Miracle-dz/UniFAR-FTUs huggingface dataset:
16 Natural Scene Text Understanding

In a society driven by visual information and with the drastic expansion of low-priced cameras, vision techniques are more and more considered and text recognition is nowadays a fast changing field, which is included in a large spectrum, named text understanding. Previously, text recognition was dealing with documents only; those which were acquired with flatbed, sheet-fed or mounted imaging devices. Recently, handheld scanners such as pen-scanners appeared to acquire small parts of text on a fairly planar surface such as that of a business card. Issues having an impact on image processing are limited to sensor noise, skewed documents and inherent degradations to the document itself. Based on this classical acquisition method, optical character recognition (OCR) systems have been designed for many years to reach a high level of recognition with constrained documents, meaning those falling into traditional layout, with relatively clean backgrounds such as regular letters, forms, faxes, checks and so on and with a sufficient resolution (at least 300 dots per inch (dpi)). With the recent explosion of handheld imaging devices (HIDs), i.e. digital cameras, standalone or embedded in cellular phones or personal digital assistants (PDAs), research on document image analysis entered a new era where breakthroughs are required: traditional document analysis systems fail against this new and promising acquisition mode and main differences and reasons of failures will be detailed in this section. Small, light, and handy, these devices enable the removal of all constraints and all objects, such as natural scenes (NS) in different situations in streets, at home or in planes may be now acquired! Moreover, recent studies [Kim, 2005] announced a decline in scanner sales while projecting that sales of HIDs will keep increasing over the next 10 years.
A qualitative study of mental health help-seeking among Catholic priests

Little is known about Catholic priests' mental health help-seeking. Using consensual qualitative research, this study examined 15 Catholic priests' narratives about help-seeking attitudes, help-seeking behaviours, and offers advice for mental health professionals regarding priest health. Analysis revealed that all 15 priests reported positive attitudes about mental health help-seeking because counselling helped to deal with and heal problems, provided a different, unbiased perspective and allowed for spiritual growth. The majority of participants (9/15; 60%) reported that they have sought help through counselling for various reasons, such as depression and stress. Barriers to help-seeking entailed perceiving no need to seek help, stigma, and concerns about counsellor competence. Participants suggested that mental health professionals understand the importance of prayer to priests, the unique stressors of the priestly role, and the impact of contextual factors (e.g., frequent transfers and sexual abuse scandal) on their health. Implications for future research and clinical practice are discussed.
The Effectiveness of Coping Resources and Strategies Used by Bereaved Parents 1 and 5 Years after the Violent Deaths of Their Children

In this study, we examined the effectiveness of the coping resources and coping strategies by following 173 bereaved parents prospectively for five years after their children's deaths by accident, suicide, homicide, or undetermined violence. Using hierarchical multiple regression procedures, we examined how three predictors influenced parents' mental distress and PTSD: self-esteem, active/affective coping, and repressive coping. The results showed that at one and five years postdeath, self-esteem was a significant predictor of mental distress and PTSD. After controlling for self-esteem, the use of active/affective coping strategies predicted less mental distress for fathers but not for mothers. Active/affective coping strategies were not significant predictors of lowered PTSD symptoms for either mothers or fathers. Rather, repressive coping strategies were significant predictors of higher PTSD symptoms for both mothers and fathers at both one and five years postdeath. The findings suggest the need for interventions that target both gender and outcomes as unique aspects of the violent death bereavement transition.
Information source detection in the SIR model: A sample path based approach

This paper studies the problem of detecting the information source in a network in which the spread of information follows the popular Susceptible-Infected-Recovered (SIR) model. We assume all nodes in the network are in the susceptible state initially except the information source which is in the infected state. Susceptible nodes may then be infected by infected nodes, and infected nodes may recover and will not be infected again after recovery. Given a snapshot of the network, from which we know all infected nodes but cannot distinguish susceptible nodes and recovered nodes, the problem is to find the information source based on the snapshot and the network topology. We develop a sample path based approach where the estimator of the information source is chosen to be the root node associated with the sample path that most likely leads to the observed snapshot. We prove for infinite-trees, the estimator is a node that minimizes the maximum distance to the infected nodes. A reverse-infection algorithm is proposed to find such an estimator in general graphs. We prove that for g-regular trees such that gq > 1, where g is the node degree and q is the infection probability, the estimator is within a constant distance from the actual source with high probability, independent of the number of infected nodes and the time the snapshot is taken. Our simulation results show that for tree networks, the estimator produced by the reverse-infection algorithm is closer to the actual source than the one identified by the closeness centrality heuristic.
Mining micro-practices from operational data

