gebhart/patrepeval huggingface dataset:
A cost-benefit analysis of leaves of four Australian savanna species (1998)

We conducted a cost-benefit analysis of the contrasting phenologies of two evergreen and two deciduous species of the savannas of north Australia. Stomatal conductance, rates of light-saturated assimilation (A(max)) and dark respiration were measured for six leaves from each of five or six trees. These leaves were then analyzed for total nitrogen, ether-soluble lipids, ash content, and heat of combustion. Construction and maintenance costs, nitrogen-use efficiencies and instantaneous transpiration efficiencies were then calculated from these data. Evergreen species had significantly lower specific leaf area, leaf nitrogen and leaf ash content than deciduous species. Evergreen species also had significantly higher heat of combustion and lipid content of crude extracts than deciduous species. Light-saturated assimilation rates were higher in evergreen species on a leaf area basis, but were higher in deciduous species on a leaf dry weight basis. In both evergreen and deciduous species, A(max) and total Kjeldahl nitrogen were linearly related. Similarly, nitrogen-use efficiency did not differ among species. Leaf construction costs were significantly higher for evergreen species than for deciduous species, but maintenance costs did not differ among species. Evergreen species had a higher cost:benefit ratio than deciduous species but because of their longer-lived leaves, the payback interval was longer in evergreen species than in deciduous species. These results support the hypotheses that: (1) longer-lived leaves are more expensive to construct than shorter-lived leaves, and (2) there is a higher investment of nitrogen into short-lived leaves to support a higher A(max) over a shorter payback interval. We conclude that deciduous and evergreen species partition resources both temporally and spatially, thereby reducing interspecies competition.
Factor Analysis of Auto-Associative Neural Networks With Application in Speaker Verification (2013)

Auto-associative neural network (AANN) is a fully connected feed-forward neural network, trained to reconstruct its input at its output through a hidden compression layer, which has fewer numbers of nodes than the dimensionality of input. AANNs are used to model speakers in speaker verification, where a speaker-specific AANN model is obtained by adapting (or retraining) the universal background model (UBM) AANN, an AANN trained on multiple held out speakers, using corresponding speaker data. When the amount of speaker data is limited, this adaptation procedure may lead to overfitting as all the parameters of UBM-AANN are adapted. In this paper, we introduce and develop the factor analysis theory of AANNs to alleviate this problem. We hypothesize that only the weight matrix connecting the last nonlinear hidden layer and the output layer is speaker-specific, and further restrict it to a common low-dimensional subspace during adaptation. The subspace is learned using large amounts of development data, and is held fixed during adaptation. Thus, only the coordinates in a subspace, also known as i-vector, need to be estimated using speaker-specific data. The update equations are derived for learning both the common low-dimensional subspace and the i-vectors corresponding to speakers in the subspace. The resultant i-vector representation is used as a feature for the probabilistic linear discriminant analysis model. The proposed system shows promising results on the NIST-08 speaker recognition evaluation (SRE), and yields a 23% relative improvement in equal error rate over the previously proposed weighted least squares-based subspace AANNs system. The experiments on NIST-10 SRE confirm that these improvements are consistent and generalize across datasets.
SVM-RFE: selection and visualization of the most relevant features through non-linear kernels (2018)

The proposed approaches can be implemented with accuracy to select variables and assess direction and strength of associations in analysis of biomedical data using SVM for categorical or time-to-event responses. Conducting variable selection and interpreting direction and strength of associations between predictors and outcomes with the proposed approaches, particularly with the RFE-pseudo-samples approach can be implemented with accuracy when analyzing biomedical data. These approaches, perform better than the classical RFE of Guyon for realistic scenarios about the structure of biomedical data.
Genome and Proteome of Campylobacter jejuni Bacteriophage NCTC 12673 (2011)

