LLukas22/scidocs huggingface dataset:
Analysis of air-launched ground-penetrating radar techniques to measure the soil surface water content: SURFACE WATER CONTENT FROM AIR-LAUNCHED GPR

[1] We analyze the common surface reflection and full-wave inversion methods to retrieve the soil surface dielectric permittivity and correlated water content from airlaunched ground-penetrating radar (GPR) measurements. In the full-wave approach, antenna effects are filtered out from the raw radar data in the frequency domain, and fullwave inversion is performed in the time domain, on a time window focused on the surface reflection. Synthetic experiments are performed to investigate the most critical hypotheses on which both techniques rely, namely, the negligible effects of the soil electric conductivity (s) and layering. In the frequency range 1–2 GHz we show that for s > 0.1 Sm , significant errors are made on the estimated parameters, e.g., an absolute error of 0.10 in water content may be observed for s = 1 Sm . This threshold is more stringent with decreasing frequency. Contrasting surface layering may proportionally lead to significant errors when the thickness of the surface layer is close to one fourth the wavelength in the medium, which corresponds to the depth resolution. Absolute errors may be >0.10 in water content for large contrasts. Yet we show that full-wave inversion presents valuable advantages compared to the common surface reflection method. First, filtering antenna effects may prevent absolute errors >0.04 in water content, depending of the antenna height. Second, the critical reference measurements above a perfect electric conductor (PEC) are not required, and the height of the antenna does not need to be known a priori. This averts absolute errors of 0.02–0.09 in water content when antenna height differences of 1–5 cm occur between the soil and the PEC. A laboratory experiment is finally presented to analyze the stability of the estimates with respect to actual measurement and modeling errors. While the conditions were particularly well suited for applying the common reflection method, better results were obtained using fullwave inversion.
Validity of Montreal Cognitive Assessment in non-english speaking patients with Parkinson's disease.

BACKGROUND
The Montreal Cognitive Assessment is a brief and easy screening tool for accurately testing cognitive dysfunction in Parkinson's disease. We tested its validity for use in non-English (Malayalam) speaking patients with Parkinson's disease.


MATERIALS AND METHODS
We developed a Malayalam (a south-Indian language) version of Montreal Cognitive Assessment and applied to 70 patients with Parkinson's disease and 60 age- and education-matched healthy controls. Metric properties were assessed, and the scores were compared with the performance in validated Malayalam versions of Mini Mental Status Examination and Addenbrooke's Cognitive Examination.


RESULTS
The Montreal Cognitive Assessment-Malayalam showed good internal consistency and test-retest reliability and its scores correlated with Mini Mental Status Examination (patients: R = 0.70; P < 0.001; healthy controls: R = 0.26; P = 0.04) and Addenbrooke's Cognitive Examination (patients: R = 0.8; P < 0.001; healthy controls: R = 0.52; P < 0.001) scores.


CONCLUSION
This study establishes the reliability of cross-cultural adaptation of Montreal Cognitive Assessment for assessing cognition in Malayalam-speaking Parkinson's disease patients for early screening and potential future interventions for cognitive dysfunction.
Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search

We present Grid Beam Search (GBS), an algorithm which extends beam search to allow the inclusion of pre-specified lexical constraints. The algorithm can be used with any model that generates a sequence ŷ = {y0 . . . yT }, by maximizing p(y|x) = ∏ t p(yt|x; {y0 . . . yt−1}). Lexical constraints take the form of phrases or words that must be present in the output sequence. This is a very general way to incorporate additional knowledge into a model’s output without requiring any modification of the model parameters or training data. We demonstrate the feasibility and flexibility of Lexically Constrained Decoding by conducting experiments on Neural Interactive-Predictive Translation, as well as Domain Adaptation for Neural Machine Translation. Experiments show that GBS can provide large improvements in translation quality in interactive scenarios, and that, even without any user input, GBS can be used to achieve significant gains in performance in domain adaptation scenarios.
Roles of Urban Tree Canopy and Buildings in Urban Heat Island Effects: Parameterization and Preliminary Results

