Miracle-dz/UniFAR-FTUs huggingface dataset:
STRENGTH APPRAISAL OF ARTIFICIAL SAND AS FINE AGGREGATE IN SFRC

The huge quantity of concrete is consumed by the construction industry all over the world, probably second largest after water. In India, the conventional concrete is produced by using natural sand from riverbeds as fine aggregate. Dwindling sand resources poses the environmental problem and hence government restrictions on sand quarrying resulted in scarcity and significant increase in its cost. This paper presents the study of steel fiber reinforced concrete with artificial sand as fine aggregate. Three matrices with compressive strength 20, 30 and 40 MPa were designed and reinforced with crimpled steel fibers at dosage rate of volume fraction 0, 0.5, 1.0, 1.5 and 2.0 percent. The specimens were prepared, cured and tested for compressive strength, flexural strength and split tensile strength. The strength of steel fiber reinforced natural sand concrete (SFRNSC) and steel fiber reinforced artificial sand concrete (SFRASC) have been compared with the test data from the present study. The promotional use of artificial sand will conserve the natural resources for the sustainable development of the concrete in construction industry.
From COGWHEELS to COGNITION The Knowledgeable Robot

Recent progress in the contributing disciplines of cognitive science (philosophy of mind, neurophysiology, genetics, ethology, evolutionary theory, computer science, artificial intelligence, etc.) have made it possible and interesting to compare the “mental” capabilities of people, animals, parts of minds, and computer systems. Whereas computer scientists routinely use metaphorically extended terms like “decide” to refer to decision-like processes in computers, some philosophers of mind insist that such mentalistic terms be restricted to the operations of the full orchestra of the human mind. Consequently terminological confusion has confounded the interesting debate about the extent to which machines could ever be made to think using this or that approach. This paper proposes ways of developing more terminologies with which we can talk more clearly about the varieties of mental capabilities available to different kinds of creatures and devices, both natural and artificial. Focussing on the questions of attributing knowledge to a robot, and how knowledge may be implemented in a robot, leads to the development of the idea of seeing the robot mind/body complex as a hierarchy of technology domains. This in turn leads into a cybernetic or behaviour-based view of mind, encompassing the interactive complex of brain, body, and world, in which brain (or computer) is not the host of mind, but its generative organ. Stent [Scientific American Dec 1972] also considers the possibility that an entire field of enquiry may lack connexion . with the body of knowledge possessed by the scientific community at large. This is precisely the situation of machine intelligence research, which uses the techniques of computing to investigate questions not of natural science but of philosophy. [Michie 73] Technology is at present covert philosophy; the point is to make it openly philosophical. [Agre 97], p240.
Multi-parametric Segmentation of MR images of the Brain

This work deals with segmentation of magnetic resonance images. For better distinguishing between particular tissues, particular properties of tissues and their manifestation in different types of imaging are used. Specifically, T1 and T2 images are used. The segmentation is based on the approximation of more dimensional histograms. Since the noise distribution in MR images is close to Gaussian distribution for large signal-to-noise ratio, the approximation is done by Gaussian Mixture Model, where the number of components is determined using Bayesian Information Criterion and Elbow method.
A Model for the Formation of Maternal Authority Styles Starting from Attachment, and Mediated by Temperament and Character

Parenting styles powerfully influence child outcomes, and are thus of multi-generational significance. This study set out to examine a developmentally informed model that attachment styles, and then temperament traits, followed by character traits would predict parental styles. One hundred and eightytwo women in their thirties, mothers to children three to five years of age, self-reported online on the Temperament and Character Inventory, the Parental Authority Questionnaire, and the Experiences in Close Relationships. A structural equation model was built with excellent goodness of fit indices. Temperament and character traits were significantly predicted by attachment styles and in turn completely mediated the influence of attachment styles on parental styles. All four temperament traits and two character traits pointed meaningfully to the formation of parenting styles. In particular, being high on the temperament trait of Novelty seeking was detrimental to parental maintenance of boundaries and discipline. Being high on the character traits of Self-directedness and Cooperativeness was helpful for authoritative parenting and protective against authoritarian parenting. The current study found that mature personality, characterized by traits central to emotional regulation, goal-directed behavior, and working harmoniously with others, is beneficial to authoritative parenting. These results suggest that interventions to enhance parenting could focus on character development.
FreeForm: an informal environment for interface prototyping

Best practice in interface design suggests that hand-drawn sketches are preferable at the early stages of the design process. This paper describes the FreeForm software which supports informal sketched interface design by acting as a Visual Basic Add-In. The software utilises a digital whiteboard and pen input to support sketching and "running" of an informal prototype.
Challenges in Treating Older Patients with Acute Myeloid Leukemia

Whereas in younger patients diagnosed with acute myeloid leukemia (AML) treatment is straightforward and the goal is cure, the optimal treatment decision for older adults remains highly controversial. Physicians need to determine whether palliation, “something” beyond palliation, intensive therapy, or an investigational therapy is the most appropriate treatment option. This requires understanding of the biology and risk profile of the AML, clinical judgment in evaluating the functional status of the patient, communication skills in understanding the patient's wishes and social background, and medical expertise in available therapies. The physician has to accurately inform the patient about (a) the unique biological considerations of his leukemia and his prognosis; (b) the risks and benefits of all available treatment options; (c) novel therapeutic approaches and how the patient can get access to these treatments. Last but not least, he has to recommend a treatment. This paper tries to discuss each of these issues.
Vibration suppression with approximate finite dimensional compensators for distributed systems: Computational methods and experimental results

Based on a distributed parameter model for vibrations, an approximate finite dimensional dynamic compensator is designed to suppress vibrations (multiple modes with a broad band of frequencies) of a circular plate with Kelvin-Voigt damping and clamped boundary conditions. The control is realized via piezoceramic patches bonded to the plate and is calculated from information available from several pointwise observed state variables. Examples from computational studies as well as use in laboratory experiments are presented to demonstrate the effectiveness of this design.
On the Interplay Between Individuals’ Evolving Interaction Patterns and Traits in Dynamic Multiplex Social Networks

The interplay between individuals' social interactions and traits has been studied extensively but traditionally from static or homogeneous social network perspectives. The recent availability of dynamic and heterogeneous (multiplex) network data has introduced a variety of new challenges. Critically, novel computational models are needed that can cope with data dynamics and heterogeneity. In this paper, we introduce a computational framework that is broadly applicable to a variety of dynamic, multiplex domains, which focuses on: 1) measuring changes in node interaction patterns with time, 2) clustering nodes with similar evolving patterns, and 3) linking the clusters with trait similarities. We apply the framework to study the interplay between evolving topology and traits in an 18-month social network dataset encompassing both digital communications and co-location instances. Notably, we demonstrate how our framework captures results that would otherwise be missed by a simpler approach such as static network analysis alone. In addition, we uncover network-trait interplays that have not been studied to date and could lead to novel insights by domain scientists.
Experimental and natural host specificity of Loma salmonae ( Microsporidia )

The microsporidian L o n ~ a salmonae (Putz, Hoffman & Dunbar, 1965) h4orrison & Sprague, 1981 has caused significant gill disease in Pacific salmon Oncorhynchus spp. Host specif~city of the parasite was examined experimentally by per OS challenge of selected salmon~ds and non-salmonids with infective chinook salmon 0, tshawytscha gill material Pink Oncorhynchus gorbuscha and chum salmon 0. keta, brown S a h o trutta and brook trout Salvelinus fontlnalis, and chlnook salmon (controls) were positive, whereas Atlantic salmon Salmo salar and Arctic char Salvelinus alpinus were negative. In addition, no non-salmonids were susceptible to expenmental exposure Wild Pacific salmon species in Bntish Columbia, Canada, were examined for L. salmonae during their freshwater life history stages (smolts, prespawning, spawning) All stages were infected, although infections In smolts were only detectable using a L. salmonae-specific PCR test. Many previous Loma spp described from Oncorhychus spp. are likely L. salmonae based on host, parasite morphology, and slte of Infection
Semi-automatically augmenting virtual environments with plausibly located clutter

We present an approach for semiautomatically augmenting existing virtual environments with sensibly and plausibly distributed features which model the clutter we find in real-world scenes. It focuses on the stages of identifying sensible potential clutter placement regions and then describes a novel use of parametric surfaces as a generalised means of specifying distribution patterns within these regions
Spoofing Attack Detection and Localization of Multiple Adversaries in Wireless Networks

In wireless networks, Spoofing attacks are easy to launch but it degrades the performance of the networks. To identity an attacker node, it can be verified through cryptographic authentication, authentication is always not possible because it requires key management and additional infrastructural overhead. The proposed approach is used for 1) Detecting spoofing attacks 2) Determining the number of attackers when multiple adversaries masquerading the same node identity and 3) Localizing multiple adversaries. The proposed system uses spatial correlation of received signal strength (RSS) to detect the spoofing attacks. Cluster-based mechanisms are introduced to determine the number of attackers. In this paper, K-Nearest-Neighbor classifier (KNN) is proposed to improve the performance of determining the number of attacks. Finally, An Integrated Detection and Localization system is used to localize the positions of multiple attackers.
Notice of RetractionThe application of multilayer distributed intelligent decision support system to regional economy

For forecasting, early warning and simulation of economic policy, this paper has established a multi-level-based distributed intelligent decision support for regional economic system, analysis of the laws governing the operation of regional economic system, trends and influencing factors. In the regional economy take full advantage of multi-level distributed intelligent decision support system to successfully assist the Government in policy-making departments to keep abreast of regional economic development of relevant information and provides the user the actual economic development and systems analysis of the evaluation index system derived, using scientific analysis model, and gives the best and reliable conclusions, at any time for decision-makers to provide efficient, timely, high-quality decision-making information, thereby enhancing the scientific nature of decision-making, and guide the healthy development of the regional economy.
Particulate air pollution and daily mortality on Utah's Wasatch Front.

Reviews of daily time-series mortality studies from many cities throughout the world suggest that daily mortality counts are associated with short-term changes in particulate matter (PM) air pollution. One U.S. city, however, with conspicuously weak PM-mortality associations was Salt Lake City, Utah; however, relatively robust PM-mortality associations have been observed in a neighboring metropolitan area (Provo/Orem, Utah). The present study explored this apparent discrepancy by collecting, comparing, and analyzing mortality, pollution, and weather data for all three metropolitan areas on Utah's Wasatch Front region of the Wasatch Mountain Range (Ogden, Salt Lake City, and Provo/Orem) for approximately 10 years (1985-1995). Generalized additive Poisson regression models were used to estimate PM-mortality associations while controlling for seasonality, temperature, humidity, and barometric pressure. Salt Lake City experienced substantially more episodes of high PM that were dominated by windblown dust. When the data were screened to exclude obvious windblown dust episodes and when PM data from multiple monitors were used to construct an estimate of mean exposure for the area, comparable PM-mortality effects were estimated. After screening and by using constructed mean PM [less than/equal to] 10 microm in aerodynamic diameter (PM10) data, the estimated percent change in mortality associated with a 10-mg/m3 increase in PM10 (and 95% confidence intervals) for the three Wasatch Front metropolitan areas equaled approximately 1. 6% (0.3-2.9), 0.8% (0.3-1.3), and 1.0% (0.2-1.8) for the Ogden, Salt Lake City, and Provo/Orem areas, respectively. We conclude that stagnant air pollution episodes with higher concentrations of primary and secondary combustion-source particles were more associated with elevated mortality than windblown dust episodes with relatively higher concentrations of coarse crustal-derived particles. ImagesFigure 1Figure 2Figure 3Figure 4
Robust Semantic Segmentation using Deep Fusion

