LLukas22/scidocs huggingface dataset:
Life cycle approach to sustainability assessment: a case study of remanufactured alternators

Sustainability is an international issue with increasing concern and becomes a crucial driver for the industry in international competition. Sustainability encompasses the three dimensions: environment, society and economy. This paper presents the results from a sustainability assessment of a product. To prevent burden shifting, the whole life cycle of the products is necessary to be taken into account. For the environmental dimension, life cycle assessment (LCA) has been practiced for nearly 40 years and is the only one standardised by the International Organization for Standardization (ISO) (14040 and 14044). Life cycle approaches for the social and economic dimensions are currently under development. Life cycle sustainability assessment (LCSA) is a complementary implementation of the three techniques: LCA (environmental), life cycle costing (LCC economic) and social LCA (SLCA social). This contribution applies the state-of-the-art LCSA on remanufacturing of alternators aiming at supporting managers and product developers in their decision-making to design product and plant. The alternator is the electricity generator in the automobile vehicle which produces the needed electricity. LCA and LCC are used to assess three different alternator design scenarios (namely conventional, lightweight and ultra-lightweight). The LCA and LCC results show that the conventional alternator is the most promising one. LCSA of three different locations (Germany, India and Sierra Leone) for setting the remanufacturing mini-factory, a worldwide applicable container, are investigated on all three different sustainability dimensions: LCA, LCC and SLCA. The location choice is determined by the SLCA and the design alternatives by the LCA and LCC. The case study results show that remanufacturing potentially causes about 12% of the emissions and costs compared to producing new parts. The conventional alternator with housing of iron cast performs better in LCA and LCC than the lightweight alternatives with aluminium housing. The optimal location of remanufacturing is dependent on where the used alternators are sourced and where the remanufactured alternators are going to be used. Important measures to improve the sustainability of the remanufacturing process in life cycle perspective are to confirm if the energy efficiency of the remanufactured part is better than the new part, as the use phase dominates from an environmental and economical point of view. The SLCA should be developed further, focusing on the suitable indicators and conducting further case studies including the whole life cycle.
Reducing the progression of myopia with atropine: a long term cohort study of Olmsted County students.

BACKGROUND
Myopia is an important public health problem because it is common and is associated with increased risk for chorioretinal degeneration, retinal detachment, and other vision- threatening abnormalities. In animals, ocular elongation and myopia progression can be lessened with atropine treatment. This study provides information about progression of myopia and atropine therapy for myopia in humans.


METHODS
A total of 214 residents of Olmsted County, Minnesota (118 girls and 96 boys, median age, 11 years; range 6 to 15 years) received atropine for myopia from 1967 through 1974. Control subjects were matched by age, sex, refractive error, and date of baseline examination to 194 of those receiving atropine. Duration of treatment with atropine ranged from 18 weeks to 11.5 years (median 3.5 years).


RESULTS
Median followup from initial to last refraction in the atropine group (11.7 years) was similar to that in the control group (12.4 years). Photophobia and blurred vision were frequently reported, but no serious adverse effects were associated with atropine therapy. Mean myopia progression during atropine treatment adjusted for age and refractive error (0.05 diopters per year) was significantly less than that among control subjects (0.36 diopters per year)(P<.001). Final refractions standardized to the age of 20 years showed a greater mean level of myopia in the control group (3.78 diopters) than in the atropine group (2.79 diopters) (P<.001).


CONCLUSIONS
The data support the view that atropine therapy is associated with decreased progression of myopia and that beneficial effects remain after treatment has been discontinued.
Impact of point-of-care testing for CYP2C19 on platelet inhibition in patients with acute coronary syndrome and early dual antiplatelet therapy in the emergency setting.

AIMS
Only limited data exist about the role of point of care CYP2C19 testing in the acute setting in the early phase of acute coronary syndromes (ACS). Therefore, the present study was designed to investigate the impact of CYP2C19 loss-of-function point-of-care (POC) genotyping in patients presenting with acute coronary syndromes (ACS) and treated with dual antiplatelet therapy in the emergency setting.


