Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of LUT and cluster size on deep-submicron FPGA performance and density

In this paper, we revisit the field-programmable gate-array (FPGA) architectural issue of the effect of logic block functionality on FPGA performance and density. In particular, in the context of lookup table, cluster-based island-style FPGAs (Betz et al. 1997) we look at the effect of lookup table (LUT) size and cluster size (number of LUTs per cluster) on the speed and logic density of an FPGA. We use a fully timing-driven experimental flow (Betz et al. 1997), (Marquardt, 1999) in which a set of benchmark circuits are synthesized into different cluster-based (Betz and Rose, 1997, 1998) and (Marquardt, 1999) logic block architectures, which contain groups of LUTs and flip-flops. Across all architectures with LUT sizes in the range of 2 to 7 inputs, and cluster size from 1 to 10 LUTs, we have experimentally determined the relationship between the number of inputs required for a cluster as a function of the LUT size (K) and cluster size (N). Second, contrary to previous results, we have shown that clustering small LUTs (sizes 2 and 3) produces better area results than what was presented in the past. However, our results also show that the performance of FPGAs with these small LUT sizes is significantly worse (by almost a factor of 2) than larger LUTs. Hence, as measured by area-delay product, or by performance, these would be a bad choice. Also, we have discovered that LUT sizes of 5 and 6 produce much better area results than were previously believed. Finally, our results show that a LUT size of 4 to 6 and cluster size of between 3-10 provides the best area-delay product for an FPGA.
Sensitivity of Diffusion Dynamics to Network Uncertainty

Simple diffusion processes on networks have been used to model, analyze and predict diverse phenomena such as spread of diseases, information and memes. More often than not, the underlying network data is noisy and sampled. This prompts the following natural question: how sensitive are the diffusion dynamics and subsequent conclusions to uncertainty in the network structure? In this paper, we consider two popular diffusion models: Independent cascades (IC) model and Linear threshold (LT) model. We study how the expected number of vertices that are influenced/infected, given some initial conditions, are affected by network perturbation. By rigorous analysis under the assumption of a reasonable perturbation model we establish the following main results. (1) For the IC model, we characterize the susceptibility to network perturbation in terms of the critical probability for phase transition of the network. We find the expected number of infections is quite stable, unless the the transmission probability is close to the critical probability. (2) We show that the standard LT model with uniform edge weights is relatively stable under network perturbations. (3) Empirically, the transient behavior, i.e., the time series of the number of infections, in both models appears to be more sensitive to network perturbations. We also study these questions using extensive simulations on diverse real world networks, and find that our theoretical predictions for both models match the empirical observations quite closely.
Automated Image Interpretation Computer-Assisted Diagnostics

Much of the difficulty in reaching consistent evaluations of radiology and pathology imaging studies arises from subjective impressions of individual observers. Developing strategies that can reliably transform complex visual observations into well-defined algorithmic procedures is an active area of exploration which can advance clinical practice, investigative research and outcome studies. The literature shows that when characterizations are based upon computer-aided analysis, objectivity, reproducibility and sensitivity improve considerably. Advanced imaging and computational tools could potentially enable investigators to detect and track subtle changes in measurable parameters leading to the discovery of novel diagnostic and prognostic clues which are not apparent by human visual inspection alone. The overarching objective of this book chapter is to provide readers with a summary of the origin, evolution and future directions for the fields of automated image interpretation and computer-assisted diagnostics. The chapter begins with a high-level overview of the fields of image processing, pattern recognition, and computer vision followed by a description of how these disciplines relate to the more comprehensive fields of computer-assisted diagnostics and image guided decision support. Throughout the remainder of the chapter we have supplied multiple illustrative examples demonstrating how recent advances and innovations in each of these areas have impacted clinical and research activities throughout pathology and radiology including high-throughput tissue microarray analysis, multi-spectral imaging, and image co-registration.
A comparative analysis of thermogenic capacity and cold tolerance in small birds

