Miracle-dz/UniFAR-FTUs huggingface dataset:
Dealing with Non-Functional Requirements: Three Experimental Studies of a Process-Oriented Approach

Quality characteristics are vital for the success of software systems. To remedy the problems inherent in ad hoc development, a framework has been developed to deal with non-functional requirements (quality requirements or NFRs). Taking the premise that the quality of a product depends on the quality of the process that leads from high-Ievel NFRs to the product, the framework's objectives are to represent NFR-specific requirements, consider design tradeoffs, relate design decisions to IYFRs, justify the decisions, and assist defect detection. The purpose of this paper is to give an initial evaluation of the extent to which the framework's objectives are met. Three small portions of information systems were studied by the authors using the framework. The framework and empirical studies are evaluated herein, both from the viewpoint of domain experts who have reviewed the framework and studies, and ourselves as framework developers and users. The systems studied have a variety of characteristics, reflecting a variety of real application domains, and the studies deal with three important classes of NFRs for systems, namely, accuracy, security, and performance. The studies provide preliminary support for the usefulness of certain aspects of the framework, while raising some open issues.
Task-oriented teleoperation systems for groups of mobile robots with time-varying communication delays

This paper presents system framework and control algorithm for a human operator to remotely teleoperate a group of mobile robots over a network with time-varying delays. By utilizing the task-space technique adopted from control of redundant robotic manipulator, a human operator is able to command the task abstraction of a multi-robot system under the proposed architecture. Given the control gains, which are contingent on the upper bound of the round-trip delays, stability and tracking performance in the task space can be guaranteed. Moreover, the sub-task control in the null space of the multi-robot system can be utilized for mobile robots to achieve additional missions other than tracking the task functions. Experiments on a robotic manipulator and a group of differential-driven mobile robots are introduced to validate the proposed bilateral teleoperation system.
Pulmonary edema--hypoxia and overperfusion.

The report in this issue describing four subjects who had acute pulmonary edema after exertion at high altitude and who had congenital absence of the right pulmonary artery is intriguing, not just because it describes a medical curiosity but because of its wider implications. Approximately 5000 people have unilateral pneumonectomies annually in the United States, many for solitary lesions in otherwise normal lungs. Surely, one may expect that some of them travel to high altitude and that at least a few exercise there. Are they at high risk for acute pulmonary edema at high altitude? A study of this population .
The emerging physiological roles of the glycerophosphodiesterase family

The glycerophosphodiester phosphodiesterases are evolutionarily conserved proteins that have been linked to several patho/physiological functions, comprising bacterial pathogenicity and mammalian cell proliferation or differentiation. The bacterial enzymes do not show preferential substrate selectivities among the glycerophosphodiesters, and they are mainly dedicated to glycerophosphodiester hydrolysis, producing glycerophosphate and alcohols as the building blocks that are required for bacterial biosynthetic pathways. In some cases, this enzymatic activity has been demonstrated to contribute to bacterial pathogenicity, such as with Hemophilus influenzae. Mammalian glyerophosphodiesterases have high substrate specificities, even if the number of potential physiological substrates is continuously increasing. Some of these mammalian enzymes have been directly linked to cell differentiation, such as GDE2, which triggers motor neuron differentiation, and GDE3, the enzymatic activity of which is necessary and sufficient to induce osteoblast differentiation. Instead, GDE5 has been shown to inhibit skeletal muscle development independent of its enzymatic activity.
A self-organizing model for affective memory

Emotions are related to many different parts of our lives: from the perception of the environment around us to different learning processes and natural communication. Therefore, it is very hard to achieve an automatic emotion recognition system which is adaptable enough to be used in real-world scenarios. This paper proposes the use of a growing and self-organizing affective memory architecture to improve the adaptability of the Cross-channel Convolution Neural Network emotion recognition model. The architecture we propose, besides being adaptable to new subjects and scenarios also presents means to perceive and model human behavior in an unsupervised fashion enabling it to deal with never seen emotion expressions. We demonstrate in our experiments that the proposed model is competitive compared with the state-of-the-art approach, and how it can be used in different affective behavior analysis scenarios.
Absolute position total internal reflection microscopy with an optical tweezer

