Miracle-dz/UniFAR-FTUs huggingface dataset:
Age specific responses to acute inhalation of diffusion flame soot particles: Cellular injury and the airway antioxidant response

Current studies of particulate matter (PM) are confounded by the fact that PM is a complex mixture of primary (crustal material, soot, metals) and secondary (nitrates, sulfates, and organics formed in the atmosphere) compounds with considerable variance in composition by sources and location. We have developed a laboratory-based PM that is replicable, does not contain dust or metals and that can be used to study specific health effects of PM composition in animal models. We exposed both neonatal (7 days of age) and adult rats to a single 6-h exposure of laboratory generated fine diffusion flame particles (DFP; 170 µg/m3), or filtered air. Pulmonary gene and protein expression as well as indicators of cytotoxicity were evaluated 24 h after exposure. Although DFP exposure did not alter airway epithelial cell composition in either neonates or adults, increased lactate dehydrogenase activity was found in the bronchoalveolar lavage fluid of neonates indicating an age-specific increase in susceptibility. In adults, 16 genes were differentially expressed as a result of DFP exposure whereas only 6 genes were altered in the airways of neonates. Glutamate cytsteine ligase protein was increased in abundance in both DFP exposed neonates and adults indicating an initiation of antioxidant responses involving the synthesis of glutathione. DFP significantly decreased catalase gene expression in adult airways, although catalase protein expression was increased by DFP in both neonates and adults. We conclude that key airway antioxidant enzymes undergo changes in expression in response to a moderate PM exposure that does not cause frank epithelial injury and that neonates have a different response pattern than adults.
Cirrus cloud ice water content in the uppermost troposphere: Six years of observations from the Cloud and Aerosol Lidar with Orthogonal Polarization

The purpose of this paper is to provide an overview description of the global cloud ice water content product provided by the first long-term space lidar mission. The Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) has been providing data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite for more than six years, since June, 2007. Figure 1 is a schematic representation of CALIPSO with CALIOP operating as part of the NASA A-Train. CALIPSO is host to three co-aligned nadirviewing instruments; these are CALIOP (lidar), as well as the Imaging Infrared Radiometer (IIR) and Wide Field Camera (WFC). CALIOP provides a suite of cloud and aerosol data products, including ice water content (IWC), ice water path (IWP), cloud particle extinction and optical depth (OD). The IIR also provides cloud data products, including IWP, OD, effective diameter and a microphysical parameter that diagnoses cloud particle habit. Data from the three instruments on CALIPSO are synergistic since they provide perfectly collocated information about the clouds below the satellite. An overview of the CALIPSO mission is available in Winker et. al. (2010).
Continuous-Time Bayesian Modeling of Clinical Data

Inference from hospital patient records is difficult because data collection is done at arbitrary (not evenlyspaced) time intervals, and key clinical information is recorded only in unstructured form (as free text in doctors’ notes). We present remind, a framework for performing inference from patient records based upon continuous-time Markov models and Bayesian networks. We empirically justify the need for such a complex model. remind only uses easily-available domain knowledge which we obtain from physicians and medical literature, which may be inaccurate. We also demonstrate the robustness of our approach to parameter assignment.
Unified Analytic Model for Current–Voltage Behavior in Amorphous Oxide Semiconductor TFTs

We present a simple and semi-physical analytical description of the current-voltage characteristics of amorphous oxide semiconductor thin-film transistors in the above-threshold and sub-threshold regions. Both regions are described by single unified expression that employs the same set of model parameter values directly extracted from measured terminal characteristics. The model accurately reproduces measured characteristics of amorphous semiconductor thin film transistors in general, yielding a scatter of <;4%.
Data‐driven modeling reconciles kinetics of ERK phosphorylation, localization, and activity states

The extracellular signal‐regulated kinase (ERK) signaling pathway controls cell proliferation and differentiation in metazoans. Two hallmarks of its dynamics are adaptation of ERK phosphorylation, which has been linked to negative feedback, and nucleocytoplasmic shuttling, which allows active ERK to phosphorylate protein substrates in the nucleus and cytosol. To integrate these complex features, we acquired quantitative biochemical and live‐cell microscopy data to reconcile phosphorylation, localization, and activity states of ERK. While maximal growth factor stimulation elicits transient ERK phosphorylation and nuclear translocation responses, ERK activities available to phosphorylate substrates in the cytosol and nuclei show relatively little or no adaptation. Free ERK activity in the nucleus temporally lags the peak in nuclear translocation, indicating a slow process. Additional experiments, guided by kinetic modeling, show that this process is consistent with ERK's modification of and release from nuclear substrate anchors. Thus, adaptation of whole‐cell ERK phosphorylation is a by‐product of transient protection from phosphatases. Consistent with this interpretation, predictions concerning the dose‐dependence of the pathway response and its interruption by inhibition of MEK were experimentally confirmed.
Accessing Music Collections Via Representative Cluster Prototypes in a Hierarchical Organization Scheme

