Miracle-dz/UniFAR-FTUs huggingface dataset:
Fertilization success in Galeolaria caespitosa (Polychaeta serpulidae): gamete characteristics, role of sperm dilution, gamete age, and contact time

Variability in gamete traits and the factors affecting fertilization success were studied in a common gregarious broadcast-spawning serpulid polychaete Galeolaria caespitosa . Variability of egg size and sperm velocity were not related to the adult size. High sperm concentrations (10 7 -10 8 sperm. ml -1 ) were required to achieve fertilization rates of 60-80%. The gamete contact time required to achieve high fertilization rates (70-80%) in G. caespitosa did not exceed 5 minutes of gamete exposure given sufficiently high sperm concentrations. This suggests that attachment of sperm to the egg takes place very rapidly, and a short-term exposure to highly concentrated sperm is a common feature of fertilization ecology of this gregarious species. A sharp decline in fertilization rates at high sperm concentrations usually attributable to polyspermy was not observed. Sperm were motile for up to 6 hours after activation; however, swimming velocity and fertilization success decreased after 2 hours. Eggs of G. caespitosa were fertilizable up to 10 hours after spawning, but the number of embryos resulting from fertilizations by fresh sperm decreased after 2 hours. The gamete traits of G. caespitosa appear to have evolved to enable this sessile organism to reproduce under conditions of high population density and increased risk of polyspermy.
Social Research Methods: Migration in Perspective

Migration specific methodologies for research have not yet emerged in a unified manner; hence, a void in scholarship persists which has resulted in the growing dilemmas in conducting research on migrant populations. The growing attention given to the research that involves migration has not yet been passably translated into corresponding research on the methodological challenges researchers generally handle. Quantitative methods have come under criticism for not providing an in-depth description of a phenomenon. Hence many researchers employ the mixed-method approach. This allows numerical data to be supplemented by qualitative findings and contextual explanations of both researchers and researched. We argue that no way is researching in a normal condition similar to the precarious conditions migrants go through. Due to the vulnerable positions of migrants who are the main population of migration research, it demands special attention in selecting and implementing appropriate methods.
Outcomes of Regular and Special Class Placement for Students with Special Educational Needs – A Quasi-experimental Study

ABSTRACT This study reports on an investigation of the differences in results between students with special educational needs assigned to special classes or regular classes in lower secondary education. Cognitive competencies were measured using curricular Finnish and mathematics tasks, school achievement using grade point average (GPA), and learning motivation by using self-reported goal-orientation scales. Propensity score matching was utilized to match the students according to their propensity to be placed in special classes, and 134 pairs were produced out of 860 available students with SEN from which 477 were assigned to special classes. Results of students assigned to special classes did not differ in curricular Finnish and mathematics in ninth grade when compared to their closely-matched peers in regular classes. However, students in special classes had higher GPAs and a higher performance-approach orientation and mastery-extrinsic orientation than students assigned to regular classes.
Visible–near infrared spectral indices for mapping mineralogy and chemistry with OSIRIS‐REx

The primary objective of the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS‐REx) mission is to return to Earth a pristine sample of carbonaceous material from the primitive asteroid (101955) Bennu. To support compositional mapping of Bennu as part of sample site selection and characterization, we tested 95 spectral indices on visible to near infrared laboratory reflectance data from minerals and carbonaceous meteorites. Our aim was to determine which indices reliably identify spectral features of interest. Most spectral indices had high positive detection rates when applied to spectra of pure, single‐component materials. The meteorite spectra have fewer and weaker absorption features and, as a result, fewer detections with the spectral indices. Indices targeting absorptions at 0.7 and 2.7–3 μm, which are attributable to hydrated minerals, were most successful for the meteorites. Based on these results, we identified a set of 17 indices that are most likely to be useful at Bennu. These indices detect olivines, pyroxenes, carbonates, water/OH‐bearing minerals, serpentines, ferric minerals, and organics. Particle size and albedo are known to affect band depth but had a negligible impact on interpretive success with spectral indices. Preliminary analysis of the disk‐integrated Bennu spectrum with these indices is consistent with expectations given the observed absorption near 3 μm. Our study prioritizes spectral indices to be used for OSIRIS‐REx spectral analysis and mapping and informs the reliability of all index‐derived data products, including a science value map for sample site selection.
ML-SWAN-v1: a hybrid machine learning framework for the
prediction of daily surface water nutrient concentrations

