Miracle-dz/UniFAR-FTUs huggingface dataset:
A 0.4 V 75 kbit SRAM macro in 28 nm CMOS featuring a 3-adjacent MBU correcting ECC

A 0.4 V single cycle 75 kbit SRAM macro protected with a multi-bit upset (MBU) correcting circuit is fabricated in a 28 nm LP-CMOS process. The novel error correcting circuit (ECC) is capable of 3-bit adjacent error correction and 8bit adjacent error detection. Simulation results show that the code provides a 2.35x improvement in corrected soft error rate (SER) over a Bose-Chaudhuri-Hocquenghem (BCH) double error correcting (DEC) code at a raw-SER of 1300 FIT/Mb while requiring 3 fewer check-bits. Further an alternative 2-bit adjacent error correcting implementation provides an corrected-SER approximately equal to the BCH DEC code for the same check-bit overhead as a single error correcting double error detecting (SEC-DED) code in the same error channel. Measurement results confirm an average active energy of 0.015 fJ/bit and leakage current of 10.1 pA/bit.
Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing

The common uncertain sampling approach searches for the most uncertain samples closest to the decision boundary for a classication task. However, we might fail to nd the uncertain samples when we have a poor probabilistic model. In this work, we develop an active learning strategy called \Uncertainty Sampling with Biasing Consensus" (USBC) which predicts the unbalanced data by multi-model committee and ranks the informativeness of samples by uncertainty sampling with higher weight on the minority class. For prediction, we use Random Forests based multiple models that generate the consensus posterior probability for each sample as part of USBC. To further improve the initial performance in active learning, we also use a semi-supervised learning model that self labels predicted negative samples without querying. For more stable initial performance, we use a lter to avoid querying samples with high variance. We also introduce batch size validation to nd the optimal initial batch size for querying samples in active learning.
Products of conjugacy classes and fixed point spaces

We prove several results on products of conjugacy classes in finite simple groups. The first result is that there always exists a uniform generating triple. This result and other ideas are used to solve a 1966 conjecture of Peter Neumann about the existence of elements in an irreducible linear group with small fixed space. We also show that there always exist two conjugacy classes in a finite non-abelian simple group whose product contains every nontrivial element of the group. We use this to show that every element in a non-abelian finite simple group can be written as a product of two rth powers for any prime power r (in particular, a product of two squares).
Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models

Much research in Bayesian modeling has been done to elicit a prior distribution that incorporates domain knowledge. We present a novel and more direct approach by imposing First-Order Logic (FOL) rules on the posterior distribution. Our approach unifies FOL and Bayesian modeling under the regularized Bayesian framework. In addition, our approach automatically estimates the uncertainty of FOL rules when they are produced by humans, so that reliable rules are incorporated while unreliable ones are ignored. We apply our approach to latent topic modeling tasks and demonstrate that by combining FOL knowledge and Bayesian modeling, we both improve the task performance and discover more structured latent representations in unsupervised and supervised learning.
The inclusion of homemakers as an occupation amongst people with upper limb repetitive stress injuries.

BACKGROUND Risk factors contributing to upper limb repetitive stress injuries (RSIs) have been well-documented in literature, but there has been no such data in Singapore. OBJECTIVE To investigate potential contributory factors to upper limb RSIsMETHODS: We performed a retrospective cohort study of clients who were referred to outpatient upper limb rehabilitation in 2012. Demographic information was retrieved from an electronic documentation system. Descriptive analyses were performed using Statistical Package for Social Sciences (SPSS) Version 17. RESULTS A total of 1108 upper limb RSI referrals (827 females, 281 males) were included in this study. The mean age of the group was 53.74 (s.d. 13.03) with a significant proportion within the range of 51-60 years old. The 3 diagnoses which accounted for the majority of clients were: flexor tendinitis of the hand and fingers, DeQuervain's tenosynovitis and carpal tunnel syndrome. A statistically significant proportion of these clients were also involved in doing housework. CONCLUSIONS Upper limb RSIs are prevalent amongst the general population, especially in females. Participation in housework may entail biomechanical loads which may contribute to or worsen upper limb RSIs. Occupational classification systems should include homemakers as a standalone category, distinct from paid domestic help, given the similar nature of physical work involved.
The role of organic nitrogen in the nitrogen cycle of a high-elevation catchment