SUMMARY Small birds showing marked seasonal changes in cold tolerance also exhibit winter increases in summit metabolic rate (Msum=maximum cold-induced thermogenesis or thermogenic capacity) relative to summer birds. However, some birds show modest seasonal changes in cold tolerance without winter increases in Msum and others exhibit large seasonal changes in cold tolerance with only minor changes in Msum. Thus, the degree of correlation between cold tolerance and Msum is uncertain and no interspecific study has directly addressed this question. In this study, we measured cold tolerance and Msum in summer- (21 species) and winter- (11 species) acclimatized birds from southeastern South Dakota. Msum was measured as the maximum oxygen consumption attained during exposure of individual birds to a declining series of temperatures in 79% helium/21% oxygen (helox). Cold tolerance was measured as the temperature at cold limit (TCL), which is the helox temperature that induced hypothermia in individual birds. Residuals from allometric regressions of logMsum and logTCL were significantly and negatively related for summer (R2=0.34, P=0.006) and winter (R2=0.40, P=0.037) birds. Data were also subjected to a comparative analyses with phylogenetically independent contrasts to remove potential confounding effects of phylogeny, and results were similar to the non-phylogenetic analyses, with significant negative correlations in both summer (R2=0.47, P<0.001) and winter (R2=0.40, P=0.049). Thus, birds with high Msum tended to show reduced TCL (i.e. high cold tolerance), suggesting that cold tolerance and summit metabolism are phenotypically linked in small birds.
Comparison of Criteria for Significant Threshold Shift in Workplace Hearing Conservation Programs

The National Institute for Occupational Safety and Health (NIOSH) recommended that the Standard Threshold Shift (STS) be replaced as the sentinel indicator of hearing loss in workplace audiometric surveillance programs. We conducted a retrospective cohort study of 1220 workers followed for eight consecutive years in the hearing conservation program at the Hanford nuclear facility, to evaluate the relative accuracy of eight candidate threshold-shift criteria for detecting hearing loss over time, using two evaluation methods and comparing to NIOSH findings. The NIOSH-recommended criterion was one of the better criteria. However, the differences between better criteria were less evident using a different evaluation method than the one described by NIOSH. Also, when we compared our findings with those underlying the NIOSH recommendation, the between-database differences were large enough that the smaller between-criteria differences may have limited importance.
Using application domain ontology to construct an initial system model

This paper describes a case study on application of natural language processing in very early stages of the requirements engineering. In our previous work [7] we have shown how natural language processing can be applied to build an application domain model from the requirements document. In this paper we want to go one step further. We want to build an initial system model. To do so, we match the extracted application domain model and the meta model of the specification formalism. It turns out that such a matching is possible and it yields a sensible model, extensible to a full–fledged specification.
Low‐Molecular‐Weight DNA in Blood Plasma as an Index of the Influence of Ionizing Radiation

Abstract: Low‐molecular‐weight DNA (180 bp) appears in blood plasma of irradiated rats. Its amount correlates directly with the irradiation dose. The cloned low‐molecular‐weight DNA is enriched with G/C pairs (48% compared with 40% in the rodent genome). Computer search against EMBL data showed that the sequence of these clones is homologous to various genomic repetitive elements. The program for identification of nucleosome‐positioning sequences in eukaryotic nuclear DNA has shown that low‐molecular‐weight DNA fragments are able to form rather sustainable nucleosomes and have some peculiarity. The difference in the composition of low‐molecular‐weight DNA isolated from blood plasma of rats after irradiation at doses of 8 and 100 Gy consisted of the change in the levels of two dinucleotides (CpG and CpT). The DNA in question originates from different types of cells.
Vehicular mesh networks for infotainment content delivery: The Carmesh perspective

Low cost and high bandwidth Wireless Mesh Networks (WMNs) can be seen as an attractive technology to provide Infotainment services in metropolitan areas. Many network operators and city authorities deploy mesh networks to enable Internet access for visitors and local citizens, but they do not offer any dedicated services. One of the main problems in delivering such services to mobile users (drivers, passengers, pedestrians) is the reliability and performance of the data transfer and high cost of service deployment. This paper describes a flexible service architecture, which was designed for highly mobile vehicular mesh network environments. The proposed architecture takes advantage of dedicated network mechanisms and cloud computing technologies to achieve reliable telematics services provisioning, while offering enhanced functionality, low cost and ease of deployment.
Acquisition and Analysis of Digital Evidence in Android Smartphones

From an expert's standpoint, an Android phone is a large data repository that can be stored either locally or remotely. Besides, its platform allows analysts to acquire device data and evidence, collecting information about its owner and facts under investigation. This way, by means of exploring and cross referencing that rich data source, one can get information related to unlawful acts and its perpetrator. There are widespread and well documented approaches to forensic examining mobile devices and computers. Nevertheless, they are neither specific nor detailed enough to be conducted on Android cell phones. These approaches are not totally adequate to examine modern smartphones, since these devices have internal memories whose removal or mirroring procedures are considered invasive and complex, due to difficulties in having direct hardware access. The exam and analysis are not supported by forensic tools when having to deal with specific file systems, such as YAFFS2 (Yet Another Flash File System). Furthermore, specific features of each smartphone platform have to be considered prior to acquiring and analyzing its data. In order to deal with those challenges, this paper proposes a method to perform data acquisition and analysis of Android smartphones, regardless of version and manufacturer. The proposed approach takes into account existing techniques of computer and cell phone forensic examination, adapting them to specific Android characteristics, its data storage structure, popular applications and the conditions under which the device was sent to the forensic examiner. The method was defined in a broad manner, not naming specific tools or techniques. Then, it was deployed into the examination of six Android smartphones, which addressed different scenarios that an analyst might face, and was validated to perform an entire evidence acquisition and analysis.
A Smartphone Indoor Positioning Method

