Miracle-dz/UniFAR-FTUs huggingface dataset:
Circadian Phenotype Composition is a Major Predictor of Diurnal Physical Performance in Teams

Team performance is a complex phenomenon involving numerous influencing factors including physiology, psychology, and management. Biological rhythms and the impact of circadian phenotype have not been studied for their contribution to this array of factors so far despite our knowledge of the circadian regulation of key physiological processes involved in physical and mental performance. This study involved 216 individuals from 12 different teams who were categorized into circadian phenotypes using the novel RBUB chronometric test. The composition of circadian phenotypes within each team was used to model predicted daily team performance profiles based on physical performance tests. Our results show that the composition of circadian phenotypes within teams is variable and unpredictable. Predicted physical peak performance ranged from 1:52 to 8:59 p.m. with performance levels fluctuating by up to 14.88% over the course of the day. The major predictor for peak performance time in the course of a day in a team is the occurrence of late circadian phenotypes. We conclude that circadian phenotype is a performance indicator in teams that allows new insight and a better understanding of team performance variation in the course of a day as often observed in different groupings of individuals.
Joint Routing and Channel Assignment for Delay Minimization in Multi-Channel Multi-Flow Mobile Cognitive Ad Hoc Networks

Channel interference and node mobility cause significant performance degradation to wireless networks. In multichannel multi-flow mobile cognitive ad hoc networks, it becomes even worse due to both unexpected primary user activities and potential interference among multiple flows. In this paper, we propose a Joint Routing and Channel Assignment (JRCA) approach based on delay prediction. Firstly, it formulates the JRCA problem with the objective of delay minimization. Next, a delay prediction model is proposed based on the channel collision probability. Then, a heuristic algorithm joints routing and channel assignment is designed to solve the JRCA problem. the JRCA algorithm can find out the path with minimal end- toend (e2e) delay. NS2-based simulation results demonstrate that the JRCA approach significantly outperforms related proposals in terms of average e2e delay.
Development and complexity-based fitness function modifiers

Artificial Development is a promising approach to evolutionary design optimization inspired by biological development. However, there is still no consensus as to which problem classes this approach has a clear advantage over classical direct encodings. We attack this problem by introducing the concept of fitness function modifiers based on complexity. Our results indicate that using these modifiers, we are able to discriminate a developmental mapping from a direct encoding with respect to their efficiency at solving classes of problems defined by the fitness modifiers.
Who is to blame

Contradictory evidence can be found in the literature about whether ingroup identification and perceived relative deprivation are positively or negatively related. Indeed, theoretical arguments can be made for both effects. It was proposed that the contradictory findings can be explained by considering a hitherto unstudied moderator: the extent to which deprivation is attributed to the ingroup. It was hypothesized that identification would only have a negative impact on deprivation, and that deprivation would only have a negative impact on identification, if ingroup attributions are high. To test this, we experimentally manipulated attributions to the ingroup among British student participants (N = 189), who were asked about their perceived deprivation vis-a-vis German students, yielding support for the hypotheses.
Control of asynchronous dynamical systems with rate constraints on events

We consider dynamical systems which are driven by external "events" that occur asynchronously. It is assumed that the event rates are fixed, or at least they can be bounded on any time period of length T. Such systems are becoming increasingly important in control due to the very rapid advances in digital systems, communication systems, and data networks. Examples of asynchronous systems include, control systems in which signals are transmitted over an asynchronous network, parallelized numerical algorithms, and queuing networks. We present a Lyapunov-based theory for asynchronous dynamical systems and show how Lyapunov functions and controllers can be constructed for such systems by solving linear matrix inequality (LMI) and bilinear matrix inequality (BMI) problems. Examples are also presented that demonstrate the effectiveness of the approach in analyzing practical systems.
Voltage Control in Active Distribution Networks and an Approach based on Model Predictive Control

