Miracle-dz/UniFAR-FTUs huggingface dataset:
Reflection Attacks on Product Ciphers

In this paper we describe a novel attack method on product ciphers, the reflection attack. The attack method exploits certain similarities among round functions which have not been utilized in previous self similarity attacks. We give practical examples illustrating the power of the reflection attack on several ciphers such as GOST, DEAL and some variants of DES and Magenta. Many interesting and exceptional properties of the attack are also presented in these examples. In addition, we discuss new design criteria that make product ciphers resistant to self similarity attacks and introduce a definition of similarity degree.
Application of a Proactive Risk Analysis to Emergency Department Sickle Cell Care

Introduction Patients with sickle cell disease (SCD) often seek care in emergency departments (EDs) for severe pain. However, there is evidence that they experience inaccurate assessment, suboptimal care, and inadequate follow-up referrals. The aim of this project was to 1) explore the feasibility of applying a failure modes, effects and criticality analysis (FMECA) in two EDs examining four processes of care (triage, analgesic management, high risk/high users, and referrals made) for patients with SCD, and 2) report the failures of these care processes in each ED. Methods A FMECA was conducted of ED SCD patient care at two hospitals. A multidisciplinary group examined each step of four processes. Providers identified failures in each step, and then characterized the frequency, impact, and safeguards, resulting in risk categorization. Results Many “high risk” failures existed in both institutions, including a lack of recognition of high-risk or high-user patients and a lack of emphasis on psychosocial referrals. Specific to SCD analgesic management, one setting inconsistently used existing analgesic policies, while the other setting did not have such policies. Conclusion FMECA facilitated the identification of failures of ED SCD care and has guided quality improvement activities. Interventions can focus on improvements in these specific areas targeting improvements in the delivery and organization of ED SCD care. Improvements should correspond with the forthcoming National Heart, Lung and Blood-sponsored guidelines for treatment of patients with sickle cell disease.
Signalling Pathways that Inhibit the Capacity of Precursor Cells for Myelin Repair

In demyelinating disorders such as Multiple Sclerosis (MS), targets of injury are myelin and oligodendrocytes, leading to severe neurological dysfunction. Regenerative therapies aimed at promoting oligodendrocyte maturation and remyelination are promising strategies for treatment in demyelinating disorders. Endogenous precursor cells or exogenous transplanted cells are potential sources for remyelinating oligodendrocytes in the central nervous system (CNS). Several signalling pathways have been implicated in regulating the capacity of these cell populations for myelin repair. Here, we review neural precursor cells and oligodendrocyte progenitor cells as potential sources for remyelinating oligodendrocytes and evidence for the functional role of key signalling pathways in inhibiting regeneration from these precursor cell populations.
Business Process Patterns for Integrated Supply Chain Planning

Today's competitive global market makes most enterprise endeavor to specialize their business areas, and co-operate with trading partners in supply chain by forms of collaboration, information and business process sharing. However, even the supply chain plan generated by co-operation often fails to be executed successfully, because it was generated without capacities of suppliers and more over nested suppliers. To overcome this limitation, the supply chain plan should be generated truly integrated way. In this paper, we classify business patterns based on scenarios, and present business process models about them. In addition, we describe the types of supply chain planning problem.
Trust calculation in wireless sensor networks

A wireless sensor network (WSN) is a collection of distributed sensor nodes to work together for monitoring the physical and environmental conditions. Trust in wireless sensor networks is an important issue and it solves the problem of access control, privacy, secure routing scheme and reliable communication. This paper introduces a new approach to calculate the trust in WSN. The proposed algorithm and the evaluation of the trust value of the node in the network depend on the trust attributes, metrics and trust parameters.
Using Social Network Analysis to Better Understand the Dependencies in UML Use Cases Collection

For a large scale software development project, requirements and design artifacts like UML models are increasingly produced and collected in a software repository and can be later reused for new software development projects. The purpose of this paper is to analyze and visualize the dependencies in these artifacts to help software developers to see some interesting structural patterns. We adopt the techniques of social network analysis to do this purpose. This paper focuses on use case model artifacts and proposes the way to represent use case models as relation networks, i.e., system, use case, actor, system-use case, actor-use case, and system-actor networks. To demonstrate our work, a hospital software project is used as a case study.
Wireless Sensor Network software testing framework

