Miracle-dz/UniFAR-FTUs huggingface dataset:
INSTITUTO DE COMPUTAÇÃO UNIVERSIDADE ESTADUAL DE CAMPINAS MR-Image Segmentation of Brain Tissues based on Bias Correction and Optimum-Path Forest Clustering

Magnetic resonance (MR) image segmentation of brain tissues has become crucial to advance research, diagnosis and treatment procedures in Neurology. Despite the large number of published papers, there is no standard method suitable for all cases. We present here a fast, accurate and robust to anatomical variations approach based on inhomogeneity/bias correction and clustering by optimum-path forest (OPF). The method assumes skull stripping and corrects voxel values in the brain based on local estimations of the white-matter intensities. We use two segmentation steps with different parameters (e.g., graph topologies and image features). The first separates the cerebrospinal fluid (CSF) from the white-matter (WM) and gray-matter (GM) tissues and the second separates WM from GM voxels. In each step, random samples are uniformly estimated to form a small unlabeled training set. Groups of training voxels with similar features are obtained by OPF clustering, a class label is assigned to each group and the labels are propagated to the remaining voxels. Each step is also repeated a few times (e.g., 3) to take the majority vote as the final label. The method was evaluated using several data sets from three protocols; control subjects, phantoms and patients; quantitative and qualitative evaluation methodologies; and two state-of-the-art approaches. The results show that it can solve brain tissue segmentation in less than 5 minutes on modern PCs with higher accuracy and robustness than the baseline approaches.
A Rosetta stone for epidemiology: genomic risk profile scores contain clues related to modifiable risk factors

In this volume, we are proud to present two invited editorials that provide guidance for future gene-by-environment interaction (G × E) studies. Ruud van Winkel (2014) argues that the field needs to undergo a conceptual shift related to our expectations – we need to shift focus away from the assumption that G × E studies are new tools to help ‘hunt for genes’. Instead, these studies can help partition subgroups of affected individuals, who are more likely to share aetiology and pathogenetic mechansims. This partitioning, in turn, may help to identify biological mechanisms associated with relevant environmental exposures (henceforth exposures) and/or risk alleles. Van Winkel reminds us that clinical diagnostic boundaries (which have been used to define caseness in genomewide association studies; GWAS), do not capture genetic nor neurobiological reality. Nor should they define tight linkages between exposures and psychiatric disorders.
Using quadratic programming to estimate feature relevance in structural analyses of music

To identify repeated patterns and contrasting sections in music, it is common to use self-similarity matrices (SSMs) to visualize and estimate structure. We introduce a novel application for SSMs derived from audio recordings: using them to learn about the potential reasoning behind a listener's annotation. We use SSMs generated by musically-motivated audio features at various timescales to represent contributions to a structural annotation. Since a listener's attention can shift among musical features (e.g., rhythm, timbre, and harmony) throughout a piece, we further break down the SSMs into section-wise components and use quadratic programming (QP) to minimize the distance between a linear sum of these components and the annotated description. We posit that the optimal section-wise weights on the feature components may indicate the features to which a listener attended when annotating a piece, and thus may help us to understand why two listeners disagreed about a piece's structure. We discuss some examples that substantiate the claim that feature relevance varies throughout a piece, using our method to investigate differences between listeners' interpretations, and lastly propose some variations on our method.
A q-Matrix Encoding Extending the Parikh Matrix Mapping

We introduce a generalization of the Parikh mapping called the Parikh q-matrix encoding, which takes its values in matrices with polynomial entries. The encoding represents a word w over a k-letter alphabet as a (k + 1)-dimensional upper-triangular matrix with entries that are nonnegative integral polynomials in variable q. Putting q = 1, we obtain the morphism introduced by Mateescu, Salomaa, Salomaa, and Yu [6] which extends the Parikh mapping to (k + 1)-dimensional (numerical) matrices. The Parikh q-matrix encoding however, produces matrices that carry more information about w than the numerical Parikh matrix. In fact it is injective. The entries of the q-matrix image of w under this encoding is constructed by q-counting the number of occurrences of certain words as scattered subwords of w. This construction is distinct from the Parikh q-matrix mapping into k-dimensional upper-triangular matrices with integral polynomial entries introduced by Egecioglu and Ibarra [2].
Adaptive Multi-beam Transmission of Uncompressed Video over 60GHz Wireless Systems

Millimeter wave (mmWave) technology provides possibility to replace uncompressed high-definition video cables (such as HDMI, DVI, or DisplayPort) with wireless links. However, it is very challenging to meet the strict quality of service (QoS) requirements from uncompressed video streaming applications since 60 GHz wireless signals can be easily blocked by human body and other obstacles. In this paper, we first discuss the specific technical challenges in mmWave system to support long-time stable video streaming. Then, we propose a new adaptive multi-beam transmission solution in which pixel partitioning, switched multi- beam transmission, and fast video format adaptation are key techniques to solve the raised technical problems. Initial performance evaluation shows that our approach can achieve high- quality video streaming performance.
Experiences and Observations from the NoAH Infrastructure

Monitoring large chunks of unused IP address space yields interesting observations and useful results. However, the volume and diversity of the collected data makes the extraction of information a challenging task. Additionally, the maintenance of the monitoring infrastructure is another demanding and time-consuming effort. To overcome these problems, we present several visualization techniques that enable users to observe what happens in their unused address space over arbitrary time periods and provide the necessary tools for administrators to monitor their infrastructure. Our approach, which is based on open-source standard technologies, transforms the raw information at the network level and provides a customized and Web-accessible view. In this paper, we present the design, implementation and early experiences of the visualization techniques and tools deployed for the NoAH project, a large-scale honey pot-based infrastructure. Additionally, we provide a traffic analysis of data collected over a six month period of our infrastructure's operation. During the data collection period, we observed that the number of attackers continually increased as did the volume of traffic they generated. Furthermore, interesting patterns for specific types of traffic have been identified, such as the diurnal cycle of the traffic targeting TCP port 445 (Windows Directory Services), the port that receives the largest volume of attack traffic.
A New Action Description Scheme for Informal Reasoning

Reasoning about Actions has an important place in the development of Intelligent Agents. While reasoning about Actions, Action Representation plays an important role. General practice is to use Preconditions and Posteffects for defining an Action. We believe that for an agent that assists humans in making decisions for daily life in a Smart Home environment, Preconditions are not adequate to represent the complexity due to the huge number of different situations resulting from various factors affecting a decision. We propose an extension to this basic idea by introducing the concept of Hindering and Supporting factors for Actions and argue that this can describe many Informal Reasoning situations more succinctly than traditional Action description schemes. We present the reasoning algorithm based on this new Action Description and show with examples how this new scheme helps in reaching more appropriate decisions in a Smart Home environment and hence improving the quality of living for its inhabitants.
Efficient Similarity Search by Reducing I/O with Compressed Sketches

Sketches are compact bit string representations of objects. Objects that have the same sketch are stored in the same database bucket. By calculating the hamming distance of the sketches, an estimation of the similarity of their respective objects can be obtained. Objects that are close to each other are expected to have sketches with small hamming distance values. This estimation helps to schedule the order in which buckets are visited during search time. Recent research has shown that sketches can effectively approximate $L_1$ and $L_2$ distances in high dimensional settings. A remaining task is to provide a general sketch for arbitrary metric spaces. This paper presents a novel sketch based on generalized hyperplane partitioning that can be employed on arbitrary metric spaces. The core of the sketch is a heuristic that tries to generate balanced partitions. The indexing method AESA stores all the distances among database objects, and this allows it to perform a small number of distance computations. Experimental evaluations show that given a good early termination strategy, our algorithm performs up to one order of magnitude fewer distance operations than AESA in string spaces. Comparisons against other methods show greater gains. Furthermore, we experimentally demonstrate that it is possible to reduce the physical size of the sketches by a factor of ten with different run length encodings.
Black holes in general relativity

