Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective synaptic interactions in subsampled nonlinear networks with strong coupling

A major obstacle to understanding neural coding and computation is the fact that experimental recordings typically sample only a small fraction of the neurons in a circuit. Measured neural properties are skewed by interactions between recorded neurons and the "hidden" portion of the network. To properly interpret neural data, we thus need a better understanding of the relationships between measured effective neural properties and the true underlying physiological properties. Here, we focus on how the effective spatiotemporal dynamics of the synaptic interactions between neurons are reshaped by coupling to unobserved neurons. We find that the effective interactions from a pre-synaptic neuron $r'$ to a post-synaptic neuron $r$ can be decomposed into a sum of the true interaction from $r'$ to $r$ plus corrections from every directed path from $r'$ to $r$ through unobserved neurons. Importantly, the resulting formula reveals when the hidden units have---or do not have---major effects on reshaping the interactions among observed neurons. As a prominent example, we derive a formula for strong impact of hidden units in random networks with connection weights that scale with $1/\sqrt{N}$, where $N$ is the network size---precisely the scaling observed in recent experiments.
Witnessing the Hierarchical Assembly of the Brightest Cluster Galaxy in a Cluster at z = 1.26

We have obtained a new high-resolution K′-band image of the central region of the rich X-ray cluster RX J0848.9+4452 at z = 1.26. We found that the brightest cluster galaxy (BCG) in the cluster is clearly separated into two distinct objects. Whereas the optical to near-infrared colors of the objects are consistent with the predictions of passive evolution models for galaxies formed at high redshift, the luminosities of the two galaxies are both considerably fainter than predicted by passive evolution of BCGs in low- and intermediate-redshift clusters. We argue that this is evidence of an ongoing merger of normal cluster elliptical galaxies to form the dominant galaxy in the core of RX J0848.9+4452. The two galaxies appear to point toward the nearby cluster ClG J0848+4453 and are aligned with the outer X-ray contour of their parent cluster, supporting a model of BCG formation by collimated infall along the surrounding large-scale structure.
Teamwork, coordination and customer relationship management skills: As important as technical skills in preparing our SE graduates

Teaching real-world software engineering (SE) skills requires innovative methods to facilitate students' learning technical as well as communication, teamwork, and analysis of ill-structured problems. In this paper we describe our experiences in designing and teaching these skills in our SE courses at the University of Victoria in the last 10 years. We describe the learning outcomes and instructional design in our courses, as well as the challenges we face.
High-Resolution Time-to-Digital Converter in Field Programmable Gate Array

Two high-resolution time-interval measuring systems implemented in a SRAM-based FPGA device are presented. The two methods ought to be used for time interpolation within the system clock cycle. We designed and built a PCB hosting a Virtex-5 Xilinx FPGA. We exploited high stability oscillators to test the two different architectures. In the first method, dedicated carry lines are used to perform fine time measurement, while in the second one a differential tapped delay line is used. In this paper we compare the two architectures and show their performance in terms of stability and resolution.
Predictors of secondary attention-deficit/hyperactivity disorder in children and adolescents 6 to 24 months after traumatic brain injury.

OBJECTIVE To assess the phenomenology and predictive factors of attention-deficit/hyperactivity disorder (ADHD) after traumatic brain injury (TBI), also called secondary ADHD (SADHD). METHOD Children without preinjury ADHD 5-14 years old with TBI from consecutive admissions (n = 143) to five trauma centers were observed prospectively from 6 to 12 months (12-month assessment) and from 12 to 24 months (24-month assessment) postinjury with semistructured psychiatric interviews. Injury and preinjury psychosocial variables were assessed. RESULTS SADHD occurred in 15 of 103 (15%) of participants between 6 and 12 months after injury and 17 of 82 (21%) in the second year after injury. SADHD was significantly (p < .05) comorbid with personality change due to TBI and new-onset disruptive behavior disorders. Preinjury adaptive function was a consistent predictor of SADHD. Regression analyses revealed that preinjury psychosocial adversity was an independent predictor of SADHD in the second year after injury. Neither severity of injury nor lesion location predicted SADHD from 6 to 24 months postinjury. CONCLUSIONS Determination of preinjury psychosocial adversity and the child's preinjury functioning during the index hospitalization would improve identification of children at highest risk of development of SADHD.
Targeting colorectal cancer with anti-epidermal growth factor receptor antibodies: focus on panitumumab

