LLukas22/scidocs huggingface dataset:
The dynamics of absorption coefficients of CDOM and particles in the St. Lawrence estuarine system: Biogeochemical and physical implications

a r t i c l e i n f o Keywords: CDOM Particles Optical properties Absorption Molecular weight Water mass tracer Estuarine mixing Estuary Fjord Absorption spectra of chromophoric dissolved organic matter (CDOM) and particles were obtained in May 2007 in the St. Lawrence estuary (SLE, Canada), the northwestern Gulf of St. Lawrence (NWG), and the Saguenay Fjord (CDOM only), the main tributary of the SLE. CDOM absorption generally decreased downstream and with depth and showed an inverse relationship to tidal cycles. Phytoplankton absorption in surface water of the SLE increased seaward while non-algal particle absorption trended oppositely; both variables declined with depth. Surface water CDOM absorption surpassed particle absorption in the SLE while phytoplankton absorption dominated in the NWG. Elevated non-algal and CDOM absorption were found in the turbidity maximum zone near the head of the SLE. Enriched CDOM absorption also occurred in the bottom water of the lower SLE and NWG. The spectral slope ratio of CDOM absorption, defined as the ratio of the spectral slope between 275 and 295 nm to that between 350 and 400 nm, was confirmed to be an indicator of the source and molecular weight of CDOM. This surrogate functionality, however, failed for absorption spectra exhibiting shoulders in short ultraviolet wavelengths observed in deep waters of the SLE and NWG. CDOM absorption mainly displayed conservative mixing behavior in both the SLE and the Sag-uenay Fjord. CDOM was employed to trace the source identity of the Fjord's deepwater. It was found that the marine end member of the Fjord's deepwater possessed a salinity of 32.92 and a temperature of ca. 1 °C and originated from the intermediate cold layer of the lower SLE. The marine end member contributed 94% of the deepwater by volume while freshwater mainly flown from the Saguenay River supplied the remaining 6%. Implications of our results for remote sensing-based assessments of primary productivity, surface water circulation , and water column photochemistry in the SLE are also discussed. 1.1. Overview of absorption properties in marine waters Chromophoric dissolved organic matter (CDOM), phytoplankton, and non-algal particles (NAP) are major ultraviolet (UV) and visible light absorbing constituents in the ocean. Independent variability of these optically active constituents complicates remote sensing of chlorophyll a concentration (chl a) and hence the estimation of primary productivity from ocean color imagery (e.g. Antoine et al., 1996; Behrenfeld and Falkowski, 1997). Using standard empirical algorithms to retrieve …
Marketing Science , Models , Monopoly Models , and Why We Need Them

Despite popular belief, the marketing discipline was an offshoot of economics (Bartels 1951, Sheth et al. 1988). Early researchers, often educated in economics, felt economics was preoccupied with variables such as prices and costs. They focused on other variables. They also investigated marketing as a productive activity (i.e., adding value) by adopting different sets of assumptions other than economics (Bartels 1976). Were profit variations across firms caused entirely by random exogenous factors beyond managerial control, marketing would have no ‘‘valueadded,’’ and the discipline of marketing would have diminished purpose. Mathematical marketing models appeared much later as a precise, logical and scientific way to ‘‘add value.’’ By 1970, researchers developed mathematical models for many purposes, including better forecasting, integration of data, and understanding of markets. Just a few of the many high-impact pre-1970 marketing models include those of Bass (1969a, 1969b), Bass and Parsons (1969), Cox (1967), Frank et al. (1965), Friedman (1958), Green and Rao (1970), Kuehn (1962), Little and Lodish (1969), Little et al. (1963), Morrison (1969), Telser (1960, 1962), Urban (1969), Vidale and Wolfe (1957), and Winters (1960). Today, mathematical models in Marketing Science cover many topics. Just a few examples (presented alphabetically) include: advance selling (Xie and Shugan 2001); creating customer satisfaction (Anderson and Sullivan 1993); direct marketing (e.g., Rossi et al. 1996); forming empirical generalizations (e.g., Mahajan et al. 1995); identifying first-mover advantages (e.g., Kalyanaram et al. 1995); implementing a wide range of marketing instruments (e.g., Padmanabhan and Rao 1993, Shaffer and Zhang 1995); modeling customer heterogeneity (Gonul and Srinivasan 1993); implementing the new empirical IO (Kadiyali et al. 2000); creating new product development (e.g., Griffin and Hauser 1993); understanding channels (e.g., Messinger and Narasimhan 1995); understanding dynamic brand choice (e.g., Erdem and Keane 1996); and understanding market evolution (e.g., Dekimpe and Hanssens 1995). Mathematics, as the language of science, allows interplay between empirical and theoretical research (Hauser 1985). Marketing Science publishes both empirical and theoretical mathematical models. Precise definitions of mathematical marketing models are controversial (Leeflang et al. 2000). We could narrowly define models as mathematical optimizations of marketing variables. However, Marketing Science adopts a more generic definition, which includes mathematical representations that answer important research questions in marketing. That definition allows publication of mathematical models from a multitude of disciplines, including Management Science, Statistics, Econometrics, Economics, Psychometrics, and Psychology. Note that the following discussion only considers models used by researchers. Models for use by * Steven M. Shugan is the Russell Berrie Foundation Eminent Scholar of Marketing.
Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model

