Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Adsorption Removal of Pb(II) and Cr(III) by Using Nickel Ferrite-Reduced Graphene Oxide Nanocomposite

The heavy metals, such as Pb(II) and radioisotope Cr(III), in aqueous solutions are toxic even at trace levels and have caused adverse health impacts on human beings. Hence the removal of these heavy metals from the aqueous environment is of the utmost importance to protect biodiversity, hydrosphere ecosystems, and human beings. In this study, the reduced graphene oxide based inverse spinel nickel ferrite (rGONF) nanocomposite has been prepared and was utilized for the removal of Pb(II) and Cr(III) from aqueous solutions. The prepared rGONF has been confirmed by X-ray photoelectron (XPS) and Raman spectroscopy. The surface characteristics of rGONF were measured by scanning electron microscopy (SEM), High-Resolution Transmission Electron Microscope (HR-TEM), and Brunauer-Emmett-Teller (BET) surface analysis. The average particle size of rGONF was found to be 32.0 ± 2.0 nm. The surface site density for the specific surface area (Ns) of rGONF was found to be 0.00238 mol·g−1, which was higher than that of the graphene oxide (GO) and NiFe2O4, which was expected. The prepared rGONF has been successfully applied for the removal of Pb(II) and Cr(III) by batch mode. The batch adsorption studies concluded that the adsorption of Pb(II) and Cr(III) onto rGONF was rapid and the adsorption percentage was more than 99% for both metal ions. The adsorption isotherm results found that the adsorptive removal of both metal ions onto rGONF occurred through monolayer adsorption on a homogeneous surface of rGONF. The pH-edge adsorption results suggest the adsorption occurs through an inner-sphere surface complex, which is proved by 2-pKa-diffusion model fitting, where the pH-edge adsorption data was well fitted. The adsorption of metal ions increased with increasing temperature. The overall obtained results demonstrated that the rGONF was an effective adsorbent for Pb(II) and Cr(III) removal from wastewater.
Sensor Mobility Control for Multitarget Tracking in Mobile Sensor Networks

In emerging tracking systems using mobile wireless sensor networks, sensor mobility management is essential for balancing the tracking performance and costs under limited network resources and sensor movements. This paper considers the sensor mobility control problem for multitarget tracking (MTT), in which multiple mobile sensors are dynamically grouped and moved to track multiple targets and collaborate within each sensor group via track data fusion. A novel sensor mobility control framework for the mobile sensor network-based MTT is proposed. It is formulated as a constrained optimization problem that aims to maximize the overall tracking performance for all targets while conserving network energy and providing tracking coverage guarantee. The optimization problem is relaxed as a convex programming problem for computational tractability and its solution is implemented in a distributed manner. The newly proposed sensor mobility control scheme, implemented on the basis of iterative subgradient search, is shown via computer simulation to have better performance over the static sensor network-based MTT.
Exploring Dynamic Redundancy to Resuscitate Faulty PCM Blocks

DRAM technology challenges have increased the necessity to adapt to the emerging memory technologies like Phase-Change Memory (PCM or PRAM). While such emerging technologies provide benefits like storage density, nonvolatility, and low energy consumption, they are constrained by limited write endurance that becomes more pronounced with process variation. In this article, we explore a novel PRAM-based main memory system which resuscitates a group of faulty pages in a cost-effective manner to significantly extend the PCM main memory lifetime while minimizing the performance impact. In particular, we explore three different dimensions of dynamic redundancy levels and group sizes, and design low-cost hardware and software support for our proposed schemes. We aim to have minimal hardware modifications (that have less than 1% on-chip and off-chip area overheads). Also, our schemes can improve the PRAM lifetime by up to 105× (times) over a chip with no error correction capabilities, and outperform prior schemes such as DRM and ECP at a small fraction of the hardware cost. The performance overhead resulting from our scheme is less than 8% on average across 21 applications from SPEC2006, Splash-2, and PARSEC benchmark suites.
Mining urban land-use patterns from volunteered geographic information by means of genetic algorithms and artificial neural networks

In the context of OpenStreetMap (OSM), spatial data quality, in particular completeness, is an essential aspect of its fitness for use in specific applications, such as planning tasks. To mitigate the effect of completeness errors in OSM, this study proposes a methodological framework for predicting by means of OSM urban areas in Europe that are currently not mapped or only partially mapped. For this purpose, a machine learning approach consisting of artificial neural networks and genetic algorithms is applied. Under the premise of existing OSM data, the model estimates missing urban areas with an overall squared correlation coefficient (R 2) of 0.589. Interregional comparisons of European regions confirm spatial heterogeneity in the model performance, whereas the R 2 ranges from 0.129 up to 0.789. These results show that the delineation of urban areas by means of the presented methodology depends strongly on location.
Stimulation of a Ca2+-Calmodulin-activated Histone 3 Arginine Kinase in Quiescent Rat Heart Endothelial Cells Compared to Actively Dividing Cells (*)

A Ca-calmodulin-activated histone 3 kinase was partially purified from nuclear extracts of dividing and quiescent rat heart endothelial cells. The histone 3 phosphorylating activity was 20-100-fold higher in quiescent than in dividing cells. Base hydrolysis followed by amino acid analysis revealed that histone 3 was phosphorylated on arginine. Further investigations were conducted to determine whether phosphorylation of histone 3 also occurred in vivo. Cells were incubated for 3 h in a phosphate-free medium supplemented with [P]phosphoric acid. It was observed that the nuclear content of arginine-phosphorylated histone 3 was considerably higher in quiescent than in dividing rat heart endothelial cells. The histone 3 arginine kinase is a component of a complex containing a Ca-dependent calmodulin-binding protein of apparent molecular mass of 85 kDa. Using polyclonal antibodies to an 85-kDa protein, also the major Ca-dependent calmodulin-binding component of the histone 3 arginine kinase from calf thymus, an immunoreactive protein of identical apparent molecular mass was found to be present in equal amounts both in dividing and quiescent cells. We propose that the 85-kDa protein is either the histone 3 arginine kinase or one of its subunits and that phosphorylation of histone 3 is involved with cell cycle exit in eukaryotes.
Enhancing Social Support at the Workplace: Assessing the Effects of the Caregiver Support Program

Although the health-enhancing effects of social support have been well documented, little is known about how to increase the flow of social support among network members. This article describes and evaluates the Caregiver Support Program, a worksite program that attempts to improve the quality of work relationships among house managers and direct care staff who work in group homes for the developmentally disabled. The progam incorporates three strategies for increasing social support: (1) adding a new person or group of persons to the employee's social network, (2) enhancing existing relationships by improving the focal employee's skills for maintaining strong networks and mobilizing support, and (3) enhancing existing relationships by training members of the employee's social network in ways to be more supportive. The Caregiver Support Program was evaluated in a randomized field trial. Results indicate that the program was effective in improving the relationships between direct care staff participants and their house managers. However, other work relationships remained unaffected. The relationship between direct care staff and their house managers was the only work relationship for which both members of the interpersonal dyad participated in the program. The implications of these findings for health education practice and future research are discussed.
Serum ferritin as a measure of iron stores in normal subjects.

Serum ferritin has been measured by a two-site immunoradiometnic assay employing antibody-coated polystyrene tubes. Normal values were established by performing measurements in male and female subjects between 20 and 50 years of age in whom iron-deficient erythropoiesis was excluded on the basis of transferrin saturation and red cell protoporphyrin. The serum fernitin was log-normally distributed with a geometric mean of 94 ng/ml in 174 males and 34 ng/ml in 152 females. Additional studies were performed in 83 healthy women to determine the relationshipbetween serum ferritin and iron stores measured by radioiron absorption. A high correlation between these measurements indicates that the serum ferritin is a useful survey tool for the initial assessment and prospective monitoring of iron stores in a normal population. Am. J. Clin. Nutr. 27: 681 -687, 1974.
Active learning for tag recommendation utilizing on-line photos lacking tags

Recommending text tags for on-line photos is useful for Internet photo services. Typical solutions to this problem require analysis of the correlation among different attributes of the photos, including the correlation between the textual features and visual features computed from a photo. However, most on-line photos have very few tags or even no tags, and thus they contribute little or none to the analysis of tag-photo correlation, which is a key component in those schemes that rely on such analysis for tag recommendation. To address this practical challenge, we propose an active learning method for incorporating photos with no or few tags so as to enhance the correlation analysis for improved performance in tag recommendation. We demonstrate the effectiveness of the proposed approach using a dataset of more than 33,000 photos collected from Flickr.
Towards a Better Understanding of Predict and Count Models

In a recent paper, Levy and Goldberg pointed out an interesting connection between prediction-based word embedding models and count models based on pointwise mutual information. Under certain conditions, they showed that both models end up optimizing equivalent objective functions. This paper explores this connection in more detail and lays out the factors leading to differences between these models. We find that the most relevant differences from an optimization perspective are (i) predict models work in a low dimensional space where embedding vectors can interact heavily; (ii) since predict models have fewer parameters, they are less prone to overfitting. Motivated by the insight of our analysis, we show how count models can be regularized in a principled manner and provide closed-form solutions for L1 and L2 regularization. Finally, we propose a new embedding model with a convex objective and the additional benefit of being intelligible.
A Maximum Likelihood Solution to Doa Estimation for Discrete Sources

