LLukas22/scidocs huggingface dataset:
An Adaptive Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-ion Batteries

Prognostics is an emerging science of predicting the health condition of a system (or its components) based upon current and previous system states. A reliable predictor is very useful to a wide array of industries to predict the future states of the system such that the maintenance service could be scheduled in advance when needed. In this paper, an adaptive recurrent neural network (ARNN) is proposed for system dynamic state forecasting. The developed ARNN is constructed based on the adaptive/recurrent neural network architecture and the network weights are adaptively optimized using the recursive Levenberg-Marquardt (RLM) method. The effectiveness of the proposed ARNN is demonstrated via an application in remaining useful life prediction of lithium-ion batteries. *
Credit Card Fraud Detection with Artificial Immune System

We apply Artificial Immune Systems(AIS) [4] for credit card fraud detection and we compare it to other methods such as Neural Nets(NN) [8] and Bayesian Nets(BN) [2], Naive Bayes(NB) and Decision Trees(DT) [13]. Exhaustive search and Genetic Algorithm(GA) [7] are used to select optimized parameters sets, which minimizes the fraud cost for a credit card database provided by a Brazilian card issuer. The specifics of the fraud database are taken into account, such as skewness of data and different costs associated with false positives and negatives. Tests are done with holdout sample sets, and all executions are run using Weka [18], a publicly available software. Our results are consistent with the early result of Maes in [12] which concludes that BN is better than NN, and this occurred in all our evaluated tests. Although NN is widely used in the market today, the evaluated implementation of NN is among the worse methods for our database. In spite of a poor behavior if used with the default parameters set, AIS has the best performance when parameters optimized by GA are used.
Relationships between sleep, physical activity and human health

Although sleep and exercise may seem to be mediated by completely different physiological mechanisms, there is growing evidence for clinically important relationships between these two behaviors. It is known that passive body heating facilitates the nocturnal sleep of healthy elderly people with insomnia. This finding supports the hypothesis that changes in body temperature trigger somnogenic brain areas to initiate sleep. Nevertheless, little is known about how the core and distal thermoregulatory responses to exercise fit into this hypothesis. Such knowledge could also help in reducing sleep problems associated with nocturnal shiftwork. It is difficult to incorporate physical activity into a shiftworker's lifestyle, since it is already disrupted in terms of family commitments and eating habits. A multi-research strategy is needed to identify what the optimal amounts and timing of physical activity are for reducing shiftwork-related sleep problems. The relationships between sleep, exercise and diet are also important, given the recently reported associations between short sleep length and obesity. The cardiovascular safety of exercise timing should also be considered, since recent data suggest that the reactivity of blood pressure to a change in general physical activity is highest during the morning. This time is associated with an increased risk in general of a sudden cardiac event, but more research work is needed to separate the influences of light, posture and exercise per se on the haemodynamic responses to sleep and physical activity following sleep taken at night and during the day as a nap.
Long-term effects of negotiated treatment plans on self-management behaviors and satisfaction with care among women with asthma.

OBJECTIVE
To examine characteristics of women with negotiated treatment plans, factors that contribute to newly forming a treatment plan, and the impact of plans on asthma management, and their satisfaction with care over 2 years.


METHODS
Data came from telephone interviews with 324 women with asthma at baseline, 12 and 24 months. The effect of having a negotiated treatment plan on medication adherence, asking the physician questions about asthma, asthma management self-efficacy, and satisfaction with care was assessed over 24 months. Data were analyzed using mixed models. Analyses controlled for patient characteristics.


RESULTS
Thirty-eight percent of participants reported having a negotiated treatment plan at three time points. Seeing an asthma specialist (χ(2)(1) = 24.07, p < .001), was associated with having a plan. Women who did not have a negotiated treatment plan at baseline, but acquired one at 12 or 24 months, were more likely to report greater urgent office visits for asthma (odds ratio (OR) = 1.37, 95% confidence interval (CI) = 1.07-1.61). No associations were observed between having a plan and urgent healthcare use or symptom frequency. When adjusting for household income, level of asthma control, and specialty of the caregiving provider, women who did not have a negotiated treatment plan (OR = 0.28, 95% CI = 0.09-0.79) and those with a plan at fewer than three time points (OR = 0.30, 95% CI = 0.11-0.83) were less likely to report medication adherence and satisfaction with their care (regression coefficient (standard error) = -0.65 (0.17), p < .001). No differences in asthma management self-efficacy or asking the doctor questions about asthma were observed.


