gebhart/patrepeval huggingface dataset:
Rewriting the Genetic Code (2017)

The genetic code-the language used by cells to translate their genomes into proteins that perform many cellular functions-is highly conserved throughout natural life. Rewriting the genetic code could lead to new biological functions such as expanding protein chemistries with noncanonical amino acids (ncAAs) and genetically isolating synthetic organisms from natural organisms and viruses. It has long been possible to transiently produce proteins bearing ncAAs, but stabilizing an expanded genetic code for sustained function in vivo requires an integrated approach: creating recoded genomes and introducing new translation machinery that function together without compromising viability or clashing with endogenous pathways. In this review, we discuss design considerations and technologies for expanding the genetic code. The knowledge obtained by rewriting the genetic code will deepen our understanding of how genomes are designed and how the canonical genetic code evolved.
Bend Testing of IMM and Triple Junction Solar Cells (2018)

A number of SolAero Inverted Metamorphic Multijunction (IMM) and ZTJ solar cells, both bare and CICs, were subjected to ever increasing displacement 4-point bend testing. Following each flexure, the cells were characterized by current-voltage and electroluminescence measurements. The data demonstrated that on average IMM CICs can be displaced 65% further than ZTJ CICs before fracturing. The IMM CICs are also more easily flexed, bending ~65% further under equivalent load. Finally, the electrical degradation behavior were very different for the IMM and ZTJ devices, with the ZTJ demonstrating a step-like loss in performance when fractured whereas the IMM demonstrated a more graceful degradation. Modifications to the IMM configuration may be beneficial in significantly reducing the degradation, providing an even larger mechanical benefit.
Minimum Data Requirement for Neural Networks Based on Power Spectral Density Analysis (2012)

One of the most critical challenges ahead for diesel engines is to identify new techniques for fuel economy improvement without compromising emissions regulations. One technique is the precise control of air/fuel ratio, which requires the measurement of instantaneous fuel consumption. Measurement accuracy and repeatability for fuel rate is the key to successfully controlling the air/fuel ratio and real-time measurement of fuel consumption. The volumetric and gravimetric measurement principles are well-known methods for measurement of fuel consumption in internal combustion engines. However, the fuel flow rate measured by these methods is not suitable for either real-time control or real-time measurement purposes because of the intermittent nature of the measurements. This paper describes a technique that can be used to find the minimum data [consisting of data from just 2.5% of the non-road transient cycle (NRTC)] to solve the problem concerning discontinuous data of fuel flow rate measured using an AVL 733S fuel meter for a medium or heavy-duty diesel engine using neural networks. Only torque and speed are used as the input parameters for the fuel flow rate prediction. Power density analysis is used to find the minimum amount of the data. The results show that the nonlinear autoregressive model with exogenous inputs could predict the particulate matter successfully with R(2) above 0.96 using 2.5% NRTC data with only torque and speed as inputs.
Demonstration of 3,010 km WDM Transmission in 3.83 THz Bandwidth Using SOAs (2020)

We transmit 5.53Tb/s over 3,010km using SOAs, ultralow-loss fibers (0.145dB/km) and a new coded modulation format with SE=1.5 b/s/Hz. C-band transmission capacity in a ~602km circulating loop testbed with 3.83THz bandwidth is confirmed with FEC.
Synthesis and Characterization of Gallosilicate Molecular Sieves with High Gallium Contents:  Examples of Structure Direction Exerted by Gallium (2000)

Hydrothermal syntheses of the microporous gallosilicates TNU-1 (CGS topology), TNU-2 (GIS topology), TNU-3 (a synthetic counterpart of the natural zeolite gonnardite, NAT topology), and TNU-4 (a synthetic counterpart of the natural zeolite natrolite, NAT topology) are presented. In the range of synthesis conditions studied here, the presence of Ga itself is found to be the critical factor directing the crystallization of microporous gallosilicate materials with topologies different from those of the aluminosilicate zeolites obtained when Ga is replaced by Al. This suggests that the introduction of Ga into silicate synthesis mixtures may be a viable route for the synthesis of novel low-silica zeolite structures. The Si, Ga ordering in TNU-3 and TNU-4 materials is investigated in an attempt to understand why the crystallization of the same synthesis mixture at different temperatures results in two materials with the same topology and chemical composition but with different symmetries. A high degree of Si, Ga ordering is observed in TNU-4 by 29Si MAS NMR, and possibly as a consequence, its 71Ga MAS NMR spectrum clearly shows a line shape affected by second- order quadrupolar interactions rarely found in these kinds of materials.
Supplementary Data from Dual Targeting of CDK and Tropomyosin Receptor Kinase Families by the Oral Inhibitor PHA-848125, an Agent with Broad-Spectrum Antitumor Efficacy (2023)

