gebhart/patrepeval huggingface dataset:
The role of asymptotic functions in network optimization and feasibility studies (2017)

Solutions to network optimization problems have greatly benefited from developments in nonlinear analysis, and, in particular, from developments in convex optimization. A key concept that has made convex and nonconvex analysis an important tool in science and engineering is the notion of asymptotic function, which is often hidden in many influential studies on nonlinear analysis and related fields. Therefore, we can also expect that asymptotic functions are deeply connected to many results in the wireless domain, even though they are rarely mentioned in the wireless literature. In this study, we show connections of this type. By doing so, we explain many properties of centralized and distributed solutions to wireless resource allocation problems within a unified framework, and we also generalize and unify existing approaches to feasibility analysis of network designs. In particular, we show sufficient and necessary conditions for mappings widely used in wireless communication problems (more precisely, the class of standard interference mappings) to have a fixed point. Furthermore, we derive fundamental bounds on the utility and the energy efficiency that can be achieved by solving a large family of max-min utility optimization problems in wireless networks.
Performance Improvement of Carbon-Nanotube-Incorporated Transparent Conducting Anode Film for Organic Device Application (2008)

Carbon nanotubes (CNTs) were incorporated into indium tin oxide and polythiophene by mixing and then spin coating or screen printing to form the transparent conducting electrode (TCE). With only approximately 0.005%, by weight, of CNTs in the TCE, the sheet resistance was found to drop by about 25% to 40%, without any significant decrease in the transmittance. Organic light-emitting devices (OLEDs) were then fabricated using these composite TCEs as the anode. In comparison with a device without the CNTs, there was an increase in the current density for the same applied voltage, mainly due to the contribution of hole current. In addition, the mechanical strength was improved, as seen from bending test of the device.
Multi-functional Coexistence of Radar-Sensing and Communication Waveforms (2020)

In this study, a novel transmission scheme is proposed to serve radar-sensing and communication objectives at the same time and allocated bandwidth. The proposed transmitted frame non-orthogonally superimposes two different waveforms, which are frequency modulated continuous-wave (FMCW) for radar-sensing and orthogonal frequency division multiplexing (OFDM) for communication. Also, the receiver scheme that performs channel estimation via radar-sensing functionality without degrading data rate of communication operation is introduced. As numerically evaluated, the proposed system achieves good sensing accuracy even if the signal-to-noise ratio (SNR) is low, and communication performance is only 0.6 dB less at the target bit-error rate (BER) of 1% compared to the assumption of perfect channel state information (CSI) without any pilot overhead over OFDM subcarriers.
104 Effect of Connective Tissue Growth Factor on Protein Kinase Expression and Activity in Human Corneal Fibroblasts (2004)

Purpose : To evaluate expression patterns of protein kinases and protein kinase activities in human corneal fibroblasts treated with connective tissue growth factor (CTGF). Methods : Human corneal fibroblast cultures were grown to confluence and treated with CTGF for 0, 5, and 15 minutes. Cytoplasmic protein extracts were obtained; protein kinase expression and activity arrays were performed using Kinetworks™ analysis (screening for expression of 75 different protein kinases and 31 different phosphoproteins). Further studies using extended time courses of CTGF exposure in corneal fibroblasts (0, 1, 2, 3, 4, 5, 10, 15, 30, and 60 minutes) were performed using immunoblot analysis to detect expression of protein kinase A catalytic subunit (PKA‐cat), and focal adhesion kinase (FAK). All results and were normalized by comparison to beta‐actin. Results : After 5 minutes of exposure to CTGF, levels of active proteins increased for 21 of the 75 kinases analyzed. Some notable protein kinases that were induced include: death‐associated kinase 1, focal adhesion kinase (FAK), G‐protein coupled receptor kinase 2, protein kinase A catalytic subunit (PKA‐cat), protein kinase B alpha, and protein kinase C (ε, μ, and ζ, subunits). Extended time course analysis of PKA‐cat and FAK showed statistically significant increases in expression following CTGF stimulation within 15 minutes. Conclusion : CTGF increased the levels of active protein kinases in human corneal fibroblast cultures, including PKA‐cat and FAK after 5 minutes of exposure. These results further our understanding of the signal transduction mechanism activated by CTGF in corneal fibroblasts. This suggests that CTGF mediates the effects of transforming growth factor beta (TGF‐β) on protein kinase expression and phosphorylation of second messengers in processes such as cell proliferation and collagen synthesis. Acknowledgments: Funding source: NEI 05587
Once and future epidemics: Zika virus emerging (2016)

