Miracle-dz/UniFAR-FTUs huggingface dataset:
Crossline wavefield reconstruction from multi‐component streamer data: multichannel interpolation by matching pursuit

We introduce a new technique that uses multicomponent seismic measurements that would be recorded by a true multicomponent streamer to reconstruct the seismic wavefield at any desired position between streamers. This method, called Multichannel Interpolation by Matching Pursuit (MIMAP), operates on pressure and crossline particle motion measurements. As a data-dependent technique, MIMAP can interpolate severely aliased data without any assumptions about seismic events such as linearity or the model related to the seismic wavefield. MIMAP has the capability to perform well in the presence of irregular sampling and is robust even when only a small number of samples are available.
Frame buffer compression for low-power video coding

In this paper, we propose a novel hybrid frame buffer compression algorithm to reduce the memory bandwidth for low-power video coding. In our work, we first decompose the full-resolution image into low resolution (LR) and high resolution (HR) components. We then calculate the HR residual by taking the difference between original HR pixel and an estimate derived from surrounding LR pixels. Finally, we use absolute moment block truncation coding to quantize and compress the LR pixel and HR residual data so as to reduce the memory bandwidth. We integrate our approach into the JCT-VC reference software for High Efficiency Video Coding (HEVC). Results show negligible impact on coding efficiency with significant memory bandwidth reduction. Specifically, we observe a bit rate increase of 0.38% and 1% with 21% and 31% memory bandwidth reduction, respectively.
GENETIC LOAD AND THE MATING SYSTEM IN HOMOSPOROUS FERNS

The mutational genetic load was calculated assuming mutation‐selection‐inbreeding equilibrium and applied to homosporous ferns. Diploid species with past inbreeding should have a low genetic load while outcrossers should have a high genetic load. These predictions are consistent with the bimodal pattern of genetic load found in 18 diploid homosporous fern species. The prediction that tetraploids should have a low genetic load is also consistent with estimates of genetic load in several species.
What we can and cannot (yet) do with functional near infrared spectroscopy

Functional near infrared spectroscopy (NIRS) is a relatively new technique complimentary to EEG for the development of brain-computer interfaces (BCIs). NIRS-based systems for detecting various cognitive and affective states such as mental and emotional stress have already been demonstrated in a range of adaptive human–computer interaction (HCI) applications. However, before NIRS-BCIs can be used reliably in realistic HCI settings, substantial challenges oncerning signal processing and modeling must be addressed. Although many of those challenges have been identified previously, the solutions to overcome them remain scant. In this paper, we first review what can be currently done with NIRS, specifically, NIRS-based approaches to measuring cognitive and affective user states as well as demonstrations of passive NIRS-BCIs. We then discuss some of the primary challenges these systems would face if deployed in more realistic settings, including detection latencies and motion artifacts. Lastly, we investigate the effects of some of these challenges on signal reliability via a quantitative comparison of three NIRS models. The hope is that this paper will actively engage researchers to acilitate the advancement of NIRS as a more robust and useful tool to the BCI community.
Neighbor combination for atmospheric turbulence image reconstruction

In this paper, we propose a novel neighbor combination framework for the reconstruction of the atmospheric turbulence degenerated image sequence. To utilize the spatial and temporal redundancy, a neighbor vector sampling strategy in spatial and temporal domain is conducted relying on the modeling of the registered sequence. Then, a combinator of neighbor vectors is developed based on a resampling maximum likelihood model and a relative approximation. Relying on the neighbor combination and spatial-invariant deconvolution, a clear image is reconstructed. Experiments on real data sets demonstrate the effectiveness of this framework.
Effect of protein and solution properties on the donnan effect during the ultrafiltration of proteins