Campylobacter jejuni continues to be the leading cause of bacterial food-borne illness worldwide, so improvements to current methods used for bacterial detection and disease prevention are needed. We describe here the genome and proteome of C. jejuni bacteriophage NCTC 12673 and the exploitation of its receptor-binding protein for specific bacterial detection. Remarkably, the 135-kb Myoviridae genome of NCTC 12673 differs greatly from any other proteobacterial phage genome described (including C. jejuni phages CP220 and CPt10) and instead shows closest homology to the cyanobacterial T4-related myophages. The phage genome contains 172 putative open reading frames, including 12 homing endonucleases, no visible means of packaging, and a putative trans-splicing intein. The phage DNA appears to be strongly associated with a protein that interfered with PCR amplification and estimation of the phage genome mass by pulsed-field gel electrophoresis. Identification and analyses of the receptor-binding protein (Gp48) revealed features common to the Salmonella enterica P22 phage tailspike protein, including the ability to specifically recognize a host organism. Bacteriophage receptor-binding proteins may offer promising alternatives for use in pathogen detection platforms.
Continuum Electron Wavefunction Shifts in Semiconductor Quantum Dot (1998)

In this paper, the mathematical model for electron wavefunction shifts in the continuum part of the electronic spectrum of a GaAs-Al0.3Ga0.7As based semiconductor quantum dot (QD) is presented. The electron states in the continuum are obtained by solving the Schrodinger equation written in the effective-mass approximation. The influence of accumulated charges in the well region of QD an conduction band bending in this model is taken via self-consistent procedure. Analytical derivation and numerical calculations of the behavior of electron wavefunction shifts, considered as they depend on electron energy in the high energy limit, show their considerable deviation from those expected according to Levinsons theorem violation in the case of QD is the effective-mass mismatch at the heterointerface of Qd constitutive materials.
Optimization of Straight Line Programs (1972)

We provide a set of transformations capable of transforming a straight line program into any other equivalent one assuming no algebraic laws hold. We then show that optimization of straight line code under “reasonable” cost criteria can always be accomplished by applying sequences of these transformations in a prescribed order.
A randomized, double‐blind, placebo‐controlled study of the kappa opioid receptor antagonist, CERC‐501, in a human laboratory model of smoking behavior (2019)

Preclinical data indicate that selective kappa opioid receptor antagonists reduce nicotine self-administration and withdrawal symptoms. The aim of the current study was to determine whether treatment with CERC-501, an orally available, potent, and selective kappa opioid receptor antagonist, could alleviate nicotine withdrawal and craving and mitigate mood alterations associated with nicotine withdrawal in humans. Healthy, adult cigarette smokers were enrolled into this randomized, multisite, double-blind, placebo-controlled, crossover study. Participants completed two 8-day treatment phases during which they received either CERC-501 (15 mg, p.o., once daily) or placebo. On the seventh day of each dosing phase, participants were admitted as inpatients for an 18-hour cigarette abstinence period followed by experimental testing. The primary outcome measures were (a) performance on the McKee Smoking Lapse test (ie, latency to smoke in exchange for money) and (b) number of cigarettes self-administered during a 60-minute ad lib smoking period. Other outcomes included measures of craving, mood, anxiety, nicotine withdrawal, and subjective effects of cigarette smoking. A total of 71 participants who smoked an average of approximately 23 cigarettes per day were enrolled, and 56 subjects completed the study. CERC-501 was well tolerated, but it did not significantly alter the latency to start smoking (CERC-501: 16.5 min vs placebo: 17.7 min) or the number of cigarettes smoked (CERC-501: 3.3 cigarettes vs placebo: 3.1 cigarettes). Compared with placebo, CERC-501 also did not affect cigarette craving, mood, anxiety, nicotine withdrawal, or subjective effects of smoking. These findings do not support a role for CERC-501 in the treatment of nicotine use disorder.
Novel RNA Viruses from the Transcriptome of Pheromone Glands in the Pink Bollworm Moth, Pectinophora gossypiella (2021)

