LLukas22/scidocs huggingface dataset:
Pediatric lipoblastoma in the head and neck: a systematic review of 48 reported cases.

BACKGROUND
Lipoblastoma is an exceedingly rare cause of pediatric head and neck masses. There have been 47 cases previously reported in the English literature. We present an additional case and review of the available literature on this rare neoplasm.


OBJECTIVE
To review and assess the current published literature regarding the efficacy of preserving neurovascular structures in the surgical management of pediatric lipoblastoma.


METHODS
Literature analysis of case reports was performed. MEDLINE was searched for the terms "neonatal lipoblastoma", "lipoblastomatosis", and "benign lipoblastoma". Results in the English literature were mined for relevant clinical data when available. The citations of case reviews found were searched to find additional cases.


RESULTS
Including our new case, a total of 48 cases of head and neck lipoblastoma have been reported in the English literature within 23 manuscripts. Four manuscripts presented cases series (Evidence Based Medicine Level 4) and 19 were case reports (Level 5). The median sample size was 1 (range 1-4). For those 14 articles (N=23 cases) reporting follow-up, the median follow-up duration was 22 months. Male to female ratio was 2.1:1 with an average age at presentation of 2.1 years (range: newborn to 12 years). Lesions ranged from 3 to 12 cm in longest diameter. Recurrence was seen in 27% of patients in which there was at least 1-year follow-up. The most common presenting symptoms were painless enlarging neck mass (53%, 17/32) and respiratory distress (12%, 4/32). An exact binomial sign test indicated that most authors recommend conservative complete excision with preservation of vital structures with 10 of 11 authors giving a stance supporting conservative surgical resection, p=.012.


CONCLUSIONS
Our findings suggest that although total excision is ideal and curative, subtotal resection may be a viable treatment alternative for lipoblastoma of the head and neck. This tumor presents a clinical challenge and should be considered in infants presenting with a cervical mass. It is difficult to differentiate from the much more common lymphangioma on clinical and radiological examination. Additionally, the potential for rapid growth and adhesion to neurovascular tissue makes surgical resection arduous. Nonetheless, recurrence rates for head and neck lipoblastomas are similar to those rates observed elsewhere in the body.
Informant discrepancies in clinical reports of youths and interviewers' impressions of the reliability of informants.

OBJECTIVE
In this study the authors examined whether discrepancies between parent and youth reports of the youth's emotional and behavioral functioning are related to interviewers' reliability ratings of parents and youths.


METHODS
In a consecutive case series analysis of 328 parents and youths aged 11-17 years, parents and youths provided reports of youth emotional and behavioral functioning and participated in structured clinical interviews. At the conclusion of the interviews, interviewers rated the reliability of informants. Interviewers rated youths' clinical severity and parents and youths provided information on youth demographics. Nominal logistic regressions tested patterns of discrepancies between parent and youth reports (i.e., which informant consistently reported greater degrees of youth emotional and behavioral concerns than the other) as predictors of interviewers' ratings of the reliability of parents and youths. All analyses controlled for variance explained by youth demographics and youth severity.


RESULTS
When parents reported greater degrees of youth emotional and behavioral concerns than youths self-reported, interviewers were likely to rate the youth as an unreliable informant, and were unlikely to rate the youth as an unreliable informant when parents reported less concerns than youths self-reported. However, interviewers' ratings of parents' reliability did not relate to the discrepancies between reports, regardless of which informant reported greater degrees of youth concerns.


CONCLUSIONS
Prior research indicates that informant discrepancies potentially reveal important information of youths' emotional and behavioral concerns, such as the settings in which youths express these concerns. Yet, when parents and youths disagree in their clinical reports of the youth's functioning, this relates to whether a clinical interviewer views the youth as a reliable informant of their own functioning. To increase the cost-effectiveness and clinical utility of multi-informant clinical evaluations, practitioners and researchers should anticipate informant discrepancies and predict what they may represent before conducting clinical evaluations.
Fiberoptic ductoscopy for breast cancer patients with nipple discharge