Micro-practices are actual (and usually undocumented or incorrectly documented) activity patterns used by individuals or projects to accomplish basic software development tasks, such as writing code, testing, triaging bugs, or mentoring newcomers. The operational data in software repositories presents the tantalizing possibility to discover such fine-scale behaviors and use them to understand and improve software development. We propose a large-scale evidence-based approach to accomplish this by first creating a mirror of the projects in the open source universe. The next step would involve the inductive generalization from in-depth studies of specific projects from one side and the categorization of micro-practices in the entire universe from the other side.
The Neural Basis of Retrograde Memory: Evidence From Positron Emission Tomography for the Role of Non-mesial Temporal Lobe Structures

Abstract Lesion studies have suggested that retrieval of old, factual, concrete knowledge (retrograde memory) and learning of new, factual, concrete knowledge (anterograde memory) depend on distinct systems in the temporal lobe. Here we report a case study using serial neuropsychological assessments and serial structural and functional imaging studies which provides further support for this notion. A 70-year-old right-handed woman with limbic encephalitis attributed to thymoma was evaluated 4 months after diagnosis. Severe multimodal anterograde and retrograde memory defects were found. An [18F] fluorodeoxyglucose (FDG) resting positron emission tomography (PET) scan showed diffuse cortical, but especially right anterolateral temporal hypometabolism. Two years later, there was marked resolution of the retrograde memory defect, with persistent anterograde memory Impairment. A repeat FDG resting PET showed improved metabolism in the anterolateral temporal cortex and in other cortical regions. Metabolism in .
Approximately Counting H-Colourings is #BIS-Hard

We consider the problem of counting H-colourings from an input graph G to a target graph H . We show that if H is any fixed graph without trivial components, then the problem is as hard as the well-known problem #BIS, which is the problem of (approximately) counting independent sets in a bipartite graph. #BIS is a complete problem in an important complexity class for approximate counting, and is believed not to have an FPRAS. If this is so, then our result shows that for every graph H without trivial components, the H-colouring counting problem has no FPRAS. This problem was studied a decade ago by Goldberg, Kelk and Paterson. They were able to show that approximately sampling H-colourings is #BIS-hard, but it was not known how to get the result for approximate counting. Our solution builds on non-constructive ideas using the work of Lovász.
Smart-homes: A New Challenge for Artificial Intelligence

: Recent advances in information and communication technology opened the perspective of embedding “intelligence” in a number of components of our home, transforming it into a kind of multi-functional robot, usually referred to as “smart-home”. Leaving apart an excess of technology that probably we don’t want in our everyday life, a number of potential facilities exist that could effectively increase the quality of life by solving important social problems, such as security, elderly people leaving alone, child care, handicapped support. Here, we will investigate how AI techniques can be effectively integrated into smart-home technology solving important problems, which are beyond the reach of non-AI techniques. The first application area is “security and protection” intended either as “protection” against intruders or as protection/rescue of a person with respect to possible accidents in the domestic environment. A number of techniques have been proposed to detect risk conditions or to detect the occurrence of an accident. Some of them are based on image analysis and others make use of specific sensors that the person to be protected is required to wear. However, no single technique is fully reliable for deploying critical applications. We will discuss how AI methods are essential in order to trespass these limitations. The second application area is user interface. Even though simple traditional interfaces, such as switches, buttons, or infrared remote-controls, are the ones most users still prefer, there are a number of cases where advanced interfaces such as vocal or gestural are required. This is the case for handicapped people with severe mobility reduction due to aging or disease. This is a challenging area where machine learning and adaptive algorithms can be exploited to quickly develop specific solutions tailored to the user physiological conditions.
Steward organization in a professional union: The case of the Royal College of nursing

This article examines notions of renewal in a professional union by exploring the developing role of the steward in the Royal College of Nursing. Drawing on survey and other data, it assesses different dimensions of the union renewal process linked to workplace activities, issues and relations. The findings suggest that the process of renewal has been based primarily upon member rather than management-facing activities, although there is strong evidence to suggest variation in the activities carried out by the RCN’s ordinary and senior stewards.
Learning recursive programs with cooperative coevolution of genetic code mapping and genotype

The Probabilistic Adaptive Mapping Developmental Genetic Programming (PAM DGP) algorithm that cooperatively coevolves a population of adaptive mappings and associated genotypes is used to learn recursive solutions given a function set consisting of general (not implicitly recursive) machine-language instructions. PAM DGP using redundant encodings to model the evolution of the biological genetic code is found to more efficiently learn 2nd and 3rd order recursive Fibonacci functions than related developmental systems and traditional linear GP. PAM DGP using redundant encoding is also demonstrated to produce the semantically highest quality solutions for all three recursive functions considered (Factorial, 2nd and 3rd order Fibonacci). PAM DGP is then shown to have produced such solutions by evolving redundant mappings to select and emphasize appropriate subsets of the function set useful for producing the naturally recursive solutions.
The Place of Emotion in Identity.

