Miracle-dz/UniFAR-FTUs huggingface dataset:
The assessment of fishery status depends on fish habitats

At the crux of the debate over the global sustainability of fisheries is what society must do to prevent over‐exploitation and aid recovery of fisheries that have historically been over‐exploited. The focus of debates has been on controlling fishing pressure, and assessments have not considered that stock production may be affected by changes in fish habitat. Fish habitats are being modified by climate change, built infrastructure, destructive fishing practices and pollution. We conceptualize how the classification of stock status can be biased by habitat change. Habitat loss and degradation can result in either overly optimistic or overly conservative assessment of stock status. The classification of stock status depends on how habitat affects fish demography and what reference points management uses to assess status. Nearly half of the 418 stocks in a global stock assessment database use seagrass, mangroves, coral reefs and macroalgae habitats that have well‐documented trends. There is also considerable circumstantial evidence that habitat change has contributed to over‐exploitation or enhanced production of data‐poor fisheries, like inland and subsistence fisheries. Globally many habitats are in decline, so the role of habitat should be considered when assessing the global status of fisheries. New methods and global databases of habitat trends and use of habitats by fishery species are required to properly attribute causes of decline in fisheries and are likely to raise the profile of habitat protection as an important complementary aim for fisheries management.
Multilevel solution of the time‐harmonic Maxwell's equations based on edge elements

A widely used approach for the computation of time-harmonic electromagnetic fields is based on the well-known double-curl equation for either E or H, where edge elements are an appealing choice for finite element discretizations. Yet, the nullspace of the curl-operator comprises a considerable part of all spectral modes on the finite element grid. Thus standard multilevel solvers are rendered inefficient, as they essentially hinge on smoothing procedures like Gauss–Seidel relaxation, which cannot provide a satisfactory error reduction for modes with small or even negative eigenvalues. We propose to remedy this situation by an extended multilevel algorithm which relies on corrections in the space of discrete scalar potentials. After every standard V-cycle with respect to the canonical basis of edge elements, error components in the nullspace are removed by an additional projection step. Furthermore, a simple criterion for the coarsest mesh is derived to guarantee both stability and efficiency of the iterative multilevel solver. For the whole scheme we observe convergence rates independent of the refinement level of the mesh. The sequence of nested meshes required for our multilevel techniques is constructed by adaptive refinement. To this end we have devised an a posteriori error indicator based on stress recovery. Copyright © 1999 John Wiley & Sons, Ltd.
A Closer Look at the Aumann-Serrano and Foster-Hart Measures of Riskiness

Hart (2011) argues that the Aumann and Serrano (2008) and Foster and Hart (2009) measures of riskiness have an objective and universal appeal, assuming expected utility preferences. We show that mean-riskiness decision-making criteria using either measure violate expected utility. Alongside much experimental evidence, this motivates exploring universality beyond expected utility. We demonstrate that riskiness measures satisfying Hart’s other behavioral requirements do not generally exist when non-expected utility maximizers are additionally incorporated into the argument. We identify other attributes of the Aumann-Serrano and Foster-Hart measures that raise questions concerning their usefulness in a decision making, risk management, or risk assessment setting.
The last five glacial‐interglacial transitions: A high‐resolution 450,000‐year record from the subantarctic Atlantic

[1] A submillennial resolution, radiolarian-based record of summer sea surface temperature (SST) documents the last five glacial to interglacial transitions at the subtropical front, southern Atlantic Ocean. Rapid fluctuations occur both during glacial and interglacial intervals, and sudden cooling episodes at glacial terminations are recurrent. Surface hydrography and global ice volume proxies from the same core suggest that summer SST increases prior to terminations lead global ice-volume decreases by 4.7 ± 3.7 ka (in the eccentricity band), 6.9 ± 2.5 ka (obliquity), and 2.7 ± 0.9 ka (precession). A comparison between SST and benthic δ13C suggests a decoupling in the response of northern subantarctic surface, intermediate, and deep water masses to cold events in the North Atlantic. The matching features between our SST record and the one from core MD97-2120 (southwest Pacific) suggests that the super-regional expression of climatic events is substantially affected by a single climatic agent: the Subtropical Front, amplifier and vehicle for the transfer of climatic change. The direct correlation between warmer ΔTsite at Vostok and warmer SST at ODP Site 1089 suggests that warmer oceanic/atmospheric conditions imply a more southward placed frontal system, weaker gradients, and therefore stronger Agulhas input to the Atlantic Ocean.
Modeling the Learning That Takes Place Between Online Assessments