Urban heat island (UHI) effects can strengthen heat waves and air pollution episodes. In this study, the dampening impact of urban trees on the UHI during an extreme heat wave in the Washington, D.C., and Baltimore, Maryland, metropolitan area is examined by incorporating trees, soil, and grass into the coupled Weather Research and Forecasting model and an urban canopy model (WRF-UCM). By parameterizing the effects of these natural surfaces alongside roadways and buildings, the modified WRF-UCM is used to investigate how urban trees, soil, and grass dampen the UHI. The modified model was run with 50% tree cover over urban roads and a 10% decrease in the width of urban streets to make space for soil and grass alongside the roads and buildings. Results show that, averaged over all urban areas, the added vegetation decreases surface air temperature in urban street canyons by 4.1 K and road-surface and building-wall temperatures by 15.4 and 8.9 K, respectively, as a result of tree shading and evapotranspiration. These temperature changes propagate downwind and alter the temperature gradient associated with the Chesapeake Bay breeze and, therefore, alter the strength of the bay breeze. The impact of building height on the UHI shows that decreasing commercial building heights by 8 m and residential building heights by 2.5 m results in up to 0.4-K higher daytime surface and near-surface air temperatures because of less building shading and up to 1.2-K lower nighttime temperatures because of less longwave radiative trapping in urban street canyons.
Prognostic factors of unresectable pancreatic cancer treated with nafamostat mesilate combined with gemcitabine chemotherapy.

BACKGROUND
The aim of this study was to investigate prognostic factors of survival for patients with unresectable pancreatic cancer treated with nafamostat mesilate combined with gemcitabine chemotherapy.


PATIENTS AND METHODS
The study included 41 patients who were diagnosed with unresectable pancreatic cancer and eligible for our clinical study of nafamostat mesilate, combined with gemcitabine chemotherapy for unresectable pancreatic cancer between February 2007 and November 2010 at Jikei University Hospital. We retrospectively investigated the relation between patients' characteristics and overall survival using univariate and multivariate analyses.


RESULTS
In univariate analysis, absence of jaundice (p=0.0365), presence of ascites with or without histological diagnosis of carcinomatosis (p=0.0042), lymphocyte count ≥2,000/μl (p=0.0088), serum C-reactive protein ≥1 mg/dl (p=0.014), serum carcinoembryonic antigen ≥5 ng/ml (p=0.0064) and serum CA19-9 ≥500 U/ml (p=0.0164) were significant predictors of poor overall survival. In multivariate analysis, absence of jaundice (p=0.0057), presence of ascites with or without histological diagnosis of carcinomatosis (p=0.0326), lymphocyte ≥2,000/μl (p<0.0001) and CA19-9 ≥500 U/ml (p=0.0198) were independent predictors.


CONCLUSION
Jaundice, ascites, high lymphocyte count and high serum CA19-9 levels are independent prognostic predictors for poor overall survival of patients with unresectable pancreatic cancer treated with nafamostat mesilate combined with gemcitabine chemotherapy.
Tales from the Map Room: Fact and Fiction about Maps and Their Makers

Written to accompany a six-part TV series, takes an intriguing look at all sorts of maps, from military and navigational charts used for strategic planning in wartime to medieval monster maps and the first maps of metropolitan London.
Opioid maintenance therapy in Switzerland: an overview of the Swiss IMPROVE study.

BACKGROUND/AIMS
Switzerland's drug policy model has always been unique and progressive, but there is a need to reassess this system in a rapidly changing world. The IMPROVE study was conducted to gain understanding of the attitudes and beliefs towards opioid maintenance therapy (OMT) in Switzerland with regards to quality and access to treatment. To obtain a "real-world" view on OMT, the study approached its goals from two different angles: from the perspectives of the OMT patients and of the physicians who treat patients with maintenance therapy. The IMPROVE study collected a large body of data on OMT in Switzerland. This paper presents a small subset of the dataset, focusing on the research design and methodology, the profile of the participants and the responses to several key questions addressed by the questionnaires.


METHODS
IMPROVE was an observational, questionnaire-based cross-sectional study on OMT conducted in Switzerland. Respondents consisted of OMT patients and treating physicians from various regions of the country. Data were collected using questionnaires in German and French. Physicians were interviewed by phone with a computer-based questionnaire. Patients self-completed a paper-based questionnaire at the physicians' offices or OMT treatment centres.


