Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioassessment Tools for Stony Corals: Field Testing of Monitoring Protocols in the US Virgin Islands (St. Croix)

SUMMARY The goal of this study was to field test data collection and analysis protocols for stony coral assemblages. From this study the most biologically meaningful and statistically precise methods will be selected for inclusion in a long-term reef monitoring program for the US Virgin Islands (USVI). Coral reef condition was measured at 61 reef stations in St. Croix, USVI during 2006. Three observations for stony corals were recorded: species, size, and percent live tissue. Stony corals were selected because they are primary producers of the reef environment, they provide structure and habitat for other reef organisms, and they support tourism and fisheries. Dive teams from the US Environmental Protection Agency and the USVI Division of Environmental Protection (DEP) collected physical measurements and recorded the condition of coral colonies found within a radial belt transect. Different dive teams sampling the same reef station reported very similar values indicating that the field protocol had good precision and low measurement error associated with coral measurements. Indicators of coral condition were tested against a gradient of human disturbance at three locations. Candidate metrics for assessing coral condition were derived from four categories: species abundance and composition, physical stature, biological condition, and coral community structure. Human disturbance gradients were based on visual observations and narrative descriptions of land use on shore. No quantitative or chemical measures of water quality were collected. For the most intensely disturbed area, four metrics were highly correlated with distance from an industrial point source: total surface area of coral, total live surface area, taxa richness, and average colony size. For the other two gradients, changes in indicator values were not associated with human influence, possibly because disturbance in these areas was minimal or because indicators tested here were not be capable of detecting subtle differences in reef condition. Many metrics were highly correlated with depth, even when the range was only 20–40 ft. A statistical power analysis determined that a survey area of 50 m 2 was no more precise than a survey area half that size. Coral metrics derived from this protocol had adequate precision to detect a reasonable level of change in coral reef condition that would be protective of the resource.
A Controlled Comparison of Errorless and Errorful Learning in Individuals with Moderate-to-Severe Traumatic Brain Injury

A Controlled Comparison of Errorless and Errorful Learning in Individuals with Moderate-to-Severe Traumatic Brain Injury Joseph Edward Fair Department of Psychology, BYU Doctor of Philosophy The prevalence and sequelae of moderate-to-severe (M/S) traumatic brain injury (TBI) are significant and pervasive problems, and effective rehabilitation techniques are key. Errorless learning is regarded as a useful tool for memory impairments; however, the efficacy of errorless learning in a M/S TBI population is unclear. The primary goal (aim 1) of this study was to evaluate the efficacy of a single session of errorless vs. errorful learning in a group of M/S TBI survivors and matched controls. A secondary goal (aim 2) was to investigate the neural time course of errorless learning in participants with M/S TBI by analyzing the error-related negativity (ERN) component of the scalp-recorded event-related potential (ERP). The ERN is an electrophysiological measure of error processing that is disrupted in M/S TBI survivors. Measures of neuropsychological performance, selfand informant-report of executive functioning, and affect further informed both study aims. Data from 28 M/S TBI survivors (9 female) and 28 controls (9 female) were analyzed for aim 1, with data from 19 M/S TBI survivors (6 female) and 20 controls (8 female) analyzed for aim 2. There were significant differences between the TBI and control groups with regard to executive, mood, and neuropsychological functioning. Results from aim 1 indicated that TBI participants were slower across learning conditions, while both groups had significantly faster reaction times in the errorless condition. Regarding accuracy, there was not a statistically significant main effect of learning condition (p = .07), group (p = .06), or Group x Condition x Accuracy interaction (p = .33). Indices of memory and executive functioning, and group (TBI, Control) used in regressions predicted accuracy in both learning conditions (ps .22). ERN latency was not predictive of accuracy for either condition (ps > .08). Group was a significant independent predictor of accuracy in the errorless condition (p = .05), but not the errorful condition (p = .45). Findings indicate that memory functioning was a better predictor of accuracy than executive functioning or group membership. This suggests that the errorless learning benefit may be specific to memory functioning, rather than other cognitive variables. This conclusion aligns with research reporting that benefits of errorless learning depend upon the severity of memory impairments. Results from ERN analyses are only partially supported by previous research, and further work is needed to clarify the role of neural representations of errorless learning in M/S TBI.
Exchange Rates and Fundamentals: Footloose or Evolving Relationship?

