Miracle-dz/UniFAR-FTUs huggingface dataset:
LARA: an aspect-oriented programming language for embedded systems

The development of applications for high-performance embedded systems is typically a long and error-prone process. In addition to the required functions, developers must consider various and often conflicting non-functional application requirements such as performance and energy efficiency. The complexity of this process is exacerbated by the multitude of target architectures and the associated retargetable mapping tools. This paper introduces an As-pect-Oriented Programming (AOP) approach that conveys domain knowledge and non-functional requirements to optimizers and mapping tools. We describe a novel AOP language, LARA, which allows the specification of compi-lation strategies to enable efficient generation of software code and hardware cores for alternative target architectures. We illustrate the use of LARA for code instrumentation and analysis, and for guiding the application of compiler and hardware synthesis optimizations. An important LARA feature is its capability to deal with different join points, action models, and attributes, and to generate an aspect intermediate representation. We present examples of our aspect-oriented hardware/software design flow for mapping real-life application codes to embedded platforms based on Field Programmable Gate Array (FPGA) technology.
SRF selectively controls tip cell invasive behavior in angiogenesis

Efficient angiogenic sprouting is essential for embryonic, postnatal and tumor development. Serum response factor (SRF) is known to be important for embryonic vascular development. Here, we studied the effect of inducible endothelial-specific deletion of Srf in postnatal and adult mice. We find that endothelial SRF activity is vital for postnatal growth and survival, and is equally required for developmental and pathological angiogenesis, including during tumor growth. Our results demonstrate that SRF is selectively required for endothelial filopodia formation and cell contractility during sprouting angiogenesis, but seems dispensable for vascular remodeling. At the molecular level, we observe that vascular endothelial growth factor A induces nuclear accumulation of myocardin-related transcription factors (MRTFs) and regulates MRTF/SRF-dependent target genes including Myl9, which is important for endothelial cell migration in vitro. We conclude that SRF has a unique function in regulating migratory tip cell behavior during sprouting angiogenesis. We hypothesize that targeting the SRF pathway could provide an opportunity to selectively target tip cell filopodia-driven angiogenesis to restrict tumor growth.
Progressive isosurface extraction from tetrahedral meshes

The authors present a technique for transforming a tetrahedral mesh into a progressive representation based on half edge collapses. This allows the efficient transmission of the mesh from a remote computer where the simulation was computed to a visualization computer. During the transmission, the user can start visualizing while the transmission is still in progress. We show a technique for progressively extracting isosurfaces from the progressive mesh. Starting with the base mesh, an isosurface for a specific value is computed and will locally be improved where a vertex is inserted into the mesh.
Noncovalent functionalization of carbon nanotubes for highly specific electronic biosensors

Novel nanomaterials for bioassay applications represent a rapidly progressing field of nanotechnology and nanobiotechnology. Here, we present an exploration of single-walled carbon nanotubes as a platform for investigating surface–protein and protein–protein binding and developing highly specific electronic biomolecule detectors. Nonspecific binding on nanotubes, a phenomenon found with a wide range of proteins, is overcome by immobilization of polyethylene oxide chains. A general approach is then advanced to enable the selective recognition and binding of target proteins by conjugation of their specific receptors to polyethylene oxide-functionalized nanotubes. This scheme, combined with the sensitivity of nanotube electronic devices, enables highly specific electronic sensors for detecting clinically important biomolecules such as antibodies associated with human autoimmune diseases.
How Buyer Experience in Online Auctions Affects the Dimensionality of Trust in Sellers: An Unexpected Finding

In commercial transactions, trust in sellers (TIS) is the degree of trust that buyers bestow upon sellers. The existence and level of TIS is obviously a factor determining whether buyers will buy. TIS is particularly important in consumer-to-consumer e-commerce transactions, such as online auctions, which are characterized by anonymity and asymmetric product quality information. Given the importance of TIS, the dimensionality of the construct was investigated using confirmatory factor analysis, employing buyer experience as a mediator. The expectation was that experienced subjects (subjects who have made a bid) would have a more detailed, differentiated conceptualization of TIS than inexperienced subjects (subjects who have never bid before), but the opposite was found. This is tentatively ascribed to the halo/horns effect, well-known from the performance appraisal literature. The managerial implications of this result, its possible effects on buyers' purchase intentions, and directions for future research are discussed.
Record process on the Continuum Random Tree

By considering a continuous pruning procedure on Aldous's Brownian tree, we construct a random variablewhich is distributed, conditionally given the tree, according to the probability law introduced by Janson as the limit distribution of the number of cuts needed to isolate the root in a critical Galton-Watson tree. We also prove that this random variable can be obtained as the a.s. limit of the number of cuts needed to cut down the subtree of the continuum tree spanned by n leaves.
Lost in Network Address Translation: Lessons from Scaling the World's Simplest Middlebox