With the rise in penetration of renewable energy sources in electric distribution networks, reliable operation and control of power system have become a challenge for power system operators. The paradigm shift from passive to active distribution network causes various issues such as, stability, voltage and frequency regulation, designing of protection equipment, etc. Thus, there arises the need of a proper control strategy to deal with such concerns. This paper presents a review of the voltage control strategies already existed in literature. Subsequently, a methodology is also proposed here to regulate voltages in active distribution networks.
Review of fault diagnosis and fault-tolerant control for modular multilevel converter of HVDC

This review focuses on faults in Modular Multilevel Converter (MMC) for use in high voltage direct current (HVDC) systems by analyzing the vulnerable spots and failure mechanism from device to system and illustrating the control & protection methods under failure condition. At the beginning, several typical topologies of MMC-HVDC systems are presented. Then fault types such as capacitor voltage unbalance, unbalance between upper and lower arm voltage are analyzed and the corresponding fault detection and diagnosis approaches are explained. In addition, more attention is dedicated to control strategies, when running in MMC faults or grid faults. This paper ends up with a discussion of other opportunities for future development.
CYP17A1 Intron Mutation Causing Cryptic Splicing in 17α-Hydroxylase Deficiency

17α-hydroxylase/17, 20-lyase deficiency (17OHD) is an autosomal recessive disease causing congenital adrenal hyperplasia and a rare cause of hypertension with hypokalemia. The CYP17A1 gene mutation leads to 17OHD and its clinical features. We described an 18 y/o female with clinical features of 17α-hydroxylase/17, 20-lyase deficiency and characterized the functional consequences of an intronic CYP17A1 mutation. The coding regions and flanking intronic bases of the CYP17A1 gene were amplified by PCR and sequenced. The patient is a compound heterozygote for the previously described p.R358X and IVS1 +2T>C mutations. A first intron splice donor site mutation was re-created in minigene and full-length expression vectors. Pre-mRNA splicing of the variant CYP17A1 intron was studied in transfected cells and in a transformed lymphoblastoid cell line. When the full-length CYP17A1 gene and minigene containing the intronic mutation was expressed in transfected cells, the majority (>90%) of mRNA transcripts were incorrectly spliced. Only the p.R358X transcript was detected in the EBV-transformed lymphoblastoid cell line. The IVS1 +2T>C mutation abolished most 17α-hydroxylase/17, 20-lyase enzyme activity by aberrant mRNA splicing to an intronic pseudo-exon, causing a frame shift and early termination.
Alleviation and Sanctions in Social Dilemma Games

This paper reports an experiment which compares behaviour in two punishment regimes: (i) a standard public goods game with punishment in which subjects are given the opportunity to punish other group members (democratic punishment regime) and (ii) a public goods game environment where all group members exogenously experience an automatic reduction of their income (irrespective of their behaviour) and are given the opportunity to alleviate the automatic penalty (undemocratic punishment regime). We employ a within-subjects design where subjects experience both environments and control for order effects by alternating their sequence. Our findings indicate that average contributions and earnings in the undemocratic punishment environment are significantly lower relative to the standard public goods game with punishment. We also observe that in the undemocratic environment average contributions decay over time only when subjects have experienced the standard public goods game with punishment. As a result, alleviation is significantly less when subjects have experienced the standard public goods game with punishment compared to when they do not have such experience. However, the assignment of punishment is robust irrespective of the order in which the games are played.
Chunkyspread: Multi-tree Unstructured Peer-to-Peer Multicast

The latest debate in P2P and overlay multicast systems is whether or not to build trees. The main argument on the anti-tree side is that tree construction is complex, and that trees are fragile. The main counter-argument is that non-tree systems have a lot of overhead. In this paper, we argue that you can have it both ways: that one can build multi-tree systems with simple and scalable algorithms, and can still yield fast convergence and robustness. This paper presents Chunkyspread, a multi-tree, heterogeneous P2P multicast algorithm based on an unstructured overlay. Through simulation, we show that Chunkyspread can control load to within a few percent of a heterogeneous target load, and how this can be traded off for improvements in latency and tit-for-tat incentives.
The effects of coachee readiness and core self-evaluations on leadership coaching outcomes: a controlled trial

This study investigates the impact of coachee readiness for change and core personality traits as both criteria and predictors of outcomes after strength-based leadership coaching. Specifically this study examined developmental readiness, change readiness and core self-evaluations (CSEs; locus of control, neuroticism, self-efficacy and self-esteem), in the coachee to measure both their capacity to predict changes in transformational leadership and to act as outcome criteria in themselves after coaching. Thirty executives and senior managers from a large not-for-profit organisation were assigned to either a coaching or waitlist cohort using a between-subjects non-equivalent control group design. The coaching cohort received six sessions of leadership coaching involving feedback on leadership and strengths, goal setting and strengths development. After six sessions of coaching over three months, cohorts then switched roles. The results showed that participants in the waitlist first group declined in both developmental and coaching readiness whilst waiting for coaching. For the coaching first group their CSEs increased significantly over time but this was not the case for the waitlist first group. Only change readiness at Time 1 and CSEs at Time 2 were significant predictors of enhanced leadership effectiveness after coaching. The results suggest that these coachee variables are potential outcome criteria and predictors of change after leadership coaching.
TAXI: Trace Analysis for x86 Interpretation

Although x86 processors have been around for a long time and are the most ubiquitous processors in the world, the amount of academic research regarding details of their performance has been minimal. We introduce an x86 simulation environment, called TAXI (Trace Analysis for X86 Interpretation), and use it to present results for eight Win32 applications. In this paper, we explain the design and implementation of TAXI.
An interactive ontology learning workbench for non-experts

Ontologies are an integral part of Knowledge and Information Management systems and there is increased interest in using ontologies for organizational memory. Ontology learning workbenches are used for semi-automatic learning of ontologies from representative text collections. This paper presents a new interactive workbench that gives the users more freedom in their ontology engineering process and frees them from knowing any ontology language syntax. The workbench is implemented as part of a search project, in which ontologies are used to search for movie information on the web. New techniques are steadily being added to the workbench, though early testing has already confirmed the validity of the ontology learning approach.
A Comprehensive Survey of Pelagic Megafauna: Their Distribution, Densities, and Taxonomic Richness in the Tropical Southwest Indian Ocean

The distribution and density of pelagic megafauna (marine mammals, seabirds, elasmobranches and sea turtles) are important indicators of marine biodiversity, reflecting the condition of the underlying ecosystems. Taking advantage of their relative accessibility at the sea surface, a dedicated aerial survey was conducted in the tropical Southwest Indian Ocean to map their distribution, the taxonomic diversity and to estimate their densities for a reference standpoint on the area. This large survey across three ecological sub-regions revealed contrasting spatial distributions: maps of taxonomic richness of marine mammals and seabirds revealed different “hotspots” in the area. Densities were estimated for eight cetacean taxa with small and large Delphininae, or small Globicephalinae dominating, and for seven seabird taxa, with terns and noddies dominating. At the community level, the Southwest Indian Ocean megafauna was structured by the marine environment with strong differences between the Mozambique Channel and the Mascarene Islands, or between shelf and slope/oceanic habitats. Our results illustrate how multi-taxa aerial surveys are relevant and cost-effective monitoring tools for marine megafauna, allowing a community-wide approach.
Identification of protein O-GlcNAcylation sites using electron transfer dissociation mass spectrometry on native peptides