Even in the last years has been recorded an important growth in the number of developed Wireless Sensor Networks (WSN) applications, the testing methodologies for this type of applications hasn't changed much. In this paper we present a WSN software testing framework architecture. Due to the constraints and special features of the WSN technology, the applications require a different testing approach. We propose a testing framework for this type of applications, combining test driven development, unit testing, and remote integration testing. The usage of this framework makes possible the development of specific testing applications for the base station node and executing manual or automatic remote testing accordingly.
Temporal mechanisms of polarization in online reviews

In this paper we study the temporal evolution of review ratings. We observe that on average ratings tend to become more polarized over time. To explain this phenomenon we propose a simple model that captures the tendency of users for rating manipulation. Simulations with our model demonstrate that it is successful in capturing the aggregate behavior of the users.
Spread Spectrum Audio Indoor Localization

This paper presents the results of an indoor localization experiment that uses spread spectrum modulated audio signals. Indoor spaces do not have line-of-sight to global navigation satellite systems and do not have a truly universal localization system to allow mobile devices to localize themselves. Previous approaches focused in using custom made hardware with several types of signals that, even though with good performance, are not feasible to adopt in a wide scale utilization. The proposed approach uses pre-existent off-the-shelf hardware and easy to handle audio signals present in our everyday lives. However, the challenges when using audible and very susceptible to multipath types of signals are many and require validation of the subjacent principles. An experiment in a real indoor environment was conducted to estimate localization while using spread spectrum noise like signals barely perceptible to people. Results demonstrated a 1.3 cm average accuracy in the center area. These and other results demonstrate the possibility of the use of audio signals with all the advantages regarding wide scale dissemination of an indoor localization solution.
Learning Web Page Block Functions using Roles of Images

Making use of block information in Web IR and Data Mining tasks calls for a good understanding of the function of each block. Existing works on classifying block functions and judging block importance have not made full use of the image factor, and only simple image features were considered. We regard image as a strong indicator of Web page blocks with various functions and propose to learn block functions using roles of images as part of block features. Blocks are generated from Web page segmentation and roles of images are automatically decided by image classification. We experiment on 140 Web pages and demonstrate that utilizing roles of images can significantly improve the classification quality of learning Web page block functions. We also measure the usefulness of different roles of images and evaluate the effect of two page segmentation methods.
The Risk of the New Developmentalism: 'Brasil Maior' Plan and Bureaucratic Rings

This working paper examines the rise of the “new developmentalism” in Brazil and the role of the last three industrial policies created by the federal government since 2004, specially the latest, which is called “Brasil Maior. ” The main purpose of the paper is to analyse the risk of political alliances between private sector elites and the government in the promotion of national companies and the development of some sectors of the economy. The paper brings back the concept of “bureaucratic rings,” used by the sociologist Fernando Henrique Cardoso in the seventies to analyse Brazilian developmental State, to examine the role played by the Brazilian Development Bank today and the possibility of formation of pressure rings between the public and private sector inside the public bureaucracy.
Incentivizing High-Quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium

We study the existence of pure Nash equilibrium (PNE) for the mechanisms used in Internet services (e.g., online reviews and question-answering websites) to incentivize users to generate high-quality content. Most existing work assumes that users are homogeneous and have the same ability. However, real-world users are heterogeneous and their abilities can be very different from each other due to their diversity in background, culture, and profession. In this work, we consider the following setting: (1) the users are heterogeneous and each of them has a private type indicating the best quality of the content he/she can generate; (2) all the users share a fixed total reward. With this setting, we study the existence of pure Nash equilibrium of several mechanisms composed by different allocation rules, action spaces, and information availability. We prove the existence of PNE for some mechanisms and the non-existence for some other mechanisms. We also discuss how to find a PNE (if exists) through either a constructive way or a search algorithm.
The Effect of Hippotherapy on Ten Children with Cerebral Palsy