Panitumumab is a fully humanized monoclonal antibody with a high degree of affinity for the extracellular domain of the epidermal growth factor receptor. Phase II clinical evaluation of this drug, when administered as a single agent, in patients with metastatic colorectal cancer refractory to chemotherapy, demonstrated a modest objective radiographic response rate with acceptable toxicity; the most frequently observed side effect is rash. A randomized phase III study in subjects with chemotherapy-refractory metastatic colorectal cancer documented a progression-free survival advantage in subjects treated with panitumumab plus best supportive care versus best supportive care alone; a difference in survival was not observed, likely due to the high cross over rate. Primary tumor KRAS mutation analysis performed in this study indicated that the benefit was confined to those patients whose tumors did not contain a KRAS mutation. Further studies with panitumumab will be required to develop biomarkers of response and to determine if panitumumab has a role in combination with cytotoxic chemotherapy. This article summarizes the current state-of-the-science knowledge on panitumumab therapy in the treatment of advanced colorectal cancer.
VHDL Implementation of Interval Arithmetic Algorithms for Single Precision Floating Point Numbers

This paper proposes a new approach where the design and implementation of single precision (32bit) Interval Arithmetic Adder/subtractor unit is carried using VHDL for computing interval arithmetic operations & functions suited for hardware implementation. The algorithms are coded in VHDL & validated through extensive simulation . This VHDL code is then synthesized by synopsys tool to generate the gate level net list that can be implemented on the FPGA using Xilinx. This paper shows that interval arithmetic can be efficiently implemented in terms of performance and cost.
A performance comparison of contemporary algorithmic approaches for automated analysis operations on feature models

The formalization of variability models (e.g. feature models) is a prerequisite for the automated analysis of these models. The efficient execution of the analysis operations depends on the selection of well-suited solver implementations. Regarding feature models, on the one hand, the formalization with Boolean expressions enables the use of SAT or BDD solvers. On the other hand, feature models can be transformed into a Constraint-Satisfaction Problem (CSP) in order to use CSP solvers for validation. This paper presents a performance comparison regarding nine contemporary high-performance solvers, three for each base problem structure (BDD, CSP, and SAT). Four operations on 90 feature models are run on each solver. The results will in turn clear the way for new improvements regarding the automatic verification of software product lines, since the efficient execution of analysis operations is essential to such automatic verification approaches.
Evaluating the Impact of Management Traffic and Self-Similarity on Wireless Network Performance

This article makes a taxonomic study of wireless traffic using a model of self-similarity based on traffic components at the link, network and transport layer. We evaluate applications performance using two different simulation scenarios in which the traffic is defined according to the statistical parameters observed in real traffic. The simulations evaluate network performance using different compositions of wireless management traffic and several degrees of self-similarity. The results show a better performance for delay and loss when certain management traffic components are removed, even for the cases when the traffic is self-similar. The results may help to identify unwanted management traffic components for certain network scenarios.
A simple ranging technique based on received signal strength measurements in a narrowband 2.4 GHz channel: A space diversity approach

Indoor positioning using RF signals is usually a difficult task, due to multipath phenomena, that, especially for narrowband transmissions, can deeply affect signal propagation. In this paper, a simple technique for improving the accuracy of a received signal strength based ranging system is proposed. It is shown that, using narrowband low power transmissions in the 2.4 GHz channel and a multiple input multiple output approach, multipath effects can be mitigated, leading to a significant improvement in accuracy.
Climatically-active gases in the Eastern Boundary Upwelling and Oxygen Minimum Zone (OMZ) systems

