Core Mapping Research Articles

Integrated Through-Silicon Via Placement and Application Mapping for 3D Mesh-Based NoC Design

This article proposes a solution to the integrated problem of Through-Silicon Via (TSV) placement and mapping of cores to the routers in a three-dimensional mesh-based Network-on-Chip (NoC) system. TSV geometry restricts their number in three-dimensional (3D) ICs. As a result, only about 25% of routers in a 3D NoC can possess vertical connections. Mapping plays an important role in evolving good system solutions in such a situation. TSVs have been placed with detailed consultation with the application mapping process. The integrated problem was first solved using the exact method of Integer Liner Programming (ILP). Next, a solution was obtained via a Particle Swarm Optimization (PSO) formulation. Several augmentations to the basic PSO strategy have been proposed to generate good-quality solutions. The results obtained are better than many of the contemporary approaches and close to the theoretical situation in which all routers are 3D in nature.

A Hybrid Multi-Step Model for Forecasting Day-Ahead Electricity Price Based on Optimization, Fuzzy Logic and Model Selection

The day-ahead electricity market is closely related to other commodity markets such as the fuel and emission markets and is increasingly playing a significant role in human life. Thus, in the electricity markets, accurate electricity price forecasting plays significant role for power producers and consumers. Although many studies developing and proposing highly accurate forecasting models exist in the literature, there have been few investigations on improving the forecasting effectiveness of electricity price from the perspective of reducing the volatility of data with satisfactory accuracy. Based on reducing the volatility of the electricity price and the forecasting nature of the radial basis function network (RBFN), this paper successfully develops a two-stage model to forecast the day-ahead electricity price, of which the first stage is particle swarm optimization (PSO)-core mapping (CM) with self-organizing-map and fuzzy set (PCMwSF), and the second stage is selection rule (SR). The PCMwSF stage applies CM, fuzzy set and optimized weights to obtain the future price, and the SR stage is inspired by the forecasting nature of RBFN and effectively selects the best forecast during the test period. The proposed model, i.e., CM-PCMwSF-SR, not only overcomes the difficulty of reducing the high volatility of the electricity price but also leads to a superior forecasting effectiveness than benchmarks.

Lake Victoria Goldfields

After a period of relative dormancy, the Lake Victoria Goldfields (LVG) in Tanzania, Kenya and Uganda have emerged as an important site for gold mining and exploration in Africa. The Neoarchaean greenstone belts of the LVG are composed mainly of metavolcanic sequences overlain by younger Kavirondian clastic metasedimentary strata. Intermediate to felsic plutonic rocks include local, older syn-volcanic bodies and an extensive suite of late, circa 2650-2640 Ma potassic (K)-granitoids, which substantially invade and disrupt the greenstone belts. Gold deposits are widely distributed but particularly concentrated in three belts: Sukumaland, Musoma-Mara and Busia-Kakamega. Many deposits are simply composed of quartz veins in shear zones and fractures in the Nyanzian host rocks (e.g. Bulyanhulu, Buck Reef and Rosterman). Buzwagi and Nyabirama are composed of quartz vein arrays within intrusions. Several are hosted by folded banded iron-formation (Geita, Golden Ridge, Tulawaka, and Nyanzaga). Nyanzaga, however, is a discordant pipe shaped stockwork containing dolomite, silica and sulphides as open-space fill in high level veins. Gokona- Nyabigena at North Mara is closely associated with porphyritic volcanic and sub-volcanic intrusive rocks and is noted for stockwork-disseminated mineralisation and extreme K-feldspar alteration. Field evidence points to a relatively late, syn-orogenic timing for the majority of the deposits irrespective of style. Most deposits were discovered and exploited in colonial times but many have been expanded considerably by modern exploration. Improved geological knowledge has resulted from this private sector exploration using high-resolution aeromagnetic, electromagnetic and radiometric surveys, followed up by regolith and outcrop mapping and systematic drill testing of large areas (rotary air blast (RAB), reverse circulation (RC), aircore and diamond drill core). Lithogeochemistry and geochronological studies have been carried out by several companies in support of their regional exploration programmes. The LVG is now considered mature from an exploration point of view, so future developments will require the investigation of vein deposits to greater depth and/or the discovery of additional examples of the lower grade stockwork-disseminated styles which may have been overlooked during the early rounds of exploration.

SOFIA MID-INFRARED IMAGING AND CSO SUBMILLIMETER POLARIMETRY OBSERVATIONS OF G034.43+00.24 MM1*

ABSTRACT We present 11.1 to 37.1 μm imaging observations of the very dense molecular cloud core MM1 in G034.43+00.24 using FORCAST on SOFIA and submillimeter (submm) polarimetry using SHARP on the Caltech Submillimeter Observatory. We find that at the spatial resolution of SOFIA, the point-spread function (PSF) of MM1 is consistent with being a single source, as expected based on millimeter (mm) and submm observations. The spectral energy distributions (SEDs) of MM1 and MM2 have a warm component at the shorter wavelengths not seen in mm and submm SEDs. Examination of H(1.65 μm) stellar polarimetry from the Galactic Plane Infrared Polarization Survey shows that G034 is embedded in an external magnetic field aligned with the Galactic Plane. The SHARP polarimetry at 450 μm shows a magnetic field geometry in the vicinity of MM1 that does not line up with either the Galactic Plane or the mean field direction inferred from the CARMA interferometric polarization map of the central cloud core, but is perpendicular to the long filament in which G034 is embedded. The CARMA polarimetry does show evidence for grain alignment in the central region of the cloud core, and thus does trace the magnetic field geometry near the embedded Class 0 YSO.

BPGA- an ultra-fast pan-genome analysis pipeline.

Recent advances in ultra-high-throughput sequencing technology and metagenomics have led to a paradigm shift in microbial genomics from few genome comparisons to large-scale pan-genome studies at different scales of phylogenetic resolution. Pan-genome studies provide a framework for estimating the genomic diversity of the dataset, determining core (conserved), accessory (dispensable) and unique (strain-specific) gene pool of a species, tracing horizontal gene-flux across strains and providing insight into species evolution. The existing pan genome software tools suffer from various limitations like limited datasets, difficult installation/requirements, inadequate functional features etc. Here we present an ultra-fast computational pipeline BPGA (Bacterial Pan Genome Analysis tool) with seven functional modules. In addition to the routine pan genome analyses, BPGA introduces a number of novel features for downstream analyses like core/pan/MLST (Multi Locus Sequence Typing) phylogeny, exclusive presence/absence of genes in specific strains, subset analysis, atypical G + C content analysis and KEGG & COG mapping of core, accessory and unique genes. Other notable features include minimum running prerequisites, freedom to select the gene clustering method, ultra-fast execution, user friendly command line interface and high-quality graphics outputs. The performance of BPGA has been evaluated using a dataset of complete genome sequences of 28 Streptococcus pyogenes strains.

Quantitative two-dimensional strain mapping of small core–shell FePt@Fe3O4 nanoparticles

We report a facile one-pot chemical synthesis of colloidal FePt@Fe3O4 core–shell nanoparticles (NPs) with an average diameter of 8.7 ± 0.4 nm and determine their compositional morphology, microstructure, two-dimensional strain, and magnetic hysteresis. Using various state-of-the-art analytical transmission electron microscopy (TEM) characterization techniques—including high resolution TEM imaging, TEM tomography, scanning TEM-high angle annular dark field imaging, and scanning TEM-energy dispersive x-ray spectroscopy elemental mapping—we gain a comprehensive understanding of the chemical and physical properties of FePt@Fe3O4 NPs. Additional analysis using x-ray photoelectron spectroscopy, x-ray diffraction, and superconducting quantum interference device magnetometry distinguishes the oxide phase and determines the magnetic properties. The geometric phase analysis method is effective in revealing interfacial strain at the core–shell interface. This is of fundamental interest for strain engineering of nanoparticles for desirable applications.