BACKGROUND
In temperate zones, all-cause mortality exhibits a marked seasonality, and influenza represents a major cause of winter excess mortality. We present a statistical model, FluMOMO, which estimate influenza-associated mortality from all-cause mortality data and apply it to Danish data from 2010/11 to 2016/17.


METHODS
We applied a multivariable time series model with all-cause mortality as outcome, influenza activity and extreme temperatures as explanatory variables while adjusting for time trend and seasonality. Three indicators of weekly influenza activity (IA) were explored: percentage of consultations for influenza-like illness (ILI) at primary health care, national percentage of influenza-positive samples, and the product of ILI percentage and percentage of influenza-positive specimens in a given week, that is, the Goldstein index.


RESULTS
Independent of the choice of parameter to represent influenza activity, the estimated influenza-associated mortality showed similar patterns with the Goldstein index being the most conservative. Over the 7 winter seasons, the median influenza-associated mortality per 100 000 population was 17.6 (range: 0.0-36.8), 14.1 (0.3-31.6) and 8.3 (0.0-25.0) for the 3 indicators, respectively, for all ages.


CONCLUSION
The FluMOMO model fitted the Danish data well and has the potential to estimate all-cause influenza-associated mortality in near real time and could be used as a standardised method in other countries. We recommend using the Goldstein index as the influenza activity indicator in the FluMOMO model. Further work is needed to improve the interpretation of the estimated effects.
Pruning and Dynamic Scheduling of Cost-Sensitive Ensembles

Previous research has shown that averaging ensemble can scale up learning over very large cost-sensitive datasets with linear speedup independent of the learning algorithms. At the same time, it achieves the same or even better accuracy than a single model computed from the entire dataset. However, one major drawback is its inefficiency in prediction since every base model in the ensemble has to be consulted in order to produce a final prediction. In this paper, we propose several approaches to reduce the number of base classifiers. Among various methods explored, our empirical studies have shown that the benefit-based greedy approach can safely remove more than 90% of the base models while maintaining or even exceeding the prediction accuracy of the original ensemble. Assuming that each base classifier consumes one unit of prediction time, the removal of 90% of base classifiers translates to a prediction speedup of 10 times. On top of pruning, we propose a novel dynamic scheduling approach to further reduce the "expected" number of classifiers employed in prediction. It measures the confidence of a prediction by a subset of classifiers in the pruned ensemble. This confidence is used to decide if more classifiers are needed in order to produce a prediction that is the same as the original unpruned ensemble. This approach reduces the "expected" number of classifiers by another 25% to 75% without loss of accuracy.
High-resolution mapping of large gas emitting mud volcanoes on the Egyptian continental margin (Nile Deep Sea Fan) by AUV surveys.