In this contribution, we propose a maximum likelihood solution t o the direction-of-arrival estimation for discrete sources (a problem which arises in digital communication context). The likelihoDd expression being in general very involved, direct solutions or approximations of the likelihood equations are likely to be rather messy. To alleviate this problem, we resort t o the standard complete/incomplete dat,a model, where the observations play the role of the incomplete da ta while the source signals are the missing data. We then maximize the incomplete likelihood (the likelihhod of the observations) by iteratively maximizing the complete likelihood function using (i) the deterministic ECM algorithm and (ii) a stochastic version of it, the SEM, which is efficiently implemented by resorting to a Gibbs sampler. Ext.ensive numerical simulations show that this method outperforms the standard higher-order statistics based techniques. Numerical investigation of the Cramer-Rao lower bound is also undertaken.
Virtual 3 D shape and orientation discrimination using point distance information

Distance information is critical to our understanding of our surrounding environment, especially in virtual reality settings. Unfortunately, as we gage distance mainly visually, the blind are prevented from properly utilizing this parameter to formulate 3D cognitive maps and cognitive imagery of their surroundings. We show qualitatively that with no training it is possible for blind and blindfolded subjects to easily learn a simple transformation between virtual distance and sound, based on the concept of a virtual guide cane (paralleling in a virtual environment the “EyeCane”, developed in our lab), enabling the discrimination of virtual 3D orientation and shapes using a standard mouse and audio-system.
plosOpenRExploring FP7 funded PLOS publications

This case study explores alternative science metrics on grant-supported research publications. The study is based on plosOpenR, a software package for the statistical computing environment R. plosOpenR facilitates access to the application programming interfaces API provided by Open Access publisher Public Library of Science PLOS and OpenAIRE --Open Access Infrastructure for Research in Europe.We report 1,166 PLOS articles that acknowledge grant support from 624 different research projects funded by the European Union's 7th Framework Programme FP7. plosOpenR allows the exploration of PLOS Article-Level Metrics PLOS ALM, including citations, usage and social media events as well as collaboration patterns on these articles. Findings reveal the potential of reusing data, that are made openly and automatically available by publishers, funders and the repository community.
An exploration of men's experiences of depression during the postnatal period : an IPA study

Postnatal Depression (PND) is a construct that exists across time and culture, affecting both women and men at a ratio of 2:1 respectively. The dominant discourse focuses on women’s experiences of PND and the motherinfant relationship, presented within the framework of an overarching biomedical model that produced a plethora of studies underpinned by the positivist paradigm. In contrast, this research seeks to explore what it actually means for men, as fathers, to experience depression during the postnatal period. The literature to date highlights a threefold gap regarding approach to research into the phenomenon of PND: the epistemological underpinning, the methodological approaches chosen and the gender bias. To address this gap it is necessary for a paradigm shift regarding approach to research to embrace further qualitative methodology. Interpretive Phenomenological Analysis is the methodology identified for this research, as it provides the medium for consideration of the phenomenological and idiographic nature of the experience of PND, to include the role of the researcher and interpretation that reflects the central tenet of reflexivity within the discipline of Counselling Psychology. The overall gestalt presents a transitional adjustment process whereby the life event of the birth of a child initiated a process of deconstruction in preparation for adjusting to a new role within a changed family dynamic. The data revealed three super-ordinate and six sub-ordinate themes highlighting a complexity regarding how men made sense of their experience of depression during the postnatal period, including contemplation of past, present and possible future selves. Negative cognitive appraisal and attribution of meaning relating to childhood experiences, negative perceptions of fatherhood, masculinities, gender roles, the fatherchild relationship and socio-cultural contextual influences blocked the reconstructive process, resulting in increased stress and anxiety that led to depression. This study draws attention to risk factors, such as, childhood trauma, negative inter-generational relationships and differences in gendered expression of cognitive dissonance and anxiety. Conclusions consider implications for Counselling Psychology, highlighting the complex inter-subjective nature of men’s experiences and the value of an inter-disciplinary approach to future research, healthcare practice and intervention strategies to develop appropriate care and support for parents, particularly for men during the perinatal period.
Pictures in words or words in pictures? New insights from Indian print advertising research