CONCLUSION
Women with asthma who had a negotiated treatment plan were more likely to see an asthma specialist. In the long-term, not having a treatment plan that is developed in partnership with a clinician may have an adverse impact on medication use and patient views of clinical services.
Smart Driving of a Vehicle Using Model Predictive Control for Improving Traffic Flow

Traffic management on road networks is an emerging research field in control engineering due to the strong demand to alleviate traffic congestion in urban areas. Interaction among vehicles frequently causes congestion as well as bottlenecks in road capacity. In dense traffic, waves of traffic density propagate backward as drivers try to keep safe distances through frequent acceleration and deceleration. This paper presents a vehicle driving system in a model predictive control framework that effectively improves traffic flow. The vehicle driving system regulates safe intervehicle distance under the bounded driving torque condition by predicting the preceding traffic. It also focuses on alleviating the effect of braking on the vehicles that follow, which helps jamming waves attenuate to in the traffic. The proposed vehicle driving system has been evaluated through numerical simulation in dense traffic.
Rational Transformations of Formal Power Series

Formal power series are an extension of formal languages. Recognizable formal power series can be captured by the so-called weighted finite automata, generalizing finite state machines. In this paper, motivated by codings of formal languages, we introduce and investigate two types of transformations for formal power series. We characterize when these transformations preserve rationality, generalizing the recent results of Zhang [15] to the formal power series setting. We show, for example, that the "square-root" operation, while preserving regularity for formal languages, preserves rationality for formal power series when the underlying semiring is commutative or locally finite, but not in general.
Persistent isolationist or collaborator? The nurse's role in interprofessional collaborative practice.

AIM
The present study explores current understanding about interprofessional collaborative client-centred practice and nursing's role in this form of care delivery.


BACKGROUND
A profession-only focus on nursing practice has been challenged at professional, national governmental and World Health Organization levels stressing for more interprofessional patient-centred collaborative teamwork.


EVALUATION
Moving to patient-centred collaborative practice is fraught with barriers. Enablers can result in building trust, power sharing and shared decision-making. Changing current workplace environments requires institutional commitments to support collaborative team development.


KEY ISSUE(S)
Nurses can become collaborative members of teams through: (1) re-socialize; (2) understanding and articulating nurses roles, knowledge and skills to others; (3) other health providers sharing the same to nurses; (4) identifying where shared roles, knowledge and skills exist; and (5) learning to work in collaborative teams. Nurses must address some fundamental issues about practice that negate collaboration and patient-centred care.


CONCLUSIONS
All professionals, including nurses, must move away from a service-oriented delivery to a patient-centred collaborative approach to care.


IMPLICATIONS FOR NURSING MANAGEMENT
The values within health organizations need to be underpinned by collaborative interprofessional patient-centred practice. To accomplish this goal, administrators and managers must support assessment of employees and visiting physicians as to their conformance with agency established expectations for such practice.
Symptom Trajectories After an Emergency Department Visit for Potential Acute Coronary Syndrome.

BACKGROUND
Many patients evaluated for acute coronary syndrome (ACS) in emergency departments (EDs) continue to experience troubling symptoms after discharge-regardless of their ultimate medical diagnosis. However, comprehensive understanding of common post-ED symptom trajectories is lacking.


OBJECTIVES
The aim of this study was to identify common trajectories of symptom severity in the 6 months after an ED visit for potential ACS.


METHODS
This was a secondary analysis of data from a larger observational, prospective study conducted in five U.S. EDs. Patients (N = 1005) who had electrocardiogram and biomarker testing ordered, and were identified by the triage nurse as potentially having ACS, were enrolled. Symptom severity was assessed in the hospital after initial stabilization and by telephone at 30 days and 6 months using the validated 13-item ACS Symptom Checklist. Growth mixture modeling was used for the secondary analysis. The eight most commonly reported symptoms (chest discomfort, chest pain, chest pressure, light-headedness, shortness of breath, shoulder pain, unusual fatigue, and upper back pain) were modeled across the three study time points. Models with increasing numbers of classes were compared, and final model selection was based on a combination of interpretability, theoretical justification, and statistical fit indices.


RESULTS
The sample was 62.6% male with a mean age of 60.2 years (SD = 14.17 years), and 57.1% ruled out for ACS. Between two and four distinct trajectory classes were identified for each symptom. The seven different types of trajectories identified across the eight symptoms were labeled "tapering off," "mild/persistent," "moderate/persistent," "moderate/worsening," "moderate/improving," "late onset, "and "severe/improving." Trajectories differed on age, gender, and diagnosis.


DISCUSSION
Research on the individual nature of symptom trajectories can contribute to patient-centered, rather than disease-centered, care. Further research is needed to verify the existence of multiple symptoms trajectories in diverse populations and to assess the antecedents and consequences of individual symptom trajectories.
Neuropsychiatric symptoms in patients with dementia in primary care: a study protocol

BACKGROUND
Neuropsychiatric symptoms (NPS) frequently occur in patients with dementia. To date, prospective studies on the course of NPS have been conducted in patients with dementia in clinical centers or psychiatric services. The primary goal of this study is to investigate the course of NPS in patients with dementia and caregiver distress in primary care. We also aim to detect determinants of both the course of NPS in patients with dementia and informal caregiver distress in primary care.