Abstract. Nutrient data from catchments discharging to receiving waters are necessary to monitor and manage water quality, however, they are often sparse in time and space and have non-linear responses to environmental factors, making it difficult to systematically analyse long- and short-term trends and undertake nutrient budgets. To address these challenges, we developed a hybrid machine learning (ML) framework that first separated baseflow and quickflow from total flow, and then generated data for missing nutrient species, using relationships with hydrological data, rainfall, and temporal data. The generated nutrient data were then included as additional variables in a final simulation of tributary water quality. Hybrid random forest (RF) and gradient boosting machines (GBM) models were employed and their performance compared with a linear model, a multivariate weighted regression model and stand-alone RF and GBM models that did not pre-generate nutrient data. The six models were used to predict TN, TP, NH3, dissolved organic carbon (DOC), dissolved organic nitrogen (DON), and filterable reactive phosphorus (FRP) discharged from two study sites in Western Australia: Ellen Brook (small and ephemeral) and the Murray River (large and perennial). Our results showed that the hybrid RF and GBM models had significantly higher accuracy and lower prediction uncertainty for almost all nutrient species across the two sites. We demonstrated that the hybrid model provides a flexible method to combine data of varied resolution and quality, and is accurate for the prediction of responses of surface water nutrient concentrations to hydrologic variability.
Impact of automated writing evaluation on teacher feedback, student revision, and writing improvement

Abstract Recent years have witnessed an increasing interest in the use of automated writing evaluation (AWE) in second language writing classrooms. This increase is partially due to the belief that AWE can assist teachers by allowing them to devote more feedback to higher-level (HL) writing skills, such as content and organization, while the technology addresses lower-level (LL) skills, such as grammar. As is speculated, student revisions will then be positively impacted. However, little evidence has supported these claims, calling into question the impact of AWE on teaching and learning. The current study explored these claims by comparing two second language writing classes that were assigned to either an AWE + teacher feedback condition or a teacher-only-feedback condition. Findings suggest that using AWE as a complement to teacher feedback did not have a significant impact on the amount of HL teacher feedback, but the teacher who did not use AWE tended to provide a greater amount of LL feedback than AWE alone. Furthermore, students seemed to revise the teacher’s LL feedback more frequently than LL feedback from the computer. Interestingly, students retained their improvement in accuracy in the long-term when they had access to AWE, but students who did not have access appeared to have lower retention. We explain the relevance of our findings in relation to an argument-based validation framework to align our work with state-of-the-art research in the field and contribute to a broader discussion about how AWE can be best provided to support second language writing development.
Optimizing Inverse Distance Weighting with Particle Swarm Optimization

Spatial analysis of hydrological data often requires the interpolation of a variable from point samples. Commonly used methods for solving this problem include Inverse Distance Weighting (IDW) and Kriging (KG). IDW is easily extensible, has a competitive computational cost with respect to KG, hence it is usually preferred for this task. This paper proposes the optimization of finding the IDW parameter using a nature-inspired metaheuristic, namely Particle Swarm Optimization (PSO). The performance of the improved algorithm is evaluated in a complex scenario and benchmarked against the KG algorithm for 51 precipitation series from the Dobrogea region (Romania). Apart from facilitating the process of applying IDW, the PSO implementation for Optimizing IDW (OIDW) is computationally lighter than the traditional IDW approach. Compared to Kriging, OIDW is straightforward to be implemented and does not require the difficult process of identification of the most appropriate variogram for the given data.
Imaging techniques for defect detection of fiber reinforced polymer‐bonded civil infrastructures