The EBUS (Eastern Boundary Upwelling Systems) and OMZs (Oxygen Minimum Zone) contribute very significantly to the gas exchange between the ocean and the atmosphere, notably with respect to the greenhouse gases (hereafter GHG). From in-situ ocean measurements, the uncertainty of the net global ocean-atmosphere CO2 fluxes is between 20 and 30%, and could be much higher in the EBUS-OMZ. Off Peru, very few in-situ data are available presently, which justifies alternative approaches for assessing these fluxes. In this contribution we introduce.
Parallel Algorithms for High-Dimensional Proximity Joins

We consider the problem of parallelizing highdimensional proximity joins. We present a parallel multidimensional join algorithm based on an the epsilon-kdB tree and compare it with the more common approach of space partitioning. An evaluation of the algorithms on an IBM SP2 shared-nothing multiprocessor is presented using both synthetic and real-life datasets. We also examine the effectiveness of the algorithms in the context of a specific data-mining problem, that of finding similar time-series. The empirical results show that our algorithm exhibits good performance and scalability, as well an ability to handle dataskew.
Comprehensive Analysis of the Effects of Escherichia coli ORFs on Protein Translation Reaction*S

Protein synthesis is one of the most important reactions in the cell. Recent experimental studies indicated that this complex reaction can be achieved with a minimum complement of 36 proteins and ribosomes by reconstituting an Escherichia coli-based in vitro translation system with these protein components highly purified on an individual basis. From the protein-protein interaction (PPI) network of E. coli proteins, these minimal protein components are known to interact physically with large numbers of proteins. However, it is unclear what fraction of E. coli proteins are linked functionally with the minimal protein synthesis system. We investigated the effects of each of the 4194 E. coli ORF products on the minimal protein synthesis system; at least 12% of the entire ORF products, a significant fraction of the gene product of E. coli, affect the activity of this system. Furthermore 34% of these functional modifiers present in the PPI network were shown by mapping to be directly linked (i.e. to interact physically) with the minimal components of the PPI network. Topological analysis of the relationships between modifiers and the minimal components in the PPI network indicated clustering of the minimal components. The modifiers showed no such clustering, indicating that the location of functional modifiers is spread across the PPI network rather than clustering close to the minimal protein components. These observations may reflect the evolutionary process of the protein synthesis system.
Nuclear lamins: key regulators of nuclear structure and activities

• The lamin molecule ‐ Domain organization of lamins ‐ Lamins are divided to type A and type B ‐ Post‐translational processing of lamin molecules ‐ Lamin molecules in evolution • The supramolecular assembly of lamins ‐ From lamin monomer to lamin dimer ‐ From dimers to filaments ‐ The roles of the different domains in the assembly of lamins ‐ Laminopathic mutations affect lamin filament assembly ‐ Lamin assembly in vivo • Lamin‐binding proteins ‐ Lamins, chromatin and epigenesis ‐ Lamin binding to DNA ‐ Lamin binding to chromatin ‐ Lamins affect chromatin organization and epigenesis ‐ Lamins are involved in many nuclear functions ‐ Lamins determine the shape and stiffness of the nucleus ‐ Lamins and DNA replication ‐ Lamins in transcription and splicing • Lamins and aging ‐ Lamins and laminopathies ‐ Mutations in lamins and their associated proteins causing ‘laminopathies’ ‐ Animal models for laminopathies ‐ Molecular models for laminopathies • Lamins and stem cells ‐ The Notch pathway ‐ The Wnt/β‐catenin pathway ‐ Other pathways • Lamins and cancer ‐ Lamins as biomarkers for cancer ‐ Lamins and cancer regulating pathways ‐ Lamins and cancer related aneuploidy • Lamin and viruses
Robust fuzzy model-following control of robot manipulators

A robust fuzzy model-following control system is proposed for the control of robot manipulators. The application field to n-link robot manipulators with torque disturbance and measurement noise is addressed. The control objective is obtained by tailoring a nominal adaptation process of parameters to implement appropriate function approximation and facilitating a self-tuning mechanism on the consequent membership functions to overcome the equivalent uncertainty. A novel fuzzy system with self-tuning mechanism provides robust property and the rule-base in the form of "IF situation THEN the control input". The proposed multilayer fuzzy logic controller can improve both transient and stability margins without a priori knowledge about the dynamic model or parameters of the robotic system. Using the Lyapunov stability method, the uniform ultimate boundedness of tracking error has been proved. The performance is demonstrated by simulating the control of a two-link robot in various situations.
An Efficient Task Clustering Heuristic for Scheduling DAGs on Multiprocessors

For task clustering with no duplication, the DSC algorithm of Gerasoulis and Yang is empirically the best known algorithm to date in terms of both speed and solution quality. The DSC algorithm is based on the critical path method. In this paper, we present an algorithm called CASS-II for task clustering with no duplication which is competitive to DSC in terms of both speed and solution quality. With respect to speed, CASS-II is better than DSC: it has a time complexity of O(jEj + jV j lg jV j), as opposed to DSC’s O((jEj + jV j) lg jV j). Indeed, our experimental results show that CASS-II is between 3 to 5 times faster than DSC. (It is worth pointing out that we used the C code for DSC developed by the authors of the DSC algorithm. The C code for CASS-II was developed by the authors of this paper.) With respect to solution quality, experimental results show that CASS-II is virtually as good as DSC and, in fact, even outperforms DSC for very fine grain DAGs (granularity less than 0.6).
Influence of Asymmetry and Driving Forces on the Propulsion of Bubble-Propelled Catalytic Micromotors

Bubble-propelled catalytic micromotors have recently been attracting much attention. A bubble-propulsion mechanism has the advantage of producing a stronger force and higher speed than other mechanisms for catalytic micromotors, but the nature of the fluctuated bubble generation process affects the motions of the micromotors, making it difficult to control their motions. Thus, understanding of the influence of fluctuating bubble propulsion on the motions of catalytic micromotors is important in exploiting the advantages of bubble-propelled micromotors. Here, we report experimental demonstrations of the bubble-propelled motions of propeller-shaped micromotors and numerical analyses of the influence of fluctuating bubble propulsion on the motions of propeller-shaped micromotors. We found that motions such as trochoid-like motion and circular motion emerged depending on the magnitude or symmetricity of fluctuations in the bubble-propulsion process. We hope that those results will help in the construction and application of sophisticated bubble-propelled micromotors in the future.
An Empirical Comparison of Compiler Testing Techniques

Compilers, as one of the most important infrastructure of today’s digital world, are expected to be trustworthy. Different testing techniques are developed for testing compilers automatically. However, it is unknown so far how these testing techniques compared to each other in terms of testing effectiveness: how many bugs a testing technique can find within a time limit. In this paper, we conduct a systematic and comprehensive empirical comparison of three compiler testing techniques, namely, Randomized Differential Testing (RDT), a variant of RDT—Different Optimization Levels (DOL), and Equivalence Modulo Inputs (EMI). Our results show that DOL is more effective at detecting bugs related to optimization, whereas RDT is more effective at detecting other types of bugs, and the three techniques can complement each other to a certain degree. Furthermore, in order to understand why their effectiveness differs, we investigate three factors that influence the effectiveness of compiler testing, namely, efficiency, strength of test oracles, and effectiveness of generated test programs. The results indicate that all the three factors are statistically significant, and efficiency has the most significant impact.
Action recognition in spatiotemporal volume

We recognize actions and activities in video sequences as distinguishing patterns in the 3D spatiotemporal volume of motion energy. Local motion descriptors, which capture highly discriminative invariant motion characteristics in a spherical neighborhood, are computed in the 3D volume at points of salient motion to represent actions or activities in video sequences. Two actions are then matched based on the similarity between their representing motion descriptors. Our action recognition algorithm using the new motion descriptors has achieved an accuracy rate of 98.6% on the Weizmann action dataset [1].
System analysis via integral quadratic constraints