Formulation of protein biopharmaceuticals as highly concentrated liquids can improve the drug substance storage and supply chain, improve the target product profile, and allow greater flexibility in dosing methods. The Donnan effect can cause a large offset in pH from the target value established with the diafiltration buffer during the concentration and diafiltration of charged proteins with ultrafiltration membranes. For neutral formulations, the pH will typically increase above the diafiltration buffer pH for basic monoclonal antibodies and decline below the diafiltration buffer pH for acidic Fc‐fusion proteins. In this study, new equations for the Donnan effect during the diafiltration and concentration of proteins in solutions containing monovalent and divalent ions were derived. The new Donnan models obey mass conservation laws, account for the buffering capacity of proteins, and account for protein‐ion binding. Data for the pH offsets of an Fc‐fusion protein and a monoclonal antibody were predicted in both monovalent and divalent buffers using these equations. To compensate for the pH offset caused by the Donnan effect, diafiltration buffers with pH and excipient values offset from the ultrafiltrate pool specifications can be used. The Donnan offset observed during the concentration of an acidic Fc‐fusion protein was mitigated by operating at low temperature. It is important to account for the Donnan effect during preformulation studies. The excipients levels in an ultrafiltration pool may differ from the levels in a protein solution obtained by adding buffers into concentrated protein solutions due to the Donnan effect. © 2010 American Institute of Chemical Engineers Biotechnol. Prog. , 2011
A Utility-Theoretic Approach to Privacy and Personalization

Online services such as web search, news portals, and e-commerce applications face the challenge of providing high-quality experiences to a large, heterogeneous user base. Recent efforts have highlighted the potential to improve performance by personalizing services based on special knowledge about users. For example, a user's location, demographics, and search and browsing history may be useful in enhancing the results offered in response to web search queries. However, reasonable concerns about privacy by both users, providers, and government agencies acting on behalf of citizens, may limit access to such information. We introduce and explore an economics of privacy in personalization, where people can opt to share personal information in return for enhancements in the quality of an online service. We focus on the example of web search and formulate realistic objective functions for search efficacy and privacy. We demonstrate how we can identify a near-optimal solution to the utility-privacy tradeoff. We evaluate the methodology on data drawn from a log of the search activity of volunteer participants. We separately assess users' preferences about privacy and utility via a large-scale survey, aimed at eliciting preferences about peoples' willingness to trade the sharing of personal data in returns for gains in search efficiency. We show that a significant level of personalization can be achieved using only a small amount of information about users.
Uncovering Biological Network Function via Graphlet Degree Signatures

Motivation Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker's yeast. Methods for determining protein function have shifted their focus from targeting specific proteins based solely on sequence homology to analyses of the entire proteome based on protein-protein interaction (PPI) networks. Since proteins interact to perform a certain function, analyzing structural properties of PPI networks may provide useful clues about the biological function of individual proteins, protein complexes they participate in, and even larger subcellular machines. Results We design a sensitive graph theoretic method for comparing local structures of node neighborhoods that demonstrates that in PPI networks, biological function of a node and its local network structure are closely related. The method summarizes a protein's local topology in a PPI network into the vector of graphlet degrees called the signature of the protein and computes the signature similarities between all protein pairs. We group topologically similar proteins under this measure in a PPI network and show that these protein groups belong to the same protein complexes, perform the same biological functions, are localized in the same subcellular compartments, and have the same tissue expressions. Moreover, we apply our technique on a proteome-scale network data and infer biological function of yet unclassified proteins demonstrating that our method can provide valuable guidelines for future experimental research such as disease protein prediction. Availability Data is available upon request.
GA201 (RG7160): A Novel, Humanized, Glycoengineered Anti-EGFR Antibody with Enhanced ADCC and Superior In Vivo Efficacy Compared with Cetuximab

Purpose: Anti-EGF receptor (EGFR) antibodies and small-molecule tyrosine kinase inhibitors have shown activity in epithelial tumors; however, agents that work by blocking the EGFR growth signal are ineffective when the oncogenic stimulus arises downstream, such as in tumors with KRAS mutations. Antibodies of the IgG1 subclass can also kill tumor cells directly through antibody-dependent cell-mediated cytotoxicity (ADCC), and the efficacy of this is determined by the interaction of the Fc portion of the target cell–bound antibody and Fc receptors present on immune effector cells. Experimental Design: We report the development of GA201, a novel anti-EGFR monoclonal antibody with enhanced ADCC properties. GA201 was derived by humanization of the rat ICR62 antibody. The Fc region of GA201 was glycoengineered to contain bisected, afucosylated carbohydrates for enhanced binding to FcγRIIIA. Results: In vitro binding of GA201 to EGFR inhibited EGF ligand binding, EGFR/HER2 heterodimerization, downstream signaling, and cell proliferation to a similar extent as cetuximab. However, GA201 exhibited superior binding to both the low- and high-affinity variants of FcγRIIIA. This resulted in significantly enhanced induction of ADCC compared with cetuximab against both KRAS-wild-type and -mutant tumor cells lines. This enhanced ADCC translated into superior in vivo efficacy in a series of mouse xenograft models. Efficacy of GA201 was further increased when administered in combination with chemotherapy (irinotecan). Conclusions: These data suggest that GA201 may be more effective than cetuximab in patients with EGFR-positive solid tumors and may also represent a first-in-class treatment of patients with KRAS-mutated tumors. Clin Cancer Res; 19(5); 1126–38. ©2012 AACR.
Cluster-based adaptation using density forest for HMM phone recognition

The dissimilarity between the training and test data in speech recognition systems is known to have a considerable effect on the recognition accuracy. To solve this problem, we use density forest to cluster the data and use maximum a posteriori (MAP) method to build a cluster-based adapted Gaussian mixture models (GMMs) in HMM speech recognition. Specifically, a set of bagged versions of the training data for each state in the HMM is generated, and each of these versions is used to generate one GMM and one tree in the density forest. Thereafter, an acoustic model forest is built by replacing the data of each leaf (cluster) in each tree with the corresponding GMM adapted by the leaf data using the MAP method. The results show that the proposed approach achieves 3:8% (absolute) lower phone error rate compared with the standard HMM/GMM and 0:8% (absolute) lower PER compared with bagged HMM/GMM.
Detection of Prion Protein in Urine-Derived Injectable Fertility Products by a Targeted Proteomic Approach

Background Iatrogenic transmission of human prion disease can occur through medical or surgical procedures, including injection of hormones such as gonadotropins extracted from cadaver pituitaries. Annually, more than 300,000 women in the United States and Canada are prescribed urine-derived gonadotropins for infertility. Although menopausal urine donors are screened for symptomatic neurological disease, incubation of Creutzfeldt-Jakob disease (CJD) is impossible to exclude by non-invasive testing. Risk of carrier status of variant CJD (vCJD), a disease associated with decades-long peripheral incubation, is estimated to be on the order of 100 per million population in the United Kingdom. Studies showing infectious prions in the urine of experimental animals with and without renal disease suggest that prions could be present in asymptomatic urine donors. Several human fertility products are derived from donated urine; recently prion protein has been detected in preparations of human menopausal gonadotropin (hMG). Methodology/Principal Findings Using a classical proteomic approach, 33 and 34 non-gonadotropin proteins were identified in urinary human chorionic gonadotropin (u-hCG) and highly-purified urinary human menopausal gonadotropin (hMG-HP) products, respectively. Prion protein was identified as a major contaminant in u-hCG preparations for the first time. An advanced prion protein targeted proteomic approach was subsequently used to conduct a survey of gonadotropin products; this approach detected human prion protein peptides in urine-derived injectable fertility products containing hCG, hMG and hMG-HP, but not in recombinant products. Conclusions/Significance The presence of protease-sensitive prion protein in urinary-derived injectable fertility products containing hCG, hMG, and hMG-HP suggests that prions may co-purify in these products. Intramuscular injection is a relatively efficient route of transmission of human prion disease, and young women exposed to prions can be expected to survive an incubation period associated with a minimal inoculum. The risks of urine-derived fertility products could now outweigh their benefits, particularly considering the availability of recombinant products.
Conceptual Metaphor and the Cognitive Foundations of Mathematics: Actual Infinity and Human Imagination*

