Miracle-dz/UniFAR-FTUs huggingface dataset:
Nest parasitism, promiscuity, and relatedness among wood ducks

Nest parasitism is a common reproductive strategy used by many species of cavity nesting birds. Among these, the wood duck (Aix sponsa) is known to have evolved very specific strategies of when and whom to parasitize that is often based on population and/or environmental queues. Here, we investigated the genetic relationship of two female wood ducks competing over an artificial nesting box in Delaware, including the continued incubation of one female despite the death and body remains of the other female throughout the incubation process. We test whether such an extreme case of nest parasitism can be explained by relatedness, egg lineage composition, or a combination of other factors. To do so, we extracted genomic DNA from blood and tissue of the females, as well as chorioallantoic membranes of all viable and inviable eggs. Subsequently, we assessed relatedness among females and eggs based on hundreds of nuclear loci and the mitochondrial control region. We concluded that (1) the two incubating females were entirely unrelated, (2) the single clutch is in fact represented by a minimum of four unrelated females, and (3) a single female can lay eggs sired by different males. The latter finding is the first direct evidence for successful extra-pair copulation in wood ducks. With decreasing costs and increasing effectiveness, genomic methods have the potential to provide important insights into more complex ecological and evolutionary tactics of such populations.
Hybrid empirical/analytical modeling of guided wave generation by circular piezoceramics

Classical piezoceramic transducer design methods in structural health monitoring based on guided wave propagation rely mostly on the use of the pin-force model, assuming that a piezoelectric actuator can be modelled as a constant shear stress applied at its circumference, whatever the frequency generated. However, the assumptions of this model are only valid for thin piezoelectric elements, weak coupling between the host structure and the transducer, and when the wavelength of the generated guided wave is above the size of the transducer. In order to overcome those limitations, this paper presents an axisymmetric analysis of guided wave generation by a circular piezoceramic, considering the complex shear and normal interfacial stress profiles between the transducer and the host structure. The excitation terms are estimated empirically using a best-fit model and a function derived from measured admittance. The validity of the approach is assessed numerically and experimentally, and the influence of piezoceramic thickness on guided wave generation is accurately modeled for frequencies below the second electro–mechanical resonance frequency.
Performance of vertical up-flow constructed wetlands integrating with microbial fuel cell (VFCW-MFC) treating ammonium in domestic wastewater.

Vertical up-flow constructed wetlands integrating with microbial fuel cell (VFCW-MFC) was evaluated for NH4+-N removal and bioelectricity recovery. The experiments were carried out in lab-scale VFCW-MFC microcosms treating synthetic domestic wastewater under different operational conditions of pH, hydraulic retention time, and mass loading rate. Effects of a wild ornamental grass (Cenchrus setaceus) on treatment performance and voltage output were investigated simultaneously. Experiments demonstrated that the neutral pH of influents favored NH4+-N removal and power generation. Extended retention time improved treatment capacity and power output but likely depending on the substrate availability. COD removal and power output increased, while NH4+-N removal decreased, with the increase of mass loading rates. At the loading rate of 88.31 mg COD/L.day, planted VFCW-MFCs exhibited better NH4+-N treatment performance (36.9%) and higher voltage output (132-143%) than unplanted systems. The presence of plants did not affect COD removal efficiency of VFCW-MFCs (> 95%). Power density varied in the range of 1.26-1.59 mW/m2 in planted microcosms with a maximum CE of 13.6%. The anode layer accounted for a major proportion of NH4+-N removal in VFCW-MFCs. This study implies that NH4+-N in domestic wastewaters with relatively high COD:N ratios can be treated effectively in up-flow CW-MFCs via anaerobic processes, including anammox and heterotrophic denitrifying process. The mass loading rate could be a critical parameter to balance different microbial processes, thus, coincidently determined the potential of power recovery from wastewaters.
Correlations of diffusion tensor imaging and clinical measures with spinal cord cross-sectional area measurements in pediatric spinal cord injury patients