It is demonstrated how a number of widely used tools for stability analysis can be conveniently unified and generalized using integral quadratic constraints (IQCs). The approach has emerged under a combination of influences from the western and Russian traditions of control theory. An IQC based stability theorem is presented, which covers classical small gain conditions with anti-causal multipliers, but gains flexibility by avoiding extended spaces and truncated signals. <<ETX>>
Monte Carlo Studies of the Orientational Order-Disorder Phase Transition in Solid Ammonium Chloride

Monte Carlo methods are used to study the phase transition in ammonium chloride from the orientationally ordered $\delta$ phase to the orientationally disordered $\gamma$ phase. An effective pair potential is used to model the interaction between ions. Thermodynamic properties are computed in the canonical and isothermal-isobaric ensembles. Each ammonium ion is treated as a rigidly rotating body and the lattice is fixed in the low-temperature CsCl geometry. A simple extension of the Metropolis Monte Carlo method is used to overcome quasiergodicity in the rotational sampling. In the constant-$NVT$ calculations the lattice is held rigid; in the constant-$NpT$ calculations the lattice parameter is allowed to fluctuate. In both ensembles the order parameter rapidly falls to zero in the range (200 - 250)K, suggesting that the model disorders at a temperature in fair agreement with the experimental disordering temperature (243K). Peaks in the heat capacity and thermal expansivity curves are also found in the same temperature range.
Balance Between Creativity and Methodology in Software Projects

Taking into account trends of innovation in economy and increasing interest in applying creativity techniques in computer science, this paper focuses on relationship between creativity and methodology in software project. First, it extracts useful knowledge about creativity from creativity research. Then, it makes an attempt to combine creativity issues and dimensions with concepts from software project area. It presents also lessons learned from analysis of diploma projects in computer science in which students were encouraged to use creativity skills and techniques. Both theoretical analysis on the edge of creativity and methodology and lessons learned show that there is a need to balance creativity and methodology in software project.
Optimal nonlinear codes for the perception of natural colours

We discuss how visual nonlinearity can be optimized for the precise representation of environmental inputs. Such optimization leads to neural signals with a compressively nonlinear input-output function the gradient of which is matched to the cube root of the probability density function (PDF) of the environmental input values (and not to the PDF directly as in histogram equalization). Comparisons between theory and psychophysical and electro-physiological data are roughly consistent with the idea that parvocellular (P) cells are optimized for precision representation of colour: their contrast-response functions span a range appropriately matched to the environmental distribution of natural colours along each dimension of colour space. Thus P cell codes for colour may have been selected to minimize error in the perceptual estimation of stimulus parameters for natural colours. But magnocellular (M) cells have a much stronger than expected saturating nonlinearity; this supports the view that the function of M cells is mainly to detect boundaries rather than to specify contrast or lightness.
Composition and calibration of a custom made omnidirectional camera

Conventional perspective cameras have been used before to create 3D camera systems. However, these systems are hindered by the field of view of the cameras, which limit the angle of the scene that can be reconstructed. Augmenting these systems to larger reconstructed scene angle requires more cameras or increasing the field of view of the cameras. A 3D camera system is introduced which utilizes omnidirectional cameras. These cameras are capable of capturing the scene in 360 degrees, and only a limited number of cameras are required to reconstruct the entire surrounding. In this article the design, construction and calibration of omnidirectional cameras are discussed. The used camera model is presented which allows us to use an omnidirectional camera as a perspective camera, and the distortion model that is suitable for correcting precision problems of the assembly process.
New object-oriented segmentation algorithm based on the CNN paradigm

This paper illustrates a new object-oriented segmentation algorithm based on the cellular neural network (CNN) paradigm. The approach, which exploits rigorous model of the image contours, presents two remarkable features: 1) it provides more accurate segmented objects than the ones obtained by other CNN-based techniques; 2) it makes use of CNN templates that take into account the hardware characteristics imposed by the CNNUM. Results carried out for benchmark video sequences highlight the capabilities of the proposed technique.