Student models for adaptive learning environments and intelligent tutoring systems typically assume a paradigm of use where a student completes exercises or activities, and learns from those exercises or activities. However, many modern systems, including MOOCs, intersperse declarative content or lecture with assessment of the learning from this content. In this paper, we present a variant of a common student modeling algorithm, Bayesian Knowledge Tracing, which assumes that most learning occurs during use of declarative content rather than between exercises. We compare this algorithm’s predictive ability to classic Bayesian Knowledge Tracing and another common algorithm, Performance Factors Assessment. We find that our new algorithm, BKT-PL, performs slightly better than algorithms designed for the standard intelligent tutoring paradigm. Moreso, we can use BKT-PL to determine which declarative content is most and least effective, to drive iterative re-design.
Lightning in Western Patagonia

On the basis of 8 years (2005–2012) of stroke data from the World Wide Lightning Location Network we describe the spatial distribution and temporal variability of lightning activity over Western Patagonia. This region extends from ~40°S to 55°S along the west coast of South America, is limited to the east by the austral Andes, and features a hyper‐humid, maritime climate. Stroke density exhibits a sharp maximum along the coast of southern Chile. Although precipitation there is largely produced by cold nimbostratus, days with more than one stroke occur up to a third of the time somewhere along the coastal strip. Disperse strokes are also observed off southern Chile. In contrast, strokes are virtually nonexistent over the austral Andes—where precipitation is maximum—and farther east over the dry lowlands of Argentina. Atmospheric reanalysis and satellite imagery are used to characterize the synoptic environment of lightning‐producing storms, exemplified by a case study and generalized by a compositing analysis. Lightning activity tends to occur when Western Patagonia is immersed in a pool of cold air behind a front that has reached the coast at ~40°S. Under these circumstances, midlevel cooling occurs before and is more prominent than near‐surface cooling, leading to a weakly unstable postfrontal condition. Forced uplift of the strong westerlies impinging on the coastal mountains can trigger convection and produces significant lightning activity in this zone. Farther offshore, large‐scale ascent near the cyclone's center may lift near‐surface air parcels, fostering shallow convection and dispersing lightning activity.
Does Adding Reinforcement of Implementation Intentions Support Behaviour Change?

It has been suggested that implementation intentions could help people to translate intentions into action and help them form a new habit by repeating their behavioural action consistently. However, implementation intentions remain underused. Previous studies have used reminders to strengthen implementation intentions. However, this could lead to dependency towards the reminders and hinder automaticity. So, in this experiment, we have tried a different approach by conducting a 4-week study to investigate the impact of reinforcement on implementation intentions for reporting daily mood. Unlike reminders sent when the action happens, our reinforcements were sent in advance to remind people of their implementation intentions. Our findings suggest that adding reinforcements leads to better compliance but not necessarily increased automaticity. The reinforcements also help people to remember their implementation intentions.
Marrow Stromal Cell based Stem Cell Based Transcatheter Aortic Valve Implantation: First Experiences in a Preclinical Model

