nils-herrmann/clean_scirepeval huggingface dataset:
Potential roles of anaerobic ammonium and methane oxidation in the nitrogen cycle of wetland ecosystems
Venue: Applied Microbiology and Biotechnology
Year: 2010

Anaerobic ammonium oxidation (anammox) and anaerobic methane oxidation (ANME coupled to denitrification) with nitrite as electron acceptor are two of the most recent discoveries in the microbial nitrogen cycle. Currently the anammox process has been relatively well investigated in a number of natural and man made ecosystems, while ANME coupled to denitrification has only been observed in a limited number of freshwater ecosystems. The ubiquitous presence of anammox bacteria in marine ecosystems has changed our knowledge of the global nitrogen cycle. Up to 50% of N2 production in marine sediments and oxygen depleted zones may be attributed to anammox bacteria. However, there are only few indications of anammox in natural and constructed freshwater wetlands. In this paper, the potential role of anammox and denitrifying methanotrophic bacteria in natural and artificial wetlands is discussed in relation to global warming. The focus of the review is to explore and analyze if suitable environmental conditions exist for anammox and denitrifying methanotrophic bacteria in nitrogen rich freshwater wetlands.
Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?
Venue: International journal of molecular sciences
Year: 2020

Bipolar disorder (BD) is a complex neurobiological disorder characterized by a pathologic mood swing. Digital phenotyping, defined as the 'moment by moment quantification of the individual level human phenotype in its own environment' represents a new approach aimed at measuring the human behavior and may theoretically enhance clinicians' capability in early identification, diagnosis, and management of any mental health conditions, including BD. Moreover, a digital phenotyping approach may easily introduce and allow clinicians to perform a more personalized and patient tailored diagnostic and therapeutic approach, in line with the framework of precision psychiatry. The aim of the present paper is to investigate the role of digital phenotyping in BD. Despite scarce literature published so far, extremely heterogeneous methodological strategies, and limitations, digital phenotyping may represent a grounding research and clinical field in BD, by owning the potentialities to quickly identify, diagnose, longitudinally monitor, and evaluating clinical response and remission to psychotropic drugs. Finally, digital phenotyping might potentially constitute a possible predictive marker for mood disorders.
Dipole Repeller Gravity Effects at Different Universal Scales as the Origin of Large Scale and Local Quantum Gravity and Hubble Redshift.
Year: 2017

According to Quantum Function Follows Form Theory, the Big Bang was the evaporation and splitting of a former Big Crunch black hole nucleus of compressed Axion Higgs particles into the oscillating Axion /Higgs field vacuum lattice respectively chunky nuclei of dark matter black holes. The vacuum Lattice is supposed to represent a dynamic reference frame and the so called Dark Energy or Zero Point Energy acting as the motor for all Fermion spin and as the transfer medium for all photon information, leading to local lightspeed and local time. The energetic vacuum lattice is also assumed to act as a Gravity Quantum Dipole Repeller because gravitons do not supposed to attract but repel Fermions with less impulse than the vacuum dark energy particles. So, Feynman diagrams become more complex than before. Recent measurements by Yehuda Hoffman et al. did show the large scale repelling effect of "empty space" in opposition of the "attracting gravity effect" of super clusters which he called "Dipole Repeller" effect. This seems to be a great support for the dual Quantum gravity proposal of Quantum FFF Theory, as opposing quantum push effects between vacuum particles and gravitons on Fermion around massive objects. Recently I found that the merging of galaxy clusters itself show dynamic observational signs of a contraction of the vacuum inside the merging galaxy clusters by the anomalous central clustering of the dark matter black hole content which seems to be stripped from the individual galaxy clusters located at the borders of the new super cluster. see Abell 520 and bullet cluster: "no inertia effect of dark matter black holes" If there is vacuum absorption inside galaxy clusters, (Black Holes EAT the vacuum (Axion Higgs Field) then we also may assume that the universal vacuum between galaxy clusters should be also subjected to this absorption process, which surpass the redshift of relative speed) as a sign for universal contraction and negative entropy, leading to a cyclic universe. All Black holes EAT the dark energy Axion Higgs vacuum lattice supposed to be the origin of the Hubble redshift and universal contraction.
Location Extraction from Social Media
Venue: ACM Trans. Inf. Syst.
Year: 2018

Location extraction, also called "toponym extraction," is a field covering geoparsing, extracting spatial representations from location mentions in text, and geotagging, assigning spatial coordinates to content items. This article evaluates five "best of class" location extraction algorithms. We develop a geoparsing algorithm using an OpenStreetMap database, and a geotagging algorithm using a language model constructed from social media tags and multiple gazetteers. Third party work evaluated includes a DBpedia based entity recognition and disambiguation approach, a named entity recognition and Geonames gazetteer approach, and a Google Geocoder API approach. We perform two quantitative benchmark evaluations, one geoparsing tweets and one geotagging Flickr posts, to compare all approaches. We also perform a qualitative evaluation recalling top N location mentions from tweets during major news events. The OpenStreetMap approach was best (F1 0.90+ for geoparsing English, and the language model approach was best (F1 0.66) for Turkish. The language model was best (F1@1km 0.49) for the geotagging evaluation. The map database was best (R@20 0.60+ in the qualitative evaluation. We report on strengths, weaknesses, and a detailed failure analysis for the approaches and suggest concrete areas for further research.
Recent progress of sample stacking in capillary electrophoresis (2016 2018)
Venue: Electrophoresis
Year: 2019

Electrophoretic sample stacking comprises a group of capillary electrophoretic techniques where trace analytes from the sample are concentrated into a short zone (stack) This paper is a continuation of our previous reviews on the topic and brings a survey of more than 120 papers published approximately since the second quarter of 2016 till the first quarter of 2018. It is organized according to the particular stacking principles and includes chapters on concentration adjustment (Kohlrausch) stacking, on stacking techniques based on pH changes, on stacking in electrokinetic chromatography and on other stacking techniques. Where available, explicit information is given about the procedure, electrolyte(s) used, detector employed and sensitivity reached. Not reviewed are papers on transient isotachophoresis which are covered by another review in this issue.
Securing the Industrial Internet of Things for Critical Infrastructure (IIoT CI)
Venue: 2019 IEEE 5th World Forum on Internet of Things (WF IoT)
Year: 2019

The Industrial Internet of Things (IIoT) is a term applied to the industrial application of M2M devices. The security of IIoT devices is a difficult problem and where the automation of critical infrastructure is intended, risks may be unacceptable. Remote attacks are a significant threat and solutions are sought which are secure by default. The problem space may be analyzed using threat modelling methods. Software Defined Networks (SDN) provide mitigation for remote attacks which exploit local area networks. Similar concepts applied to the WAN may improve availability and performance and provide granular data on link characteristics. Schemes such as the Software Defined Perimeter allow IIoT devices to communicate on the Internet, mitigating avenues of remote attack. Finally, separation of duties at the IIoT device may prevent attacks on the integrity of the device or the confidentiality and integrity of its communications. Work remains to be done on the mitigation of DDoS.
Operational calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible and near infrared channels
Year: 2010

The Advanced Very High Resolution Radiometer (AVHRR) visible and near infrared channels must be calibrated after launch to maintain the accuracy of data derived from these channels for quantitative utilizations. The postlaunch calibration of these channels can only be carried out vicariously. The National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite, Data, an Information Service (NESDIS) has been using the Libyan Desert as reference for operational calibration of AVHRR visible and near infrared channels since 1995. A previous algorithm was successful correcting for the long term instrument degradation in recalibration but had difficulty updating instrument calibration in near real time operation. This paper describes the operational calibration algorithm implemented since 2003, which overcomes the existing shortcomings by reducing target contamination and accounting for the effects of target bidirectional reflectance distribution function. Application of the algorithm shortens the latency of postlaunch calibration from 3 to 4 years for NOAA 14 and NOAA 16 to less than 2 years for NOAA 17 and to a few months for later satellites. Compared with the previous algorithm, the current algorithm enhances the calibration precision from 1.7% to 0.9% for channel 1.
Data driven Optimal Operational Control of Complex Grinding Processes
Year: 2014

For hematite grinding processes, it is not only difficult to describe the dynamics between grinding particle size (GPS) and control loop outputs by using mathematical formulas, but also impossible to measure the GPS online. Moreover, the process is sensitively influenced by the frequent fluctuation of ore compositions and properties. The above practical problems make the existing control methods unable to be applied. In this paper, a data driven optimal operational control approach, which consists of loop pre setting optimizer, performance index estimator, optimum setpoints critic, and GPS soft sensor, is proposed by using neural network. In this approach, the GPS is estimated by the GPS soft sensor first, then the loop pre setting optimizer generates the optimum loop pre setting values by making performance index estimate close to its optimal value. Finally, via the optimum setpoints critic the optimal setpoint is obtained. With the help of the control loops, the GPS can be maintained inside its desired range, and close to its target value as much as possible. Experiments using a developed research platform of optimal operational control are carried out with real time data to show the effectiveness of the proposed method.
TANTANGAN GURU PENDIDIKAN AGAMA ISLAM DALAM MENGHADAPI PERKEMBANGAN DI ERA INDUSTRI 4.0
Year: 2020

