Miracle-dz/UniFAR-FTUs huggingface dataset:
Multipath Routing Protocol Based on Congestion Control Mechanism Implemented by Cross-Layer Design Concept for WSN

To solve the problem of congestion which often occurs in the process of the large data transmission in largescale wireless senator networks, a multipath routing protocol based on congestion control mechanism implemented by crosslayer design concept is proposed. Realizing the multipath routing protocol on the basis of AODV protocol, congestion control mechanism with active congestion avoidance, real-time detection and alleviative congestion is implemented by applying interaction information of cross-layer design between MAC layer and Routing layer. The simulation results show that the proposed multipath routing protocol with congestion control mechanism has some advantages in packet delivery ratio, end-to-end delay and normalized overheads. The proposed protocol can ensure the reliability and validity of service, and save energy consumption to prolong the working lifetime of wireless sensor networks. Keywords-Wireless Sensor Networks; multipath routing protocol; cross-layer design; congestion control
Matching with Contracts

We develop a model of matching with contracts which incorporates, as special cases, the college admissions problem, the Kelso-Crawford labor market matching model, and ascending package auctions. We introduce a new "law of aggregate demand" for the case of discrete heterogeneous workers and show that, when workers are substitutes, this law is satisfied by profit-maximizing firms. When workers are substitutes and the law is satisfied, truthful reporting is a dominant strategy for workers in a worker-offering auction/matching algorithm. We also parameterize a large class of preferences satisfying the two conditions.
Role of inflammation in oral carcinogenesis (Part II): CD8, FOXP3, TNF-α, TGF-β and NF-κB expression

Due to the frequent presence of inflammation in cases of carcinoma and its use as a parameter for the assessment of tumor aggressiveness, the role of inflammation in oral carcinogenesis was investigated. This was performed by evaluating the expression of cellular markers, cytokines and nuclear transcription factors that identify the cells that participate in the antitumor defense in cases of oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC). A semi-quantitative immunohistochemical analysis was performed for the transcription factors cluster of differentiation 8 (CD8), forkhead box P3 (FOXP3), transforming growth factor (TGF)-β, tumor necrosis factor (TNF)-α and nuclear factor κ-light chain enhancer of activated B-cells (NF-κB), in cases of OED and OSCC. CD8, TGF-β, TNF-α and NF-κB participated in the processes of tumor transformation and progression. The presence of inflammatory infiltrate in cases of OED favors the transformation and invasion process when stromal TNF-α and NF-kB are overexpressed, as NF-kB activated by TNF-α during inflammation predisposes the lesion to transformation, functioning as a link between inflammation and cancer. The control of these inflammatory mediators may prevent malignant transformation in the oral cavity.
End User Creativity: A Critical Realist Perspective

There has been a recent trend in the IS literature toward viewing IT systems less as material artifacts and more as imbricated, socio-technical assemblages. This suggests that greater attention must be paid to the detailed processes behind the interaction of users with systems. In this thesis, I explored the creative process that occurs when end users discover or develop novel and useful ways to appropriate IT systems. I used Eisenhardt (1989)’s framework for inducting theory from case studies, and conducted an embedded multiple-case study of users who have implemented creative ways to apply existing IT systems. I applied Critical Realist assumptions and employed theoretical lenses drawn from cognitive science (distributed cognition), cognitive psychology (dual-process theory) and Markus and Silver (2008)’s variant of Adaptive Structuration Theory (AST). I addressed the research question: What are the causal mechanisms that explain the creative appropriation of IT systems by end users? Using AST as a foundation, I developed a theoretical framework to represent the problem space that must be traversed by users making appropriation moves, which I have named Affordance Field Theory. I employed Narrative Networks (Pentland & Feldman, 2007) for my primary retroductive analysis, then re-analysed the data using Framework Matrices (Ritchie & Lewis, 2003). The complementary logical forms (processual and thematic, respectively) of the analytical tools provide empirical corroboration for the findings. I have derived a set of cognitive mechanisms that describe the information-processing operations involved in end user creativity. Using metaphors provided by distributed cognition, I have demonstrated how these mechanisms can be used to explain information processing at both the individual and collective levels. I have also developed an integrative model to explain how the mechanisms work together to explain creative action at the individual level. I have maintained my primary case study database in NVivo 10.
Using optical flow for the detection of floating mines in IR image sequences

In the first Gulf War, unmoored floating mines proved to be a real hazard for shipping traffic. An automated system capable of detecting these and other free-floating small objects, using readily available sensors such as infra-red cameras, would prove to be a valuable mine-warfare asset, and could double as a collision avoidance mechanism, and a search-and-rescue aid. The noisy background provided by the sea surface, and occlusion by waves make it difficult to detect small floating objects using only algorithms based upon the intensity, size or shape of the target. This leads us to look at the sequence of images for temporal detection characteristics. The target's apparent motion is such a determinant, given the contrast between the bobbing motion of the floating object and the strong horizontal component present in the propagation of the wavefronts. We have applied the Proesmans optical flow algorithm to IR video footage of practice mines, in order to extract the motion characteristic and a threshold on the vertical motion characteristic is then imposed to detect the floating targets.
Co-parent selection for fast region merging in pyramidal image segmentation

