nils-herrmann/clean_scirepeval huggingface dataset:
DL-Lite Ontology Revision Based on An Alternative Semantic Characterization

Ontology engineering and maintenance require (semi-)automated ontology change operations. Intensive research has been conducted on TBox and ABox changes in description logics (DLs), and various change operators have been proposed in the literature. Existing operators largely fall into two categories: syntax-based and model-based. While each approach has its advantages and disadvantages, an important topic that has rarely been explored is how to achieve a balance between syntax-based and model-based approaches. Also, most existing operators are specially designed for either TBox change or ABox change, and cannot handle the general ontology revision task—given a DL knowledge base (KB, a pair consisting of a TBox and an ABox), how to revise it by a set of TBox and ABox axioms (i.e., a new DL KB). In this article, we introduce an alternative structure for DL-Lite, called a featured interpretation, and show that featured models provide a finite and tight characterization to the classical semantics of DL-Lite. A key issue for defining a change operator is the so-called expressibility, that is, whether a set of models (or featured models here) is axiomatizable in DLs. It is indeed much easier to obtain expressibility results for featured models than for classical DL models. As a result, the new semantics determined by featured models provides a method for defining and studying various changes of DL-Lite KBs that involve both TBoxes and ABoxes. To demonstrate the usefulness of the new semantic characterization in ontology change, we define two revision operators for DL-Lite KBs using featured models and study their properties. In particular, we show that our two operators both satisfy AGM postulates. We show that the complexity of our revisions is ΠP2-complete, that is, on the same level as major revision operators in propositional logic, which further justifies the feasibility of our revision approach for DL-Lite. Also, we develop algorithms for these DL-Lite revisions.
Trace Alignment in Process Mining: Opportunities for Process Diagnostics

Process mining techniques attempt to extract non-trivial knowledge and interesting insights from event logs. Process mining provides a welcome extension of the repertoire of business process analysis techniques and has been adopted in various commercial BPM systems (BPM|one, Futura Reflect, ARIS PPM, Fujitsu, etc.). Unfortunately, traditional process discovery algorithms have problems dealing with lessstructured processes. The resulting models are difficult to comprehend or even misleading. Therefore, we propose a new approach based on trace alignment. The goal is to align traces in a way that event logs can be explored easily. Trace alignment can be used in a preprocessing phase where the event log is investigated or filtered and in later phases where detailed questions need to be answered. Hence, it complements existing process mining techniques focusing on discovery and conformance checking.
CATENARY CURVE FITTING FOR GEOMETRIC CALIBRATION

In modern road surveys, hanging power cables are among the most commonly-found geometric features. These cables are catenary curves that are conventionally modelled with three parameters in 2D Cartesian space. With the advent and popularity of the mobile mapping system (MMS), the 3D point clouds of hanging power cables can be captured within a short period of time. These point clouds, similarly to those of planar features, can be used for feature-based self-calibration of the system assembly errors of an MMS. However, to achieve this, a well-defined 3D equation for the catenary curve is needed. This paper proposes three 3D catenary curve models, each having different parameters. The models are examined by least squares fitting of simulated data and real data captured with an MMS. The outcome of the fitting is investigated in terms of the residuals and correlation matrices. Among the proposed models, one of them could estimate the parameters accurately and without any extreme correlation between the variables. This model can also be applied to those transmission lines captured by airborne laser scanning or any other hanging cable-like objects.
Open Social Student Modeling for Personalized Learning

Open student modeling (OSM) is an approach to technology-based learning, which makes student models available to the learners for exploration. OSM is known for its ability to increase student engagement, motivation, and knowledge reflection. A recent extension of OSM known as open social student modeling (OSSM) complements cognitive aspects of OSM with social aspects by allowing students to explore models of peer students and/or an aggregated class model. In this paper, we introduce an OSSM interface, MasteryGrids, and report the results of a large-scale classroom study, which explored the impact of the social dimension of OSSM. Students in a database management course accessed nonrequired learning materials (examples and problems) via the MasteryGrids interface using either OSM or OSSM. The results revealed that OSSM-enhanced learning, especially for students with lower prior knowledge, compared with OSM. It also enhanced user attitude and engagement. Amount of student usage, efficiency of student usage, and student attitude varied depending on the combination of interface condition (OSM/OSSM), gender, and student social comparison orientation.
Complex-Valued Neural Networks: Advances and Applications [Book Review]

This book contains a wide variety of hot topics on advanced computational intelligence methods which incorporate the concept of complex and hypercomplex number systems into the framework of artificial neural networks. In most chapters, the theoretical descriptions of the methodology and its applications to engineering problems are excellently balanced. This book suggests that a better information processing method could be brought about by selecting a more appropriate information representation scheme for specific problems, not only in artificial neural networks but also in other computational intelligence frameworks. The advantages of CVNNs and hypercomplex-valued neural networks over real-valued neural networks are confirmed in some case studies but still unclear in general. Hence, there is a need to further explore the difference between them from the viewpoint of nonlinear dynamical systems. Nevertheless, it seems that the applications of CVNNs and hypercomplex-valued neural networks are very promising.
Teaching Text and Context Through Multimedia.

The use of multimedia technology to teach language in its authentic cultural context represents a double challenge for language learners and teachers. On the one hand, the computer gives learners access to authentic video footage and other cultural materials that can help them get a sense of the sociocultural context in which the language is used. On the other hand, CD-ROM multimedia textualizes this context in ways that need to be "read" and interpreted. Learners are thus faced with the double task of (a) observing and choosing culturally relevant features of the context and (b) putting linguistic features in relation to other features to arrive at some understanding of language in use. This paper analyzes the interaction of text and context in a multimedia Quechua language program, and makes suggestions for teaching foreign languages through multimedia technology.
Impact of Soil Salinity on the Relation Between Soil Moisture and Dielectric Permittivity

Soil complex dielectric permittivity spectrum depends mainly on soil volumetric water content and salinity, but other soil properties such as temperature, density and clay content can also significantly impact its dielectric properties. Especially, the influence of soil salinity and texture can have significant impact on the accuracy of moisture determination with the use of soil moisture-dielectric permittivity calibration curves. The paper deals with the impact of soil salinity on the real part of complex dielectric permittivity of soils of various texture. Soil samples of various moisture content and salinity were measured with the use of a coaxial transmission-line cell connected to a one-port vector-network-analyzer in the 0.01–3 GHz frequency range. The relations between soil moisture and the real part of dielectric permittivity at frequencies of 30, 70, 150, 200, 500 and 1000 MHz were examined and the frequency bands with the smallest impact of soil salinity and particle-size distribution were obtained. For the tested soils it occurred that the optimal frequency bands were located between 150 and 500 MHz.
MRI anatomy of parametrial extension to better identify local pathways of disease spread in cervical cancer.

This paper highlights an updated anatomy of parametrial extension with emphasis on magnetic resonance imaging (MRI) assessment of disease spread in the parametrium in patients with locally advanced cervical cancer. Pelvic landmarks were identified to assess the anterior and posterior extensions of the parametria, besides the lateral extension, as defined in a previous anatomical study. A series of schematic drawings and MRI images are shown to document the anatomical delineation of disease on MRI, which is crucial not only for correct image-based three-dimensional radiotherapy but also for the surgical oncologist, since neoadjuvant chemoradiotherapy followed by radical surgery is emerging in Europe as a valid alternative to standard chemoradiation.
Interactive Creation of Virtual Worlds Using Procedural Sketching

Procedural modelling is an attractive alternative to cut down the costs of manual content creation for virtual worlds. We discuss our declarative modelling approach to the creation of 3D virtual worlds, which integrates a variety of procedural techniques in order to enable a non-specialist user to interactively create a complete 3D virtual world in minutes. In particular, we introduce procedural sketching, a novel paradigm which allows designers to quickly specify and see the effects of their procedural modelling operations, and describe its main features as implemented in our prototype system SketchaWorld. Two main interaction modes are described, for specifying the landscape and terrain features, respectively. Our approach automatically fits all generated terrain features with their surroundings, for example by smoothing out rough terrain for roads, or creating a bridge to cross a river. It is concluded that this approach provides designers with the productivity gain of procedural methods, while still allowing for fine user control and actively supporting iterative modelling.
Signs in chest imaging.

A radiological sign can sometimes resemble a particular object or pattern and is often highly suggestive of a group of similar pathologies. Awareness of such similarities can shorten the differential diagnosis list. Many such signs have been described for X-ray and computed tomography (CT) images. In this article, we present the most frequently encountered plain film and CT signs in chest imaging. These signs include for plain films the air bronchogram sign, silhouette sign, deep sulcus sign, Continuous diaphragm sign, air crescent ("meniscus") sign, Golden S sign, cervicothoracic sign, Luftsichel sign, scimitar sign, doughnut sign, Hampton hump sign, Westermark sign, and juxtaphrenic peak sign, and for CT the gloved finger sign, CT halo sign, signet ring sign, comet tail sign, CT angiogram sign, crazy paving pattern, tree-in-bud sign, feeding vessel sign, split pleura sign, and reversed halo sign.
Provision of positive and negative selections in retroviral vectors containing the cytosine deaminase gene