Purpose: The purpose of this study was to determine whether hippotherapy has an effect on the general functional development of children with cerebral palsy. Methods: The study employed a repeated-measures design with two pre-tests and two post-tests conducted 10 weeks apart using the Pediatric Evaluation of Disability Inventory (PEDI) and the Gross Motor Function Measure (GMFM) as outcome measures. A convenience sample of 10 children with cerebral palsy participated whose ages were 2.3 to 6.8 years at baseline (mean ± SD 4.1 ± 1.7). Subjects received hippotherapy once weekly for 10 weeks between pre-test 2 and post-test 1. Test scores on the GMFM and PEDI were compared before and after hippotherapy. Results: One-way analysis of variance of group mean scores with repeated measures was significant (p < 0.05) for all PEDI subscales and all GMFM dimensions except lying/rolling. Post hoc analyses with the Tukey test for honest significant differences on the PEDI and GMFM total measures as well as GMFM crawling/kneeling and PEDI social skills subtests were statistically significant between pre-test 2 and post-test 1. Conclusions: The results of this study suggest that hippotherapy has a positive effect on the functional motor performance of children with cerebral palsy. Hippotherapy appears to be a viable treatment strategy for therapists with experience and training in this form of treatment and a means of improving functional outcomes in children with cerebral palsy, although specific functional skills were not investigated.
Pan-Sharpening with Multi-scale Wavelet

In satellite image processing, pan-sharpening is the image fusion process in which a low resolution (LR) multi-spectral (MS) image is sharpened using the corresponding high resolution (HR) panchromatic (Pan) image to obtain a HR MS image. In this paper we propose a novel pansharpening method which combines the ideas of classical wavelet-based pan-sharpening with recently developed dictionary learning (DL) methods. The HR MS image is generated using wavelet-based pan-sharpening, regulated by promoting sparsity with respect to a dictionary. The dictionary is obtained using DL on the multi-scale wavelet tree vectors of the image to be pansharpened. A significant advantage of our approach compared to most DL-based approaches is that it does not require a large database of images on which to train the dictionary. Experiments on degraded satellite images demonstrate that our method significantly reduces color distortions and wavelet artifacts compared to the state of the art. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c ©Mitsubishi Electric Research Laboratories, Inc., 2012 201 Broadway, Cambridge, Massachusetts 02139
GrabCutSFM: How 3D information improves unsupervised object segmentation

In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called GrabCutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.
Hydrogen Peroxide Is a Second Messenger in the Salicylic Acid-Triggered Adventitious Rooting Process in Mung Bean Seedlings

In plants, salicylic acid (SA) is a signaling molecule that regulates disease resistance responses, such as systemic acquired resistance (SAR) and hypertensive response (HR). SA has been implicated as participating in various biotic and abiotic stresses. This study was conducted to investigate the role of SA in adventitious root formation (ARF) in mung bean (Phaseolus radiatus L) hypocotyl cuttings. We observed that hypocotyl treatment with SA could significantly promote the adventitious root formation, and its effects were dose and time dependent. Explants treated with SA displayed a 130% increase in adventitious root number compared with control seedlings. The role of SA in mung bean hypocotyl ARF as well as its interaction with hydrogen peroxide (H2O2) were also elucidated. Pretreatment of mung bean explants with N, N’-dimethylthiourea (DMTU), a scavenger for H2O2, resulted in a significant reduction of SA-induced ARF. Diphenyleneiodonium (DPI), a specific inhibitor of membrane-linked NADPH oxidase, also inhibited the effect of adventitious rooting triggered by SA treatment. The determination of the endogenous H2O2 level indicated that the seedlings treated with SA could induce H2O2 accumulation compared with the control treatment. Our results revealed a distinctive role of SA in the promotion of adventitious rooting via the process of H2O2 accumulation. This conclusion was further supported by antioxidant enzyme activity assays. Based on these results, we conclude that the accumulation of free H2O2 might be a downstream event in response to SA-triggered adventitious root formation in mung bean seedlings.
An exploratory study of identifier renamings

Identifiers play an important role in source code understandability, maintainability, and fault-proneness. This paper reports a study of identifier renamings in software systems, studying how terms (identifier atomic components) change in source code identifiers. Specifically, the paper (i) proposes a term renaming taxonomy, (ii) presents an approximate lightweight code analysis approach to detect and classify term renamings automatically into the taxonomy dimensions, and (iii) reports an exploratory study of term renamings in two open-source systems, Eclipse-JDT and Tomcat. We thus report evidence that not only synonyms are involved in renamings but also (in a small fraction) more unexpected changes occur: surprisingly, we detected hypernym (a more abstract term, e.g., size vs. length) and hyponym (a more concrete term, e.g., restriction vs. rule) renamings, and antonym renamings (a term replaced with one having the opposite meaning, e.g., closing vs. opening). Despite being only a fraction of all renamings, synonym, hyponym, hypernym, and antonym renamings may hint at some program understanding issues and, thus, could be used in a renamingrecommendation system to improve code quality.
Prognostic significance of CD44 in human colon cancer and gastric cancer: Evidence from bioinformatic analyses

