gebhart/patrepeval huggingface dataset:
Immunological Relationship between the Class I Epitope of Streptococcal M Protein and Myosin (1998)

The class I epitope of streptococcal M protein is an epidemiological marker for acute rheumatic fever (ARF)-associated serotypes of group A streptococci and is recognized by anti-M protein monoclonal antibody (MAb) 10B6. Using MAb 10B6, we determined the relationship between the class I epitope of M protein and the α-helical coiled-coil protein myosin. MAb 10B6 reacted by enzyme-linked immunosorbent assay and Western blotting with human cardiac myosin and rabbit skeletal myosin and its heavy meromyosin (HMM) subfragment. Overlapping synthetic peptides of M5 protein were used to identify the region of M5 protein recognized by MAb 10B6. Two C repeat peptides (C2A and C3) containing the amino acid sequence KGLRRDLDASREAK reacted with MAb 10B6. Partial sequence identity, RRDL, was found in the HMM fragment of myosin, which reacted with MAb 10B6. However, not all peptides of M5 protein and myosin containing the RRDL sequence reacted with MAb 10B6. ARF sera and sera from uncomplicated pharyngitis (UNC) reacted with C repeat region peptides of M protein, while acute glomerulonephritis sera were not as reactive. Affinity-purified human antibody to peptide C3 reacted with myosin. The data demonstrate that the class I epitope of M protein is immunologically cross-reactive with myosin and the HMM subfragment, and antibodies to peptide C3 and myosin were present in ARF and UNC sera.
Growth of branched gold nanoparticles on solid surfaces and their use as surface-enhanced Raman scattering substrates (2015)

Branched gold nanoparticles were synthesized directly on solid surfaces (silicon, glass, ITO) in high yield. They revealed strong SERS activity for the detection of R6G with an enhancement factor estimated as greater than 8 orders of magnitude.
Ubiquitous Sensors: When Will They Be Here? (2009)

Chemical and biological sensors are necessary for making continuous measurements in a variety of settings. A typical sensor comprises a molecular recognition element coupled to a transducer. Binding of the analyte to the recognition element leads to signal transduction. Many sensors employ an extrinsic label to indirectly signal the presence of the analyte. Label-free methods have the advantage that no exogenous reagents are required, making the sensor simple to implement. New label-free transduction methods should facilitate the wider application of sensors. Challenges remain with reproducibility, calibration, and manufacturability. Solving these problems will require an interdisciplinary collaboration between chemists, biologists, biochemists, and engineers. An article by Sailor and co-workers in this issue takes a significant step toward this goal. The availability of inexpensive sensors for wide-scale deployment will transform society in terms of health care as well as home and workplace monitoring.
Broad donor consent for human biobanks in Germany and Europe: a strategy to facilitate cross-border sharing and exchange of human biological materials and related data (2019)

Abstract Background Human biobanks are generally recognized as essential resources for effective biomedical research. All over the world biosamples and data from human subjects are collected in large biobanks. The biological material is stored long term for current and future (undetermined) research issues, which often require cross-border exchange of biosamples and related data. Content Commonly, the informed consent for research on human biospecimen is intended to cover only defined, specific research objectives. In June 2016, the biobank Task-Force of the Working Party of the German Medical Ethics Committees (WP-GMEC) updated its template for the broad use of human biological samples and related data. It complies with the current Organisation for Economic Co-operation and Development (OECD) and World Medical Association (WMA) recommendations and furnishes a framework that permits long-term storage and multi-purpose research use of human biological material and related data, including cross-border research. However, both (i) human biobanks storing and (ii) research projects requesting “broad consent” biological samples generally require an ethical approval; in addition, “broad consent” conditions should be reciprocated by making biobank processes transparent and by fostering both donor and public involvement. Outlook The broad consent template of the WP-GMEC clearly states that biological samples and data donated for medical research serve to address current and future research questions. It appears perfectly suited as a template for a Europe-wide harmonized broad consent facilitating biobank-based cross-border research.
Contextual Bandit with Adaptive Feature Extraction (2018)