Supplementary Data from Dual Targeting of CDK and Tropomyosin Receptor Kinase Families by the Oral Inhibitor PHA-848125, an Agent with Broad-Spectrum Antitumor Efficacy
Reduction of quantization noise in PCM speech coding (1980)

A new technique to reduce the effect of quantization noise in PCM speech coding is proposed. The procedure consists of using dither noise to ensure that the quantization errors can be modeled as additive signal-independent noise, and then reducing this noise through the use of a noise reduction system. The procedure is illustrated with examples.
Characteristics of Chronic Rejection in Heart Transplantation: Important Elements of Pathogenesis and Future Treatments (2010)

Although 85,000 heart transplantations have been performed worldwide, coronary allograft vasculopathy (CAV), which is a phenomenon of chronic rejection, is still a serious problem. Because CAV involves all the allograft arteries, angioplasty, stenting or bypass grafting are not practical treatment options. Therefore, CAV is the biggest long-term limitation in cardiac allograft recipients. Although the cause of CAV is mostly immunologic, nonimmune pathways also contribute to its development. Several cytokines, chemokines and adhesion molecules play a critical role in the process. Cell adhesion, migration and proliferation of bone marrow progenitor and and other cells are involved in its development. Although there is not an established clinical strategy for preventing or treating CAV, recent investigations have provided some promising methodologies. Progress in DNA technology, such as antisense oligodeoxynucleotides (ODNs) to regulate the transcription of disease-related genes, has an important role in its therapeutic applications. Antisense ODN transfection preventing CAV in experimental cardiac allografts has been reported for the first time. The ODN strategy has not only been useful in the experimental studies, but is also a novel clinical strategy for gene therapy. The pathological and immunological characteristics of CAV and some promising methodologies for prevention of the disease are reviewed.
Data-driven inversion-based control of nonlinear systems (2015)

In this paper, we introduce the Data-Driven Inversion-Based Control (D2-IBC) method for nonlinear control system design. The method relies on a two degree-of-freedom architecture, with a nonlinear controller and a linear controller running in parallel, and does not require any detailed physical knowledge of the plant to control. Specically, we use input/output data to synthesize the control action by employing convex optimization tools only. We show the eectiveness of the proposed approach on a simulation example, where the D2-IBC performance is also compared to that of the Direct FeedbacK (DFK) design approach, a benchmark method for nonlinear controller design from data.
Resource Management Policies for Wireless and Visual Sensor Networks (2008)

In this book, we explore application-aware techniques for managing the limited resources in wireless sensor networks, focusing on ways to maximize the network lifetime for clustered wireless sensor networks and for visual sensor networks. First, we explore energy efficient clustered network architectures, as well as cluster head selection policies that satisfy the application-specific QoS constraints. Next, as we believe that the real potential of wireless sensor networks lies in their integration with advanced sensing modalities, we explore the use of application-aware resource allocation specifically for visual sensor networks. Designing efficient visual sensor networks is challenging due to their high demand for network resources, their tight QoS requirements and the unique sensing capabilities of the imagers. We focus specifically on camera-node management policies, discussing methods for the selection and scheduling of camera-nodes in user-centric visual sensor networks. These management strategies provide an efficient means of managing the network's resources by reducing the redundant data while providing the user with the required quality of data.
Motor, somatosensory and auditory cortex localization by fMRI and MEG (1998)

Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) were performed in six subjects during self-paced finger movement performance, tactile somatosensory stimulation and binaural auditory stimulation using identical stimulation paradigms. Both functional imaging modalities localized brain activity in adjacent areas of anatomically correct cortex. The mean distances measured between fMRI activity and the corresponding MEG dipoles were 10.1 mm (motor), 10.7 mm (somatosensory), 13.5 mm (auditory right hemisphere) and 14.3 mm (auditory left hemisphere). The distances found may reflect the correlation between electrophysiological and hemodynamic responses due to the different underlying substrates of neurophysiology measured by fMRI and MEG: BOLD contrast vs neuronal biomagnetic activity.
Design of integrated planar Marchand balun using physical transformer model (2009)

A simple and effective technique for designing integrated planar Marchand balun is presented in this paper. The approach uses the physical transformer model to replace the lossy coupled transmission lines in a conventional Marchand balun design. As a demonstration and validation of the design approach, a Marchand balun using silicon-based integrated passive device (IPD) technology is carried out at a center frequency of 2.45 GHz. The measured results show low insertion loss and high balance property over a wide bandwidth for the implemented Marchand balun. Comparison among modeled, EM simulated and measured results shows good agreement.
I-SEE: Intelligent, Secure, and Energy-Efficient Techniques for Medical Data Transmission Using Deep Reinforcement Learning (2020)

The rapid evolution of remote health monitoring applications is foreseen to be a crucial solution for facing an unpredictable health crisis and improving the quality of life. However, such applications come with many challenges, including: the transmission of a large amount of private medical data and the limited power budget for battery-operated devices. Thus, this article proposes an intelligent, secure, and energy-efficient (I-SEE) framework for secure and energy-efficient medical data transmission, leveraging the potential of physical-layer security. In particular, we incorporate a practical secrecy metric, namely, the secrecy outage probability (SOP), along with the adaptive compression at the edge for providing a secure solution for health monitoring applications. In the proposed framework, we first formulate an optimization problem that maximizes the energy efficiency, while maintaining quality-of-service constraints of the health application. Second, we propose a deep reinforcement learning process that obtains the optimal strategy for secure data transmission. Specifically, a multiobjective reward function is defined to optimize energy efficiency and distortion, resulting from the compression scheme. Then, a deep deterministic policy gradients (DDPGs) algorithm, named Static-DDPG is proposed to solve our problem efficiently. Third, the problem is extended to consider the battery lifetime maximization with varying channel conditions. Indeed, a Dynamic-DDPG algorithm is proposed in order to allow the edge to adapt to the environment dynamics while maximizing its battery lifetime. The conducted simulations validate the efficiency of the proposed algorithms in terms of finding the optimal policy that addresses the tradeoff between the considered conflicting objectives, along with the battery lifetime maximization
Design of a synthetic yeast genome (2017)

We describe complete design of a synthetic eukaryotic genome, Sc2.0, a highly modified <i>Saccharomyces cerevisiae</i> genome reduced in size by nearly 8%, with 1.1 megabases of the synthetic genome deleted, inserted, or altered. Sc2.0 chromosome design was implemented with BioStudio, an open-source framework developed for eukaryotic genome design, which coordinates design modifications from nucleotide to genome scales and enforces version control to systematically track edits. To achieve complete Sc2.0 genome synthesis, individual synthetic chromosomes built by Sc2.0 Consortium teams around the world will be consolidated into a single strain by "endoreduplication intercross." Chemically synthesized genomes like Sc2.0 are fully customizable and allow experimentalists to ask otherwise intractable questions about chromosome structure, function, and evolution with a bottom-up design strategy.
Impaired wakefulness is associated with reduced anterior cingulate CBF in patients with normal pressure hydrocephalus (2004)

IW in NPH is associated with reduced rrCBF in the anterior cingulate cortex. Improved wakefulness following surgery corresponds to rrCBF increments in the frontal association cortex. This study provides support for a functional coupling between frontal, hippocampal, thalamic and mesencephalic rrCBF in NPH at large.
CATBERT: Context-Aware Tiny BERT for Detecting Social Engineering Emails (2020)

Targeted phishing emails are on the rise and facilitate the theft of billions of dollars from organizations a year. While malicious signals from attached files or malicious URLs in emails can be detected by conventional malware signatures or machine learning technologies, it is challenging to identify hand-crafted social engineering emails which don't contain any malicious code and don't share word choices with known attacks. To tackle this problem, we fine-tune a pre-trained BERT model by replacing the half of Transformer blocks with simple adapters to efficiently learn sophisticated representations of the syntax and semantics of the natural language. Our Context-Aware network also learns the context representations between email's content and context features from email headers. Our CatBERT(Context-Aware Tiny Bert) achieves a 87% detection rate as compared to DistilBERT, LSTM, and logistic regression baselines which achieve 83%, 79%, and 54% detection rates at false positive rates of 1%, respectively. Our model is also faster than competing transformer approaches and is resilient to adversarial attacks which deliberately replace keywords with typos or synonyms.
13C NMR rotating frame relaxation in a solid with strongly coupled protons: Polyethylene (1979)

The validity of interpreting measured rotating frame relaxation times, T1ρC*, in terms of molecular motion is investigated for crystalline, oriented, linear polyethylene (PE) as a representative rigid organic solid with reasonably strong dipolar couplings. T1ρC* data are presented at three temperatures, −100, 28, and 100 °C and for 13C rf fields, ν1C, in the range 35&amp;lt;ν1C&amp;lt;90 kHz, for the orientation where B0 is parallel to the PE chain axes. With the exception of the T1ρC* data taken at ν1C≳80 kHz and T=100 °C, all T1ρC* data observed were determined not by molecular motion, but rather by spin–spin effects in which the spin-locked carbon system seeks to equilibrate with the proton dipolar system with a characteristic time constant TCHD(ν1C), while at the same time the proton dipolar system is equilibrating with the lattice with a time constant T1D. The TCHD values deduced from T1ρC* support existing theory which predicts that TCHD(ν1C) ∝ exp(2πν1CτD) where τD is the correlation time for dipolar fluctuations. A calculation of τD from PE crystal structure agrees very well with the experimentally determined τD of 24 μs. Further experimental proof of the importance of the spin–spin contribution to T1ρC* is demonstrated via changes in the carbon rotating frame magnetization, MSL(τ), for differing states of proton dipolar order. The question of extracting information about molecular motion from T1ρC* data is examined under the assumption that the total reduced correlation function for the local proton dipolar field at a carbon nucleus is the product of a Lorentzian reduced correlation function describing dipolar fluctuations and an exponential reduced correlation function describing molecular motion. It is shown for molecular motion in the long correlation time regime and for sufficiently large ν1C that contributions to T1ρC* from molecular motion and dipolar fluctuations are cleanly separated. Pertinent background material for the interpretation of T1ρC* data is also presented; this includes effects of sample spinning, transients in carbon and proton magnetization, and ambiguities which arise when molecular motion is fast enough to cause some averaging of the static dipolar line shape. Criteria are offered whereby one can decide on the validity of interpreting T1ρC* data in terms of molecular motion. As an example, the T1ρC* data point for ν1C=87 kHz and T=100 °C is interpreted in terms of molecular motion and the deduced correlation time, assuming a flip–flop motion of the polymer chains, is shown to be qualitatively consistent with published proton T1ρH results. Finally, 13C longitudinal relaxation time measurements are discussed as a possible alternative to T1ρC* for obtaining information about molecular motion.
High Density Pipelined 8bit Multiplier Systolic Arrays for FPGA (2020)

With the advent of AI and machine learning as the highest profile FPGA applications, INT8 performance is currently one of the key benchmarking metrics. In current devices, INT8 multipliers must be extracted from higher precision multipliers. Recently, we reported the implementation of a mixed DSP Block and soft logic design, with 22,400 INT8 multipliers, and a system clock rate of 416MHz, on the Intel Stratix 10 2800 chip.
Flow cytometric readout based on Mitotracker Red CMXRos staining of live asexual blood stage malarial parasites reliably assesses antibody dependent cellular inhibition (2012)

A flow cytometry method based on CMXRos staining for detection of live parasite populations has been optimized. This is a rapid and sensitive method with high inter-assay reproducibility which can reliably determine the anti-parasite effect mediated by antibodies in functional in vitro assays such as ADCI assay.
Moisture Resistance of Plasma Enhanced Chemical Vapor Deposited Oxides Used for Ultralarge Scale Integrated Device Applications (1995)

