gebhart/patrepeval huggingface dataset:
Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning (2023)

Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI) measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer's disease. Traditionally, this task is performed by formulating a linear regression problem. Recently, it is found that using a linear sparse regression model can achieve better prediction accuracy. However, most existing studies only focus on the exploitation of sparsity of regression coefficients, ignoring useful structure information in regression coefficients. Also, these linear sparse models may not capture more complicated and possibly nonlinear relationships between cognitive performance and MRI measures. Motivated by these observations, in this work we build a sparse multivariate regression model for this task and propose an empirical sparse Bayesian learning algorithm. Different from existing sparse algorithms, the proposed algorithm models the response as a nonlinear function of the predictors by extending the predictor matrix with block structures. Further, it exploits not only inter-vector correlation among regression coefficient vectors, but also intra-block correlation in each regression coefficient vector. Experiments on the Alzheimer's Disease Neuroimaging Initiative database showed that the proposed algorithm not only achieved better prediction performance than state-of-the-art competitive methods, but also effectively identified biologically meaningful patterns.
Thermodynamic Computing (2019)

The hardware and software foundations laid in the first half of the 20th Century enabled the computing technologies that have transformed the world, but these foundations are now under siege. The current computing paradigm, which is the foundation of much of the current standards of living that we now enjoy, faces fundamental limitations that are evident from several perspectives. In terms of hardware, devices have become so small that we are struggling to eliminate the effects of thermodynamic fluctuations, which are unavoidable at the nanometer scale. In terms of software, our ability to imagine and program effective computational abstractions and implementations are clearly challenged in complex domains. In terms of systems, currently five percent of the power generated in the US is used to run computing systems - this astonishing figure is neither ecologically sustainable nor economically scalable. Economically, the cost of building next-generation semiconductor fabrication plants has soared past $10 billion. All of these difficulties - device scaling, software complexity, adaptability, energy consumption, and fabrication economics - indicate that the current computing paradigm has matured and that continued improvements along this path will be limited. If technological progress is to continue and corresponding social and economic benefits are to continue to accrue, computing must become much more capable, energy efficient, and affordable. We propose that progress in computing can continue under a united, physically grounded, computational paradigm centered on thermodynamics. Herein we propose a research agenda to extend these thermodynamic foundations into complex, non-equilibrium, self-organizing systems and apply them holistically to future computing systems that will harness nature's innate computational capacity. We call this type of computing "Thermodynamic Computing" or TC.
Focusing The Mediating Role Of Knowledge Management Practices: How Does Institutional And Interpersonal Trust Support Exploitative And Exploratory Innovation? (2015)

&lt;p&gt;The purpose of this paper is to investigate the influence of both institutional and interpersonal trust on innovation and deepens the analysis by exploring the mediating role of knowledge management (KM) practices in this relationship. Conceptually, this reflection leads to the proposal of a conceptual model summarizing the relationships between the research variables. This model was tested with 226 senior officials in companies operating in the information and communication technologies (ICT) Tunisian sector on the basis of a structured questionnaire. The collected data were treated by structural equation analysis using AMOS software. The results of the empirical study highlighted the significant relationship between interpersonal trust and innovation and confirmed that KM practices act as partial mediators in this relationship. Findings show also that institutional trust is not correlated to KM practices and to innovation.&lt;/p&gt;
Genomic Prediction Using Prior Quantitative Trait Loci Information Reveals a Large Reservoir of Underutilised Blackleg Resistance in Diverse Canola ( Brassica napus L.) Lines (2018)

Genomic prediction is becoming a popular plant breeding method to predict the genetic merit of lines. While some genomic prediction results have been reported in canola, none have been evaluated for blackleg disease. Here, we report genomic prediction for seedling emergence, survival rate, and internal infection), using 532 Spring and Winter canola lines. These lines were phenotyped in two replicated blackleg disease nurseries grown at Wickliffe and Green Lake, Victoria, Australia. A transcriptome genotyping-by-sequencing approach revealed 98,054 single nucleotide polymorphisms (SNPs) after quality control. We assessed various genomic prediction scenarios based on Genomic Best Linear Unbiased Prediction (GBLUP), BayesR and BayesRC, which can make use of prior quantitative trait loci information, via cross-validation. Clustering based on genomic relationships showed that Winter and Spring lines were genetically distinct, indicating limited gene flow between sets. Genetic correlations within traits between Spring and Winter lines ranged from 0.68 and 0.90 (mean = 0.76). Based on GBLUP in the whole population, moderate to high genomic prediction accuracies were achieved within environments (0.35-0.74) and were reduced across environments (0.28-0.58). Prediction accuracy within the Spring set ranged from 0.30-0.69, and from 0.19-0.71 within the Winter set. The BayesR model resulted in slightly lower accuracy to GBLUP. The proportion of genetic variance explained by known blackleg quantitative trait loci (QTL) was < 30%, indicating that there is a large reservoir of genetic variation in blackleg traits that remains to be discovered, but can be captured with genomic prediction. However, providing prior information of known QTL in the BayesRC method resulted in an increased prediction accuracy for survival and internal infection, particularly with Spring lines. Overall, these promising results indicate that genomic prediction will be a valuable tool to make use of all genetic variation to improve blackleg resistance in canola.
Aberration corrected analytical electron microscopy studies of sol-immobilized Au + Pd, Au{Pd} and Pd{Au} catalysts used for benzyl alcohol oxidation and hydrogen peroxide production (2011)

In this study, a systematic series of AuPd bimetallic particles were prepared by colloidal synthesis methods, in order to gain better control over the particle size distribution and structure. Particles having random alloy structures, as well as 'designer' particles with Pd-shell/Au-core and Au-shell/Pd-core morphologies, have been prepared and immobilized on both activated carbon and TiO2 supports. Aberration corrected analytical electron microscopy (ACEAM) has been extensively used to characterize these sol-immobilized materials. In particular, state-of-the-art z-contrast STEM-HAADF imaging and STEM-XEDS spectrum imaging has been employed. These techniques have provided invaluable new (and often unexpected) information on the atomic structure, elemental distribution within particles, and compositional variations between particles for these controlled catalyst preparations. In addition, we have been able to compare their differing thermal stability, sintering and wetting behaviors on activated carbon and TiO2 supports. These sol immobilized materials have also been compared as catalysts for (i) benzyl alcohol oxidation and (ii) the direct production of H2O2 in an attempt to elucidate the optimum particle morphology/ support combination for each reaction.
Comparative Study of Al2O3 and HfO2 for Surface Passivation of Cu(In,Ga)Se2 Thin Films: An Innovative Al2O3/HfO2 Multistack Design (2021)

In Cu(In,Ga)Se 2 (CIGS) thin‐film solar cells, interface recombination is one of the most important limiting factors with respect to device performance. Herein, metal–insulator–semiconductor samples are used to investigate and compare the passivation effects of Al 2 O 3 and HfO 2 at the interface with CIGS. Capacitance–voltage–frequency measurements allow to qualitatively and quantitatively assess the existence of high negative charge density ( Q f ≈ −10 12 cm −2 ) and low interface‐trap density ( D it ≈ 10 11 cm −2 eV −1 ). At the rear interface of CIGS solar cells, these, respectively, induce field‐effect and chemical passivation. A trade‐off is highlighted between stronger field‐effect for HfO 2 and lower interface‐trap density for Al 2 O 3 . This motivates the usage of Al 2 O 3 to induce chemical passivation at the front interface of CIGS solar cells but raises the issue of its processing compatibility with the buffer layer. Therefore, an innovative Al 2 O 3 /HfO 2 multistack design is proposed and investigated for the first time. Effective chemical passivation is similarly demonstrated for this novel design, suggesting potential decrease in recombination rate at the front interface in CIGS solar cells and increased efficiency. 300 °C annealing in N 2 environment enable to enhance passivation effectiveness by reducing D it while surface cleaning may reveal useful for alternative CIGS processing methods.
Integrating deep learning algorithm for the lung segmentation with body-part-specific anatomical classification of medical imaging data hosted by Medical Imaging and Data Resource Center (MIDRC) (2023)

Medical Imaging and Data Resource Center (MIDRC) has been built to support AI-based research in response to the COVID-19 pandemic. One of the main goals of MIDRC is to make data collected in the repository ready for AI analysis. Due to data heterogeneity, there is a need to standardize data and make data-mining easier. Our study aims to stratify imaging data according to underlying anatomy using open-source image processing tools. The experiments were performed using Google Colaboratory on computed tomography (CT) imaging data available from the MIDRC. We adopted the existing open-source tools to process CT series (N=389) to define the image sub-volumes according to body part classification, and additionally identified series slices containing specific anatomic landmarks. Cases with automatically identified chest regions (N=369) were then processed to automatically segment the lungs. In order to assess the accuracy of segmentation, we performed outlier analysis using 3D shape radiomics features extracted from the left and right lungs. Standardized DICOM objects were created to store the resulting segmentations, regions, landmarks and radiomics features. We demonstrated that the MIDRC chest CT collections can be enriched using open-source analysis tools and that data available in MIDRC can be further used to evaluate the robustness of publicly available tools.
Optical bistability in axially modulated OmniGuide fibers (2003)

We demonstrate the feasibility of optical bistability in an axially modulated nonlinear OmniGuide fiber through analytical theory and detailed numerical experiments. At 1.55-microm carrier wavelength, the in-fiber devices that we propose can operate with only a few tens of milliwatts of power, can have a nearly instantaneous response and recovery time, and can be shorter than 100 microm.
Supersonic shear imaging (2005)

There is a great interest for developing in vivo quantitative imaging of the shear tissue properties. This can be achieved by using an ultrafast ultrasonic imaging device able to follow in real time the propagation of low frequency transient shear wave in the body. We have developed such an ultrafast scanner that can give up to 5.000 images/s. From the spatio-temporal evolution of the elastic field a local inversion algorithm allows to recover the shear modulus and viscosity map without the limitations induced by diffraction. Transient shear sources are induced by ultrasonic radiation pressure generated by the ultrasonic probe array. The most interesting configuration that induces high amplitude shear waves used a sonic shear source that moves at supersonic velocities. In vitro and in vivo results will be presented that demonstrate the great interest of supersonic shear imaging.
Lignin--Designed Randomness (2012)

0 0 1 282 1608 Biologic Institute 13 3 1887 14.0 Normal 0 false false false EN-US ZH-CN X-NONE Humans have long used wood as a structural material for some of the same reasons that trees use it—it combines great strength, flexibility and durability with a relatively low density. These desirable properties depend partly on lignin , a major chemical constituent of many plants, including trees. Lignin is the most abundant aromatic polymer on earth and the second most abundant organic polymer of any kind, exceeded only by cellulose. It is estimated that 30% of the earth’s non-fossil organic carbon is in the form of lignin. Considering its massive abundance and its high energy content (40% higher than cellulose, gram for gram), it is striking that no organism seems to have tapped it as an energy source. After posing this as an evolutionary enigma, we prepare to address it by reviewing what is known about the structure, biosynthesis and biodegradation of wood in general and of lignin in particular. Then, returning to the enigma, we ask whether it is more readily explained within a Darwinian framework or a design framework. The Darwinian account must somehow reconcile 400 million years of failure to evolve a relatively modest innovation—growth on lignin—with a long list of spectacular innovations thought to have evolved in a fraction of that time. How can one mechanism have been at the same time so effective and so ineffective? That tension vanishes completely when the design perspective is adopted. Terrestrial animal life is crucially dependent on terrestrial plant life, which is crucially dependent on soil, which is crucially dependent on the gradual photo- and biodegradation of lignin. Fungi accomplish th e bio degradation, and the surprising fact that it costs them energy to do so keeps the process gradual. The peculiar properties of lignin therefore make perfect sense when seen as part of a coherent design for the entire ecosystem of our planet.
A single amino acid defines cross‐species reactivity of tree shrew (Tupaia belangeri) CD1d to human invariant natural killer T (iNKT) cells (2009)

The non-classical major histocompatibility complex (MHC) class I molecule CD1d presents lipid antigens to invariant natural killer T (iNKT) cells, which are an important part of the innate immune system. CD1d/iNKT systems are highly conserved in evolution, and cross-species reactivity has been suggested to be a common feature of different animals based on research in humans and mice. However, we found that CD1d from the tree shrew (Tupaia belangeri), a close evolutionary relative of primates, failed to stimulate human iNKT cells, despite being more homologous to human CD1d than that of mouse. Sequence comparison and molecular modelling showed that two of the key amino acid residues in human CD1d proposed to be in direct contact with T-cell receptors were mutated in tree shrew CD1d. Substitution of one of the residues, but not the other, with the human residue enabled tree shrew CD1d to regain the ability to present lipid antigen to human iNKT cells. These results indicate that CD1d/iNKT recognition is species-specific, and that cross-species reactivity may be less common than currently proposed. Also, a naturally occurring CD1d mutation(s) that confers inability to stimulate iNKT cell function may have implications for future studies on CD1d/iNKT-associated diseases.
ChemInform Abstract: Metal Template Control of Self‐Assembly in Supramolecular Chemistry (1997)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
A Framework for Mooring and Anchor Design in Sand Considering Seabed Trenches Based on Floater Hydrodynamics (2023)

Seabed trenches reduce anchor capacity. However, the adverse influence is not considered in the current design, and no guideline is found in engineering practice. This paper presents a framework for mooring and anchor design in sand considering seabed trenches based on floater hydrodynamics. First, a hydrodynamic calculation of the studied floater coupled with the mooring system was conducted. Then, the potential trench profile was assessed using a mooring line–seabed dynamic model. Third, after assessing the suction anchor performance based on its installation and capacity, a refined anchor, caisson–plate gravity anchor (CPGA), was proposed, and the capacity mechanisms were analyzed. It was found that the tensions of mooring lines l1 and l2 resist maximum loads under a 45° load condition. Due to the sand’s high strength, a trench is difficult to form in this mooring type. The suction anchor is not suitable as an anchor for the carbonate sand, considering its installation and capacity. The analyses indicate that the increase in soil stress and soil mobilized range in front of the caisson promotes the capacity of CPGA. This paper provides a framework/example to design moorings and anchors considering potential trenches and provides a solution to the anchor design in carbonate sand.
Broadband dielectric spectroscopy study of the solvent/electrolyte-soaked C-LiFePO4 Li-ion battery electrode (2011)

LGEP 2011 ID = 922
Phase 2 study of cemiplimab, a human monoclonal anti-PD-1, in patients (pts) with metastatic cutaneous squamous cell carcinoma (mCSCC; Group 1): 12-month follow-up. (2019)

9526 Background: Primary analysis (Oct 2017) of cemiplimab (REGN2810) in pts with mCSCC in a Phase 2 study demonstrated substantial antitumor activity, durable responses, and acceptable safety profile. We now report 12-month follow-up data from these pts (NCT02760498; data cutoff date: Sep 20, 2018). Methods: Pts with mCSCC received cemiplimab 3 mg/kg IV every 2 weeks (Q2W). Tumor measurements were performed Q8W. The primary objective was to evaluate objective response rate (ORR; complete response [CR] + partial response [PR]) according to independent central review (per RECIST 1.1 for scans; modified WHO criteria for photos). Results: 59 pts (median age: 71 years) were enrolled. Median duration of follow-up was 16.5 months (range: 1.1–26.6). ORR by central review was 49.2% (95% CI: 35.9–62.5; 10 CRs and 19 PRs [4 CRs and 25 PRs by investigator-assessment (INV)]). Median duration of response (DOR) has not been reached. The longest DOR at data cut-off was 21.6 months and was still ongoing. Observed DOR exceeded 12 months in 22/29 pts (75.9%) with response. Durable disease control rate (stable disease or response for ≥16 weeks) was 62.7% (95% CI: 49.1–75.0). Median observed time to response was 1.9 months (range: 1.7–9.1). Median progression-free survival was 18.4 months (95% CI: 7.3–not evaluable); median overall survival has not been reached. The most common treatment-emergent adverse events (all grades, Grade ≥3) were diarrhea (28.8%, 1.7%), fatigue (25.4%, 1.7%), and nausea (23.7%, 0%). By INV, grade ≥3 immune-related adverse events occurred in 13.6% of pts. Conclusions: This analysis demonstrates substantial antitumor activity and increasing DOR with cemiplimab 3 mg/kg Q2W in pts with mCSCC. There were no new safety signals. These data strongly support the recent FDA approval of cemiplimab-rwlc for pts with mCSCC or locally advanced CSCC who are not candidates for curative surgery or curative radiation. Clinical trial information: NCT02760498.
The Use of Biofeedback with MCLAWS to Guide Respiration and Provide Inspiratory and Expiratory Images from a Single Navigator-Gated 3D Coronary MRA Acquisition (2010)