METHODS/DESIGN
This is a prospective observational study on the course of NPS in patients with dementia in primary care. Thirty-seven general practitioners (GPs) in 18 general practices were selected based on their interest in participating in this study. We will retrieve electronic medical files of patients with dementia from these general practices. Patients and caregivers will be followed for 18 months during the period January 2012 to December 2013. Patient characteristics will be collected at baseline. Time to death or institutionalization will be measured. Co-morbidity will be assessed using the Charlson index. Psychotropic drug use and primary and secondary outcome measures will be measured at 3 assessments, baseline, 9 and 18 months. The primary outcome measures are the Neuropsychiatric Inventory score for patients with dementia and the Sense of Competence score for informal caregivers. In addition to descriptive analyses frequency parameters will be computed. Univariate analysis will be performed to identify determinants of the course of NPS and informal caregiver distress. All determinants will then be tested in a multivariate regression analysis to determine their unique contribution to the course of NPS and caregiver distress.


DISCUSSION
The results of this study will provide data on the course of NPS, which is clinically important for prognosis. The data will help GPs and other professionals in planning follow-up visits and in the timing for offering psycho-education, psychosocial interventions and the provision of care. In addition, these data will enlarge health professionals' awareness of NPS in their patients with dementia.
Steganography and Its Applications in Security

Steganography is the dark cousin of cryptography, the use of codes. While cryptography provides privacy, steganography is intended to provide secrecy. Steganography is a method of covertly communicating. Steganography is a process that involves hiding a message in an appropriate carrier for example an image or an audio file. The carrier can then be sent to a receiver without anyone else knowing that it contains a hidden message. This is a process, which can be used for example by civil rights organizations in repressive states to communicate their message to the outside world without their own government being aware of it. In this article we have tried to elucidate the different approaches towards implementation of Steganography using ‘multimedia’ file (text, static image, audio and video). Steganalysis is a newly emerging branch of data processing that seeks the identification of steganographic covers, and if possible message extraction. It is similar to cryptanalysis in cryptography. The technique is ancient emerging monster that have gained immutable notice as it have newly penetrated the world of digital communication security. Objective is not only to prevent the message being read but also to hide its existence.
Recent advances in differential evolution - An updated survey

Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed since the first comprehensive survey article was published on DE by Das and Suganthan in 2011. Several developments have been reported on various aspects of the algorithm in these 5 years and the research on and with DE have now reached an impressive state. Considering the huge progress of research with DE and its applications in diverse domains of science and technology, we find that it is a high time to provide a critical review of the latest literatures published and also to point out some important future avenues of research. The purpose of this paper is to summarize and organize the information on these current developments on DE. Beginning with a comprehensive foundation of the basic DE family of algorithms, we proceed through the recent proposals on parameter adaptation of DE, DE-based single-objective global optimizers, DE adopted for various optimization scenarios including constrained, large-scale, multi-objective, multi-modal and dynamic optimization, hybridization of DE with other optimizers, and also the multifaceted literature on applications of DE. The paper also presents a dozen of interesting open problems and future research issues on DE. & 2016 Published by Elsevier B.V.
A replicated molecular genetic basis for subtyping antisocial behavior in children with attention-deficit/hyperactivity disorder.

CONTEXT
Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder that in some cases is accompanied by antisocial behavior.


OBJECTIVE
To test if variations in the catechol O-methyltransferase gene (COMT) would prove useful in identifying the subset of children with ADHD who exhibit antisocial behavior.


DESIGN
Three independent samples composed of 1 clinical sample of ADHD cases and 2 birth cohort studies.


PARTICIPANTS
Participants in the clinical sample were drawn from child psychiatry and child health clinics in England and Wales. The 2 birth cohort studies included 1 sample of 2232 British children born in 1994-1995 and a second sample of 1037 New Zealander children born in 1972-1973.


MAIN OUTCOME MEASURES
Diagnosis of ADHD and measures of antisocial behavior.


RESULTS
We present replicated evidence that the COMT valine/methionine polymorphism at codon 158 (COMT Val158Met) was associated with phenotypic variation among children with ADHD. Across the 3 samples, valine/valine homozygotes had more symptoms of conduct disorder, were more aggressive, and were more likely to be convicted of criminal offenses compared with methionine carriers.