Using novel real-time data on a broad set of economic fundamentals for five major US dollar exchange rates over the recent float, we employ a predictive procedure that allows the relationship between exchange rates and fundamentals to evolve over time in a very general fashion. Our key findings are that: (i) the well-documented weak out-of-sample predictive ability of exchange rate models may be caused by poor performance of model-selection criteria, rather than lack of information content in the fundamentals; (ii) the difficulty of selecting the best predictive model is largely due to frequent shifts in the set of fundamentals driving exchange rates, which can be interpreted as reflecting swings in market expectations over time. However, the strength of the link between exchange rates and fundamentals is different across currencies.
Autonomous pallet localization and picking for industrial forklifts: a robust range and look method

A combined double-sensor architecture, laser and camera, and a new algorithm named RLPF are presented as a solution to the problem of identifying and localizing a pallet, the position and angle of which are a priori known with large uncertainty. Solving this task for autonomous robot forklifts is of great value for logistics industry. The state-of-the-art is described to show how our approach overcomes the limitations of using either laser ranging or vision. An extensive experimental campaign and uncertainty analysis are presented. For the docking task, new dynamic nonlinear path planning which takes into account vehicle dynamics is proposed.
Field Metabolic Rate Is Dependent on Time-Activity Budget in Ring-Billed Gulls (Larus delawarensis) Breeding in an Anthropogenic Environment

Environmental and behavioral factors have long been assumed to affect variation in avian field metabolic rate (FMR). However, due to the difficulties in measuring continuous behavior of birds over prolonged periods of time, complete time-activity budgets have rarely been examined in relation to FMR. Our objective was to determine the effect of activity (measured by detailed time-activity budgets) and a series of extrinsic and intrinsic factors on FMR of the omnivorous ring-billed gull (Larus delawarensis). The experiment was conducted during the incubation period when both members of the pair alternate between attending the nest-site and leaving the colony to forage in aquatic and anthropogenic environments (city, agricultural). FMR was determined using the doubly labeled water method. Time-activity budgets were extrapolated from spatio-temporal data (2-5 days) obtained from bird-borne GPS data loggers. Gulls had low FMRs compared to those predicted by allometric equations based on recorded FMRs from several seabird species. Gulls proportioned their time mainly to nest-site attendance (71% of total tracking time), which reduced FMR/g body mass, and was the best variable explaining energy expenditure. The next best variable was the duration of foraging trips, which increased FMR/g; FMR/g was also elevated by the proportion of time spent foraging or flying (17% and 8% of tracking time respectively). Most environmental variables measured did not impact FMR/g, however, the percent of time birds were subjected to temperatures below their lower critical temperature increased FMR. Time-activity budgets varied between the sexes, and with temperature and capture date suggesting that these variables indirectly affected FMR/g. The gulls foraged preferentially in anthropogenic-related habitats, which may have contributed to their low FMR/g due to the high availability of protein- and lipid-rich foods. This study demonstrates that activities were the best predictors of FMR/g in ring-billed gulls, thus providing strong support for this long-standing theory in bioenergetics.
Effects of communication on the performance of nursing students during the simulation of an emergency situation.

AIM To explore how nursing performance is impacted by different forms of team communication including a message transmitted through an earpiece which triggers reflective thinking in the simulation of a deteriorating patient situation. BACKGROUND Communication can either support team performance or produce interruptions potentially leading to error. Today, technology offers the opportunity to use devices that can permit communication. DESIGN An experimental protocol was used with quantitative and qualitative analyses. METHODS Pairs of nursing students (N = 26) were dispatched to either an experimental group having to wear an earpiece priming reflective thinking, or to a control group. The study was conducted between October 2013-April 2014. RESULTS The number of spontaneous information exchanges between pairs of participants was positively correlated with overall performance (actions performed and physician call) and with actions performed at the right moment. The number of questions in the team was positively correlated with overall action performance. No quantitative effect of the earpiece message on the performance indicators was found. But, a qualitative observation showed that this message can allow for error avoidance. Subjective evaluation of the earpiece as an aid was negatively correlated with overall action performance. Its evaluation as a disturbance was also negatively correlated with the measurement of actions performed at the right moment. CONCLUSION The ability to exchange information and to ask questions seems to contribute to performance in care delivery. The use of communication devices to trigger reflective thinking must be studied in more depth to assess their capacity to improve performance.
Beheading hydras: performing effective botnet takedowns

Devices infected with malicious software typically form botnet armies under the influence of one or more command and control (C&C) servers. The botnet problem reached such levels where federal law enforcement agencies have to step in and take actions against botnets by disrupting (or "taking down") their C&Cs, and thus their illicit operations. Lately, more and more private companies have started to independently take action against botnet armies, primarily focusing on their DNS-based C&Cs. While well-intentioned, their C&C takedown methodology is in most cases ad-hoc, and limited by the breadth of knowledge available around the malware that facilitates the botnet. With this paper, we aim to bring order, measure, and reason to the botnet takedown problem. We propose a takedown analysis and recommendation system, called rza, that allows researchers to perform two tasks: 1) a postmortem analysis of past botnet takedowns, and 2) provide recommendations on how to successfully execute future botnet takedowns. As part of our system evaluation, we perform a postmortem analysis of the recent Kelihos, Zeus and 3322.org takedowns. We show that while some of these takedowns were effective, others did not appear to have a significant long-term impact on the targeted botnet. In addition to the postmortem analysis, we provide takedown recommendation metrics for 45 currently active botnets, where we find that 42 of them can likely be disabled entirely by using a DNS-based takedown strategy only.
Multiscale Centerline Detection by Learning a Scale-Space Distance Transform

We propose a robust and accurate method to extract the centerlines and scale of tubular structures in 2D images and 3D volumes. Existing techniques rely either on filters designed to respond to ideal cylindrical structures, which lose accuracy when the linear structures become very irregular, or on classification, which is inaccurate because locations on centerlines and locations immediately next to them are extremely difficult to distinguish. We solve this problem by reformulating centerline detection in terms of a regression problem. We first train regressors to return the distances to the closest centerline in scale-space, and we apply them to the input images or volumes. The centerlines and the corresponding scale then correspond to the regressors local maxima, which can be easily identified. We show that our method outperforms state-of-the-art techniques for various 2D and 3D datasets.
Liver Dysfunction Assessed by Model for End-Stage Liver Disease Excluding INR (MELD-XI) Scoring System Predicts Adverse Prognosis in Heart Failure

Aims Liver dysfunction due to heart failure (HF) is often referred to as cardiac or congestive hepatopathy. The composite Model for End-Stage Liver Disease excluding INR (MELD-XI) is a robust scoring system of liver function, and a high score is associated with poor prognosis in advanced HF patients with a heart transplantation and/or ventricular assist device. However, the impact of MELD-XI on the prognosis of HF patients in general remains unclear. Methods and Results We retrospectively analyzed 562 patients who were admitted to our hospital for the treatment of decompensated HF. A MELD-XI score was graded, and patients were divided into two groups based on the median value of MELD-XI score: Group L (MELD-XI <10, n = 289) and Group H (MELD-XI ≥10, n = 273). We compared all-cause mortality and echocardiographic findings between the two groups. In the follow-up period (mean 471 days), 104 deaths (62 cardiac deaths and 42 non-cardiac deaths) were observed. The event (cardiac death, non-cardiac death, all-cause death)-free rate was significantly higher in group L than in group H (logrank P<0.05, respectively). In the Cox proportional hazard analysis, a high MELD-XI score was found to be an independent predictor of cardiac deaths and all-cause mortality in HF patients. Regarding echocardiographic parameters, right atrial and ventricular areas, inferior vena cava diameter, and systolic pulmonary artery pressure were higher in group H than in group L (P<0.05, respectively). Conclusions The MELD-XI scoring system, a marker of liver function, can identify high-risk patients with right heart volume overload, higher pulmonary arterial pressure and multiple organ failure associated with HF.
The formation of a disk galaxy within a growing dark halo

We present a dynamical model for the formation and evolution of a massive disk galaxy, within a growing dark halo whose mass evolves according to cosmological simulations of structure formation. The galactic evolution is simulated with a new three-dimensional chemo-dynamical code, including dark matter, stars and a multi-phase ISM. The simulations start at redshift z = 4.85 with a small dark halo in a ΛCDM universe and we follow the evolution until the present epoch. The energy release by massive stars and supernovae prevents a rapid collapse of the baryonic matter and delays the maximum star formation until redshift z ≈ 1. The metal enrichment history in this model is broadly consistent with the evolution of (Zn/H) in damped Lyα systems. The galaxy forms radially from inside-out and vertically from halo to disk. As a function of metallicity, we have described a sequence of populations, reminiscent of the extreme halo, inner halo, metal-poor thick disk, thick disk, thin disk and inner bulge in the Milky Way. The first galactic component that forms is the halo, followed by the bulge, the disk-halo transition region, and the disk. At redshift z ≈ 1, a bar begins to form which later turns into a triaxial bulge. Despite the still idealized model, the final galaxy resembles present-day disk galaxies in many aspects. The bulge in the model consists of at least two stellar subpopulations, an early collapse population and a population that formed later in the bar. The initial metallicity gradients in the disk are later smoothed out by large scale gas motions induced by the bar. There is a pronounced deficiency of low-metallicity disk stars due to pre-enrichment of the disk ISM with metal-rich gas from the bulge and inner disk ("G-dwarf problem"). The mean rotation and the distribution of orbital eccentricities for all stars as a function of metallicity are not very different from those observed in the solar neighbourhood, showing that early homogeneous collapse models are oversimplified. The approach presented here provides a detailed description of the formation and evolution of an isolated disk galaxy in a ΛCDM universe, yielding new information about the kinematical and chemical history of the stars and the interstellar medium, but also about the evolution of the luminosity, the colours and the morphology of disk galaxies with redshift.
Research on speed-control of BLDCM based on intelligent control algorithm