We consider an online decision making setting known as contextual bandit problem, and propose an approach for improving contextual bandit performance by using an adaptive feature extraction (representation learning) based on online clustering. Our approach starts with an off-line pre-training on unlabeled history of contexts (which can be exploited by our approach, but not by the standard contextual bandit), followed by an online selection and adaptation of encoders. Specifically, given an input sample (context), the proposed approach selects the most appropriate encoding function to extract a feature vector which becomes an input for a contextual bandit, and updates both the bandit and the encoding function based on the context and on the feedback (reward). Our experiments on a variety of datasets, and both in stationary and non-stationary environments of several kinds demonstrate clear advantages of the proposed adaptive representation learning over the standard contextual bandit based on "raw" input contexts.
Deep Learning for Consumer Devices and Services 2—AI Gets Embedded at the Edge (2019)

The recent explosive growth of deep learning is enabling a new generation of intelligent consumer devices. Specialized deep learning inference now provides data analysis capabilities that once required an active cloud connection, while reducing latency and enhancing data privacy. This paper addresses current progress in Edge artificial intelligence (AI) technology in several consumer contexts including privacy, biometrics, eye gaze, driver monitoring systems, and more. New developments and challenges in edge hardware and emerging opportunities are identified. Our previous article, “Deep learning for consumer devices and services,” introduced many of the basics of deep learning and AI. In this paper, we explore the current paradigm shift of AI from the data center into CE devices-“Edge-AI”.
3,3′:5,6-Di-O-isopropylidene-3-C-hydroxymethyl-D-allono-1,4-lactone: an organic structure containing large unoccupied voids (2007)

The Kiliani reaction of d-hamamelose with sodium cyanide, followed by acetonation, affords crystalline 3,3′:5,6-di-O-isopropyl­idene-3-C-hydroxy­methyl-d-allono-1,4-lactone, C13H20O7, a carbon-branched sugar with potential as an enanti­omerically pure carbohydrate scaffold. The lactone has one single free hydroxyl group unprotected, with six other functional groups protected in a single step as ketals or esters. The resulting crystal structure is unusual in that it contains large voids (544 Å3) within which there is no evidence of included solvent.
Spin-exchange optical pumping using a frequency-narrowed high power diode laser (2000)

We describe a method for frequency narrowing commercial high power diode lasers from 2 to 0.1 nm bandwidth with modest loss of power (&amp;lt;2 dB). The resulting laser light is well suited for spin-exchange optical pumping, and we demonstrate that the polarization produced by a 2.5 W narrowband laser exceeds that of a 15 W array by 40% in our optical pumping system.
Language skills and identity in bilingual education: a case study of a bilingual primary school in England (2021)

A common concern for bilingual education is that while it supports additional language learning, it detracts from students’ progress with the society’s dominant language. Several studies in this flourishing area of research have focused on bilingual educational settings using the dominant societal language and a language of that is the native one of the students. Findings are hard to generalise to other educational settings, due to the inherent heterogeneity of bilingual education, including not only the choice of languages used but also the amount and type of exposure to each of them. Here we report on the first stage of a longitudinal study of students in a bilingual primary school in England which uses English, the dominant societal language, and French, a foreign language which is not the home language of any sizeable group of students in the school. In the quantitative part of this research we report that primary school students were achieving progress with foundational language skills in English within the expected range, and that this was the case both for monolingual students as well as children who had an additional home language. In the qualitative part we report on the role which bilingual education can play in the construction of students’ broader multilingual identities. The emerging picture is one where students in this type of bilingual setting are not negatively impacted in their progress with the dominant societal language, and in fact, experience positive changes thanks to the formation of a multilingual identity.
Implementation of deep learning artificial intelligence in vision-threatening disease screenings for an underserved community during COVID-19 (2023)