Abstract We investigate the combination of transcatheter aortic-valve implantation (TAVI) and a novel concept of stem cell-based, tissue-engineered heart-valves (TEHV) comprising minimally-invasive techniques for both, cell-harvest and valve-delivery. TAVI represents an emerging technology for the treatment of aortic-valve disease. The utilized bioprostheses are inherently prone to calcific-degeneration and recent evidence suggests even accelerated degeneration resulting from structural-damage due to the crimping-procedures. Autologous, living heart-valve prosthesis with regeneration and repair capacities would overcome such limitations. Methods: Within a one-step intervention, tri-leaflet TEHV, generated from biodegradable synthetic-scaffolds, were integrated into self-expanding nitinol-stents, seeded with autologous bone-marrow mononuclear cells, crimped and transapically delivered into adult sheep (n=12). The animals were followed up for up to 2 weeks. TEHV-functionality was assessed by fluoroscopy, echocardiography and computed-tomography. Post-mortem analysis was performed using histology, extracellular-matrix analysis and electron-microscopy. Transapical aortic implantation of TEHV was successful in all animals (n=12) and the entire procedure-time from cell-harvest to TEHV-delivery was 109±14min. Fluoroscopy and echocardiography displayed TEHV-functionality demonstrating an adequate leaflet-mobility and co-aptation. Explanted TEHV showed intact leaflet-structures with well defined cusps without signs of thrombus-formation or structural-damage. Histology and ECM analysis displayed a high cellularity indicative for an early cellular-remodelling and in-growth after 2weeks. For the first time, we demonstrate the principal feasibility of a transcatheter, stem cell-based TEHV implantation into the aortic-valve position within a one-step intervention. Its long term functionality proven, a stem cell-based TEHV approach may represent a next generation heart-valve concept extending the clinical indication of transcatheter valves beyond elderly high-risk patients.
Predictive Analysis of Heart Disease using Stochastic Gradient Boosting along with Recursive Feature Elimination

: Coronary heart disease (CHD) is an illness in which plaque constructs up inside the coronary arteries.CHD descriptions for over 15.9% of all deaths creates it the most regular origin of death globally. Health professionals are facing tough to anticipate the heart alignment as it is capable of medical practitioners that require experience and knowledge. Over the past few years machine learning has proved to be a very successful tool in clinical diagnosis which take up the huge amount of data. This contains hidden information that can be used effectively in making informed decisions. The investigation such type of data utilizes maximum time in terms of execution and utilization of resources. Data features do not support for the outcomes. Therefore, it is especially significant to recognize the features that add further in recognizing diseases. The aim of this work is to predicting the heart disease stage level of a patient by employ machine learning algorithms. In this regard we used the stochastic gradient boosting algorithm along with Recursive Feature Elimination (RFE) for selecting the best features in the data.
On the consistency between global and regional methane emissions inferred from SCIAMACHY, TANSO-FTS, IASI and surface measurements

Abstract. Satellite retrievals of methane weighted atmospheric columns are assimilated within a Bayesian inversion system to infer the global and regional methane emissions and sinks for the period August 2009 to July 2010. Inversions are independently computed from three different space-borne observing systems and one surface observing system under several hypotheses for prior-flux and observation errors. Posterior methane emissions are compared and evaluated against surface mole fraction observations via a chemistry-transport model. Apart from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY), the simulations agree fairly well with the surface mole fractions. The most consistent configurations of this study using TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer), IASI (Infrared Atmospheric Sounding Interferometer) or surface measurements induce posterior methane global emissions of, respectively, 565 ± 21 Tg yr−1, 549 ± 36 Tg yr−1 and 538 ± 15 Tg yr−1 over the one-year period August 2009–July 2010. This consistency between the satellite retrievals (apart from SCIAMACHY) and independent surface measurements is promising for future improvement of CH4 emission estimates by atmospheric inversions.
Revisiting Kazdin (1980): Contemporary Treatment Acceptability for Problem Behavior in Children