Significance Total internal reflection microscopy is a low noise, minimally invasive, near surface particle-tracking technique widely used in physics and biology for the precise investigation of surface forces and interactions and fluorescent imaging of live cells and single molecules. In total internal reflection microscopy (TIRM), a particle is tracked, with nanometer precision, by the intensity of light it scatters from the evanescent field of a totally internally reflected beam of light. The present work introduces the first to our knowledge in situ, absolute position calibration method for TIRM (and total internal reflection fluorescence microscopy), which has the potential to greatly expand its measurement capabilities and bring quantitative results to studies using this technique. A noninvasive, in situ calibration method for total internal reflection microscopy (TIRM) based on optical tweezing is presented, which greatly expands the capabilities of this technique. We show that by making only simple modifications to the basic TIRM sensing setup and procedure, a probe particle’s absolute position relative to a dielectric interface may be known with better than 10 nm precision out to a distance greater than 1 μm from the surface. This represents an approximate 10× improvement in error and 3× improvement in measurement range over conventional TIRM methods. The technique’s advantage is in the direct measurement of the probe particle’s scattering intensity vs. height profile in situ, rather than relying on assumptions, inexact system analogs, or detailed knowledge of system parameters for calibration. To demonstrate the improved versatility of the TIRM method in terms of tunability, precision, and range, we show our results for the hindered near-wall diffusion coefficient for a spherical dielectric particle.
Saccharomyces cerevisiae as a Model Organism: A Comparative Study

Background Model organisms are used for research because they provide a framework on which to develop and optimize methods that facilitate and standardize analysis. Such organisms should be representative of the living beings for which they are to serve as proxy. However, in practice, a model organism is often selected ad hoc, and without considering its representativeness, because a systematic and rational method to include this consideration in the selection process is still lacking. Methodology/Principal Findings In this work we propose such a method and apply it in a pilot study of strengths and limitations of Saccharomyces cerevisiae as a model organism. The method relies on the functional classification of proteins into different biological pathways and processes and on full proteome comparisons between the putative model organism and other organisms for which we would like to extrapolate results. Here we compare S. cerevisiae to 704 other organisms from various phyla. For each organism, our results identify the pathways and processes for which S. cerevisiae is predicted to be a good model to extrapolate from. We find that animals in general and Homo sapiens in particular are some of the non-fungal organisms for which S. cerevisiae is likely to be a good model in which to study a significant fraction of common biological processes. We validate our approach by correctly predicting which organisms are phenotypically more distant from S. cerevisiae with respect to several different biological processes. Conclusions/Significance The method we propose could be used to choose appropriate substitute model organisms for the study of biological processes in other species that are harder to study. For example, one could identify appropriate models to study either pathologies in humans or specific biological processes in species with a long development time, such as plants.
How self-organization can guide evolution

Self-organization and natural selection are fundamental forces that shape the natural world. Substantial progress in understanding how these forces interact has been made through the study of abstract models. Further progress may be made by identifying a model system in which the interaction between self-organization and selection can be investigated empirically. To this end, we investigate how the self-organizing thermoregulatory huddling behaviours displayed by many species of mammals might influence natural selection of the genetic components of metabolism. By applying a simple evolutionary algorithm to a well-established model of the interactions between environmental, morphological, physiological and behavioural components of thermoregulation, we arrive at a clear, but counterintuitive, prediction: rodents that are able to huddle together in cold environments should evolve a lower thermal conductance at a faster rate than animals reared in isolation. The model therefore explains how evolution can be accelerated as a consequence of relaxed selection, and it predicts how the effect may be exaggerated by an increase in the litter size, i.e. by an increase in the capacity to use huddling behaviours for thermoregulation. Confirmation of these predictions in future experiments with rodents would constitute strong evidence of a mechanism by which self-organization can guide natural selection.
Hole Filling of a 3D Model by Flipping Signs of a Signed Distance Field in Adaptive Resolution