The moisture resistance of plasma enhanced chemical vapor deposited (PECVD) oxide films used in ultralarge scale integrated (ULSI) device applications has been characterized using infrared (IR) spectroscopy. The differences in the moisture absorption characteristics between tetraethylorthosilicate (TEOS) and silane‐based PECVD oxides are presented. Our results indicate that the film thickness and the as‐deposited film stress are important factors in controlling the moisture resistance of these PECVD oxides; the deposition of these PECVD oxides using higher ratios enhances moisture resistance; the use of instead of as the oxidizing agent incorporates nitrogen as well as Si—H bonds in the film which enhance moisture resistance, and that an in situ plasma post‐treatment of PECVD films improves the moisture barrier characteristics of the these oxide films.
Tumor treating fields (TTFields) impairs aberrant glycolysis in glioblastoma as evaluated by [18F]DASA-23, a non-invasive probe of pyruvate kinase M2 (PKM2) expression (2020)

Despite the anti-proliferative and survival benefits from tumor treating fields (TTFields) in human glioblastoma (hGBM), little is known about the effects of this form of alternating electric fields therapy on the aberrant glycolysis of hGBM. [<sup>18</sup>F]FDG is the most common radiotracer in cancer metabolic imaging, but its utility in hGBM is impaired due to high glucose uptake in normal brain tissue. With TTFields, radiochemistry, Western blot, and immunofluorescence microscopy, we identified pyruvate kinase M2 (PKM2) as a biomarker of hGBM response to therapeutic TTFields. We used [<sup>18</sup>F]DASA-23, a novel radiotracer that measures PKM2 expression and which has been shown to be safe in humans, to detect a shift away from hGBM aberrant glycolysis in response to TTFields. Compared to unexposed hGBM, [<sup>18</sup>F]DASA-23 uptake was reduced in hGBM exposed to TTFields (53%, P< 0.05) or temozolomide chemotherapy (33%, P > 0.05) for 3 d. A 6-d TTFields exposure resulted in a 31% reduction (P = 0.043) in 60-min uptake of [<sup>18</sup>F]DASA-23. [<sup>18</sup>F]DASA-23 was retained after a 10 but not 30-min wash-out period. Compared to [<sup>18</sup>F]FDG, [<sup>18</sup>F]DASA-23 demonstrated a 4- to 9-fold greater uptake, implying an improved tumor-to-background ratio. Furthermore, compared to no-TTFields exposure, a 6-d TTFields exposure caused a 35% reduction in [<sup>18</sup>F]DASA-23 30-min uptake compared to only an 8% reduction in [<sup>18</sup>F]FDG 30-min uptake. Quantitative Western blot analysis and qualitative immunofluorescence for PKM2 confirmed the TTFields-induced reduction in PKM2 expression. This is the first study to demonstrate that TTFields impairs hGBM aberrant glycolytic metabolism through reduced PKM2 expression, which can be non-invasively detected by the [<sup>18</sup>F]DASA-23 radiotracer.
Metal-Induced Structural Organization and Stabilization of the Metalloregulatory Protein MntR (2005)

MntR is a metalloregulatory protein that helps to modulate the level of manganese in Bacillus subtilis. MntR shows a metal-response profile distinct from other members of the DtxR family of metalloregulatory proteins, which are generally considered to be iron(II)-activated. As part of an ongoing effort to elucidate the mechanism and metal-selectivity of MntR, several biophysical studies on wild-type MntR and two active site mutants, MntR E99C and MntR D8M, have been performed. Using circular dichroism (CD) spectroscopy, the thermal stability of these proteins has been examined in the presence of various divalent metal ions. Fluorescence intensity measurements of 8-anilino-1-naphthalenesulfonic acid (ANS) were monitored to examine the folding of these proteins in the presence of different metal ions. These experiments indicate that MntR undergoes a significant conformational change upon metal binding that results in stabilization of the protein structure. These studies also show that the MntR D8M active site mutation causes a detrimental effect on the metal-responsiveness of this protein. Fluorescence anisotropy experiments have been performed to quantify the extent of metal-activated DNA binding by these proteins to two different cognate recognition sequences. Binding of MntR and MntR E99C to the mntA cognate sequence closely parallels that of the mntH operator, confirming that the proteins bind both sequences with comparable affinity depending on the activating metal ion. Fluorescence anisotropy experiments on MntR D8M indicate significantly impaired DNA binding, providing additional evidence that MntR D8M is a dysfunctional regulator.