What is going on (as of August 2008) at the interface between theoretical general relativity, string-inspired models, and observational astrophysics? Quite a lot. In this mini-survey I will make a personal choice and focus on four specific questions: Do black holes "exist"? (For selected values of the word "exist".) Is black hole formation and evaporation unitary? Can one mimic a black hole to arbitrary accuracy? Can one detect the presence of a horizon using local physics?
From Pathways to Biomolecular Events: Opportunities and Challenges

The construction of pathways is a major focus of present-day biology. Typical pathways involve large numbers of entities of various types whose associations are represented as reactions involving arbitrary numbers of reactants, outputs and modifiers. Until recently, few information extraction approaches were capable of resolving the level of detail in text required to support the annotation of such pathway representations. We argue that event representations of the type popularized by the BioNLP Shared Task are potentially applicable for pathway annotation support. As a step toward realizing this possibility, we study the mapping from a formal pathway representation to the event representation in order to identify remaining challenges in event extraction for pathway annotation support. Following initial analysis, we present a detailed study of protein association and dissociation reactions, proposing a new event class and representation for the latter and, as a step toward its automatic extraction, introduce a manually annotated resource incorporating the type among a total of nearly 1300 annotated event instances. As a further practical contribution, we introduce the first pathway-to-event conversion software for SBML/CellDesigner pathways and discuss the opportunities arising from the ability to convert the substantial existing pathway resources to events.
Design and Implementation of a High Quality and High Throughput TRNG in FPGA

This paper focuses on the design and implementa- tion of a high-quality and high-throughput true-random number generator (TRNG) in FPGA. Various practical issues which we encountered are highlighted and the influence of the various parameters on the functioning of the TRNG are discussed. We also propose a few values for the parameters which use the minimum amount of the resources but still pass common random number generator test batteries such as DieHard and TestU01.
Evolution and Expression Plasticity of Opsin Genes in a Fig Pollinator, Ceratosolen solmsi

Figs and fig pollinators have co-evolved species-specific systems of mutualism. So far, it was unknown how visual opsin genes of pollinators have evolved in the light conditions inside their host figs. We cloned intact full-length mRNA sequences of four opsin genes from a species of fig pollinator, Ceratosolen solmsi, and tested for selective pressure and expressional plasticity of these genes. Molecular evolutionary analysis indicated that the four opsin genes evolved under different selective constraints. Subsets of codons in the two long wavelength sensitive opsin (LW1, LW2) genes were positively selected in ancestral fig pollinators. The ultraviolet sensitive opsin (UV) gene was under strong purifying selection, whereas a relaxation of selective constrains occurred on several amino acids in the blue opsin. RT-qPCR analysis suggested that female and male fig pollinators had different expression patterns possibly due to their distinct lifestyles and different responses to light within the syconia. Co-evolutionary history with figs might have influenced the evolution and expression plasticity of opsin genes in fig pollinators.
Statistical analysis of the quantization stage of robust perceptual image hashing

In this paper, we consider the problem of the quantization stage of robust perceptual image hashing in authentication application. The main goal of our analysis is to study the behavior of the extracted image features to be hashed against malicious/non-malicious manipulations. In our analysis, we consider only an additive noise. Note that even if the noise is small, it can cause errors during the quantization stage of perceptual image hashing system. For this purpose, we present theoretical analysis of the extracted feature under additive noise, as well as the probability of a false quantization of these selected features. We then introduce our proposed approach based on this theoretical analysis. Finally, several experiments are conducted to validate our theoretical analysis.
Reliable Transfer of Ownership for Estranged Embedded Devices Reliable Transfer of Ownership for Estranged Embedded Devices

