Miracle-dz/UniFAR-FTUs huggingface dataset:
Symphony: A Framework for Accurate and Holistic WSN Simulation

Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles.
Adaptive Notch Filter for Harmonic Current Mitigation

This paper presents an effective technique for harmonic current mitigation using an adaptive notch filter (ANF) to estimate current harmonics. The proposed filter consists of multiple units of ANF connected in parallel structure; each unit is governed by two ordinary differential equations. The frequency estimation is carried out based on the output of these units. The simulation and experimental results show the ability of the proposed tracking scheme to accurately estimate harmonics. The proposed filter was implemented digitally in TMS320F2808 and used in the control of hybrid active power filter (HAPF). The theoretical expectations are verified and demonstrated experimentally.
A two-point algorithm for stereo visual odometry in open outdoor environments

This paper proposes a novel method to estimate relative poses for a calibrated stereo camera. Three corresponding points in 3D space are theoretically required to recover unconstraint motion which has six degrees of freedom. The proposed method solves this problem with only two 3D points by exploiting a common reference direction between poses. Two points are selected in accordance with the distance to the camera: one distant point is used for deriving a reference direction, and one near point is used for estimating accurate translation. The distance is computed by triangulation in stereo vision. The uncertainty of triangulation can be mitigated by the appropriate selection strategy. The experiments using synthetic and real data demonstrate the effectiveness and higher stability of the proposed method against image pixel noise.
Feature Papers to Celebrate the Landmarks of Catalysts

Catalysis is a critical scientific field that underpins much of the world’s chemical industry. For example, it is often quoted that catalysis plays a role in 90% of all industrial chemical products. This importance has led to numerous academic journals and specialized conferences on the subject, as practitioners seek outlets to publish their cutting-edge research on catalysis. [. ]
The Virtual Cell Modeling and Simulation Software Environment

The Virtual Cell (VCell; http://vcell.org/) is a problem solving environment, built on a central database, for analysis, modeling and simulation of cell biological processes. VCell integrates a growing range of molecular mechanisms, including reaction kinetics, diffusion, flow, membrane transport, lateral membrane diffusion and electrophysiology, and can associate these with geometries derived from experimental microscope images. It has been developed and deployed as a web-based, distributed, client-server system, with more than a thousand world-wide users. VCell provides a separation of layers (core technologies and abstractions) representing biological models, physical mechanisms, geometry, mathematical models and numerical methods. This separation clarifies the impact of modeling decisions, assumptions, and approximations. The result is a physically consistent, mathematically rigorous, spatial modeling and simulation framework. Users create biological models and VCell will automatically (i) generate the appropriate mathematical encoding for running a simulation, and (ii) generate and compile the appropriate computer code. Both deterministic and stochastic algorithms are supported for describing and running non-spatial simulations; a full partial differential equation solver using the finite volume numerical algorithm is available for reactiondiffusion-advection simulations in complex cell geometries including 3D geometries derived from microscope images. Using the VCell database, models and model components can be reused and updated, as well as privately shared among collaborating groups, or published. Exchange of models with other tools is possible via import/export of SBML, CellML, and MatLab formats. Furthermore, curation of models is facilitated by external database binding mechanisms for unique identification of components and by standardized annotations compliant with the MIRIAM standard. VCell is now open source, with its native model encoding language (VCML) being a public specification, which stands as the basis for a new generation of more customized, experiment-centric modeling tools using a new plug-in based platform.
Three-dimensional intracranial EEG monitoring in presurgical assessment of MRI-negative frontal lobe epilepsy

AbstractMagnetic resonance imaging (MRI)-negative epilepsy is associated with poor clinical outcomes prognosis. The present study was aimed to assess whether intracranial 3D interictal and ictal electroencephalography (EEG) findings, a combination of EEG at a different depth, in addition to clinical, scalp EEG, and positron emission tomography–computed tomography (PETCT) data help to predict outcome in a series of patients with MRI-negative frontal lobe epilepsy (FLE) after surgery.Patients with MRI-negative FLE who were presurgically evaluated by 3D-intracranial EEG (3D-iEEG) recording were included. Outcome predictors were compared in patients with seizure freedom (group 1) and those with recurrent seizures (group 2) at least 24 months after surgery.Forty-seven patients (15 female) were included in this study. MRI was found normal in 38 patients, whereas a focal or regional hypometabolism was observed in 33 cases. Twenty-three patients (48.9%) were seizure-free (Engel class I), and 24 patients (51.1%) continued to have seizures (12 were class II, 7 were class III, and 5 were class IV). Detailed analysis of intracranial EEG revealed widespread (>2 cm) (17.4%:75%; P = 0.01) in contrast to focal seizure onset as well as shorter latency to onset of seizure spread (5.9 ± 7.1 s; 1.4 ± 2.9 s; P = 0.016) and to ictal involvement of brain structures beyond the frontal lobe (21.8 ± 20.3 s; 4.9 ± 5.1 s; P = 0.025) in patients without seizure freedom.The results suggest that presurgical evaluation using 3D-iEEG monitoring lead to a better surgical outcome as seizure free in MRI-negative FLE patients.
Evolutionary-based conflict-free scheduling of collective communications on spidergon NoCs

The Spidergon interconnection network has become popular recently in multiprocessor systems on chips. To the best of our knowledge, algorithms for collective communications (CC) have not been discussed in the literature as yet, contrary to pair-wise routing algorithms. The paper investigates complexity of CCs in terms of lower bounds on the number of communication steps at conflict-free scheduling. The considered networks on chip make use of wormhole switching, full duplex links and all-port non-combining nodes. A search for conflict-free scheduling of CCs has been done by means of evolutionary algorithms and the resulting numbers of communication steps have been summarized and compared to lower bounds. Time performance of CCs can be evaluated from the obtained number of steps, the given start-up time and link bandwidth. Performance prediction of applications with CCs among computing nodes of the Spidergon network is thus possible.
Predication of Meaning of Bisyllabic Chinese Compound Words Using Back Propagation Neural Network

A three layer back propagation neural net is set up to study the functional dependency between the semantic class of a bisyllabic Chinese word and that of its two constituent Chinese characters. Simulations were performed using a three-layer back-propagation neural net with various combination of inputs. The inputs are (1) semantic classes of the constituent characters, (2) Entropy of the characters and (3) semantic strength[1] of the characters. Our simulations show that we can obtain the meaning class of a bisyllabic word from the meaning classes of its two constituent characters to an accuracy of 81 % by taking the semantic classes and semantic strength of the characters as input. This research establishes the dependency between the meaning class of a Chinese compound word and that of its two constituent characters.
The fine structure of the developing retina in Xenopus laevis.

The fine structure of the developing retinal cells in Xenopus laevis was studied from stages 26 to 36. At all stages examined the cells contained large numbers of free ribosomes, polysomes, small mitochondria, lipid and yolk droplets and scanty granular reticulum. A basal lamina covered the smooth internal margin of the optic vesicle and also the external aspect of the germinal pigment epithelial cells. At all stages examined zonulae adhaerentes occurred between adjacent cells at the outer aspect of the optic vesicle and maculae adhaerentes diminutae were occasionally observed. A third type of intercellular junction, characterized by a narrow gap of 3–9 nm, occurred throughout the retina up to stage 30 but only at the periphery beyond this stage. It is suggested that the disappearance of these junctions from the central portion of the retina may be correlated with retinal cell specification* which is known to occur at stage 30–31. These junctions may represent sites for the cell to cell transfer of small molecules which are required for cell differentiation. Since new cells are continually being added to the retina from the ciliary margin beyond stage 30 the persistence of junctions in this region may explain how these new cells also become specified. *
Blocking microsomal triglyceride transfer protein interferes with apoB secretion without causing retention or stress in the ER Published, JLR Papers in Press, February 16, 2003. DOI 10.1194/jlr.M300020-JLR200

Microsomal triglyceride transfer protein (MTP) is an intraluminal protein in the endoplasmic reticulum (ER) that is essential for the assembly of apolipoprotein B (apoB)-containing lipoproteins. In this study, we examine how the livers of mice respond to two distinct methods of blocking MTP function: Cre-mediated disruption of the gene for MTP and chemical inhibition of MTP activity. Blocking MTP significantly reduced plasma levels of triglycerides, cholesterol, and apoB-containing lipoproteins in both wild-type C57BL/6 and LDL receptor-deficient mice. While treating LDL receptor-deficient mice with an MTP inhibitor for 7 days lowered plasma lipids to control levels, liver triglyceride levels were increased by only 4-fold. Plasma levels of apoB-100 and apoB-48 fell by >90% and 65%, respectively, but neither apoB isoform accumulated in hepatic microsomes. Surprisingly, loss of MTP expression was associated with a nearly complete absence of apoB-100 in hepatic microsomes. Levels of microsomal luminal chaperone proteins [e.g., protein disulfide isomerase, glucose-regulated protein 78 (GRP78), and GRP94] and cytosolic heat shock proteins (HSPs) (e.g., HSP60, HSC, HSP70, and HSP90) were unaffected by MTP inhibition. These findings show that the liver responds rapidly to inhibition of MTP by degrading apoB and preventing its accumulation in the ER. The rapid degradation of secretion-incompetent apoB in the ER may block the induction of proteins associated with unfolded protein and heat shock responses.
MIREX 2012 AUDIO BEAT TRACKING EVALUATION : NEUROBEAT