The E. coli cytosine deaminase (CD) provides a negative selection system for suicide gene therapy as CD transfectants are eliminated following 5-fluorocytosine (5FC) treatment. Here we report a positive selection system for the CD gene using 5-fluorouracil (5FU) and cytosine in selection medium to screen for CD-positive transfectants. It is based on the relief of 5FU toxicity by uracil which is converted from cytosine via CD catalysis, as uracil competes with the toxic 5FU in subsequent pyrimidine metabolism. Hence, a retroviral vector containing the CD gene may pro- vide both positive and negative selections after gene transfer. The CD transfectants selected with the positive selection system showed susceptibility to 5FC in subsequent negative selection in vitro and in vivo. Therefore, this dual selection system is useful not only for combination therapy with transgene and CD gene, but can also act to eliminate selectively transduced cells after the transgene has furnished its effects or upon undesired conditions if 5FC is applied for negative selection in vivo.
Modeling, design, and fabrication of ultra-high bandwidth 3D Glass Photonics (3DGP) in glass interposers

This paper presents, for the first time, the 3D Glass Photonics (3DGP) technology being developed by Georgia Tech, based on ultra-thin 3D glass interposer . The 3DGP system integrates both optical and electrical interconnects in the same glass substrate using photo-sensitive polymer core, and polymer cladding within an ultra-thin glass substrate. The 3DGP processes are demonstrated using 180 & 100 um thick glass substrates with 30 um diameter via and 8 um wide waveguide structures. The optical vias are used as mode transformer and high-tolerance coupler between fibers and chips. Finite-difference analysis is performed to determine the alignment tolerances of such vias.
A Reformed K-Nearest Neighbors Algorithm for Big Data Sets

Vo Ngoc Phu Nguyen Tat Thanh University, 300A Nguyen Tat Thanh Street, Ward 13, District 4, Ho Chi Minh City, 702000, Vietnam Email: vongocphu03hca@gmail.com vongocphu@ntt.edu.vn  A Data Mining Has Already Had Many Algorithms Which A KNearest Neighbors Algorithm, K-NN, Is A Famous Algorithm For Researchers. K-NN Is Very Effective On Small Data Sets, However It Takes A Lot Of Time To Run On Big Datasets. Today, Data Sets Often Have Millions Of Data Records, Hence, It Is Difficult To Implement K-NN On Big Data. In This Research, We Propose An Improvement To K-NN To Process Big Datasets In A Shortened Execution Time. The Reformed KNearest Neighbors Algorithm (R-K-NN) Can Be Implemented On Large Datasets With Millions Or Even Billions Of Data Records. R-K-NN Is Tested On A Data Set With 500,000 Records. The Execution Time Of R-KNN Is Much Shorter Than That Of K-NN. In Addition, R-K-NN Is Implemented In A Parallel Network System With Hadoop Map (M) And Hadoop Reduce (R).
p21 in cancer: intricate networks and multiple activities

One of the main engines that drives cellular transformation is the loss of proper control of the mammalian cell cycle. The cyclin-dependent kinase inhibitor p21 (also known as p21WAF1/Cip1) promotes cell cycle arrest in response to many stimuli. It is well positioned to function as both a sensor and an effector of multiple anti-proliferative signals. This Review focuses on recent advances in our understanding of the regulation of p21 and its biological functions with emphasis on its p53-independent tumour suppressor activities and paradoxical tumour-promoting activities, and their implications in cancer.
Video processing techniques for traffic flow monitoring: A survey

Video-based traffic flow monitoring is a fast emerging field based on the continuous development of computer vision. A survey of the state-of-the-art video processing techniques in traffic flow monitoring is presented in this paper. Firstly, vehicle detection is the first step of video processing and detection methods are classified into background modeling based methods and non-background modeling based methods. In particular, nighttime detection is more challenging due to bad illumination and sensitivity to light. Then tracking techniques, including 3D model-based, region-based, active contour-based and feature-based tracking, are presented. A variety of algorithms including MeanShift algorithm, Kalman Filter and Particle Filter are applied in tracking process. In addition, shadow detection and vehicles occlusion bring much trouble into vehicle detection, tracking and so on. Based on the aforementioned video processing techniques, discussion on behavior understanding including traffic incident detection is carried out. Finally, key challenges in traffic flow monitoring are discussed.
Myocardial damage in dogs affected by heartworm disease (Dirofilaria immitis): immunohistochemical study of cardiac myoglobin and troponin I in naturally infected dogs.