ACKNOWLEDGMENTS I would like to express my deepest gratitude to my adviser, Professor Mani Srivastava. Thank you for guiding me as I explored this problem space. I also would like to thank fellow NESL PhD student and mentor David Jea for his insightful input and feedback as I progressed through my research. The experiment for the thesis is a joint work with Dave. I also appreciate the earnest assistance provided by Zainul Charbiwala in building the SOS driver for the SPO2 sensor used in the experiments. Finally, credit goes to NESL for the devices provided for the experimentation and evaluation. A body sensor network(BSN) is a wearable constellation of sensor nodes that collectively monitors the wearer's vital signals. The BSN is also a highly mobile system where the embedded devices can be added to and removed from its topology dynamically and frequently. When deploying a BSN for each victim during an emergency relief operation, previously uninitialized sensor nodes placed within the same BSN need to quickly associate with one another. The problem we seek to address here is that of node estrangement. A node should be disassociated from a BSN when certain conditions satisfy and may need to be reassociated with another BSN. This thesis targets specific aspects of the device estrangement and present a system solution that utilizes dynamic context to address the problem. We first investigate the conditions that satisfy for a device's estrangement from its current network or system, which leads into the process of disassociation of the former owner of node from an vii estranged device. If the estranged device needs to join a new BSN, it will have to formally reassociate with the latter. We propose a solution that involves an experiment which demonstrates two BSNs effectively identifying device estrangement when a sensor node is moved from one's body to another. Each BSN will recognize a change in the context information it has collected and automatically perform the necessary disassociation or reassociation with the estranged device. We present results based on the evaluation of the system's efficiency and security.
Efficient built in self repair techniques for repairing multiport embedded RAMs

Innovation in VLSI technology rapidly increases memory capacity, density which further improves the yield and the need for testing. The redundant rows (columns) in memory array can be used to replace faulty cells anywhere in the memory, using some testing and repairing algorithms. A novel built in self repair redundant mechanism is proposed for multiport memory by combining HESP algorithm for repairing orthogonal faults and faulty rows (columns) and DLA algorithm for repairing inter port faults. The redundancy analysis and testing circuits can be integrated with the repairing circuits. Moreover, redundant memory can be shared among all memory cores within same memory group. Experimental results using simulation shows the reduction in area overhead and improvement in repair rate due to efficient usage of redundancy.
Fast Vortex Core Switching at Moderate Temperatures

Ferromagnetic vortex core switching is investigated using micromagnetic simulations. For that the OOMMF program is used together with a temperature extension we have developed recently. This is a continuum micromagnetic approach, where the well-known Landau Lifshitz Gilbert equation (valid for zero temperature) is replaced by the Landau Lifshitz Bloch equation. In our research we simulate switching of a ferromagnetic vortex core in a at disk (diameter 200 nm, thickness 20 nm) with material parameters that resemble permalloy. Temperatures in the range 400 K to 700 K are considered. Switching itself is caused by application of a very short oscillating magnetic pulse. Parameters used resemble conditions met in the experiment: oscillation period 141 ps (equal to the peak width) and amplitude 60 mT. Surprisingly, no large temperatureor discretization dependence is found. Reasons for that are discussed.
Geographic Expansion of the Invasive Mosquito Aedes albopictus across Panama—Implications for Control of Dengue and Chikungunya Viruses