Treatment acceptability may influence whether effective interventions can be disseminated successfully. The current study was designed to assess contemporary acceptability of four treatments for problem behavior in children. Comparisons were made between gender of the respondents and between a group of students and a group of Board Certified Behavior Analysts to evaluate some variables that might influence treatment acceptability. In a replication of Kazdin's (1980) study, an on-line survey was used to evaluate levels of acceptability for four treatments (time out, electric shock, reinforcement, and drug) for two children's problem behavior described in brief vignettes. Treatment acceptability was compared as a function of the case, the participant's gender, and the participant's status as a Board Certified Behavior Analyst (BCBA). Reinforcement was rated most acceptable, followed by time out, drug, and shock. An ANOVA revealed a significant treatment by child interaction. Differences between male and female participants and between certified behavior analysts and untrained individuals were also observed. The findings suggest that treatments vary in acceptability and that variables related to the case and clinician can influence acceptability levels.
Thermoelectric properties of n-type nanocrystalline bismuth-telluride-based thin films deposited by flash evaporation

The thermal conductivity of n-type nanocrystalline bismuth-telluride-based thin films (Bi2.0Te2.7Se0.3) is investigated by a differential 3ω method at room temperature. The nanocrystalline thin films are grown on a glass substrate by a flash evaporation method, followed by hydrogen annealing at 250 °C. The structure of the thin films is studied by means of atomic force microscopy, x-ray diffraction, and energy-dispersive x-ray spectroscopy. The thin films exhibit an average grain size of 60 nm and a cross-plane thermal conductivity of 0.8 W∕m K. The in-plane electrical conductivity and in-plane Seebeck coefficient are also investigated. Assuming that the in-plane thermal conductivity of the thin films is identical to that of the cross-plane direction, the in-plane figure of merit of the thin films is estimated to be ZT=0.7. As compared with a sintered bulk sample with average grain size of 30 μm and nearly the same composition as the thin films, the nanocrystalline thin films show approximately a 50% redu.
Optimal Estimation when the Parameter Space is of Infinite Dimension

Many classical nonparametric estimation problems (density estimation, nonparametric estimation of a regression function, estimation of the spectrum of a stationary process) can be reduced to the estimation of an infinite dimensional parameter vector. Typical examples are the representation of a function by a series (Fourier,.), or the estimation of a spectrum by a very long, (possibly infinite) autoregressive process. We adapt concepts of the classical Hajek-Blackwell-LeCam theory to develop a theory of asymptotically optimal estimation of the parameter in our case. Maximum likelihood estimators do not exist in most of the cases, so we have no “canonical” candidate for a “best” estimator. We define suitable loss functions for the estimation error, which allow us to uniquely characterize some estimators. When estimating functions, it is quite common to assume higher order differentiability or some other smoothness conditions. We construct some simple prior distributions for the parameter which force the parameter to obey said smoothness condition. Our results show that certain estimators are asymptotically efficient. We analyze estimators constructed as a function of “sieve estimators”. A sieve estimator is constructed by choosing a number say m (which increases to infinity, just as the sample size increases) and then simply estimate the first m parameters by setting all the other parameters to zero. We show that estimators of the following type are asymptotically optimal :1. “Shrunken sieve estimators”: The estimator is constructed by “shrinking” the sieve estimator (i.e. multiplying with matrix which makes it smaller analogous to Ridge estimators or Bayesian estimators in linear models. 2. The sieve estimator, whose length is determined by AIC, BIC: The variance of the prior distribution of the components of the parameter converge to zero exponentially. 3. If the
Detecting Anomalous Signals from GPS Satellites

Abstract: The international civil aviation community is developing two systems to augment the global navigation satellite services (GNSS). With such augmentation, GNSS will serve as the primary means of air navigation. Both augmentations include ground networks of reference receivers and a data link to the aircraft. The first system is called a local area augmentation system (LAAS), and it places reference receivers at a single airport and uses a VHF data link to communicate with aircraft approaching that airport. Each LAAS serves aircraft within 40 miles of the instrumented airport and the intrinsic capability of the system includes all categories of precision approach including auto-land. Wide area augmentation systems (WAAS) deploy reference networks that span continents and use geostationary satellites to communicate with the aircraft. They support enroute flight across continental areas, terminal area operations, and provide vertical guidance for approaching aircraft.
Vibrational Spectra ( FTIR , FT-Raman and NMR ) of 1 , 5-Difluoro-2 , 4-dinitrobenzene based on Density Functional Calculations