The present article provides a state‐of‐the‐art review of imaging techniques used for defect detection of fiber reinforced polymer (FRP)‐bonded civil engineering structures. Compared to the conventional techniques by equipping a structure with stress wave sensors, the contactless imaging techniques feature efficient instrumentation, convenient data acquisition, and rapid evaluation in the procedures of nondestructive testing (NDT). Recently, a substantial progress in utilizing electromagnetic waves for development of imaging NDT techniques (e.g., synthetic aperture radar, infrared thermography, laser shearography, and laser reflection technique) with the purpose to identify debonding or delamination of FRP‐bonded structural systems has been made. As another electromagnetic wave‐based imaging technique, X‐ray computed tomography is promising for exploration of the damage evolution in this structural system, despite little application in structural health monitoring of real infrastructures. Apart from these imaging techniques, more recently, there have been computer‐aided motion magnification techniques for defect identification. The motion magnification technique only requires a digital camera and a computer with vision algorithm, which can amplify the motion of defect region and render it visible in a video. This advanced imaging technique achieves high‐resolution measurement, simultaneous full‐field inspection, and straightforward defect identification in the scene. In this review, both Eulerian motion magnification and phase‐based motion magnification techniques for structural visual inspection are presented and discussed. Furthermore, the present article recommends the combination of imaging NDT techniques with artificial intelligence approaches (e.g., deep learning algorithms) to realize the automated and efficient defect detection towards FRP‐bonded civil infrastructures.
Chromosomes: Organization and Function

Preface 1. Why Study Chromosomes? 2. Mitosis, Meiosis And The Cell Cycle 3. DNA, The Genetic Code 4. Assembly Of Chromatin 5. The Chromosomes In Interphase 6. Structure Of Mitotic And Meiotic Chromosomes 7. Constitutive Heterochromatin 8. Sex Chromosomes And Sex Determination 9. Imprinting 10. Euchromatin And The Longitudinal Differentiation Of Chromosomes 11. The Nucleolus And The Nucleolus Organizing Regions (Nors) 12. Centromeres, Kinetochores And The Segregation Of Chromosomes 13. Telomeres 14. Lampbrush Chromosomes 15. Polytene Chromosomes 16. Chromosomes, The Karyotype And Evolution 17. Chromosomes And Disease 18. Chromosome Engineering And Artificial Chromosomes
Automated Detection of Interictal Epileptiform Discharges from Scalp Electroencephalograms by Convolutional Neural Networks

Visual evaluation of electroencephalogram (EEG) for Interictal Epileptiform Discharges (IEDs) as distinctive biomarkers of epilepsy has various limitations, including time-consuming reviews, steep learning curves, interobserver variability, and the need for specialized experts. The development of an automated IED detector is necessary to provide a faster and reliable diagnosis of epilepsy. In this paper, we propose an automated IED detector based on Convolutional Neural Networks (CNNs). We have evaluated the proposed IED detector on a sizable database of 554 scalp EEG recordings (84 epileptic patients and 461 nonepileptic subjects) recorded at Massachusetts General Hospital (MGH), Boston. The proposed CNN IED detector has achieved superior performance in comparison with conventional methods with a mean cross-validation area under the precision-recall curve (AUPRC) of 0.838[Formula: see text]±[Formula: see text]0.040 and false detection rate of 0.2[Formula: see text]±[Formula: see text]0.11 per minute for a sensitivity of 80%. We demonstrated the proposed system to be noninferior to 30 neurologists on a dataset from the Medical University of South Carolina (MUSC). Further, we clinically validated the system at National University Hospital (NUH), Singapore, with an agreement accuracy of 81.41% with a clinical expert. Moreover, the proposed system can be applied to EEG recordings with any arbitrary number of channels.
Seasonal incidence of defoliators in urd bean (Vigna mungo L. Hepper) and their correlation with meteorological parameters.