RESULTS
A total of 200 physicians and 207 patients participated in the study. Liquid methadone and methadone tablets or capsules were the medications most commonly prescribed by physicians (60% and 20% of patient load, respectively) whereas buprenorphine use was less frequent. Patients (88%) and physicians (83%) were generally satisfied with the OMT currently offered. The current political framework and lack of training or information were cited as determining factors that deter physicians from engaging in OMT. About 31% of OMT physicians interviewed were ≥60 years old, indicating an ageing population. Diversion and misuse were considered a significant problem in Switzerland by 45% of the physicians.


CONCLUSION
The subset of IMPROVE data presented gives a present-day, real-life overview of the OMT landscape in Switzerland. It represents a valuable resource for policy makers, key opinion leaders and drug addiction researchers and will be a useful basis for improving the current Swiss OMT model.
The LANAP Protocol (laser-assisted new attachment procedure) - A Minimally Invasive Bladeless Procedure.

Khadtare Y, Chaudhari A, Waghmare P, Prashant S. (laser-assisted new attachment procedure) The LANAP Protocol A Minimally Invasive Bladeless Procedure. J Periodontol Med Clin Pract 2014;01: 264-271 1 2 2 3 Dr. Yogesh Khadtare , Dr. Amit Chaudhari , Dr. Pramod Waghmare , Dr. Shekhar Prashant Review Article Journal of Periodontal Medicine & Clinical Practice JPMCP Journal of Periodontal Medicine & Clinical Practice
Hybridization of intelligent techniques and ARIMA models for time series prediction

Traditionally, the autoregressive moving average (ARMA) model has been one of the most widely used linear models in time series prediction. Recent research activities in forecasting with artificial neural networks (ANNs) suggest that ANNs can be a promising alternative to the traditional ARMA structure. These linear models and ANNs are often compared with mixed conclusions in terms of the superiority in forecasting performance. In this paper we propose a hybridization of intelligent techniques such as ANNs, fuzzy systems and evolutionary algorithms, so that the final hybrid ARIMA–ANN model could outperform the prediction accuracy of those models when used separately. More specifically, we propose the use of fuzzy rules to elicit the order of the ARMA or ARIMA model, without the intervention of a human expert, and the use of a hybrid ARIMA–ANN model that combines the advantages of the easy-to-use and relatively easy-to-tune ARIMA models, and the computational power of ANNs. © 2007 Elsevier B.V. All rights reserved.
A CAD-Free and a CAD-Based Geometry Control System for Aerodynamic Shape Optimization

The performance of an aerodynamic shape optimization routine is greatly dependent on its geometry control system. This system must accurately parameterize the initial geometry and generate a flexible set of design variables for the optimization cycle. It must also generate new instances of the geometry based on the changes to the design variables dictated by the optimization routine. In response to changes in the geometry, it is also desirable to generate a new surface grid with the same topology as the original grid. This new surface grid can be used to perturb the associated volume grid. This paper presents two geometry control systems, a CAD-free system, and a CATIA V5 CAD-based system. The two systems provide practical tools for aerodynamic optimization. They also provide a basis for comparing CAD-free and CAD-based systems and understanding additional issues that need to be addressed in order to develop reliable optimization systems.
MOOC dropout prediction using machine learning techniques: Review and research challenges

MOOC represents an ultimate way to deliver educational content in higher education settings by providing high-quality educational material to the students throughout the world. Considering the differences between traditional learning paradigm and MOOCs, a new research agenda focusing on predicting and explaining dropout of students and low completion rates in MOOCs has emerged. However, due to different problem specifications and evaluation metrics, performing a comparative analysis of state-of-the-art machine learning architectures is a challenging task. In this paper, we provide an overview of the MOOC student dropout prediction phenomenon where machine learning techniques have been utilized. Furthermore, we highlight some solutions being used to tackle with dropout problem, provide an analysis about the challenges of prediction models, and propose some valuable insights and recommendations that might lead to developing useful and effective machine learning solutions to solve the MOOC dropout problem.
Conditional Monte Carlo Dense Occupancy Tracker

