Miracle-dz/UniFAR-FTUs huggingface dataset:
Data type specification: Parameterization and the power of specification techniques

This paper extends our earlier work on abstract data types by providing an algebraic treatment of parametrized data types (e.g., sets-of-(), stacks-of-(), etc.), as well as answering a number of questions on the power and limitations of algebraic specification techniques. In brief: we investigate the “hidden function” problem (the need to include operations in specifications which we want to be hidden from the user); we prove that conditional specifications are inherently more powerful than equational specifications; we show that parameterized specifications must contain “side conditions” (e.g., that finite-sets-of-d requires an equality predicate on d), and we compare the power of the algebraic approach taken here with the more categorical approach of Lehman and Smyth.
Joint edge detector based on Laplacian pyramid

In order to capture the details of the edge, continuous, thin and noise free, this paper describes an improved edge detection based on Laplacian pyramid. We studied the edge detection based on Laplacian Pyramid (LP edge detector) in detail, proposed Joint edge detector which is consists of the Laplacian sharpening and Laplacian pyramid. This method is equivalent to that the Laplacian sharpening was followed by a Gaussian impulse response low-pass filter and multiscale image decomposition. Laplacian sharpening enhanced image details, and the two follow up steps improved the stability of the noise. The experimental results showed that the method inherits the advantages of multiscale edge detection, plays to the advantages of Laplacian sharpening. The method improves the ability to capture the details of the edge, and eliminates the noise.
Exploring Trust to Reduce Communication Barriers in Virtual World Collaborations

Virtual worlds (VW) have paved a new and important channel for workplace collaborations. However, analysts have noted that several organizations that made a strong entrance into using VW as a nouveau channel for communication and collaboration are stepping back due to limited user response. Motivated by this fact, we propose a trust-theoretic ‘virtual world model’ for communication and collaborations in virtual worlds. The model, grounded in literature on ‘organizational communication’ and ‘trust’, theoretically examines the role of trust in developing behavioural intentions for using this rich virtual communication medium for collaborations. Results establish the important roles of perceived structural assurance and perceived social presence for fostering user trust in VW. Further, results also indicate that user trust is a key factor in influencing organizational members to develop behavioural intention to use the VW for collaborations. Implications for research and practice are discussed.
Accountability and the fairness bias in the context of joint production: Effects of bonuses and opportunities

According to the accountability principle a person's fair allocation takes into account the input-relevant variables she can influence, like effort, but not the variables she cannot influence, like a randomly assigned exogenous factor. This study is based on a real effort-task experiment, where the exogenous influence is twofold: it comes either as a production factor or as a bonus. We confirm that in a base treatment, i.e in absence of exogenous factors, subjects base their allocation decisions largely on effort. When exogenous differences are present behavior changes. Whereas bonuses are largely ignored and subjects still mostly base their decisions on effort, production factors render allocations more selfish. Furthermore, we study whether accountability holds for decisions over opportunities. We apply the so-called lottery-points-method, where a binary lottery in the last experimental stage allocates the whole amount to one of the workers. We find that subjects claim more for themselves when allocating opportunities in all treatments.
Efficacy of pemetrexed-based regimen in relapsed advanced thymic epithelial tumors and its association with thymidylate synthetase level

Purpose Due to the rarity of thymic epithelial tumors (TET), no standard chemotherapy regimen has been identified in the relapsed setting. The aim of this study was to investigate the activity of a pemetrexed-based regimen in advanced TET as palliative treatment after failure of previous chemotherapy, and to detect its association with thymidylate synthetase (TS) level. Methods Patients with pathologically confirmed TET and treated with pemetrexed-based regimen were evaluated from 2006 to 2014 in Zhejiang Cancer Hospital. TS mRNA level was detected by real-time polymerase chain reaction. The Kaplan–Meier method was used for survival analysis. Results A total of 22 TET patients were identified, of whom eight had thymoma and 14 had thymic carcinoma. In total, the objective response rate and disease control rate of the 22 patients were 22.7% and 68.2%, respectively. Median progression-free survival and overall survival were 4.5 months and 34.9 months, respectively. A trend of lower TS mRNA levels existed in patients with disease control compared to those with progressive disease (268.0±160.5×10−4 vs 567.0±445.0×10−4, P=0.065). Conclusion Patients with advanced TET may benefit from pemetrexed-based regimen therapy. TS mRNA level is valuable for predicting the efficacy of pemetrexed in TET.
Friendly Fire and the Sustained Attention to Response Task

Objective: We investigated whether losses of inhibitory control could be responsible for some friendly-fire incidents. Background: Several factors are commonly cited to explain friendly-fire incidents, but failure of inhibitory control has not yet been explored. The Sustained Attention to Response Task (SART) could be a valid model for inhibition failures in some combat scenarios. Method: Participants completed small-arms simulations using near infrared emitter guns, confronting research assistants acting as friends or foes. In Experiment 1, seven participants completed three conditions with three different proportions of foes (high, medium, low). In Experiment 2, 13 participants completed high-foe (high-go) and low-foe (low-go) versions of a small-arms simulation as well as comparative computer tasks. Results: Participants made more friendly-fire errors (errors of commission) when foe proportion was high. A speed–accuracy trade-off was apparent, with participants who were faster to fire on foes also more likely to accidentally shoot friends. When foe proportion was higher, response times to foe stimuli were faster, and subjective workload ratings were higher. Conclusion: Failures of inhibitory control may be responsible for some friendly-fire incidents and the SART could be a suitable empirical model for some battlefield environments. The effect appears to be disproportionately greater at higher foe proportions. The exact nature of performance reductions associated with high-foe proportions requires further investigation. Application: The SART may be a useful model of friendly-fire scenarios. It could be used to indicate a soldier’s likelihood to commit a friendly-fire mistake and to identify high-risk environments.
Using Evolutional Properties of Gene Networks in Understanding Survival Prognosis of Glioblastoma

Previously, we investigated survival prognosis of glioblastoma by applying a gene regulatory approach to a human glioblastoma dataset. Here, we further extend our understanding of survival prognosis of glioblastoma by refining the network inference technique we apply to the glioblastoma dataset with the intent of uncovering further topological properties of the networks. For this study, we modify the approach by specifically looking at both positive and negative correlations separately, as opposed to absolute correlations. There is great interest in applying mathematical modeling approaches to cancer cell line datasets to generate network models of gene regulatory interactions. Analysis of these networks using graph theory metrics can identify genes of interest. The principal approach for modeling microarray datasets has been to group all the cell lines together into one overall network, and then, analyze this network as a whole. As per the previous study, we categorize a human glioblastoma cell line dataset into five categories based on survival data, and analyze each category separately using both negative and positive correlation networks constructed using a modified version of the WGCNA algorithm. Using this approach, we identified a number of genes as being important across different survival stages of the glioblastoma cell lines.
Graph summarization for attributed graphs

The increasing popularity of graph data in various domains has led to a renewed interest in understanding hidden relationships between nodes in a single large graph. And graph summarization is to find a concise but meaningful representation of a given graph. In this paper, we studied the problem of summarizing graph with content associated with nodes. We propose a graph summarization algorithm AGSUMMARY, which achieves a combination of topological and attribute similarities. Our method utilizes the Minimum Description Length (MDL) principle to model the graph summarization problem into a code cost function, and compute an optimal summary of graph with neighborhood greedy strategy. It requires no specified number of summary parts and its running time scales linearly with graph size and the average degree of nodes. Experimental results demonstrate the effectiveness and efficiency of our proposed method. For further illustration, a case example is given to explain our method.
Curing Mice with Large Tumors by Locally Delivering Combinations of Immunomodulatory Antibodies

Purpose: Immunomodulatory mAbs can treat cancer, but cures are rare except for small tumors. Our objective was to explore whether the therapeutic window increases by combining mAbs with different modes of action and injecting them into tumors. Experimental Design: Combinations of mAbs to CD137/PD-1/CTLA-4 or CD137/PD-1/CTLA-4/CD19 were administrated intratumorally to mice with syngeneic tumors (B16 and SW1 melanoma, TC1 lung carcinoma), including tumors with a mean surface of approximately 80 mm2. Survival and tumor growth were assessed. Immunologic responses were evaluated using flow cytometry and qRT-PCR. Results: More than 50% of tumor-bearing mice had complete regression and long-term survival after tumor injection with mAbs recognizing CD137/PD-1/CTLA-4/CD19 with similar responses in three models. Intratumoral injection was more efficacious than intraperitoneal injection in causing rejection also of untreated tumors in the same mice. The three-mAb combination could also induce regression, but was less efficacious. There were few side effects, and therapy-resistant tumors were not observed. Transplanted tumor cells rapidly caused a Th2 response with increased CD19 cells. Successful therapy shifted this response to the Th1 phenotype with decreased CD19 cells and increased numbers of long-term memory CD8 effector cells and T cells making IFNγ and TNFα. Conclusions: Intratumoral injection of mAbs recognizing CD137/PD-1/CTLA-4/CD19 can eradicate established tumors and reverse a Th2 response with tumor-associated CD19 cells to Th1 immunity, whereas a combination lacking anti-CD19 is less effective. There are several human cancers for which a similar approach may provide clinical benefit. Clin Cancer Res; 21(5); 1127–38. ©2014 AACR. See related commentary by Dronca and Dong, p. 944
1 EE 368 C : project proposal Transmission of layered video using priority dropping Group # 6

There is an increasing interest in the deployment of high quality video over the Internet, for applications such as Video on Demand or Video Conferencing. A significant amount of work has been done on scalable video coding to deal with the heterogeneous conditions in the Internet. However, scalable coding is only part of the problem and it should be appropriately used at transmission time. One of the router mechanisms that could work together with the scalable encoding, is priority dropping, which is provided by the AF class of the DiffServ standards. In this paper, we want to show the benefit of using priority dropping for the transmission of layered video and to provide some guidelines on how to configure the parameters, of both layering and dropping, in various network scenarios. 1. BACKGROUND 1.1 Scalable video encoding The scalable video coder produces a bit stream, decodable in multiple layers, which provides different levels of quality. It allows computation-time and memory-limited decoding on less powerful hardware platforms, and it can substantially improve the quality of video transmitted over error-prone channels such as the Internet or wireless. Temporal, SNR, and spatial scalability have been defined in the international video coding standards, e.g., the MPEG-2 [10] and the H.263 [9]. All of these types of scalable video consist of a base layer (BL) and one or more enhancement layers (ELs) as shown in Figure 1. The BL of the scalable video stream represents, in general, the minimum amount of data needed for decoding that stream. The EL represents additional information, and therefore it enhances the video signal representation when decoded by the receiver. Figure 1. Basic Video Scalability Structures Figure 2. Video Scalability Structure with Fine-Granularity It is virtually impossible to achieve a good coding efficiency/video-quality tradeoff over such a wide range of rates. To achieve fine granularity, van der Schaar et al. [2] proposed a scalable Internet video based on MPEG-4 scalable video coding method using both a prediction-based base layer and a finegranular enhancement layer shown in Figure 2. One of the advantages of the fine-granular scalability approach is that the enhancement layer sub-streams can be combined at the receiver into a single stream and decoded using a single EL decoder.
AR-12 Inhibits Chaperone Proteins Preventing Virus Replication and the Accumulation of Toxic Misfolded Proteins

Laurence Booth1, Jane L Roberts1, Heath Ecroyd2, St. Patrick Reid3, Stefan Proniuk4, Alexander Zukiwski4, Abraham Jacob5, Elsa Damonte6, María J Tuñón7 and Paul Dent1* 1Department of Biochemistry and Molecular Biology, Virginia Commonwealth University, Richmond, VA 23298, USA 2School of Biological Sciences and Illawarra Health and Medical Research Institute, University of Wollongong, NSW 2522, Australia 3Molecular and Translational Science, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), 1425 Porter Street, Fort Detrick, Frederick, MD 21702-5011, USA
A New Approach for Centralized End-System Multicast Protocol

In this paper we propose a new approach of application-level multicast protocol providing a group communication service. This protocol, called End-System Multicast (ESM), and can be used when native multicast routing is not available. ESM is a centralized protocol where everything is being controlled by a single host called Rendez-vous point (RPL1), connected indirectly to the group members via some hosts called secondary Rendez-vous Point (RPL2). Each RPL2 has some group members that constitute a cluster, and each cluster is controlled by its RPL2. Since the group control is divided among some RPL2 and a main controller (RPL1) manages the relation among RPL2s and between itself and RPL2s, we found that the scalability is improved and it also avoids the bottleneck problem near the RPL1, or there is a load balance.
A Social Judgment? Extralegal Contrast Effects in Hypothetical Legal Decision Making

Social judgments in ambiguous situations often rely on heuristics and biases, and legal decision makers are often faced with evidence that does not clearly favor one decision over another. Across two studies, we tested whether one extralegal factor, contrast cases, influenced decision making when judicial factors were held constant. In Study 1, participants (n = 100) evaluated whether an imagined prosecutor had sufficient evidence to send the same three target cases to trial. Before deciding these cases, though, the participants first evaluated cases with either relatively stronger or weaker evidence than the targets. Those in the weak-case comparison group were significantly more likely to send target cases to trial, and they believed the prosecutor had a stronger case. In Study 2, all participants (n = 100) evaluated hypothetical parole applications, but the method was otherwise the same as that used in Study 1. The same contrast-oriented pattern emerged. Participants who first viewed weaker parole applications rated the identical targets as significantly more rehabilitated. Taken together, the results of these two studies suggest that contrast effects may be one extralegal factor involved in shaping individual-level social judgments made in legal contexts such as grand juries and parole boards.
Exploiting Linked Data for Open and Configurable Named Entity Extraction

Named Entity Extraction (NEE) is the process of identifying entities in texts and, very commonly, linking them to related (Web) resources. This task is useful in several applications, e.g. for question answering, annotating documents, post-processing of search results, etc. However, existing NEE tools lack an open or easy configuration although this is very important for building domain-specific applications. For example, supporting a new category of entities, or specifying how to link the detected entities with online resources, is either impossible or very laborious. In this paper, we show how we can exploit semantic information (Linked Data) at real-time for configuring (handily) a NEE system and we propose a generic model for configuring such services. To explicitly define the semantics of the proposed model, we introduce an RDF/S vocabulary, called “Open NEE Configuration Model”, which allows a NEE service to describe (and publish as Linked Data) its entity mining capabilities, but also to be dynamically configured. To allow relating the output of a NEE process with an applied configuration, we propose an extension of the Open Annotation Data Model which also enables an application to run advanced queries over the annotated data. As a proof of concept, we present X-Link, a fully-configurable NEE framework that realizes this approach. Contrary to the existing tools, X-Link allows the user to easily define the categories of entities that are interesting for the application at hand by exploiting one or more semantic Knowledge Bases. The user is also able to update a category and specify how to semantically link and enrich the identified entities. This enhanced configurability allows X-Link to be easily configured for different contexts for building domain-specific applications. To test the approach, we conducted a task-based evaluation with users that demonstrates its usability, and a case study that demonstrates its feasibility.
Seize the Moments: Approximating American Option Prices in the GARCH Framework

This paper proposes an efficient approach to compute the prices of American style options in the GARCH framework. Rubinstein's (1998) Edgeworth tree idea is combined with the analytical formulas for moments of the cumulative return under GARCH developed in Duan et al. (1999, 2002) to yield a simple recombining binomial tree for option valuation in the GARCH context. Since the resulting tree is univariate, the proposed approach represents a convenient approximation of the bivariate GARCH system. Numerical analyses are used to demonstrate the speed and accuracy of the proposed approximation.
Continuous Articulatory-to-Acoustic Mapping using Phone-based Trajectory HMM for a Silent Speech Interface

The article presents an HMM-based mapping approach for converting ultrasound and video images of the vocal tract into an audible speech signal, for a silent speech interface application. The proposed technique is based on the joint modeling of articulatory and spectral features, for each phonetic class, using Hidden Markov Models (HMM) and multivariate Gaussian distributions with full covariance matrices. The articulatory-toacoustic mapping is achieved in 2 steps: 1) finding the most likely HMM state sequence from the articulatory observations; 2) inferring the spectral trajectories from both the decoded state sequence and the articulatory observations. The proposed technique is compared to our previous approach, in which only the decoded state sequence was used for the inference of the spectral trajectories, independently from the articulatory observations. Both objective and perceptual evaluations show that this new approach leads to a better estimation of the spectral trajectories.
Optimal control for maximizing velocity of the CompAct™ compliant actuator

The CompAct™ actuator features a clutch mechanism placed in parallel with its passive series elastic transmission element and can therefore benefit from the advantages of both series elastic actuators (SEA) and rigid actuators. The actuator is capable of effectively managing the storage and release of the potential energy of the compliant element by the appropriate control of the clutch subsystem. Controlling the timing of the energy storage/release in the elastic element is exploited for improving motion control in this research. This paper analyses how this class of actuation systems can be used to maximize the link velocity of the joint. The dynamic model of the joint is derived and an optimal control strategy is proposed to identify optimal input reference profiles for the actuator (motor position/velocity and clutch activation timing) which permit the link velocity maximization. The effect of compliance of the joint on the performance of the system is studied and the optimal stiffness is analyzed.
Primary T-lymphocytes rescue the replication of HIV-1 DIS RNA mutants in part by facilitating reverse transcription

The dimerization initiation site (DIS) stem-loop within the HIV-1 RNA genome is vital for the production of infectious virions in T-cell lines but not in primary cells. In comparison to peripheral blood mononuclear cells (PBMCs), which can support the replication of both wild type and HIV-1 DIS RNA mutants, we have found that DIS RNA mutants are up to 100 000-fold less infectious than wild-type HIV-1 in T-cell lines. We have also found that the cell-type-dependent replication of HIV-1 DIS RNA mutants is largely producer cell-dependent, with mutants displaying a greater defect in viral cDNA synthesis when viruses were not derived from PBMCs. While many examples exist of host–pathogen interplays that are mediated via proteins, analogous examples which rely on nucleic acid triggers are limited. Our data provide evidence to illustrate that primary T-lymphocytes rescue, in part, the replication of HIV-1 DIS RNA mutants through mediating the reverse transcription process in a cell-type-dependent manner. Our data also suggest the presence of a host cell factor that acts within the virus producer cells. In addition to providing an example of an RNA-mediated cell-type-dependent block to viral replication, our data also provides evidence which help to resolve the dilemma of how HIV-1 genomes with mismatched DIS sequences can recombine to generate chimeric viral RNA genomes.