Using vital statistics and core-habitat maps to manage critically endangered orchids in the Western Australian wheatbelt

Vital-statistics data concerning population viability were gathered for four of the rarest orchids in Western Australia using surveys to define population sizes and habitat areas and annual measurements of plant demographics. These orchids were Caladenia melanema, C. graniticola, C. williamsiae and Drakaea isolata from the wheatbelt of Western Australia. This agricultural area has a Mediterranean climate with unreliable rainfall, and is >80% cleared of native vegetation. Surveys with 10–30 volunteers increased population-size estimates by up to 10 times and provided spatial data to define core habitat areas. These areas included most of the individuals of a species, but were only 2–10 ha in size. Within these areas, orchids were often highly aggregated in patches a few metres wide, potentially resulting in a high degree of intraspecific competition. Vital statistics were obtained using 4-m wide and 30–50-m-long transects to measure rates of emergence, flowering, grazing and seed-set for each orchid. Plants emerging at the same position in different years were considered to be the same individual, but most emerged in new positions. Many plants emerged just once in 4 years, and 2–3 years of dormancy was common. Emergence frequencies were used to provide estimates of population sizes that were two or three times larger than suggested by data from a single year. Seed production was typically very low. Grazing by kangaroos and rabbits was most severe for C. melanema, but was greatly reduced by fencing. Severe drought prevented flowering of C. graniticola in the driest year, whereas other species were more resilient. These orchids are likely to persist as long as there are some years where rainfall is sufficient for flowering and seed set followed by a year with adequate rain for seed germination. Populations of all these orchids were stable or increasing, but they are still at high risk of extinction because of the impacts of increasing soil salinity or fire on their habitats. These species are unlikely to spread elsewhere in the highly cleared and fragmented wheatbelt. Intervention by hand-pollination, grazing protection and translocation to new locations is required to mitigate these risks. Results were summarised in vital statistics report cards with thresholds set to inform conservation management for these species. Core habitat maps and vital-statistics report cards should also be valuable new tools for terrestrial-orchid conservation in other biomes.

A System-Level Cosynthesis Framework for Power Delivery and On-Chip Data Networks in Application-Specific 3-D ICs

With increasing core counts ushering in power-constrained 3-D multiprocessor system-on-chips (MPSoCs), optimizing communication power dissipated by the 3-D network-on-chip (NoC) fabric is critical. At the same time, with increased power densities in 3-D ICs, problems of IR drops in the power delivery network (PDN) as well as thermal hot spots on the 3-D die are becoming very severe. Even though the PDN and NoC design goals are nonoverlapping, both the optimizations are interdependent. Unfortunately, designers today seldom consider the design of the PDN, while designing NoCs. Moreover, for each new configuration of computation core and communication mapping on an MPSoC, the corresponding intercore communication patterns, 3-D on-chip thermal profile, as well as IR-drop distribution in the PDN can vary significantly. Based on this observation, we propose a novel design-time system-level application-specific cosynthesis framework that intelligently maps computation and communication resources on a die, for a given workload. The goal is to minimize the NoC power as well as chip-cooling power and optimize the 3-D PDN architecture; while meeting performance goals and satisfying thermal constraints, for a microfluidic cooling-based application-specific 3-D MPSoC. Our experimental results indicate that the proposed 3-D NoC-PDN cosynthesis framework is not only able to meet PDN design goals unlike prior 3-D NoC synthesis approaches, but also provides better overall optimality with the solution quality improvement of up to 35.4% over a probabilistic metaheuristic-based cooptimization approach proposed in prior work.

Chemical mapping of mine waste drill cores with laser-induced breakdown spectroscopy (LIBS) and energy dispersive X-ray fluorescence (EDXRF) for mineral resource exploration

Resource estimation for metals in mine tailings and ore deposits requires many samples, usually in the form of drill cores. In order to detect zones of metal enrichment or depletion as well as different lithological zones in such cores, two different core scanning methods were tested on three drill core metres from tailings of a former Pb–Zn mine to obtain chemical information. The results provide an objective basis for further sub-sampling of the taken drill cores and help reduce the amount of samples and therefore the costs for further investigations.For the determination of element concentrations a prototype of a core scanner working with laser-induced breakdown spectroscopy (LIBS) was tested and the results were compared to data from a commercially available ITRAX core scanner, working with energy-dispersive X-ray fluorescence (EDXRF). Apart from a smooth surface, no complex sample preparation was necessary. Peak intensities of selected elements determined by the two scanners were calibrated by means of linear regression (LR) and partial least squares (PLS) regression with respect to bulk geochemical wavelength-dispersive XRF (WDXRF) analysis results of representative core samples. The application of PLS compensates for matrix effects in LIBS and EDXRF and improves prediction accuracy for most elements, compared to LR. In general, prediction ability of PLS models is slightly higher for EDXRF results than for LIBS. The advantage of the LIBS core scanner is the high spatial resolution and the ability to create two-dimensional (2D) element distribution images as well as phase or mineral distribution maps of the drill core at larger scales. Within the analysed tailing cores metal-rich layers with concentrations up to a maximum of 2.2% Pb+Zn+Cu, could be detected by both core scanning methods. Since these layers are not visible by the human eye, the used core scanning methods are appropriate methods for mineral exploration.