The goal of image segmentation is to partition an image into regions that are internally homogeneous and heterogeneous with respect to other neighbouring regions. We build on the pyramid image segmentation work proposed by [3] and [9] by making a more efficient method by which children chose parents within the pyramid structure. Instead of considering only four immediate parents as in [3], in [9] each child node considers the neighbours of its candidate parent, and the candidate parents of its neighbouring nodes in the same level. In this paper, we also introduce the concept of a co-parent node for possible region merging at the end of each iteration. The new parents of the former children are co-parent candidates as if they are similar. The co-parent is chosen to be the one with the largest receptive field among candidate co-parents. Each child then additionally considers one more candidate, the co-parent of the previous parent. Other steps in the algorithm, and its overall layout, were also improved. The new algorithm is tested on a set of images. Our algorithm is fast (produces segmentations within seconds), results in the correct segmentation of elongated and large regions, very simple compared to plethora of existing algorithms, and appears competitive in segmentation quality with the best publicly available implementations. The major improvement over [9] is that it produces visually appealing results at earlier levels of pyramid segmentation, and not only at the top one.
Cross-Lingual Identification of Ambiguous Discourse Connectives for Resource-Poor Language

The lack of annotated corpora brings limitations in research of discourse classification for many languages. In this paper, we present the first effort towards recognizing ambiguities of discourse connectives, which is fundamental to discourse classification for resource-poor language such as Chinese. A language independent framework is proposed utilizing bilingual dictionaries, Penn Discourse Treebank and parallel data between English and Chinese. We start from translating the English connectives to Chinese using a bi-lingual dictionary. Then, the ambiguities in terms of senses a connective may signal are estimated based on the ambiguities of English connectives and word alignment information. Finally, the ambiguity between discourse usage and non-discourse usage were disambiguated using the co-training algorithm. Experimental results showed the proposed method not only built a high quality connective lexicon for Chinese but also achieved a high performance in recognizing the ambiguities. We also present a discourse corpus for Chinese which will soon become the first Chinese discourse corpus publicly available.
Modified Vaccinia Virus Ankara Triggers Type I IFN Production in Murine Conventional Dendritic Cells via a cGAS/STING-Mediated Cytosolic DNA-Sensing Pathway

Modified vaccinia virus Ankara (MVA) is an attenuated poxvirus that has been engineered as a vaccine against infectious agents and cancers. Our goal is to understand how MVA modulates innate immunity in dendritic cells (DCs), which can provide insights to vaccine design. In this study, using murine bone marrow-derived dendritic cells, we assessed type I interferon (IFN) gene induction and protein secretion in response to MVA infection. We report that MVA infection elicits the production of type I IFN in murine conventional dendritic cells (cDCs), but not in plasmacytoid dendritic cells (pDCs). Transcription factors IRF3 (IFN regulatory factor 3) and IRF7, and the positive feedback loop mediated by IFNAR1 (IFN alpha/beta receptor 1), are required for the induction. MVA induction of type I IFN is fully dependent on STING (stimulator of IFN genes) and the newly discovered cytosolic DNA sensor cGAS (cyclic guanosine monophosphate-adenosine monophosphate synthase). MVA infection of cDCs triggers phosphorylation of TBK1 (Tank-binding kinase 1) and IRF3, which is abolished in the absence of cGAS and STING. Furthermore, intravenous delivery of MVA induces type I IFN in wild-type mice, but not in mice lacking STING or IRF3. Treatment of cDCs with inhibitors of endosomal and lysosomal acidification or the lysosomal enzyme Cathepsin B attenuated MVA-induced type I IFN production, indicating that lysosomal enzymatic processing of virions is important for MVA sensing. Taken together, our results demonstrate a critical role of the cGAS/STING-mediated cytosolic DNA-sensing pathway for type I IFN induction in cDCs by MVA. We present evidence that vaccinia virulence factors E3 and N1 inhibit the activation of IRF3 and the induction of IFNB gene in MVA-infected cDCs.
A Proposed framework for improved identification of implicit aspects in tourism domain using supervised learning technique

The sudden boom of e-commerce web sites, has paved a way for users to write different reviews about an entity on these sites. This large amount of data must be extracted for analyzing the opinion to perform better by taking optimized decisions in different streams. In this paper, we have proposed an explicit and implicit aspect opinion mining framework and algorithm for the tourism domain. It first determines the explicit aspects using the frequent nouns. It, then extracts the implicit aspects using implicit aspect recognizer which is deployed using a supervised machine learning technique i.e. CRF. The trained CRF file will be used for recognizing the implicit aspects indicator in the tourism domain. The proposed algorithm has been validated empirically by showing the extracted implicit and explicit aspects.
Texture Tiling on 3D Models Using Automatic Polycube-maps and Wang Tiles