This paper addresses the issue of automatically organizing a possibly large music collection for intuitive access. We present an approach to cluster tracks in a hierarchical manner and to automatically find representative pieces of music for each cluster on each hierarchy level. To this end, audio signal-based features are complemented with features derived via Web content mining in a novel way. Automatic hierarchical clustering is performed using a variant of the Self-Organizing Map, which we further modified in order to create playlists containing similar tracks. The proposed approaches for playlist generation on a hierarchically structured music collection and finding prototypical tracks for each cluster are then integrated into the Traveller’s Sound Player, a mobile audio player application that organizes music in a playlist such that the distances between consecutive tracks are minimal. We extended this player to deal with the hierarchical nature of the playlists generated by the proposed structuring approach. As for evaluation, we first assess the quality of the clustering method using the measure of entropy on a genre-annotated test set. Second, the goodness of the method to find prototypical tracks for each cluster is investigated in a user study.
Effects of Zusanli and Ashi Acupoint Electroacupuncture on Repair of Skeletal Muscle and Neuromuscular Junction in a Rabbit Gastrocnemius Contusion Model

Objective. To explore the effects of electroacupuncture (EA) at ST36 (EA-ST36) and at Ashi acupoints (EA-Ashi) on skeletal muscle repair. Methods. Seventy-five rabbits were randomly divided into five groups: normal, contusion, EA-Ashi, EA-ST36, and EA at Ashi acupoints and ST36 (EA-AS). EA (0.4 mA, 2 Hz, 15 min) was applied after an acute gastrocnemius contusion. The morphology of myofibers and neuromuscular junctions (NMJs) and expressions of growth differentiation factor-8 (GDF-8), acetylcholinesterase (AChE), Neuregulin 1 (NGR1), and muscle-specific kinase (MuSK) were assessed 7, 14, and 28 days after contusion. Results. Compared with that in contusion group, there was an increase in the following respective parameters in treatment groups: the number and diameter of myofibers, the mean staining area, and continuities of NMJs. A comparison of EA-Ashi and EA-ST36 groups indicated that average myofiber diameter, mean staining area of NMJs, and expressions of AChE and NRG1 were higher in EA-Ashi group, whereas expression of GDF-8 decreased on day 7. However, increases in myofiber numbers, expressions of MuSK and AChE, as well as decreases in GDF-8 expression, and the discontinuities were observed in EA-ST36 group on the 28th day. Conclusion. Both EA-ST36 and EA-Ashi promoted myofiber regeneration and restoration of NMJs. EA-Ashi was more effective at earlier stages, whereas EA-ST36 played a more important role at later stages.
Bringing computer graphics to everyday environments with informative art

The field of display technology is rapidly developing, and LCD-and plasma-displays are already invading our surroundings. Alternative technologies such as "electronic ink", electro-luminescent materials, and even color-changing textiles [Holmquist and Melin 2001] will further increase the number of possibilities to integrate computer graphics in our everyday lives. We believe that computer graphics for everyday life will have requirements that are very different from those of a Web page or a movie special effect. To explore this, we have developed a type of applications that anticipates a future use of computer graphics, so-called Informative Art.
Regularized Negative Correlation Learning for Neural Network Ensembles

Negative correlation learning (NCL) is a neural network ensemble learning algorithm that introduces a correlation penalty term to the cost function of each individual network so that each neural network minimizes its mean square error (MSE) together with the correlation of the ensemble. This paper analyzes NCL and reveals that the training of NCL (when ¿ = 1) corresponds to training the entire ensemble as a single learning machine that only minimizes the MSE without regularization. This analysis explains the reason why NCL is prone to overfitting the noise in the training set. This paper also demonstrates that tuning the correlation parameter ¿ in NCL by cross validation cannot overcome the overfitting problem. The paper analyzes this problem and proposes the regularized negative correlation learning (RNCL) algorithm which incorporates an additional regularization term for the whole ensemble. RNCL decomposes the ensemble's training objectives, including MSE and regularization, into a set of sub-objectives, and each sub-objective is implemented by an individual neural network. In this paper, we also provide a Bayesian interpretation for RNCL and provide an automatic algorithm to optimize regularization parameters based on Bayesian inference. The RNCL formulation is applicable to any nonlinear estimator minimizing the MSE. The experiments on synthetic as well as real-world data sets demonstrate that RNCL achieves better performance than NCL, especially when the noise level is nontrivial in the data set.
Towards automated 10–30 m resolution land cover mapping in insular South-East Asia

Abstract In this study, we create and critically analyse an automated decision tree classification approach for regional level land cover mapping in insular South-East Asian conditions, using a combination of 10–30 m resolution optical and radar data. The resulting map contains 11 land cover classes and reveals a great deal of contextual information due to high spatial resolution. A limited accuracy assessment indicates 59–97% class wise accuracies. The unprecedented spatial detail of closed canopy oil palm mapping (with user’s accuracy of 90%) is seen as the most promising feature of the mapping approach. The incapability of separating primary forests from other tree cover, and the large variety of different landscapes (e.g. home gardens and tea plantations) classified as shrubland, are considered the main areas for future improvement. Overall, the study demonstrates the great potential of multi-source 10–30 m resolution high data volume land cover mapping approaches in insular South-East Asian conditions.
An evolutionary learning approach for adaptive negotiation agents

Developing effective and efficient negotiation mechanisms for real‐world applications such as e‐business is challenging because negotiations in such a context are characterized by combinatorially complex negotiation spaces, tough deadlines, very limited information about the opponents, and volatile negotiator preferences. Accordingly, practical negotiation systems should be empowered by effective learning mechanisms to acquire dynamic domain knowledge from the possibly changing negotiation contexts. This article illustrates our adaptive negotiation agents, which are underpinned by robust evolutionary learning mechanisms to deal with complex and dynamic negotiation contexts. Our experimental results show that GA‐based adaptive negotiation agents outperform a theoretically optimal negotiation mechanism that guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for real‐world applications. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 41–72, 2006.
Directing exploratory search with interactive intent modeling

We introduce interactive intent modeling, where the user directs exploratory search by providing feedback for estimates of search intents. The estimated intents are visualized for interaction on an Intent Radar, a novel visual interface that organizes intents onto a radial layout where relevant intents are close to the center of the visualization and similar intents have similar angles. The user can give feedback on the visualized intents, from which the system learns and visualizes improved intent estimates. We systematically evaluated the effect of the interactive intent modeling in a mixed-method task-based information seeking setting with 30 users, where we compared two interface variants for interactive intent modeling, namely intent radar and a simpler list-based interface, to a conventional search system. The results show that interactive intent modeling significantly improves users' task performance and the quality of retrieved information.
A predominant increase in the APC gene isoform with exon 9a in a case of attenuated familial adenomatous polyposis

To the Editor: Familial adenomatous polyposis (FAP) is an autosomal dominantly inherited cancer-predisposition syndrome classically characterized by the progressive development of more than 100 colorectal adenomatous polyps and extracolonic manifestations. The disorder is caused by a germline mutation of the adenomatous polyposis coli (APC) gene mapped at 5q21 (1). In contrast to classical FAP, attenuated FAP (AAPC) with fewer than 100 colorectal adenomatous polyps has been assigned to have germline mutations in the 5ƒ region, exon 9 and the 3ƒ region of the APC gene (2–4) An exon 9 splicedonor mutation at position 5 in intron 9 and a frameshift mutation in the alternatively spliced region of exon 9 have also been shown to be associated with late-onset FAP (5, 6). These findings suggest that an altered proportion of the products of the alternatively spliced-APC gene may lead to a phenotype of the disease. Here, we described an AAPC patient associated with a cribriform-morular variant of papillary thyroid carcinoma. Molecular analysis revealed a predominant accumulation of a transcript containing APC exon 9a. A 34-year-old female patient presented to the Kuma Hospital for a cribriform-morular variant of papillary thyroid carcinoma, which is observed frequently in FAP-associated thyroid carcinoma. The diagnosis of AAPC was based on the presence of 85 colonic adenomatous polyps. Her paternal grandmother had died of pancreas cancer. Her sister was affected by a colonic adenomatous polyp and an adenomatous goiter of the thyroid. APC molecular screening was carried out using the protein truncation test (PTT) described in the literature (7), but it failed to demonstrate a truncated mutation in each exon of the APC gene. The alterations identified by two independent PTTs were a signal of decreased intensity representing a segment of wild-type APC protein (codons 1 to 479), as well as a signal of significantly increased intensity corresponding to the smaller product of
Joint Video and Text Parsing for Understanding Events and Answering Queries

This article proposes a multimedia analysis framework to process video and text jointly for understanding events and answering user queries. The framework produces a parse graph that represents the compositional structures of spatial information (objects and scenes), temporal information (actions and events), and causal information (causalities between events and fluents) in the video and text. The knowledge representation of the framework is based on a spatial-temporal-causal AND-OR graph (S/T/C-AOG), which jointly models possible hierarchical compositions of objects, scenes, and events as well as their interactions and mutual contexts, and specifies the prior probabilistic distribution of the parse graphs. The authors present a probabilistic generative model for joint parsing that captures the relations between the input video/text, their corresponding parse graphs, and the joint parse graph. Based on the probabilistic model, the authors propose a joint parsing system consisting of three modules: video parsing, text parsing, and joint inference. Video parsing and text parsing produce two parse graphs from the input video and text, respectively. The joint inference module produces a joint parse graph by performing matching, deduction, and revision on the video and text parse graphs. The proposed framework has the following objectives: to provide deep semantic parsing of video and text that goes beyond the traditional bag-of-words approaches; to perform parsing and reasoning across the spatial, temporal, and causal dimensions based on the joint S/T/C-AOG representation; and to show that deep joint parsing facilitates subsequent applications such as generating narrative text descriptions and answering queries in the forms of who, what, when, where, and why. The authors empirically evaluated the system based on comparison against ground-truth as well as accuracy of query answering and obtained satisfactory results.
The social complexities of user-centered design in ICTD: Experiences from four schools in India's villages and slums

Low levels of education remain a barrier to economic empowerment in the developing world. In our work on English language learning among underserved communities in India since 2004, we have observed differences between school communities in terms of their access to educational opportunities outside school, access to ICTs including cellphones and digital gaming, enthusiasm for visitors, and the relationships between students. We report on these observations and argue that they call for the greater use of a comparative approach in constructing models of the micro-cultures at various schools, so that user-centered design processes and methods can better account for the unique differences across communities.
Satellite Flatness based Fault Tolerant Control

Applying flat systems technique in attitude fault tolerant control of an under-actuated satellite has been investigated in this article. The main purpose of this study is development and implementation of a new idea in order to recovery of satellite stability and its acceptable performance in actuator fault scenarios. Solving the attitude fault tolerant control problem is based on consideration a realistic assumption which can show the ability of FTC system in managing the fault scenarios. Lose of effectiveness of actuators which could be caused in many of fault scenarios, modeled and simulated by multiplicative model. Thanks to provided new idea in this study it will be proven that, a wide range of actuator fault scenarios with different intense of faults could be managed without need to reconfiguring the main controller. Usage of this idea affects in reducing the volume of main controller computations and provides an appropriate base for its robust designing in other to dealing with systematically fault scenarios. Furthermore, the provided active fault tolerant attitude control scheme uses analytical redundancy system which could be considered as analytical observer. The suggested analytical observer by this technique, which belongs to nonlinear observer category, can observe all of the dynamic variables in allowable range of error. Practical implications of this study belong in this fact which analytical redundancy based on new idea in order to maintaining stability could be a perfect option in different fault scenarios such as systematically uncertainties and sensor faults. Hence this idea could be implemented without need to any physical instrument. General Terms Fault tolerant, flatness based control.
Confidence intervals for population attributable fractions using complex survey data

This paper describes an easy-to-implement method for producing confidence intervals (CIs) for population attributable fraction (PAF) statistics using survey data. The PAF is used by epidemiologists and policymakers to assess how much of the disease burden in a population could be reduced if the exposure to certain risk factors were eliminated. The PAF is defined as ( 1) / p rr rr − , where p denotes the proportion of cases exposed to a risk factor and rr denotes the model-based relative risk comparing the proportion of cases among the exposed group with the proportion of cases among the unexposed group. The rr is obtained by modeling the log of the prevalence of the disease as a linear function of covariates where exposure to the risk factor is included as one of the model covariates. The proposed methodology is based on the Taylor series linearization and properly accounts for survey design features in estimating the variances and covariances of the estimated quantities. The methodology is implemented using the VARGEN procedure of SUDAAN® version 11.0 software on 2013 Behavioral Risk Factor Surveillance System data to produce state-by-age group PAF estimates and CIs of hypertension with diabetes as the risk factor.
Dynamic bandwidth allocation for quality-of-service over Ethernet PONs

Ethernet-based passive optical network (EPON) technology is being considered as a promising solution for next-generation broadband access networks due to the convergence of low-cost Ethernet equipment and low-cost fiber infrastructures. A major feature for this new architecture is the use of a shared transmission media between all users; hence, medium access control arbitration mechanisms are essential for the successful implementation of EPON: i.e., to ensure a contention-free transmission and provide end users with equal access to the shared media. We propose to use the multipoint control protocol defined by the IEEE 802.3ah task force to arbitrate the transmission of different users, and we present different dynamic bandwidth allocation (DBA) algorithms to allocate bandwidths effectively and fairly between end users. These DBA algorithms are also augmented to support differentiated services, a crucial requirement for a converged broadband access network with heterogeneous traffic. We show that queueing delays under strict bandwidth allocation algorithms result in an unexpected behavior for certain traffic classes, and we suggest the use of DBA with appropriate local queue management to alleviate this inappropriate behavior. We conduct detailed simulation experiments to study the performance and validate the effectiveness of the proposed protocols.