Miracle-dz/UniFAR-FTUs huggingface dataset:
ZnO1−xTex highly mismatched alloys beyond the dilute alloy limit: Synthesis and electronic band structure

We have synthesized ZnO1−xTex highly mismatched alloys (HMAs) with high, up to x = 0.34, Te content using pulsed laser deposition. We have found that the film composition is strongly dependent on the growth temperature and background pressure during growth. Lowering the growth temperature and/or increasing the background Ar or N2 pressure increases the Te content in the film. When grown in O2 atmosphere, however, oxidation of the Te species occurred, resulting in much less Te incorporation in the O sublattice. While a lower substrate temperature is needed for the incorporation of more Te in the ZnO1−xTex film, the crystallinity of the film degrades at low growth temperature. X-ray photoemission, soft x-ray absorption, and x-ray emission measurements reveal that the observed drastic narrowing of the optical bandgap with increasing Te content is primarily due to the modification of the valence band. The experimentally observed evolution of the optical properties of ZnO1−xTex HMAs from dilute to mid-composition range (x > 0.3) is analyzed within the framework of a modified band anticrossing model with composition dependent coupling parameters describing the anticrossing interaction between the valence band of the matrix and Te localized states. Electrically, we found that adding Te in ZnO increases the film resistivity. When doped with N, a drastic drop in n from mid-1019 to 1015 cm−3 is observed for ZnO1−xTex with ∼2%–4% of Te. These electrical behaviors can be understood as the effect of the upward shift of the valence band, which favors the formation of native as well as N acceptors.We have synthesized ZnO1−xTex highly mismatched alloys (HMAs) with high, up to x = 0.34, Te content using pulsed laser deposition. We have found that the film composition is strongly dependent on the growth temperature and background pressure during growth. Lowering the growth temperature and/or increasing the background Ar or N2 pressure increases the Te content in the film. When grown in O2 atmosphere, however, oxidation of the Te species occurred, resulting in much less Te incorporation in the O sublattice. While a lower substrate temperature is needed for the incorporation of more Te in the ZnO1−xTex film, the crystallinity of the film degrades at low growth temperature. X-ray photoemission, soft x-ray absorption, and x-ray emission measurements reveal that the observed drastic narrowing of the optical bandgap with increasing Te content is primarily due to the modification of the valence band. The experimentally observed evolution of the optical properties of ZnO1−xTex HMAs from dilute to mid-composit.
Detection of Histone H2AX Phosphorylation on Ser‐139 as an Indicator of DNA Damage

This unit describes immunocytochemical detection of histone H2AX phosphorylated on Ser‐139 (γH2AX) to reveal DNA damage, particularly when the damage involves the presence of DNA double‐strand breaks (DSBs). These breaks often result from DNA damage induced by ionizing radiation or by treatment with anticancer drugs such as DNA topoisomerase inhibitors. Furthermore, DSBs are generated in the course of DNA fragmentation during apoptosis. The unit presents strategies to distinguish radiation‐ or drug‐induced DNA breaks from those intrinsically formed in untreated cells or associated with apoptosis. The protocol describes immunocytochemical detection of γH2AX combined with measurement of DNA content to identify cells that have DNA damage and concurrently to assess their cell‐cycle phase. The detection is based on indirect immunofluorescence using FITC– or Alexa Fluor 488–labeled antibody, with DNA counterstained with propidium iodide and cellular RNA removed with RNase A. © 2019 by John Wiley & Sons, Inc.
Phylogenetic analyses of pandemic influenza A (H1N1) virus in university students at Tobetsu, Hokkaido, Japan

Pandemic influenza H1N1 virus (A[H1N1]pdm09) emerged in 2009. To determine the phylogeography of A(H1N1)pdm09 in a single population, 70 strains of the virus were isolated from university students or trainee doctors at Tobetsu, Hokkaido, Japan, between September and December 2009. The nucleotide sequences of the HA1 region of the HA genes and described phylogenetic relationships of the strains circulating among them were analyzed. It was found that the 70 isolates could be phylogenetically separated into three groups and that two epidemics were caused by different groups of the virus. The three groups were also distinguishable from each other by three amino acid changes: A197T, S203T and Q293H. The substitution of S203T, which is located in the antigenic site, suggests antigenic drift of the virus.
Post-conditioning to improve cardiopulmonary resuscitation