Purpose: The purpose of this work was to employ a semi-automatic method for measuring spinal cord cross-sectional area (SCCSA) and investigate the correlations between diffusion tensor imaging (DTI) metrics and SCCSA for the cervical and thoracic spinal cord for typically developing pediatric subjects and pediatric subject with spinal cord injury. Methods: Ten typically developing (TD) pediatric subjects and ten pediatric subjects with spinal cord injury (SCI) were imaged using a Siemens Verio 3 T MR scanner to acquire DTI and high-resolution anatomic scans covering the cervical and thoracic spinal cord (C1-T12). SCCSA was measured using a semi-automated edge detection algorithm for the entire spinal cord. DTI metrics were obtained from whole cord axial ROIs at each vertebral level. SCCSA measures were compared to DTI metrics by vertebral level throughout the entire cord, and above and below the injury site. Correlation analysis was performed to compare SCCSA, DTI and clinical measures as determined by the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) examination. Results: In subjects with SCI, FA and SCCSA had a positive correlation (r = 0.81, P < 0.01), while RD and SCCSA had a negative correlation (r = −0.68, P = 0.02) for the full spinal cord. FA and SCCSA were correlated above (r = 0.56, P < 0.01) and below (r = 0.54, P < 0.01) the injury site. TD subjects showed negative correlations between AD and SCCSA (r = −0.73, P = 0.01) and RD and SCCSA (r = −0.79, P < 0.01). Conclusion: The ability to quickly and effectively measure SCCSA in subjects with SCI has the potential to allow for a better understanding of the progression of atrophy following a SCI. Correlations between cord cross section and DTI metrics by vertebral level suggest that imaging inferior and superior to lesion may yield useful information for diagnosis and prognosis.
Development and Practical Implementation of a Deep Learning–Based Pipeline for Automated Pre- and Postoperative Glioma Segmentation

The authors show the feasibility and advantages of building a coordinated model with a clinical pipeline for the rapid and accurate deep learning segmentation of both preoperative and postoperative gliomas. The ability of the model to accommodate cases of postoperative glioma is clinically important for follow-up. BACKGROUND AND PURPOSE: Quantitative volumetric segmentation of gliomas has important implications for diagnosis, treatment, and prognosis. We present a deep-learning model that accommodates automated preoperative and postoperative glioma segmentation with a pipeline for clinical implementation. Developed and engineered in concert, the work seeks to accelerate clinical realization of such tools. MATERIALS AND METHODS: A deep learning model, autoencoder regularization–cascaded anisotropic, was developed, trained, and tested fusing key elements of autoencoder regularization with a cascaded anisotropic convolutional neural network. We constructed a dataset consisting of 437 cases with 40 cases reserved as a held-out test and the remainder split 80:20 for training and validation. We performed data augmentation and hyperparameter optimization and used a mean Dice score to evaluate against baseline models. To facilitate clinical adoption, we developed the model with an end-to-end pipeline including routing, preprocessing, and end-user interaction. RESULTS: The autoencoder regularization–cascaded anisotropic model achieved median and mean Dice scores of 0.88/0.83 (SD, 0.09), 0.89/0.84 (SD, 0.08), and 0.81/0.72 (SD, 0.1) for whole-tumor, tumor core/resection cavity, and enhancing tumor subregions, respectively, including both preoperative and postoperative follow-up cases. The overall total processing time per case was ∼10 minutes, including data routing (∼1 minute), preprocessing (∼6 minute), segmentation (∼1–2 minute), and postprocessing (∼1 minute). Implementation challenges were discussed. CONCLUSIONS: We show the feasibility and advantages of building a coordinated model with a clinical pipeline for the rapid and accurate deep learning segmentation of both preoperative and postoperative gliomas. The ability of the model to accommodate cases of postoperative glioma is clinically important for follow-up. An end-to-end approach, such as used here, may lead us toward successful clinical translation of tools for quantitative volume measures for glioma.
The design of a contact-less energy transfer system for a people mover system

This paper describes a contactless power transfer system to provide intervention free battery charging to a specially designed low weight electric vehicle for use in an historic New Zealand national park. The noncontact feature of the ICPT (inductively coupled power transfer) system is significant in that the charging is transparent to the driver. When the driver stops at the loading platform, the charging unit automatically senses the vehicle and begins charging if required. Four charging bays (buried under the ground) are provided allowing opportunity charging throughout the day. This minimises the necessary on-board batteries, and therefore the vehicle weight, while still allowing the vehicles to be operated continuously.
A Comparison of the Curve Number and Green-Ampt Models in an Agricultural Watershed

The curve number and Green-Ampt rainfall-runoff models were compared in the highly agricultural San Joaquin River watershed in California using the Soil and Water Assessment Tool (SWAT). The rainfall-runoff models were left uncalibrated to objectively assess model performances; however, streamflow simulations showed high accuracy compared to observed data caused by the large impact of reservoir releases on streamflow. For daily simulations, the Nash-Sutcliffe model efficiency coefficients were 0.81 for the curve number model and 0.78 for the Green-Ampt model. A Nash-Sutcliffe coefficient of 0.93 was found for both models for the monthly simulations. The Green-Ampt model more accurately predicted large streamflow events than the curve number model, while the curve number model better predicted normal flow events. Both models tended to overpredict streamflow. The average monthly hydrologic components of surface runoff, groundwater flow, lateral soil flow, and the amount of water in the soil column were also compared to quantify the underlying differences between the two rainfall-runoff models. These comparisons yielded equal or comparable average monthly surface runoff values between the two rainfall-runoff models, but higher subsurface flows (lateral soil and groundwater inflows) and soil water volumes for the Green-Ampt model. These results are largely due to the difference in model assumptions, where the curve number model assumes an initial abstraction before surface runoff and the Green-Ampt model assumes surface runoff only when the precipitation rates is greater than the infiltration rate. The selection of the most appropriate rainfall-runoff model should be based on the watershed physical characteristics and the overall goal of the watershed modeling.
Determining the power rating of a multichannel linear amplifier

