Miracle-dz/UniFAR-FTUs huggingface dataset:
Throughput of Rateless Codes Over Broadcast Erasure Channels

In this paper, we characterize the throughput of a broadcast network with n receivers using rateless codes with block size K. We assume that the underlying channel is a Markov modulated erasure channel that is i.i. d. across users, but can be correlated in time. We characterize the system throughput asymptotically in n. Specifically, we explicitly show how the throughput behaves for different values of the coding block size K as a function of n, as n→ ∞. For finite values of K and n, under the more restrictive assumption of Gilbert-Elliott erasure channels, we are able to provide a lower bound on the maximum achievable throughput. Using simulations, we show the tightness of the bound with respect to system parameters n and K and find that its performance is significantly better than the previously known lower bounds.
A Comparative Study on Excess-Loop-Delay Compensation Techniques for Continuous-Time Sigma–Delta Modulators

Excess loop delay (ELD) is well known for its detrimental effect on the performance and stability of continuous-time sigma-delta modulators. A detailed analysis on the most recently published compensation techniques for single-stage modulators is performed in this paper, thus enabling their application to an arbitrary modulator. Based on different characteristics such as circuit complexity, achievable dynamic range, or requirements on the operational amplifiers, their advantages and disadvantages are investigated. Subsequently, the analysis is extended to cascaded modulators. Contrary to intuition, the results indicate that a compensation of ELD in every stage of the cascade is insufficient for optimal performance. Although not configured in a feedback configuration and as such not suffering from stability problems, each coupling network between two stages must additionally be compensated for ELD.
The Impact of Business Process Outsourcing on Firm Performance and the Influence of Governance: A Long Term Study in the German Banking Industry

Does BPO pay off at the firm-level? Although there are several studies which analyze the potential benefits of BPO, there is a virtual absence of research papers on BPO outcomes. Based on an analysis of 137 Business process outsourcing (BPO) ventures at 254 German banks in a period between 1994 and 2005, we found that the outsourcer's financial performance in terms of profitability and cost efficiency was increased significantly compared to industry peers without BPO. The increase stems not from workforce reductions but rather from increased employee productivity. Further, we show how BPO governance ensures BPO success: individually negotiated outsourcing contracts help to improve cost efficiency and profitability measures. Relational governance based on trust has only positive effects on profitability.
Towards Continual Knowledge Graph Embedding via Incremental Distillation

Traditional knowledge graph embedding (KGE) methods typically require preserving the entire knowledge graph (KG) with significant training costs when new knowledge emerges. To address this issue, the continual knowledge graph embedding (CKGE) task has been proposed to train the KGE model by learning emerging knowledge efficiently while simultaneously preserving decent old knowledge. However, the explicit graph structure in KGs, which is critical for the above goal, has been heavily ignored by existing CKGE methods. On the one hand, existing methods usually learn new triples in a random order, destroying the inner structure of new KGs. On the other hand, old triples are preserved with equal priority, failing to alleviate catastrophic forgetting effectively. In this paper, we propose a competitive method for CKGE based on incremental distillation (IncDE), which considers the full use of the explicit graph structure in KGs. First, to optimize the learning order, we introduce a hierarchical strategy, ranking new triples for layer-by-layer learning. By employing the inter- and intra-hierarchical orders together, new triples are grouped into layers based on the graph structure features. Secondly, to preserve the old knowledge effectively, we devise a novel incremental distillation mechanism, which facilitates the seamless transfer of entity representations from the previous layer to the next one, promoting old knowledge preservation. Finally, we adopt a two-stage training paradigm to avoid the over-corruption of old knowledge influenced by under-trained new knowledge. Experimental results demonstrate the superiority of IncDE over state-of-the-art baselines. Notably, the incremental distillation mechanism contributes to improvements of 0.2%-6.5% in the mean reciprocal rank (MRR) score. More exploratory experiments validate the effectiveness of IncDE in proficiently learning new knowledge while preserving old knowledge across all time steps.
A Sparse Reformulation of the Green’s Function Formalism Allows Efficient Simulations of Morphological Neuron Models

We prove that when a class of partial differential equations, generalized from the cable equation, is defined on tree graphs and the inputs are restricted to a spatially discrete, well chosen set of points, the Green’s function (GF) formalism can be rewritten to scale as with the number n of inputs locations, contrary to the previously reported scaling. We show that the linear scaling can be combined with an expansion of the remaining kernels as sums of exponentials to allow efficient simulations of equations from the aforementioned class. We furthermore validate this simulation paradigm on models of nerve cells and explore its relation with more traditional finite difference approaches. Situations in which a gain in computational performance is expected are discussed.
NOTES AND CORRESPONDENCE A Variational Method for Computation of Sensible Heat Flux over the Arctic Sea Ice