Purpose of reviewDespite decades of advances in prehospital and in-hospital medical care, patients with out-of-hospital cardiac arrest continue to have poor neurologic and cardiac function following otherwise successful resuscitation. This review examines the mechanisms and therapeutic strategies currently under development to activate the post-conditioning pathways and thereby improve survival and function. Recent findingsPost-conditioning utilizes the reperfusion injury salvage kinase (RISK) and survivor activating factor enhancement (SAFE) pathways as common avenues to promote cell survival and function. Ischemic post-conditioning and multiple medications activate these pathways resulting in improved cardiac and neurological function in animal models of cardiac arrest. SummaryDetailed knowledge of the RISK and SAFE pathways can be used for further drug development. Human studies are now underway to test some of these strategies, but further clinical trials are necessary to translate these therapies to clinical practice.
Exploiting sparsity and co-occurrence structure for action unit recognition

We present a novel Bayesian framework for facial action unit recognition. The first key observation behind this work is sparsity: out of possible 45 (and more) facial action units, only very few are active at any moment. The second is the strong statistical co-occurrence structure: most facial expressions are made by common combinations of facial action units, so knowing the presence of one can act as a strong prior for inferring the presence of others. We developed a novel Bayesian graphical model that encodes these two natural aspects of facial action units via compressed sensing and group-wise sparsity inducing priors. One crucial aspect of our approach is the allowance of overlapping group structures, which proves useful in dealing with action units that occur frequently across multiple groups. We derive an efficient inference scheme and show how such sparsity and co-occurrence can be automatically learned from data. Experiments on three standard benchmark datasets show superiority over the state-of-the-art.
Articulation: an integrated approach to the diagnosis, replanning, and rescheduling of software process failures

The paper presents an integrated approach to articulate software process plans that fail. Articulation repairs a plan when a diagnosed failure occurs and reschedules changes that ensure the plan's continuation. In implementing articulation, we combine diagnosis, replanning, and rescheduling into a powerful mechanism supporting adaptive process-based software development. Use of articulation in plan execution supports recovery and repair of anticipated failures, as well as revising and improving the plans to become more effective. We also describe how a prototype knowledge-based system we developed implements the articulation approach. <<ETX>>
A combined TCP aware scheduling and assembly scheme for OBS networks

The efficient transmission of TCP traffic over OBS networks is a challenging problem, due to the high sensitivity of TCP congestion control mechanism to losses. In this work, we propose solutions to this problem, through the burst assembly and scheduling mechanism of OBS. We investigate and propose algorithms to achieve performance enhancements for TCP traffic by taking into account TCP state information. We prove our claims with references to well-established TCP models, and validate the proposed algorithms through simulations.
Learning the Structure for Structured Sparsity

Structured sparsity has recently emerged in statistics, machine learning and signal processing as a promising paradigm for learning in high-dimensional settings. All existing methods for learning under the assumption of structured sparsity rely on prior knowledge on how to weight (or how to penalize) individual subsets of variables during the subset selection process, which is not available in general. Inferring group weights from data is a key open research problem in structured sparsity. In this paper, we propose a Bayesian approach to the problem of group weight learning. We model the group weights as hyperparameters of heavy-tailed priors on groups of variables and derive an approximate inference scheme to infer these hyperparameters. We empirically show that we are able to recover the model hyperparameters when the data are generated from the model, and we demonstrate the utility of learning weights in synthetic and real denoising problems.
Volume visualization of sparse irregular meshes

An algorithm that was designed for the data typically found in reservoir simulation and structural analysis is presented. Designed for general applicability and high efficiency, it can be used to visualize scalar volumes of irregular computational meshes. The algorithm accepts as input virtually any 3-D mesh used in computer simulations. Pictures of practical value can be drawn interactively. <<ETX>>
Application of Speech Recognition Technology on the Evaluation of English Pronunciation Teaching