—Robust semantic scene understanding of unstructured environments is critical for robots operating in the real world. Several inherent natural factors such as shadows, glare and snow make this problem highly challenging, especially using RGB images. In this paper, we propose the use of multispectral and multimodal images to increase robustness of segmentation in real-world outdoor environments. Deep Convolutional Neural Network (DCNN) architectures deﬁne the state of the art in various segmentation tasks, however, architectures that incorporate fusion has not been sufﬁciently explored. We explore early and late fusion architectures for dense pixel-wise segmentation from RGB, Near-InfraRed (NIR) channels, and depth data. We identify data augmentation strategies that enable training of very deep fusion models using small datasets. We qualitatively and quantitatively evaluate our approach and show it exceeds several other state of the art architectures. In addition, we present experimental results for segmentation under challenging real-world conditions. Demo and dataset is publicly available at http://deepscene.cs. uni-freiburg.de.
A Color Based Image Segmentation and its Application to Text Segmentation

The goal of this article is twofold. First, it deals with color image segmentation in hue-saturation space. A model for circular data is provided by the vM-Gauss distribution, which is a joint distribution of von-Mises and Gaussian distributions. The mixture of vM-Gauss distributions is used to model hue-saturation data. After segmentation, a post processing based on both spectral and spatial similarity of clusters is applied to separate such identifiable objects in the image. The results and comparisons are shown on Berkeley segmentation dataset. The problem of text extraction from a color image is taken as an application of the proposed method. We use a laboratory made text image dataset to test the method.
Cellular Functions of Genetically Imprinted Genes in Human and Mouse as Annotated in the Gene Ontology

By analyzing the cellular functions of genetically imprinted genes as annotated in the Gene Ontology for human and mouse, we found that imprinted genes are often involved in developmental, transport and regulatory processes. In the human, paternally expressed genes are enriched in GO terms related to the development of organs and of anatomical structures. In the mouse, maternally expressed genes regulate cation transport as well as G-protein signaling processes. Furthermore, we investigated if imprinted genes are regulated by common transcription factors. We identified 25 TF families that showed an enrichment of binding sites in the set of imprinted genes in human and 40 TF families in mouse. In general, maternally and paternally expressed genes are not regulated by different transcription factors. The genes Nnat, Klf14, Blcap, Gnas and Ube3a contribute most to the enrichment of TF families. In the mouse, genes that are maternally expressed in placenta are enriched for AP1 binding sites. In the human, we found that these genes possessed binding sites for both, AP1 and SP1.
The Methods for Solving Influence Diagrams: A Review

Influence diagrams (IDs) are one of the most commonly used graphical decision models for reasoning under uncertainty. Solving an ID means determining the optimal strategy for the decision maker and the value or certain equivalent of the decision situation when that optimal strategy is applied. Much research effort has been devoted to develop methods and algorithms for solving IDs, and a vast literature on this problem has been yielded. This paper attempts a brief exposition on the methods common used for solving IDs, for the purpose of providing a help for decision makers to select appropriate methods when they solve IDs.
Steganalysis with cover-source mismatch and a small learning database

Many different hypotheses may be chosen for modeling a steganography/steganalysis problem. In this paper, we look closer into the case in which Eve, the steganalyst, has partial or erroneous knowledge of the cover distribution. More precisely we suppose that Eve knows the algorithms and the payload size that has been used by Alice, the steganographer, but she ignores the images distribution. In this source-cover mismatch scenario, we demonstrate that an Ensemble Classifier with Features Selection (EC-FS) allows the steganalyst to obtain the best state-of-the-art performances, while requiring 100 times smaller training database compared to the previous state-of-the art approach. Moreover, we propose the islet approach in order to increase the classification performances.
Influence of wind turbine generator fault-tolerant control on power production quality