In this study, a variational approach was employedto compute surface sensible heatflux over the Arctic sea ice. Because the variational approach is able to take into account information from the Monin‐Obukhov similarity theory (MOST) as well as the observed meteorological information, it is expected to improve the pure MOST-based approach in computation of sensible heat flux. Verifications using the direct eddycorrelation measurements over the Arctic sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment period of 1997/98 show that the variational method yields good agreement between the computed and the measured sensible heat fluxes. The variational method is also shown to be more accurate than the traditional MOST method in the computation of sensible heat flux over the Arctic sea ice.
RETARDED GROWTH OF EMBRYO 1 , a New Basic Helix-Loop-Helix Protein , Expresses in Endosperm to Control Embryo Growth 1 [ W ]

We have isolated two dominant mutants from screening approximately 50,000 RIKEN activation-tagging lines that have short inflorescence internodes. The activation T-DNAs were inserted near a putative basic helix-loop-helix (bHLH) gene and expression of this gene was increased in the mutant lines. Overexpression of this bHLH gene produced the original mutant phenotype, indicating it was responsible for the mutants. Specific expression was observed during seed development. The loss-of-function mutation of the RETARDED GROWTH OF EMBRYO1 (RGE1) gene caused small and shriveled seeds. The embryo of the loss-offunction mutant showed retarded growth after the heart stage although abnormal morphogenesis and pattern formation of the embryo and endosperm was not observed. We named this bHLH gene RGE1. RGE1 expression was determined in endosperm cells using the b-glucuronidase reporter gene and reverse transcription-polymerase chain reaction. Microarray and real-time reverse transcription-polymerase chain reaction analysis showed specific down-regulation of putative GDSL motif lipase genes in the rge1-1 mutant, indicating possible involvement of these genes in seed morphology. These data suggest that RGE1 expression in the endosperm at the heart stage of embryo development plays an important role in controlling embryo growth.
In vitro Inhibition Study against A. flavus with Stenotrophomonas maltophilia Immobilized in Calcium Alginate Gel Beads

Enhanced chitinase secretion was demonstrated in batch fermentation process by immobilizing a novel bacterial isolate SJ602 in alginate beads. The phylogenetic data affirmed the identity of the SJ602 as Stenotrophomonas maltophilia strain. Optimization of the conditions suggested the alginate concentration of 4% at a pH range of 6.0-7.0 and temperature of 37 °C, are the more convenient conditions for achieving maximal enzyme activity of immobilized cells. Amendment of alginate with 5% skimmed milk powder added greater stability, and also maintained the viability of bacterial cells inside the entrapped alginate beads. Thus, the alginate immobilization, described above, improve the bacterial life and the chitinase activity as compared to non-immobilized bacterial cells. The results described the effect of the biodegradable polymers as the nutrient source in maintaining the critical biomass and enhanced stability during long term storage at ambient temperature. The study showed S. maltophilia SJ602 as a potential candidate for agricultural and biotechnological applications.
Isolation and characterization of a Pichia anomala strain: a promising candidate for bioethanol production

A yeast strain designated as Y-1 was isolated and characterized from wine yeast (“Jiuqu”). Based on the morphological and biochemical results, along with the rDNA internal transcribed spacer region (ITS), Y-1 was identified to be a Pichia anomala strain. Y-1 is an ethanol-tolerant strain, enduring ethanol concentrations of up to 14 %. Y-1 growth medium conditions were optimized, results showing good growth in medium with pH ranges from 3.5–6.5, temperature ranges from 25–30 °C, and inoculums range of 8 %-12 %, while optimum growth conditions were reached at a temperature of 30 °C, pH 5.0, and inoculums of 10 %. Furthermore, when the alkaline hydrolyzed Shatian pummelo peel solutions were inoculated with 10 % Y-1 and fermented at 30 °C for 6 d, 4.7 % pure ethanol (w/w) was produced, as evidenced by gas chromatography analysis. Our present study shows potential for the Y-1 strain to be a promising candidate for bioethanol production.
Of lemmings and snowshoe hares: the ecology of northern Canada

Two population oscillations dominate terrestrial community dynamics in northern Canada. In the boreal forest, the snowshoe hare (Lepus americanus) fluctuates in cycles with an 8–10 year periodicity and in tundra regions lemmings typically fluctuate in cycles with a 3–4 year periodicity. I review 60 years of research that has uncovered many of the causes of these population cycles, outline areas of controversy that remain and suggest key questions to address. Lemmings are keystone herbivores in tundra ecosystems because they are a key food resource for many avian and mammalian predators and are a major consumer of plant production. There remains much controversy over the role of predation, food shortage and social interactions in causing lemming cycles. Predation is well documented as a significant mortality factor limiting numbers. Food shortage is less likely to be a major limiting factor on population growth in lemmings. Social interactions might play a critical role in reducing the rate of population growth as lemming density rises. Snowshoe hares across the boreal forest are a key food for many predators and their cycles have been the subject of large-scale field experiments that have pinpointed predation as the key limiting factor causing these fluctuations. Predators kill hares directly and indirectly stress them by unsuccessful pursuits. Stress reduces the reproductive rate of female hares and is transmitted to their offspring who also suffer reduced reproductive rates. The maternal effects produced by predation risk induce a time lag in the response of hare reproductive rate to density, aiding the cyclic dynamics.
Syncopation: generational real-time garbage collection in the metronome

Real-time garbage collection has been shown to be feasible, but for programs with high allocation rates, the utilization achievable is not sufficient for some systems.Since a high allocation rate is often correlated with a more high-level, abstract programming style, the ability to provide good real-time performance for such programs will help continue to raise the level of abstraction at which real-time systems can be programmed.We have developed techniques that allow generational collection to be used despite the problems caused by variance in program behavior over the short time scales in which a nursery can be collected. Syncopation allows such behavior to be detected by the scheduler in time for allocation to by-pass the nursery and allow real-time bounds to be met.We have provided an analysis of the costs of both generational and non-generational techniques, which allow the trade-offs to be evaluated quantitatively. We have also provided measurements of application behavior which show that while syncopation is necessary, the need for it is rare enough that generational collection can provide major improvements in real-time utilization. An additional technique, arraylet pre-tenuring, often significantly improves generational behavior.
An Accurate BJT-Based CMOS Temperature Sensor With Duty-Cycle-Modulated Output

This paper describes the design of a precision bipolar junction transistor based temperature sensor implemented in standard 0.7-μm CMOS technology. It employs substrate p-n-ps as sensing elements, which makes it insensitive to the effects of mechanical (packaging) stress and facilitates the use of low-cost packaging technologies. The sensor outputs a duty-cycle-modulated signal, which can easily be interfaced to the digital world and, after low-pass filtering, to the analog world. In order to eliminate the errors caused by the component mismatch, chopping and dynamic element matching (DEM) techniques have been applied. The required component shuffling was done concurrently rather than sequentially, resulting in a fast DEM scheme that saves energy without degrading accuracy. After a single-temperature trim, the sensor's inaccuracy is ±0.1 °C (−20 to 60 °C) and ±0.3 °C (−45 to 130 °C), respectively. Measurements of sensors in different packages show that the package-induced shift is less than 0.1 °C. Measurements of eight sensors over 367 days show that their output drift is less than 6 mK. While dissipating only 200 μW, the sensor achieves a resolution of 3 mK (rms) in a 1.8-ms measurement time, and a state-of-the-art resolution figure of merit of 3.2 pJK2. This combination of high accuracy, high resolution, high speed, and low-energy consumption makes this sensor suited for commercial and industrial applications.
The geometry of Vaidya spacetimes.

In 1943, Prahalad Chunnilal Vaidya solved a long standing problem in relativity : ﬁnding a modiﬁcation of the Schwarzschild metric in order to allow for a radiating mass. We investigate the geometrical structure of Vaidya’s spacetime in the case of a white hole with decreasing mass, stabilising to a black hole in ﬁnite or inﬁnite time or evaporating completely. We focus on the behaviour of the two null congruences of principal null geodesics that are the conformal skeleton of the spacetime and among which are the generators of the past and future horizons. We devote special attention to the case of a complete evaporation in inﬁnite time and establish the existence of an asymptotic light-like singularity of the conformal curvature, touching both the past space-like singularity and future time-like inﬁnity. This singularity is present independently of the decay rate of the mass. We derive an explicit formula that relates directly the strength of this null singularity to the asymptotic behaviour of the mass function. This is work in collaboration with Armand Coudray (Brest). A possible point of connection with the topic of the conference is the quasi normal modes (i.e. resonances) of dynamic black holes, which appear to be an essentially open
Metadata Creation, Transformation and Discovery for Social Science Data Management: The DAMES Project Infrastructure