Structure, Composition and Dynamics of the Earth’s Core

This international symposium gathered specialists from different disciplines within the earth sciences to review recent theoretical, experimental and observational findings which have furthered our understanding of the current physical and chemical characteristics of the Earth’s core and of its evolution on a geological timescale. Since the discovery of the inner core’s anisotropy in 1986, significant efforts in seismology have gone into the detailed spatial mapping of this inner core and o...

Core map generation for the ITU TRIGA Mark II research reactor using Genetic Algorithm coupled with Monte Carlo method

The main purpose of this study is to present the results of Core Map (CM) generation calculations for the İstanbul Technical University TRIGA Mark II Research Reactor by using Genetic Algorithms (GA) coupled with a Monte Carlo (MC) based-particle transport code. Optimization problems under consideration are: (i) maximization of the core excess reactivity (ρex) using Single-Objective GA when the burned fuel elements with no fresh fuel elements are used, (ii) maximization of the ρex and minimization of maximum power peaking factor (ppfmax) using Multi-Objective GA when the burned fuels with fresh fuels are used. The results were obtained when all the control rods are fully withdrawn. ρex and ppfmax values of the produced best CMs were provided. Core-averaged neutron spectrum, and variation of neutron fluxes with respect to radial distance were presented for the best CMs. The results show that it is possible to find an optimum CM with an excess reactivity of 1.17 when the burned fuels are used. In the case of a mix of burned fuels and fresh fuels, the best pattern has an excess reactivity of 1.19 with a maximum peaking factor of 1.4843. In addition, when compared with the fresh CM, the thermal fluxes of the generated CMs decrease by about 2% while change in the fast fluxes is about 1%.Classification: J. Core physics

13C metabolic flux analysis at a genome-scale

Metabolic models used in 13C metabolic flux analysis generally include a limited number of reactions primarily from central metabolism. They typically omit degradation pathways, complete cofactor balances, and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up mapping models to a genome-scale. The core mapping model employed in this study accounts for (75 reactions and 65 metabolites) primarily from central metabolism. The genome-scale metabolic mapping model (GSMM) (697 reaction and 595 metabolites) is constructed using as a basis the iAF1260 model upon eliminating reactions guaranteed not to carry flux based on growth and fermentation data for a minimal glucose growth medium. Labeling data for 17 amino acid fragments obtained from cells fed with glucose labeled at the second carbon was used to obtain fluxes and ranges. Metabolic fluxes and confidence intervals are estimated, for both core and genome-scale mapping models, by minimizing the sum of square of differences between predicted and experimentally measured labeling patterns using the EMU decomposition algorithm.Overall, we find that both topology and estimated values of the metabolic fluxes remain largely consistent between core and GSM model. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non-zero flux for the arginine degradation pathway was identified to meet biomass precursor demands as detailed in the iAF1260 model. Inferred ranges for 81% of the reactions in the genome-scale metabolic (GSM) model varied less than one-tenth of the basis glucose uptake rate (95% confidence test). This is because as many as 411 reactions in the GSM are growth coupled meaning that the single measurement of biomass formation rate locks the reaction flux values. This implies that accurate biomass formation rate and composition are critical for resolving metabolic fluxes away from central metabolism and suggests the importance of biomass composition (re)assessment under different genetic and environmental backgrounds. In addition, the loss of information associated with mapping fluxes from MFA on a core model to a GSM model is quantified.