In the era of industrial revolution this has an influence on the world of education. many changes in attitudes experienced by students by incidentally are millennials who are familiar with the digital world and they are familiar with the flow of information and industrial technology 4.0 teachers have a very impnortant role to influence the education of students. especially PAI teachers whose duty is not only to convey knowledge or merely transfer knowledge, but also to be responsible in the moral and moral education of students. increasingly sophisticated technological developments should be managed positively so as to provide benefits and positive and positive impacts for the advancement of education, especially in the current era of the industrial revolution.
Single cell transcriptomic analysis of Alzheimer's disease
Venue: Nature
Year: 2019

Alzheimer's disease is a pervasive neurodegenerative disorder, the molecular complexity of which remains poorly understood. Here, we analysed 80,660 single nucleus transcriptomes from the prefrontal cortex of 48 individuals with varying degrees of Alzheimer's disease pathology. Across six major brain cell types, we identified transcriptionally distinct subpopulations, including those associated with pathology and characterized by regulators of myelination, inflammation, and neuron survival. The strongest disease associated changes appeared early in pathological progression and were highly cell type specific, whereas genes upregulated at late stages were common across cell types and primarily involved in the global stress response. Notably, we found that female cells were overrepresented in disease associated subpopulations, and that transcriptional responses were substantially different between sexes in several cell types, including oligodendrocytes. Overall, myelination related processes were recurrently perturbed in multiple cell types, suggesting that myelination has a key role in Alzheimer's disease pathophysiology. Our single cell transcriptomic resource provides a blueprint for interrogating the molecular and cellular basis of Alzheimer's disease.Single cell transcriptomics from 48 individuals with varying degrees of Alzheimer's disease pathology demonstrates that gene expression changes in Alzheimer's disease are both cell type specific and shared, and that transcriptional responses show sexual dimorphism.
Simultaneous Designing of a Heat Exchangers Network with least Cost and Emissions
Year: 2018

Energy conservation, clean environment are important topics for search. Heat Exchangers Network [HEN] is an effective way for achieving energy recovery and so on minimizing operating cost for chemical plants. Reduction of greenhouse gasses (GHG) emission is a direct result of energy integration while gathering it with clean fuel switching minimizes emissions. In this work we formulated a simultaneous methodology with a multiobjective function of minimizing cost and maximizing emission 'reduction through designing a [HEN] constrained by fuel type and minimum temperature difference approach (DTmin) Application of this methodology with a mathematical solver (GAMS) on an existing naphtha treating unit resulted excellent results. Energy recovery technique through HENs at several values of (DTmin) reduced energy consumption by 27% to 18% and reduced gasses emissions by 21% to 12% comparing to actual data of the treating unit. While application of fuel switching technique; increased emission reduction percentage to 34% Combination both techniques improved results; where HEN at optimum (DTmin=18oC) with natural gas switching achieved reduction of energy and GHG by 24% and 44% respectively, so it is the candidate design for the unit revamping. Another revamping technique was fuel switching to coke, where adding Post Combustion Carbon Capture (PCC) is an emission reduction solution by 85%
The Effect of Heavy Metals and Trace Elements in the Meconium on Preterm Delivery of Unknown Etiology
Year: 2012

Prematurity is an important etiologic factor for perinatal mortality and morbidity. In our country, preterm births and complications of prematurity account for 26% of perinatal mortality. There are many maternal, fetal or placental, genetic and environmental eti ologic factors that cause prematurity. There have been no studies to show an association between preterm delivery of unknown etiology and exposure to heavy metals and trace elements at toxic levels in meconium. The purpose of this study is to measure the levels of heavy metals (lead, cad mium) and trace elements (zinc, iron, copper) in meconium samples and to understand their as sociations with preterm delivery of unknown etiology.  The levels of heavy metals and trace elements in the meconiums of 810 term or preterm infants with known and un known etiology for being preterm were measured with a flame atomic absorption spectropho tometer.  Lead and cadmium were detected in all meconium samples. Heavy metal and trace element levels in meconium were significantly higher in preterms of unknown and known etiology for being preterm compared to term infants (for all p<0.0001) Lead levels in meconium were significantly higher in preterm of unknown etiology compared to preterm of known eti ology in posthoc analysis with Bonferroni corrected Mann Whitney U test.  These re sults may suggest that lead levels in meconium samples are higher in preterm newborns especially with unknown etiology compared to term newborns. Therefore, we suggest that preterm deliv ery of unknown etiology may be decreased by decreasing air pollution.
International financial integration and real exchange rate long run dynamics in emerging countries: Some panel evidence
Year: 2009

The aim of this article is to provide new empirical evidence on the impact of international financial integration on the long run Real Exchange Rate (RER) in 39 developing countries belonging to three different geographical regions (Latin America, Asia and MENA) It covers the period 1979 2004, and carries out 'second generation' tests for non stationary panels. Several factors, including international financial integration, are shown to drive the long run RER in emerging countries. It is found that the new financial environment characterised by international financial integration leads to a depreciation of the RER in the long run. Further, RER misalignments take the form of an under valuation in most MENA countries and an over valuation in most Latin American and Asian countries.
Study on three level supply chain coordination based on revenue sharing under fuzzy demand
Year: 2012

The supply chain coordination problems is the core of the management of supply chain.This paper studied a three level supply chain with one supplier,one manufacturer and one retailer,considering the market demand under the influence of fuzzy variables.Through the establishment of uncertain theory,designed the model of integrated supply chain and revenue sharing contract based on the feasibility of distribution,then got the optimal strategy.Finally,through numerical examples to accurate the results.This paper shows that the optimal order of the retailers and manufacturers floated nearby the center of fuzzy demand.In addition,different income distribution coefficient corresponded to different wholesale price,to get the coordination between the members of supply chain by select the appropriate income distribution coefficient.
Waste, Leaks, and Failures in the Biomarker Pipeline.
Venue: Clinical chemistry
Year: 2017

The large, expanding literature on biomarkers is characterized by almost ubiquitous significant results, with claims about the potential importance, but few of these discovered biomarkers are used in routine clinical care. CONTENT The pipeline of biomarker development includes several specific stages: discovery, validation, clinical translation, evaluation, implementation (and, in the case of nonutility, deimplementation) Each of these stages can be plagued by problems that cause failures of the overall pipeline. Some problems are nonspecific challenges for all biomedical investigation, while others are specific to the peculiarities of biomarker research. Discovery suffers from poor methods and incomplete and selective reporting. External independent validation is limited. Selection for clinical translation is often shaped by nonrational choices. Evaluation is sparse and the clinical utility of many biomarkers remains unknown. The regulatory environment for biomarkers remains weak and guidelines can reach biased or divergent recommendations. Removing inefficient or even harmful biomarkers that have been entrenched in clinical care can meet with major resistance.  The current biomarker pipeline is too prone to failures. Consideration of clinical needs should become a starting point for the development of biomarkers. Improvements can include the use of more stringent methodology, better reporting, larger collaborative studies, careful external independent validation, preregistration, rigorous systematic reviews and umbrella reviews, pivotal randomized trials, and implementation and deimplementation studies. Incentives should be aligned toward delivering useful biomarkers.
Validation of a preclinical model of heart failure with reduced ejection fraction by a dual angiotensin receptor neprilysin inhibitor and an angiotensin converting enzyme inhibitor
Venue: Archives of Cardiovascular Diseases Supplements
Year: 2019

Heart failure (HF) patients often suffer from several co existing diseases and co morbidities. Among them, hypertension and myocardial infarction (MI) are two of the most frequent causes of HF1. Thus, as expected, experimental induction of MI in Spontaneously Hypertensive Rats (SHR) provokes severe left ventricular dysfunction and is associated with signs of HF2. Therapeutic effects of Angiotensin converting enzyme inhibitor (ACEi) and Angiotensin receptor neprilysin inhibitor (ARNi) have been demonstrated in HF patients with reduced ejection fraction (HFrEF)  The aim of the present study was to validate the translational value of the HF preclinical model SHR PMI using ARNi (Valsartan/Sacubitril, LCZ696) and ACEi (perindopril) treatments recommended by the ESC guidelines for HFrEF patients.  Permanent MI (PMI) was induced by coronary ligation in SHR (8 week old; N 30) randomized in three groups: placebo, LCZ696 (68 mg/kg/d) Perindopril (1 mg/kg/d) compared to a sham operated group (N 10) Three months post MI, LV function was assessed by echocardiography and hemodynamic study. HF signs were assessed by LV end diastolic pressure (LVEDP, mmHg) lung and right ventricle (RV) weights (mg) Results Two vehicle treated SHR PMI died during the follow up, no death was observed in LCZ696 or Perindopril treated groups. Post MI, both ARNi or ACEi treatments had beneficial effects on the adverse LV remodeling and seemed to prevent the mortality and signs of HF (further studies required to confirm these results)  In summary, the SHR PMI model has a good predictive value and can be used as preclinical model for the evaluation of new therapeutic strategy in HFrEF
Assess the Level of Knowledge Regarding Cardiopulmonary Resuscitation among Nursing students.
Year: 2019

The present study was aimed to assess the level of knowledge regarding cardiopulmonary resuscitation among nursing students by using a structured questionnaire. The objectives of the study were to assess the level of knowledge using structured questionnaire and to determine the association between knowledge regarding cardiopulmonary resuscitation and selected sample characteristics. The sample size consists of 60 subjects from a selected college of nursing at Alappuzha. The tool was structured questionnaire to assess the level of knowledge among nursing students. The data collected were analyzed with descriptive and inferential statistics. The study depicts that majority of students 81.6% were having average level of knowledge, 16.7% having poor knowledge and 1.7% having good level of knowledge regarding cardiopulmonary resuscitation