Zika virus again reminds us that we need a globally coordinated system to protect against outbreaks caused by perilous pathogens.
Optimized 4 and 8 Dimensional Modulation Formats for Variable Capacity in Optical Networks (2016)

We present enhanced modulation formats optimized for nonlinear performance over a range of spectral efficiency. Maximum transmission distance is improved by > 600 km at PM-8QAM capacity and by > 3500 km at PM-BPSK rates.
Simultaneous measurement of strain and temperature by means of polarization division multiplexing optical frequency domain reflectometry (2009)

Simultaneous measurement of strain and temperature by means of the polarization division multiplexing optical frequency domain reflectometry was demonstrated. In the measurement, a high birefringence PANDA type polarization maintaining fiber was used for a fiber Bragg grating portion. It was confirmed that Bragg reflection wavelengths corresponding to slow and fast axes have different dependence on strain and temperature. High accuracy simultaneous measurement of strain and temperature within errors ±20 &mu;&epsilon; and ±2 °C was achieved for any strain and temperature conditions used in this study.
Transmission of 300 Mbit/s BPSK at 39 GHz usingfeedforwardoptical modulation (1994)

The transmission of 300 Mbit/s BPSK data on a 39GHz subcarrier over 2.2 km of optical fibre using feedforward optical modulation is reported. This is the highest subcarrier frequency transmission reported to date. The Letter shows that this technique can be used to transmit gigabit data at carrier frequencies up to 100GHz and beyond.
Multiscale Phase Retrieval (2020)

While characterization of coherent wavefields is essential to laser, x-ray and electron imaging, sensors measure the squared magnitude of the field, rather than the field itself. Holography or phase retrieval must be used to characterize the field. The need for a reference severely restricts the utility of holography. Phase retrieval, in contrast, is theoretically consistent with sensors that directly measure coherent or partially coherent fields with no prior assumptions. Unfortunately, phase retrieval has not yet been successfully implemented for large-scale fields. Here we show that both holography and phase retrieval are capable of quantum-limited coherent signal estimation and we describe phase retrieval strategies that approach the quantum limit for &gt;1 megapixel fields. These strategies rely on group testing using networks of interferometers, such as might be constructed using emerging integrated photonic, plasmonic and/or metamaterial devices. Phase-sensitive sensor planes using such devices could eliminate the need both for lenses and reference signals, creating a path to large aperture diffraction limited laser imaging.
Long-lasting neuronal desynchronization caused by coordinated reset stimulation (2011)

A number of brain diseases, e.g. movement disorders such as Parkinsons disease, are characterized by abnormal neuronal synchronization. Within the last years permanent high-frequency (HF) deep brain stimulation became the standard therapy for medically refractory movement disorders. To overcome limitations of standard HF deep brain stimulation, we use a model based approach. To this end, we make mathematical models of affected neuronal target populations and use methods from statistical physics and nonlinear dynamics to develop mild and efficient control techniques. Along the lines of a top-down approach we test our control techniques in oscillator networks as well as neural networks. In particular, we specifically utilize dynamical self-organization principles and plasticity rules. In this way, we have developed coordinated reset (CR) stimulation, an effectively desynchronizing brain stimulation technique. The goal of CR stimulation is not only to counteract pathological synchronization on a fast time scale, but also to unlearn pathological synchrony by therapeutically reshaping neural networks. The CR theory, results from animal experiments as well as clinical applications will be presented: Animal and human data will be shown on electrical CR stimulation for the treatment of Parkinsons disease via chronically implanted depth electrodes.

