Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Car License Plate Localization using Wavelet Analysis

Detection of vehicle license plate is vital for identifying the vehicle because the license plate has unique information for each vehicle. However, in India, vehicle license plate standards, though they exist, are rarely practiced. Large amount of variations are seen in the parameters of license plate like size of number plate, its location, background and foreground color, etc. which makes the task of number plate localization for recognition more difficult. This paper presents a Wavelet analysis based methodology for precise localization of Indian number plates.
Genotype × Environment Interactions of Yield Traits in Backcross Introgression Lines Derived from Oryza sativa cv. Swarna/Oryza nivara

Advanced backcross introgression lines (BILs) developed from crosses of Oryza sativa var. Swarna/O. nivara accessions were grown and evaluated for yield and related traits. Trials were conducted for consecutive three seasons in field conditions in a randomized complete block design with three replications. Data on yield traits under irrigated conditions were analyzed using the Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype × Environment Interaction (GGE) and modified rank-sum statistic (YSi) for yield stability. BILs viz., G3 (14S) and G6 (166S) showed yield stability across the seasons along with high mean yield performance. G3 is early in flowering with high yield and has good grain quality and medium height, hence could be recommended for most of the irrigated locations. G6 is a late duration genotype, with strong culm strength, high grain number and panicle weight. G6 has higher yield and stability than Swarna but has Swarna grain type. Among the varieties tested DRRDhan 40 and recurrent parent Swarna showed stability for yield traits across the seasons. The component traits thousand grain weight, panicle weight, panicle length, grain number and plant height explained highest genotypic percentage over environment and interaction factors and can be prioritized to dissect stable QTLs/ genes. These lines were genotyped using microsatellite markers covering the entire rice genome and also using a set of markers linked to previously reported yield QTLs. It was observed that wild derived lines with more than 70% of recurrent parent genome were stable and showed enhanced yield levels compared to genotypes with higher donor genome introgressions.
Consensus of a group of multiple integrator agents using bounded control

This paper studies global leader-following consensus of a group of networked multi-integrator systems subject to control input saturation. A weighted nonlinear state feedback control law is proposed to solve this problem. Both the case of a fixed undirected communication topology and the case of a switching undirected communication topology are considered. We show that leader-following consensus can be achieved by using the proposed control laws when the communication topology is connected or jointly connected. Simulation results are given to illustrate the theoretical results.
Developmental changes in using verbal self-cueing in task-switching situations: the impact of task practice and task-sequencing demands

In this study we examined whether developmental changes in using verbal self-cueing for task-goal maintenance are dependent on the amount of task practice and task-sequencing demands. To measure task-goal maintenance we applied a switching paradigm in which children either performed only task A or B in single-task blocks or switched between them on every second trial in mixed-task blocks. Task-goal maintenance was determined by comparing the performance between both blocks (mixing costs). The influence of verbal self-cueing was measured by instructing children to either name the next task aloud or not to verbalize during task preparation. Task-sequencing demands were varied between groups whereas one group received spatial task cues to support keeping track of the task sequence, while the other group did not. We also varied by the amount of prior practice in task switching while one group of participants practiced task switching first, before performing the task naming in addition, and the other group did it vice versa. Results of our study investigating younger (8–10 years) and older children (11–13 years) revealed no age differences in beneficial effects of verbal self-cueing. In line with previous findings, children showed reduced mixing costs under task-naming instructions and under conditions of low task-sequence demands (with the presence of spatial task cues). Our results also indicated that these benefits were only obtained for those groups of children that first received practice in task switching alone with no additional verbalization instruction. These findings suggest that internal task-cueing strategies can be efficiently used in children but only if they received prior practice in the underlying task so that demands on keeping and coordinating various instructions are reduced. Moreover, children benefitted from spatial task cues for better task-goal maintenance only if no verbal task-cueing strategy was introduced first.
Clinical Factors Associated with Plasma F2-Isoprostane Levels in HIV-Infected Adults