In order to better the current English learning environment and teaching mode so as to improve the efficiency of spoken English learning, the speech recognition technology is applied to the scoring of English pronunciation teaching. It is pointed out that the feature score be divided into three domains, including the pronunciation segment, the hyper articulation segment and the perceptual domain. The speech recognition technology is used to identify the pronunciation features, and the value of recognition accuracy is used to get the fractional value. After calculating and measuring the correlation coefficient, the correlation coefficient between the synthesized machine score by the three domains and expert score is higher than that of the pronunciation segment score, which is also higher than the effect of the synthesized machine score of any two fields. The research shows that the performance of the scoring mechanism is much better than the previous scoring mechanism, suggesting that it is helpful to the evaluation of English pronunciation teaching.
SF2/ASF Binds the Human Papillomavirus Type 16 Late RNA Control Element and Is Regulated during Differentiation of Virus-Infected Epithelial Cells

ABSTRACT Pre-mRNA splicing occurs in the spliceosome, which is composed of small ribonucleoprotein particles (snRNPs) and many non-snRNP components. SR proteins, so called because of their C-terminal arginine- and serine-rich domains (RS domains), are essential members of this class. Recruitment of snRNPs to 5′ and 3′ splice sites is mediated and promoted by SR proteins. SR proteins also bridge splicing factors across exons to help to define these units and have a central role in alternative and enhancer-dependent splicing. Here, we show that the SR protein SF2/ASF is part of a complex that forms upon the 79-nucleotide negative regulatory element (NRE) that is thought to be pivotal in posttranscriptional regulation of late gene expression in human papillomavirus type 16 (HPV-16). However, the NRE does not contain any active splice sites, is located in the viral late 3′ untranslated region, and regulates RNA-processing events other than splicing. The level of expression and extent of phosphorylation of SF2/ASF are upregulated with epithelial differentiation, as is subcellular distribution, specifically in HPV-16-infected epithelial cells, and expression levels are controlled, at least in part, by the virus transcription regulator E2.
Wildlife rescue and relocation efforts associated with the Panamá Canal Third Locks Expansion Project

Since the ceding of the Panamá Canal from the United States to the Republic of Panamá in 1999, human development has accelerated in Panamá, resulting in the loss of habitat and declines in wildlife populations. We implemented a wildlife rescue and relocation program associated with the third locks expansion project of the Panamá Canal and here describe our efforts and findings. During 2007–2010, 896 animals were rescued from 11 sites along the canal; 84% of these individuals (n = 806) were successfully relocated to protected areas and 6% (n = 57) were relocated to captivity. One-hundred three species were rescued during >16,000 h of human effort; of those species, 66 were listed as Least Concern or higher on the IUCN Red List. We estimated wildlife biodiversity values from rescue sites; mean values were 0.2, 0.9, 2.5, and 2.1 for Berger–Parker, Simpson, Shannon, and Brillouin indices, respectively, indicating high diversity in species composition. Our research provides rare insight into the process and phases of a large wildlife rescue operation as well as an examination of wildlife diversity found in the Panamá Canal Watershed.
QoS routing for P 2 P networking

Growth of dynamic P2P (peer-to-peer) systems is almost unique in the history of Internet. The massive use of such systems could almost be comparised to the growth of Internet itself. This survey reviews the field of Quality-of-Servicerouting. First traditional IP-routing concept and it’s QoSrouting factors are introduced. Then some IP-routing QoSalgorithms are examined, as well as some related techniques like resource reservation protocol (RSVP), differential services (DiffServ) and multiprotocol label switching (MPLS), traffic engineering, and admission control. Then we dive into the peer-to-peer networks where P2P features, performance issues and algorithms will be researched. Some P2P systems will be looked closely. Then some P2P searching and routing techniques are researched deeper. Overlay routing and efficient information retrieval for example. Then we look the QoS challenges for P2Psystems including interoperability problems, dynamic QoS interconnection. It is shown that P2P is not a solution for all the problems, instead it has problems itself, security and reliability for example. When operating anonymous in the Internet, the security issues are always a problem.
Gibbs Sampling in Probabilistic Description Logics with Deterministic Dependencies