Furthermore, acoustic CR stimulation for the treatment of subjective tinnitus will be explained. Subjective tinnitus is an acoustic phantom phenomenon characterized by abnormal synchronization in the central auditory system. In a multicenter proof of concept study it has been shown that acoustic CR stimulation significantly and effectively counteracts tinnitus symptoms as well as the underlying pathological neuronal synchronization processes.
Full-Chip Power Supply Noise Time-Domain Numerical Modeling and Analysis for Single and Stacked ICs (2016)

In this paper, a distributed circuit model for on-die power distribution network in single and 3-D ICs is developed, and a set of difference equations are derived based on the circuit model and numerically solved using the finite-difference method. Both IR-drop and simultaneous switching noise, two components of power supply noise (PSN), are iteratively solved in time domain, thereby enabling a transient analysis of PSN. Under the assumptions that on-die power/ground pads, power density, and decoupling capacitors are uniformly distributed, PSN within a unit cell is accurately simulated with <;1% error compared with HSPICE simulation. By reducing modeling grid fineness, the numerical modeling approach is applied to a full chip that has multiple blocks with nonuniform power/ground pads, power density, and decoupling capacitance density. Based on full-chip modeling, the PSN distribution of a two-die stack is simulated, and the impact of increasing decoupling capacitance and power/ground pads is investigated.
Polymerase chain reaction‐based identification of a novel serpin from human dendritic cells (1997)

A subtraction library of CD40-stimulated human tonsil dendritic cells has been constructed using a polymerase chain reaction approach adapted for low numbers of cells. From this library we identified a cDNA for a serine protease inhibitor, a serpin, which is absent from monocytes, B cells and T cells but expressed in CD40-activated monocyte- and progenitor cell-generated dendritic cells. In addition, the serpin is expressed in a lung fibroblast cell line and keratinocytes. Its mRNA is detected only in tonsil and thymus. The serpin described here reportedly functions as a megakaryocyte maturation factor in the presence of interleukin (IL)-3 and IL-11. This suggests that dendritic cells may promote the immune response by protecting IL-3 and IL-11 or other essential proteins from degradation.
Symbiotic Information Processing and Technological Progress (2022)

The goal of the paper is the introduction and exploration of new types of information processing. Starting with the typology developed in such an important class of information processing as computation, we extend this typology by analyzing information representations used in computational processes and delineating novel forms of information representations. While the traditional approach deals only with two dimensions of information processing&mdash;symbolic and sub-symbolic, our analysis explicated one more dimension&mdash;super-symbolic information processing. Information processing in biological systems is both symbolic and sub-symbolic, having the form of genes and neural networks. Nevertheless, in their evolution, biological systems have advanced their abilities one step further by developing super-symbolic information processing and evolving symbiotic information processing that performs information processing on the combined knowledge in the brain from both symbolic, subsymbolic, and super-symbolic information processing to derive higher order autopoietic and cognitive behaviors. Performing all forms of information processing, biological systems achieve much higher cognitive and intelligence level. That is why here we also consider a new type of computing automata called structural machines with the goal of transferring these advantageous features of biological systems to the existing information processing technology.
Indian Ginseng Withania Somnifera (L.) (2012)