The mCLAWS technique produces whole heart images in the fastest possible time for a given respiratory pattern and gating window, as well as image datasets at end expiration and end inspiration. The end inspiratory images are generally poorer quality than the end expiratory images because the end inspiratory position is usually more variable and the end inspiratory pause shorter. We have implemented a respiratory biofeedback ‘game’ with a multi-navigator mCLAWS technique to regularise the subjects’ breathing patterns and to enable the acquisition of high quality end inspiratory and end expiratory images from a single whole heart acquisition.
Neutralizing antibody responses to an HIV envelope glycan hole are not easily broadened (2019)

ABSTRACT Extensive studies with subtype A BG505-derived HIV envelope glycoprotein (Env) SOSIP immunogens have revealed that the dominant autologous neutralizing site in rabbits is located in an exposed region of the heavily glycosylated trimer that lacks potential N-linked glycosylation sites at positions 230, 241, and 289. The Env derived from B41, a subtype B virus, shares a glycan hole centered on positions 230 and 289. BG505 and B41 SOSIP immunogens were combined to test whether immunization in rabbits could induce broader Tier 2 neutralizing responses to the common glycan hole shared between BG505 and B41. Here we isolated autologous neutralizing antibodies (nAbs) that were induced by immunization with B41 SOSIP alone, as well as B41 and BG505 co-immunization, and describe their structure in complex with the B41 SOSIP trimer. Our data suggest that distinct autologous nAb lineages are induced by BG505 and B41 immunogens, even when both immunogens were administered together. In contrast to previously described BG505 glycan hole antibodies, the B41-specific nAbs accommodate the highly conserved N241 glycan (&gt;97% conserved), which is present in B41. Single particle cryo-electron microscopy (cryoEM) studies confirmed that B41 and BG505-specific nAbs bind to overlapping glycan hole epitopes. In an attempt to broaden the reactivity of a B41-specific nAb, mutations in the BG505 glycan hole epitope guided by our high-resolution data only recovered partial binding. Overall, designing prime-boost immunogens to increase the breath of nAb responses directed at glycan holes epitopes remains challenging even when the typically immunodominant glycan holes despite overlap with different Envs. IMPORTANCE A glycan hole is one of the most dominant autologous neutralizing epitopes targeted on BG505 and B41 SOSIP trimer immunized rabbits. Our high-resolution cryoEM studies of B41 in complex with a B41-specific antibody complex elucidate the molecular basis of this strain-specific glycan hole response. We conclude that eliciting cross-reactive responses to this region would likely require hybrid immunogens that bridge between BG505 and B41.
Winning Isn't Everything: Training Human-Like Agents for Playtesting and Game AI. (2019)

Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. We consider an alternative approach that instead addresses game design for a better player experience by training human-like game agents. Specifically, we study the problem of training game agents in service of the development processes of the game developers that design, build, and operate modern games. We highlight some of the ways in which we think intelligent agents can assist game developers to understand their games, and even to build them. Our early results using the proposed agent framework mark a few steps toward addressing the unique challenges that game developers face.