METHODS AND RESULTS
137 subjects with ACS scheduled for percutaneous coronary intervention were consecutively enrolled. Pre- and on-treatment platelet aggregation was assessed by multiple electrode aggregometry (MEA) after stimulation with adenosine diphosphate (ADP). Patients were loaded according to current guideline adherent indications and contraindications for use of P2Y12 inhibitors in ACS. POC genotyping for CYP2C19*2 was performed in the emergency room after obtaining a buccal swab using the Spartan RX CYP2C19 system and obtaining patient's informed consent. Prasugrel and ticagrelor treated patients had significantly lower PR compared to clopidogrel-treated patients. The benefits of prasugrel and ticagrelor compared to clopidogrel treated patients in terms of platelet inhibition were more pronounced in CYP2C19*2 carriers. Non-carriers showed similar inhibition regardless of particular P2Y12 inhibitor treatment. Statistical analyses adjusting for factors associated with response (e.g. smoking) revealed that CYP2C19*2 allele carrier status and loading with different type of P2Y12 receptor blockers were significant predictors of on-treatment platelet reactivity in the early phase of ACS.


CONCLUSION
The results of this pilot study of treatment of patients in the early phase of ACS indicate that CYP2C19*2 POC genotyping might help to identify patients at risk with poor response to clopidogrel treatment, thereby benefiting from reloading and switching to alternative P2Y12 receptor inhibition.
Female Victims of Violence

This report provides the current findings on nonfatal and fatal violent crimes committed against females. Data are from the Bureau of Justice Statistics’ National Crime Victimization Survey (NCVS), 1993 to 2008, and the Federal Bureau of Investigation’s (FBI) Uniform Crime Reporting Program's (UCR) Supplementary Homicide Reports (SHR), 1993 to 2007 (the most recent data available). The report focuses on nonfatal intimate partner violence (IPV), fatal IPV, rape and sexual assault, and stalking. It includes estimates of the extent of crimes against females and the characteristics of crimes and victims. Crime trends are also presented, along with comparative estimates of crimes against males.
The impact of document structure on keyphrase extraction

Keyphrases are short phrases that reflect the main topic of a document. Because manually annotating documents with keyphrases is a time-consuming process, several automatic approaches have been developed. Typically, candidate phrases are extracted using features such as position or frequency in the document text. Document structure may contain useful information about which parts or phrases of a document are important, but has rarely been considered as a source of information for keyphrase extraction.
 We address this issue in the context of keyphrase extraction from scientific literature. We introduce a new, large corpus that consists of full-text journal articles, where the rich collection and document structure available at the publishing stage is explicitly annotated.
 We explore features based on the XML tags contained in the documents, and based on generic section types derived using position and cue words in section titles. For XML tags we find sections, abstract, and title to perform best, but many smaller elements may be beneficial in combination with other features. Of the generic section types, the discussion section is found to be most useful for keyphrase extraction.
Familial clustering of obesity and the role of nutrition: Tehran Lipid and Glucose Study

OBJECTIVE: To clarify the hypothesis that parent's dietary intakes are associated with their offspring's body mass index.DESIGN: Observational analytical cross-sectional survey among inhabitants of district 13 in the east of Tehran.SUBJECTS: A total of 117 healthy families comprising 474 subjects including 240 offspring (3–25 y old).MEASUREMENTS: Weight and height were measured by a standard protocol and body mass index (kg/m2) was calculated. Dietary intakes were assessed by means of a 2 day dietary recall questionnaire.RESULTS: The prevalence of overweight was 11.8% in offspring of normal-weight parents, 19.0% in offspring of overweight fathers and normal-weight mothers, 25.4% in offspring of overweight mothers and normal-weight fathers and 40.8% in offspring with both parents overweight. The Offspring's overweight was significantly and independently associated with high-energy intake of both parents (odds ratio; 95% CI 2.7; 1.6–4.5). Adjusted for the sex of parents, the chances of offspring being overweight were higher in overweight (3.8; 1.5–9.2) and high-energy-intake mothers (2.6; 1.2–5.6) and high-energy-intake fathers (2.0; 1.1–3.9) as compared with children of normal-weight parents. High fat intake of husbands was an independent risk factor increasing the chances of their wives being overweight (2.1; 1.5–3.6) and vice versa (1.8; 1.2–2.8).CONCLUSION: The observed familial obesity pattern was shown to be associated with the familial dietary intakes. Hence, familial intervention seems essential to stop the accelerated rise in the prevalence of overweight and obesity in our community.
Patterns and predictors of inpatient falls and fall-related injuries in a large academic hospital.