Deep learning artificial intelligence can increase the efficiency and accessibility of vision-threatening disease screenings, particularly in underserved communities. Deep learning artificial intelligence should be adaptable to different environments. Consideration should be given to how deep learning artificial intelligence can best be utilized in a real-world application, whether in computer-aided or autonomous diagnosis.
Nanoconjugation of PSMA-Targeting Ligands Enhances Perinuclear Localization and Improves Efficacy of Delivered Alpha-Particle Emitters against Tumor Endothelial Analogues (2015)

This study aims to evaluate the effect on killing efficacy of the intracellular trafficking patterns of α-particle emitters by using different radionuclide carriers in the setting of targeted antivascular α-radiotherapy. Nanocarriers (lipid vesicles) targeted to the prostate-specific membrane antigen (PSMA), which is unique to human neovasculature for a variety of solid tumors, were loaded with the α-particle generator actinium-225 and were compared with a PSMA-targeted radiolabeled antibody. Actinium-225 emits a total of four α-particles per decay, providing highly lethal and localized irradiation of targeted cells with minimal exposure to surrounding healthy tissues. Lipid vesicles were derivatized with two types of PSMA-targeting ligands: a fully human PSMA antibody (mAb) and a urea-based, low-molecular-weight agent. Target selectivity and extent of internalization were evaluated on monolayers of human endothelial cells (HUVEC) induced to express PSMA in static incubation conditions and in a flow field. Both types of radiolabeled PSMA-targeted vesicles exhibit similar killing efficacy, which is greater than the efficacy of the radiolabeled control mAb when compared on the basis of delivered radioactivity per cell. Fluorescence confocal microscopy demonstrates that targeted vesicles localize closer to the nucleus, unlike antibodies which localize near the plasma membrane. In addition, targeted vesicles cause larger numbers of dsDNAs per nucleus of treated cells compared with the radiolabeled mAb. These findings demonstrate that radionuclide carriers, such as PSMA-targeted lipid-nanocarriers, which localize close to the nucleus, increase the probability of α-particle trajectories crossing the nuclei, and, therefore, enhance the killing efficacy of α-particle emitters.
Low noise subpicosecond pulse generation from a 22 GHz AlInGaAs multiple quantum well laser by direct RF modulation (2012)

Here we present 860 fs pulses from a monolithic AlInGaAs multiple quantum well two-section MLL fabricated by employing a very simple self-aligned wet etching technique. By using Benzocyclobutene (BCB) as the isolation layer and minimizing the metal pad size, we are able to modulate the SA at 22 GHz and synchronize the laser to an external source. By doing so we achieve very effective FHML (280 fs timing jitter) which shows distinct advantages over other methods.
Genetic Determinants Enabling Medium-Dependent Adaptation to Nafcillin in Methicillin-Resistant Staphylococcus aureus (2020)

