Hauptsätze der Differential- und Integral-Rechnung : als Leitfaden zum Gebrauch bei Vorlesungen / zusammengestellt von Robert Fricke ; 1. Theil

\u3cp\u3eThe conventional approach of moving data to the CPU for computation has become a significant performance bottleneck for emerging scale-out data-intensive applications due to their limited data reuse. At the same time, the advancement in 3D integration technologies has made the decade-old concept of coupling compute units close to the memory — called near-memory computing (NMC) — more viable. Processing right at the “home” of data can significantly diminish the data movement problem of data-intensive applications. In this paper, we survey the prior art on NMC across various dimensions (architecture, applications, tools, etc.) and identify the key challenges and open issues with future research directions. We also provide a glimpse of our approach to near-memory computing that includes i) NMC specific microarchitecture independent application characterization ii) a compiler framework to offload the NMC kernels on our target NMC platform and iii) an analytical model to evaluate the potential of NMC.\u3c/p\u3

Reply to comment by Jose Pujol on “Laboratory measurements of ultrasonic wave velocities in rocks from the Campi Flegrei volcanic system and their relation to other field data”

International audienc

Correlation between serum and fecal concentrations of reproductive steroids throughout gestation in goats

Non-invasive techniques such as the measurement of fecal steroids are now widely used to monitor reproductive hormones in captive and free-ranging wild-life. These methods offer great advantages and deserve to be used in domestic animals. The aim of the present study was to determine the endocrine profile of dairy goats throughout pregnancy by the quantification of fecal progestins and estrogens and assess its con-elation with serum concentrations. Blood and fecal samples were collected weekly from I I adult, multiparous goats, from mating through pregnancy and 2 weeks post-partum. The extraction of estradiol and progesterone fecal metabolites was performed by dilution in ethanol. The radioimmunoassay (RIA) in solid phase was used to quantify serum 17 beta-estradiol (estradiol) and progesterone, as well as their fecal metabolites. The mean concentrations of both fecal and serum estradiol started to increase between weeks 7 and 11, reached peak values near parturition and then decreased sharply (range: 19.8 +/- 5.8 ng/g of feces to 608.6 +/- 472.4 ng/g of feces and 0.007 +/- 0.005 ng/ml to 0.066 +/- 0.024 ng/ml). An increase in both fecal and blood progestagens occurred in the second week, mean concentrations remained greater until week 20, and then decreased in the last week of gestation and 2 weeks post-partum (range: 108.8 +/- 43.6 ng/g of feces to 3119.5 +/- 2076.9 ng/g of feces and 0. 12 +/- 0.04 ng/ml to 13.10 +/- 4.29 ng/ml). The changes in blood and fecal hormone concentrations were analyzed and compared throughout gestation for each single goat, for each breed and for the whole group. Results indicated that matched values of serum and fecal hormone concentrations were correlated (r = 0.79; p < 0.001 for progesterone and r = 0.84;p < 0.001 for estradiol mean concentrations in the whole group). Regression analysis showed that logarithmic model allows significant prediction of serum from fecal concentrations with an R-2 = 0.729 (y = 0.013 1n x - 0.021) for estradiol and R-2 = 0.788 (y = 3.835 1n x - 18.543) for progesterone. Neither fecal nor serum concentrations were affected by the breed but a significant effect of the number of fetuses on progestin concentrations was found. Therefore, the profiles of progesterone and estradiol fecal metabolites reflect the serum concentrations of the same hormones in pregnant goats. (C) 2006 Elsevier B.V. All rights reserved

Reduced social coordination in Autism Spectrum Disorders

In the present study, we investigated whether individuals with Autism Spectrum Disorders (ASD) were able to coordinate with an unknown partner on the same outcome using a two-person pure coordination game. Twenty-one adults with ASD and twenty-one typically developed (TD) control participants were presented with sets of four items, and were asked to choose one of these items under three conditions: Picking one's own personal preferred item, guessing what might be the partner's preference, and choosing an item in order to coordinate with the partner's choice. Each set included a salient item that stood out for its distinctive properties, known as the focal point. The results showed that individuals with ASD choose more often their preferred items than the salient cues to coordinate with others and to guess the partner's preference, as compared to TD controls. Performance for coordination was related to clinical scores assessing difficulties in communication and the severity of the autistic traits, but was unrelated to verbal intelligence and verbally mediated Theory-of-Mind task. These findings suggest that self-bias processes in decision-making might be a source of impairment in social coordination and interaction in ASD

TDO-CIM:Transparent Detection and Offloading for Computation In-memory

Computation in-memory is a promising non-von Neumann approach aiming at completely diminishing the data transfer to and from the memory subsystem. Although a lot of architectures have been proposed, compiler support for such architectures is still lagging behind. In this paper, we close this gap by proposing an end-to-end compilation flow for in-memory computing based on the LLVM compiler infrastructure. Starting from sequential code, our approach automatically detects, optimizes, and offloads kernels suitable for in-memory acceleration. We demonstrate our compiler tool-flow on the PolyBench/C benchmark suite and evaluate the benefits of our proposed in-memory architecture simulated in Gem5 by comparing it with a state-of-the-art von Neumann architecture

A review of near-memory computing architectures:Opportunities and challenges

\u3cp\u3eThe conventional approach of moving stored data to the CPU for computation has become a major performance bottleneck for emerging scale-out data-intensive applications due to their limited data reuse. At the same time, the advancement in integration technologies have made the decade-old concept of coupling compute units close to the memory (called Near-Memory Computing) more viable. Processing right at the 'home' of data can completely diminish the data movement problem of data-intensive applications. This paper focuses on analyzing and organizing the extensive body of literature on near-memory computing across various dimensions: starting from the memory level where this paradigm is applied, to the granularity of the application that could be executed on the near-memory units. We highlight the challenges as well as the critical need of evaluation methodologies that can be employed in designing these special architectures. Using a case study, we present our methodology and also identify topics for future research to unlock the full potential of near-memory computing.\u3c/p\u3

A review of near-memory computing architectures: Opportunities and challenges

The conventional approach of moving stored data to the CPU for computation has become a major performance bottleneck for emerging scale-out data-intensive applications due to their limited data reuse. At the same time, the advancement in integration technologies have made the decade-old concept of coupling compute units close to the memory (called Near-Memory Computing) more viable. Processing right at the 'home' of data can completely diminish the data movement problem of data-intensive applications. This paper focuses on analyzing and organizing the extensive body of literature on near-memory computing across various dimensions: starting from the memory level where this paradigm is applied, to the granularity of the application that could be executed on the near-memory units. We highlight the challenges as well as the critical need of evaluation methodologies that can be employed in designing these special architectures. Using a case study, we present our methodology and also identify topics for future research to unlock the full potential of near-memory computing

Synthesis and Biological Evaluation of Novel Neuroprotective Pyridazine Derivatives as Excitatory Amino Acid Transporter 2 (EAAT2) Activators

LDN-212320 (3) was found to be a potent EAAT2 activator at a translational level, restoring the normal clearance of glutamate and providing neuronal protection. Since the pharmacologic activation of EAAT2 represents a valuable strategy to relieve neuropathic pain, we synthesized novel activators (4a-f) of EAAT2. Among them 4f, analyzed in comparison with 3 by different paradigms in a rat model of oxaliplatin-induced neuropathic pain, showed the better antihypersensitive profile being able to fully counteract the oxaliplatin-induced neuropathy