Here we report on three years (1996-1998) of measurements of organic and inorganic nitrogen (N) fluxes to and from Green Lakes Valley, a high-elevation ecosystem in the Colorado Front Range of the Rocky Mountains. Nitrate-N (NO3−N) was the dominant form of N in both precipitation and streamwater. Annual precipitation contained 52% NO3−N, 32% ammonium-N (NH4−N), 9% dissolved organic N (DON), and 7% particulate organic N (PON). Annual export of N in streamflow was composed of 70% NO3−N, 4% NH4−N, 14% DON, and 12% PON. Thus, the percentage of organic N increased from 16% of total N in precipitation to 26% of total N in streamflow. Subtracting inputs from outputs, Green Lakes Valley always shows net retention of inorganic N. The only form of N that showed net export was DON. DON export was low (0.18 to -0.13 kg ha−1 yr−1), with net export recorded in two years and basin retention one year. There was a seasonal pattern in the concentrations of inorganic N (NO3−N + NH4−N) and organic N (DON + PON). Concentrations of inorganic N were about 15 to 25 μmol L−1 during baseflow, increased to about 30 μmol L−1 on the rising limb of the hydrograph during snowmelt runoff, then decreased to about 5 μmol L−1 on the recession limb of late summer, with a return to baseflow values in the autumn. In contrast, organic N was 7 to 15 μmol L−1 during baseflow, decreased to near or below detection limits on the rising limb of the hydrograph, with a gradual but consistent increase on the recession limb and on into the autumn. The amount of N in dissolved organic matter changed over time, with the DOC:DON ratio decreasing from about 45 on the rising limb of the hydrograph to less than 20 in the autumn. Spatially, there was a striking difference in the ratios of NO3−N and DON between talus and tundra areas. Nitrate concentrations in surface water draining talus areas were always greater than DON. In constrast, DON concentrations in surface water draining tundra areas were always greater than NO3−N. Concentrations of DON were not significantly correlated with DOC (R = 0.04, p > 0.05), indicating that controls on DON export may be different than controls on DOC export. Our results suggest that the ratio of the annual mass flux of inorganic N to organic N in streamwaters may provide a novel index to evaluate the N status of terrestrial ecosystems from various biomes.
IBM Research Report Road Traffic Prediction with Spatio-Temporal Correlations

The spatio-temporal relationship is an essential aspect of road traﬃc prediction. The fundamental observation is that the traﬃc condition at a link is aﬀected by the immediate past traﬃc conditions of some number of its neighboring links. A time lag function deﬁnes how traﬃc ﬂows are related in the temporal dimension. In parallel, the spatial structure deﬁnes which neighboring links have an eﬀect on the traﬃc characteristics of other links, as a function of road type, speed, etc. This paper presents a new method which provides a complete description of the most important spatio-temporal interactions in a road network while maintaining the estimatability of the model. It improves upon existing methods proposed in the area and provides high accuracy on both urban and expressway roads.
Targeting of the Synaptic Vesicle Protein Synaptobrevin in the Axon of Cultured Hippocampal Neurons: Evidence for Two Distinct Sorting Steps