Protein O-GlcNAcylation occurs in all animals and plants and is implicated in modulation of a wide range of cytosolic and nuclear protein functions, including gene silencing, nutrient and stress sensing, phosphorylation signaling, and diseases such as diabetes and Alzheimer's. The limiting factor impeding rapid progress in deciphering the biological functions of protein O-GlcNAcylation has been the inability to easily identify exact residues of modification. We describe a robust, high-sensitivity strategy able to assign O-GlcNAcylation sites of native modified peptides using electron transfer dissociation mass spectrometry. We have studied the murine postsynaptic density pseudoorganelle and report the assignment of 58 modification sites from a single experiment–significantly increasing the number of sites known in the literature. Components of several repressor complexes, such as NCoR1, polyhomeotic-like protein3, and EMSY, are modified. In addition, 28 O-GlcNAc sites were found on the protein Bassoon, effectively matching the number of phosphorylation sites reported previously on this protein. This finding suggests that on certain proteins, O-GlcNAcylation may be as extensive and important as phosphorylation in regulating protein function. Three of the newly discovered O-GlcNAc sites on Bassoon have previously been reported as phosphorylation sites, highlighting the interplay of the modifications. Surprisingly, several peptides with GlcNAc modifications on asparagines within the N-X-S/T consensus sequence were also observed from membrane protein extracellular domains. This powerful strategy fulfills a long-standing need in the biological community by facilitating modification site identifications that will accelerate understanding of the biological significance of this elusive regulatory posttranslational modification.
Speckle noise reduction in ultrasound image based on A Multiplicative Multiresolution Decomposition ( MMD )

This paper turns on ultrasound image despeckling by using Multiplicative Multiresolution Decomposition MMD. The proposed method is based on MMD’s coefficient thresholding. The used thresholds are automatically evaluated from the transformed image content. Tests are conducted on simulated speckled and real ultrasound images. Obtained results show that the proposed method outperforms the considered existing ones. Keywords-Ultrasound imaging; Speckle noise; MMD transform; Wavelet transform.
Artificial Neural Network Models for Rainfall Prediction in Pondicherry

Rainfall forecasting plays an important role in catchment management applications, the flood warning system being one of them. Rainfall forecasting is one of the most difficult tasks given the variability of space, time and other given conditions change rapidly. Over the years, with the evolution of the intelligent computing methods, many rainfall prediction methods have been proposed, Artificial Neural Network being one of the most prominent. Since the last decade, many researchers have proposed different artificial neural network models in order to create accurate rainfall prediction models. In this paper, different artificial neural networks have been created for the rainfall prediction of Pondicherry, a coastal region in India. These ANN models were created using three different training algorithms namely, feed-forward back propagation algorithm, layer recurrent algorithm and feedforward distributed time delay algorithm. The number of neurons for all the models was kept at 20. The mean squared error was measured for each model and the best accuracy was obtained by feed-forward distributed time delay algorithm with MSE value as low as . 0083.
A fast and robust iris localization method based on texture segmentation

With the development of the current networked society, personal identification based on biometrics has received more and more attention. Iris recognition has a satisfying performance due to its high reliability and non-invasion. In an iris recognition system, preprocessing, especially iris localization plays a very important role. The speed and performance of an iris recognition system is crucial and it is limited by the results of iris localization to a great extent. Iris localization includes finding the iris boundaries (inner and outer) and the eyelids (lower and upper). In this paper, we propose an iris localization algorithm based on texture segmentation. First, we use the information of low frequency of wavelet transform of the iris image for pupil segmentation and localize the iris with a differential integral operator. Then the upper eyelid edge is detected after eyelash is segmented. Finally, the lower eyelid is localized using parabolic curve fitting based on gray value segmentation. Extensive experimental results show that the algorithm has satisfying performance and good robustness.
Facile fabrication of luminescent organic dots by thermolysis of citric acid in urea melt, and their use for cell staining and polyelectrolyte microcapsule labelling

Luminescent organic dots (O-dots) were synthesized via a one-pot, solvent-free thermolysis of citric acid in urea melt. The influence of the ratio of the precursors and the duration of the process on the properties of the O-dots was established and a mechanism of their formation was hypothesized. The multicolour luminescence tunability and toxicity of synthesized O-dots were extensively studied. The possible applications of O-dots for alive/fixed cell staining and labelling of layer-by-layer polyelectrolyte microcapsules were evaluated.
In Vitro Activity of Plant Extracts and Alkaloids against Clinical Isolates of Extended-Spectrum β-Lactamase (ESBL)-Producing Strains

