Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct, Continuous Monitoring of Air Pollution by Transgenic Sensor Mice Responsive to Halogenated and Polycyclic Aromatic Hydrocarbons

Background The aryl hydrocarbon receptor (AhR, also called the dioxin receptor) plays crucial roles in toxicologic responses of animals to environmental pollutants, especially to halogenated and polycyclic aromatic hydrocarbons. To achieve direct, continuous risk assessment of air pollution using biological systems, we generated transgenic sensor mice that produce secreted alkaline phosphatase (SEAP) under the control of AhR. Methods To characterize responses of the mice to AhR agonists, sensor mice were orally administered 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), 3-methylcholanthrene (3MC), benzo[a]pyrene (B[a]P), or β-naphthoflavone (BNF), and serum levels of SEAP were evaluated. To monitor air pollution caused by cigarette smoke, we placed the mice each day in an experimental smoking room, and evaluated activity of serum SEAP for up to 4 days. Activation of AhR in individual organs was also examined by reverse transcription–polymerase chain reaction (RT-PCR) analysis of SEAP. Results In response to oral exposure to TCDD, sensor mice exhibited dramatic and sustained activation of AhR. The mice also responded sensitively to 3MC, B[a]P, and BNF. Activation of AhR was dose dependent, and the liver was identified as the main responding organ. After exposure to the smoking environment, sensor mice consistently exhibited transient, reversible activation of AhR. RT-PCR analysis of SEAP revealed that activation of AhR occurred predominantly in the lung. Conclusion We are the first laboratory to demonstrate successfully direct, comprehensive monitoring of air pollution using genetically engineered mammals. The established system would be useful for real risk assessment of halogenated and polycyclic aromatic hydrocarbons in the air, especially in smoking environments.
Attention and Visual Search: Active Robotic Vision Systems that Search

Visual attention is a multi-faceted phenomenon, playing different roles in different situations and for different processing mechanisms. Regardless, attention is a mechanism that optimizes the search processes inherent in vision. This perspective leads to a sound theoretical foundation for studies of attention in both machine and in the brain. The development of this foundation and the many ways in which attentive processes manifest themselves will be overviewed. One particular example of a practical robotic vision system that employs some of these attentive processes will be described. A difficult problem for robotic vision systems is visual search for a given target in an arbitrary 3D space. A solution to this problem will be described that optimizes the probability of finding the target given a fixed cost limit in terms of total number of robotic actions the robot requires to find its visual target. A robotic realization will be shown.
Evaluating the acceleration of typical scientific problems on the GPU

General-purpose computation on graphics processing units (GPGPU) has great potential to accelerate many scientific models and algorithms. However, some problems are considerably more difficult to accelerate than others, and it may be difficult for those new to GPGPU to ascertain the difficulty of accelerating a particular problem. Additionally, problems of different levels of difficulty require varying complexities of optimisations to achieve satisfactory results, and currently there is no clear separation between the different levels of known optimisations, which would be helpful to new users of GPGPU. Through what was learned in the acceleration of three problems, problem attributes have been identified to assist in evaluating the difficulty of accelerating a problem on a GPU. We envisage that with further development, these attributes could form the foundation of a difficulty classification system that could be used to determine whether GPU acceleration is practical for a candidate GPU acceleration problem, aid in identifying appropriate techniques and optimisations, and outline the required GPGPU knowledge.
Effect of forest bathing integrated with mindfulness-based stress reduction on immune cell populations and quality of life in breast cancer patients : a controlled pilot study

Department of Integrative Medicine, Korea University Hospital, 126-1 Anam-Dong, SungbukGu, Seoul, 136-705, Korea, Tel: 82-2-920-6637 Sam Medical Center, Anyang 5-Dong, Manan-Gu, Anyang, Gyeonggi-Do, Korea Department of Mind-Body Integration, Seoul University of Buddhism, 1038-2 Doksan-Dong, Geumcheon-Gu, Seoul, Korea Korea Forest Research Institute, 57 Hoegi-Ro, Dongdaemun-Gu, Seoul, Korea Korea Institute of Science and Technology, 39-1 Hawolgok-Dong, Sungbuk-Gu, Seoul, Korea
AN OLAM APPROACH TO ANALYZE E-COMMERCE CLICKSTREAMS

Clickstream analysis can reveal usage patterns on the company’s web site and give highly improved understanding of customer behavior. This understanding can then be utilized for improving customer satisfaction with the website and the company in general, yielding a great business advantage. Such summary information and rules have to be extracted from very large collections of clickstreams in web sites. This is challenging data mining, both in terms of the magnitude of data involved, and the need to incrementally adapt the mined patterns and rules as new data is collected. In this paper, we present some guidelines for implementing on-line analytical mining (OLAM) engines. In addition, we describe our e-Miner project called CubeMiner, which is an OLAM approach for analyzing clickstreams. Besides, we based our research on implementations that we consider efficient approaches on on-line analytical mining systems, such as DBMiner and WebLobMiner from Simon Fraser University (CA), and the OLAP-based Web Access Engine from HP Labs (USA). Moreover, our previous experience in clickstream analysis using datasets from KDDCup 2000 (focus on web mining tasks) is also discussed.
Three-dimensional versus two-dimensional laparoscopy in urology: A randomized study

Introduction: Conventional two-dimensional (2D) laparoscopy systems have the drawback of poor depth perception and spatial orientation. Three-dimensional (3D) laparoscopic systems have stereoscopic vision in which depth perception is achieved by different unique images received by each eye. We evaluated 3D laparoscopy in comparison with conventional 2D laparoscopy in urological procedures in a prospective randomized study. Materials and Methods: Over a 19 month study period, 108 patients scheduled to undergo various urological procedures were randomized to either conventional 2D or 3D laparoscopy (2D n = 53; 3D n = 55). A single senior surgeon performed all the surgeries. Parameters such as total operative time, dissection and suturing time, blood loss, hospital stay, complications (Clavien-Dindo), and visual analog scale (VAS) score for pain were assessed. The subjective assessment of the operating surgeon of superiority and inferiority of either technology on parameters defining surgical skills was recorded using a Likert scale. Results: The total operative time (P < 0.0003), blood loss (P < 0.028), dissection, suturing and stenting time (P < 0.0001), and the State-Trait Anxiety Inventory for Adults score (P < 0.0001) was significantly in favor of 3D laparoscopy. Post operative pain, hospital stay, and complications after surgery were similar in both groups. The subjective assessment of the operating surgeon also favored the 3D system. Conclusion: Our study showed significant advantages of the 3D system over 2D laparoscopy. These advantages include enhanced operative performance and greater surgeon comfort.
The Ins and Outs of Pipeline Coatings: Coatings Used to Protect Oil and Gas Pipelines

This article reviews the evolution of coatings for steel pipes from field applied asphalt and coal tar based materials to the currently used high tech, field and plant applied coatings. The coatings and linings reviewed are used to protect oil, gas, and liquid pipelines. The overview includes the following: polymeric tapes, heat shrinkable tape coatings, fusion bonded epoxy, two layer polyolefin coatings, three layer polyolefin coatings, coal tar enamel and asphalt coatings, spray applied liquid coatings, field joint coatings, internal diameter coatings, and concrete weight and barrier coatings.
Effect of Gamma Radiation on the Mechanical Properties of Urea-Treated Rice Straw Polypropylene Composites

Rice straw (RS) polypropylene (PP) composites were prepared in the different ratios of 10:90, 20:80, 30:70, 40:60 and 50:50 (RS wt% : PP wt%) by extrusion moulding and hot press compression technique and investigated the mechanical properties like tensile strength (TS), bending strength (BS), impact strength (IS) and elongations at break (Eb%) of the composites. RS was soaked in the different ratios of urea solution and it was observed that 1% urea-treated RS content composites exhibited better mechanical properties. Gamma-irradiated RSPP composites showed superior performance. Water uptake and degradation studies of composites were also monitored.
Implants in the posterior maxilla: a comparative clinical and radiologic study.

PURPOSE The aim of this study was to evaluate implants placed according to several methods of sinus floor augmentation. MATERIALS AND METHODS Forty-eight patients (median age of 62 years, range 23 to 89) had been treated at least 3 years prior to examination with screw-type implants in the posterior maxilla. Depending on the vertical dimension of the residual bone, 1 of 3 surgical procedures had been performed: sinus lift by lateral antrostomy (SL) in 13 patients; osteotome technique (OT) in 18 patients; standard implantation in 17 patients (control). In each patient 1 implant was randomly chosen for analysis (48 implants with a mean observation time of 4.6 +/- 1.4 years). Examination included probing pocket depth (PPD) measurement and radiographic examination. Radiographs were digitized to assess the marginal bone level. Differences between the groups were tested using analysis of variance, the Student t test and the Kruskal-Wallis test. RESULTS Mean PPD was 3.0 mm for the SL, 3.1 mm for OT, and 3.1 mm for control. The mean radiographic bone level was 1.53 mm for SL, 2.40 mm for OT, and 1.96 mm for control. No statistically significant differences were found between the groups for either of these parameters. DISCUSSION AND CONCLUSION Clinical examinations as well as radiographically stable bone levels indicated similar biomechanical conditions for prosthetic restorations when applying the 3 surgical procedures tested.
An information-theoretic approach to traffic matrix estimation

Traffic matrices are required inputs for many IP network management tasks: for instance, capacity planning, traffic engineering and network reliability analysis. However, it is difficult to measure these matrices directly, and so there has been recent interest in inferring traffic matrices from link measurements and other more easily measured data. Typically, this inference problem is ill-posed, as it involves significantly more unknowns than data. Experience in many scientific and engineering fields has shown that it is essential to approach such ill-posed problems via "regularization". This paper presents a new approach to traffic matrix estimation using a regularization based on "entropy penalization". Our solution chooses the traffic matrix consistent with the measured data that is information-theoretically closest to a model in which source/destination pairs are stochastically independent. We use fast algorithms based on modern convex optimization theory to solve for our traffic matrices. We evaluate the algorithm with real backbone traffic and routing data, and demonstrate that it is fast, accurate, robust, and flexible.
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels

Link prediction and clustering are key problems for network-structured data. While spectral clustering has strong theoretical guarantees under the popular stochastic blockmodel formulation of networks, it can be expensive for large graphs. On the other hand, the heuristic of predicting links to nodes that share the most common neighbors with the query node is much fast, and works very well in practice. We show theoretically that the common neighbors heuristic can extract clusters with high probability when the graph is dense enough, and can do so even in sparser graphs with the addition of a "cleaning" step. Empirical results on simulated and real-world data support our conclusions.
Distribution of interneurons in the CA2 region of the rat hippocampus

The CA2 region of the mammalian hippocampus is a unique region with its own distinctive properties, inputs and pathologies. Disruption of inhibitory circuits in this region appears to be linked with the pathology of specific psychiatric disorders, promoting interest in its local circuitry, its role in hippocampal function and its dysfunction in disease. In previous studies, CA2 interneurons, including a novel subclass of CA2 dendrite-preferring interneurons that has not been identified in other CA regions, have been shown to display physiological, synaptic and morphological properties unique to this sub-field and may therefore play a crucial role in the hippocampal circuitry. The distributions of immuno-labeled interneurons in dorsal CA2 were studied and compared with those of interneurons in CA1 and CA3. Like those in CA1 and CA3, the somata of CA2 parvalbumin-immunoperoxidase-labeled interneurons were located primarily in Stratum Pyramidale (SP) and Stratum Oriens (SO), with very few cells in Stratum Radiatum (SR) and none in Stratum Lacunosum Moleculare (SLM). There was, however, a greater proportion of GAD-positive cells were immunopositive for PV in SP in CA2 than in CA1 or CA3. CA2 SP also contained a larger density of somatostatin-, calbindin-, and VIP-immunopositive somata than CA1 and/or CA3. Like those in CA1 and CA3, CCK-immunopositive somata in CA2 were mostly located in SR. Reelin- and NPY- immunolabeled cell bodies were located in all layers of the three CA regions. However, a higher density of Reelin-positive somata was found in SP and SR of CA2 than in CA1 or CA3.
Towards automatic feature vector optimization for multimedia applications

We systematically evaluate a recently proposed method for unsupervised discrimination power analysis for feature selection and optimization in multimedia applications. A series of experiments using real and synthetic benchmark data is conducted, the results of which indicate the suitability of the method for unsupervised feature selection and optimization. We present an approach for generating synthetic feature spaces of varying discrimination power, modeling main characteristics from real world feature vector extractors. A simple, yet powerful visualization is used to communicate the results of the automatic analysis to the user.
A Heuristic Energy-Conserving Multicast Routing Protocol for Wireless Multihop Networks

How to provide low energy consumption and high packet delivery ratio are considered the major issues in the protocol design for the wireless multihop networks. The main focus of this paper is to reduce the number of data transmissions such that the energy consumption can be decreased. In the wired networks, the Steiner-Tree is regarded as an optimal approach to construct the multicast structure for specific senders and receivers. However, it is considered an NP-hard problem for achieving the minimum cost multicast tree under the wireless broadcast environment. In this paper, an energy-conserving multicast routing (ECMR) protocol is proposed as a heuristic scheme to reduce the number of relaying nodes for the construction of the multicast mesh. Moreover, the proposed algorithm is implemented on an ARM-based embedded platform for performance evaluation. Comparing with the existing multicast routing protocol, the experimental results show that the proposed ECMR scheme can provide better energy conservation while the packet delivery ratio is still preserved.
Enterprise frameworks for workflow management systems

This paper proposes an enterprise framework for workflow management (WFM) systems based on the Workflow Management Coalition generic architecture. In addition, it presents one smaller object‐oriented framework for task scheduling. This framework is obtained by refining one of the packages of the overall framework. The task scheduling framework was designed following the concept of model framework as in Catalysis. This sort of framework can be used as a template to generate code components within an application domain. According to this approach we can develop WFM components that can interoperate within a well‐defined enterprise framework. This paper also presents the process of developing interoperable code components from model frameworks. Copyright © 2002 John Wiley & Sons, Ltd.
A Version Management Framework for RDF Triple Stores

RDF is widely used as an ontology language for representing the metadata in Semantic Web, knowledge management system and E-commerce. Since ontologies model the knowledge in a particular domain, they may change over time. Furthermore, ontologies are usually developed and controlled in a distributed and collaborative way. Thus, it is very important to be able to manage multiple versions for RDF data. Earlier studies on RDF versions have focused on providing the accesses to different versions (i.e. snapshots) and computing the differences between those two versions. However, the existing approaches suffer from the space overhead for large scale data, since all snapshots should be redundantly kept in a repository. Moreover, it is very time consuming to compute the delta between two specific versions, which is very common in RDF applications. In this paper, we propose a framework for RDF version management in relational databases. It stores the original version and the deltas between two consecutive versions, thereby reducing the space requirement considerably. The other benefit of our approach is appropriate for change queries. On the flip side, in order to answer a query on a specific logical version, version should be constructed on the fly by applying the deltas between the original version and the logical version. This can slow down query performance. In order to overcome this, we propose a compression technique for deltas, called Aggregated Delta, to create a logical version directly rather than executing the sequence of deltas. An experimental study with real life RDF data sets shows our framework maintains multiple versions efficiently.
Modalities consensus for multi-modal constraint propagation