In this paper, a beat tracking system is presented that simultaneously extracts downbeats, beats, tempo and meter. After generating beat activations by a bidirectional Long Short-Term Memory recurrent neural network, the temporal structure is infered using a Hidden Markov Model (HMM). From all MIREX beat tracking evaluation results between 2006 and 2012 it obtains average results for datasets MCK and MAZ, but performes best in four of ten measures for the SMC dataset.
The Do's and Don'ts of Neurofeedback Training: A Review of the Controlled Studies Using Healthy Adults

The goal of EEG neurofeedback (EEG-NFB) training is to induce changes in the power of targeted EEG bands to produce beneficial changes in cognitive or motor function. The effectiveness of different EEG-NFB protocols can be measured using two dependent variables: (1) changes in EEG activity and (2) behavioral changes of a targeted function (for therapeutic applications the desired changes should be long-lasting). To firmly establish a causal link between these variables and the selected protocol, similar changes should not be observed when appropriate control paradigms are used. The main objective of this review is to evaluate the evidence, reported in the scientific literature, which supports the validity of various EEG-NFB protocols. Our primary concern is to highlight the role that uncontrolled nonspecific factors can play in the results generated from EEG-NFB studies. Nonspecific factors are often ignored in EEG-NFB designs or the data are not presented, which means conclusions should be interpreted cautiously. As an outcome of this review we present a do's and don'ts list, which can be used to develop future EEG-NFB methodologies, based on the small set of experiments in which the proper control groups have excluded non-EEG-NFB related effects. We found two features which positively correlated with the expected changes in power of the trained EEG band(s): (1) protocols which focused on training a smaller number of frequency bands and (2) a bigger number of electrodes used for neurofeedback training. However, we did not find evidence in support of the positive relationship between power changes of a trained frequency band(s) and specific behavioral effects.
An Improved MAC Protocol for WBAN Through Modified Frame Structure

In WBAN environment, it is important to achieve energy efficiency of nodes implanting into human body. At the same time, a master also plays an important role in collecting data from nodes and controlling the nodes. By maintaining a master properly, any kinds of situation can be handled. Therefore, low power MAC protocol between a master and a node is highly required appropriately. A MAC protocol proposed in this paper aims to satisfy with these requirements and improve energy consumption rate that tends to grow high as the number of nodes increases. For the efficient and objective evaluation of the proposed MAC protocol, IEEE 802.15. 6 MAC is used to compare with it and we show that the advantage of the proposed MAC meet our expectation.
Early Detection of High-Risk Claims at the Workers' Compensation Board of British Columbia

We developed a combined decision-analysis and logistic-regression approach for identifying high-risk claims at the Workers' Compensation Board of British Columbia (WCB). The early detection of such claims and subsequent intervention is likely to reduce their eventual cost and to speed up worker rehabilitation. High-risk claims are extremely costly to the WCB; for the approximately 321,000 short-term disability claims with injury dates between 1989 and 1992, high-risk claims accounted for $1.2 billion (64 percent) of the total payment of $1.8 billion, even though they constituted only 4.2 percent of the claims. We developed separate logistic regression models for each injury type. We found that the age of worker and number of workdays lost were predictive of high-risk status. We used decision analysis to develop a classification rule that has high out-of-sample predictive power. The WCB has incorporated these results in a claims-profiling scorecard, which identifies claims needing early intervention. We estimate that our method saves the WCB $4.7 million annually.
Transforming Growth Factor β Promotes Neuronal Cell Fate of Mouse Cortical and Hippocampal Progenitors In Vitro and In Vivo: Identification of Nedd9 as an Essential Signaling Component