In this study, we analyzed the transcriptome obtained from the pheromone gland isolated from two Israeli populations of the pink bollworm <i>Pectinophora gossypiella</i> to identify viral sequences. The lab population and the field samples carried the same viral sequences. We discovered four novel viruses: two positive-sense single-stranded RNA viruses, Pectinophora gossypiella virus 1 (PecgV1, a virus of <i>Iflaviridae</i>) and Pectinophora gossypiella virus 4 (PecgV4, unclassified), and two negative-sense single-stranded RNA viruses, Pectinophora gossypiella virus 2 (PecgV2, a virus of <i>Phasmaviridae</i>) and Pectinophora gossypiella virus 3 (PecgV3, a virus of <i>Phenuiviridae</i>). In addition, sequences derived from two negative-sense single-stranded RNA viruses that belong to <i>Mononegavirales</i> were found in the data. Analysis of previous transcriptome sequencing data derived from the midgut of pink bollworm larvae of a USA population only identified PecgV1, but no other viruses. High viral sequence coverages of PecgV1 and PecgV4 were observed in both field and lab populations. This is the first report of viral sequences discovered from the pink bollworm. Results from this investigation suggest that the pink bollworm harbors multiple viruses. Further investigation of the viral pathogens may help to develop novel pest management strategies for control of the pink bollworm.
Three-Layer Core/Shell Structure in Au−Pd Bimetallic Nanoparticles (2007)

This paper describes the internal structure of Au-Pd nanoparticles exhibiting newly discovered three-layer core/shell morphology, which is composed of an evenly alloyed inner core, an Au-rich intermediate layer, and a Pd-rich outer shell. By exploitation of spatially resolved imaging and spectroscopic and diffraction modes of transmission electron microscopy (TEM), insights were gained on the composition of each one of the observed three layers, indicating a significant extent of intimate alloy among the monometallic elements.
Oblivious routing and QoS guarantee in wireless mesh networks (2010)

Routing with QoS guarantee has been studied extensively for wireless mesh networks. While most of previous research assumes a static and known traffic demand, this assumption often does not hold in a real network. Oblivious routing has been proved an effective approach to tackle the routing and QoS problem when traffic demand uncertainty exists. In this paper, an oblivious-routing based QoS architecture, called a nonblocking network, is proposed to guarantee hard QoS in wireless mesh networks. In this architecture, as long as each edge node admits traffic no more than a specified amount, the network will never experience link congestion. The main difficulty in designing such a network is to find the optimal routing that can maximize the amount of traffic admissible to the network. We develop analytical models to find the optimal routing schemes for both unicast and multicast networks. For multicast networks, we show that if the network uses network coding, the optimal solution to the multicast routing network problem can be solved with linear programming. The analytical results indicate that our optimal QoS routing schemes perform much better than traditional shortest tree based multicast routing algorithm.
Active control of sound and vibration (1990)

Due to recent advances in DSP technology, active control now shows much promise for reducing sound and vibration in a number of difficult applications. In this tutorial the concepts behind the active control approach will be introduced with some historical perspective. The basics of feedforward control will then be reviewed and related to the more traditional state feedback methods. Application of the technique to fundamental problems in the control of sound and vibration will be given with some consideration of the design and choice of the appropriate control transducers and cost functions. Useful analytical methods and mechanisms of control will be considered. Recent successful applications of the technique to realistic systems will be reviewed and future promising research directions discussed.
An Algorithm of Managing the TCP Stream Based on Two-Level Hash Tables (2015)

With the development of computer network technology, network security issues become increasingly more serious, firewall technology is one of the most effective methods to protect network security. Stream filter technology is a new firewall technology, which not only can supervise the network layer as packet filtering firewall, but also can supervise transport layer and application layer as the application proxy firewall. Hash table algorithm has been often used to manage the TCP stream table in firewall. However, the 4-tuple of TCP stream is not uniform distribution, it may lead to the worst case when searching in the hash table. When the worst case happens on the firewall, the quality of service may become very bad in the network. In order to control the worst case, we propose two-level hash tables algorithm based on bloom filter counter algorithm and multi-level hash tables algorithm. We search in the small hash table firstly, if it's fail, then search in the big hash table. The algorithm we proposed can not only decline the probability of worst case, but also reduce the number of memory access in worst case. And our theoretical research and simulation experiments proof that.
LR B-splines to approximate bathymetry datasets: An improved statistical criterion to judge the goodness of fit (2022)