Accepted : May, 2010 Black gram [Vigna mungo (L) Hepper] is an important pulse crop. Among the major problems known to limit the yield of this pulse, incidence of insect pests are the main constrains. It has been reported that 18 species of insect pests infest on urd bean (Lal et al., 1980). Out of these, five insect pests viz., Spodoptera litura Fab. Madurasia Obscurella Jac. , Empoasca kerri Pruthi, Aphis craccivora Koch; Spilarctia obliqua Walk. and Euchrysops cnejus Fab. have been recorded as the major pests on urd bean (Kumar et al., 1998). Keeping this in view, the present study was undertaken to know the seasonal incidence of defoliators in urd bean and their correlation with meteorological parameters.
The Short-Term and Long-Term Hazard Ratio Model: Parameterization Inconsistency

Abstract The test of Yang and Prentice, based on the short-term and long-term hazard ratio model for the presence of a regression effect appears to be an attractive one, being able to detect departures from a null hypothesis of no effect against quite broad alternatives. We recall the model on which this test is based and the test itself. In simulations, the test has shown good performance and is judged to be of potential value when alternatives to the null may be of a nonproportional hazards nature. However, the model, even when valid, suffers from a parameterization inconsistency in the sense that parameter estimates can violate the model’s assumed parametric structure even when true. This leads to awkward behavior in some situations. For example, this inconsistency implies that inference will not be invariant to the coding of treatment allocation. While this is a theoretical observation, we provide real examples that highlight the difficulty in making clear cut inferences from the model. Potential solutions are available and we provide some discussion on this.
Measuring high orbital angular momentum of vortex beams with an improved multipoint interferometer

A multipoint interferometer (MI), uniformly distributed point-like pinholes in a circle, was proposed to measure the orbital angular momentum (OAM) of vortex beams [Phys. Rev. Lett.101, 100801 (2008)PRLTAO0031-900710.1103/PhysRevLett.101. 100801], which can be used for measuring OAM of light from astronomical sources. This is a simple and robust method; however, it is noted that this method is only available for low topological charge because the diffracted intensity patterns for vortex beams with higher OAM will repeat periodically. Here, we propose an improved multipoint interferometer (IMI) for measuring the OAM of an optical vortex with high topological charge. The structure of our IMI is almost the same as the MI, but the size of each pinhole is larger than a point in the MI. Such a small change enables each pinhole to get more phase information from the incident beams; accordingly, the IMI can distinguish any vortex beams with different OAM. We demonstrate its viability both theoretically and experimentally.
Ten Legal Lessons for Special Educators

ABSTRACT The purpose of this article is to provide special educators with significant and perhaps surprising recent lessons in special education law. These lessons under the Individuals with Disabilities Education Act and Section 504 of the Rehabilitation Act range from the threshold issues of child find and eligibility through the central obligation of free and appropriate public education in the least restrictive environments to specialized issues, such as discipline and the statute of limitations. The conclusion emphasizes that legal requirements in special education are often not absolute and constitute a bottom boundary, different from the generally advisable guiding norm of best practice.
Oxidative Bio-Desulfurization by Nanostructured Peroxidase Mediator System

Bio-desulfurization is an efficient technology for removing recalcitrant sulfur derivatives from liquid fuel oil in environmentally friendly experimental conditions. In this context, the development of heterogeneous bio-nanocatalysts is of great relevance to improve the performance of the process. Here we report that lignin nanoparticles functionalized with concanavalin A are a renewable and efficient platform for the layer-by-layer immobilization of horseradish peroxidase. The novel bio-nanocatalysts were applied for the oxidation of dibenzothiophene as a well-recognized model of the recalcitrant sulfur derivative. The reactions were performed with hydrogen peroxide as a green primary oxidant in the biphasic system PBS/n-hexane at 45 °C and room pressure, the highest conversion of the substrate occurring in the presence of cationic polyelectrolyte layer and hydroxy-benzotriazole as a low molecular weight redox mediator. The catalytic activity was retained for more transformations highlighting the beneficial effect of the support in the reusability of the heterogeneous system.
Comparisons of arthropod and avian communities in insecticide-treated and untreated hemlock stands in Great Smoky Mountains National Park

Great Smoky Mountains National Park is using systemic imidacloprid in Hemlock Conservation Areas to treat eastern hemlocks (Tsuga canadensis) infested with hemlock woolly adelgid (Adelges tsugae, HWA). The purpose of this study was to investigate the effects of systemic imidacloprid treatments on the insectivorous bird community and on the hemlock canopy arthropod community in the context of food availability for insectivores. Territory mapping of three hemlock-associated Neotropical migratory foliage-gleaning bird species was conducted in six pairs of treated and untreated hemlock study sites. Relationships between bird territory density and hemlock foliar density were also examined. Canopy arthropods were sampled in these paired sites by clipping mid-canopy hemlock branches. Arthropods were identified to order except Hemiptera to suborder. Arthropods were further categorized into focal bird prey guilds and non-target herbivorous insect guilds. Focal bird densities did not differ between treated and untreated sites but were positively related to branch foliage mass, implying a preference in these birds for well-foliated hemlocks. There was no difference in HWA infestation between treated and untreated sites, indicating that treated hemlock trees were not sampled at peak efficacy of imidacloprid treatments. Over 900 non-HWA arthropods from 16 orders were collected. There were no differences in richness, abundance, composition, or density between treated and untreated sites for total arthropods or for the two focal bird prey guilds arthropods = 3 mm and larvae = 3 mm, revealing little impact on the overall arthropod crop from imidacloprid treatments. However, non-target herbivorous Hemiptera and larval Lepidoptera were significantly reduced in treated hemlocks. Although larval Lepidoptera are primary prey for focal birds, lack of differences in bird densities suggests the birds are finding other food resources in these mixed hemlock-deciduous stands. Results of this study indicate that controlling HWA-induced defoliation through use of imidacloprid may in the short term benefit hemlock-associated birds. However, while imidacloprid treatments did not appear to affect most non-target arthropods, guilds of non-target herbivorous insects should be monitored for long-term declines.
The metabolic and functional consequences of hyperammonaemia

Ammonia is an essential intermediate of a number of metabolic pathways in the body, from the maintenance of normal brain function, efficient immune response, to the production of energy within muscle cells to maintain contraction during exercise. However, ammonia levels must be carefully maintained within a low concentration range (no greater than 50-100μmol/L), or toxicity may develop. Excess ammonia, also known as hyperammonaemia, has been linked to the development of neurological dysfunction in liver disease states and certain in-born genetic metabolic defects (e.g. urea cycle enzyme deficiencies), whilst it is also believed to impair the regulation of protein metabolism in a number of tissues.
Bionutritional efficiency of crossbred beef cattle finished on feedlot andslaughtered at different body weights

The objective of this study was to assess the bionutritional efficiency of crossbred F1 Red Angus × Nellore (½ RA ½ N) and F1 Blonde D'Aquitaine × Nellore (½ BA ½ N) young bulls finished on feedlot and slaughtered at 480, 520 and 560 kg body weight. A completely randomized experimental design in a 2 × 3 (genetic group × slaughter weight) factorial arrangement with six replicates was used. The ½ BA ½ N young bulls showed higher kidney, pelvic and inguinal fat (KPIF, kg and % BW) and lower multivariate biological nutritional index (MBNI) and residual feed intake than ½ RA ½ N young bulls. The young bulls slaughtered at heavier weight had larger ribeye area (cm2), fat thickness over the 12-13th rib, fat thickness over the rump, KPIF (kg and % BW), dry matter intake (DMI, kg/d), net energy intake (MJ/d) and metabolizable protein intake (g/d), and MBNI compared to young bulls slaughtered at lighter weight. Furthermore, the ½ BA ½ N young bulls slaughtered at 480 kg had lower feed conversion than the others. On the other hand, the average daily weight gain (kg/d), DMI (% BW and g/BW0.75), feed efficiency and Kleiber ratio did not differ between genetic group, slaughter weight and genetic group versus slaughter weight interaction. Therefore, crossbred F1 Blonde D'Aquitaine × Nellore young bulls and animals slaughtered at lighter weights are more bionutritionally efficient in the finishing phase on feedlot.