Synaptic vesicles are concentrated in the distal axon, far from the site of protein synthesis. Integral membrane proteins destined for this organelle must therefore make complex targeting decisions. Short amino acid sequences have been shown to act as targeting signals directing proteins to a variety of intracellular locations. To identify synaptic vesicle targeting sequences and to follow the path that proteins travel en route to the synaptic vesicle, we have used a defective herpes virus amplicon expression system to study the targeting of a synaptobrevin-transferrin receptor (SB-TfR) chimera in cultured hippocampal neurons. Addition of the cytoplasmic domain of synaptobrevin onto human transferrin receptor was sufficient to retarget the transferrin receptor from the dendrites to presynaptic sites in the axon. At the synapse, the SB-TfR chimera did not localize to synaptic vesicles, but was instead found in an organelle with biochemical and functional characteristics of an endosome. The chimera recycled in parallel with synaptic vesicle proteins demonstrating that the nerve terminal efficiently sorts transmembrane proteins into different pathways. The synaptobrevin sequence that controls targeting to the presynaptic endosome was not localized to a single, 10– amino acid region of the molecule, indicating that this targeting signal may be encoded by a more distributed structural conformation. However, the chimera could be shifted to synaptic vesicles by deletion of amino acids 61–70 in synaptobrevin, suggesting that separate signals encode the localization of synaptobrevin to the synapse and to the synaptic vesicle.
Theory of the Stochastic Resonance Effect in Signal Detection: Part I—Fixed Detectors

This paper develops the mathematical framework to analyze the stochastic resonance (SR) effect in binary hypothesis testing problems. The mechanism for SR noise enhanced signal detection is explored. The detection performance of a noise modified detector is derived in terms of the probability of detection PD and the probability of false alarm PFA. Furthermore, sufficient conditions are established to determine the improvability of a fixed detector using SR. The form of the optimal noise pdf is determined and the optimal stochastic resonance noise pdf which renders the maximum PD without increasing PFA is derived. Finally, an illustrative example is presented where performance comparisons are made between detectors where the optimal stochastic resonance noise, as well as Gaussian, uniform, and optimal symmetric noises are applied to enhance detection performance.
Molecular Characterization of the Elaeis guineensis Medium-Chain Fatty Acid Diacylglycerol Acyltransferase DGAT1-1 by Heterologous Expression in Yarrowia lipolytica

Diacylglycerol acyltransferases (DGAT) are involved in the acylation of sn-1,2-diacylglycerol. Palm kernel oil, extracted from Elaeis guineensis (oil palm) seeds, has a high content of medium-chain fatty acids mainly lauric acid (C12:0). A putative E. guineensis diacylglycerol acyltransferase gene (EgDGAT1-1) is expressed at the onset of lauric acid accumulation in the seed endosperm suggesting that it is a determinant of medium-chain triacylglycerol storage. To test this hypothesis, we thoroughly characterized EgDGAT1-1 activity through functional complementation of a Yarrowia lipolytica mutant strain devoid of neutral lipids. EgDGAT1-1 expression is sufficient to restore triacylglycerol accumulation in neosynthesized lipid droplets. A comparative functional study with Arabidopsis thaliana DGAT1 highlighted contrasting substrate specificities when the recombinant yeast was cultured in lauric acid supplemented medium. The EgDGAT1-1 expressing strain preferentially accumulated medium-chain triacylglycerols whereas AtDGAT1 expression induced long-chain triacylglycerol storage in Y. lipolytica. EgDGAT1-1 localized to the endoplasmic reticulum where TAG biosynthesis takes place. Reestablishing neutral lipid accumulation in the Y. lipolytica mutant strain did not induce major reorganization of the yeast microsomal proteome. Overall, our findings demonstrate that EgDGAT1-1 is an endoplasmic reticulum DGAT with preference for medium-chain fatty acid substrates, in line with its physiological role in palm kernel. The characterized EgDGAT1-1 could be used to promote medium-chain triacylglycerol accumulation in microbial-produced oil for industrial chemicals and cosmetics.
H E ] 4 M ay 2 01 6 Atmospheres and radiating surfaces of neutron stars with strong magnetic fields

Alexander Y. Potekhin ∗,abcd Wynn C. G. Ho, e Gilles Chabrier d f aIoffe Institute, Politekhnicheskaya 26, Saint Petersburg , 194021, Russia bSt Petersburg Polytechnic University, Politeknicheskaya 29, Saint Petersburg, 195251, Russia cCentral Astronomical Observatory at Pulkovo, Pulkovskoe S hosse 65, Saint Petersburg, 196140, Russia dCentre de Recherche Astrophysique de Lyon, Université de Ly on, Université Lyon 1, Observatoire de Lyon, Ecole Normale Supérieure de Lyon, CNR S, UMR 5574, 46 allée d’Italie, 69364, Lyon Cedex 07, France eMathematical Sciences, Physics & Astronomy, and STAG Resea rch Centre, University of Southampton, Southampton, SO17 1BJ, UK f School of Physics, University of Exeter, Exeter, EX4 4QL, UK E-mail: palex@astro.ioffe. ru,wynnho@slac.stanford. edu, gilles.chabrier@ens-lyon.fr
Tropical Tropospheric-Only Responses to Absorbing Aerosols

AbstractAbsorbing aerosols affect the earth’s climate through direct radiative heating of the troposphere. This study analyzes the tropical tropospheric-only response to a globally uniform increase in black carbon, simulated with an atmospheric general circulation model, to gain insight into the interactions that determine the radiative flux perturbation. Over the convective regions, heating in the free troposphere hinders the vertical development of deep cumulus clouds, resulting in the detrainment of more cloudy air into the large-scale environment and stronger cloud reflection. A different mechanism operates over the subsidence regions, where heating near the boundary layer top causes a substantial reduction in low cloud amount thermodynamically by decreasing relative humidity and dynamically by lowering cloud top. These findings, which align well with previous general circulation model and large-eddy simulation calculations for black carbon, provide physically based explanations for the main character.
Recombinant alpha‐interferon inhibits colony formation of bone marrow fibroblast progenitor cells (CFU‐F)

Alpha‐Interferon (IFN‐α) has been shown to inhibit colony formation of hematopoietic progenitor cells, including colony‐forming unit‐granulocyte, erythroid, macrophage, megakaryocyte (CFU‐GEMM), day 7 colony‐forming unit granulocyte‐macrophage (CFU‐GM), day 14 CFU‐GM, burst‐forming unit erythroid (BFU‐E), pluripotent stem cells (CFU‐S), and colony‐forming unit megakaryocyte (CFU‐MK). The present study was designed to see whether IFN‐α also has inhibitory effects on bone marrow fibroblast progenitors (CFU‐F). We found that IFN‐α exerted a significant inhibitory effect on both rabbit and human CFU‐F formation. Inhibition of human marrow CFU‐F formation by alpha interferon was unaffected by removal of 98% of monocytes/macrophages and T lymphocytes from light density marrow cells. This finding suggests that IFN‐α probably exerts a direct inhibitory effects. © 1992 Wiley‐Liss, Inc.
Describing Complex Charts in Natural Language: A Caption Generation System

Graphical presentations can be used to communicate information in relational data sets succinctly and effectively. However, novel graphical presentations that represent many attributes and relationships are often difficult to understand completely until explained. Automatically generated graphical presentations must therefore either be limited to generating simple, conventionalized graphical presentations, or risk incomprehensibility. A possible solution to this problem would be to extend automatic graphical presentation systems to generate explanatory captions in natural language, to enable users to understand the information expressed in the graphic. This paper presents a system to do so. It uses a text planner to determine the content and structure of the captions based on: (1) a representation of the structure of the graphical presentation and its mapping to the data it depicts, (2) a framework for identifying the perceptual complexity of graphical elements, and (3) the structure of the data expressed in the graphic. The output of the planner is further processed regarding issues such as ordering, aggregation, centering, generating referring expressions, and lexical choice. We discuss the architecture of our system and its strengths and limitations. Our implementation is currently limited to 2-D charts and maps, but, except for lexical information, it is completely domain independent. We illustrate our discussion with figures and generated captions about housing sales in Pittsburgh.
Alcoholism and the Brain: An Overview

Alcoholism can affect the brain and behavior in a variety of ways, and multiple factors can influence these effects. A person’s susceptibility to alcoholism-related brain damage may be associated with his or her age, gender, drinking history, and nutrition, as well as with the vulnerability of specific brain regions. Investigators use a variety of methods to study alcoholism-related brain damage, including examining brains of deceased patients as well as neuroimaging, a technique that enables researchers to test and observe the living brain and to evaluate structural damage in the brain.
The Metabotropic Glutamate 5 Receptor Modulates Extinction and Reinstatement of Methamphetamine-Seeking in Mice