The task of representing remotely sensed scattered point clouds with mathematical surfaces is ubiquitous to reduce a high number of observations to a compact description with as few coefficients as possible. To reach that goal, locally refined B-splines provide a simple framework to perform surface approximation by allowing an iterative local refinement. Different setups exist (bidegree of the splines, tolerance, refinement strategies) and the choice is often made heuristically, depending on the applications and observations at hand. In this article, we introduce a statistical information criterion based on the t-distribution to judge the goodness of fit of the surface approximation for remote sensing data with outliers. We use a real bathymetry dataset and illustrate how concepts from model selection can be used to select the most adequate refinement strategy of the LR B-splines.
A high‐performance sorting algorithm for multicore single‐instruction multiple‐data processors (2011)

SUMMARY Many sorting algorithms have been studied in the past, but there are only a few algorithms that can effectively exploit both single‐instruction multiple‐data (SIMD) instructions and thread‐level parallelism. In this paper, we propose a new high‐performance sorting algorithm, called aligned‐access sort (AA‐sort), that exploits both the SIMD instructions and thread‐level parallelism available on today's multicore processors. Our algorithm consists of two phases, an in‐core sorting phase and an out‐of‐core merging phase. The in‐core sorting phase uses our new sorting algorithm that extends combsort to exploit SIMD instructions. The out‐of‐core algorithm is based on mergesort with our novel vectorized merging algorithm. Both phases can take advantage of SIMD instructions. The key to high performance is eliminating unaligned memory accesses that would reduce the effectiveness of SIMD instructions in both phases. We implemented and evaluated the AA‐sort on PowerPC 970MP and Cell Broadband Engine platforms. In summary, a sequential version of the AA‐sort using SIMD instructions outperformed IBM's optimized sequential sorting library by 1.8 times and bitonic mergesort using SIMD instructions by 3.3 times on PowerPC 970MP when sorting 32 million random 32‐bit integers. Also, a parallel version of AA‐sort demonstrated better scalability with increasing numbers of cores than a parallel version of bitonic mergesort on both platforms. Copyright © 2011 John Wiley &amp; Sons, Ltd.
Interaction of Bacteria and Fungi with Lectins and Lectin-Like Substances (1981)

INTRODUCTION . Background .. What Are Lectins? . Areas of Study . Scope of This Review ..
Optical reflectivity of 3C and 4H-SiC polytypes: Theory and experiment (1993)

Experimental and theoretical optical reflectivity in the range 4–10 eV are reported for the 3C and 4H polytypes of SiC. The calculations used the linear muffin-tin orbital method and the local density approximation. Good agreement in peak positions and line shape is obtained except for a nearly constant shift of ∼1.00 eV.
CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization (2020)

The COVID-19 global pandemic has resulted in international efforts to understand, track, and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related publications across scientific disciplines. As of May 2020, 128,000 coronavirus-related publications have been collected through the COVID-19 Open Research Dataset Challenge. Here we present CO-Search, a retriever-ranker semantic search engine designed to handle complex queries over the COVID-19 literature, potentially aiding overburdened health workers in finding scientific answers during a time of crisis. The retriever is built from a Siamese-BERT encoder that is linearly composed with a TF-IDF vectorizer, and reciprocal-rank fused with a BM25 vectorizer. The ranker is composed of a multi-hop question-answering module, that together with a multi-paragraph abstractive summarizer adjust retriever scores. To account for the domain-specific and relatively limited dataset, we generate a bipartite graph of document paragraphs and citations, creating 1.3 million (citation title, paragraph) tuples for training the encoder. We evaluate our system on the data of the TREC-COVID information retrieval challenge. CO-Search obtains top performance on the datasets of the first and second rounds, across several key metrics: normalized discounted cumulative gain, precision, mean average precision, and binary preference.
JSDM and multi-cell networks: Handling inter-cell interference through long-term antenna statistics (2014)