Two highly active mud volcanoes located in 990–1,265 m water depths were mapped on the northern Egyptian continental slope during the BIONIL expedition of R/V Meteor in October 2006. Highresolution swath bathymetry and backscatter imagery were acquired with an autonomous underwater vehicle (AUV)-mounted multibeam echosounder, operating at a frequency of 200 kHz. Data allowed for the construction of ~1 m pixel bathymetry and backscatter maps. The newly produced maps provide details of the seabed morphology and texture, and insights into the formation of the two mud volcanoes. They also contain key indicators on the distribution of seepage and its tectonic control. The acquisition of high-resolution seafloor bathymetry and acoustic imagery maps with an AUV-mounted multibeam echosounder fills the gap in spatial scale between conventional multibeam data collected from a surface vessel and in situ video observations made from a manned submersible or a remotely operating vehicle.
Analyzing the Relationship between Regulation and Investment in the Telecom Sector

This study analyses the relationship between entry regulation and infrastructure investment in the telecommunication sector. The empirical analysis we conduct is based on a comprehensive data set covering 180 fixed-line and mobile operators in 25 European countries over 10 years and employs a newly created indicator measuring regulatory intensity in the European countries. We carefully treat the endogeneity problem of regulation by applying instrumental variables and find that tough entry regulation (e.g. unbundling) discourages infrastructure investment by entrants but has no effect on incumbents in fixed-line telecommunications. We do not find significant impact of entry regulation on investment in mobile telephony.
Tutorial on Variational Autoencoders

In just three years, Variational Autoencoders (VAEs) have emerged as one of the most popular approaches to unsupervised learning of complicated distributions. VAEs are appealing because they are built on top of standard function approximators (neural networks), and can be trained with stochastic gradient descent. VAEs have already shown promise in generating many kinds of complicated data, including handwritten digits [1, 2], faces [1, 3, 4], house numbers [5, 6], CIFAR images [6], physical models of scenes [4], segmentation [7], and predicting the future from static images [8]. This tutorial introduces the intuitions behind VAEs, explains the mathematics behind them, and describes some empirical behavior. No prior knowledge of variational Bayesian methods is assumed.
Is EQ-5D a valid quality of life instrument in patients with Parkinson's disease? A study in Singapore.

INTRODUCTION
The purpose of the present study was to evaluate the validity of the EQ-5D in patients with Parkinson's disease (PD) in Singapore.


MATERIALS AND METHODS
In a cross-sectional survey, patients with PD completed English or Chinese version of the EQ-5D, the 8-item Parkinson's disease questionnaire (PDQ-8), and questions assessing socio-demographic and health characteristics. Clinical data were retrieved from patients' medical records. The validity of the EQ-5D was assessed by testing a-priori hypotheses relating the EQ-5D to the PDQ-8 and clinical data.


RESULTS
Two hundred and eight PD patients (English speaking: 135) participated in the study. Spearman correlation coefficients between the EQ-5D and PDQ-8 ranged from 0.25 to 0.75 for English-speaking patients and from 0.16 to 0.67 for Chinese-speaking patients. By and large, the EQ-5D scores were weakly or moderately correlated with Hoehn and Yahr stage (correlation coefficients: 0.05 to 0.43), Schwab and England Activities of Daily Living score (correlation coefficients: 0.10 to 0.60), and duration of PD (correlation coefficients: 0.16 to 0.43). The EQ-5D index scores for patients with dyskinesia or "wearing off" periods were significantly lower than those without these problems. The EQ-5D Visual Analog Scale (EQ-VAS) scores also differed for English-speaking patients with deferring dyskinesia, "wearing off" periods, or health transition status; however, such differences were not observed in patients who completed the survey in Chinese.