The Asian tiger mosquito, Aedes (Stegomyia) albopictus, is an invasive species that has expanded its territory to over 40% of the earth’s terrestrial landmass in the last 30 years [1]. Ae. albopictus is an efficient vector of all serotypes of dengue, a disease that has increased in frequency over the past 30 years in the Americas [2], where it represents an annual cost of 2,100,000,000 USD per year [3]. This mosquito is also an efficient vector of the three genotypes of Chikungunya virus, a worldwide emerging pathogen that causes fever, fatigue, and joint swelling in humans. Since 2006, Chikungunya outbreaks have been increasingly recorded outside the virus’s native range in tropical Africa, perhaps because of a mutation in the virus’s envelope gene, which increases the replication and dissemination capacity of the virus in Ae. albopictus [4]. During the second quarter of 2014, Chikungunya has been detected throughout much of the Americas, with major outbreaks occurring in several Caribbean nations, and local transmission confirmed or suspected in the United States, Panama, Venezuela, Peru, and Chile, creating an imminent threat for humans throughout the Americas, who have no prior exposure to this infection [5]. The first cases of Chikungunya disease in Panama were reported in May 2014, occurring in nonresidents who most likely picked up the virus in their Caribbean countries of origin. On 23 July 2014, Panama’s health authority reported autochthonous transmission of Chikungunya virus. Coincidentally, the earliest cases involved patients located in Juan Diaz, an urban area on the eastern outskirts of Panama City, where the first specimen of invasive Ae. albopictus was collected in 2002. Ae. albopictus has expanded across much of Panama since that time, yet to date, no information exists about the degree of expansion or about the factors contributing to the geographic expansion of this important mosquito vector across Panama. Here, we map the temporal expansion of Ae. albopictus, use species distribution models to determine the ecological and nonecological factors associated with its expansion, and comment on the implications for vector and disease control programs in Panama and elsewhere in the American tropics.
Weakly trained dual features extraction based detector for frontal face detection

This paper investigates the inconvenience of using huge number of features, enormous training dataset and lengthy training session to achieve a good performance frontal face detector. The proposed face detector is based on a novel idea which proposes using joint decision from two parallel different features trained detectors, one detector is trained with Local Binary Patterns (LBP) features and the other with Haar-like features. Both detectors are trained with few features using not a huge face/non-face dataset and within relatively short period of time. Hence, both detectors agree on the face image but seldom agree on the non-face image. The result is significantly improved using a multi-detections merging algorithm using simple clustering method. The robustness of the detector is examined once using a face/non-face dataset and compared to Lienhart frontal face detector, and secondly using a real-life sequence.
A Study of the Spatial Protein Organization of the Postsynaptic Density Isolated from Porcine Cerebral Cortex and Cerebellum

Postsynaptic density (PSD) is a protein supramolecule lying underneath the postsynaptic membrane of excitatory synapses and has been implicated to play important roles in synaptic structure and function in mammalian central nervous system. Here, PSDs were isolated from two distinct regions of porcine brain, cerebral cortex and cerebellum. SDS-PAGE and Western blotting analyses indicated that cerebral and cerebellar PSDs consisted of a similar set of proteins with noticeable differences in the abundance of various proteins between these samples. Subsequently, protein localization in these PSDs was analyzed by using the Nano-Depth-Tagging method. This method involved the use of three synthetic reagents, as agarose beads whose surface was covalently linked with a fluorescent, photoactivable, and cleavable chemical crosslinker by spacers of varied lengths. After its application was verified by using a synthetic complex consisting of four layers of different proteins, the Nano-Depth-Tagging method was used here to yield information concerning the depth distribution of various proteins in the PSD. The results indicated that in both cerebral and cerebellar PSDs, glutamate receptors, actin, and actin binding proteins resided in the peripheral regions within ∼10 nm deep from the surface and that scaffold proteins, tubulin subunits, microtubule-binding proteins, and membrane cytoskeleton proteins found in mammalian erythrocytes resided in the interiors deeper than 10 nm from the surface in the PSD. Finally, by using the immunoabsorption method, binding partner proteins of two proteins residing in the interiors, PSD-95 and α-tubulin, and those of two proteins residing in the peripheral regions, elongation factor-1α and calcium, calmodulin-dependent protein kinase II α subunit, of cerebral and cerebellar PSDs were identified. Overall, the results indicate a striking similarity in protein organization between the PSDs isolated from porcine cerebral cortex and cerebellum. A model of the molecular structure of the PSD has also been proposed here.