Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision fusion for robust horizon estimation using Dempster Shafer Combination Rule

In this paper, we address the problem of decision fusion for robust horizon estimation using Dempster Shafer Combination Rule (DSCR). We provide a framework for decision fusion to select robust horizon estimate out of `n' estimates, based on confidence factor. Vision-based attitude estimation depends on robust horizon estimation and no single algorithm gives accurate results for different kind of scenarios. We propose to combine the evidence parameters to generate confidence factor using DSCR to justify the correctness of the estimated horizon. We compute Confidence Interval (CI) based on Gaussian Mixture Model (GMM). We also propose two techniques to provide evidence parameters for the estimated horizon using CI. We demonstrate the effectiveness of the decision framework on clear and noisy data sets of simulated and real images/videos captured by Micro Air Vehicle (MAV).
The Effect of Altitude on the Pattern of Gene Flow in the Endemic Canary Island Pine, Pinus canariensis

Abstract Pinus canariensis is endemic to the western Canary Islands (NW coast of Africa), where it forms forest spanning an altitude from 500 to 2500 m. There are dramatic changes in environmental conditions (temperature, moisture and solar radiation) over short distances due to this elevation gradient in the Canary Island pine forest. Those differences in environmental conditions may lead to asynchronous flowering times among elevations. In this study we used nuclear and chloroplast microsatellites to characterize the genetic structure of two altitudinal transects on the southern slopes of Tenerife Island to test for genetic isolation among altitudes. Although significant differentiation among sites was detected, this differentiation was very low (FST = 0.013 with chloroplast markers, FST= 0.019 with nuclear markers) and appeared to be unrelated to altitude. The contrasting results between nuclear and chloroplast markers are also discussed in terms of statistical accuracy of markers and genome inheritance.
Adaptive cruise control for an intelligent vehicle

In this research, an adaptive cruise control system is developed and implemented on an AIT intelligent vehicle. To develop the adaptive cruise control system, the original throttle system and braking system of the vehicle have to be modified. The original throttle valve which is controlled by a cable from the accelerator pedal is modified to the drive-by-wire system by using a dc motor with a position control algorithm. The braking system is modified by using a dc servo motor to directly control the brake pedal. A proportional and derivative control with error compensation algorithm is proposed to perform the velocity control mode. In the distance control mode, a fuzzy logic algorithm is applied. Inputs of the fuzzy controller are distance error and relative velocity read from a laser range finder. The experiments on a racing circuit show that the vehicle can perform adaptive cruise control efficiently.
Toward Normative Expert Systems: Part I The Pathfinder Project

Abstract: Pathfinder is an expert system that assists surgical pathologists with the diagnosis of lymph-node diseases. The program is one of a growing number of normative expert systems that use probability and decision theory to acquire, represent, manipulate, and explain uncertain medical knowledge. In this article, we describe Pathfinder and our research in uncertain-reasoning paradigms that was stimulated by the development of the program. We discuss limitations with early decision-theoretic methods for reasoning under uncertainty and our initial attempts to use non-decision-theoretic methods. Then, we describe experimental and theoretical results that directed us to return to reasoning methods based in probability and decision theory.
Laplacian MinMax Discriminant Projections

A new algorithm, Laplacian MinMax Discriminant Projection (LMMDP), is proposed in this paper for supervised dimensionality reduction. LMMDP aims at learning a linear transformation which is an extension of Linear Discriminant Analysis (LDA). Speci¿cally, we de¿ne the within-class scatter and the between-class scatter using similarities which are based on pairwise distances in sample space. After the transformation, the considered pairwise samples within the same class are as close as possible, while those between classes are as far as possible. The structural information of classes is contained in the within-class and the between-class Laplacian matrices. Thus the discriminant projection subspace can be derived by controlling the structural evolution of Laplacian matrices. The performance on several data sets demonstrates the competence of the proposed algorithm.
Model-Assisted Estimation for Complex Surveys Using Penalized Splines

Estimation of finite population totals in the presence of auxiliary information is considered. A class of estimators based on penalised spline regression is proposed. These estimators are weighted linear combinations of sample observations, with weights calibrated to known control totals. They allow straightforward extensions to multiple auxiliary variables and to complex designs. Under standard design conditions, the estimators are design consistent and asymptotically normal, and they admit consistent variance estimation using familiar design-based methods. Data-driven penalty selection is considered in the context of unequal probability sampling designs. Simulation experiments show that the estimators are more efficient than parametric regression estimators when the parametric model is incorrectly specified, while being approximately as efficient when the parametric specification is correct. An example using Forest Health Monitoring survey data from the U.S. Forest Service demonstrates the applicability of the methodology in the context of a two-phase survey with multiple auxiliary variables. Copyright 2005, Oxford University Press.
Chinese Word Sketch and Mapping Principles: a Corpus-Based Study of Conceptual Metaphors Using the Building Source Domain