In mapping textures onto 3D models, it is essential to eliminate all seams and avoid excessive distortions. To achieve these goals, texture tiling provides an alternative approach for texturing surfaces. In this paper, a texture tiling approach that combines poly-cube-maps and Wang tiles for 3D models is proposed. The poly-cube of a 3D model is first constructed automatically and a tiling mechanism is then used to fill the tiles on the polycube. Finally, rectangular cells which are transformed from the polycube are generated and textures are mapped onto the 3D model. The results show that the proposed approach leads to seamless texture mapping on 3D models.
Evaluating shape and appearance descriptors for 3D human pose estimation

In this paper, we present a comparative evaluation of several appearance and shape descriptors in the context of 3D human pose estimation. Among the shape descriptors, we evaluate the Discrete Cosine Transform (DCT) and the Histogram of Shape Context (HoSC) descriptors. The five appearance descriptors that we evaluate are all variants of the Histogram of Oriented Gradients (HOG) descriptor. We evaluate these descriptors quantitatively using the HumanEva-I dataset. We report the performance of the descriptors using the Relevance Vector Machine (RVM) regression and K-nearest neighbor (KNN) regression methods. We found that the appearance descriptor computed at multiple spatial regions gave the best performance when RVM regression was used for pose estimation. The DCT descriptor performed the best when KNN regression was used for pose estimation.
Age-Friendly Environments and Self-Rated Health:

While a number of organizations and government entities have encouraged the development of more “age-friendly” environments, to date there has been limited research linking these environment features to elder outcomes. Using a representative sample of older adults living in Detroit, this study examined the association between age-friendly environment factors and self-rated health. Results indicated that access to health care, social support, and community engagement were each associated with better self-rated health, while neighborhood problems were associated with poorer self-rated health. Moreover, individual-level income and education no longer predicted self-rated health once age-friendly environment factors were taken into account. These findings highlight the need for more research documenting the effects of age-friendly environments, particularly across diverse contexts and populations.
What can (partition) logic contribute to information theory

Logical probability theory was developed as a quantitative measure based on Boole's logic of subsets. But information theory was developed into a mature theory by Claude Shannon with no such connection to logic. A recent development in logic changes this situation. In category theory, the notion of a subset is dual to the notion of a quotient set or partition, and recently the logic of partitions has been developed in a parallel relationship to the Boolean logic of subsets (subset logic is usually mis-specified as the special case of propositional logic). What then is the quantitative measure based on partition logic in the same sense that logical probability theory is based on subset logic? It is a measure of information that is named "logical entropy" in view of that logical basis. This paper develops the notion of logical entropy and the basic notions of the resulting logical information theory. Then an extensive comparison is made with the corresponding notions based on Shannon entropy.
Identifying criteria for multimodel software process improvement solutions – based on a review of current problems and initiatives

In this article, we analyze current initiatives in multimodel software process improvement and identify criteria for multimodel solutions. With multimodel, we mean the simultaneous usage of more than one quality approach (e.g. standards, methods, techniques to improve software processes). This paper discusses first the current problems regarding the use of multiple software quality approaches. Subsequently, multimodel initiatives are categorized into three different groups, respectively: quality approach harmonization, quality approach integration, and quality approach mapping. Based on an analysis of the strengths and weaknesses of current multimodel initiatives in these three classes, we derive a set of criteria, which can provide a basis for multimodel software process improvement solutions. Copyright © 2011 John Wiley & Sons, Ltd.
Suture Bridge Fixation Technique for Posterior Cruciate Ligament Avulsion Fracture

We presented a surgical technique including a suture bridge technique with relatively small incision for the reduction and fixation of posterior ligament avulsion fractures. A suture anchor was used to hold the avulsed fragment and a knotless anchor was used to continuously compress the bony fragment into the fracture site, thereby maintaining reduction during healing.
Literature-Related Discovery: A Review