Background: Breast cancer and precancer are thought to originate in the lining of the milk duct, but until recently, we have not had direct access to this area other than in tissue removed blindly by core biopsy or fine-needle aspiration. Fiberoptic ductoscopy (FDS) is an emerging technique that allows direct visual access of the ductal system of the breast through nipple orifice cannulation and exploration. To date, this technique has been used only in pilot studies. Previously, we have demonstrated that fiberoptic ductoscopy in patients with and without nipple discharge is a safe and effective means of visualizing the intraductal lesion. When combined with cytology, it is a screening technique that has high predictive value. Methods: We applied ductoscopy to 415 women with nipple discharge with the specific intent of detecting those patients with nipple discharge who had intraductal carcinoma (DCIS) as the basis of their discharge. Results: In this cohort of patients, ductoscopy was successful in visualizing an intraductal lesion in 166 patients (40%). In these cases, ductal lavage following ductoscopy increased the yield of cytologically interpretable ductal epithelial cells 100-fold compared to discharge fluid alone. In the majority of these patients, FDS examination detected lesions that had the appearance of typical papillomas. However, in 10 patients, the intraductal lesion exhibited one of several atypical features, including bleeding, circumferential obstruction, and gross fungating projections. In eight of these patients, the subsequent histopathology turned out to be DCIS. In two of these eight patients, endoscopic biopsy revealed cytologically malignant cells; in two others, ductal lavage (washings) revealed cytologically malignant cells. In three additional patients, although FDS examination uncovered a typical papilloma that was not biopsied, ductal lavage (washings) revealed cytologically malignant cells. On surgical pathology review of the extirpated lesions, all 11 patients were subsequently shown to have DCIS. Of these 11 cases of DCIS that were initially detected with a combination of FDS and ductal lavage cytology, six were completely negative on mammogram and physical exam. Conclusion: Although nipple discharge is an unusual presentation for DCIS, in patients with nipple discharge, FDS with ductal lavage cytology is a useful technique for diagnosing DCIS prior to definitive surgery.
Data mining in manufacturing: a review based on the kind of knowledge

In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, such as product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection and so on. Data mining has emerged as an important tool for knowledge acquisition in manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with an special emphasis on the type of functions to be performed on data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been applied to the abstracts and keywords of 150 identified literatures to identify the research gaps and find the linkages between knowledge area, knowledge type and data mining tools and techniques applied. 1 Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, Loughborough, Leicestershire, UK, LE113TU
Non-line-of-sight Imaging with Partial Occluders and Surface Normals.

Fig. 1. Non-line-of-sight (NLOS) imaging aims at recovering the shape and albedo of objects hidden from a camera or a light source. Using ultra-fast pulsed illumination and single photon detectors, the light transport in the scene is sampled for visible objects (left). The global illumination components of these time-resolved measurements (A,E) contain sufficient information to estimate the shape of hidden objects (B,C). Using a novel formulation for NLOS light transport that models partial occlusions of hidden objects (D) via visibility terms (F), we demonstrate higher-fidelity reconstructions (C) than previous approaches to NLOS imaging (B).
Author ' s personal copy Video Games : Good , Bad , or Other ?

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Deep Reinforcement Learning for Continuous Control

Reinforcement learning is a mathematical framework for agents to interact intelligently with their environment. In this field, real-world control problems are particularly challenging because of the noise and the high-dimensionality of input data (e.g., visual input). In the last few years, deep neural networks have been successfully used to extract meaning from such data. Building on these advances, deep reinforcement learning achieved stunning results in the field of artificial intelligence, being able to solve complex problems like Atari games [1] and Go [2]. However, in order to apply the same methods to real-world control problems, deep reinforcement learning has to be able to deal with continuous action spaces. In this thesis, Deep Deterministic Policy Gradients, a deep reinforcement learning method for continuous control, has been implemented, evaluated and put into context to serve as a basis for further research in the field.
Congruent leadership: values in action.

AIM(S)
To discuss the significance of an appropriate leadership theory in order to develop an understanding of clinical leadership.


BACKGROUND
Leadership theories developed from management and related paradigms, particularly transformational leadership, may be ineffective in supporting nurses to gain insights into clinical leadership or to develop and implement clinical leadership skills. Instead, congruent leadership theory, based on a match between the clinical leaders' actions and their values and beliefs about care and nursing, may offer a more firm theoretical foundation on which clinical nurses can build an understanding of and capacity to implement clinical leadership or become clinical leaders. Evaluation The information used is drawn from the contemporary literature and a study conducted by the author.


KEY ISSUE(S)
Leadership can be better understood when an appropriate theoretical foundation is employed.


CONCLUSIONS
With regard to clinical leadership, congruent leadership is proposed as the most appropriate theory.