To understand whether the promise of Network Function Virtualization can be accomplished in practice, we set out to create a software version of the simplest middlebox that keeps per flow state: the NAT. While there is a lot of literature in the wide area of SDN in general and in scaling middleboxes, we find that by aiming to create a NAT good enough to compete with hardware appliances requires a lot more care than we had thought when we started our work. In particular, limitations of OpenFlow switches force us to rethink load balancing in a way that does not involve the centralized controller at all. The result is a solution that can sustain, on six low-end commodity boxes, a throughput of 40Gbps with 64B packets, on par with industrial offerings but at a third of the cost. To reach this performance, we designed and implemented our NAT from scratch to be migration friendly and optimized for common cases (inbound traffic, many mappings). Our experience shows that OpenFlow-based load balancing is very limited in the context of NATs (and by relation NFV), and that scalability can only be ensured by keeping the controller out of the data plane.
Can faces verify blood-relations?

Humans can verify unknown parent-offspring and sibling pairs over unrelated subject pairs. A computational scheme to accomplish the task robustly, in the presence of challenges due to gender and age gap between related-pairs, finds many applications such as matching orphaned/lost children, identifying relatives from a photo collection. We propose one of the first computational schemes to verify sibling pairs along with parent-child relation. Towards the same, we present a novel ensemble metric learning scheme that combines the advantages of task-specific learning, adaptive prototype and feature selection and `late fusion'. We demonstrate the robustness of the scheme on a very large scale, real-world dataset. Specifically, we show that the gender difference among related-pairs leads to lower performance of traditional verification and metric learning algorithms. Through various experiments, we quantitatively study the robustness of the proposed scheme in the general and specific case of different gender related-pairs, achieving up to 80%, 75% accuracy for the parent-child and siblings relations respectively.
Two ellipse-based pruning methods for group nearest neighbor queries

Group nearest neighbor (GNN) queries are a relatively new type of operations in spatial database applications. Different from a traditional kNN query which specifies a single query point only, a GNN query has multiple query points. Because of the number of query points and their arbitrary distribution in the data space, a GNN query is much more complex than a kNN query. In this paper, we propose two pruning strategies for GNN queries which take into account the distribution of query points. Our methods employ an ellipse to approximate the extent of multiple query points, and then derive a distance or minimum bounding rectangle (MBR) using that ellipse to prune intermediate nodes in a depth-first search via an R$^*$-tree. These methods are also applicable to the best-first traversal paradigm. We conduct extensive performance studies. The results show that the proposed pruning strategies are more efficient than the existing methods.
Profiling of low molecular weight proteins in plasma from locally irradiated individuals

In studies reported in the 1960s and since, blood plasma from radiation-exposed individuals has been shown to induce chromosome damage when transferred into lymphocyte cultures of non-irradiated persons. This effect has been described to occur via clastogenic factors, whose nature is still mostly unknown. We have previously examined clastogenic factors from irradiated individuals by looking at plasma-induced DNA damage in reporter cells. Plasma was tested from ca. 30 locally exposed clinical patients receiving fractionated radiation treatment, as well as from three radiological accident victims exposed in 1994, albeit sampled 14 years post-accident. In the current work, proteome changes in the plasma from all subjects were examined with 2D gel electrophoresis-based proteomics techniques, in order to evaluate the level of protein expression with respect to the findings of a clastogenic factor effect. No differences were observed in protein expression due to local radiation exposure (pre- vs post-exposure). In contrast, plasma from the radiation accident victims showed alterations in the expression of 18 protein spots (in comparison with plasma from the control group). Among these, proteins such as haptoglobin, serotransferrin/transferrin, fibrinogen and ubiquitin-60S ribosomal protein L40 were observed, none of them likely to be clastogenic factors. In conclusion, the proteomics techniques applied were unable to identify changes in the proteome of the locally irradiated patients, whereas such differences were observed for the accident victims. However, association with the clastogenic effect or any specific clastogenic factor remains unresolved and thus further studies with more sensitive techniques are warranted.
LESFOIL: A European Project on Large Eddy Simulations Around a High-lift Airfoil at High Reynolds Number