Two studies are presented that examine the place of emotion in self-construct models. The first study (N = 20 female subject; age range: 15 to 25 years) presents the three categories of adolescent identity types produced with the self-construct models: connected, contracted, and expanded. The second study (N = 49 male and female subjects; age range: 10 to 17 years) verifies that the contracted and expanded categories are more typical of adolescents than of children or adults. Contracted models of adolescent identity do not contain active negative emotion. Both the connected and expanded models contain both negative and positive emotion, but the expanded models contain more negative. Within the identity constructs, there is an indication of emotional change accompanying identity change in adolescence.
The Role of microRNA Markers in the Diagnosis, Treatment, and Outcome Prediction of Spinal Cord Injury

Spinal cord injury (SCI) is a devastating condition that affects many people worldwide. Treatment focuses on controlling secondary injury cascade and improving regeneration. It has recently been suggested that both the secondary injury cascade and the regenerative process are heavily regulated by microRNAs (miRNAs). The measurement of specific biomarkers could improve our understanding of the disease processes, and thereby provide clinicians with the opportunity to guide treatment and predict clinical outcomes after SCI. A variety of miRNAs exhibit important roles in processes of inflammation, cell death, and regeneration. These miRNAs can be used as diagnostic tools for predicting outcome after SCI. In addition, miRNAs can be used in the treatment of SCI and its symptoms. Significant laboratory and clinical evidence exist to show that miRNAs could be used as robust diagnostic and therapeutic tools for the treatment of patients with SCI. Further clinical studies are warranted to clarify the importance of each subtype of miRNA in SCI management.
The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies

Preface and Overview Acknowledgements 1. The Distinctiveness of Comparative social Science 2. Heterogeneity and Causal Complexity 3. Case-Oriented Comparative Methods 4. The Variable-Oriented Approach 5. Combined Versus Synthetic Comparative Strategies 6. A Boolean Approach to Qualitative Comparison: Basic Concepts 7. Extensions of Boolean Methods of Qualitatve Comparison 8. Applications of Boolean Methods of Qualitative Comparison 9. The Dialogue of Ideas and Evidence in Social Research Bibliography Index
Coupling Between Local Cerebral Blood Flow and Metabolism After Hypertonic/Hyperoncotic Fluid Resuscitation from Hemorrhage in Conscious Rats

The effects of small volume hypertonic/hyperoncotic fluid resuscitation from hemorrhage on brain metabolism and blood flow were evaluated by autoradiographic techniques with high spatial resolution.The data were compared to fluid resuscitation with a volume equal to shed blood of isotonic 6% hydroxyethyl starch solution (HES) and a control group without hemorrhage and fluid resuscitation (n = 6 in each group). In conscious rats, volume-controlled hemorrhage for 30 min (30 mL/kg body weight, resulting in a blood loss of approximately 50% of the circulating blood volume) was followed by intravenous infusion of a hypertonic/hyperoncotic saline hydroxyethyl starch solution (HTHO; 7.5% saline/10% hydroxyethyl starch, 4.0 mL/kg body weight). Local cerebral blood flow (LCBF) and local cerebral glucose utilization (LCGU) were measured in 34 brain structures 2 h after fluid resuscitation by means of the quantitative autoradiographic iodo [(14) C]antipyrine and 2-[(14) C]-deoxy-D-glucose methods. Compared to the untreated control group, LCBF increased significantly in all brain regions analyzed after fluid resuscitation with HTHO (mean, +63%) or HES (mean, +56%). The increases in LCBF after fluid resuscitation were sufficient to restore cerebral oxygen delivery to the level calculated for the untreated control group. LCGU was unchanged after fluid resuscitation. The close relationship between LCGU and LCBF observed in the control group (r = 0.95) was preserved after hemorrhage and fluid resuscitation with HTHO (r = 0.97) and HES (r = 0.96), although the LCBF-to-LCGU ratio was reset to a higher level (1.5 mL/micro mol in the control group and 2.7 mL/micro mol after fluid resuscitation with HTHO and HES, P < 0.05). We conclude that the increase in LCBF compensates for the reduction of arterial oxygen content to maintain cerebral oxygen delivery. Therefore, "small volume resuscitation" appears to be as effective as resuscitation with large volumes of isotonic HES in meeting the circulatory and metabolic demands of the brain tissue within the first 2 h after fluid resuscitation from hemorrhage. (Anesth Analg 1996;82:52-60)
Cell Cycle–Regulated Attachment of the Ubiquitin-Related Protein Sumo to the Yeast Septins