Abstract Purpose: Oxidant stress may be an effect of antiretroviral therapy (ART) or chronic HIV infection. Plasma F2-isoprostanes (F2-IsoP) reflect lipid peroxidation and oxidant stress and have been described in ART-associated toxicities. We explored factors associated with F2-IsoP in HIV-infected adults. Methods: HIV-infected adults enrolled in this cross-sectional study were (a) on ART including zidovudine or stavudine but not non-nucleoside reverse transcriptase inhibitors (NNRTI), (b) on ART including NNRTI, or (c) not on ART. Plasma F2-IsoP levels were quantified by GC/MS, and clinical and laboratory data were collected at enrollment. Results: Among 285 participants, 24% were female, 37% were African American, and 194 (68%) were on ART; 44 (23%) of whom were receiving efavirenz, 45 (23%) nevirapine, and 85 (44%) protease inhibitors. Median F2-IsoP was lower in those on NNRTI than those on ART without NNRTI (p = .02). In a multivariable model, factors independently associated with increased F2-IsoP were female sex (p = .002), higher BMI (p = .01), and heavy smoking (p = .004). There was a trend toward lower F2-IsoP among nevirapine users (p = .054). Conclusions: Among HIV-infected adults, oxidant stress status differs by sex, BMI, smoking status, and perhaps specific ART. Prospective studies should better define relationships between oxidant stress and complications of HIV infection and its therapy.
Cumulus Cells Gene Expression Profiling in Terms of Oocyte Maturity in Controlled Ovarian Hyperstimulation Using GnRH Agonist or GnRH Antagonist

In in vitro fertilization (IVF) cycles controlled ovarian hyperstimulation (COH) is established by gonadotropins in combination with gonadotropin-releasing hormone (GnRH) agonists or antagonists, to prevent premature luteinizing hormone (LH) surge. The aim of our study was to improve the understanding of gene expression profile of cumulus cells (CC) in terms of ovarian stimulation protocol and oocyte maturity. We applied Affymetrix gene expression profiling in CC of oocytes at different maturation stages using either GnRH agonists or GnRH antagonists. Two analyses were performed: the first involved CC of immature metaphase I (MI) and mature metaphase II (MII) oocytes where 359 genes were differentially expressed, and the second involved the two GnRH analogues where no differentially expressed genes were observed at the entire transcriptome level. A further analysis of 359 differentially genes was performed, focusing on anti-Müllerian hormone receptor 2 (AMHR2), follicle stimulating hormone receptor (FSHR), vascular endothelial growth factor C (VEGFC) and serine protease inhibitor E2 (SERPINE2). Among other differentially expressed genes we observed a marked number of new genes connected to cell adhesion and neurotransmitters such as dopamine, glycine and γ-Aminobutyric acid (GABA). No differential expression in CC between the two GnRH analogues supports the findings of clinical studies where no significant difference in live birth rates between both GnRH analogues has been proven.
Variations in Streamflow Response to Large Hurricane-Season Storms in a Southeastern U.S. Watershed

AbstractFloods caused by hurricane storms are responsible for tremendous economic and property losses in the United States. To minimize flood damages associated with large hurricane-season storms, it is important to be able to predict streamflow amount in response to storms for a range of hydroclimatological conditions. However, this is challenging considering that streamflow response exhibits appreciable variability even for hurricane-season storms that deliver similar precipitation amounts. As such, better estimates of event responses require refined understanding of the causes of flood response variability. Here, a physically based, distributed hydrologic model and supporting hydrologic datasets are used to identify and evaluate dominant hydrologic controls on streamflow amount variability. The analysis indicates that variability in flood response in the Lake Michie watershed is primarily driven by antecedent soil moisture conditions near the land surface and evapotranspiration during postevent streamf.
Green Communication in Next Generation Cellular Networks: A Survey

In order to meet the intense user demands, the 5G networks are evolving, and will be available by 2020. The unfolding cellular technology has raised the energy consumption in mobile networks with the carbon footprint surging to alarming rates. This is causing an adverse effect on the environment and human health. Addressing these aspects, this paper presents a survey on techniques for making the next generation cellular networks GREEN. A number of technologies form a part of the 5G networks, in order to support the drastic user demands, and are receiving substantial attention from the perspective of green communication. These include device-to-device communication, spectrum sharing, ultra dense networks, massive MIMO, and the Internet of Things. Also, a prime concern in the current scenario is the battery life of the mobile terminals. For enhancing the battery life of the user terminals, a proposal is given in this paper, with spectrum sharing as its basis, to overcome the energy crunch. Major research challenges have been discussed, and the ongoing projects and standardization activities also stated in this paper.
Tools for large graph mining

Graphs show up in a surprisingly diverse set of disciplines, ranging from computer networks to sociology, biology, ecology and many more. How do such “normal” graphs look like? How can we spot abnormal subgraphs within them? Which nodes/edges are “suspicious? ” How does a virus spread over a graph? Answering these questions is vital for outlier detection (such as terrorist cells, money laundering rings), forecasting, simulations (how well will a new protocol work on a realistic computer network? ), immunization campaigns and many other applications. We attempt to answer these questions in two parts. First, we answer questions targeted at applications : what patterns/properties of a graph are important for solving specific problems? Here, we investigate the propagation behavior of a computer virus over a network, and find a simple formula for the epidemic threshold (beyond which any viral outbreak might become an epidemic). We find an “information survival threshold” which determines whether, in a sensor or P2P network with failing nodes and links, a piece of information will survive or not. We also develop a scalable, parameter-free method for finding groups of “similar” nodes in a graph, corresponding to homogeneous regions (or CrossAssociations) in the binary adjacency matrix of the graph. This can help navigate the structure of the graph, and find un-obvious patterns. In the second part of our work, we investigate recurring patterns in real-world graphs, to gain a deeper understanding of their structure. This leads to the development of the R-MAT model of graph generation for creating synthetic but “realistic” graphs, which match many of the patterns found in real-world graphs, including power-law and lognormal degree distributions, small diameter and “community” effects.
Retargeting 3D Objects and Scenes with a General Framework

In this paper, we introduce an interactive method suitable for retargeting both 3D objects and scenes. Initially, the input object or scene is decomposed into a collection of constituent components enclosed by corresponding control bounding volumes which capture the intra‐structures of the object or semantic grouping of objects in the 3D scene. The overall retargeting is accomplished through a constrained optimization by manipulating the control bounding volumes. Without inferring the intricate dependencies between the components, we define a minimal set of constraints that maintain the spatial arrangement and connectivity between the components to regularize the valid retargeting results. The default retargeting behavior can then be easily altered by additional semantic constraints imposed by users. This strategy makes the proposed method highly flexible to process a wide variety of 3D objects and scenes under an unified framework. In addition, the proposed method achieved more general structure‐preserving pattern synthesis in both object and scene levels. We demonstrate the effectiveness of our method by applying it to several complicated 3D objects and scenes.
Behavioural alterations are independent of sickness behaviour in chronic experimental Chagas disease

The existence of the nervous form of Chagas disease is a matter of discussion since Carlos Chagas described neurological disorders, learning and behavioural alterations in Trypanosoma cruzi-infected individuals. In most patients, the clinical manifestations of the acute phase, including neurological abnormalities, resolve spontaneously without apparent consequence in the chronic phase of infection. However, chronic Chagas disease patients have behavioural changes such as psychomotor alterations, attention and memory deficits, and depression. In the present study, we tested whether or not behavioural alterations are reproducible in experimental models. We show that C57BL/6 mice chronically infected with the Colombian strain of T. cruzi (150 days post-infection) exhibit behavioural changes as (i) depression in the tail suspension and forced swim tests, (ii) anxiety analysed by elevated plus maze and open field test sand and (iii) motor coordination in the rotarod test. These alterations are neither associated with neuromuscular disorders assessed by the grip strength test nor with sickness behaviour analysed by temperature variation sand weight loss. Therefore, chronically T. cruzi-infected mice replicate behavioural alterations (depression and anxiety) detected in Chagas disease patients opening an opportunity to study the interconnection and the physiopathology of these two biological processes in an infectious scenario.
Social support, attachment, and drug misuse in suicidal African American women

Abstract This study examined social support and attachment in women with and without drug misuse. Data were collected from 146 African American female suicide attempters who presented at an inner-city hospital. MANOVAs revealed that compared to their counterparts who did not misuse drugs, women who reported drug misuse had lower levels of family and friend support (Social Support Behaviours Scale), lower scores on secure attachment and higher scores on fearful and dismissive attachments (Relationship Style Questionnaire). Low-social support and less secure attachments make treatment engagement challenging and require interventions designed to enhance participation.
Incremental context mining for adaptive document classification

Automatic document classification (DC) is essential for the management of information and knowledge. This paper explores two practical issues in DC: (1) each document has its context of discussion, and (2) both the content and vocabulary of the document database is intrinsically evolving. The issues call for adaptive document classification (ADC) that adapts a DC system to the evolving contextual requirement of each document category, so that input documents may be classified based on their contexts of discussion. We present an incremental context mining technique to tackle the challenges of ADC. Theoretical analyses and empirical results show that, given a text hierarchy, the mining technique is efficient in incrementally maintaining the evolving contextual requirement of each category. Based on the contextual requirements mined by the system, higher-precision DC may be achieved with better efficiency.
Stalwarts in Sport

Abstract This paper reports further analysis of an Omnibus Survey of volunteering in sport, conducted in 2002 for Sport England (Taylor, et al. 2003). From this survey of over 8000 individuals it has been possible to identify those who both volunteer in sports clubs organised by their members, and contribute over 300 hours a year to volunteering in sport. Analysis of the sex, age, education, work status and motivation of these volunteers shows that the only significant distinguishing characteristic of these volunteers is their motivation. This leads to implications for further research, including studies of the career paths of key volunteers, the relation of volunteering to club attachment, and the internal management of clubs.
Operative assessment of predicted generalization errors on non-stationary distributions in data-intensive applications