This paper discusses the use of metadata, underpinned by DDI (Data Documentation Initiative), to support social science data management. Social science data management refers broadly to the discovery, preparation, and manipulation of social science data for the purposes of research and analysis. Typical tasks include recoding variables within a dataset, and linking data from different sources. A description is given of the DAMES project (Data Management through e-Social Science), a UK project which is building resources and services to support quantitative social science data management activities. DAMES provides generic facilities for performing (and recording) operations on data. Specific resources include support for analysis through micro-simulation, and support for access to specialist data on occupations, educational qualifications, measures of ethnicity and immigration, social care, and mental health. The DAMES project tools and services can generate, use, transform, and search metadata that describe social science datasets (including microdata from social survey datasets and aggregate-level macrodata). On DAMES, these metadata are described by various standards including DDI Version 2, DDI Version 3, JSDL (Job Submission Definition Language), and the purpose-designed JFDL (Job Flow Definition Language). The paper describes how DAMES uses metadata with a range of resources that are integrated with a job execution infrastructure, a Web portal, and a tool for data fusion.
ASSESSING THE IMPACT OF SUPPLY CHAIN INTEGRATION THROUGH AN ERP SYSTEM

Many organizations have implemented Enterprise Resource Planning (ERP) systems, hoping to use the information integration these systems provide to improve process efficiency and effectiveness. In particular, ERP systems may be instrumental in realizing Cooperative Planning, Forecasting, and Replenishment (CPFR). In this paper, we present an experimental approach that will be used to assess the real impact of the implementation of CPFR through an ERP system.
Optimizing Preprocessing and Analysis Pipelines for Single-Subject fMRI: 2. Interactions with ICA, PCA, Task Contrast and Inter-Subject Heterogeneity

A variety of preprocessing techniques are available to correct subject-dependant artifacts in fMRI, caused by head motion and physiological noise. Although it has been established that the chosen preprocessing steps (or “pipeline”) may significantly affect fMRI results, it is not well understood how preprocessing choices interact with other parts of the fMRI experimental design. In this study, we examine how two experimental factors interact with preprocessing: between-subject heterogeneity, and strength of task contrast. Two levels of cognitive contrast were examined in an fMRI adaptation of the Trail-Making Test, with data from young, healthy adults. The importance of standard preprocessing with motion correction, physiological noise correction, motion parameter regression and temporal detrending were examined for the two task contrasts. We also tested subspace estimation using Principal Component Analysis (PCA), and Independent Component Analysis (ICA). Results were obtained for Penalized Discriminant Analysis, and model performance quantified with reproducibility (R) and prediction metrics (P). Simulation methods were also used to test for potential biases from individual-subject optimization. Our results demonstrate that (1) individual pipeline optimization is not significantly more biased than fixed preprocessing. In addition, (2) when applying a fixed pipeline across all subjects, the task contrast significantly affects pipeline performance; in particular, the effects of PCA and ICA models vary with contrast, and are not by themselves optimal preprocessing steps. Also, (3) selecting the optimal pipeline for each subject improves within-subject (P,R) and between-subject overlap, with the weaker cognitive contrast being more sensitive to pipeline optimization. These results demonstrate that sensitivity of fMRI results is influenced not only by preprocessing choices, but also by interactions with other experimental design factors. This paper outlines a quantitative procedure to denoise data that would otherwise be discarded due to artifact; this is particularly relevant for weak signal contrasts in single-subject, small-sample and clinical datasets.
Increased reliance on temporal 1 coding when target sound is softer 2 than the background 3

9 Everyday environments often contain multiple concurrent sound sources that ﬂuctuate over time. 10 Normally hearing listeners can beneﬁt from high signal-to-noise ratios (SNRs) in energetic dips of 11 temporally ﬂuctuating background sound, a phenomenon called dip-listening. Specialized 12 mechanisms of dip-listening exist across the entire auditory pathway. Both the instantaneous 13 ﬂuctuating and the long-term overall SNR shape dip-listening. An unresolved issue regarding 14 cortical mechanisms of dip-listening is how target perception remains invariant to overall SNR, 15 speciﬁcally, across diﬀerent tone levels with an ongoing ﬂuctuating masker. Equivalent target 16 detection over both positive and negative overall SNRs (SNR invariance) is reliably achieved in 17 highly-trained listeners. Dip-listening is correlated with the ability to resolve temporal ﬁne 18 structure, which involves temporally-varying spike patterns. Thus the current work tests the 19 hypothesis that at negative SNRs, neuronal readout mechanisms need to increasingly rely on 20 decoding strategies based on temporal spike patterns, as opposed to spike count. Recordings 21 from chronically implanted electrode arrays in core auditory cortex of trained and awake 22 Mongolian gerbils that are engaged in a tone detection task in 10 Hz amplitude-modulated 23 background sound reveal that rate-based decoding is not SNR-invariant, whereas temporal 24 coding is informative at both negative and positive SNRs. 25
Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow

AbstractAs a component of Earth’s hydrologic cycle, and especially at higher latitudes, falling snow creates snowpack accumulation that in turn provides a large proportion of the freshwater resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011/12 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite and radiometers on constellation member satellites. Multiparameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precip.