This paper attempts to explore the impact of pictures on the accompanying verbal information in print advertisements for high-imagery and low-imagery copy, and for high-involvement and low-involvement products. The impact is measured in terms of advertisement recall as well as in terms of affect or feelings generated by the advertisement. Using an experimental design involving corporate executives, the research adopted random assignment of subjects to different treatment conditions. The results show that when the verbal attribute information in the advertisement copy is not imagery-provoking, the addition of pictures exemplifying that information enhances both recall and affect, while, when the verbal attribute information itself is imagery-provoking, the addition of pictures increases affect but not recall. These findings were also found to be contingent upon the extent of consumer involvement in the product category. The research has strong implications for marketing strategists and advertisement agencies.
Supplementation with a polyphenolic blend improves post-exercise strength recovery and muscle soreness

Background Exercise can initiate a cascade of inflammatory and oxidative stress–related events leading to delayed onset muscle soreness. Polyphenols possess antioxidant and anti-inflammatory properties. Objective The current study examined the effects of a proprietary polyphenolic blend (PB), containing catechins and theaflavins, on exercise performance and recovery following an eccentric exercise challenge. Design Male participants (18–35 years of age) received placebo or PB at a low dose (PB-L, 1,000 mg/d) or high dose (PB-H, 2,000 mg/d) for 13 weeks. During the 13th week of supplementation, participants completed an eccentric exercise (40 min downhill treadmill run) followed by a strength assessment (peak torque on isokinetic leg extensions) pre-exercise, and 24, 48, and 96 h post-exercise. Muscle soreness (subjective questionnaire), markers of muscle stress (cortisol and creatine phosphokinase [CK]), and antioxidant capacity (ferric reducing ability of plasma [FRAP]) were also assessed. Results PB-H attenuated the decrease in peak torque observed in the placebo group from pre-exercise to 48 h (p=0.012) and 96 h (p=0.003) post-exercise. At 48 h post-exercise, PB-H reduced whole body and hamstring soreness (p=0.029) versus placebo. Chronic consumption of PB improved serum FRAP (p=0.039). As expected, serum cortisol and CK increased from pre- to post-exercise in all groups; however, by 96 h, cortisol and CK levels returned to pre-exercise levels following PB supplementation. At 96 h, the change in cortisol from pre- to post-exercise was significantly greater in placebo versus PB-H (p=0.039). Conclusion These findings show that chronic consumption of PB improved antioxidant status, reduced markers of muscle stress, and promoted strength recovery post-exercise.
Decentralized Sampled-Data Tracking Control of Large-Scale Fuzzy Systems: An Exact Discretization Approach

In this paper, a decentralized sampled-data tracking controller design technique for Takagi–Sugeno fuzzy interconnected systems is proposed. The overall large-scale system is assumed to consist of fuzzy subsystems with unknown but norm-bounded interconnections. This paper focuses mainly on the design of a sampled-data decentralized model reference tracking controller based on the exact discretization approach, by which the resulting large-scale error dynamics becomes asymptotically stabilized with a predefined H-infinity performance criterion. To this end, we first design a continuous-time decentralized tracking controller based on the proposed design technique. After that, by using the discrete-time fuzzy Lyapunov function, the proposed design technique is extended to cover a sampled-data tracking controller design. The proposed controller design techniques are formulated in terms of linear matrix inequalities. Finally, numerical examples are given to show the effectiveness of the proposed methods by comparing them with other methods.
Design of networked periodic reset control systems

The aim of this work is to develop tunnig rules for networked reset control systems with periodic reset actions. The reset law is simplified for the reset instants to be periodic, but on the other hand a key idea is the use of a variable reset value at each instant that minimizes the error between consecutive reset actions. This variable reset value defines by itself a different controller so the system may be considered as an hybrid system that combines the base linear system and a complementary system given by the variable reset value. Simple rules for adjusting the complementary system and for the switching will be given. Simulation results show how to apply these rules to networked control systems.
An effective grid clustering algorithm based on least clustering cell and its application

The basic concept of clustering and its correlating research work is firstly present, a new algorithm based on least clustering cell (LCC) is proposed and analyzed which concerns the advantages and disadvantage of k-means and grid clustering algorithm. This algorithm is efficient in dealing with huge amounts of data and can make paralleled processing, which is proved to be correct, efficient and fast through application in customer relationship management. It overcomes the disadvantage of given the value k in k-means clustering algorithm and data dense in grid based clustering algorithm. Lastly the analysis and evaluation of the algorithm is given.
Smart cards: a system support for service accessibility from heterogeneous devices

With the proliferation of computers which do not resemble computers, such as mobile phones, TV's, PDA's, end-users wish to take advantage of them to access their applications and information, wherever they are and whatever the device used.This article deals with a common means to access a same service from various kinds of devices, and explains how smart cards, as mediums compatible with most types of terminals, can be used as application bootstrap.