Proper modeling of dynamic environments is a core task in the field of intelligent vehicles. The most common approaches involve the modeling of moving objects, through Detection And Tracking of Moving Objects (DATMO) methods. An alternative to a classic object model framework is the occupancy grid filtering domain. Instead of segmenting the scene into objects and track them, the environment is represented as a regular grid of occupancy, in which spatial occupancy is tracked at a sub-object level. In this paper, we present the Conditional Monte Carlo Dense Occupancy Tracker, a generic spatial occupancy tracker, which infers dynamics of the scene through an hybrid representation of the environment, consisting of static occupancy, dynamic occupancy, empty spaces and unknown areas. This differentiation enables the use of state specific models (classic occupancy grid for motion-less components, set of moving particles for dynamic occupancy) as well as proper confidence estimation and management of data-less areas. The approach leads to a compact model that drastically improves the accuracy of the results and the global efficiency in comparison to previous methods.
Randomized, multicenter trial to assess the efficacy, safety and tolerability of a single dose of a novel AMPA receptor antagonist BGG492 for the treatment of acute migraine attacks.

BACKGROUND
Glutamate is implicated in migraine pathophysiology; amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor antagonists represent a potential therapeutic approach because of their anti-excitatory actions.


METHODS
This randomized, double-blind, proof-of-concept study assessed the efficacy of the AMPA receptor antagonist, BGG492 (250 mg), vs placebo and sumatriptan (100 mg), in 75 subjects with acute migraine attacks. Efficacy was measured using the Patient Migraine Diary. Pharmacokinetic and safety data were collected.


RESULTS
Improvement from severe/moderate to mild/no headache pain (primary response) was reported in 58%, 58%, and 54% of BGG492-treated subjects at 2, 3, and 4 hours post-dose ( P = 0.2, 0.5, and 0.5 vs placebo), respectively, compared with 68%, 84%, and 92% sumatriptan-treated subjects, and 40%, 48%, and 44% in the placebo group. Percentages of subjects with ≥ 2-point improvement in pain score from baseline at 2 hours were 29%, 40%, and 16% for BGG492, sumatriptan, and placebo, respectively. Pain-free response at 2 hours was reported for 25%, 24%, and 16% of BGG492, sumatriptan, and placebo subjects, respectively. Adverse events were reported by 80%, 56%, and 60% of BGG492, sumatriptan, and placebo subjects, respectively.


CONCLUSIONS
Proof-of-concept criterion was not met (≥ 25% BGG492 subjects with a primary response vs placebo at two timepoints). BGG492 was comparable to sumatriptan in terms of pain-free response.
Progression of Seed-Induced Aβ Deposition within the Limbic Connectome.

An important early event in the pathogenesis of Alzheimer's disease (AD) is the aberrant polymerization and extracellular accumulation of amyloid-β peptide (Aβ). In young transgenic mice expressing the human Aβ-precursor protein (APP), deposits of Aβ can be induced by the inoculation of minute amounts of brain extract containing Aβ aggregates ("Aβ seeds"), indicative of a prion-like seeding phenomenon. Moreover, focal intracerebral injection of Aβ seeds can induce deposits not only in the immediate vicinity of the injection site, but, with time, also in distal regions of the brain. However, it remains uncertain whether the spatial progression of Aβ deposits occurs via nonsystematic diffusion from the injection site to proximal regions or via directed transit along neuroanatomical pathways. To address this question, we analyzed the spatiotemporal emergence of Aβ deposits in two different APP-transgenic mouse models that had been previously inoculated with Aβ seeds into the hippocampal formation. The results revealed a specific, neuroanatomically constrained pattern of induced Aβ deposits in structures corresponding to the limbic connectome, supporting the hypothesis that neuronal pathways act as conduits for the movement of proteopathic agents among brain regions, thereby facilitating the progression of disease.
Cayuga: A General Purpose Event Monitoring System

We describe the design and implementation of the Cornell Cayuga System for scalable event processing. We present a query language based on Cayuga Algebra for naturally expressing complex event patterns. We also describe several novel system design and implementation issues, focusing on Cayuga’s query processor, its indexing approach, how Cayuga handles simultaneous events, and its specialized garbage collector.
Model for perianth formation in orchids