Antimicrobial susceptibility testing standards driving clinical decision-making have centered around the use of cation-adjusted Mueller-Hinton broth (CA-MHB) as the medium with the notion of supporting bacterial growth, without consideration of recapitulating the <i>in vivo</i> environment. However, it is increasingly recognized that various medium conditions have tremendous influence on antimicrobial activity, which in turn may have major implications on the ability of <i>in vitro</i> susceptibility assays to predict antibiotic activity <i>in vivo.</i> To elucidate differential growth optimization and antibiotic resistance mechanisms, adaptive laboratory evolution was performed in the presence or absence of the antibiotic nafcillin with methicillin-resistant <i>Staphylococcus aureus</i> (MRSA) TCH1516 in either (i) CA-MHB, a traditional bacteriological nutritionally rich medium, or (ii) Roswell Park Memorial Institute (RPMI), a medium more reflective of the <i>in vivo</i> host environment. Medium adaptation analysis showed an increase in growth rate in RPMI, but not CA-MHB, with mutations in <i>apt</i>, adenine phosphoribosyltransferase, and the manganese transporter subunit, <i>mntA</i>, occurring reproducibly in parallel replicate evolutions. The medium-adapted strains showed no virulence attenuation. Continuous exposure of medium-adapted strains to increasing concentrations of nafcillin led to medium-specific evolutionary strategies. Key reproducibly occurring mutations were specific for nafcillin adaptation in each medium type and did not confer resistance in the other medium environment. Only the <i>vraRST</i> operon, a regulator of membrane- and cell wall-related genes, showed mutations in both CA-MHB- and RPMI-evolved strains. Collectively, these results demonstrate the medium-specific genetic adaptive responses of MRSA and establish adaptive laboratory evolution as a platform to study clinically relevant resistance mechanisms.<b>IMPORTANCE</b> The ability of pathogens such as <i>Staphylococcus aureus</i> to evolve resistance to antibiotics used in the treatment of infections has been an important concern in the last decades. Resistant acquisition usually translates into treatment failure and puts patients at risk of unfavorable outcomes. Furthermore, the laboratory testing of antibiotic resistance does not account for the different environment the bacteria experiences within the human body, leading to results that do not translate into the clinic. In this study, we forced methicillin-resistant <i>S. aureus</i> to develop nafcillin resistance in two different environments, a laboratory environment and a physiologically more relevant environment. This allowed us to identify genetic changes that led to nafcillin resistance under both conditions. We concluded that not only does the environment dictate the evolutionary strategy of <i>S. aureus</i> to nafcillin but also that the evolutionary strategy is specific to that given environment.
iPROBE-O: FIB-aware Place and Route for Probing Protection Using Orthogonal Shields (2022)

Focused ion beam (FIB) probing attacks rely on advanced milling and deposition capabilities to significantly threaten the confidentiality of on-chip security assets such as private keys and device configuration. The existing countermeasures either suffer from the prohibitively high area overhead or low reliability, failing to serve as a perfect fit to address the issues. Recently, iPROBE framework has been proposed as a physical design flow enhancing the layout/device security against FIB attacks by adding additional shield nets at a minor cost. However, the parallel shielding methodology and metrics of iPROBE merely focus on the perpendicular FIB model instead of covering a more threatening one, tilted probing. In this paper, we present iPROBE-O to enable FIB-aware placement and routing using orthogonal shields to thwart both perpendicular and titled FIB intrusions. Besides, we extend the definition of shield coverage in the previous iPROBE work and propose the tilted shield security metric to comprehensively quantify the shield protection on every layer beneath the shield against tilted probing attacks. This metric allows users to choose the desired scheme such as shield layers and density accordingly for the optimal trade-off between overhead and security. Moreover, to alleviate the routing congestion risks from the orthogonal shields, we introduce keepout region between the shield drivers and target cells allowing more space and analytically assessing how the factors keepout region and a total number of gates jointly impact the overall protection strength. We demonstrate the effectiveness of iPROBE-O framework on a variety of benchmarks including AES, DES, and Simon by reducing up to 80% decrease on the exposed area can be achieved and the timing and area overhead is less than 3%.
Performanace and reliability analysis of 3D-integration structures employing Through Silicon Via (TSV) (2009)

Large thermal mismatch stress can be introduced in 3D-Integration structures employing Through-Silicon-Via (TSV). The stress distribution in silicon and interconnect is affected by the via diameter and layout geometry. The TSV induced stress changes silicon mobility and ultimately alters device performance. The mobility and performance change differs in nand p- silicon and is a function of the distance to the TSV. In addition, the TSV induced stress acts on the barrier layer, the landing pad, the interconnects, and the dielectrics. The interactions with defects may lead to crack nucleation and growth, and compromise the structure reliability. Furthermore, the material choice that reduces silicon stress for less impact on performance may increase stresses in other regions where reliability is of concern. This paper studies these effects and their dependence on various integration configurations.
Directing Neurite Growth in 3D Collagen Scaffolds With Gradients of Mechanical Properties (2007)

