gebhart/patrepeval huggingface dataset:
Why Quasi-Monte Carlo is Better Than Monte Carlo or Latin Hypercube Sampling for Statistical Circuit Analysis (2010)

At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical interest present themselves as probability distributions. Thus, Monte Carlo techniques comprise the strategy of choice for statistical circuit analysis. There are many challenges in applying these techniques efficiently: circuit size, nonlinearity, simulation time, and required accuracy often conspire to make Monte Carlo analysis expensive and slow. Are we-the integrated circuit community-alone in facing such problems? As it turns out, the answer is “no.” Problems in computational finance share many of these characteristics: high dimensionality, profound nonlinearity, stringent accuracy requirements, and expensive sample evaluation. We perform a detailed experimental study of how one celebrated technique from that domain-quasi-Monte Carlo (QMC) simulation-can be adapted effectively for fast statistical circuit analysis. In contrast to traditional pseudorandom Monte Carlo sampling, QMC uses a (shorter) sequence of deterministically chosen sample points. We perform rigorous comparisons with both Monte Carlo and Latin hypercube sampling across a set of digital and analog circuits, in 90 and 45 nm technologies, varying in size from 30 to 400 devices. We consistently see superior performance from QMC, giving 2× to 8× speedup over conventional Monte Carlo for roughly 1% accuracy levels. We present rigorous theoretical arguments that support and explain this superior performance of QMC. The arguments also reveal insights regarding the (low) latent dimensionality of these circuit problems; for example, we observe that over half of the variance in our test circuits is from unidimensional behavior. This analysis provides quantitative support for recent enthusiasm in dimensionality reduction of circuit problems.
Structural, magnetic, and electrical properties of Li2Ir1−xRuxO3 (2014)

The crystal structure, resistivity, and magnetic susceptibility of the Li${}_{2}$Ir${}_{1\ensuremath{-}x}$Ru${}_{x}$O${}_{3}$ ($x=0$--1) polycrystals have been investigated. We found that the parent antiferromagnetic phase disappears for $x&gt;0.2$ and bond dimers appear in the averaged structure for $x&gt;0.5$ and likely fluctuate for much smaller $x$. Unexpectedly, this system remains insulating for all the doping levels, contrary to the predictions based on the one-band ${j}_{\mathrm{eff}}=1/2$ Kitaev-Heisenberg model. These results suggest that the honeycomb iridates doped with ruthenium are a unique $5d$-orbital-based platform for studying the interplay of the charge, orbital, spin, and lattice degrees of freedom.
The target of ezetimibe is Niemann-Pick C1-Like 1 (NPC1L1) (2005)

Ezetimibe is a potent inhibitor of cholesterol absorption that has been approved for the treatment of hypercholesterolemia, but its molecular target has been elusive. Using a genetic approach, we recently identified Niemann-Pick C1-Like 1 (NPC1L1) as a critical mediator of cholesterol absorption and an essential component of the ezetimibe-sensitive pathway. To determine whether NPC1L1 is the direct molecular target of ezetimibe, we have developed a binding assay and shown that labeled ezetimibe glucuronide binds specifically to a single site in brush border membranes and to human embryonic kidney 293 cells expressing NPC1L1. Moreover, the binding affinities of ezetimibe and several key analogs to recombinant NPC1L1 are virtually identical to those observed for native enterocyte membranes. KD values of ezetimibe glucuronide for mouse, rat, rhesus monkey, and human NPC1L1 are 12,000, 540, 40, and 220 nM, respectively. Last, ezetimibe no longer binds to membranes from NPC1L1 knockout mice. These results unequivocally establish NPC1L1 as the direct target of ezetimibe and should facilitate efforts to identify the molecular mechanism of cholesterol transport.
Exploring and Comparing Unsupervised Clustering Algorithms (2020)

One of the most widely used approaches to explore and understand non-random structure in data in a largely assumption-free manner is clustering. In this paper, we detail two original Shiny apps written in R, openly developed at Github, and archived at Zenodo, for exploring and comparing major unsupervised algorithms for clustering applications: k-means and Gaussian mixture models via Expectation-Maximization. The first app leverages simulated data and the second uses Fisher’s Iris data set to visually and numerically compare the clustering algorithms using data familiar to many applied researchers. In addition to being valuable tools for comparing these clustering techniques, the open source architecture of our Shiny apps allows for wide engagement and extension by the broader open science community, such as including different data sets and algorithms.
The morphometric co‐atrophy networking of schizophrenia, autistic and obsessive spectrum disorders (2018)

By means of a novel methodology that can statistically derive patterns of co-alterations distribution from voxel-based morphological data, this study analyzes the patterns of brain alterations of three important psychiatric spectra-that is, schizophrenia spectrum disorder (SCZD), autistic spectrum disorder (ASD), and obsessive-compulsive spectrum disorder (OCSD). Our analysis provides five important results. First, in SCZD, ASD, and OCSD brain alterations do not distribute randomly but, rather, follow network-like patterns of co-alteration. Second, the clusters of co-altered areas form a net of alterations that can be defined as morphometric co-alteration network or co-atrophy network (in the case of gray matter decreases). Third, within this network certain cerebral areas can be identified as pathoconnectivity hubs, the alteration of which is supposed to enhance the development of neuronal abnormalities. Fourth, within the morphometric co-atrophy network of SCZD, ASD, and OCSD, a subnetwork composed of eleven highly connected nodes can be distinguished. This subnetwork encompasses the anterior insulae, inferior frontal areas, left superior temporal areas, left parahippocampal regions, left thalamus and right precentral gyri. Fifth, the co-altered areas also exhibit a normal structural covariance pattern which overlaps, for some of these areas (like the insulae), the co-alteration pattern. These findings reveal that, similarly to neurodegenerative diseases, psychiatric disorders are characterized by anatomical alterations that distribute according to connectivity constraints so as to form identifiable morphometric co-atrophy patterns.
The δ agent: HBsAg particles with δ antigen and RNA in the serum of an HBV carrier (1981)

The hepatitis B virus-associated delta antigen was detected in the serum of a young female drug addict with acute hepatitis and a previous history of hepatitis B surface antigen carrier. Delta antigen was associated with a 35- to 37-nm subpopulation of hepatitis B surface antigen particles which banded at a density of 1.25 gm per cm3 of CsCl and contained a small RNA of approximately 5.5 X 10(5) molecular weight. This report demonstrates that delta antigen is associated with a unique subpopulation of hepatitis B surface antigen particles and small RNA in human serum.
Reversible and Irreversible Expansion of Lithium-Ion Batteries Under a Wide Range of Stress Factors (2021)

Lithium-ion batteries cell thickness changes as they degrade. These changes in thickness consist of a reversible intercalation-induced expansion and an irreversible expansion. In this work, we study the cell expansion evolution under variety of conditions such as temperature, charging rate, depth of discharge, and pressure. A specialized fixture was used to keep the cells at a constant pressure during cycling, while measuring the thickness change both within a cycle and the cumulative growth over many cycles. The changes in positive and negative electrode capacity and stoichiometric range can be diagnosed from the evolution of the reversible expansion. The changes in the reversible expansion if combined with the voltage, lead to a higher-confidence estimation of cell health parameters important for lifetime prediction and adaptive battery management such as asymmetric charge/discharge power limits. This study raises the importance of monitoring the expansion for enabling advanced and more-informed health diagnostics of lithium-ion batteries.
[Molecular basis of organic acidemia--propionic acidemia]. (1990)

Propionic acidemia is an inborn error of organic acid metabolism caused by deficiency of propionyl-CoA carboxylase (PCC: E. C. 6. 4. 1. 3.). We have detected three types of mutation in the same exon of the coding sequence of beta-subunit of PCC (beta PCC) from two ethnic background (Caucasians and Japanese): an insertion/deletion which replaces 14 nucleotides with 12 unrelated nucleotides results in the elimination of an Msp I site; a 3-bp inframe deletion results in loss of one of two consecutive isoleucine codons immediately preceding the same Msp I site; the C----T transition results a in loss of the same Msp I site. The insertion/deletion and the C----T transition show high allele frequency in Caucasians (0.32) and in Japanese (0.3), respectively. These results reveal the possibility of the independent origin of the mutation in the two ethnic backgrounds and suggest a key role of this exon in the structure and catalytic function of the beta-subunit of PCC.
Keynote Lecture “Exploitation of olive oil industry by-products for pilot isolation and semi-synthesis of promising medicinal agents” (2022)

Extra virgin olive oil (EVOO) the main product of Olea europaea and key ingredient of Mediterranean diet, is characterized by substantial nutritional and health beneficial value [1]. However, despite olive oil's economic and health impact, olive oil industry must deal with significant environmental problems arising from the vast quantity of by-products such as vegetation waters, olive cake, olive pulp and olive branches and leaves [2]. For instance, the amount of olive leaves, produced every year, exceed 18 million tons, and are used mostly as animal feed, compost production or simply are burned. Recent studies show that burning of olive tree branches is a major organic aerosol source in the Mediterranean basin [3]. Given that olive by-products contain high amounts of added-value compounds such as triterpenoids, secoiridoids, flavonoids, phenolic alcohols, phenolic acids and lignans, known also as olive polyphenols and possessing strong antioxidant profile and other important biological activities (e.g., anti-inflammatory, anticancer) there is an increased industrial interest for their possible nutraceutical and pharmaceutical applications. Among these lines, our research is focused on suggesting alternative strategies to manage olive oil industry residues towards their exploitation for the recovery of polyphenols, structured into two axes. Firstly, the development of liquid/liquid or solid/liquid extraction followed by partition chromatography techniques for the isolation of these compounds in multi gram scale and on the other hand, the use of compounds such as oleoside and EDA as starting material for the hemi-synthesis of new analogues and their evaluation as potential antitumor agents.
‘Who controls the past controls the future’: Black history and community development (2018)

What role does “Black history” play in community development? This chapter discusses how Black and Asian minority ethnic (BAME) communities have been excluded from contributing to national and local histories, depriving them of resources that would enable them to develop different futures in the context of a British historical narrative dominated by whiteness. It focuses on the intersection of history and community development and how community-based organisations have worked in collaboration with the University of Huddersfield (in West Yorkshire in the north of England). The chapter suggests that there are advantages in the co-production of historical knowledge, one of which is that a collaborative approach enables greater inclusion and diversity of views, especially as there is a lack of ethnic diversity amongst academic staff at British universities.
Influence of fiber withdrawal during high-power transmission through optical connector with large splice loss (2019)

We investigated the influence of a high-power transmission on the structural and optical characteristics of an optical connector with a large splice loss. We show the relationship between optical power loss and fiber withdrawal.
Resilient Drinking Water Resources (2020)

Abstract A significant challenge for managers of drinking water infrastructures is to make effective strategic decisions for assets with a long lifetime in an uncertain and changing environment. Water resources, which are part of the drinking water infrastructures, have a special position in this decision making process as they operate at the interface of the socio-technical and the socio-ecological subsystems: water resources are the input for the technical system, consisting of pipes and pumps that interact with different actors; and water resources can be seen as output from the ecological system which is influenced by environmental and political issues like climate change, drought and competing and changing uses of water and space. This paper discusses how to design the water resources in such a way that they function in the desired way at present, but that the design also fits an uncertain future as good as possible. To this extent, a framework was developed based upon the notion of resilience. Existing general design principles for socio-technical systems from literature were used as building blocks in the development of our water resources design principles (WR-DP) framework. Three key characteristics of water resources were distinguished in this framework: water quantity, water quality and the environmental impact of the water resources. In addition, we distinguished two dimensions that allowed us to explicitly describe all possible design principles: system scale and class. The first dimension, system scale, ranges from one water resource to a network of water resources. The second dimension, class, makes a distinction between social aspects and technical aspects. Application of the WR-DP framework in a case of a drinking water company in the Netherlands showed the usability of the framework.
Anterolateral Mini-incision Hip Replacement Surgery (2004)

Mini-incision total hip replacement seeks to eliminate some complications of traditional extensile exposure and also attempts to facilitate more rapid rehabilitation of patients after surgery. Different surgical approaches historically have been used to do hip replacement surgery. Anterior or anterolateral approaches have often been selected to decrease the risk of posterior dislocation. Traditional anterolateral approaches have divided the anterior portion of the gluteus medius and minimus and potentially jeopardized the superior gluteal nerve. These disadvantages have been associated with abductor weakness, prolonged limp and decreased patient satisfaction. To overcome these problems, a mini-incision approach was developed using the intermuscular plane between the gluteus medius and the tensor fascia lata. This intermuscular interval through a small incision provides good exposure for total hip replacement and preserves muscle integrity so that rehabilitation can be rapid and the posterior capsule remains intact so that posterior dislocation is less of an issue. The surgical technique for this new innovative approach is described in this article.
Score Following by Particle Filtering for Music Robots (2010)

As an increasing number of robots are expected to get more involved in our human society, the means of interac-tion between humans and robots, such as verbal dialogue, music, or eyecontacts, have great importance. Music is es-
A constraint-based genetic algorithm for concurrent engineering (1998)

Concurrent engineering is a complex problem in that a large number of considerations have to be brought to bear during the design stage. Compounding this complexity is that concurrent engineering problems are also likely to encompass both numeric and symbolic variables, and constraints that range from simple algebraic constraints, through conditional constraints, to potentially very complex database constraints. Previous approaches have concentrated on finding good solutions to simplified problems or, alternatively, to finding a feasible solution which may not be close to optimal. This paper presents an approach to concurrent engineering problems that extends the conventional genetic algorithm approach to handle the complex variety of variables and constraints that are inherent in a typical concurrent engineering problem. This poses some severe research challenges and this paper describes three genetic operators (the constraint-based initialization, crossover, and mutation operators) that preserve feasibility during initialization, crossover, and mutation. Preserving feasibility is achieved by incorporating local constraint propagation, boundary propagation, and set propagation. This overall approach is called the constraint-based genetic algorithm (CBGA) and aims to determine a near-optimal solution to concurrent engineering problems. The paper describes the background to constraint modelling, and genetic algorithms. The constraint-based initialization, crossover and mutation operators are then detailed, together with a description of the implementation of the CBGA in a system called Comet. Finally an example application is given.
3D Convolution Recurrent Neural Networks for Multi-Label Earthquake Magnitude Classification (2022)