In many applications there is interest in representing both probabilistic and deterministic dependencies. This is especially the case in applications using Description Logics (DLs), where ontology engineering usually is based on strict knowledge, while there is also the need to represent uncertainty. We introduce a Markovian style of probabilistic reasoning in first-order logic known as Markov logic and investigate the opportunities for restricting this formalism to DLs. In particular, we show that Gibbs sampling with deterministic dependencies specified in an appropriate fragment remains correct, i.e., probability estimates approximate the correct probabilities. We propose a Gibbs sampling method incorporating deterministic dependencies and conclude that this incorporation can speed up Gibbs sampling significantly.
Learning Optimal Nonlinearities for Iterative Thresholding Algorithms

Iterative shrinkage/thresholding algorithm (ISTA) is a well-studied method for finding sparse solutions to ill-posed inverse problems. In this letter, we present a data-driven scheme for learning optimal thresholding functions for ISTA. The proposed scheme is obtained by relating iterations of ISTA to layers of a simple feedforward neural network and developing a corresponding error backpropagation algorithm for fine-tuning the thresholding functions. Simulations on sparse statistical signals illustrate potential gains in estimation quality due to the proposed data adaptive ISTA.
Thymic selection of CD8+ single positive cells with a class II major histocompatibility complex-restricted receptor

We describe mice that express a transgenic T cell receptor alpha/beta (TCR-alpha/beta) specific for peptide 111-119 from influenza hemagglutinin presented by I-Ed class II major histocompatibility complex (MHC) molecules. The transgenic TCR is expressed on CD4+8- as well as CD4-8+ mature T cells even in mice that are deficient in rearrangement or do not express endogenous TCR-alpha genes. The CD4-8+ T cells require I-Ed class II MHC molecules for positive selection and can be activated to proliferate and to kill by I-Ed molecules presenting the relevant peptide. Full maturation of these cells, however, also requires the presence of class I MHC molecules. The results are compatible with the notion that T cell maturation requires multiple receptor-ligand interactions and establish an exception to the rule that class II-restricted TCRs are exclusively expressed by mature CD4+8- cells.
Clustering-Based Content Adaptive Tiles Under On-chip Memory Constraints

Tiles have been introduced to the next generation video coding standard, high-efficiency video coding (HEVC) standard, as a fundamental tool to reduce on-chip memory requirement during encoding and decoding high-definition video. In this paper, a content adaptive tile partitioning approach is proposed to improve the compression efficiency for HEVC under the on-chip memory constraint. Local competition optimization-based rectangular clustering is proposed to partition the frames into a required number of tiles adapting to content variations. Under the same memory constraint, the adaptive scheme improves compression efficiency by up to 1.8% bitrate saving relative to uniformly spaced tiles with negligible complexity increment. It especially benefits the videos with regional high spatial correlations and no penalty in compression efficiency is observed for other types of videos.
Cortical visual prosthesis: a detailed large-scale simulation study

Recent advances in applying optogenetics in primates initiated the development of light based prosthetic implants for sensory restoration. Thanks to being the most well explored cortical area that is readily accessible at the surface of the brain, vision restoration via direct optogenetic activation of primary visual cortex is one of the most promising early targets for a optogenetics based prosthetic program. However, two fundamental elements of the cortical optogenetic prosthesis remain unclear. First, the exact mechanisms of neural dynamics under direct cortical stimulation, especially in the context of living, active and functionally specific intra-cortical neural circuitry, is poorly understood. Second, we lack protocols for transformation of arbitrary visual stimuli into light activation patterns that would induce perception of the said stimulus by the subject. In this study we address these issues using a large-scale spiking neural network modeling strategy of high biological fidelity. We examine the relationship between specific spatial configuration of light delivered to cortex and the resulting spatio-temporal pattern of activity evoked in the simulated cortical circuitry. Using such virtual experiments, we design a protocol for translation of a specific set of stimuli to activation pattern of a matrix of light emitting elements and provide a detailed assessment of the resulting cortical activations with respect to the natural vision control condition. In this study we restrict our focus to the grating stimulus class, which are an ideal starting point for exploration due to their thoroughly characterized representation in V1 and well-defined information content. However, we also provide an outline of a straight-forward road-map for transforming this grating centric stimulation protocol towards general strategy capable of transforming arbitrary spatio-temporal visual stimulus to a spatio-temporal pattern of light, thus enabling vision restoration via optogenetic V1 activation.
Animal models of emphysema: the next generations.