CONCLUSIONS
The EQ-5D questionnaire appears valid for measuring quality of life in patients with PD in Singapore. However, the validity of EQ-VAS in Chinese-speaking patients with PD should be further assessed.
Inkjet printed System-in-Package design and manufacturing

Additive manufacturing technology using inkjet offers several improvements to electronics manufacturing compared to current nonadditive masking technologies. Manufacturing processes can be made more efficient, straightforward and flexible compared to subtractive masking processes, several time-consuming and expensive steps can be omitted. Due to the additive process, material loss is minimal, because material is never removed as with etching processes. The amounts of used material and waste are smaller, which is advantageous in both productivity and environmental means. Furthermore, the additive inkjet manufacturing process is flexible allowing fast prototyping, easy design changes and personalization of products. Additive inkjet processing offers new possibilities to electronics integration, by enabling direct writing on various surfaces, and component interconnection without a specific substrate. The design and manufacturing of inkjet printed modules differs notably from the traditional way to manufacture electronics. In this study a multilayer inkjet interconnection process to integrate functional systems was demonstrated, and the issues regarding the design and manufacturing were considered. r 2008 Elsevier Ltd. All rights reserved.
Solution of differential-difference equations by using differential transform method

In this work, we successfully extended differential transform method (DTM), by presenting and proving new theorems, to the solution of differential–difference equations (DDEs). Theorems are presented in the most general form to cover a wide range of DDEs, being linear or nonlinear and constant or variable coefficient. In order to show the power and the robustness of the method and to illustrate the pertinent features of related theorems, examples are presented. 2006 Elsevier Inc. All rights reserved.
Detecting Foggy Images and Estimating the Haze Degree Factor

At present, most outdoor video-surveillance, driver-assistance and optical remote sensing systems have been designed to work under good visibility and weather conditions. Poor visibility often occurs in foggy or hazy weather conditions and can strongly influence the accuracy or even the general functionality of such vision systems. Consequently, it is important to import actual weather-condition data to the appropriate processing mode. Recently, significant progress has been made in haze removal from a single image [1,2]. Based on the hazy weather classification, specialized approaches, such as a dehazing process, can be employed to improve recognition. Figure 1 shows a sample processing flow of our dehazing program.
Adaptive inventory control models for supply chain management

Uncertainties inherent in customer demands make it difficult for supply chains to achieve just-in-time inventory replenishment, resulting in loosing sales opportunities or keeping excessive chain-wide inventories. In this paper, we propose two adaptive inventory-control models for a supply chain consisting of one supplier and multiple retailers. The one is a centralized model and the other is a decentralized model. The objective of the two models is to satisfy a target service level predefined for each retailer. The inventory-control parameters of the supplier and retailers are safety lead time and safety stocks, respectively. Unlike most extant inventory-control approaches, modelling the uncertainty of customer demand as a statistical distribution is not a prerequisite in the two models. Instead, using a reinforcement learning technique called action-value method, the control parameters are designed to adaptively change as customerdemand patterns changes. A simulation-based experiment was C.O. Kim ( ) School of Computer and Industrial Engineering, Yonsei University, Seoul, 120-749, Republic of Korea E-mail: kimco@yonsei.ac.kr Tel: (+822) 2123-2711 Fax: (+822) 364-7807 J. Jun Research Institute for Information and Communication Technologies, Korea University, Seoul, 136-701, Republic of Korea J.K. Baek Department of Industrial System Management, Seoul College, Seoul, 131-702, Republic of Korea R.L. Smith Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109-2117, USA Y.D. Kim Department of Industrial Engineering, Korea Advanced Institute of Science and Technology, Daejon, 305-701, Republic of Korea performed to compare the performance of the two inventorycontrol models.
Endovascular treatment of ruptured thoracic aortic aneurysm in patients older than 75 years.

OBJECTIVES
To investigate the outcomes of thoracic endovascular aortic repair (TEVAR) for ruptured descending thoracic aortic aneurysm (rDTAA) in patients older than 75 years.


METHODS
We retrospectively identified all patients treated with TEVAR for rDTAA at seven referral centres between 2002 and 2009. The cohort was stratified according to age ≤75 and >75 years, and the outcomes after TEVAR were compared between both groups.