It has recently been reported that dogs affected by canine heartworm disease (Dirofilaria immitis) can show an increase in plasma levels of myoglobin and cardiac troponin I, two markers of muscle/myocardial injury. In order to determine if this increase is due to myocardial damage, the right ventricle of 24 naturally infected dogs was examined by routine histology and immunohistochemistry with anti-myoglobin and anti-cardiac troponin I antibodies. Microscopic lesions included necrosis and myocyte vacuolization, and were associated with loss of staining for one or both proteins. Results confirm that increased levels of myoglobin and cardiac troponin I are indicative of myocardial damage in dogs affected by heartworm disease.
Refining the Nasal Dorsum with Free Diced Cartilage.

Refining the nasal dorsum has become a major challenge in modern rhinoplasty as irregularities of the nasal dorsum account for a significant number of revision surgeries. In our department, free diced cartilage is now routinely applied for smoothening of the nasal dorsum. In this retrospective study, the outcomes with regard to irregularities or contour deficits of the nasal dorsum of 431 rhinoplasty cases operated by a single surgeon between July 2013 and June 2015, using free diced cartilage, are compared with 327 cases operated by the same surgeon between January 2007 and December 2008, before the introduction of the free diced cartilage technique. A decrease in early revision surgeries (i.e., revision within the 2-year period evaluated) due to dorsal irregularities or contour deficits is seen. Being a quick, easy, and highly cost-effective procedure, we feel that free diced cartilage is currently the ideal technique for refinements of the nasal dorsum.
Cloud Computing Pricing Models : A Survey

Cloud computing is emerging as a promising field offering a variety of computing services to end users. These services are offered at different prices using various pricing schemes and techniques. End users will favor the service provider offering the best QoS with the lowest price. Therefore, applying a fair pricing model will attract more customers and achieve higher revenues for service providers. This work focuses on comparing many employed and proposed pricing models techniques and highlights the pros and cons of each. The comparison is based on many aspects such as fairness, pricing approach, and utilization period. Such an approach provides a solid ground for designing better models in the future. We have found that most approaches are theoretical and not implemented in the real market, although their simulation results are very promising. Moreover, most of these approaches are biased toward the service provider.
Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring

The real-time monitoring of human movement can provide valuable information regarding an individual's degree of functional ability and general level of activity. This paper presents the implementation of a real-time classification system for the types of human movement associated with the data acquired from a single, waist-mounted triaxial accelerometer unit. The major advance proposed by the system is to perform the vast majority of signal processing onboard the wearable unit using embedded intelligence. In this way, the system distinguishes between periods of activity and rest, recognizes the postural orientation of the wearer, detects events such as walking and falls, and provides an estimation of metabolic energy expenditure. A laboratory-based trial involving six subjects was undertaken, with results indicating an overall accuracy of 90.8% across a series of 12 tasks (283 tests) involving a variety of movements related to normal daily activities. Distinction between activity and rest was performed without error; recognition of postural orientation was carried out with 94.1% accuracy, classification of walking was achieved with less certainty (83.3% accuracy), and detection of possible falls was made with 95.6% accuracy. Results demonstrate the feasibility of implementing an accelerometry-based, real-time movement classifier using embedded intelligence
Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues.

Advances in the application of electron microscopy (EM) to serial imaging are opening doors to new ways of analyzing cellular structure. New and improved algorithms and workflows for manual and semiautomated segmentation allow us to observe the spatial arrangement of the smallest cellular features with unprecedented detail in full three-dimensions. From larger samples, higher complexity models can be generated; however, they pose new challenges to data management and analysis. Here we review some currently available solutions and present our approach in detail. We use the fully immersive virtual reality (VR) environment CAVE (cave automatic virtual environment), a room in which we are able to project a cellular reconstruction and visualize in 3D, to step into a world created with Blender, a free, fully customizable 3D modeling software with NeuroMorph plug-ins for visualization and analysis of EM preparations of brain tissue. Our workflow allows for full and fast reconstructions of volumes of brain neuropil using ilastik, a software tool for semiautomated segmentation of EM stacks. With this visualization environment, we can walk into the model containing neuronal and astrocytic processes to study the spatial distribution of glycogen granules, a major energy source that is selectively stored in astrocytes. The use of CAVE was key to the observation of a nonrandom distribution of glycogen, and led us to develop tools to quantitatively analyze glycogen clustering and proximity to other subcellular features.  2016.
Miniaturized microstrip slotted holy shaped patch structure for high frequency applications

The three stage design of a microstrip slotted holy shaped patch structure intended to serve high frequency applications in the frequency range between 19.52 GHz to 31.5 GHz is proposed in this paper. The geometrical stages use FR4 epoxy substrate with small dimensions of 10 mm × 8.7 mm × 1.6 mm and employ coaxial feeding technique. An analysis of the three design stages has been done over HFSS-15to obtain the corresponding reflection coefficient, bandwidth, radiation pattern, gain and VSWR. The graphical as well as tabulated comparison of the standard parameters has been included in the results section.