Location based services are very useful to human beings. The vehicle navigation service that is used by almost all drivers in the world is an example location based service. As the man made constructions are getting bigger and bigger, indoor location based services are demanded. Matter of fact, researches for indoor location based service started in the early 1990s and developing techniques with which universally available efficient indoor location based service systems can be built is one of the hottest current research issues. Considering the features of smart phones, its computing power and the sensor devices equipped on it, moreover it is one of the most popular personal belongings, we conclude that a smart phone is the most ideal device on which indoor location based service systems should be executed. Therefore, we propose a method of indoor positioning that determines the user's current position with the smart phone's sensor values. Referring to the accelerometer values, our method counts steps. With the orientation values, our method estimates the direction. With the step count and the direction, our method determines the current location of the user. Referring to the floor map, our method adjusts the user's current location from time to time. We have implemented the proposed method on Android smart phones and our test results are discussed in this paper.
Parameterized Analysis of Intrusion Detection and Prevention Systems and their Implications on Attack Alerts and Event Co-relation

In this paper, we present a detailed study of how architecture of an IDPS plays a key role in its performance and the ability to co-relate known as well as unknown attacks. We categorize IDPS based on architecture as local or distributed. A detailed comparison is shown in this paper and finally we justify our proposed solution, which deploys agents at host-level locally to give better performance in terms of better attack co-relation and accurate detection and prevention.
A workflow for parallel and distributed computing of large-scale genomic data

Workflow management systems are emerging as dominant solution in bioinformatics because they enable researchers to analyze the huge amount of data generated by modern laboratory equipment. The growth of genomic data generated by next generation sequencing (NGS) results in an increasing need to analyze data on distributed computer clusters. In this paper, we construct a semi-automated workflow system for the analysis of large-scale sequence data sets, describe a pipeline designed with parallel computation to perform the optimal computational steps required to analyze whole genome sequence data, and report the overall execution time of the pipeline using cores on multiple machines.
Late Pleistocene to present lake-level fluctuations at Pyramid and Winnemucca lakes, Nevada, USA

Abstract A new lake-level curve for Pyramid and Winnemucca lakes, Nevada, is presented that indicates that after the ~15,500 cal yr BP Lake Lahontan high stand (1338 m), lake level fell to an elevation below 1200 m, before rising to 1230 m at the 12,000 cal yr BP Younger Dryas high stand. Lake level then fell to 1155 m by ~10,500 cal yr BP followed by a rise to 1200 m around 8000 cal yr BP. During the mid-Holocene, levels were relatively low (~1155 m) before rising to moderate levels (1190–1195 m) during the Neopluvial period (~4800–3400 cal yr BP). Lake level again plunged to about 1155 m during the late Holocene dry period (~2800–1900 cal yr BP) before rising to about 1190 m by ~1200 cal yr BP. Levels have since fluctuated within the elevation range of about 1170–1182 m except for the last 100 yr of managed river discharge when they dropped to as low as 1153 m. Late Holocene lake-level changes correspond to volume changes between 25 and 55 km3 and surface area changes between 450 and 900 km2. These lake state changes probably encompass the hydrologic variability possible under current climate boundary conditions.
Dissection of a Novel Nuclear Localization Signal in Open Reading Frame 29 of Varicella-Zoster Virus

ABSTRACT Open reading frame 29 (ORF29) of varicella-zoster virus (VZV) encodes a 120-kDa single-stranded DNA binding protein (ORF29p) that is not packaged in the virion and is expressed during latency. During lytic infection, ORF29p is localized primarily to infected cell nuclei. In contrast, ORF29p is found exclusively in the cytoplasm in neurons of the dorsal root ganglia obtained at autopsy from seropositive latently infected patients. ORF29p accumulates in the nuclei of neurons in dorsal root ganglia obtained at autopsy from patients with active zoster. The localization of this protein is, therefore, tightly correlated with the proposed VZV lytic/latent switch. In this report, we have investigated the nuclear import mechanism of ORF29p. We identified a novel nuclear targeting domain bounded by amino acids 9 to 154 of ORF29p that functions independent of other VZV-encoded factors. In vitro import assays in digitonin-permeabilized HeLa cells reveal that ORF29p is transported into the nucleus by a Ran-, karyopherin α- and β-dependent mechanism. These data are further supported by the demonstration that a glutathione S-transferase-karyopherin α fusion interacts with ORF29p, but not with a protein containing a point mutation in its nuclear localization signal (NLS). Therefore, the region of ORF29p responsible for its nuclear targeting is also involved in the association with karyopherin α. As a result of this interaction, this noncanonical NLS appears to hijack the classical cellular nuclear import machinery. Elucidation of the mechanisms governing ORF29p nuclear targeting could shed light on the VZV reactivation process.
EFFECTS OF GLOBAL CLIMATE CHANGE ON TERRESTRIAL SMALL MAMMAL COMMUNITIES IN ITALY