Joint Spatial Division and Multiplexing (JSDM) is a novel paradigm for splitting the functions of multiuser MIMO precoding into a concatenation of blocks: a pre-beamforming projection depending only on the channel covariances, and a precoder achieving multiplexing gain over the effective channel including pre-beamforming. In this paper, we extend our study of JSDM to a multi-cell system, where the pre-beamforming projections are jointly selected across cells together with user scheduling, such that inter-cell interference can be handled using only the channel covariances (the so-called “long-term” antenna statistics), which are much easier to collect than the classical instantaneous channel state information.
MODERN STATE OF THE ATHLET SETUP AT THE TIEN SHAN (2005)

We present up-to-date state of new experimental complex ATHLET.
Study of the Mechanisms by Which Angptl5 and IGFBP2 Support Ex Vivo Expansion of Human Cord Blood Hematopoietic Stem Cells. (2008)

Abstract We previously showed that angiopoietin-like protein 5 (Angptl5) and IGF Binding Protein 2 (IGFBP2) support dramatic ex vivo expansion of human hematopoietic stem cells (HSCs). To understand the mechanisms of their action, here we studied the effects of Angptl5 and IGFBP2 on the surface phenotype, signaling activation, self-renewal, apoptosis, differentiation, and homing of human cord blood CD34+ cells. Using immunofluorescence staining, we showed that Angptl5 and IGFBP2 activate certain signaling pathways such as MAPK and Stat5 in human cord blood CD34+ cells. IGFBP2 and Angptl5 increased the expression of transcription factors HoxB4, Bmi-1, EZH2, and survivin, measured by intracellular staining flow cytometry analysis and real-time RT-PCR. IGFBP2 and Angptl5 also inhibit expression of certain transcription factors important for differentiation of myeloid, erythroid, and lymphoid lineages. To test whether IGFBP2 and Angptl5 affect the homing of HSCs, we cultured human cord blood CD34+ cells in serum-free medium supplemented with SCF, TPO, Flt3-L, IGFBP2 or Angptl5, and transplanted them into sublethally irradiated NOD/SCID mice intraveneously or intrafemorally. Both IGFBP2 and Angptl5 support ex vivo expansion of SRCs in intrafemorally injected mice, suggesting the expansion-stimulating effects elicited by both factors are not caused by modulation of HSC homing. Interestingly, when we used intrafemoral injection, we found that Angptl5 treated HSCs have enhanced engraftment in non-injected bone marrow. This suggests Angptl5 treated HSCs further facilitate the mobilization of HSCs in vivo. We conclude that IGFBP2 and Angptl5 support self-renewal and inhibit differentiation of human cord blood HSCs. Our data also suggest that a combination of expression of transcription factors important for self-renewal, survival, and differentiation of HSCs can be used as a “stemness index” that predicts the activity of cultured human HSCs.
Organic Field-Effect Transistor-Based Nonvolatile Memory Devices Having Controlled Metallic Nanoparticle/Polymer Composite Layers (2010)

Nonvolatile memory devices based on the pentacene film and controlled gold nanoparticle composite layers were developed. Organic field-effect transistor-based nonvolatile memory devices having self-assembled exhibited controllable and reliable current level differences (on- and off-states) according to the applied gate voltages (programming/erasing operations). The memory devices showed large memory windows as well as good data retention properties by adopting charge storage layers of controlled separated by insulating polymer layers. The process for fabricating nonvolatile memory devices was based on the solution processes and organic semiconductor layers, so it has a potential use in flexible nonvolatile memory applications.
Chromoselective Photocatalysis: Controlled Bond Activation through Light‐Color Regulation of Redox Potentials (2016)

Catalysts that can be regulated in terms of activity and selectivity by external stimuli may allow the efficient multistep synthesis of complex molecules and pharmaceuticals. Herein, we report the light-color regulation of the redox potential of a photocatalyst to control the activation of chemical bonds. Light-color control of the redox power of a photocatalyst introduces a new selectivity parameter to photoredox catalysis: Instead of changing the catalyst or ligand, alteration of the color of the visible-light irradiation adjusts the selectivity in catalytic transformations. By using this principle, the selective activation of aryl-halide bonds for C-H arylation and the sequential conversion of functional groups with different reduction potentials is possible by simply applying different colors of light for excitation of the photocatalyst.