on environmental factors during the years in which the samples were collected were incorporated, and a presence‐only modelling method was used to evaluate the species' habitat preferences and to predict its potential distribution in northwestern mainland China. Jackknife analysis revealed that several meteorological variables, including maximum temperature in the warmest quarter, precipitation in the driest month, daily average temperature and daily precipitation, significantly affected the presence of this species. Moreover, the presence of P. chinensis was significantly associated with grassland and shrubland. Probability distributions using maximum entropy were used to map the distribution ranges of P. chinensis based on suitable habitats in northwestern mainland China. The models generated can be used to develop detailed strategies for the prevention and control of leishmaniasis.