SUMO is a ubiquitin-related protein that functions as a posttranslational modification on other proteins. SUMO conjugation is essential for viability in Saccharomyces cerevisiae and is required for entry into mitosis. We have found that SUMO is attached to the septins Cdc3, Cdc11, and Shs1/Sep7 specifically during mitosis, with conjugates appearing shortly before anaphase onset and disappearing abruptly at cytokinesis. Septins are components of a belt of 10-nm filaments encircling the yeast bud neck. Intriguingly, only septins on the mother cell side of the bud neck are sumoylated. We have identified four major SUMO attachment-site lysine residues in Cdc3, one in Cdc11, and two in Shs1, all within the consensus sequence (IVL)KX(ED). Mutating these sites eliminated the vast majority of bud neck-associated SUMO, as well as the bulk of total SUMO conjugates in G2/M-arrested cells, indicating that sumoylated septins are the most abundant SUMO conjugates at this point in the cell cycle. This mutant has a striking defect in disassembly of septin rings, resulting in accumulation of septin rings marking previous division sites. Thus, SUMO conjugation plays a role in regulating septin ring dynamics during the cell cycle.
The Telephone Interview for Cognitive Status (TICS): Reliability and validity in a stroke sample

The Telephone Interview for Cognitive Status (TICS) is an 11‐item screening test (maximum score=41 points) that was developed for the assessment of cognitive function in patients with Alzheimer's disease who are unwilling or unable to be examined in person. To investigate the 1‐month test‐retest reliablility and validity of the TICS in a stroke sample, we administered it twice by telephone to 36 stroke patients (age = 72.3 ± 8.9; education = 9.7 ± 4.7) and 36 stroke‐free non‐demented control subjects (age = 71.8 ± 6.8; education = 13.1 ± 4.1). Dementia was diagnosed in six stroke patients based on neuropsychological and functional examinations performed during an outpatient visit and the Mini‐Mental State Examination (MMSE) was also given. Multiple regression analyses determined that stroke status was significantly related to performance on the TICS (β= −0.26, p = 0.006), while adjusting for demographic variables. Among stroke patients, test‐retest reliability was excellent (r = 0.90, p < 0.001) and performance was significantly correlated with MMSE score (r = 0.86, p <0.001). A TICS cutoff score <25 best distinguished between demented and non‐demented patients; sensitivity (1.00) and specificity (0.83) were excellent and comparable to the sensitivity (0.83) and specificity (0.87) of the MMSE, with dementia defined as a score <24/30. We conclude that the TICS is a reliable mental status test that can provide accurate information regarding cognitive function in stroke patients who cannot be assessed in person.
Red-RF: Reduced Random Forest for Big Data Using Priority Voting &amp; Dynamic Data Reduction

Random Forests have been used as effective ensemble models for classification. We present in this paper a new type of Random Forests (RFs) called Red(uced) RF that adopts a new dynamic data reduction principle and a new voting mechanism called Priority Vote Weighting (PV) which improve accuracy, execution time and AUC values compared to Breiman's RF. Red-RF also shows that the strength of a random forest can increase without noticeably increasing correlation between the trees. We then compare performance of Red-RF and Breiman's RF in 8 experiments that involve classification problems with datasets of different sizes. Finally, we conduct 2 additional experiments that involve considerably big datasets with one million points in each.
Petri nets-based method to model and analyse the self-healing web service composition

Service composition is an important means for integrating the individual web services to create new value added systems that can satisfy complex requirements. Such applications are subject to unexpected failure owing to the distributive and heterogeneous environment of web service. In this paper, we propose a Petri nets-based method to model and analyse the self-healing service composition. Aspect oriented programming is used to extract composition processes and self-healing strategy as the core and crosscutting concerns. A self-healing strategy of component and service composition is proposed, and the related operations of self-healing are abstracted as meta-objects by using reflection mechanism. Petri nets are used to construct the base layer model, meta layer model, meta-object protocol and other components, thus forming the self-healing model. The operational semantics and related theories of Petri nets help prove its effectiveness and correctness. A simulation example shows that our approach correctly describes the self-healing process of service composition, and contributes to improving the quality.
The Development of Thought: Equilibration of Cognitive Structures

Interestingly, the development of thought equilibration of cognitive structures that you really wait for now is coming. It's significant to wait for the representative and beneficial books to read. Every book that is provided in better way and utterance will be expected by many peoples. Even you are a good reader or not, feeling to read this book will always appear when you find it. But, when you feel hard to find it as yours, what to do? Borrow to your friends and don't know when to give back it to her or him.
Least squares time sequenced adaptive filtering for the detection of fragmented micropotentials

The authors show a signal enhancement technique based on a time-sequenced adaptive filter (TSAF). The time-sequenced approach allows enhancement of signals with rapidly time-varying statistics if this time-variance exhibits cyclostationary characteristics. In event based signals such as ECGs this time-invariance is synchronised with each beat and is hence cyclostationary. Instead of conventional LMS based TSAF the authors are controlling their filter through a least squares (LS) updating criterion. They are able to show a significant convergence rate improvement using LS adaption and therefore they require much shorter data sets. <<ETX>>