Indian Ginseng (Ashwagandha) Withania somnifera, is a medicinal plant of immense therapeutic value & wide geographic distribution. It has several medicinal properties adaptogenic, anti-inflammatory, immunosuppressive, immunomodulatory & anti-cancer; attributed to the presence of novel group of compounds known as Withanolides. The present book comprehensively amalgamates three aspects-Morphogenesis & regeneration, Withanolide biosynthesis in vitro and Ri/Ti based genetic transformations in W. somnifera & is a complete documentation of the research conducted by authors which has been organized into chapters with introductory remarks & description of review of status of available knowledge. The information in the book provides valuable information on details of methodologies adopted & experimental data recorded as outcome of well planned experiments which would serve as important reference for future research in this important medicinal plant. The book is useful for Postgraduates & Researchers in the field of Medicinal Plant Biotechnology & related areas like plant biology, biotechnology, biochemistry & natural medicines as well as professionals working in Herbal drug industry.
Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors (2021)

Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulation repertoire to its counterpart OR through machine learning (ML) will enable understanding of olfactory system, receptor characterization, and exploitation of their therapeutic potential. In the current study, we have selected two broadly tuned ectopic human OR proteins, OR1A1 and OR2W1, for expanding their known chemical space by using molecular descriptors. We present a scheme for selecting the optimal features required to train an ML-based model, based on which we selected the random forest (RF) as the best performer. High activity agonist prediction involved screening five databases comprising ~23 M compounds, using the trained RF classifier. To evaluate the effectiveness of the machine learning based virtual screening and check receptor binding site compatibility, we used docking of the top target ligands to carefully develop receptor model structures. Finally, experimental validation of selected compounds with significant docking scores through in vitro assays revealed two high activity novel agonists for OR1A1 and one for OR2W1.
Self-Diffusion in Silicon: Similarity between the Properties of Native Point Defects (1999)

Self-diffusion measurements in silicon are extended to the range 800--900 \ifmmode^\circ\else\textdegree\fi{}C by monitoring ${}^{30}\mathrm{Si}$ diffusion in isotopically enriched structures. Comparing P, Sb, and self-diffusion under nonequilibrium conditions, we determine that the interstitial-mediated fraction of self-diffusion is confined between 0.50 and 0.62 in the temperature range of 800--1100 \ifmmode^\circ\else\textdegree\fi{}C. This allows activation enthalpies of 4.68 and 4.86 eV to be determined for the interstitial and vacancy mechanisms, respectively. Both mechanisms are also found to exhibit large activation entropies. This result is in contrast to values extracted from metal diffusion experiments.
Machine Learning Assisted PHYSEC Attacks and SLP Countermeasures for Multi-Antenna Downlink Systems (2019)

Most physical-layer security (PLS) works employ information theoretic metrics for performance analysis. In this paper, however, we investigate PLS from a signal processing point of view, where we rely on bit-error rate (BER) at the eavesdropper (Eve) as a metric for information leakage. Recently, symbol-level precoding (SLP) has been shown to enhance PLS in the presence of an Eve. In this work, nonetheless, we introduce a machine learning (ML) based attack to which even SLP schemes can be vulnerable. Namely, this attack manifests when an Eve utilizes ML in order to learn the precoding pattern when precoded pilots are sent. With this ability, an Eve can decode data with favorable accuracy. As a countermeasure to this attack, we propose a novel security enhanced precoding technique. The proposed countermeasure yields high BER at the Eve, which makes symbol detection practically infeasible for the latter, thus providing physical-layer security between the base station (BS) and the users. In the numerical results, we validate both the attack and the countermeasure, and show that this gain in security can be achieved at the expense of only a small additional power consumption at the transmitter.
Electrical Stimuli in the Central Nervous System Microenvironment (2014)

Electrical stimulation to manipulate the central nervous system (CNS) has been applied as early as the 1750s to produce visual sensations of light. Deep brain stimulation (DBS), cochlear implants, visual prosthetics, and functional electrical stimulation (FES) are being applied in the clinic to treat a wide array of neurological diseases, disorders, and injuries. This review describes the history of electrical stimulation of the CNS microenvironment; recent advances in electrical stimulation of the CNS, including DBS to treat essential tremor, Parkinson's disease, and depression; FES for the treatment of spinal cord injuries; and alternative electrical devices to restore vision and hearing via neuroprosthetics (retinal and cochlear implants). It also discusses the role of electrical cues during development and following injury and, importantly, manipulation of these endogenous cues to support regeneration of neural tissue.
Clinical Effectiveness Protocols for Imaging in the Management of Ureteral Calculous Disease: AUA Technology Assessment (2012)