Renewable energy sources bring to fore the significance of power electronics and corresponding control. The topic of wind turbine fault-tolerant control has emerged as a promising line of research for improving their market competence. The paper presents summarized control of wind turbine converter with a fault-tolerant control extension for generator electromechanical faults, based on a proper modulation of the stator magnetic flux. The modulation also introduces hard periodic oscillations in the stator currents and generator output power. Simulation results obtained with a Matlab-Simplorer co-simulation and detailed power converter model show that DC-link capacitor and corresponding control algorithm act like an energy buffer that suppress the influence of generator stator oscillations on currents passed to the grid and maintain the high quality of power production. Following from the results, the generator and grid side controls are justified to be considered as two independent problems.
Cutaneous water loss and sphingolipids covalently bound to corneocytes in the stratum corneum of house sparrows Passer domesticus

SUMMARY The barrier to water loss from the skin of birds and mammals is localized in the stratum corneum (SC), the outer layer of the epidermis. The SC consists of corneocytes, each surrounded by a protein envelope, and a lipid compartment, formed by an extracellular matrix of lipids and by lipids covalently bound to the protein envelope. In mammals, covalently bound lipids in the SC consist of ω-hydroxyceramides attached to the outer surface of corneocytes. Evidence suggests that covalently bound lipids in the SC might be crucial for the establishment of a competent permeability barrier. In this study we assessed the composition of covalently bound lipids of the avian SC and their relationship to cutaneous water loss (CWL) in two populations of house sparrows, one living in the deserts of Saudi Arabia and the other in mesic Ohio. Previously, we showed that CWL of adult desert sparrows was 25% lower than that of mesic birds. In the present study we characterize covalently bound lipids of the SC using thin layer chromatography and high performance liquid chromatography coupled with atmospheric pressure Photospray® ionization mass spectrometry. Our study is the first to demonstrate the existence of sphingolipids covalently bound to corneocytes in the SC of birds. Although ω-hydroxyceramides occurred in the lipid envelope surrounding corneocytes, the major constituent of the covalently bound lipid envelope in house sparrows was ω-hydroxycerebrosides, ceramides with a hexose molecule attached. Sparrows from Saudi Arabia had more covalently bound cerebrosides, fewer covalently bound ceramides and a lower ceramide to cerebroside ratio than sparrows living in Ohio; these differences were associated with CWL.
The Influence of Psychological Intervention on Cognitive Appraisal and Level of Anxiety in Dialysis Patients: A Pilot Study

Objective: The great progress with the application of a dialysis allows patients with the end-stage renal disease to live in a satisfactory somatic state for many years. This pilot study examined if the psychological intervention improves psychic state of the patients with renal disease undergoing hemodyalisis. Methods: The study was a randomized controlled trial using a convenience sample of 62 fully informed and consenting patients with the end-stage renal disease who were assigned to experimental (psychological intervention) or control (usual care) groups. Participants in the experimental group listened to a CD with a psychological intervention twice a day during 3 weeks. The instruments were the Cognitive Appraisal Inventory and the STAI-Anxiety Inventory. Results: After the application of a psychological intervention, the experimental group had a lower level of anxiety t(30) = 2.99; p < . 005, a weaker intensity of cognitive appraisal of the treatment situation as a threat t(30)=3.48; p < . 05, a weaker intensity of cognitive appraisal of the situation as a harm/loss t(30)=2.75; p < . 05 and a stronger intensity of cognitive appraisal of the situation as a challenge t(30) = 3.49; p < . 05. The applied psychological intervention makes it possible to decrease the level of anxiety and to change cognitive appraisal of treatment situation. Conclusions: The applied psychological intervention influences the patients' psychological state in a positive way. Such changes may indirectly contribute to improving social contacts as well as to increasing satisfaction with the undertaken activities.