CONCLUSIONS
The findings confirm the presence of genetic heterogeneity in ADHD and illustrate how genetic information may provide biological evidence pointing to clinical subtypes.
It ROCS!: The RASH Online Conversion Service

In this poster paper we introduce the RASH Online Conversion Service, i.e., a Web application that allows the conversion of ODT documents into RASH, a HTML-based markup language for writing scholarly articles, and from RASH into LaTeX according to Springer LNCS and ACM ICPS.
Influence of lateral and top boundary conditions on regional air quality prediction: A multiscale study coupling regional and global chemical transport models: INFLUENCE OF BOUNDARY CONDITIONS

[1] The sensitivity of regional air quality model to various lateral and top boundary conditions is studied at 2 scales: a 60 km domain covering the whole USA and a 12 km domain over northeastern USA. Three global models (MOZART-NCAR, MOZART-GFDL and RAQMS) are used to drive the STEM-2K3 regional model with time-varied lateral and top boundary conditions (BCs). The regional simulations with different global BCs are examined using ICARTT aircraft measurements performed in the summer of 2004, and the simulations are shown to be sensitive to the boundary conditions from the global models, especially for relatively long-lived species, like CO and O3. Differences in the mean CO concentrations from three different global-model boundary conditions are as large as 40 ppbv, and the effects of the BCs on CO are shown to be important throughout the troposphere, even near surface. Top boundary conditions show strong effect on O3 predictions above 4 km. Over certain model grids, the model’s sensitivity to BCs is found to depend not only on the distance from the domain’s top and lateral boundaries, downwind/upwind situation, but also on regional emissions and species properties. The near-surface prediction over polluted area is usually not as sensitive to the variation of BCs, but to the magnitude of their background concentrations. We also test the sensitivity of model to temporal and spatial variations of the BCs by comparing the simulations with time-varied BCs to the corresponding simulations with time-mean and profile BCs. Removing the time variation of BCs leads to a significant bias on the variation prediction and sometime causes the bias in predicted mean values. The effect of model resolution on the BC sensitivity is also studied.
Detection and Tracking of Facial Features in Video Sequences

This work presents a real time system for detection and tracking of facial features in video sequences. Such system may be used in visual communication applications, such as teleconferencing, virtual reality, intelli gent interfaces, humanmachine interaction, surveill ance, etc. We have used a statistical skin-color model to segment face-candidate regions in the image. The presence or absence of a face in each region is verified by means of an eye detector, based on an eff icient template matching scheme . Once a face is detected, the pupils, nostril s and lip corners are located and these facial features are tracked in the image sequence, performing real time processing.
Light and scanning electron microscopical study on Antarctophthirus ogmorhini lice from the Antarctic seal Leptonychotes weddellii

Adult lice (Antarctophthirus ogmorhini) from the Weddell seal Leptonychotes weddellii were investigated by means of light and scanning electron microscopy. We established that this species is characterized by several morphological peculiarities which enable it to survive the low temperatures of the Antarctic sea and the body depression which occurs during the deep (450 m) and long diving periods of the seals. The main peculiarities are: (1) the cuticle of the ventral and lateral surfaces is much thinner than that of the dorsal surface, (2) the body has numerous stiff spines which are covered by a thick layer of the seal's sebum that closely surrounds the body of the louse, (3) the whole body is covered by a close layer of leaf-like scales which are apparently able to trap air bubbles and thus to provide a small zone of air close to the surface of the cuticle.
Self-Organizing Maps In Natural Language Processing

Kohonen's Self-Organizing Map (SOM) is one of the most popular arti cial neural network algorithms. Word category maps are SOMs that have been organized according to word similarities, measured by the similarity of the short contexts of the words. Conceptually interrelated words tend to fall into the same or neighboring map nodes. Nodes may thus be viewed as word categories. Although no a priori information about classes is given, during the self-organizing process a model of the word classes emerges. The central topic of the thesis is the use of the SOM in natural language processing. The approach based on the word category maps is compared with the methods that are widely used in arti cial intelligence research. Modeling gradience, conceptual change, and subjectivity of natural language interpretation are considered. The main application area is information retrieval and textual data mining for which a speci c SOM-based method called the WEBSOM has been developed. The WEBSOM method organizes a document collection on a map display that provides an overview of the collection and facilitates interactive browsing. 1
Dynamic capital structure and political patronage: The case of Malaysia

This paper investigates the effect of political patronage on firms’ capital structure. The evidence is from Malaysia a country characterised by relationship-capitalism and covers 1988 to 2009. Using a system GMM estimator we find firms set leverage targets and adjust towards them following deviations at the rate of 28 per cent per annum. Next, we construct a natural experiment and use a difference-in-differences model to investigate if the strategic financing decisions of politically patronised firms differs from non-connected firms after an exogenous shock caused by the 1997 Asian crisis. Our results unambiguously demonstrate a significant difference in the capital structure of patronised firms relative to non-connected firms following the exogenous shock but only for the crisis period 1998-2001. After 2002 the capital structures of patronised and non-connected firms are statistically equivalent. JEL Classification: G01 (Financial Crises), G32 (Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure).