Miracle-dz/UniFAR-FTUs huggingface dataset:
Eurographics Symposium on Geometry Processing (2007) Developable Surfaces from Arbitrary Sketched Boundaries

Developable surfaces are surfaces that can be unfolded into the plane with no distortion. Although ubiquitous in our everyday surroundings, modeling them using existing tools requires significant geometric expertise and time. Our paper simplifies the modeling process by introducing an intuitive sketch-based approach for modeling developables. We develop an algorithm that given an arbitrary, user specified 3D polyline boundary, constructed using a sketching interface, generates a smooth discrete developable surface that interpolates this boundary. Our method utilizes the connection between developable surfaces and the convex hulls of their boundaries. The method explores the space of possible interpolating surfaces searching for a developable surface with desirable shape characteristics such as fairness and predictability. The algorithm is not restricted to any particular subset of developable surfaces. We demonstrate the effectiveness of our method through a series of examples, from architectural design to garments.
Tutz , Leitenstorfer : Generalized smooth monotonic regression

Common approaches to monotonic regression focus on the case of a unidimensional covariate and continuous dependent variable. Here a general approach is proposed that allows for additive and multiplicative structures where one or more variables have monotone influence on the dependent variable. In addition the approach allows for dependent variables from an exponential family, including binary and Poisson distributed dependent variables. Flexibility of the smooth estimate is gained by expanding the unknown function in monotonic basis functions. For the estimation of coefficients and the selection of basis functions a likelihood based boosting algorithm is proposed which is simply to implement. Stopping criteria and inference are based on AIC-type measures. The method is applied to several data sets.
Adaptive MAP receiver via the EM algorithm and message passings for MIMO-OFDM mobile communications

This paper proposes two new types of maximum a posteriori probability (MAP) receivers for multiple-input-multiple-output and orthogonal frequency-division multiplexing mobile communications with a channel coding such as the low-density parity-check code. One proposed receiver employs the expectation-maximization algorithm so as to improve performance of approximated MAP detection. Differently from a conventional receiver employing the minimum mean-square estimation (MMSE) algorithm, it applies the recursive least squares (RLS) algorithm to the channel estimation in order to track a fast fading channel. For the purpose of further improvement, the other proposed receiver applies a new adaptive algorithm that can be derived from the message passing on factor graphs. The algorithm exploits all detected signals but one of targeted time, and can gain a considerable advantage over the MMSE and RLS. Computer simulations show that the first proposed receiver is superior in channel-tracking ability to the conventional receiver employing the MMSE. Furthermore, it is demonstrated that the second proposed receiver remarkably outperforms both the conventional and the first proposed ones.
Malware network behavior extraction based on dynamic binary analysis

Malware is a tremendous threat on the Internet. Current malware analysis systems focus on listing the malware behaviors, but make no mention of malware network behaviors which results in malware's self-duplication and self-propagation on the Internet. In this paper, we present a new method to extract malware network behaviors. Our method is based on dynamic binary analysis and dynamic taint analysis. With the dynamic binary analysis, we can extract the malware network behavior and the self-duplication behavior. We also present a method to catch malware self-propagation behavior by using dynamic taint analysis. Finally, we evaluate our method and the results show that our method is successful in extracting malware network behavior and identifying the malware self-duplication behavior.
Constraint-Variance Tolerant Data Repairing

Integrity constraints, guiding the cleaning of dirty data, are often found to be imprecise as well. Existing studies consider the inaccurate constraints that are oversimplified, and thus refine the constraints via inserting more predicates (attributes). We note that imprecise constraints may not only be oversimplified so that correct data are erroneously identified as violations, but also could be overrefined that the constraints overfit the data and fail to identify true violations. In the latter case, deleting excessive predicates applies. To address the oversimplified and overrefined constraint inaccuracies, in this paper, we propose to repair data by allowing a small variation (with both predicate insertion and deletion) on the constraints. A novel θ-tolerant repair model is introduced, which returns a (minimum) data repair that satisfies at least one variant of the constraints (with constraint variation no greater than θ compared to the given constraints). To efficiently repair data among various constraint variants, we propose a single round, sharing enabled approach. Results on real data sets demonstrate that our proposal can capture more accurate data repairs compared to the existing methods with/without constraint repairs.
SEEC: A Framework for Self-aware Management of Multicore Resources

This paper presents SEEC, a self-aware programming model, designed to reduce programming effort in modern multicore systems. In the SEEC model, application programmers specify application goals and progress, while systems programmers separately specify actions system software and hardware can take to affect an application (e.g. resource allocation). The SEEC runtime monitors applications and dynamically selects actions to meet application goals optimally (e.g. meeting performance while minimizing power consumption). The SEEC runtime optimizes system behavior for the application rather than requiring the application programmer to optimize for the system. This paper presents a detailed discussion of the SEEC model and runtime as well as several case studies demonstrating their benefits. SEEC is shown to optimize performance per Watt for a video encoder, find optimal resource allocation for an application with complex resource usage, and maintain the goals of multiple applications in the face of environmental fluctuations.
Conserved regulatory mechanism controls the development of cells with rooting functions in land plants

Significance This work describes the discovery of an ancient genetic mechanism that was used to build rooting systems when plants colonized the relatively dry continental surfaces >470 million years ago. We demonstrate that a group of basic helix–loop–helix transcription factors—the LOTUS JAPONICUS ROOTHAIRLESS1-LIKE proteins—is part of a conserved auxin-regulated gene network that controls the development of tip-growing cells with rooting functions among extant land plants. This result suggests that this mechanism was active in the common ancestor of most land plants and facilitated the development of early land plant filamentous rooting systems, crucial for the successful colonization of the land by plants. Land plants develop filamentous cells—root hairs, rhizoids, and caulonemata—at the interface with the soil. Members of the group XI basic helix–loop–helix (bHLH) transcription factors encoded by LOTUS JAPONICUS ROOTHAIRLESS1-LIKE (LRL) genes positively regulate the development of root hairs in the angiosperms Lotus japonicus, Arabidopsis thaliana, and rice (Oryza sativa). Here we show that auxin promotes rhizoid and caulonema development by positively regulating the expression of PpLRL1 and PpLRL2, the two LRL genes in the Physcomitrella patens genome. Although the group VIII bHLH proteins, AtROOT HAIR DEFECTIVE6 and AtROOT HAIR DEFECTIVE SIX-LIKE1, promote root-hair development by positively regulating the expression of AtLRL3 in A. thaliana, LRL genes promote rhizoid development independently of PpROOT HAIR DEFECTIVE SIX-LIKE1 and PpROOT HAIR DEFECITVE SIX-LIKE2 (PpRSL1 and PpRSL2) gene function in P. patens. Together, these data demonstrate that both LRL and RSL genes are components of an ancient auxin-regulated gene network that controls the development of tip-growing cells with rooting functions among most extant land plants. Although this network has diverged in the moss and the angiosperm lineages, our data demonstrate that the core network acted in the last common ancestor of the mosses and angiosperms that existed sometime before 420 million years ago.
Non-binary algebraic spatially-coupled quasi-cyclic LDPC codes

This paper considers the algebraic construction and performance of non-binary spatially-coupled low density parity check (LDPC) codes. A replicate-and-mask approach is presented to construct finite-length algebraic quasi-cyclic (QC) spatially-coupled (SC) LDPC codes. Numerical results show the superiority of non-binary algebraic SC QC LDPC codes over the corresponding random non-binary (block and SC) LDPC codes. In this paper, it is demonstrated that the threshold saturation phenomenon, previously demonstrated for binary SC LDPC codes, also holds for non-binary SC LDPC codes over the binary-input AWGN channel with BPSK modulation.
In vitro Cytotoxicity of Methanol Extract from Aerial Parts of Aralia cachemirica and Purified Continentalic Acid

The present study was designed to evaluate the in vitro cytotoxic effect of methanol extract of aerial parts including stems, leaves and twigs of Aralia cachemirica and purified continentalic acid isolated from this extract against a panel of human cancer cell lines of varied tissues. Percentage of growth inhibition was evaluated by sulphorhodamine B assay. Purified continentalic acid showed moderate cytotoxicity against all the cell lines used. In contrast, the extract exhibited significant concentration dependant cytotoxicity against A-549 (lung), THP-1 (leukemia) and MCF-7 (breast) cell lines. This work highlights cytotoxic potential of this extract, which can further be explored for different constituents for their possible use autonomously or in combined manner in cancer therapy. The detailed analysis of their cytotoxicity has been presented in this paper.
Cognitive Rehabilitation of Memory for Mild Cognitive Impairment: A Methodological Review and Model for Future Research

Abstract Several recent reviews have suggested that cognitive rehabilitation may hold promise in the treatment of memory deficits experienced by patients with mild cognitive impairment. In contrast to the previous reviews that mainly focused on outcome, the current review examines key methodological challenges that are critical for designing and interpreting research studies and translating results into clinical practice. Using methodological details from 36 studies, we first examine diagnostic variability and how the use of cutoffs may bias samples toward more severely impaired patients. Second, the strengths and limitations of several common rehabilitative techniques are discussed. Half of the reviewed studies used a multi-technique approach that precludes the causal attribution between any specific technique and subsequent improvement. Third, there is a clear need to examine the dose-response relationship since this information was strikingly absent from most studies. Fourth, outcome measures varied widely and frequently depended on neuropsychological tests with little theoretical justification or ecological relevance. Fifth, we discuss how the variability in each of these other four areas complicates efforts to examine training generalization. Overall, future studies should place greater emphasis on ecologically relevant treatment approaches and outcome measures and we propose a hierarchical model that may aid in this pursuit. (JINS, 2014, 19, 1–17)
Evolutionary Relationships and Functional Diversity of Plant Sulfate Transporters

Sulfate is an essential nutrient cycled in nature. Ion transporters that specifically facilitate the transport of sulfate across the membranes are found ubiquitously in living organisms. The phylogenetic analysis of known sulfate transporters and their homologous proteins from eukaryotic organisms indicate two evolutionarily distinct groups of sulfate transport systems. One major group named Tribe 1 represents yeast and fungal SUL, plant SULTR, and animal SLC26 families. The evolutionary origin of SULTR family members in land plants and green algae is suggested to be common with yeast and fungal SUL and animal anion exchangers (SLC26). The lineage of plant SULTR family is expanded into four subfamilies (SULTR1–SULTR4) in land plant species. By contrast, the putative SULTR homologs from Chlorophyte green algae are in two separate lineages; one with the subfamily of plant tonoplast-localized sulfate transporters (SULTR4), and the other diverged before the appearance of lineages for SUL, SULTR, and SLC26. There also was a group of yet undefined members of putative sulfate transporters in yeast and fungi divergent from these major lineages in Tribe 1. The other distinct group is Tribe 2, primarily composed of animal sodium-dependent sulfate/carboxylate transporters (SLC13) and plant tonoplast-localized dicarboxylate transporters (TDT). The putative sulfur-sensing protein (SAC1) and SAC1-like transporters (SLT) of Chlorophyte green algae, bryophyte, and lycophyte show low degrees of sequence similarities with SLC13 and TDT. However, the phylogenetic relationship between SAC1/SLT and the other two families, SLC13 and TDT in Tribe 2, is not clearly supported. In addition, the SAC1/SLT family is absent in the angiosperm species analyzed. The present study suggests distinct evolutionary trajectories of sulfate transport systems for land plants and green algae.
Database integrity monitoring for synthetic vision systems using machine vision and SHADE

In an effort to increase situational awareness, the aviation industry is investigating technologies that allow pilots to visualize what is outside of the aircraft during periods of low-visibility. One of these technologies, referred to as Synthetic Vision Systems (SVS), provides the pilot with real-time computer-generated images of obstacles, terrain features, runways, and other aircraft regardless of weather conditions. To help ensure the integrity of such systems, methods of verifying the accuracy of synthetically-derived display elements using onboard remote sensing technologies are under investigation. One such method is based on a shadow detection and extraction (SHADE) algorithm that transforms computer-generated digital elevation data into a reference domain that enables direct comparison with radar measurements. This paper describes machine vision techniques for making this comparison and discusses preliminary results from application to actual flight data.
Addressing the integration of ICT into teaching and Identification of the potential factors motivating teachers to use ICT

This present study is set up to investigate how ICT can be successfully integrated in the course of teaching and to explore the factors that motivate or de-motivate teachers to use ICT inside the classroom setting. It also seeks to examine the reasons behind sustaining their use of ICT in the teaching process. The study employed “Herzberg’ Motivation–Hygiene theory” to guide the process of understanding and categorizing the motivational factors. For the purpose of the study, data are collected through the use of semi-structured interviews with teachers who are experienced in using ICT. The deductive qualitative content analysis of the results reveal that the motivational factors which correlated most positively with ICT use are: self-perceived ability to use technology, level of resources available and satisfaction generated from utilizing IT, as well as and a sense of achievement resulting from applying technologies for teaching purposes. The study also identifies a variety of motivational factors attributed by teachers to using ICT, such as: creating a satisfying and encouraging classroom environment, making teaching stimulating by increasing the attractiveness of tasks and enjoyable by breaking the monotony of class sessions, promoting the development of group cohesiveness by making learners active task participants.
The development of the battle field simulation program using the survivability on the probability map

There are a lot of researches on the path planning algorithm for those of the unmanned vehicle. Previous researches related to the path planning mainly focused on finding the shortest path on the given map. However, on the battle field, if the vehicle just moves along the shortest path, it could not reach the goal, because of the enemy's attack. Therefore it's necessary that the new path planning algorithm for the unmanned vehicle on the battle field. In this paper, we will suggest a new path planning algorithm for the vehicle on the battle field using extended A* algorithm with survivability. For this, we will define the survivability and develop the additional cost function to find the optimal path in this situation. To verify the proposed algorithm, we developed the simulation program and the results will be shown.
CSCW in New Zealand: a snapshot

This report has been produced as one of the outputs of the FoRST funded project “Improved Computer Supported Collaborative Work Systems” which is currently running in the Department of Computer Science at the University of Waikato. Its aim is to give a snapshot of the uses of and possibilities for Computer Supported Collaborative (also Co-operative) Work (also Working) (CSCW) within New Zealand. In order to take this snapshot we followed a simple procedure:
Fibroelastoma as a Culprit of Syncope

We present a case of a valvular mass diagnosed by emergency department bedside ultrasonography in a young patient with syncope. Bedside ultrasound has become a valuable tool in the evaluation of patients with syncope in the emergency department. This patient was believed to have a fibroelastoma on ultrasound that was confirmed by magnetic resonance and ultimately by postsurgical pathological evaluation. The indications and findings of using ultrasonography as part of the workup of syncope in the emergency department are discussed.
An Energy Efficient Cooperative Density Control Algorithm in Large Wireless Sensor Networks

An energy efficient cooperative density control algorithm, EECDC, is proposed in this paper. EECDC is based on a new sensing model - cooperative sensing model (CSM) other than traditional Boolean sensing model (BSM), and multi-sensors' cooperative exploration is considered in it. According to CSM, serials of nonlinear constrained programming models are developed to find the optimal conditions for full coverage with minimal sensor nodes. A mathematical iterative algorithm is employed to solve the problems. Based on the findings, EECDC selects sensor nodes as close to optimal locations as possible to be the working nodes. Simulations show that EECDC outperforms traditional optimal density control algorithm in term of number of working nodes needed, and achieves almost the same coverage. As a result, it achieves higher energy efficiency and longer network lifetime.
An Efficient Group Signature Based on the Discrete Logarithm Problem

Group signature schemes permit a group member signing on messages anonymously and unlinkably on behalf of a group. The anonymity can be revoked when arguments occurred. This paper proposes an efficient group signature scheme based on the discrete logarithm problem, which means no trapdoor functions are used in the settings of cryptographic parameters. Both the group public key and signature size are fixed length. The signing procedure/verifying procedure requires only 9/5 modular multi-exponentiations to generate/verify a signature. It is more efficient than previous schemes based on the same cryptographic assumption.
Nonlinear controllability and stability analysis of adaptive image-based systems

In this paper, a novel adaptive visual feedback scheme is presented to solve the problem of controlling the relative pose between a robot camera and a rigid object of interest. After deriving the image-based state space representation of the camera-object visual interaction model in terms of global coordinates (2D points) fully defined in the image plane, it is shown that the system is completely controllable. By exploiting nonlinear controllability properties, global uniform asymptotic stability of the image reference set-point is proved using Lyapunov's direct method. Moreover, global uniform boundedness of the whole state vector is ensured by using an adaptive nonlinear control scheme, in case of unknown depth of the object. Experimental results with a 6-DOF robot manipulator endowed with a camera on its wrist validate the framework.
What else should we know about experiencing COPD? A narrative review in search of patients’ psychological burden alleviation

The present paper is a narrative review focusing on the psychological impact, identification of protective factors, and interventions minimizing the psychological burdens of chronic obstructive pulmonary disease (COPD). The research reviews studies on neurocognitive functions, personality, emotional problems, and health-related quality of life. This is done with regard to resources as well as activities enabling or enhancing a patient’s adaptation. PubMed and PsychArticles databases were searched for relevant medical (eg, CODP, emphysema), psychopathology (eg, depression), and psychological (eg, personality) keywords, followed by hand search. After application of the inclusion and exclusion criteria, the search resulted in 82 articles and book chapters. The choice was based on evidence accepted by evidence-based medicine, although at different levels of strength. Psychological experiencing of COPD appears to be very unequally represented with scientific research on emotional problems and functioning decrease significantly outnumbering those addressing resources or effective interventions. As our initial literature search called for an urgent need for further exploration, we have carefully pointed out numerous areas where the knowledge on how to protect or restore psychological well-being among COPD patients should be broadened.
Unbiased Sampling of Bipartite Graph

Increasing size of online social networks (OSNs) has given rise to sampling method studies that provide a relatively small but representative sample of large-scale OSNs so that the measurement and analysis burden can be affordable. So far, a number of sampling methods already exist that crawl social graphs. Most of them are suitable for one-mode graph where there is only one type of nodes. Literatures show that Metropolis-Hastings Random Walk (MHRW) produces unbiased samples with better performance than other sampling methods. But there are more and more online social networking sites with two types of nodes, such as Taobao and eBay. Representing these two-mode networks as bipartite graphs, we study the sampling methods for bipartite graphs in this paper. Our contributions include analyze the effectiveness of extending MHRW algorithm to bipartite graphs and making a modification in sampling procedure to improve the stability. Finally, we compare our MHRW sampling algorithm with Random Walk (RW) over the generated bipartite graphs as well as real two-mode network graphs. Simulations show that MHRW outperforms RW over bipartite graphs.