The demand for increased capacity in cellular and other radio networks has led to the development of more flexible base stations. As a result, the high-level combining of multiple amplifiers, with the stringent frequency planning constraints which this imposes, has been supplanted by a single multichannel linear amplifier in an increasing number of systems. The specification of such systems is a complicated issue, owing to the complex nature of the combined signal which they are required to amplify. The authors present a statistical analysis of the peak envelope power of a multicarrier signal, incorporating a variety of modulation schemes, and show that for a large number of channels, significant savings in the amplifier power rating may be made, resulting in decreased hardware and operating costs for multichannel base stations.
A novel approach of creating sustainable urban planning solutions that optimise the local air quality and environmental equity in Helsinki, Finland: The CouSCOUS study protocol

Background Air pollution is one of the major environmental challenges cities worldwide face today. Planning healthy environments for all future populations, whilst considering the ongoing demand for urbanisation and provisions needed to combat climate change, remains a difficult task. Objective To combine artificial intelligence (AI), atmospheric and social sciences to provide urban planning solutions that optimise local air quality by applying novel methods and taking into consideration population structures and traffic flows. Methods We will use high-resolution spatial data and linked electronic population cohort for Helsinki Metropolitan Area (Finland) to model (a) population dynamics and urban inequality related to air pollution; (b) detailed aerosol dynamics, aerosol and gas-phase chemistry together with detailed flow characteristics; (c) high-resolution traffic flow addressing dynamical changes at the city environment, such as accidents, construction work and unexpected congestion. Finally, we will fuse the information resulting from these models into an optimal city planning model balancing air quality, comfort, accessibility and travelling efficiency.
Large-Scale Validation of Bench-Scale Fire Toxicity Tests

A sizable number of bench-scale fire toxicity tests have been pro posed over the last two decades. To date, no test method has successfully passed through the standards bodies ISO, ASTM, or BSI. The reasons are varied, but a major concern has been that none of the methods were seen to adequately pre dict the behavior of real, large-scale building fires. Such validation efforts have been held back both due to a shortage of good quality data, and because agree ment had not been reached on the criteria for successful validation. NIST has now completed a pilot project to address both of these issues. In this study, sev eral criteria for validation have been put forth. An initial data set has been compared against these criteria, comprising 2 bench-scale methods, 3 test materials, and a single real-scale fire scenario. The project results indicate that the course being pursued is appropriate, and provide illustrative performance data for the two bench-scale methods. The present project was a pilot study; fur ther validation data will have to come from additional test materials and addi tional real-scale fire scenarios being examined. As a result of these studies, a factor-of-3 agreement between bench-scale and real-scale results was estab lished as both useful and practical.
Healthcare Fraud Management using BigData Analytics

Traditional Healthcare Fraud Management analytical solutions are based on enterprise data which is limited in many respects - variety of data, processing speed and analytical algorithms. Since BigData platform can process enterprise as well as social media data with ease, it is prudent to base such a solution on BigData platform. This paper provides one of many approaches to utilize fraud management solution to detect potential frauds. The solution is based on a high volume of historical data, predictive statistical models and social media analytics. It renders its services through client components like apps and web-services
Deployed software analysis

Profiling can offer a valuable characterization of software behavior. The richer the characterization is, the more effective the client analyses are in supporting quality assurance activities. For today’s complex software, however, obtaining a rich characterization with the input provided by in-house test suites is becoming more difficult and expensive. Extending the profiling activity to deployed environments can mitigate this shortcoming by exposing more program behavior reflecting real software usage. To make profiling of deployed software plausible, however, we need to take into consideration that there are fundamental differences between the development and the deployed environments. Deployed environments allow for less overhead, provide less control for engineers to perform profiling adjustments, and generate high volumes of information that may be overwhelming and often irrelevant to the client analyses. These characteristics make existing techniques to support in-house profiling inadequate for deployed environments. In this dissertation, we describe the challenges in performing deployed software profiling and propose deployed software analysis, i.e., a set of analysis techniques that address these challenges and enable cost-effective deployed software profiling. Specifically, we have developed and implemented techniques that can be applied to each of the following stages of deployed software profiling: (1) before the software is deployed to determine effective placements of the instrumentation probes that enable profiling; (2) during deployment to drive the adjustments in profiling activity; and (3) after deployment to efficiently process field data into meaningful and beneficial information. Each proposed analysis technique is evaluated under a variety of deployment settings to understand their efficiency and effectiveness trade-offs, and their impact on the quality of dynamic analyses that consume the profiled field information. The results suggest that the proposed analysis techniques can (1) reduce the profiling cost to satisfy a variety of overhead constraints, (2) retain significantly more of the gain provided by the field information when compared to control techniques, and (3) increase the precision of dynamic analyses’s results by removing noise in field traces.
The RCM9-A unique new instrument for measuring ocean currents and other oceanographic parameters