OBJECTIVES
Most research on hospital falls has focused on predictors of falling, whereas less is known about predictors of serious fall-related injury. Our objectives were to characterize inpatients who fall and to determine predictors of serious fall-related injury.


METHODS
We performed a retrospective observational study of 1,082 patients who fell (1,235 falls) during January 2001 to June 2002 at an urban academic hospital. Multivariate analysis of potential risk factors for serious fall-related injury (vs no or minor injury) included in the hospital's adverse event reporting database was conducted with logistic regression to calculate adjusted odds ratios (aORs) with 95% confidence intervals (CI95)


RESULTS
The median age of patients who fell was 62 years (interquartile range, 49-77 years), 50% were women, and 20% were confused. The hospital fall rate was 3.1 falls per 1,000 patient-days, which varied by service from 0.86 (women and infants) to 6.36 (oncology). Some (6.1%) of the falls resulted in serious injury, ranging by service from 3.1% (women and infants) to 10.9% (psychiatry). The most common serious fall-related injuries were bleeding or laceration (53.6%), fracture or dislocation (15.9%), and hematoma or contusion (13%). Patients 75 years or older (aOR, 3.2; CI95, 1.3-8.1) and those on the geriatric psychiatry floor (aOR, 2.8; CI95, 1.3-6.0) were more likely to sustain serious fall-related injuries.


CONCLUSIONS
There is considerable variation in fall rates and fall-related injury percentages by service. More detailed studies should be conducted by floor or service to identify predictors of serious fall-related injury so that targeted interventions can be developed to reduce them.
Reviews , Reputation , and Revenue : The Case of Yelp . com

Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp’s rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5-9 percent increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant’s average rating is affected by the number of reviews and whether the reviewers are certified as “elite” by Yelp, but is unaffected by the size of the reviewers’ Yelp friends network. † Harvard Business School, mluca@hbs.edu
Solution properties and micellization behavior of binary mixtures of sodium salts of N-tetradeconyl alanine and N-tetradeconyl phenylalanine surfactants

Abstract Two amino acid based surfactants, N -tetradecanoyl alanine and N -tetradecanoyl phenylalanine, are studied vis-a-vis their solution behavior and micellar selfassembly. The observations are correlated to their structural features and the pH of the system. Pseudobinary mixed surfactant system model is used to understand the complex surface tension profile of the surfactants. In mixed systems, surface properties and the micellization parameters and the micellar growth has been found to depend upon the composition of the surfactant mixture which has been explained on the basis of the occurrence of non-covalent π-π and NH-π interactions between the component surfactant molecules.
Real-time forest fire detection with wireless sensor networks

In this paper, we propose a wireless sensor network paradigm for real-time forest fire detection. The wireless sensor network can detect and forecast forest fire more promptly than the traditional satellite-based detection approach. This paper mainly describes the data collecting and processing in wireless sensor networks for real-time forest fire detection. A neural network method is applied to in-network data processing. We evaluate the performance of our approach by simulations.
Evolving large scale UAV communication system

Unmanned Aerial Vehicles (UAVs) have traditionally been used for short duration missions involving surveillance or military operations. Advances in batteries, photovoltaics and electric motors though, will soon allow large numbers of small, cheap, solar powered unmanned aerial vehicles (UAVs) to fly long term missions at high altitudes. This will revolutionize the way UAVs are used, allowing them to form vast communication networks. However, to make effective use of thousands (and perhaps millions) of UAVs owned by numerous disparate institutions, intelligent and robust coordination algorithms are needed, as this domain introduces unique congestion and signal-to-noise issues. In this paper, we present a solution based on evolutionary algorithms to a specific ad-hoc communication problem, where UAVs communicate to ground-based customers over a single wide-spectrum communication channel. To maximize their bandwidth, UAVs need to optimally control their output power levels and orientation. Experimental results show that UAVs using evolutionary algorithms in combination with appropriately shaped evaluation functions can form a robust communication network and perform 180% better than a fixed baseline algorithm as well as 90% better than a basic evolutionary algorithm.
Variable selection by association rules for customer churn prediction of multimedia on demand