The paper design a speed-control system of BLDCM by using the parameter self-tuning fuzzy PID control and single neuron adaptive PID control algorithm. Through simulation of double close-loop speed-control system to BLDCM model by using Simulink in MATLAB, we can synthesize the results that the rotational speed is non-overshoot, and high steady precision under single neuron adaptive PID
Quality Ranking of Features in Software Product Line Engineering

Software Product Line Engineering (SPLE) is a systematic software reuse approach that developing a set of similar software products as a family. All the visible characters of the products in a product family are represented as features and their relationships are modelled in a feature model. During application engineering, desired features are selected from the feature model in a configuration process based on the requirements. In this process, the quality of final product should be considered as early as possible which requires identifying and ranking associated features' contributions to related quality attributes before configuring member products. In this paper, we propose a ranking approach to address the issues in current quality based feature ranking approaches, we also include a case study to illustrate our approach at the end.
Analyzing Margins in Boosting

While the success of boosting or voting methods has been evident from experimental data [11], questions about why boosting does not overfit on training data remain. One idea about the effectiveness of boosting was given by Schapire et al. in which they presented an explanation of why the test error of a boosting classifier does not increase with its size by looking at margins. They showed that boosting increases the margins of training examples effectively and that this increase in margins is related to the auspicious performance of AdaBoost [12]. Breiman invented ArcGv, an algorithm that increases margins even more aggressively than AdaBoost, yet does not perform better. He claimed this contradicts Schapire’s margins explanation, since all else being equal a higher margins distribution did not in this case indicate better results [1]. In this paper, we experimentally examine Breiman’s results by comparing the margins and performance of AdaBoost and ArcGv. We also analyze our approaches and show that our results partially contradict Breiman’s findings. We also explore some other voting algorithms’ performance and present some studies only indirectly related to this problem. We also present possibilities for further research and experimentation in this area, which it is our intention to continue pursuing.
Cellular reprogramming through mitogen-activated protein kinases

Mitogen-activated protein kinase (MAPK) cascades are conserved eukaryote signaling modules where MAPKs, as the final kinases in the cascade, phosphorylate protein substrates to regulate cellular processes. While some progress in the identification of MAPK substrates has been made in plants, the knowledge on the spectrum of substrates and their mechanistic action is still fragmentary. In this focused review, we discuss the biological implications of the data in our original paper (Sustained mitogen-activated protein kinase activation reprograms defense metabolism and phosphoprotein profile in Arabidopsis thaliana; Frontiers in Plant Science 5: 554) in the context of related research. In our work, we mimicked in vivo activation of two stress-activated MAPKs, MPK3 and MPK6, through transgenic manipulation of Arabidopsis thaliana and used phosphoproteomics analysis to identify potential novel MAPK substrates. Here, we plotted the identified putative MAPK substrates (and downstream phosphoproteins) as a global protein clustering network. Based on a highly stringent selection confidence level, the core networks highlighted a MAPK-induced cellular reprogramming at multiple levels of gene and protein expression—including transcriptional, post-transcriptional, translational, post-translational (such as protein modification, folding, and degradation) steps, and also protein re-compartmentalization. Additionally, the increase in putative substrates/phosphoproteins of energy metabolism and various secondary metabolite biosynthesis pathways coincides with the observed accumulation of defense antimicrobial substances as detected by metabolome analysis. Furthermore, detection of protein networks in phospholipid or redox elements suggests activation of downstream signaling events. Taken in context with other studies, MAPKs are key regulators that reprogram cellular events to orchestrate defense signaling in eukaryotes.
Software-defined environment for reconfigurable manufacturing systems

Conventional manufacturing systems like assembly lines cannot handle the constantly changing requirements of a modern-day manufacturer, which are driven by volatile market demands. In a bid to satisfy such requirements, modern manufacturing systems, comprising innumerable cyber-physical systems (CPS), aim to be reconfigurable. CPS implement production processes through an ICT infrastructure networked with sensors and actuators embedded in the shop floor. Reconfigurability, in context of manufacturing systems, must include the entire system of networked components and hence requires a flexible ICT infrastructure. Providing flexible ICT infrastructures, often, comes at the cost of diluted quality of service (QoS) guarantees. This, however, is not an option for manufacturing systems, most of which require strict QoS guarantees to function correctly. To overcome this obstacle, we propose a new software-defined environment (SDE) for reconfigurable manufacturing systems with real-time properties in this paper. Software-defined environment is an emerging technology that provides flexible ICT infrastructures modifiable using software. Our contributions include an SDE-based system architecture for dynamically configuring the underlying infrastructure for a manufacturing system. In particular, we focus on configuring the network for the time-sensitive communication flows essential for realising CPS. Moreover, we propose a pair of routing algorithms to calculate routes for these flows while configuring the network.