The RCM 9 measures currents in the sea by use of a small acoustic Doppler sensor. This provides for an instrument with no moving parts, that is easy to install, and resistant to measurement degradation from fouling. In addition to current speed and direction the instrument also measures the temperature, conductivity, pressure and turbidity of the water. The instrument can operate for up to two years, recording all data internally or transferring data in real time by use of cable or acoustic link.
A data-driven manufacturing support system for rubber extrusion lines

A better control of extrusion processes offers clear advantages in the manufacturing of rubber profiles for the automotive industry. This work reports our experience in developing a support system aimed to ease the work of the extruder machinist while improving the quality of the profiles obtained. In order to build the system, an approach based on facts was adopted, following ISO 9000 standard quality principles. The data warehouse service available provided a wealth of information on the conditions of the running processes. The collected data, after being analysed with the appropriate data-mining techniques, allowed us to gain a better understanding of the process and to identify the main causes of variance. In particular, principal components analysis, Sammon projection and several classification techniques were applied for exploratory purposes. Different behaviours could be described for the extrusion process, allowing for the definition of a control strategy and, eventually, the development of a manufacturing support system. The estimates displayed by the system greatly improve the responsiveness of the machinist when the process departs from expected behaviour. The results of using this system in a local factory proved highly satisfactory and encouraging.
Wind Turbine Control for Load Reduction

This article reviews techniques for the control of wind turbines during power production. Pitch control is used primarily to limit power in high winds, but it also has an important effect on structural loads. Particularly as turbines become larger, there is increasing interest in designing controllers to mitigate loads as far as possible. Torque control in variable-speed turbines is used primarily to maximize energy capture below rated wind speed, and to limit the torque above rated, but it can also be used to reduce certain loads. The design of the control algorithms is clearly of prime importance. Additional sensors such as accelerometers and load sensors can also help the controller to achieve its objectives more effectively. By controlling the pitch of each blade independently, it is also possible to achieve important further reductions in loading. It is important to be able to quantify the benefits of any new controller. Although computer simulations are useful, field trials are also vital. The variability of the real wind means that particular care is needed in the design of the trials. Copyright © 2003 John Wiley & Sons, Ltd.
Cyclic combinational circuits

A collection of logic gates forms a combinational circuit if the outputs can be described as Boolean functions of the current input values only. Optimizing combinational circuitry, for instance, by reducing the number of gates (the area) or by reducing the length of the signal paths (the delay), is an overriding concern in the design of digital integrated circuits. The accepted wisdom is that combinational circuits must have acyclic (i.e., loop-free or feed-forward) topologies. In fact, the idea that “combinational” and “acyclic” are synonymous terms is so thoroughly ingrained that many textbooks provide the latter as a definition of the former. And yet simple examples suggest that this is incorrect. In this dissertation, we advocate the design of cyclic combinational circuits (i.e., circuits with loops or feedback paths). We demonstrate that circuits can be optimized effectively for area and for delay by introducing cycles. On the theoretical front, we discuss lower bounds and we show that certain cyclic circuits are one-half the size of the best possible equivalent a cyclic implementations. On the practical front, we describe an efficient approach for analyzing cyclic circuits, and we provide a general framework for synthesizing such circuits. On trials with industry-accepted benchmark circuits, we obtained significant improvements in area and delay in nearly all cases. Based on these results, we suggest that it is time to re-write the definition: combinational might well mean cyclic.
Protection from High Energy Rockfall Impacts Using Terramesh Embankments:Design and Experiences

This paper will demonstrate how the high energy impact embankment system represents an effective solution for rockfall protection that is relatively cost efficient in respect to price and maintenance in comparison with traditional rockfall barriers. The high energy impact embankments are designed to resist multiple impacts with negligible resultant deformation, and therefore, may be placed close to infrastructure. Additionally, this system may also have a vegetated facade to blend in with the surrounding environment.