This paper presents work carried out in the LESFOIL project, which studies Large Eddy Simulations (LES) of the flow around high-lift airfoils, during its first 24 months. The Reynolds number for the selected Aerospatiale A-airfoil is high (Re =2 .1·10 6 based on the freestream velocity and the chord length). If some kind of near-wall treatment could be used, the near-wall streaks would not be resolved and a much coarser grid could be used in the streamwise and spanwise directions. Two different near-wall treatment methodologies are used in the LESFOIL project, either hybrid LES-RANS (or DES) or wall functions. The angle of incidence is α =1 3.3 o , and a small separation bubble is, according to experiments, present on the suction side in the trailing edge region. Thus the method for treating the near-wall wall region must be able to handle both attached boundary layer flow, including streamwise pressure gradients, and separated flow. Subgrid-scale (SGS) models and parallelized numerical methods are two other subjects covered in the LESFOIL project. SGS models are developed and evaluated in simple flows such as channel flow. The hill flow (Reynolds number 10, 000 based on the hill height) is also used as a test case in which the performance of the wall treatment and SGS models can be evaluated in recirculating flow. The first part of the paper presents LES of channel flow. The second part presents hill flow computations. In the following section, LES around the A-airfoil is shown and conclusion are drawn in the final section.
Electrophysiological properties and carbamazepine sensitivity of epileptic human cortical neurons

There are between 20 and 30 drugs available for the treatment of seizures but despite this ~30% of the epilepsy population remains unresponsive to treatment. The underlying mechanisms behind drug resistance in temporal lobe epilepsy (TLE) have not been completely identiﬁed. The purpose of this study was to determine if distinct types of neuronal firing patterns occurring in human epileptic cortex are altered by carbamazepine (CBZ). We used whole-cell patch-clamp techniques combined with intracellular labeling to electrophysiologically and morphologically characterize neuronal populations in resected cortical tissue from patients with drug resistant epilepsy. We then determined if cells were uniformly resistant to carbamazepine or whether only a subset did not respond. Cortical spiking patterns were segregated in six main clusters: adapting high frequency cluster 1 and 2 (AHF1 and AHF2), adapting low frequency cluster 1 and 2 (ALF1 and ALF2), strongly adapting low frequency group (sALF) and one spike cluster (OS). A morphological analysis showed that some spiking patterns tend to be associated with specific neuronal morphology. OS group included only pyramidal cells while adapting high frequency groups (AHF1 &AHF2) displayed typical interneuron phenotype. Finally, we found that CBZ does not uniformly suppress neuronal activity as only ~27% of interneurons and ~40% of pyramidal cells were carbamazepine insensitive. These data indicate that in humans with DRE there is a heterogeneous CBZ insensitivity in all sub-populations of neurons.
The utility of polarized heliospheric imaging for space weather monitoring

A polarizing heliospheric imager is a critical next generation tool for space weather monitoring and prediction. Heliospheric imagers can track coronal mass ejections (CMEs) as they cross the solar system, using sunlight scattered by electrons in the CME. This tracking has been demonstrated to improve the forecasting of impact probability and arrival time for Earth‐directed CMEs. Polarized imaging allows locating CMEs in three dimensions from a single vantage point. Recent advances in heliospheric imaging have demonstrated that a polarized imager is feasible with current component technology.Developing this technology to a high technology readiness level is critical for space weather relevant imaging from either a near‐Earth or deep‐space mission. In this primarily technical review, we developpreliminary hardware requirements for a space weather polarizing heliospheric imager system and outline possible ways to flight qualify and ultimately deploy the technology operationally on upcoming specific missions. We consider deployment as an instrument on NOAA's Deep Space Climate Observatory follow‐on near the Sun‐Earth L1 Lagrange point, as a stand‐alone constellation of smallsats in low Earth orbit, or as an instrument located at the Sun‐Earth L5 Lagrange point. The critical first step is the demonstration of the technology, in either a science or prototype operational mission context.
The Impact of Implementing an "Incredible Years" Group Within a Family Living Unit in a Transitional Living Shelter: The Case of "Cathy"

Young children who experience homelessness have a markedly increased risk of behavior disorders. This case study illustrates the impact of the "Incredible Years" (IY) program, an evidence-supported group psychotherapy intervention, on "Cathy," a 4-year-old Latina girl with externalizing behaviors who was living in a transitional program for homeless women and children. Adaptations of the model to address the child and family’s trauma history and to allow for its implementation in a residential program are delineated. Qualitative and quantitative data support that the IY group had a positive impact on Cathy and her family and led to significant symptom decreases in externalizing behaviors and PTSD symptoms, as well as an improvement in the quality of child and parent interactions. Additionally, recommendations for future studies and treatment considerations and adaptations for this underserved population are addressed.
Stochastic Calculus of Wrapped Compartments