Biomaterial scaffolds for nerve and spinal cord regeneration must not only promote neurite re-growth but also direct it. Several cell types, including neurons, respond to the mechanical properties of the substrate on which they are grown. We believe that gradients of mechanical properties can be used to direct neurons. To spatially control the mechanical properties, gradients of genipin — a naturally occurring, cell-tolerated crosslinking agent — are created in 3D through a compliant collagen gel using microfluidics. Gradients of mechanical properties are evaluated by measuring genipin-induced fluorescence, which we have previously correlated to mechanical properties. Growth of neurites was evaluated in gels of uniform stiffness and a gradient generated by incubation in 0 to 1 mM genipin for 12hrs to produce approximately an order of magnitude change in the shear modulus. Neurite growth was evaluated 5 days after gradient formation. Neurites demonstrated a directional bias against the gradient of stiffness. These results demonstrate that neurites can respond to subtle gradients of mechanical properties within a 3D scaffold and point to opportunities to manipulate properties for directed nerve and spinal cord regeneration.
Microwave Transparent Catalytic Falling‐Film Microreactor for Automated Operation (2018)

Abstract Falling‐film microreactors at different scales were developed to study heterogeneously catalyzed gas‐liquid reactions under microwave irradiation, as part of the EU FP7 project MAPSYN. At pilot scale, this device formed the core part of a fully automated demonstration plant which was used for semi‐hydrogenation reactions at an industrial site. The microchannels of the reaction plate were coated with novel selective catalysts. A special fiber‐optical sensor applicable under microwave irradiation and needed for controlling the liquid level in the sump via the flow rate of the discharge pump was developed and electrically connected with the automation system.
The Pulmonary-Alveolar Macrophage (1979)

(Second of Two Parts)Immunologic Functions of the Pulmonary-Alveolar Macrophage (PAM)The PAM functions importantly in pulmonary defense by participating in specific immunologic reactions and by interacting with other components of the immune system. The composition of the bronchoalveolar lymphoid system has been studied by means of bronchopulmonary lavage. These washings contain lymphocytes with T and B-surface markers as well as lymphocytes with "null" characteristics.111 112 113 114 In one study of human subjects, T cells comprised 47 per cent of the bronchial lymphocyte population, B cells 19 per cent and null cells 34 per cent.111 Human bronchopulmonary-lavage fluid contains IgA (both 11S . . .
Onboard learning-based fuel consumption optimization in series hybrid electric vehicles (2012)

This paper considers an on-line approach to reducing engine fuel consumption in a series hybrid electric vehicle operated under power smoothing strategy, in which the generator power is slowly varying. An optimization algorithm adjusts the engine speed set-point (and other engine actuator settings as appropriate) on-line, as the vehicle is driven. The actual generator power is estimated, and the battery power output is adjusted to ensure that the wheel power and the drivability are unaffected. With this approach, operating points on the optimal operating line (OOL) can be learned during vehicle driving thus compensating for the effects of the engine aging and variability while reducing upfront calibration time and effort. In the paper, the control approach is defined and an optimization algorithm is examined. Simulation results are reported.
QG-net (2018)

The ever growing amount of educational content renders it increasingly difficult to manually generate sufficient practice or quiz questions to accompany it. This paper introduces QG-Net, a recurrent neural network-based model specifically designed for automatically generating quiz questions from educational content such as textbooks. QG-Net, when trained on a publicly available, general-purpose question/answer dataset and without further fine-tuning, is capable of generating high quality questions from textbooks, where the content is significantly different from the training data. Indeed, QG-Net outperforms state-of-the-art neural network-based and rules-based systems for question generation, both when evaluated using standard benchmark datasets and when using human evaluators. QG-Net also scales favorably to applications with large amounts of educational content, since its performance improves with the amount of training data.