Niewoehner (1) wrote in 1988 that pulmonary emphysema is one of the most important causes of morbidity and mortality in our modern society, and his statement rings just as true today as it did then. Progress in the intervening years has built on the creation and analysis of animal models for this disease, many of which, including the one described by Zheng et al. (2) in a recent issue of the JCI, exploit technology that could not have been imagined at that time. Animal models are especially important for slowly progressing diseases such as pulmonary emphysema (3). They facilitate the understanding of complex pathogenetic relationships and allow hypothesis testing. They also have the potential to allow tests of preventive therapies that would be inordinately time consuming or ethically forbidden in humans. A review of past and future generations of animal models will place the contribution of Zheng and colleagues in perspective.
First‐line treatment with FOLFOXIRI for advanced pancreatic cancer in clinical practice: Patients' outcome and analysis of prognostic factors

FOLFIRINOX is a standard first‐line treatment for advanced pancreatic cancer (aPC). The Gruppo Oncologico Nord Ovest (GONO) FOLFOXIRI regimen demonstrated efficacy in metastatic colorectal cancer. We aimed to evaluate activity and tolerability of FOLFOXIRI regimen in patients with aPC and to explore putative prognostic factors. One hundred thirty‐seven consecutive aPC patients were treated with FOLFOXIRI in our institution between 2008 and 2014. Clinical, laboratory and pathological data were collected and their association with activity, progression free survival (PFS) and overall survival (OS) was investigated. After a median follow up of 30 months, median PFS and OS were 8.0 months (95% CI 6.19–9.81) and 12 months (95% CI 9.75–14.25), respectively. Response rate was 38.6%, while disease‐control rate 72.2%. At multivariate analysis liver metastases (p = 0.019; Hazard Ratio, HR, 0.59, 95% Confidence Interval, CI, 0.380.96), Eastern Cooperative Oncology Group (ECOG) performance status (PS) 1 (p = 0.001; HR 2.26, 95%CI 1.42–3.59) and neutrophil‐lymphocyte ratio (NLR)> 4 (p= 0.002; HR: 2.42; 95% CI 1.38–4.25) were associated with poorer OS. We categorized 119 pts with complete available data as good‐risk (0 factors, 38 pts), intermediate‐risk (1 factor, 49 pts) and poor‐risk (≥2 factors, 32 pts). Median OS for these three groups were 17.6, 11.1 and 7.4 months, respectively (p < 0.001). FOLFOXIRI is active and feasible in aPC. Prognosis of aPC pts treated with FOLFOXIRI is influenced by easily available factors: our analysis revealed ECOG PS, liver metastases and NLR as the most important predictors of survival. These factors could be helpful for treatment decision and clinical trial design.
Analysis on perfect location spoofing attacks using beamforming

Location spoofing attacks pose serious threats to the location based wireless network mechanisms. Most existing literature focuses on detecting location spoofing attacks or design of robust localization algorithms. However, our study shows that, in many circumstances, perfect location spoofing (PLS) can stay undetected even if robust localization algorithms or detection mechanisms are used. In this paper, we present theoretical analysis on the feasibility of beamforming-based PLS attacks and how it is affected by the anchor deployment. We formulate PLS as a nonlinear feasibility problem based on smart antenna array pattern synthesis. Due to the intractable nature of this feasibility problem, we solve it using semidefinite relaxation (SDR) in conjunction with a heuristic local search algorithm. Simulation results show the effectiveness of our analytical approach and provide insightful advices for defence against PLS attacks.