The experimental and theoretical study on the structures and vibrations of 1,5-Difluoro-2,4-dinitrobenzene (DFDNB) is analyzed. The Fourier transform infrared (FT-IR) spectrum (4000–400 cm) and the Fourier transform Raman (FT-Raman) spectrum (3500–100 cm−1) of the title molecule have been recorded. The complete assignments were performed on the basis of the potential energy distribution (PED) of the vibrational modes calculated with scaled quantum mechanical (SQM) method. The molecular structures and vibrational frequencies, infrared intensities and Raman scattering actives have been calculated. 13C and 1H NMR chemical shifts results were also compared with the experimental values.
The Effect of Replacing Inorganic With Organic Trace Minerals in Broiler Diets on Productive Performance and Mineral Excretion

SUMMARY In an experiment with 2,040 Ross 308 broiler chickens, the effect of substituting inorganic with organic minerals in broiler feed on performance was determined. The experiment comprised 2 dietary treatments, with 6 replicates of 170 mixed-sex broiler chickens per pen replicate. Experimental diets consisted of a control treatment, formulated with inorganic Mn, Zn, Fe, and Cu sulfates at levels of 70, 37, 45, and 12 ppm, respectively, and an organic mineral diet supplemented with lower levels of Mn, Zn, Fe (all 10 ppm), and Cu (2.5 ppm) supplied as peptide chelates (Bioplex). Production performance was measured during the 39-d trial period, and mineral excretion was evaluated at 26 d of age. In the starter period (0 to 14 d), FCR tended to improve (P = 0.06) in broilers fed the organic mineral diet. However, no significant differences were observed in any of the productive performance parameters measured during the trial. Significantly lower (P < 0.05) excretion rates were recorded for all minerals in fecal samples taken from broilers receiving the organic mineral diet. Fecal levels of Mn, Zn, Fe, and Cu were 46, 63, 73, and 55%, respectively, compared to the controls.
Evaluation of Lumbar Disk Herniation Risk Factors in Patients with Low Back Pain

ORIGINAL ARTICLE Low back pain (LBP) due to lumbar disk herniation could collaborate with various risk factors. In this study, we focused on analysis of lumbar disk herniation risk factors in patients with LBP. This comparative cross-sectional study was conducted in Hamedan-western Iran in 2014-2015. Overall, 58 cases with evidence of lumbar disk hernia were classified as a case group and 47 cases without evidence of lumbar disk herniation were classified as a control group. The data collection was performed by using a questionnaire and the statistical analysis was performed by using SPSS software. The analytic results indicated a meaningful correlation between demographic variables as body mass index (BMI) mean, occupation type and lumbar disk hernia (P<0.05). Furthermore, the abdominal circumference and the average heavy load carried by the participants throughout a day had a significant relationship with lumbar disk herniation (P<0.05). There are multiple risk factors for lumbar disk hernia regarding a combination of genetics and acquired characteristics and lifestyle.
Title: Comparison of the Efficacy of Conventional Physical Therapy Modalities and Kinesio Taping Treatments in Shoulder Impingement Syndrome

the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as: Kul A, Ugur M. Comparison of the Efficacy of Conventional Physical Therapy Modalities and Kinesio Taping Treatments in Shoulder Impingement Syndrome. Eurasian J Med 2018; DOI: 10.5152/eurasianjmed.2018. 17421 ©Copyright 2018 by Atatürk University School of Medicine Available online at www.eajm. org DOI: 10.5152/eurasianjmed.2018. 17421