The protocols generated assist the clinician in establishing the diagnosis of ureteral calculous disease, monitoring stone passage and following patients after treatment. The protocols take into account not only clinical effectiveness but also cost-effectiveness and risk/harm associated with the various imaging modalities.
Moving Horizon Sensor Selection for Reducing Communication Costs with Applications to Internet of Vehicles (2019)

Motivated by applications of the Internet of Vehicles where a large amount of data is available through communication, we consider the problem of reducing communication costs when estimating the dynamical state of a system. More specifically, assuming the knowledge of sensor specifications, such as noise characteristics, we solve the problem of determining which sensor's data are necessary to satisfy given time-varying constraints on the estimation errors. By receiving only the necessary data, instead of all available data, we reduce the communication and processing bandwidth usage. We formulate a moving horizon sensor selection problem and present an approximate, yet computationally tractable, solution to the problem by employing a greedy heuristic approach. For the heuristic, we define a metric that measures the contribution of each sensor data to the constraints in relation to its communication cost. We validate our solution on two collision avoidance examples and compare the performances of our approach with the conventional Kalman filter. The simulation results show that our approach significantly reduces communication costs without compromising the system's performance, such as safety guarantee, with high probability.
Structural and functional analysis of a potent sarbecovirus neutralizing antibody (2020)

SARS-CoV-2 is a newly emerged coronavirus responsible for the current COVID-19 pandemic that has resulted in more than one million infections and 73,000 deaths 1,2 . Vaccine and therapeutic discovery efforts are paramount to curb the pandemic spread of this zoonotic virus. The SARS-CoV-2 spike (S) glycoprotein promotes entry into host cells and is the main target of neutralizing antibodies. Here we describe multiple monoclonal antibodies targeting SARS-CoV-2 S identified from memory B cells of a SARS survivor infected in 2003. One antibody, named S309, potently neutralizes SARS-CoV-2 and SARS-CoV pseudoviruses as well as authentic SARS-CoV-2 by engaging the S receptor-binding domain. Using cryo-electron microscopy and binding assays, we show that S309 recognizes a glycan-containing epitope that is conserved within the sarbecovirus subgenus, without competing with receptor attachment. Antibody cocktails including S309 along with other antibodies identified here further enhanced SARS-CoV-2 neutralization and may limit the emergence of neutralization-escape mutants. These results pave the way for using S309 and S309-containing antibody cocktails for prophylaxis in individuals at high risk of exposure or as a post-exposure therapy to limit or treat severe disease.
Lung Cancer Risk and Past Exposure to Emissions from a Large Steel Plant (2013)

We studied the spatial distribution of cancer incidence rates around a large steel plant and its association with historical exposure. The study population was close to 600,000. The incidence data was collected for 1995-2006. From historical emission data the air pollution concentrations for polycyclic aromatic hydrocarbons (PAH) and metals were modelled. Data were analyzed using Bayesian hierarchical Poisson regression models. The standardized incidence ratio (SIR) for lung cancer was up to 40% higher than average in postcodes located in two municipalities adjacent to the industrial area. Increased incidence rates could partly be explained by differences in socioeconomic status (SES). In the highest exposure category (approximately 45,000 inhabitants) a statistically significant increased relative risk (RR) of 1.21 (1.01-1.43) was found after adjustment for SES. The elevated RRs were similar for men and women. Additional analyses in a subsample of the population with personal smoking data from a recent survey suggested that the observed association between lung cancer and plant emission, after adjustment for SES, could still be caused by residual confounding. Therefore, we cannot indisputably conclude that past emissions from the steel plant have contributed to the increased risk of lung cancer.