We examine a classification task in which signals of naturally occurring earthquakes are categorized ranging from minor to major, based on their magnitude. Generalized to a single-label classification task, most prior investigations have focused on assessing whether an earthquake’s magnitude falls into the minor or large categories. This procedure is often not practical since the tremor it generates has a wide range of variation in the neighboring regions based on the distance, depth, type of surface, and several other factors. We present an integrated 3-dimensional convolutional recurrent neural network (3D-CNN-RNN) trained to classify the seismic waveforms into multiple categories based on the problem formulation. Recent studies demonstrate using artificial intelligence-based techniques in earthquake detection and location estimation tasks with progress in collecting seismic data. However, less work has been performed in classifying the seismic signals into single or multiple categories. We leverage the use of a benchmark dataset comprising of earthquake waveforms having different magnitude and present 3D-CNN-RNN, a highly scalable neural network for multi-label classification problems. End-to-end learning has become a conventional approach in audio and image-related classification studies. However, for seismic signals classification, it has yet to be established. In this study, we propose to deploy the trained model on personal seismometers to effectively categorize earthquakes and increase the response time by leveraging the data-centric approaches. For this purpose, firstly, we transform the existing benchmark dataset into a series of multi-label examples. Secondly, we develop a novel 3D-CNN-RNN model for multi-label seismic event classification. Finally, we validate and evaluate the learned model with unseen seismic waveforms instances and report whether a specific event is associated with a particular class or not. Experimental results demonstrate the superiority and effectiveness of the proposed approach on unseen data using the multi-label classifier.
How calmodulin binding transcription activators (CAMTAs) mediate auxin responses (2010)

Phenotypic plasticity is an adaptive feature of all organisms, which, in land plants, entails changes in orientation of growth (tropism), patterns of development, organ architecture, timing of developmental processes, and resource allocation. However, little is known about the molecular components that integrate exogenous environmental cues with internal hormonal signaling pathways. This addendum describes a role for calcium-regulated calmodulin-binding transcription 1 (CAMTA1) in auxin signaling and stress responses. We discuss possible mechanisms that may underlie this role of CAMTA1, and speculate on the more general roles of CAMTAs in auxin responses and phenotypic plasticity.
Blending Methods for Coupling Atomistic and Continuum Models (2009)

Abstract We review some recent developments in the coupling of atomistic and continuum models based on the blending of the two models in an overlap, or bridge, subdomain. These coupling schemes resemble overlapping domain decomposition methods. However, their analysis and development is complicated by the non-local force model employed by the atomistic model. We present an abstract framework for atomistic-to-continuum (AtC) coupling methods and formulate precise mathematical notions of patch and consistency tests for the methods. The framework admits both force-based or energy-based coupling methods and allows us to identify four general classes of blending methods. We subject each class to patch and consistency tests and discuss important implementation issues such as: the enforcement of displacement continuity constraints in the bridge region; internal vs. external blending; the role of ghost forces, or forces that arise from coupling nonlocal and local models of force, and how they can be mitigated by blending methods.
Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer (2019)

Cellular diversity in tumors is a key factor for therapeutic failures and lethal outcomes of solid malignancies. Here, we determined the single-cell transcriptomic landscape of liver cancer biospecimens from 19 patients. We found varying degrees of heterogeneity in malignant cells within and between tumors and diverse landscapes of tumor microenvironment (TME). Strikingly, tumors with higher transcriptomic diversity were associated with patient's worse overall survival. We found a link between hypoxia-dependent vascular endothelial growth factor expression in tumor diversity and TME polarization. Moreover, T cells from higher heterogeneous tumors showed lower cytolytic activities. Consistent results were found using bulk genomic and transcriptomic profiles of 765 liver tumors. Our results offer insight into the diverse ecosystem of liver cancer and its impact on patient prognosis.
Failure mechanisms in polypropylene with glass beads (1997)

Abstract The effect of glass beads on the stress‐strain behavior of isotactic polypropylene has been examined. Poisson's ratio and secant compliance as a function of strain have been measured. Both sets of data are consistent with interfacial debonding as the initial damage mechanism. Interfacial debonding is then followed by extensive plastic yielding of the matrix at the debond sites. The maximum stress and strain to failure decrease with glass bead content and glass bead diameter. Impact properties correlate with the ability of the composites to reach high strain to failure. The proposed failure mechanisms are supported by fractography and in‐situ deformation studies by scanning electron microscopy.