Multimedia on demand (MOD) is an interactive system that provides a number of value-added services in addition to traditional TV services, such as video on demand and interactive online learning. This opens a new marketing and managerial problem for the telecommunication industry to retain valuable MOD customers. Data mining techniques have been widely applied to develop customer churn prediction models, such as neural networks and decision trees in the domain of mobile telecommunication. However, much related work focuses on developing the prediction models per se. Few studies consider the pre-processing step during data mining whose aim is to filter out unrepresentative data or information. This paper presents the important processes of developing MOD customer churn prediction models by data mining techniques. They contain the pre-processing stage for selecting important variables by association rules, which have not been applied before, the model construction stage by neural networks (NN) and decision trees (DT), which are widely adapted in the literature, and four evaluation measures including prediction accuracy, precision, recall, and F-measure, all of which have not been considered to examine the model performance. The source data are based on one telecommunication company providing the MOD services in Taiwan, and the experimental results show that using association rules allows the DT and NN models to provide better prediction performances over a chosen validation dataset. In particular, the DT model performs better than the NN model. Moreover, some useful and important rules in the DT model, which show the factors affecting a high proportion of customer churn, are also discussed for the marketing and managerial purpose. 2009 Elsevier Ltd. All rights reserved.
Prevalence and factors associated with left ventricular dysfunction in the EULAR Scleroderma Trial and Research group (EUSTAR) database of patients with systemic sclerosis.

OBJECTIVES
To measure the prevalence of, and factors associated with, left ventricular (LV) dysfunction in systemic sclerosis (SSc).


METHODS
The EUSTAR database was first searched. A case-control study of a patient subset was then performed to further identify independent factors associated with LV dysfunction by simple and multiple regression.


RESULTS
Of 7073 patients, 383 (5.4%) had an LV ejection fraction (EF) of <55%. By multiple regression analysis, age, sex, diffuse cutaneous disease, disease duration, digital ulcerations, renal and muscle involvement, disease activity score, pulmonary fibrosis and pulmonary arterial hypertension were associated with LV dysfunction. In the second phase, 129 patients with SSc with LVEF <55% were compared with 256 patients with SSc with normal LVEF. Male sex (OR 3.48; 95% CI 1.74 to 6.98), age (OR 1.03; 95% CI 1.01 to 1.06), digital ulcerations (OR 1.91; 95% CI 1.05 to 3.50), myositis (OR 2.88; 95% CI 1.15 to 7.19) and use of calcium channel blockers (OR 0.41; 95% CI 0.22 to 0.74) were independent factors associated with LV dysfunction.


CONCLUSION
The prevalence of LV dysfunction in SSc is 5.4%. Age, male gender, digital ulcerations, myositis and lung involvement are independently associated with an increased prevalence of LV dysfunction. Conversely, the use of calcium channel blockers may be protective.
From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms

Nature has provided rich models for computational problem solving, including optimizations based on the swarm intelligence exhibited by fireflies, bats, and ants. These models can stimulate computer scientists to think nontraditionally in creating tools to address application design challenges.
Image stitch algorithm based on SIFT and MVSC

Based on scale-invariant feature transform (SIFT) and mean seamless cloning (MVSC), an image stitching algorithm is presented, to improve the quality of the panoramic stiching image. Using SIFT algorithm to extract between benchmark images (await matched image) and follow-up images(with the baseline image match the image) of the feature points, identifying locations and directions, using 128 dimensional vector to describe features point. Using the nearest neighbor method to achieve two images feature point matching, identify overlap regions. Using SIFT algorithm to provide benchmark images and follow-up images to determine the source cloning domain and target cloning domain of the MVSC. Using the mean value coordinates to achieve the pixel to interpolat from the source cloning domain to target cloning domain. Finally, using MVSC algorithm to achieve the two images stitching. Experiment results shows that this method with regard to image rotation, perspective changes and image scaling to have a very good stitching results, stitching image is complete information, the quality of the image is high.
Trade unions in Uruguay: some historical features explaining their economic role

The knowledge of the nature and structure of trade unions is a basic requisite to correctly model bargaining between firms and unions. Thus, in this paper the historical background and the current characteristics of the Uruguayan trade unions are summarised.
Animal model integration to AutDB, a genetic database for autism

In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models. As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future. Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.
Hybrid simulation of an aircraft adaptive control system

The general concept of adaptive control has become well known, and the objectives and various types of adaptive systems have been classified. In particular, for adaptive control of a high performance aircraft, it is desired to alter the feedback control parameters in the basic linear control system to correct for unknown, unanticipated, or unaccounted-for changes in the aircraft's operating characteristics, inputs, or criterion of performance.