Methamphetamine (METH) is a highly addictive psychostimulant with no therapeutics registered to assist addicts in discontinuing use. Glutamatergic dysfunction has been implicated in the development and maintenance of addiction. We sought to assess the involvement of the metabotropic glutamate 5 receptor (mGlu5) in behaviours relevant to METH addiction because this receptor has been implicated in the actions of other drugs of abuse, including alcohol, cocaine and opiates. mGlu5 knockout (KO) mice were tested in intravenous self-administration, conditioned place preference and locomotor sensitization. Self-administration of sucrose was used to assess the response of KO mice to a natural reward. Acquisition and maintenance of self-administration, as well as the motivation to self-administer METH was intact in mGlu5 KO mice. Importantly, mGlu5 KO mice required more extinction sessions to extinguish the operant response for METH, and exhibited an enhanced propensity to reinstate operant responding following exposure to drug-associated cues. This phenotype was not present when KO mice were tested in an equivalent paradigm assessing operant responding for sucrose. Development of conditioned place preference and locomotor sensitization were intact in KO mice; however, conditioned hyperactivity to the context previously paired with drug was elevated in KO mice. These data demonstrate a role for mGlu5 in the extinction and reinstatement of METH-seeking, and suggests a role for mGlu5 in regulating contextual salience.
An Evaluation of High-Level Mechanistic Core Models

Large core counts and complex cache hierarchies are increasing the burden placed on commonly used simulation and modeling techniques. Although analytical models provide fast results, they do not apply to complex, many-core shared-memory systems. In contrast, detailed cycle-level simulation can be accurate but also tends to be slow, which limits the number of configurations that can be evaluated. A middle ground is needed that provides for fast simulation of complex many-core processors while still providing accurate results. In this article, we explore, analyze, and compare the accuracy and simulation speed of high-abstraction core models as a potential solution to slow cycle-level simulation. We describe a number of enhancements to interval simulation to improve its accuracy while maintaining simulation speed. In addition, we introduce the instruction-window centric (IW-centric) core model, a new mechanistic core model that bridges the gap between interval simulation and cycle-accurate simulation by enabling high-speed simulations with higher levels of detail. We also show that using accurate core models like these are important for memory subsystem studies, and that simple, naive models, like a one-IPC core model, can lead to misleading and incorrect results and conclusions in practical design studies. Validation against real hardware shows good accuracy, with an average single-core error of 11.1% and a maximum of 18.8% for the IW-centric model with a 1.5× slowdown compared to interval simulation.
A Bayesian approach to integrate satellite‐estimated instantaneous photosynthetically active radiation product for daily value calculation

[1] Most terrestrial ecology models need daily incident photosynthetically active radiation (PAR) values, but only instantaneous PAR values are directly derivable from remotely sensed data. The conventional interpolation/integration method for estimating daily PAR from instantaneous values is not an optimal choice when only sparsely spaced instantaneous PAR is available. In this study, a method of ratio (MOR) is developed as an alternative, which is proved to provide a more accurate PAR estimation than the interpolation/integration method when the time interval between adjacent instantaneous PAR increases to 3–4 h. Furthermore, a Bayesian MOR is developed to combine the information from instantaneous PAR and existing knowledge of a given location to provide probabilistic estimation of daily PAR based on posterior distribution. The Bayesian MOR models a day's full set of actual-to-maximum instantaneous PAR ratios as a population from a normal process, and it is configured to estimate the joint posterior distribution of the population's mean and variance. The inference of daily PAR is carried out through Monte Carlo simulations based on the joint posterior distribution. Applications to both synthesized ground measurement data and MODIS (Moderate Resolution Imaging Spectroradiometer) derived instantaneous PAR at six Surface Radiation network (SURFRAD) sites demonstrate that the 90% confidence interval inferred from Bayesian MOR successfully includes the actual daily PAR values. Furthermore, sensitivity study demonstrates that sensible changes in prior distribution only have insignificant impacts on the estimation accuracy of daily PAR based on posterior distribution.