Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a model driven refinement process through architecture evaluation

Real-time embedded systems engineering is a complex process used in the development of industrial systems or products. The development of these systems may need to consider the assessment of numerous different and interrelated quality attributes. The Model-Driven Development approach implies many benefits for this process, owing to the use of high-level models and model transformations. However, it must be carefully applied, since all the quality attributes must be considered if acceptable results are to be attained. In this paper, we propose a method for the incremental refinement of transformations based on the non-functional requirements tradeoff analysis and on the study of its impact on the implementation of transformations. The approach employs sensitivities and the tradeoff identification method. The approach is illustrated with a simple example.
Sequential Attention: A Context-Aware Alignment Function for Machine Reading

In this paper we propose a neural network model with a novel Sequential Attention layer that extends soft attention by assigning weights to words in an input sequence in a way that takes into account not just how well that word matches a query, but how well surrounding words match. We evaluate this approach on the task of reading comprehension (on the Who did What and CNN datasets) and show that it dramatically improves a strong baseline—the Stanford Reader—and is competitive with the state of the art.
MULTISPECTRAL IMAGE ANALYSIS USING RANDOM FOREST

Classical methods for classification of pixels in multispectral images include supervised classifiers such as the maximum-likelihood classifier, neural network classifiers, fuzzy neural networks, support vector machines, and decision trees. Recently, there has been an increase of interest in ensemble learning – a method that generates many classifiers and aggregates their results. Breiman proposed Random Forestin 2001 for classification and clustering. Random Forest grows many decision trees for classification. To classify a new object, the input vector is run through each decision tree in the forest. Each tree gives a classification. The forest chooses the classification having the most votes. Random Forest provides a robust algorithm for classifying large datasets. The potential of Random Forest is not been explored in analyzing multispectral satellite images. To evaluate the performance of Random Forest, we classified multispectral images using various classifiers such as the maximum likelihood classifier, neural network, support vector machine (SVM), and Random Forest and compare their results.
A Textbook of Physiological Psychology

Among the recent of the hybrid biomedical sciences, physiological psychology is gaining increasing interest. This is reflected in the establishment of new university courses in the subject, although there are few texts now available to meet the requirements of such courses. It is the aim of the present book to do this by giving in one volume a general introduction and a comprehensive treatment of theory, serving the purposes of undergraduate, graduate, and medical students, as well as investigators engaged in research. Reflecting the comprehensive purpose of the book, it is organized into four parts of increasing sophistication. The first part presents a very brief review of neurophysiology and a more thorough treatment of neuroanatomy. This section gives the beginning student a basic understanding of the properties of neurons and their interactions. It also gives a solid anatomical framework upon which the experimental material presented in the following parts can be placed. The second part deals with basic neural systems whose properties are relatively well understood and which illustrate principles seen throughout the nervous system. Here the recent work on the visual system is reviewed comprehensively as well as the organization of the motor systems and their interactions with sensory mechanisms. A lucid discussion of the complex reticular formation is also given. Parts three and four together make up three-fourths of the book, dealing with what the author terms "motivational mechanisms" and "associative processes," respectively. Among motivational mechanisms the following topics are covered: hunger, regulation of energy balance, thirst regulation, sexual behavior, central stimulation, and theories of motivation. The chapters in this section characteristically begin with a general statement of the nature of the topic, the historical development of theories pertaining to it, and the kinds of experiments and techniques that have been valuable in elucidating the particular mechanisms under study. In each of the chapters an excellent summary of the present theories and their bases concludes the discussion. Under the heading of associative processes, part four includes work on electrophysiological and biochemical correlates of learning, and the effects of central nervous system stimulation and lesions on acquisition and retention. The chapters here are also organized around the experimental work and the theories that have guided it in the various fields. In this book of 932 pages there are over 635 illustrations, the majority from original sources and well-known basic texts, adding greatly to its readibility and scope. It is recognized that in a field of such complexity, founded as it is in experimental controversy, complete coverage of all data and theories is not possible. It is to the author's credit, that, with the discussions and extensive references, a complete knowledge of the experimental foundation for the present understanding of the various psychological mechanisms can be obtained. This book provides a needed text for physi-
Uptake of thallium from artificially contaminated soils by kale (Brassica oleracea L. var. acephala)

A pot experiment focused on the study of factors influencing thallium transfer from contaminated soils into kale (green cabbage, Brassica oleracea L. var. acephala, variety Winterbor F1) was evaluated. Three different types of topsoils with naturally low content of thallium (heavy, medium and medium-light soil) were used for pot experiments. The soils were contaminated with thallium sulfate to achieve five levels of contamination (0, 0.52, 2.10, 4.20 and 5.88 mg/kg). There were six replicates for each combination (90 pots in the experiment). The first part of the experiment started in the year of contamination (2001) and continued in 2003. The soil samples and the samples of kale (leaves and stalks were sampled separately) were collected and analysed. Kale was found to be able to accumulate Tl without any influence on yield. The highest thallium concentration was found in the leaves of kale in the first year of the experiment and reached 326 mg/kg dry matter. Bioaccumulation factor (Biological Absorption Coefficient – BAC) was found to be over 80 during the first year of the experiment. In the third year the BAC was around 3 for the soil with the highest pH and the highest organic matter content but as high as 15 for an acid soil with the lowest content of organic matter and the lowest Cation Exchange Capacity (CEC) of soils. The content of thallium in the leaves of kale was found to be 7 to 10 times higher than in the stalks in the third year. In the first year this ratio was up to 18. From these findings it can be concluded that the ability of some plants of Brassicacea family, that are planted as common vegetables, to accumulate thallium is very high and can be a serious danger for food chains. Neutral soils high in CEC and organic matter are able to bind thallium more effectively than poor acid soils and the transfer of Tl into plants from these soils is substantially lower. The uptake of Tl from contaminated soils into kale can be very high and without any negative effect on the plant growth. The transfer of Tl into kale decreases with the time necessary to reach the equilibrium between the added Tl and the soil (ageing of a sample).
Context Encoders: Feature Learning by Inpainting

We present an unsupervised visual feature learning algorithm driven by context-based pixel prediction. By analogy with auto-encoders, we propose Context Encoders - a convolutional neural network trained to generate the contents of an arbitrary image region conditioned on its surroundings. In order to succeed at this task, context encoders need to both understand the content of the entire image, as well as produce a plausible hypothesis for the missing part(s). When training context encoders, we have experimented with both a standard pixel-wise reconstruction loss, as well as a reconstruction plus an adversarial loss. The latter produces much sharper results because it can better handle multiple modes in the output. We found that a context encoder learns a representation that captures not just appearance but also the semantics of visual structures. We quantitatively demonstrate the effectiveness of our learned features for CNN pre-training on classification, detection, and segmentation tasks. Furthermore, context encoders can be used for semantic inpainting tasks, either stand-alone or as initialization for non-parametric methods.
The Impact of Gynecological Cancer on Reproductive Issues and Pregnancy:Psychological Implications

Gynecological cancer is the fourth most common form of cancer among women. Over the past few decades, the growing number of survivors has been forced to cope with the consequences of the disease. Of these consequences, the impact of cancer on reproduction has been receiving increasing attention. Research shows that the health care of these women poses challenges other than medical ones. Although the inclusion of psychologists in health care teams has been particularly valued, studies focusing on the psychological implications of the impact of gynecological cancer on reproduction are scarce. Therefore, the first aim of this review is to critically reflect on the psychological implications of infertility, decision-making regarding childbirth, and pregnancy in the context of gynecological cancer. The second purpose of this review is to provide practice guidelines that account for the specificities and demands of these patients. Our findings suggest that gynecological cancer entails specific emotional and decisional challenges regarding reproductive issues, highlighting the importance of specialized psychological interventions with patients and their families. Providing emotional support and education about sexual and reproductive difficulties, supporting decision-making about fertility preservation and childbirth, promoting adjustment to cancer during pregnancy and supporting transition to motherhood are the main areas of intervention suggested. A
Bubble Wrap for Bullets: The Stability Imparted by a Thin Magnetic Layer

There has been significant recent work by several authors which examines a situation where a thin magnetic layer is "draped" over a core merging into a larger cluster; the same process also appears to be at work in a bubble rising from the cluster center. Such a thin magnetic layer could thermally isolate the core from the cluster medium, but only if the same shear process which generates the layer does not later disrupt it. On the other hand, if the magnetized layer can stabilize against the shear instabilities, then the magnetic layer can have the additional dynamical effect of reducing the shear-driven mixing of the core's material during the merger process. These arguments could apply equally well to underdense cluster bubbles, which would be even more prone to disruption. While it is well known that magnetic fields can suppress instabilities, it is less clear that a thin layer can suppress instabilities on scales significantly larger than its thickness. We consider here the stability imparted by a thin magnetized layer. We investigate this question in the most favorable case, that of two dimensions, where the magnetic field can most strongly affect the stability. We find that in this case such a layer can have a significant stabilizing effect even on modes with wavelengths λ much larger than the thickness of the layer l. To stabilize modes with λ ≈ 10l requires only that the Alfvén speed in the magnetized layer is comparable to or greater than the relevant destabilizing velocity—the shear velocity in the case of pure Kelvin-Helmholtz-like instability or a typical buoyancy velocity in the case of pure Rayleigh-Taylor-like instability. We confirm our calculations with two-dimensional numerical experiments using the Athena code.
On the capture probability for a large number of stations

The probability of capture under a model based on the ratio of the largest received power to the sum of interference powers is examined in the limit of a large number of transmitting stations. It is shown in great generality that the limit depends only on the capture ratio threshold and the roll-off exponent of the distribution of power received from a typical station. This exponent is insensitive to many typical channel effects such as Rician or Rayleigh fading and log-normal shadowing. The model is suitable for large systems with noncoherently combined interference.
Establishment of Hairy Root Cultures by Agrobacterium Rhizogenes Mediated Transformation of Isatis Tinctoria L. for the Efficient Production of Flavonoids and Evaluation of Antioxidant Activities

In this work, Isatis tinctoria hairy root cultures (ITHRCs) were established as an alternative source for flavonoids (FL) production. I. tinctoria hairy root line V was found to be the most efficient line and was further confirmed by the PCR amplification of rolB, rolC and aux1 genes. Culture parameters of ITHRCs were optimized by Box-Behnken design (BBD), and eight bioactive FL constituents (rutin, neohesperidin, buddleoside, liquiritigenin, quercetin, isorhamnetin, kaempferol and isoliquiritigenin) were quali-quantitatively determined by LC-MS/MS. Under optimal conditions, the total FL accumulation of ITHRCs (24 day-old) achieved was 438.10 μg/g dry weight (DW), which exhibited significant superiority as against that of 2 year-old field grown roots (341.73 μg/g DW). Additionally, in vitro antioxidant assays demonstrated that ITHRCs extracts exhibited better antioxidant activities with lower IC50 values (0.41 and 0.39, mg/mL) as compared to those of field grown roots (0.56 and 0.48, mg/mL). To the best of our knowledge, this is the first report describing FL production and antioxidant activities from ITHRCs.
Stabilization Wedges: Solving the Climate Problem for the Next 50 Years with Current Technologies

Humanity already possesses the fundamental scientific, technical, and industrial know-how to solve the carbon and climate problem for the next half-century. A portfolio of technologies now exists to meet the world's energy needs over the next 50 years and limit atmospheric CO2 to a trajectory that avoids a doubling of the preindustrial concentration. Every element in this portfolio has passed beyond the laboratory bench and demonstration project; many are already implemented somewhere at full industrial scale. Although no element is a credible candidate for doing the entire job (or even half the job) by itself, the portfolio as a whole is large enough that not every element has to be used.
Saliency propagation from simple to difficult

Saliency propagation has been widely adopted for identifying the most attractive object in an image. The propagation sequence generated by existing saliency detection methods is governed by the spatial relationships of image regions, i.e., the saliency value is transmitted between two adjacent regions. However, for the inhomogeneous difficult adjacent regions, such a sequence may incur wrong propagations. In this paper, we attempt to manipulate the propagation sequence for optimizing the propagation quality. Intuitively, we postpone the propagations to difficult regions and meanwhile advance the propagations to less ambiguous simple regions. Inspired by the theoretical results in educational psychology, a novel propagation algorithm employing the teaching-to-learn and learning-to-teach strategies is proposed to explicitly improve the propagation quality. In the teaching-to-learn step, a teacher is designed to arrange the regions from simple to difficult and then assign the simplest regions to the learner. In the learning-to-teach step, the learner delivers its learning confidence to the teacher to assist the teacher to choose the subsequent simple regions. Due to the interactions between the teacher and learner, the uncertainty of original difficult regions is gradually reduced, yielding manifest salient objects with optimized background suppression. Extensive experimental results on benchmark saliency datasets demonstrate the superiority of the proposed algorithm over twelve representative saliency detectors.
Visualizing the behavior of object-oriented systems

Numerous classes, complex inheritance and containment hierarchies, and diverse patterns of dynamic interaction all contribute to difficulties in understanding, reusing, debugging, and tuning large object-oriented systems. To help overcome these difficulties, we introduce novel views of the behavior of object-oriented systems and an architecture for creating and animating these views. We describe platform-independent techniques for instrumenting object-oriented programs, a language-independent protocol for monitoring their execution, and a structure for decoupling the execution of a subject program from its visualization. Case studies involving tuning and debugging of real systems are presented to demonstrate the benefits of visualization. We believe that visualization will prove to be a valuable tool for object-oriented software development.
Differential Proteomic Analysis of Bronchoalveolar Lavage Fluid in Asthmatics following Segmental Antigen Challenge*S

Allergic asthma is characterized by persistent airway inflammation and remodeling. Bronchoalveolar lavage conducted with fiberoptic bronchoscopy has been widely used for investigating the pathogenesis of asthma and other lung disorders. Identification of proteins in the bronchoalveolar lavage fluid (BALF) and their expression changes at different stages of asthma could provide further insights into the complex molecular mechanisms involved in this disease. In this report, we describe the first comprehensive differential proteomic analysis of BALF from both asthmatic patients and healthy subjects before and 24 h after segmental allergen challenge. Our proteomic analysis involves affinity depletion of six abundant BALF proteins, SDS-PAGE fractionation, protein in-gel digestion, and subsequent nano-LC-MS/MS analysis in conjunction with database searching for protein identification and semiquantitation. More than 1,500 distinct proteins were identified of which about 10% displayed significant up-regulation specific to the asthmatic patients after segmental allergen challenge. The differentially expressed proteins represent a wide spectrum of functional classes such as chemokines, cytokines, proteases, complement factors, acute phase proteins, monocyte-specific granule proteins, and local matrix proteins, etc. The majority of these protein expression changes are closely associated with many aspects of the pathophysiology of asthma, including inflammation, eosinophilia, airway remodeling, tissue damage and repair, mucus production, and plasma infiltration. Importantly a large portion of these proteins and their expression changes were identified for the first time from BALF, thus providing new insights for finding novel pathological mediators and biomarkers of asthma.
Comparing Strategies for Treating Emotion Perception Deficits in Traumatic Brain Injury