When we use range finders to observe the shape of an object, many occluded areas may occur. These become holes and gaps in the model and make it undesirable for various applications. We propose a novel method to fill holes and gaps to complete this incomplete model. As an intermediate representation, we use a signed distance field (SDF), which stores euclidean signed distances from a voxel to the nearest point of the mesh model. By using an SDF, we can obtain interpolating surfaces for holes and gaps. The proposed method generates an interpolating surface that becomes smoothly continuous with real surfaces by minimizing the area of the interpolating surface. Since the isosurface of an SDF can be identified as being a real or interpolating surface from the magnitude of signed distances, our method computes the area of an interpolating surface in the neighborhood of a voxel both before and after flipping the sign of the signed distance of the voxel. If the area is reduced by flipping the sign, then our method changes the sign for the voxel. Therefore, we minimize the area of the interpolating surface by iterating this computation until convergence. Unlike methods based on partial differential equations (PDEs), our method does not require any boundary condition and the initial state that we use is automatically obtained by computing the distance to the closest point of the real surface. Moreover, because our method can be applied to an SDF of adaptive resolution, our method efficiently interpolates large holes and gaps of high curvature. We tested the proposed method with both synthesized and real objects and evaluated the interpolating surfaces.
Modeling the structure and evolution of discussion cascades

We analyze the structure and evolution of discussion cascades in four popular websites: Slashdot, Barrapunto, Meneame and Wikipedia. Despite the big heterogeneities between these sites, a preferential attachment (PA) model with bias to the root can capture the temporal evolution of the observed trees and many of their statistical properties, namely, probability distributions of the branching factors (degrees), subtree sizes and certain correlations. The parameters of the model are learned efficiently using a novel maximum likelihood estimation scheme for PA and provide a figurative interpretation about the communication habits and the resulting discussion cascades on the four different websites.
Antifungal Therapy: New Advances in the Understanding and Treatment of Mycosis

The high rates of morbidity and mortality caused by fungal infections are associated with the current limited antifungal arsenal and the high toxicity of the compounds. Additionally, identifying novel drug targets is challenging because there are many similarities between fungal and human cells. The most common antifungal targets include fungal RNA synthesis and cell wall and membrane components, though new antifungal targets are being investigated. Nonetheless, fungi have developed resistance mechanisms, such as overexpression of eﬄux pump proteins and biofilm formation, emphasizing the importance of understanding these mechanisms. To address these problems, different approaches to preventing and treating fungal diseases are described in this review, with a focus on the resistance mechanisms of fungi, with the goal of developing efficient strategies to overcoming and preventing resistance as well as new advances in antifungal therapy. Due to the limited antifungal arsenal, researchers have sought to improve treatment via different approaches, and the synergistic effect obtained by the combination of antifungals contributes to reducing toxicity and could be an alternative for treatment. Another important issue is the development of new formulations for antifungal agents, and interest in nanoparticles as new types of carriers of antifungal drugs has increased. In addition, modifications to the chemical structures of traditional antifungals have improved their activity and pharmacokinetic parameters. Moreover, a different approach to preventing and treating fungal diseases is immunotherapy, which involves different mechanisms, such as vaccines, activation of the immune response and inducing the production of host antimicrobial molecules. Finally, the use of a mini-host has been encouraging for in vivo testing because these animal models demonstrate a good correlation with the mammalian model; they also increase the speediness of as well as facilitate the preliminary testing of new antifungal agents. In general, many years are required from discovery of a new antifungal to clinical use. However, the development of new antifungal strategies will reduce the therapeutic time and/or increase the quality of life of patients.
Granulation of Sound in Video Games

Granulation of sound for games is becoming a more viable tool for sound artists as the processing power of game consoles continues to improve. Granulation is a relatively recent method of sound generation which allows for sampled sound to be modified in real-time to allow pitch to change independently of tempo among other audio effects. It has not been commonly used with the previous iterations of game platforms due to its relatively costly DSP overhead and number of voices required. With the current generation of game platforms, these limitations have been relaxed allowing for the increased possibility of real-time granulation in games. The combination of granulation and the output of a game's physics engine is a promising relationship as the physics engine can supply the large amount of real-time control data for the grain parameters that granulation requires. This paper investigates some current research in sound granulation and demonstrates some effective methods of utilizing granulation for games.
On Understanding Catastrophe: The case of highly severe inﬂuenza-like illness (Position Paper)

Computational epidemiology is a form of spatiotemporal reasoning in which social link structures are employed, and spatially explicit models are speciﬁed and executed. We point to issues thus far addressed neither by engineers, nor scientists, in the light of a use case focusing on catastrophic scenarios that assume the emergence of a highly unlikely but lethal and contagious strain of inﬂuenza. Our conclusion is that important perspectives are missing when dealing with policy issues resulting from scenario execution and analyses in computational epidemiology.
Evaluation of rutting potential of asphalts using resilient modulus test parameters