The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of Looping Sequences(CLS). While keeping the same expressiveness, CWC strongly simpliﬁes the development of auto-matic tools for the analysis of biological systems. The main simpliﬁcation consists in the removal ofthe sequencing operator, thus lightening the formal treatment of the patterns to be matched in a term(whose complexity in CLS is strongly affected by the variables matching in the sequences). We deﬁne a stochastic semantics for this new calculus. As an application we model the interac-tion between macrophages and apoptotic neutrophils and a mechanism of gene regulation in E.Coli.
Near-Capacity Three-Stage Downlink Iteratively Decoded Generalized Layered Space-Time Coding with Low Complexity

This paper presents a low complexity iteratively detected space-time transmission architecture based on generalized layered space-time (GLST) codes and irregular convolutional codes (IRCCs). The GLST combines the benefits of the vertical Bell-labs layered space-time (V-BLAST) scheme and space-time coding (STC). The GLST is serially concatenated with a unity-rate code (URC) and an IRCC which are used to facilitate near-capacity operation with the aid of an extrinsic information transfer (EXIT) chart based design. Reduced- complexity iterative successive interference cancellation (SIC) is employed in the GLST decoder, instead of the significantly more complex maximum likelihood (ML) detection. For the sake of approaching the maximum achievable rate, iterative decoding is invoked to achieve decoding convergence by exchanging extrinsic information across the three serial component decoders. Finally, it is shown that the SIC-based iteratively detected IRCC-URC-GLST system is capable of providing a trade-off between the affordable computational complexity and the system throughput.
Unsupervised Hierarchical Modeling of Driving Behavior and Prediction of Contextual Changing Points

An unsupervised learning method, called double articulation analyzer with temporal prediction (DAA-TP), is proposed on the basis of the original DAA model. The method will enable future advanced driving assistance systems to determine driving context and predict possible scenarios of driving behavior by segmenting and modeling incoming driving-behavior time series data. In previous studies, we applied the DAA model to driving-behavior data and argued that contextual changing points can be estimated as changing points of chunks. A sequence prediction method, which predicts the next hidden state sequence, was also proposed in a previous study. However, the original DAA model does not model the duration of chunks of driving behavior and is not able to do a temporal prediction of the scenarios. Our DAA-TP method explicitly models the duration of chunks of driving behavior on the assumption that driving-behavior data have a two-layered hierarchical structure, i.e., double articulation structure. For this purpose, the hierarchical Dirichlet process hidden semi-Markov model is used for explicitly modeling the duration of segments of driving-behavior data. A Poisson distribution is also used to model the duration distribution of driving-behavior segments. The duration distribution of chunks of driving-behavior data is also theoretically calculated using the reproductive property of the Poisson distribution. We also propose a calculation method for obtaining the probability distribution of the remaining duration of current driving words as a mixture of Poisson distribution with a theoretical approximation for unobserved driving words. This method can calculate the posterior probability distribution of the next termination time of chunks by explicitly modeling all probable chunking results for observed data. The DAA-TP was applied to a synthetic data set having a double articulation structure to evaluate its model consistency. To evaluate the effectiveness of DAA-TP, we applied it to a driving-behavior data set recorded at actual factory circuits. The DAA-TP could predict the next termination time of chunks more accurately than the compared methods. We also report the qualitative results for understanding the potential capability of DAA-TP.
Testing the Waters: Design of Replicable Experiments for Performance Assessment of Marine Robotic Platforms

Robotics is becoming part of our daily life through home automation (called domotic) and assistive applications that are taking place in habitations, up to industrial and service employments. With this strict cooperation between humans and robots, it is of absolute necessity to assess the robotic systems' capabilities and performance to ensure safety and reliability according to actual and significant criteria and parameters. Within this context, there are delays in technology transfer from research frameworks toward actual applicative scenarios. These delays are caused by the lack of methodologies and standardized procedures for the experiment execution and result comparison. A further restraint to the needed process of technology transfer is due to the inability to understand the actual capabilities of the systems and to be aware and confident (or not) about what they can be realistically employed for. In many cases, this can also turn into the inability to define specific regulations for the employment of robotic platforms to comply with the current laws. This is the case for marine robotics. Tethered vehicles [e.g., remotely operated vehicles (ROVs)] are considered part of the vessel equipment when they are operated from a ship (because of the physical connection provided by the cable). Conversely, whenever autonomous systems, such as unmanned surface vehicles (USVs) or autonomous underwater vehicles are commanded through an acoustic or Wi-Fi/radio communication link, they are considered as navigating platforms and are subject to the regulation in force. For the commercial employment of these vehicles, it is then necessary to strongly assess the vehicle's capabilities in a standardized way, to guarantee the operating performance and evaluate limitations of the target system.