The antibacterial activity of 80% ethanol extracts of 10 medicinal plants collected in Yunnan (Southwest China), was tested against clinical isolates of extended-spectrum β-lactamase (ESBL)-producing strains. Their MIC values ranged between 1.56-12.50 mg/mL. The most active plant extract was Chelidonium majus L. (MIC = 1.56 mg/mL). Two potent isoquinoline alkaloids, 8-hydroxydihydrosanguinarine and 8-hydroxydihydrochelerythrine, were identified as the major active principles through bioassay-guided fractionation and identification of the active ethyl acetate fraction from C. majus, with minimum MIC/MBC values of 15.63/62.50 μg/mL.
PLAGIARISM: A PERSPECTIVE FROM A CASE OF A NORTHERN NIGERIAN UNIVERSITY

Academic dishonesty, especially plagiarism, is a global problem that has bedevilled the academia. It is regarded as unethical and immoral intellectual thievery that could negatively impact on not only the repute of an academic institution, but the prosperi ty of a society. This study was designed to investigate student’s awareness and indulgence in plagiarism and their perception of punishment towards Plagiarists. Towards this end, a sampling survey approach employing questionnaires and interviews was used to collect data from a total of 200 Gombe State University students (Nigeria). The result of the interviews showed that 90% of students have plagiarized at one time in the past, 68% have included textbooks and other sources in the bibliography of assignment s, out of which 50% had written books that they didn’t even consult. The data from questionnaires showed that the proportion of students whose awareness of plagiarism was partial (63%) and those completely unaware (20%) were higher than those (17%) aware of it. Further, the data showed that the majority of students plagiarize from the Internet (90%) and when asked about whether it would be fair to punish Plagiarists, 42% of students disagreed. Generally, this appears to confirm other reports about the incidence of plagiarism in the academia and pinpoints under awareness as its major cause. Hence, this calls for a campaign to increase students’ awareness of plagiarism and its ethical and moral implications; the need for plagiarism detection tools and developm ent of more strict measures for Plagiarists.
Diverse effects of interdialytic intervals on central wave augmentation in haemodialysis patients.

BACKGROUND Increased arterial stiffness is a common finding and independent predictor of mortality in end-stage renal disease (ESRD) patients. A long interdialytic interval was associated with increased risk of cardiovascular death in patients receiving conventional haemodialysis (HD). This is the first study to examine the effects of a long (3-day) versus short (2-day) interdialytic period on arterial elasticity in HD patients. METHODS Seventy ESRD patients receiving standard HD three times per week were studied at the start and end of a 3-day and a 2-day interdialytic interval. At each time point, applanation tonometry of peripheral arteries was performed to assess arterial stiffness and wave reflection parameters. Aortic and brachial pulse wave velocities (PWV) were recorded as measures of arterial stiffness and augmentation index (AIx) as a measure of wave reflections. RESULTS AIx, heart-rate-adjusted AIx and augmentation pressure were significantly increased during both interdialytic intervals, whereas aortic and brachial PWVs remained unchanged. The interdialytic increases in all the three AIx parameters were significantly higher during the 3-day interval in comparison to the 2-day interval (P < 0.001 for all comparisons). In contrast, no significant differences in interdialytic changes of aortic (P = 0.355) and brachial (P = 0.319) PWVs were noted between the two intervals. Mixed linear model analysis revealed that central aortic systolic blood pressure (SBP) and body weight, but not aortic or brachial PWV, were independent determinants of the change in heart-rate-adjusted AIx throughout the study. CONCLUSIONS AIx is increased between HD sessions, whereas arterial elasticity is not. This interdialytic increase in central wave augmentation is more pronounced during the 3-day interval, suggesting a mechanism possibly involved in the elevated cardiovascular risk of HD patients at this time point.