This study examines whether Mapping Principles, which govern how concrete concepts in a source domain are mapped to abstract concepts in a target domain, are realized in large-scale corpus data. In particular, we propose a frequency-based collocational approach to determine mapping principles based on the most productive mapping. In addition, in contrast to the target-domain-oriented method used in previous studies, we employ the source-domain-oriented method to search for lexical mappings from a particular source domain, i.e., BUILDING, to a number of target domains. The corpus data demonstrate that mapping principles exist in a source-target domain pairing. In addition, we found that different target domains select the source domain of BUILDING for different underlying reasons. Our study follows the lexical analysis of conceptual metaphors proposed by the Conceptual Mapping Model and helps us better understand how semantic networks of lexical words are represented in the lexicon via conceptual mappings.
Mexican American College Students’ Perceived Experiences of Discrimination, Ethnic Identity, and Adjustment

Given the salience of sibling relationships for Mexican American individuals, we examined the role of sibling support in the associations between discrimination, ethnic identity (EI), and the adjustment of Mexican American college students (N = 171, 80.7% female, M age = 21.6 years). Findings revealed that under conditions of high sibling support, discrimination was positively associated with EI resolution, which, in turn, was positively associated with self-esteem. Under conditions of low sibling support, discrimination was negatively associated with EI affirmation, which, in turn, was positively associated with self-esteem. Under conditions of low sibling support, there was a negative association between discrimination and EI affirmation, which, in turn, was negatively associated with depressive symptoms. These findings highlight the processes by which discrimination is associated with adjustment and the protective role of sibling support for Mexican American college students experiencing discrimination.
A fuzzy adaptive neighborhood search for function optimization

Neighborhood-based search algorithms have been applied with success in the optimization field. In this paper, the FANS (Fuzzy Adaptive Neighborhood Search) algorithm, which uses fuzzy concepts and heuristic rules in its decision procedures, together with several schedulers to adapt its behavior, is proposed. The conceptual and practical design of FANS in components allows decision makers to test different schemes and alternatives.
Efficient authentication of large, dynamic data sets using Galois/counter mode (GCM)

The Galois/counter mode (GCM) of operation can be used as an incremental message authentication code (MAC); in this respect, it is unique among the crypto algorithms used in practice. We show that it has this property, and show how to efficiently recompute a MAC after small changes within a message, after the appending or prepending of data to a message, or the truncation of data from the start or end of a message. Incremental MACs have great utility for protecting data at rest. In particular, they can be used to protect a large, dynamic data set using only a small, constant amount of memory
Flexible methods for estimating genetic distances from single nucleotide polymorphisms

With the increasing use of massively parallel sequencing approaches in evolutionary biology, the need for fast and accurate methods suitable to investigate genetic structure and evolutionary history are more important than ever. We propose new distance measures for estimating genetic distances between individuals when allelic variation, gene dosage and recombination could compromise standard approaches. We present four distance measures based on single nucleotide polymorphisms (SNP) and evaluate them against previously published measures using coalescent-based simulations. Simulations were used to test (i) whether the measures give unbiased and accurate distance estimates, (ii) whether they can accurately identify the genomic mixture of hybrid individuals and (iii) whether they give precise (low variance) estimates. The effect of rate variation among genes and recombination was also investigated. The results showed that the SNP-based GENPOFAD distance we propose appears to work well in the widest range of circumstances. It was the most accurate and precise method for estimating genetic distances and is also relatively good at estimating the genomic mixture of hybrid individuals. Our simulations provide benchmarks to compare the performance of different method that estimate genetic distances between organisms.
Team coordination in high-risk circus acrobatics

To advance understanding of the mechanisms allowing for team coordination (TC) in complex motor actions, we conducted a qualitative study with eight elite hand-to-hand circus acrobats. Data collection consisted of field observations, an open-ended interview with the participants’ head coach, and focus group interviews with all acrobats. Data analysis yielded three higher order themes: TC, collective efficacy (CE), and TC-CE linkage. Teammates’ shared and complementary mental models, as well as implicit and explicit communication dynamics, emerged as formative sub-themes of TC; self-efficacy and other’s-efficacy emerged as reflective sub-themes of CE. Our findings also suggest that TC is likely inter-related to CE in a systemic fashion. Practitioners should encourage the development of both shared and complementary models of thinking, while promoting verbal and non-verbal communication skills. Finally, increasing teammates’ confidence in themselves and in their teammates can help in the development of CE as well as the enhancement of TC.
RUNNING HEAD : Language of Interpersonal Interaction

Verbal and non-verbal information are central to social interaction between humans, and have been studied intensively in psychology. Especially, dyadic interaction settings (e.g, between romantic partners or between psychotherapist and patient) are relevant for a number of psychological research areas. However, psychological methods applied so far have not been able to handle the vast amount of data resulting from human interactions completely, impeding scientific discovery and progress. This paper presents an interdisciplinary approach using technology from engineering and computer science to work with continuous data from human communication and interaction on the verbal (e.g., use of words, content) and non-verbal (e.g., vocal features of the human voice) level. Text-mining techniques such as topic models take into account the semantic and syntactic information of written text (such as therapy session transcripts) and its structure and intercorrelations. Speech signal processing focuses on the vocal information in a speaker's voice (e.g., based on audio-or videotaped interactions). For both areas, an introduction defining the respective method and related procedures, and sample applications from psychological publications complementing or generating behavioral codes (e.g., in addition to cardiovascular indices of arousal or as a form to encode empathy), will be provided. We close with a summary on the chances and challenges of learning and applying tools from the novel approaches described in this manuscript to different areas of psychological research, and provide the interested reader with a list of additional readings on the technical aspects of topic modeling and speech signal processing. 4 Interpersonal interactions are challenging to study but are central to our daily lives and health and well-being. Consider the example of psychotherapy. A psychotherapy session is a complex interaction between a therapist and a patient, and when successful, something in the dyadic interaction leads to a reduction in psychiatric symptoms and an increase in the patient's functioning and well-being. Yet, the raw 'data' of psychotherapy is the verbal (i.e., acoustic, semantic) and non-verbal behavior of the two people, and these data streams are continuous throughout the psychotherapy session. The inherent complexity of such data has typically led researchers to use methods that drastically simplify the field's understanding of this complex process. Verbal and non-verbal data streams are not specific to psychotherapy but are common to most interpersonal interactions, which are a focus of study across an array of scholarly disciplines. Moreover, researchers use the tools they know and are often unaware of novel methodologies …
Comparison of visual-based helicopter and fixed-wing forward-looking infrared surveys for counting white-tailed deer Odocoileus virginianus

Abstract Aerial surveys using direct counts of animals are commonly used to estimate deer abundance. Forward-looking infrared (FLIR) technology is increasingly replacing traditional methods such as visual observation from helicopters. Our goals were to compare fixed-wing FLIR and visual, helicopter-based counts in terms of relative bias, influence of snow cover and cost. We surveyed five plots: four 41.4 km2 plots with free-ranging white-tailed deer Odocoileus virginianus populations in Wisconsin and a 5.3 km2 plot with a white-tailed deer population contained by a high fence in Michigan. We surveyed plots using both fixed-wing FLIR and helicopters, both with snow cover and without snow. None of the methods counted more deer than the other when snow was present. Helicopter counts were lower in the absence of snow, but lack of snow cover did not apparently affect FLIR. Group sizes of observed deer were similar regardless of survey method or season. We found that FLIR counts were generally precise (CV = 0.089) when two or three replicate surveys were conducted within a few hours. However, at the plot level, FLIR counts differed greatly between seasons, suggesting that detection rates vary over larger time scales. Fixed-wing FLIR was more costly than visual observers in helicopters and was more restrictive in terms of acceptable survey conditions. Further research is needed to understand what factors influence the detection of deer during FLIR surveys.
Sexually Dimorphic Expression of vasa Isoforms in the Tongue Sole (Cynoglossus semilaevis)

The vasa gene encodes an ATP-dependent RNA helicase of the DEAD box protein family that functions in a broad range of molecular events involving duplex RNA. In most species, the germline specific expression of vasa becomes a molecular marker widely used in the visualization and labeling of primordial germ cells (PGCs) and a tool in surrogate broodstock production through PGC transplantation. The vasa gene from tongue sole (Cynoglossus semilaevis) was characterized to promote the development of genetic breeding techniques in this species. Three C. semilaevis vasa transcripts were isolated, namely vas-l, vas-m, and vas-s. Quantitative real-time PCR results showed that C. semilaevis vasa transcripts were prevalently expressed in gonads, with very weak expression of vas-s in other tissues. Embryonic development expression profiles revealed the onset of zygotic transcription of vasa mRNAs and the maternal deposit of the three transcripts. The genetic ZW female juvenile fish was discriminated from genetic ZZ males by a pair of female specific primers. Only the expression of vas-s can be observed in both sexes during early gonadal differentiation. Before PGCs started mitosis, there was sexually dimorphic expression of vas-s with the ovary showing higher levels and downward trend. The results demonstrated the benefits of vasa as a germline specific marker for PGCs during embryonic development and gonadal differentiation. This study lays the groundwork for further application of C. semilaevis PGCs in fish breeding.
A Design Methodology for Self-Management in Distributed Environments

Autonomic computing is a paradigm that aims at reducing administrative overhead by providing autonomic managers to make applications self-managing. In order to better deal with dynamic environments, for improved performance and scalability, we advocate for distribution of management functions among several cooperative managers that coordinate their activities in order to achieve management objectives. We present a methodology for designing the management part of a distributed self-managing application in a distributed manner. We define design steps, that includes partitioning of management functions and orchestration of multiple autonomic managers. We illustrate the proposed design methodology by applying it to design and development of a distributed storage service as a case study. The storage service prototype has been developed using the distributing component management system Niche. Distribution of autonomic managers allows distributing the management overhead and increased management performance due to concurrency and better locality.
An approach to argumentative reasoning servers with conditions based preference criteria

Argumentation is a reasoning mechanism attractive due to its dialectical and non monotonic nature, and its properties of computational tractability. In dynamic domains where the agents deal with incomplete and contradictory information, an argument comparison criterion can be used to determine the accepted information. Argumentation systems with a single argument comparison criterion have been widely investigated; in some of these approaches, the comparison criterion is fixed while in others a criterion can be selected and replaced in a modular way. We present an argumentative server providing client agents with recommendations and giving the possibility of specifying which of the available argument comparison criteria will be used to answer a query; for that, we formalize a special type of contextual query which by the use of conditions allows the server to dynamically change the criterion providing a declarative way of representing users preferences.
The composition of the interstellar medium towards the Lockman Hole - $\ion{H}{I}$, UV and X-ray observations

The Lockman Hole is well known as the region with the lowest neutral atomic hydrogen column density on the entire sky. We present an analysis of the soft X-ray background radiation towards the Lockman Hole using ROSAT all-sky survey data. This data is correlated with the Leiden/Dwingeloo survey (Galactic $\ion{H}{i}$ 21 cm-line emission) in order to model the soft X-ray background by using radiative transfer calculations for four ROSAT energy bands simultaneously. It turns out, that an important gas fraction, ranging between 20–50%, of the X-ray absorbing material is not entirely traced by the $\ion{H}{i}$ but is in the form of ionized hydrogen. Far-ultraviolet absorption line measurements by FUSE are consistent with this finding and support an ionized hydrogen component towards the Lockman Hole.
Arrhythmogenic Right Ventricular Cardiomyopathy: Considerations from in Silico Experiments

Objective: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with remodeling of gap junctions and also, although less well-defined, down-regulation of the fast sodium current. The gap junction remodeling and down-regulation of sodium current have been proposed as contributors to arrhythmogenesis in ARVC by slowing conduction. The objective of the present study was to assess the amount of conduction slowing due to the observed gap junction remodeling and down-regulation of sodium current. Methods: The effects of (changes in) gap junctional conductance, cell dimensions, and sodium current on both longitudinal and transversal conduction velocity were tested by simulating action potential propagation in linear strands of human ventricular cells that were either arranged end-to-end or side-by-side. Results: A 50% reduction in gap junction content, as commonly observed in ARVC, gives rise to an 11% decrease in longitudinal conduction velocity and a 29% decrease in transverse conduction velocity. A down-regulation of the sodium current through a 50% decrease in peak current density as well as a −15 mV shift in steady-state inactivation, as observed in an experimental model of ARVC, decreases conduction velocity in either direction by 32%. In combination, the gap junction remodeling and down-regulation of sodium current result in a 40% decrease in longitudinal conduction velocity and a 52% decrease in transverse conduction velocity. Conclusion: The gap junction remodeling and down-regulation of sodium current do result in conduction slowing, but heterogeneity of gap junction remodeling, in combination with down-regulation of sodium current, rather than gap junction remodeling per se may be a critical factor in arrhythmogenesis in ARVC.