Utilizing Criticality Stacks for Dynamic Voltage and Frequency Scaling

Thread imbalance is inevitable for multithreaded applications due to the necessity of synchronization primitives to coordinate access to memory and system resources. This imbalance leads to a bounding of application performance, but, more importantly for mobile devices, this imbalance also leads to energy inefficiencies. Recent works have begun to quantify this imbalance and look to leverage it not only for performance improvements, but for energy savings as well. All these works, though, test the theory through the use of simulators and power estimation tools. These results may show that the theory is sound, but the complexities of how a real machine handles synchronization may lead to diminished results by either having too large of a performance impact, or too little energy savings. In this work, we implement one such algorithm, PCSLB, and improve upon it in order to see if the results shown for this technique are feasible for use in real machines. With the improved algorithm, PCSLB-Max, and the CritScale Linux kernel module, we show that, in fact, there are energy saving available to us while mitigating the performance

Utilizing Criticality Stacks for Dynamic Voltage and Frequency Scaling

Thread imbalance is inevitable for multithreaded applications due to the necessity of synchronization primitives to coordinate access to memory and system resources. This imbalance leads to a bounding of application performance, but, more importantly for mobile devices, this imbalance also leads to energy inefficiencies. Recent works have begun to quantify this imbalance and look to leverage it not only for performance improvements, but for energy savings as well. All these works, though, test the theory through the use of simulators and power estimation tools. These results may show that the theory is sound, but the complexities of how a real machine handles synchronization may lead to diminished results by either having too large of a performance impact, or too little energy savings. In this work, we implement one such algorithm, PCSLB, and improve upon it in order to see if the results shown for this technique are feasible for use in real machines. With the improved algorithm, PCSLB-Max, and the CritScale Linux kernel module, we show that, in fact, there are energy saving available to us while mitigating the performance

Nanoparticles modified with multiple organic acids

Surface-modified nanoparticles of boehmite, and methods for preparing the same. Aluminum oxyhydroxide nanoparticles are surface modified by reaction with selected amounts of organic acids. In particular, the nanoparticle surface is modified by reactions with two or more different carboxylic acids, at least one of which is an organic carboxylic acid. The product is a surface modified boehmite nanoparticle that has an inorganic aluminum oxyhydroxide core, or part aluminum oxyhydroxide core and a surface-bonded organic shell. Organic carboxylic acids of this invention contain at least one carboxylic acid group and one carbon-hydrogen bond. One embodiment of this invention provides boehmite nanoparticles that have been surface modified with two or more acids one of which additional carries at least one reactive functional group. Another embodiment of this invention provides boehmite nanoparticles that have been surface modified with multiple acids one of which has molecular weight or average molecular weight greater than or equal to 500 Daltons. Yet, another embodiment of this invention provides boehmite nanoparticles that are surface modified with two or more acids one of which is hydrophobic in nature and has solubility in water of less than 15 by weight. The products of the methods of this invention have specific useful properties when used in mixture with liquids, as filler in solids, or as stand-alone entities

An evaluation of indirubin analogues as phosphorylase kinase inhibitors

Phosphorylase kinase (PhK) has been linked with a number of conditions such as glycogen storage diseases, psoriasis, type 2 diabetes and more recently, cancer (Camus S. et al., Oncogene 2012, 31, 4333). However, with few reported structural studies on PhK inhibitors, this hinders a structure based drug design approach. In this study, the inhibitory potential of 38 indirubin analogues have been investigated. 11 of these ligands had IC50 values in the range 0.170 – 0.360 µM, with indirubin-3’-acetoxime (1c) the most potent. 7-bromoindirubin-3’-oxime (13b), an antitumor compound which induces caspase-independent cell-death (Ribas J. et al., Oncogene, 2006, 25, 6304) is revealed as a specific inhibitor of PhK (IC50 = 1.8 µM). Binding assay experiments performed using both PhK-holo and PhK-γtrnc confirmed the inhibitory effects to arise from binding at the kinase domain (γ subunit). High level computations using QM/MM-PBSA binding free energy calculations were in good agreement with experimental binding data, as determined using statistical analysis, and support binding at the ATP-binding site. The value of a QM description for the binding of halogenated ligands exhibiting -hole effects is highlighted. A new statistical metric, the ‘sum of the modified logarithm of ranks’ (SMLR), has been defined which measures performance of a model for both the “early recognition” (ranking earlier/higher) of active compounds and their relative ordering by potency. Through a detailed structure activity relationship analysis considering other kinases (CDK2, CDK5 and GSK-3α/β), 6’(Z) and 7(L) indirubin substitutions have been identified to achieve selective PhK inhibition. The key PhK binding site residues involved can also be targeted using other ligand scaffolds in future work

Emerging technologies for the production of renewable liquid transport fuels from biomass sources enriched in plant cell walls

Plant cell walls are composed predominantly of cellulose, a range of non-cellulosic polysaccharides and lignin. The walls account for a large proportion not only of crop residues such as wheat straw and sugarcane bagasse, but also of residues of the timber industry and specialist grasses and other plants being grown specifically for biofuel production. The polysaccharide components of plant cell walls have long been recognized as an extraordinarily large source of fermentable sugars that might be used for the production of bioethanol and other renewable liquid transport fuels. Estimates place annual plant cellulose production from captured light energy in the order of hundreds of billions of tons. Lignin is synthesized in the same order of magnitude and, as a very large polymer of phenylpropanoid residues, lignin is also an abundant, high energy macromolecule. However, one of the major functions of these cell wall constituents in plants is to provide the extreme tensile and compressive strengths that enable plants to resist the forces of gravity and a broad range of other mechanical forces. Over millions of years these wall constituents have evolved under natural selection to generate extremely tough and resilient biomaterials. The rapid degradation of these tough cell wall composites to fermentable sugars is therefore a difficult task and has significantly slowed the development of a viable lignocellulose-based biofuels industry. However, good progress has been made in overcoming this so-called recalcitrance of lignocellulosic feedstocks for the biofuels industry, through modifications to the lignocellulose itself, innovative pre-treatments of the biomass, improved enzymes and the development of superior yeasts and other microorganisms for the fermentation process. Nevertheless, it has been argued that bioethanol might not be the best or only biofuel that can be generated from lignocellulosic biomass sources and that hydrocarbons with intrinsically higher energy densities might be produced using emerging and continuous flow systems that are capable of converting a broad range of plant and other biomasses to bio-oils through so-called 'agnostic' technologies such as hydrothermal liquefaction. Continued attention to regulatory frameworks and ongoing government support will be required for the next phase of development of internationally viable biofuels industries.Hwei-Ting Tan, Kendall R. Corbin and Geoffrey B. Finche

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10-11 to 5.0 × 10-21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10-6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio