Practical perfect hashing in nearly optimal space

A hash function is a mapping from a key universe U   to a range of integers, i.e., h:U?{0,1,…,m−1}$h:U?\{\mathrm{0,1},\dots ,m-1\}$, where m is the range's size. A perfect hash function   for some set S⊆U$S\subseteq U$ is a hash function that is one-to-one on S  , where m≥|S|$m\ge \left|S\right|$. A minimal perfect hash function   for some set S⊆U$S\subseteq U$ is a perfect hash function with a range of minimum size, i.e., m=|S|$m=\left|S\right|$. This paper presents a construction for (minimal) perfect hash functions that combines theoretical analysis, practical performance, expected linear construction time and nearly optimal space consumption for the data structure. For n keys and m=n   the space consumption ranges from 2.62n+o(n)$2.62n+o(n)$ to 3.3n+o(n)$3.3n+o(n)$ bits, and for m=1.23n$m=1.23n$ it ranges from 1.95n+o(n)$1.95n+o(n)$ to 2.7n+o(n)$2.7n+o(n)$ bits. This is within a small constant factor from the theoretical lower bounds of 1.44n$1.44n$ bits for m=n   and 0.89n$0.89n$ bits for m=1.23n$m=1.23n$. We combine several theoretical results into a practical solution that has turned perfect hashing into a very compact data structure to solve the membership problem when the key set S is static and known in advance. By taking into account the memory hierarchy we can construct (minimal) perfect hash functions for over a billion keys in 46 min using a commodity PC. An open source implementation of the algorithms is available at http://cmph.sf.net under the GNU Lesser General Public License (LGPL).     

Estimation of diurnal air temperature using MSG SEVIRI data in West Africa

Spatially distributed air temperature data with high temporal resolution are desired for several modeling applications. By exploiting the thermal split window channels in combination with the red and near infrared channels of the geostationary MSG SEVIRI sensor, multiple daily air temperature estimates can be achieved using the contextual temperature-vegetation index method. Air temperature was estimated for 436 image acquisitions during the 2005 rainy season over West Africa and evaluated against in situ data from a field test site in Dahra, Northern Senegal. The methodology was adjusted using data from the test site resulting in RMSE = 2.55 K, MBE = − 0.30 K and R² = 0.63 for the estimated versus observed air temperatures. A spatial validation of the method using 12 synoptic weather stations from Senegal and Mali within the Senegal River basin resulted in overall values of RMSE = 2.96 K, MBE = − 1.11 K and R² = 0.68. The daytime temperature curve is interpolated using a sine function based on the multiple daily air temperature estimates from the SEVIRI data. These estimates (covering the 8:00-20:00 UCT time window) were in good agreement with observed values with RMSE = 2.99 K, MBE = − 0.70 K and R² = 0.64. The temperature-vegetation index method was applied as a moving window technique to produce distributed maps of air temperature with 15 min intervals and 3 km spatial resolution for application in a distributed hydrological model.     

A parallelized matheuristic for the International Timetabling Competition 2019

Journal of Scheduling - The International Timetabling Competition 2019 (ITC 2019) presents a novel and generalized university timetabling problem composed of traditional class time and room...     

Evaluation of AVHRR PAL and GIMMS 10‐day composite NDVI time series products using SPOT‐4 vegetation data for the African continent

Global 8 km resolution AVHRR (advanced very high resolution radiometer) NDVI (normalized difference vegetation index) 10‐day composite data sets have been used for numerous local to global scale vegetation time series studies during recent years. AVHRR Pathfinder (PAL) NDVI was available from 1981 until 2001, and the new AVHRR GIMMS NDVI was available from 1981 to the present time. A number of aspects potentially introduce noise in the NDVI data set due to the AVHRR sensor design and data processing. NDVI from SPOT‐4 VGT data is considered an improvement over AVHRR, and for this reason it is important to examine how and if the differences in sensor design and processing influence continental scale NDVI composite products. In this study, the quality of these AVHRR NDVI time series are evaluated by the continental scale 1 km resolution SPOT‐4 vegetation (VGT) 10‐day composite (S10) NDVI data. Three years of AVHRR PAL (1998–2000) and seven years of GIMMS (1998–2004) have been compared to 8 km resampled SPOT‐4 VGT (1998–2004) data. The dynamic range of SPOT‐4 VGT NDVI tends to be higher than the AVHRR PAL NDVI, whereas there is an exact match between AVHRR GIMMS NDVI and SPOT‐4 VGT NDVI. Ortho‐regression analysis on annually integrated values of AVHRR PAL/GIMMS and SPOT‐4 VGT on a continental scale reveals high correlations amongst the AVHRR and the SPOT data set, with lowest RMSE (root mean square error) on the GIMMS/SPOT‐4 VGT compared to the PAL/SPOT‐4 VGT.