Integrated core selection and mapping for mesh based Network-on-Chip design with irregular core sizes

Network-on-Chip (NoC) has been proposed to replace traditional bus based System-on-Chip (SoC) architecture to address the global communication challenges in nanoscale technologies. A major challenge in NoC based system design is to select Intellectual Property (IP) cores for implementing tasks and associate the selected cores to the routers to optimize cost and performance. These are commonly known as the process of core selection and application mapping respectively. In this paper, integrated core selection and mapping problem has been addressed. Mesh architecture has been considered for experimentation. The integrated core selection and mapping problem takes as input the application task graph, topology graph and a core library. It outputs the selected cores for the tasks and their mapping onto the topology graph, such that, all communication requirements of the application are satisfied. The cores present in a core library may perform more than one task and have non-uniform sizes. For this, a technique based on Particle Swarm Optimization (PSO) has been proposed to select cores from the given core library and map the resultant core graph onto mesh based architectures. An efficient heuristic for mapping has also been proposed, which maps the selected cores onto mesh based architectures, considering non-uniform core sizes. Comparisons have been carried out with step-by-step core selection and mapping approach and also with mapping algorithms that exist in the literature. Significant reductions have been observed in terms of communication cost over all the cases. Area comparisons have also been made. On average, improvement of 13.05% in communication cost and 2.07% in area have been observed. The proposed approach has also been compared in dynamic environment and significant reductions in the average network latency could be observed. On average, improvement of 5.48% in average network latency and 15.68% in network throughput has been observed. Comparison of energy consumption has also been done in both the cases.

Assessing fibrinogen extravasation into Alzheimer's disease brain using high-content screening of brain tissue microarrays

BackgroundTissue microarrays are commonly used to evaluate disease pathology however methods to automate and quantify pathological changes are limited. New methodThis article demonstrates the utility of the VSlide scanner (MetaSystems) for automated image acquisition from immunolabelled tissue microarray slides, and subsequent automated image analysis with MetaXpress (Molecular Devices) software to obtain objective, efficient and reproducible data from immunolabelled tissue microarray sections. ResultsSignificant increases in fibrinogen immunolabelling were observed in 29 Alzheimer's disease cases compared to 28 control cases analysed from a single tissue microarray slide. Western blot analysis also demonstrated significant increases in fibrinogen immunolabelling in 6 Alzheimer's cases compared to 6 control cases. The observed changes were also validated with gold standard blinded manual H-scoring. Comparison with existing methodVSlide Metafer software offers a ‘tissue microarray acquisition’ plugin for easy mapping of tissue cores with their original position on the tissue microarray map. High resolution VSlide images are compatible with MetaXpress image analysis software. This article details the coupling of these two technologies to accurately and reproducibly analyse immunolabelled tissue microarrays within minutes, compared to the gold standard method of manual counting using H-scores which is significantly slower and prone to inter-observer variation. ConclusionsHere, we couple brain tissue microarray technology with high-content screening and automated image analysis as a powerful way to address bottle necks in data generation and improve throughput, as well as sensitivity to study biological/pathological changes in brain disease.

Effect of burnup on the neutronic parameters of ITU TRIGA Mark II research reactor

This study aims to estimate burnup of the fuel elements for the Istanbul Technical University TRIGA Mark II Research and Training Reactor using a Monte Carlo-based burnup-depletion code. Effect of burnup on the core neutronic parameters, effective core multiplication factor, fast/epithermal/thermal neutron fluxes, and core-average neutron spectrum, and incoming neutron spectrum of the piercing beam port (PBP), is investigated at the Beginning of Life (BOL) and End of Life (EOL). Operational data peculiar to a selected operation sequence, which contains positions of CRs, power level of the reactor, material temperatures and latest core map, are used to determine the current fuel burnup of fuel elements at the time under consideration. A specific operation sequence is selected for the analysis. Furthermore, all control rods are considered fully withdrawn to assess the excess reactivity. Results are obtained using MONTEBURNS2 with ENDFB/V-II.1 neutron/photon library for a full power of 250 kW. Neutron cross-section libraries at the full-power operating temperatures are generated using NJOY. From the results, the calculated burnup values of the core at the sequence considered and EOL are found to be 420 MWh and 560 MWh, respectively. Remaining excess reactivity is calculated to be less than 0.3 $. It is observed that core average thermal neutron flux reduces by 1 % while the fast and epithermal neutron fluxes remain almost unchanged.