Rutting potential of asphalts can be evaluated in the laboratory by different tests. Any visco-elastic parameter of the mix evaluated at a high pavement temperature can be considered to be a possible parameter to distinguish mixes in terms of their rutting susceptibility. In this study, the potential of the time lag (between load and deformation) observed in a resilient modulus test as an appropriate parameter to explain the rutting resistance of different mixes has been examined. Resilient modulus is a parameter routinely evaluated by many agencies and is used as an input for design and evaluation of pavements. Time lag values were extracted from the resilient modulus test conducted at 35°C and 50°C on asphalt mixes prepared with (a) nine different types of binder and one aggregate gradation and (b) nine different aggregate gradations and with VG30 binder. A wheel tracking test was conducted on the mixes at 60°C. Time lag has been found to be sensitive to bitumen type and aggregate gradation. A strong correlation was observed between the time lag and rut depth measured in the wheel tracking test. It is evident from the present study that time lag measured from the resilient modulus test, which is conducted routinely by many agencies, has the potential to be used as a mix rutting parameter.
Silicon Waveguide Grating Couplers with Engineered Coupling Strength for Optimized Coupling

We describe simulation and experimental results of gratings for coupling between optical fibers and nanophotonic waveguides. The coupling strength was engineered to obtained Gaussian-like output profile. 1.2dB coupling loss is achieved to single-mode fibers. Preliminary experimental result for coupling with vertical fiber with chirped grating gives a 3dB coupling loss.
Next challenges for adaptive learning systems

Learning from evolving streaming data has become a 'hot' research topic in the last decade and many adaptive learning algorithms have been developed. This research was stimulated by rapidly growing amounts of industrial, transactional, sensor and other business data that arrives in real time and needs to be mined in real time. Under such circumstances, constant manual adjustment of models is in-efficient and with increasing amounts of data is becoming infeasible. Nevertheless, adaptive learning models are still rarely employed in business applications in practice. In the light of rapidly growing structurally rich 'big data', new generation of parallel computing solutions and cloud computing services as well as recent advances in portable computing devices, this article aims to identify the current key research directions to be taken to bring the adaptive learning closer to application needs. We identify six forthcoming challenges in designing and building adaptive learning (pre-diction) systems: making adaptive systems scalable, dealing with realistic data, improving usability and trust, integrat-ing expert knowledge, taking into account various application needs, and moving from adaptive algorithms towards adaptive tools. Those challenges are critical for the evolving stream settings, as the process of model building needs to be fully automated and continuous.
In search of the elusive ground truth: the internet's as-level connectivity structure

Despite significant efforts to obtain an accurate picture of the Internet's actual connectivity structure at the level of individual autonomous systems (ASes), much has remained unknown in terms of the quality of the inferred AS maps that have been widely used by the research community. In this paper we assess the quality of the inferred Internet maps through case studies of a set of ASes. These case studies allow us to establish the ground truth of AS-level Internet connectivity between the set of ASes and their directly connected neighbors. They also enable a direct comparison between the ground truth and inferred topology maps and yield new insights into questions such as which parts of the actual topology are adequately captured by the inferred maps, and which parts are missing and why. This information is critical in assessing for what kinds of real-world networking problems the use of currently inferred AS maps or proposed AS topology models are, or are not, appropriate. More importantly, our newly gained insights also point to new directions towards building realistic and economically viable Internet topology maps.
MoBiL: A Hybrid Feature Set for Automatic Human Translation Quality Assessment

In this paper we introduce MoBiL, a hybrid Monolingual, Bilingual and Language modelling feature set and feature selection and evaluation framework. The set includes translation quality indicators that can be utilized to automatically predict the quality of human translations in terms of content adequacy and language fluency. We compare MoBiL with the QuEst baseline set by using them in classifiers trained with support vector machine and relevance vector machine learning algorithms on the same data set. We also report an experiment on feature selection to opt for fewer but more informative features from MoBiL. Our experiments show that classifiers trained on our feature set perform consistently better in predicting both adequacy and fluency than the classifiers trained on the baseline feature set. MoBiL also performs well when used with both support vector machine and relevance vector machine algorithms.