Data-intensive applications use empirical methods to extract consistent information from huge samples. When applied to classification tasks, their aim is to optimize accuracy on unseen data hence a reliable prediction of the generalization error is of paramount importance. Theoretical models, such as Statistical Learning Theory, and empirical estimations, such as cross-validation, can both fit data-mining classification domains very well, provided some crucial assumptions are verified in advance. In particular, the stationary distribution of the observed data is critical, although it is sometimes overlooked in practice. The paper formulates an operative criterion to verify the stationary assumption; the method applies to both theoretical and practical predictions of generalization errors. The analysis addresses the specific case of clustering-based classifiers; the K-Winner Machine (KWM) model is used as a reference for its known theoretical bounds; cross-validation provides an empirical counterpart for practical comparison. The criterion, based on efficient unsupervised clustering-based probability distribution estimation, is tested experimentally on a set of different, data-intensive applications, including: intrusion detection for computer-network security, optical character recognition, text mining and pedestrian detection. Experimental results confirm the effectiveness of the proposed approach to efficiently detect non stationarity.
Copyright and cultural work: an exploration

This article first discusses the contemporary debate on cultural “creativity” and the economy. Second, it considers the current state of UK copyright law and how it relates to cultural work. Third, based on empirical research on British dancers and musicians, an analysis of precarious cultural work is presented. A major focus is how those who follow their art by way of “portfolio” work handle their rights in ways that diverge significantly from the current simplistic assumptions of law and cultural policy. Our conclusions underline the distance between present top-down conceptions of what drives production in the cultural field and the actual practice of dancers and musicians.
Piecewise smooth chebfuns

Algorithms are described that make it possible to manipulate piecewise-smooth functions on real intervals numerically with close to machine precision. Break points are introduced in some such calculations at points determined by numerical root finding and in others by recursive subdivision or automatic edge detection. Functions are represented on each smooth subinterval by Chebyshev series or interpolants. The algorithms are implemented in object-oriented Matlab in an extension of the chebfun system, which was previously limited to smooth functions on [―1, 1].
Self-esteem in Dyslexic Children

This work was supported by United States Public Health Service general research support grant FR 05521 through the Kaiser Foundation Research Institute. THE HIGH VALUE that our society places on academic achievement is manifested in the early school years by heavy emphasis on reading; yet it is estimated that at least 10 percent of United States children are handicapped by reading incompetence before they reach the seventh grade 1 About one-fourth to onethird of those with reading incompetence have primary developmental dyslexia, a specific difficulty in learning to read, often genetically determined, in a child of at least average general intelligence with no obvious brain lesion or significant impairment of hearing or vision. Initially, the child with primary developmental dyslexia has no emotional disturbance or resistance to conventional methods of instruction.
In competence we trust? Addressing conceptual ambiguity

Purpose – The competence framework continues to be plagued by unresolved conceptual ambiguity. This paper aims to consider other perspectives of managerial performance.Design/methodology/approach – This is a conceptual article that examines and critiques current perspectives of competence based on an extensive literature review.Findings – Sources of conceptual ambiguity are rooted in treating competence as both independent and dependent variables in relation to managerial performance. A managerial learning framework and a career perspective may offer less ambiguous, more promising conceptual frameworks for managerial performance.Research limitations/implications – The arguments presented for moving beyond the competence framework need to be developed into propositions that can be tested empirically.Practical implications – Management development and education activities may not be achieving their intended outcomes due to the level of conceptual ambiguity found with the competence framework. It may be nece.
Atmospheric correction and oceanic constituents retrieval, with a neuro-variational method

Ocean color sensors on board satellite measure the solar radiation reflected by the ocean and the atmosphere. This information, denoted reflectance, is affected for 90% by air molecules and aerosols in the atmosphere and for only 10% by water molecules and phytoplankton cells in the ocean. Our method focuses on the chlorophyll-a concentration (chl-a) retrieval, which is commonly used as a proxy for phytoplankton concentration. Our algorithm, denoted NeuroVaria, computes relevant atmospheric (Angstrom coefficient, optical thickness, single-scattering albedo) and oceanic parameters (chl-a, oceanic particulate scattering) by minimizing the difference over the whole spectrum (visible + near infrared) between the observed reflectance and the reflectance computed from artificial neural networks that have been learned with a radiative transfer model. NeuroVaria has been applied to SeaWiFS (sea-viewing wide field-of-view sensor) imagery in the Mediterranean sea. A comparison with in-situ measurements of the water-leaving reflectance shows that NeuroVaria enables to better reconstruct this component at 443 nm than the standard SeaWiFS processing. This leads to an improvement of the retrieval of the chl-a for the oligotrophic sea. This result is generalized to the entire Mediterranean sea through weekly maps of chl-a.