Analyses on decade data likewise show that a linear relation exists between Spot‐4 VGT NDVI and the two AVHRR composite products; GIMMS explaining most of the Spot‐4 VGT NDVI variance compared to PAL. These results show that the AVHRR GIMMS NDVI is more consistent with Spot‐4 VGT NDVI compared to AVHRR PAL versus Spot‐4 VGT NDVI (in terms of RMSE and dynamic range) and can therefore be considered the more accurate long time AVHRR data record. Analyses performed on monthly maximum composites and decade composite data, however, reveal intra‐annual variations in the correlation between SPOT‐4 VGT and the two AVHRR data sets, which are attributed to different cloud masking algorithms. The SPOT‐4 VGT cloud‐screening algorithm is insufficient, thereby suppressing the rainy season NDVI.     

Space Efficient Hash Tables with Worst Case Constant Access Time

We generalize Cuckoo Hashing to d-ary Cuckoo Hashing and show how this yields a simple hash table data structure that stores n elements in (1 + )n memory cells, for any constant > 0. Assuming uniform hashing, accessing or deleting table entries takes at most d=O (ln (1/)) probes and the expected amortized insertion time is constant. This is the first dictionary that has worst case constant access time and expected constant update time, works with (1 + )n space, and supports satellite information. Experiments indicate that d = 4 probes suffice for 0.03. We also describe variants of the data structure that allow the use of hash functions that can be evaluated in constant time.     

Strategy for Optimizing LC-MS Data Processing in Metabolomics: A Design of Experiments Approach

A strategy for optimizing LC-MS metabolomics data processing is proposed. We applied this strategy on the XCMS open source package written in R on both human and plant biology data. The strategy is a sequential design of experiments (DoE) based on a dilution series from a pooled sample and a measure of correlation between diluted concentrations and integrated peak areas. The reliability index metric, used to define peak quality, simultaneously favors reliable peaks and disfavors unreliable peaks using a weighted ratio between peaks with high and low response linearity. DoE optimization resulted in the case studies in more than 57% improvement in the reliability index compared to the use of the default settings. The proposed strategy can be applied to any other data processing software involving parameters to be tuned, e.g., MZmine 2. It can also be fully automated and used as a module in a complete metabolomics data processing pipeline.     

A dual gradient assay for the parametric analysis of cell-surface interactions

Cellular response to microgrooves is addressed using a new assay format, comprising orthogonal gradients of continuously varied groove pitch and depth. Dual layer etch masks are created using a combination of micropatterning and plasma polymer deposition. A silicon substrate with a constant groove width of 8 μm and with ridge width increasing from 8 μm in 0.5 μm steps across 10 mm is fabricated by photolithography. A plasma-polymerized hexane film which is 120 nm thick at one end of these grooves, and 10 nm at the other, is deposited under a diffusion mask. Reactive etching of the patterned sample transfers a gradient of groove pitch and groove depth into the silicon substrate. A silicon master with a gradient of groove depth spanning more than two orders of magnitude (less than 10 nm to over 1000 nm) is used to create an injection molding inlay for mass replication of the screening topography. Polycarbonate replicas are molded for use in cell culture studies, and the functionality of the topography as a high-throughput screening platform is investigated. The response of MDCK, h-TERT fibroblasts, and LE2 endothelial cells is examined, in terms of attachment and morphological response to the variation in topographical cues, with the aim of pinpointing the optimal combination of groove pitch and depth to elicit a tailored response from each cell type. When the range of topographical features screened on a single substrate is considered, this new assay represents a significant step forward in the parametric design and analysis of topographical cues at the biomaterial interface.     

Using leaf chlorophyll to parameterize light-use-efficiency within a thermal-based carbon, water and energy exchange model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C_ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C_ab into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO₂ and energy fluxes using an analytical, light-use-efficiency (LUE) approach to estimating bulk canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes, internally estimating fluctuations in effective LUE from a nominal (species-dependent) value (LUE_n) in response to short-term variations in environmental conditions. LUE_n, however, may vary on a daily timescale, responding to changes in plant phenology, physiological condition and nutrient status. Therefore, remote sensing methodologies for improving daily estimates of LUE_n have been investigated. Day-to-day variations in LUE_n were assessed for a heterogeneous corn crop field in Maryland, U.S.A. through model optimization with eddy covariance CO₂ flux tower observations. The optimized daily LUE_n values were then compared to gridded estimates of C_ab over the tower flux footprint, retrieved from a canopy reflectance model driven by green, red and near-infrared imagery acquired with an aircraft imaging system. The tower-calibrated LUE_n data were generally well correlated with airborne retrievals of C_ab, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C_ab for delineating spatio-temporal variations in LUE_n. The study highlights the potential synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for estimating carbon, water and heat fluxes within a two-source energy balance framework.     

Resilience in disaster research: three versions

This paper explores the concept of resilience in disaster management settings in modern society. The diversity and relatedness of ‘resilience’ as a concept and as a process are reflected in its presentation through three ‘versions’: (i) pastoral care and the role of the church for victims of disaster trauma, (ii) federal policy and the US Critical Infrastructure Plan, and (iii) the building of resilient communities for disaster risk reduction practices. The three versions aim to offer characteristic expressions of resilience, as increasingly evident in current disaster literature. In presenting resilience through the lens of these three versions, the article highlights the complexity in using resilience as an all-encompassing word. The article also suggests the need for understanding the nexuses between risk, vulnerability, and policy for the future of resilience discourse.