ObjectiveTo compare the efficacy of 2 strategies, errorless learning (EL) and self-instruction training (SIT), for remediating emotion perception deficits in individuals with traumatic brain injury (TBI). DesignRandomized controlled trial comparing groups receiving 25 hours (across 10 weeks) of treatment with either EL or SIT with waitlist control. Setting and ParticipantsEighteen adult outpatient volunteers with severe TBI who were at least 6 months postinjury. Main Outcomes MeasuresPhotograph-based emotion recognition tasks, The Awareness of Social Inferences Test, and questionnaire measures, for example, the Sydney Psychosocial Reintegration Scale. ResultsBoth treatment groups showed modest improvement in emotion perception ability. Limited evidence suggests that SIT may be a favorable approach for this type of remediation. ConclusionsAlthough further research is needed, there are reasons for optimism regarding rehabilitation of emotion perception following TBI.
N-Telopeptide of Type II Collagen Interacts with Annexin V on Human Chondrocytes

Type II collagen binds to chondrocytes through integrins and annexin V. While the potential integrin binding sites have been identified, it is unclear which domains bind to annexin V. Proteolytic fragments of collagen are known to modulate cell signaling pathways resulting in degradation of articular cartilage; it is unknown whether annexin V binds to the fragments. The focus of our study was to determine the binding of type II collagen and its fragments to chondrocytes using flow cytometry and fluorescence microscopy. The N-telopeptide binds to annexin V, whereas the C-telopeptide and triple helical peptides do not. These data suggest that the binding of the N-telopeptide of type II collagen is through annexin V, whereas binding of the C-telopeptide and the triple helical peptide to the surface of chondrocytes are potentially facilitated through other collagen receptors, such as integrins or cell-associated matrix proteins.
An empirical analysis of web page revisitation

There is a surprising lack of empirical research into user interaction with the web. This paper reports the results of an analysis of four months of logged data describing web use. The results update and extend earlier studies carried out in 1994 and 1995. We found that web page revisitation is a much more prevalent activity than previously reported (approximately 80% of pages have been previously visited by the user), that most pages are visited for a surprisingly short period of time, and that users maintain large (and possibly overwhelming) bookmark collections.
Tarantula Huwentoxin-IV Inhibits Neuronal Sodium Channels by Binding to Receptor Site 4 and Trapping the Domain II Voltage Sensor in the Closed Configuration*

Peptide toxins with high affinity, divergent pharmacological functions, and isoform-specific selectivity are powerful tools for investigating the structure-function relationships of voltage-gated sodium channels (VGSCs). Although a number of interesting inhibitors have been reported from tarantula venoms, little is known about the mechanism for their interaction with VGSCs. We show that huwentoxin-IV (HWTX-IV), a 35-residue peptide from tarantula Ornithoctonus huwena venom, preferentially inhibits neuronal VGSC subtypes rNav1.2, rNav1.3, and hNav1.7 compared with muscle subtypes rNav1.4 and hNav1.5. Of the five VGSCs examined, hNav1.7 was most sensitive to HWTX-IV (IC50 ∼ 26 nm). Following application of 1 μm HWTX-IV, hNav1.7 currents could only be elicited with extreme depolarizations (>+100 mV). Recovery of hNav1.7 channels from HWTX-IV inhibition could be induced by extreme depolarizations or moderate depolarizations lasting several minutes. Site-directed mutagenesis analysis indicated that the toxin docked at neurotoxin receptor site 4 located at the extracellular S3-S4 linker of domain II. Mutations E818Q and D816N in hNav1.7 decreased toxin affinity for hNav1.7 by ∼300-fold, whereas the reverse mutations in rNav1.4 (N655D/Q657E) and the corresponding mutations in hNav1.5 (R812D/S814E) greatly increased the sensitivity of the muscle VGSCs to HWTX-IV. Our data identify a novel mechanism for sodium channel inhibition by tarantula toxins involving binding to neurotoxin receptor site 4. In contrast to scorpion β-toxins that trap the IIS4 voltage sensor in an outward configuration, we propose that HWTX-IV traps the voltage sensor of domain II in the inward, closed configuration.