This paper presents a novel modalities consensus framework for multi-modal pairwise constraint propagation (MCP). We first combine multiple single-modal constraint propagation (SCP) problems together, and then explicitly introduce a new modalities consensus regularizer to force the propagation results on different modalities to be consistent with each other. With a separable consensus regularizer, the proposed approach can be effectively solved using an alternating optimization way. More importantly, based on our modalities consensus framework, two single-modal constraint propagation algorithms can be directly reformulated as two well-defined multi-modal solutions. Experimental results on constrained clustering tasks have shown that the proposed framework can achieve significant improvements with respect to the state of the arts.
Manifold reconstruction from point samples

We present an algorithm to "reconstruct" a smooth <i>k</i>-dimensional manifold <i>M</i> embedded in an Euclidean space R<sup>d</sup> from a "sufficiently dense" point sample from the manifold. The algorithm outputs a simplicial manifold that is homeomorphic and geometrically close to <i>M. </i> The running time is <i>O</i>(<i>n</i> log <i>n</i>) where <i>n</i> is the number of points in the sample (the multiplicative constant depends exponentially on the dimension though).
Reversible Watermarking Based On Histogram Shifting

In this paper, we propose a reversible watermarking algorithm where an original image can be recovered from the watermarked image. Most watermarking algorithms cause degradation of image quality in original digital contents in the process of embedding watermarks. In the proposed algorithm, the original image can be obtained when the degradation is removed from the watermarked image after extracting watermark information. In the proposed algorithm, we utilize a peak point of image histogram and the location map and modify pixel values slightly to embed data. Because the peak point of image histogram and the location map are employed in this algorithm, there is no need of extra information transmitted to the receiving side. As the locations watermark embedding are identified using the location map, the amount of watermark data can increase through recursive embedding.
Robust finite-time H∞ control for nonlinear system with parameter uncertainties and one-side Lipschitz via output feedback

This study investigates the problem of robust finite-time H∞ control for nonlinear system with parameter uncertainties and one-side Lipschitz via output feedback. The nonlinear function is considered to satisfy nonlinear condition. By means of Linear matrix inequality (LMI) techniques, design algorithms of static output feedback controller are developed. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results.
Clicky: User-centric Input for Active Spaces

We present a user-centric input system that is useful for a variety of applications in ubiquitous computing environments. Users in these environments currently switch between different keyboards and mice, or other devices, to interact with all the devices present. Allowing users to select a personal input device for the space and use it to interact with all the devices in the space is a more natural approach. Associating a user with an input device also serves to distinguish between the different users in a space, and creates the notion of a user session that is useful for applications like authenticating user actions on shared public displays or logging a particular user’s activities. Clicky is our prototype implementation of this idea. It allows a user with a single mouse and keyboard to control multiple computers and displays running standard operating systems in a smart-space environment. It is designed to be a light-weight middleware tool that does not require modifications to the base operating system. Any input device in the room, such as the keyboard and mouse on a personal laptop or handheld computer, can be used as a user’s input device to interact with the space. Clicky allows users to configure a set of displays in the space into a large “virtual display” and use a single mouse pointer to move across it. It also allows multiple users with their own input devices to share a public display. In this paper, we describe the motivation for a user-centric input system, and describe the current status of the implementation.
Adapting a Lexicalized-Grammar Parser to Contrasting Domains

Most state-of-the-art wide-coverage parsers are trained on newspaper text and suffer a loss of accuracy in other domains, making parser adaptation a pressing issue. In this paper we demonstrate that a CCG parser can be adapted to two new domains, biomedical text and questions for a QA system, by using manually-annotated training data at the pos and lexical category levels only. This approach achieves parser accuracy comparable to that on newspaper data without the need for annotated parse trees in the new domain. We find that retraining at the lexical category level yields a larger performance increase for questions than for biomedical text and analyze the two datasets to investigate why different domains might behave differently for parser adaptation.