Orchidaceae, the orchid family under the order Asparagales, contains more than 20,000 accepted species in approximately 880 genera1–3. In contrast to most flowers of actinomorphic symmetry, orchid flowers typically have zygomorphic symmetry with a striking well-differentiated labellum (lip) that acts as the main pollinator attractant by employing visual, fragrance and tactile cues4–7. Genetics models controlling patterning formation of actinomorphic flowers, such as Arabidopsis, are well known. However, the mechanisms of sepal/petal/lip determination remain obscure. Here, we demonstrate a conserved principle, called the Perianth (P) code, which involves competition between two protein complexes containing different AP3/AGL6 homologues to determine the formation of the complex perianth patterns in orchids. In the P code, the higher-order heterotetrameric SP (sepal/petal) complex (OAP3-1/OAGL6-1/OAGL6-1/OPI) specifies sepal/petal formation, whereas the L (lip) complex (OAP3-2/OAGL6-2/OAGL6-2/OPI) is exclusively required for lip formation. This model is validated by the conversion of lips into sepal/petal structures in Oncidium and Phalaenopsis orchids through the suppression of the proposed L complex activity in lips using the virus-induced gene silencing (VIGS) strategy. A comprehensive examination of four different subfamilies of Orchidaceae further validates the P code and significantly extends the current knowledge regarding the mechanism and pathways of perianth formation in orchids.
Introduction of Auricular Acupuncture in Elderly Patients Suffering from Major Depression: Protocol of a Mixed Methods Feasibility Study

BACKGROUND
Due to an increasing number of elderly people suffering from major depression and potential side effects of the prescribed drugs, the introduction of new therapeutic approaches is needed. Currently, in Germany, auricular acupuncture is no part of clinical care for gerontopsychiatric patients. Based on promising clinical experiences and existing evidence for treating addiction and trauma, a benefit of auricular acupuncture integrated in existing treatment programs in elderly patients may be hypothesized. Within this project auricular acupuncture according to the National Acupuncture Detoxification Association (NADA) will be integrated in the multimodal treatment regime for elderly patients with major depression in a daytime ward setting.


METHODS/DESIGN
To evaluate the feasibility and acceptance a mixed method approach is used. In a day clinic, a sample of 20 psychogeriatric patients with the diagnosis of major depression will be enrolled. The patients will receive a total of nine auricular acupuncture treatments according to the standardized NADA protocol in a group setting. The therapeutic process, its organization, the experience, and the willingness of patients to participate will be evaluated by interviews with patients and the therapeutic team. Data will be analyzed qualitatively using content analysis. Additionally, quantitative outcome parameters will be measured by standardized questionnaires.
Intersection Quasi-Orderings: An Alternative Proof

This note provides an alternative proof of a known result on the existence of collections of orderings generating intersection quasi-orderings. Instead of proving the result from first principles, it is illustrated how it can be obtained by making use of an analogous relationship between partial orders and linear orders.
Multicenter evaluation of dynamic three-dimensional magnetic resonance myocardial perfusion imaging for the detection of coronary artery disease defined by fractional flow reserve.

BACKGROUND
First-pass myocardial perfusion cardiovascular magnetic resonance (CMR) imaging yields high diagnostic accuracy for the detection of coronary artery disease (CAD). However, standard 2D multislice CMR perfusion techniques provide only limited cardiac coverage, and hence considerable assumptions are required to assess myocardial ischemic burden. The aim of this prospective study was to assess the diagnostic performance of 3D myocardial perfusion CMR to detect functionally relevant CAD with fractional flow reserve (FFR) as a reference standard in a multicenter setting.


METHODS AND RESULTS
A total of 155 patients with suspected CAD listed for coronary angiography with FFR were prospectively enrolled from 5 European centers. 3D perfusion CMR was acquired on 3T MR systems from a single vendor under adenosine stress and at rest. All CMR perfusion analyses were performed in a central laboratory and blinded to all clinical data. One hundred fifty patients were successfully examined (mean age 62.9±10 years, 45 female). The prevalence of CAD defined by FFR (<0.8) was 56.7% (85 of 150 patients). The sensitivity and specificity of 3D perfusion CMR were 84.7% and 90.8% relative to the FFR reference. Comparison to quantitative coronary angiography (≥50%) yielded a prevalence of 65.3%, sensitivity and specificity of 76.5% and 94.2%, respectively.


CONCLUSIONS
In this multicenter study, 3D myocardial perfusion CMR proved highly diagnostic for the detection of significant CAD as defined by FFR.