In the framework of climate change, it has been predicted that the Mediterranean Basin will experience the greatest loss of biodiversity, because it will be heavily affected by several drivers of change. In particular, Italy is an important geographical area because it represents a key hotspot of biodiversity. The aim of this study was to evaluate the effects of global climate change on terrestrial small mammals (Rodents and Soricomorphs) in Italy. Barn owl (Tyto alba) pellet analysis was applied to study the temporal variations of microteriocoenoses structure. We revisited 21 roosting sites which had been previously studied by other authors and we carried out a similar study in order to analyse possible changes in small mammal communities. Analyses covered a period of about 30 years and the gap between the first and second sampling ranges from 11 to 33 years. Collecting localities were grouped according to the Bioclimatic Map of Italy. Several ecological indexes were applied and their changes through time were analysed for each Bioclimatic Region. Results show a significant increase in thermoxerophilic species in the last thirty years, particularly in the Mediterranean Region. This observed rise is likely due to global and local warming. In fact, higher temperatures, lower precipitation and increasing xerothermic conditions could have facilitated the spread of thermoxerophilic species. The persistence of such a trend could lead to a series of serious ecological consequences in the future, including a possible reduction in biodiversity.
Polycyclic aromatic hydrocarbons—induced ROS accumulation enhances mutagenic potential of T‐antigen from human polyomavirus JC

Polycyclic aromatic hydrocarbons (PAHs) are the products of incomplete combustion of organic materials, which are present in cigarette smoke, deep‐fried food, and in natural crude oil. Since PAH‐metabolites form DNA adducts and cause oxidative DNA damage, we asked if these environmental carcinogens could affect transforming potential of the human Polyomavirus JC oncoprotein, T‐antigen (JCV T‐antigen). We extracted DMSO soluble PAHs from Deepwater Horizon oil spill in the Gulf of Mexico (oil‐PAHs), and detected several carcinogenic PAHs. The oil‐PAHs were tested in exponentially growing cultures of normal mouse fibroblasts (R508), and in R508 stably expressing JCV T‐antigen (R508/T). The oil‐PAHs were cytotoxic only at relatively high doses (1:50–1:100 dilution), and at 1:500 dilution the growth and cell survival rates were practically unaffected. This non‐toxic dose triggered however, a significant accumulation of reactive oxygen species (ROS), caused oxidative DNA damage and the formation of DNA double strand breaks (DSBs). Although oil‐PAHs induced similar levels of DNA damage in R508 and R508/T cells, only T‐antigen expressing cells demonstrated inhibition of high fidelity DNA repair by homologous recombination (HRR). In contrast, low‐fidelity repair by non‐homologous end joining (NHEJ) was unaffected. This potential mutagenic shift between DNA repair mechanisms was accompanied by a significant increase in clonal growth of R508/T cells chronically exposed to low doses of the oil‐PAHs. Our results indicate for the first time carcinogenic synergy in which oil‐PAHs trigger oxidative DNA damage and JCV T‐antigen compromises DNA repair fidelity. J. Cell. Physiol. 228: 2127–2138, 2013. © 2013 Wiley Periodicals, Inc.
State of Art of Multi Relational Data Mining Approaches: A Rule Mining Algorithm

In this 21 st century is completely called as the information science where the large organizations need useful knowledge. The data mining algorithms look for patterns in data. While most existing data mining approaches look for patterns in a single data table, multi-relational data mining (MRDM) approaches look for patterns that involve multiple tables (relations) from a relational database. The database consists of a collection of tables (a relational database). Records in each table represent parts, and individuals can be reconstructed by joining over the foreign key relations between the tables. To reduce the I/O cost, the data accessed together during extraction phase are to be clustered in the same disk block. This paper represents the index structure ,what we generally called as the Imine index structure . This structure can efficiently exploited by different item set extraction as well as this novel index structure is implemented by using FPGrowth and LCM V.2 algorithms. Again in this paper we have focused that how the MRDM techniques are used in different approaches like classification, clustering ILP (Inductive Logic Program) etc.