RESULTS
Ninety-two patients were identified of which 73% (n = 67) were ≤75 years, and 27% (n = 25) were older than 75 years. The 30-day mortality was 32.0% in patients older than 75 years, and 13.4% in the remaining patients (p = 0.041). Patients older than 75 years suffered more frequently from postoperative stroke (24.0% vs. 1.5%, p = 0.001) and pulmonary complications (40.0% vs. 9.0%, p = 0.001). The aneurysm-related survival after 2 years was 52.1% for patients >75 years, and 83.9% for patients ≤75 years (p = 0.006).


CONCLUSIONS
Endovascular treatment of rDTAA in patients older than 75 years is associated with an inferior outcome compared with patients younger than 75 years. However, the mortality and morbidity rates in patients above 75 years are still acceptable. These results may indicate that endovascular treatment for patients older than 75 years with rDTAA is worthwhile.
Eye development.

The vertebrate eye comprises tissues from different embryonic origins: the lens and the cornea are derived from the surface ectoderm, but the retina and the epithelial layers of the iris and ciliary body are from the anterior neural plate. The timely action of transcription factors and inductive signals ensure the correct development of the different eye components. Establishing the genetic basis of eye defects in zebrafishes, mouse, and human has been an important tool for the detailed analysis of this complex process. A single eye field forms centrally within the anterior neural plate during gastrulation; it is characterized on the molecular level by the expression of "eye-field transcription factors." The single eye field is separated into two, forming the optic vesicle and later (under influence of the lens placode) the optic cup. The lens develops from the lens placode (surface ectoderm) under influence of the underlying optic vesicle. Pax6 acts in this phase as master control gene, and genes encoding cytoskeletal proteins, structural proteins, or membrane proteins become activated. The cornea forms from the surface ectoderm, and cells from the periocular mesenchyme migrate into the cornea giving rise for the future cornea stroma. Similarly, the iris and ciliary body form from the optic cup. The outer layer of the optic cup becomes the retinal pigmented epithelium, and the main part of the inner layer of the optic cup forms later the neural retina with six different types of cells including the photoreceptors. The retinal ganglion cells grow toward the optic stalk forming the optic nerve. This review describes the major molecular players and cellular processes during eye development as they are known from frogs, zebrafish, chick, and mice-showing also differences among species and missing links for future research. The relevance to human disorders is one of the major aspects covered throughout the review.
Color image decomposition and restoration

Meyer has recently introduced an image decomposition model to split an image into two components: a geometrical component and a texture (oscillatory) component. Inspired by his work, numerical models have been developed to carry out the decomposition of gray scale images. In this paper, we propose a decomposition algorithm for color images. We introduce a generalization of Meyer s G norm to RGB vectorial color images, and use Chromaticity and Brightness color model with total variation minimization. We illustrate our approach with numerical examples. 2005 Elsevier Inc. All rights reserved.
Detection of microaneurysms using multi-scale correlation coefficients

This paper presents a new approach to the computer aided diagnosis (CAD) of diabetic retinopathy (DR)—a common and severe complication of long-term diabetes which damages the retina and cause blindness. Since microaneurysms are regarded as the first signs of DR, there has been extensive research on effective detection and localization of these abnormalities in retinal images. In contrast to existing algorithms, a new approach based on multi-scale correlation filtering (MSCF) and dynamic thresholding is developed. This consists of two levels, microaneurysm candidate detection (coarse level) and true microaneurysm classification (fine level). The approach was evaluated based on two public datasets—ROC (retinopathy on-line challenge, http://roc.healthcare.uiowa.edu) and DIARETDB1 (standard diabetic retinopathy database, http://www.it.lut.fi/project/imageret/diaretdb1). We conclude our method to be effective and efficient. & 2010 Elsevier Ltd. All rights reserved.
Garbage Collection in an Uncooperative Environment

Hans-Juergen Boehm Computer Science Department, Rice University, Houston, TX 77251-1892, U.S.A. Mark Weiser Xerox Corporation, Palo Alto Research Center, 3333 Coyote Hill Road, Palo Alto, CA 94304, U.S.A. A later version of this paper appeared in Software Practice and Experience 18, 9, pp. 807-820. Copyright 1988 by John Wiley and Sons, Ld. The publishers rules appear to allow posting of preprints, but only on the author’s web site.