Transforming Growth Factor β (Tgfβ) and associated signaling effectors are expressed in the forebrain, but little is known about the role of this multifunctional cytokine during forebrain development. Using hippocampal and cortical primary cell cultures of developing mouse brains, this study identified Tgfβ-regulated genes not only associated with cell cycle exit of progenitors but also with adoption of neuronal cell fate. Accordingly, we observed not only an antimitotic effect of Tgfβ on progenitors but also an increased expression of neuronal markers in Tgfβ treated cultures. This effect was dependent upon Smad4. Furthermore, in vivo loss-of-function analyses using Tgfβ2−/−/Tgfβ3−/− double mutant mice showed the opposite effect of increased cell proliferation and fewer neurons in the cerebral cortex and hippocampus. Gata2, Runx1, and Nedd9 were candidate genes regulated by Tgfβ and known to be involved in developmental processes of neuronal progenitors. Using siRNA-mediated knockdown, we identified Nedd9 as an essential signaling component for the Tgfβ-dependent increase in neuronal cell fate. Expression of this scaffolding protein, which is mainly described as a signaling molecule of the β1-integrin pathway, was not only induced after Tgfβ treatment but was also associated with morphological changes of the Nestin-positive progenitor pool observed upon exposure to Tgfβ.
Benchmarking Next Generation Hardware Platforms: An Experimental Approach

Heterogeneous multi-cores–platforms comprised of both general purpose and accelerator cores—are becoming increasingly common. Further, with processor designs in which there are many cores on a chip, a recent trend is to include functional and performance asymmetries to balance their power usage vs. performance requirements. Coupled with this trend in CPUs is the development of high end interconnects providing low latency and high throughput communication. Understanding the utility of such next generation platforms for future datacenter workloads requires investigations that evaluate the combined effects on workload of (1) processing units, (2) interconnect, and (3) usage models. For benchmarks, then, this requires functionality that makes it possible to easily yet separately vary different benchmark attributes that affect the performance observed for application-relevant metrics like throughput, end-toend latency, and the effects on both due to the presence of other concurrently running applications. To obtain these properties, benchmarks must be designed to test different and varying, rather than fixed, combinations of factors pertaining to their processing and communication behavior and their respective usage patterns (e.g., degree of burstiness). The ‘Nectere’ benchmarking framework is intended for understanding and evaluating next generation multicore platforms under varying workload conditions. This paper demonstrates two specific benchmarks constructed with Nectere: (1) a financial benchmark posing low-latency challenges, and (2) an image processing benchmark with high throughput expectations. Benchmark characteristics can be varied along dimensions that include their relative usage of heterogeneous processors, like CPUs vs. graphics processors (GPUs), and their use of the interconnect through variations in data sizes and communication rates. With Nectere, one can create a mix of workloads to study the effects of consolidation, and one can create both singleand multi-node versions of these benchmarks. Results presented in the paper evaluate workload ability or inability to share resources like GPUs or network interconnects, and the effects of such sharing on applications running in consolidated systems.
Parallel Methods for Verifying the Consistency of Weakly-Ordered Architectures

Contemporary microprocessors use relaxed memory consistency models to allow for aggressive optimizations in hardware. This enhancement in performance comes at the cost of design complexity and verification effort. In particular, verifying an execution of a program against its system's memory consistency model is an NP-complete problem. Several graph-based approximations to this problem based on carefully constructed randomized test programs have been proposed in the literature, however, such approaches are sequential and execute slowly on large graphs of interest. Unfortunately, the ability to execute larger tests is tremendously important, since such tests enable one to expose bugs more quickly. Successfully executing more tests per unit time is also desirable, since it allows for one to check for a greater variety of errors in the memory subsystem by utilizing a more diverse set of tests. This paper improves upon existing work by introducing an algorithm that not only reduces the time complexity of the verification process, but also facilitates the development of parallel algorithms for solving these problems. We first show performance improvements from a sequential approach and gain further performance from parallel implementations in OpenMP and CUDA. For large tests of interest, our GPU implementation achieves an average application speedup of 26.36x over existing techniques in use at NVIDIA.
A Perfect Sampling Method for Exponential Random Graph Models

Generation of deviates from random graph models with non-trivial edge dependence is an increasingly important problem in the social and biological sciences. In recent years, work on this problem has been greatly facilitated by the use of discrete exponential families to parameterize random graph models, and by the availability of associated Markov chain Monte Carlo methods for approximate simulation of these families. Here, we introduce a method which allows perfect sampling from random graph models in exponential family form (aka “exponential random graph” models), using a variant of Coupling From The Past. We illustrate the use of the method via an application to the Markov graphs, a family of considerable importance within the social network literature. Applications of the method to other common cases (including the non-exponentially parameterized biased net models) are also discussed.