The Infinite is one of the most intriguing ideas in which the human mind has ever engaged. Full of paradoxes and controversies, it has raised fundamental issues in domains as diverse and profound as theology, physics, and philosophy. The infinite, an elusive and counterintuitive idea, has even played a central role in defining mathematics, a fundamental field of human intellectual inquiry characterized by precision, certainty, objectivity, and effectiveness in modeling our real finite world. Particularly rich is the notion of actual infinity, that is, infinity seen as a “completed,” “realized” entity. This powerful notion has become so pervasive and fruitful in mathematics that if we decide to abolish it, most of mathematics as we know it would simply disappear, from infinitesimal calculus, to projective geometry, to set theory, to mention only a few.
Bilingual Multi-Word Term Tokenization for Chinese – Japanese Patent Translation

We propose to re-tokenize data with aligned bilingual multi-word terms to improve statistical machine translation (SMT) in technical domains. For that, we independently extract multi-word terms from the monolingual parts of the training data. Promising bilingual multi-word terms are then identified using the sampling-based alignment method by setting some threshold on translation probabilities. We estimate that the bilingual multi-word terms extracted are correct in more than 70 % of the cases. We report a significant improvement of BLEU scores in experiments conducted on a Chinese–Japanese patent corpus.
Covalently Bonded Adducts of Deoxyribonucleic Acid (DNA) Oligonucleotides with Single-Wall Carbon Nanotubes: Synthesis and Hybridization

We have developed a multistep route to the formation of covalently linked adducts of single-wall carbon nanotubes (SWNT) and deoxyribonucleic acid (DNA) oligonucleotides. X-ray photoelectron spectroscopy was used to characterize the initial chemical modification to form amine-terminated SWNTs, which were then covalently linked to DNA. The resulting DNA−SWNT adducts hybridize selectively with complementary sequences, with only minimal interaction with noncomplementary sequences.
Searching for a New Role in East Asian Regionalization: Japanese Production Networks in the Electronics Industry

This paper will be published in Peter and J. Katzenstein and Takashi Shiraishi, eds. Remaking East Asia: Beyond Americanization and Japanization, Cornell University Press. Part 1 introduces a few conceptual building-blocks that we need to capture the interactions between international business organization and regionalization. Part 2 describes the growing dependence of Japan's electronics industry on Asia, and explores how Japanese electronics firms are searching for ways to expand and upgrade their regional production networks, with China as the main prize. Part 3 examines constraints to change. I highlight peculiar features of the Japanese network management model in East Asia that once may have reflected strength. But now these very same features have turned into systemic weaknesses, as they constrain the capacity of Japanese firms to cope with and shape East Asia's increasingly complex processes of regionalization. The chapter concludes with an illustrative example of how some Japanese electronics firms are seeking to turn around gradually their EAPNs, by developing strategic alliances with emerging new industry leaders in Asia, primarily from Greater China. Forthcoming as: "Searching for a New Role in East Asian Regionalization - Japanese Production Networks in the Electronics Industry", chapter 7, in: Peter and J. Katzenstein and Takashi Shiraishi, eds., Remaking East Asia: Beyond Americanization and Japanization, Cornell University Press.
MoveMine 2.0: Mining Object Relationships from Movement Data

The development in positioning technology has enabled us to collect a huge amount of movement data from moving objects, such as human, animals, and vehicles. The data embed rich information about the relationships among moving objects and have applications in many fields, e.g., in ecological study and human behavioral study. Previously, we have proposed a system MoveMine that integrates several start-of-art movement mining methods. However, it does not include recent methods on relationship pattern mining. Thus, we propose to extend MoveMine to MoveMine 2.0 by adding substantial new methods in mining dynamic relationship patterns. Newly added methods focus on two types of pairwise relationship patterns: (i) attraction/avoidance relationship, and (ii) following pattern. A user-friendly interface is designed to support interactive exploration of the result and provides flexibility in tuning parameters. MoveMine 2.0 is tested on multiple types of real datasets to ensure its practical use. Our system provides useful tools for domain experts to gain insights on real dataset. Meanwhile, it will promote further research in relationship mining from moving objects.
Cache Coherence Protocols Workload Trends Favor Snooping Protocols Commercial Workload and Technology Trends Are Pushing Existing Shared-memory Multiprocessor Coherence Protocols in Divergent Directions. Token Coherence Provides a Framework for New Coherence Protocols That Can Reconcile These Opposi

The performance of database and Web servers is important because the services they provide are increasingly becoming part of our daily lives. Many of these servers are shared-memory multiprocessors, because most commercial workloads have abundant thread-level parallelism. Multiprocessors commonly use private per-processor caches that buffer blocks of the shared memory to improve both effective memory latency and bandwidth.
Energy-Efficient Protocol for Cooperative Networks

In cooperative networks, transmitting and receiving nodes recruit neighboring nodes to assist in communication. We model a cooperative transmission link in wireless networks as a transmitter cluster and a receiver cluster. We then propose a cooperative communication protocol for establishment of these clusters and for cooperative transmission of data. We derive the upper bound of the capacity of the protocol, and we analyze the end-to-end robustness of the protocol to data-packet loss, along with the tradeoff between energy consumption and error rate. The analysis results are used to compare the energy savings and the end-to-end robustness of our protocol with two non-cooperative schemes, as well as to another cooperative protocol published in the technical literature. The comparison results show that, when nodes are positioned on a grid, there is a reduction in the probability of packet delivery failure by two orders of magnitude for the values of parameters considered. Up to 80% in energy savings can be achieved for a grid topology, while for random node placement our cooperative protocol can save up to 40% in energy consumption relative to the other protocols. The reduction in error rate and the energy savings translate into increased lifetime of cooperative sensor networks.
Radiation Inactivation Studies of the Benzodiazepine/γ‐Aminobutyric Acid/Chloride Ionophore Receptor Complex

Abstract: Radiation inactivation was used to estimate the molecular weight of the benzodiazepine (BZ), γ‐amino‐butyric acid (GABA), and associated chloride ionophore (picrotoxinin/barbiturate) binding sites in frozen membranes prepared from rat forebrain. The target size of the BZ recognition site (as defined by the binding of the agonists [3H]diazepam and [3H]flunitrazepam, the antagonists [3H]Ro 15–1788 and [3H]CGS 8216, and the inverse agonist [3H]ethyl‐β‐carboline‐3‐carboxylate) averaged 51,000 × 2,000 daltons. The presence or absence of GABA during irradiation had no effect on the target size of the BZ recognition site. The apparent molecular weight of the GABA binding site labelled with [3H]muscimol was identical to the BZ receptor when determined under identical assay conditions. However the target size of the picrotoxinin/barbiturate binding site labelled with the cage convulsant [35S]t‐butylbicyclophosphorothionate was about threefold larger (138,000 daltons). The effects of lyophilization on BZ receptor binding activity and target size analysis were also determined. A decrease in the number of BZ binding sites (Bmax) was observed in the nonirradiated, lyophilized membranes compared with frozen membranes. Lyophilization of membranes prior to irradiation at – 135°C or 30°C resulted in a 53 and 151% increase, respectively, in the molecular weight (target size) estimates of the BZ recognition site when compared with frozen membrane preparations. Two enzymes were also added to the membrane preparations for subsequent target size analysis. In lyophilized preparations irradiated at 30°C, the target size for (i‐galactosidase was also increased 71% when compared with frozen membrane preparations. In contrast, the target size for glucose‐6‐phosphate dehydrogenase was not altered by lyophilization. Thus, in some cases lyophilization may lead to an increase in protein target size, possibly due to aggregation of protein subunits. We conclude that in frozen membrane preparations the functional target size of the BZ and GABA binding sites reflects the subunit molecular weights for the BZ/GABA/chloride ionophore receptor complex.