Abstract : Discovery in science is the generation of novel, interesting, plausible, and intelligible knowledge about the objects of study. Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked to produce novel interesting, plausible, and intelligible knowledge (i.e., potential discovery). Two major variants of LRD are open discovery systems (ODS), where one starts with a problem and generates a potential solution (or vice versa), and closed discovery systems (CDS), where one starts with a problem and a potential solution and generates linking mechanisms. This report reviews the state-of-the-art in ODS LRD only. It examines the major LRD concepts, evaluates each concept in detail from the perspective of discovery capability, and examines the level of potential "discovery" reported in the literature from each concept's implementation. In the evaluation of potential discovery claimed in the published literature, a vetting process is used that requires that both characteristics of ODS LRD are present for potential discovery to be affirmed: concepts are linked that have not been linked previously, and novel, interesting, plausible, and intelligible knowledge is produced. The major conclusions are that, until recently, most of the reported ODS LRD techniques had not generated discovery, and this lack of discovery had hampered the growth of ODS LRD substantially. However, ODS LRD techniques have been developed that allow significantly greater amounts of potential discovery to be generated systematically.
S+EPPs: Construct and Explore Bisimulation Summaries, plus Optimize Navigational Queries; all on Existing SPARQL Systems

We demonstrate S+EPPs, a system that provides fast construction of bisimulation summaries using graph analytics platforms, and then enhances existing SPARQL engines to support summary-based exploration and navigational query optimization. The construction component adds a novel optimization to a parallel bisimulation algorithm implemented on a multi-core graph processing framework. We show that for several large, disk resident, real world graphs, full summary construction can be completed in roughly the same time as the data load. The query translation component supports Extended Property Paths (EPPs), an enhancement of SPARQL 1.1 property paths that can express a significantly larger class of navigational queries. EPPs are implemented via rewritings into a widely used SPARQL subset. The optimization component can (transparently to users) translate EPPs defined on instance graphs into EPPs that take advantage of bisimulation summaries. S+EPPs combines the query and optimization translations to enable summary-based optimization of graph traversal queries on top of off-the-shelf SPARQL processors. The demonstration showcases the construction of bisimulation summaries of graphs (ranging from millions to billions of edges), together with the exploration benefits and the navigational query speedups obtained by leveraging summaries stored alongside the original datasets.
A short overview of recent advances in map evaluation

Mapping is an important task for mobile robots in general and in Safety, Security, and Rescue Robotics (SSRR) in particular - often maps are even a core mission deliverable for SSRR applications. The assessment of the quality of maps in a simple, efficient and automated way is hence of high interest. But it is not trivial and an ongoing research topic. Here, an overview of advances with a new approach on map evaluation is presented. This structure-based method makes use of a Topology Graph, a topological, abstracted representation of the map. The Topology Graph is constructed by generating and processing a Voronoi Diagram from a 2D grid map. Having a ground truth map, the Topology Graphs of both maps are matched using both similarity metrics on the vertices as well as structural matching of subgraph isomorphisms.
Differential Effects of Product Category on Shoppers' Selection of Web-based Stores: A Probabilistic Modeling Approach

This study analyzes the probability of buying products from a particular online store given a set of alternative vendors. We use a multinomial logit choice model to analyze experimental data of consumer choice in two product categories books and computers, each of which represents goods that differ along the risk dimension. Books represent search-quality, cheaper products, while computers represent experience-quality, more expensive products. Our modeling approach enabled us to capture the competitive environment of Internet shopping and at the same time obtain diagnostic information about the salient factors in the choice process. The results indicate the existence of differences in terms of the dimensions considered by consumers when buying highvs. low-risk goods. Most notably, we found that when purchasing computers online, aspects of uncertainty and risk were more salient than when purchasing books online. We discuss the implications of these findings and areas for future research.
Utilizing random noise in cryptography: Where is the Tofu?

With the massive deployment of mobile devices and sensor networks, resistance against side-channel attacks in cryptographic systems has become an active research topic in recent years. While various security measures exist in literature, most of them are deterministic in nature, where the same input plaintext always results in the same power trace with a given key. Thus, attackers can still aggregate the small deviations between the power traces to identify the correct key. Towards this, random dynamic voltage scaling has been proposed in the literature, which is demonstrated to be effective against Differential Power Analysis (DPA). In this paper, we evaluate this approach, along with the expanded feature of spatial randomness, to resist Correlation Power Analysis (CPA).
Consecutive ones Block for Symmetric Matrices

We show that a cubic graph G with girth g(G) ≥ 5 has a Hamiltonian Circuit if and only if the matrix A +I can be row permuted such that each column has at most 2 blocks of consecutive 1’s, where A is the adjacency matrix of G, I is the unit matrix, and a block can be consecutive in circular sense, i.e., the first row and the last row are viewed as adjacent rows. Then, based on this necessary and sufficient condition and the NP-completeness of Hamiltonian Circuit for cubic graphs [2], we prove that for every fixed k ≥ 2t hek-Consecutive Blocks problem (deciding whether a given binary matrix M can be permuted on rows such that each column has at most k blocks of consecutive 1’s) remains NP-Complete even if restricted to (1) symmetric matrices, or (2) matrices having at most 3 blocks of consecutive 1’s per row. This result significantly generalizes the related results of [5, 6], and gets its application in [9] in proving the NP-Completeness of all shortest paths Interval Routing Schemes with compactness k for every k ≥ 3.