Construction of high‐throughput genotyped chromosome segment substitution lines in rice (Oryza sativa L.) and QTL mapping for heading date

AbstractChromosome segment substitution lines (CSSLs) provide ideal materials for quantitative trait loci (QTLs) mapping and genetic dissection of complex traits. In this study, we developed a set of CSSL population consisting of 175 lines, which were derived between the recipient ‘Guangluai 4’ and the donor ‘Nipponbare’. Based on 260 molecular markers, we firstly constructed a physical map of core 97 lines. Then, these 97 lines were further genotyped based on resequencing data, and a resequencing‐based physical map was constructed. Compared with the molecular marker‐based physical map, the resequencing‐based physical map of 97 lines contained 367 substituted segments with 252 newly discovered segments. The total size of the 367 substituted segments was 1,074 Mb, which was 2.81 times the size of rice genome. Using the 97 CSSLs as materials, we identified nine QTLs for heading date and three of them were firstly reported. All the QTLs had positive additive effects, ranging from 9.50 to 16.50 days. These CSSLs may greatly help forge a new resource for functional genomics studies and molecular breeding in rice.

In the beginning was the U1A protein: a personal reflection.

In the beginning was the U1A protein: a personal reflection.

Energy Aware Mapping for Reconfigurable Wireless MPSoCs

Energy management for multimode software defined radio systems remains a daunting challenge. This brief develops a high level framework that generates a multiprocessor systems on chip architecture from a library of heterogeneous processing resources that can be reconfigured to support various modes of operation. The framework proposes joint task and core mapping with system level floorplanning. With the objective of minimizing energy, we develop an analytical probabilistic model that considers static, dynamic, configuration, and communication energy components for multiple applications characterized by probabilities of execution. Finally, a fast energy aware joint task and core mapping heuristic is proposed and performance is demonstrated on realistic benchmarks.

Using Genetic Algorithms for Hardware Core Placement and Mapping in NoC-Based Reconfigurable Systems

Mapping of cores has been an important activity in NoC-based system design aimed to find the best topological location onto the NoC, such that the metrics of interest can be greatly optimized. In the last years, partial reconfigurable systems (PRSs) have included Networks-on-Chips (NoCs) as their communication structure, adding complexity to the problem of mapping. Several works have proposed specific and robust NoC architectures for PRSs, forming indirect and irregular networks, in which cases the mapping and placement problems must be treated altogether. The placement deals with the physical positioning of those cores inside the reconfigurable device. Up to now, to the best of our knowledge, the mapping-placement problem for those kinds of architectures has not been addressed yet. In this work, the problem formalization for the design-time hardware core placement and mapping in PRS-NoCs is proposed and methodologies for solving it with genetic algorithms (GAs) are presented. Several GA crossovers and methodologies are compared for obtaining the best solution. Results have shown that best GA solution obtained, in average, communication costs with 4% of penalty when compared with global minimum cost, obtained in a semiexhaustive approach. In addition, the algorithm presents low execution times.

Performance-driven assignment and mapping for reliable networks-on-chips

Network-on-chip (NoC) communication architectures present promising solutions for scalable communication requests in large system-on-chip (SoC) designs. Intellectual property (IP) core assignment and mapping are two key steps in NoC design, significantly affecting the quality of NoC systems. Both are NP-hard problems, so it is necessary to apply intelligent algorithms. In this paper, we propose improved intelligent algorithms for NoC assignment and mapping to overcome the drawbacks of traditional intelligent algorithms. The aim of our proposed algorithms is to minimize power consumption, time, area, and load balance. This work involves multiple conflicting objectives, so we combine multiple objective optimization with intelligent algorithms. In addition, we design a fault-tolerant routing algorithm and take account of reliability using comprehensive performance indices. The proposed algorithms were implemented on embedded system synthesis benchmarks suite (E3S). Experimental results show the improved algorithms achieve good performance in NoC designs, with high reliability.