IMPLICATIONS FOR NURSING MANAGEMENT
It is important to recognize that leadership theories based on a management paradigm may not be appropriate for all clinical applications. Education should be aimed specifically at clinical leaders, recognizing that clinical leaders are followed not for their vision or creativity (even if they demonstrate these), but because they translate their values and beliefs about care into action.
Rule extraction from trained adaptive neural networks using artificial immune systems

Although artificial neural network (ANN) usually reaches high classification accuracy, the obtained results sometimes may be incomprehensible. This fact is causing a serious problem in data mining applications. The rules that are derived from ANN are needed to be formed to solve this problem and various methods have been improved to extract these rules. Activation function is critical as the behavior and performance of an ANN model largely depends on it. So far there have been limited studies with emphasis on setting a few free parameters in the neuron activation function. ANN’s with such activation function seem to provide better fitting properties than classical architectures with fixed activation function neurons [Xu, S., & Zhang, M. (2005). Data mining – An adaptive neural network model for financial analysis. In Proceedings of the third international conference on information technology and applications]. In this study a new method that uses artificial immune systems (AIS) algorithm has been presented to extract rules from trained adaptive neural network. Two real time problems data were investigated for determining applicability of the proposed method. The data were obtained from University of California at Irvine (UCI) machine learning repository. The datasets were obtained from Breast Cancer disease and ECG data. The proposed method achieved accuracy values 94.59% and 92.31% for ECG and Breast Cancer dataset, respectively. It has been observed that these results are one of the best results comparing with results obtained from related previous studies and reported in UCI web sites. 2007 Elsevier Ltd. All rights reserved.
Antibodies to citrullinated α-enolase peptide 1 and clinical and radiological outcomes in rheumatoid arthritis.

INTRODUCTION
The anticyclic citrullinated peptide 2 (anti-CCP2) assay is a generic test for antibodies to citrullinated proteins, among which there is a subset of about 50% with antibodies to citrullinated enolase peptide 1 (CEP-1). The anti-CEP-1 positive subset is strongly associated with the HLA-DRB1 shared epitope and its interaction with smoking.


OBJECTIVE
To investigate whether anti-CEP-1 antibodies may be helpful in predicting outcome.


METHODS
Anti-CEP-1 and anti-CCP2 antibodies were measured in two prospective cohorts of patients (Karolinska n=272, Norfolk Arthritis Register (NOAR) n=408) with early rheumatoid arthritis (RA). Outcomes measured were C-reactive protein, erythrocyte sedimentation rate, visual analogue scales for pain and global assessment of disease activity, Health Assessment Questionnaire, physician's assessment, swollen and tender joint counts and radiological progression.


RESULTS
Anti-CCP2 antibodies were present in 57% and 50%, and anti-CEP-1 in 27% and 24% of the Karolinska and NOAR cohorts, respectively. Importantly, no statistically significant differences in clinical outcomes were demonstrated between the anti-CEP-1-/CCP2+ and the anti-CEP-1+/CCP2+ subsets in either cohort, or in radiological outcomes in the Karolinska cohort.


CONCLUSION
Although antibodies to specific citrullinated proteins may have distinct genetic and environmental risk factors, the similarity in clinical phenotype suggests that they share common pathways in the pathogenesis of joint disease in RA.
Predominant Leptospiral Serogroups Circulating among Humans, Livestock and Wildlife in Katavi-Rukwa Ecosystem, Tanzania

BACKGROUND
Leptospirosis is a worldwide zoonotic disease and a serious, under-reported public health problem, particularly in rural areas of Tanzania. In the Katavi-Rukwa ecosystem, humans, livestock and wildlife live in close proximity, which exposes them to the risk of a number of zoonotic infectious diseases, including leptospirosis.


METHODOLOGY/PRINCIPAL FINDINGS
A cross-sectional epidemiological study was carried out in the Katavi region, South-west Tanzania, to determine the seroprevalence of Leptospira spp in humans, domestic ruminants and wildlife. Blood samples were collected from humans (n = 267), cattle (n = 1,103), goats (n = 248), buffaloes (n = 38), zebra (n = 2), lions (n = 2), rodents (n = 207) and shrews (n = 11). Decanted sera were tested using the Microscopic Agglutination Test (MAT) for antibodies against six live serogroups belonging to the Leptospira spp, with a cutoff point of ≥ 1:160. The prevalence of leptospiral antibodies was 29.96% in humans, 30.37% in cattle, 8.47% in goats, 28.95% in buffaloes, 20.29% in rodents and 9.09% in shrews. Additionally, one of the two samples in lions was seropositive. A significant difference in the prevalence P<0.05 was observed between cattle and goats. No significant difference in prevalence was observed with respect to age and sex in humans or any of the sampled animal species. The most prevalent serogroups with antibodies of Leptospira spp were Sejroe, Hebdomadis, Grippotyphosa, Icterohaemorrhagie and Australis, which were detected in humans, cattle, goats and buffaloes; Sejroe and Grippotyphosa, which were detected in a lion; Australis, Icterohaemorrhagie and Grippotyphosa, which were detected in rodents; and Australis, which was detected in shrews. Antibodies to serogroup Ballum were detected only in humans.


CONCLUSIONS
The results of this study demonstrate that leptospiral antibodies are widely prevalent in humans, livestock and wildlife from the Katavi-Rukwa ecosystem. The disease poses a serious economic and public health threat in the study area. This epidemiological study provides information on circulating serogroups, which will be essential in designing intervention measures to reduce the risk of disease transmission.
Particle Swarm Optimization

A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described,
How to draw a group?

Abstract A map is at the same time a group. To represent a map (that is, a graph drawn on the sphere or on another surface) we usually use a pair of permutations on the set of the ‘ends’ of edges. These permutations generate a group which we call a cartographic group . The main motivation for the study of the cartographic group is the so-called theory of “dessins d'enfants’ of Grothendieck, which relates the theory of maps to Galois theory [24]. In the present paper we address the questions of identifying the cartographic group for a given map, and of constructing the maps with a given cartographic group.
Verifying android applications using Java PathFinder

Mobile application testing is a specialised and complex field. Due to mobile applications' event driven design and mobile runtime environment, there currently exist only a small number of tools to verify these applications. This paper describes the development of JPF-ANDROID, an Android application verification tool. JPF-ANDROID is built on Java Pathfinder, a Java model checking engine. JPF-ANDROID provides a simplified model of the Android framework on which an Android application can run. It then allows the user to script input events to drive the application flow. JPF-ANDROID provides a way to detect common property violations such as deadlocks and runtime exceptions in Android applications.
Progressing the definition of "e-book"

Purpose – This paper aims to propose a definition for the concept “e-book” on the basis of an analysis of existing definitions. The e-book marketplace is growing rapidly and the potential impact of e-books on publishers, librarian and users is increasing in significance. Yet, there is agreement that despite a few widely accepted definitions there is no consensus on the definition of the term e-book, and, further that consensus on the definition would be beneficial for both researchers and practitioners. Design/methodology/approach – This paper starts with a brief overview of the developments in e-books, covering technologies, marketplaces, and the attractions and challenges associated with e-books for users and libraries. It then reports on a content analysis of existing definitions of e-book. A collection of definitions was compiled through an exhaustive literature review. Content analysis was performed to identify the frequency of occurrence of key words and phrases across these definitions. Findings – There is a consensus that definitions of e-book should include reference to: the digital or electronic nature of e-books, analogy to printed book, some indication of the content of e-books, and some allusion to e-book technologies. We propose a two-part definition that embraces these themes, but also reflects the in-use features of the e-book. Conclusions and recommendations make proposals for further discussion on the concept of e-book and, more widely, into the publication, acquisition and use of e-books. Originality/value – In the rapidly developing e-book marketplace it is essential to have agreement on the definition of e-book, and furthermore, such a definition needs to reflect both the persistent characteristics of e-books, and their dynamic and developing nature.
Resolvin E1 Reverses Experimental Periodontitis and Dysbiosis.

Periodontitis is a biofilm-induced inflammatory disease characterized by dysbiosis of the commensal periodontal microbiota. It is unclear how natural regulation of inflammation affects the periodontal biofilm. Promoters of active resolution of inflammation, including resolvin E1 (RvE1), effectively treat inflammatory periodontitis in animal models. The goals of this study were 1) to compare periodontal tissue gene expression in different clinical conditions, 2) to determine the impact of local inflammation on the composition of subgingival bacteria, and 3) to understand how inflammation impacts these changes. Two clinically relevant experiments were performed in rats: prevention and treatment of ligature-induced periodontitis with RvE1 topical treatment. The gingival transcriptome was evaluated by RNA sequencing of mRNA. The composition of the subgingival microbiota was characterized by 16S rDNA sequencing. Periodontitis was assessed by bone morphometric measurements and histomorphometry of block sections. H&E and tartrate-resistant acid phosphatase staining were used to characterize and quantify inflammatory changes. RvE1 treatment prevented bone loss in ligature-induced periodontitis. Osteoclast density and inflammatory cell infiltration in the RvE1 groups were lower than those in the placebo group. RvE1 treatment reduced expression of inflammation-related genes, returning the expression profile to one more similar to health. Treatment of established periodontitis with RvE1 reversed bone loss, reversed inflammatory gene expression, and reduced osteoclast density. Assessment of the rat subgingival microbiota after RvE1 treatment revealed marked changes in both prevention and treatment experiments. The data suggest that modulation of local inflammation has a major role in shaping the composition of the subgingival microbiota.