CD44 is a well-recognized stem cell biomarker expressed in colon and gastric cancer. In order to identify whether CD44 mRNA could be used as a prognostic marker in colon and gastric cancer, bioinformatic analyses were used in this study. cBioPortal analysis and COSMIC analysis were used to explore the CD44 mutation. CD44 mRNA levels were evaluated by using SAGE Genie tools and Oncomine analysis. Kaplan-Meier Plotter was performed to identify the prognostic roles of CD44 mRNA in these two cancers. In this study, first, we found that low alteration frequency of CD44 mRNA in colon and gastric cancer. Second, the high CD44 mRNA level was found in colon and gastric cancer, and it correlated with a benign survival rate in gastric cancer. Third, CD4 and CD74 may be used as markers to predict the prognosis of colon and gastric cancer. However, the deep mechanism(s) of these results remains unclear, further studies have to be performed in the future.
Effects of Beraprost Sodium on Subjective Symptoms in Diabetic Patients with Peripheral Arterial Disease

Background This study evaluated the effects of Beraprost sodium (Berasil) on subjective leg symptoms in patients with peripheral arterial disease caused by diabetes mellitus. Methods Ninety-four diabetic patients with peripheral arterial disease were treated with Beraprost in a fixed-dose, prospective, multicenter, cohort study. Beraprost (40 µg) was administered orally 3 times daily (120 µg/day) for 12 weeks. We developed a new disease-specific symptom questionnaire, which evaluated the effect of peripheral arterial disease on leg discomfort in daily life and assessed therapeutic responses to treatment. Patients were asked for their subjective assessment of symptoms on a written questionnaire before treatment and after 12 weeks of therapy. Results There was significant improvement in all estimated subjective symptoms (burning, coldness, edema, exertional pain, stabbing, and paresthesias) in the lower extremities at 12 weeks (p < 0.001). There were 18 patients with neuropathy in whom significant improvement was noted for 6 subjective symptoms at 12 weeks (p < 0.05). Adverse events considered to be drug-related were observed in 4 patients (4.3%), all of which were mild and resolved with discontinuation of the medication. Conclusions Beraprost is effective as a treatment for improving various subjective symptoms in the lower extremities, such as burning, coldness, edema, exertional pain, stabbing, and paresthesias, in diabetic patients with peripheral arterial disease.
The Problem of Extracting the Knowledge of Experts from the Perspective of Experimental Psychology

The first step in the development of an expert system is the extraction and characterization of the knowledge and skills of an expert. This step is widely regarded as the major bottleneck in the system development process. To assist knowledge engineers and others who might be interested in the development of an expert system, I offer (1) a working classification of methods for extracting an expert's knowledge, (2) some ideas about the types of data that the methods yield, and (3) a set of criteria by which the methods can be compared relative to the needs of the system developer. The discussion highlights certain issues, including the contrast between the empirical approach taken by experimental psychologists and the formalism-oriented approach that is generally taken by cognitive scientists.
Segmentation of Trajectories on Nonmonotone Criteria

In the trajectory segmentation problem, we are given a polygonal trajectory with n vertices that we have to subdivide into a minimum number of disjoint segments (subtrajectories) that all satisfy a given criterion. The problem is known to be solvable efficiently for monotone criteria: criteria with the property that if they hold on a certain segment, they also hold on every subsegment of that segment. To the best of our knowledge, no theoretical results are known for nonmonotone criteria. We present a broader study of the segmentation problem, and suggest a general framework for solving it, based on the start-stop diagram: a 2-dimensional diagram that represents all valid and invalid segments of a given trajectory. This yields two subproblems: (1) computing the start-stop diagram, and (2) finding the optimal segmentation for a given diagram. We show that (2) is NP-hard in general. However, we identify properties of the start-stop diagram that make the problem tractable and give a polynomial-time algorithm for this case. We study two concrete nonmonotone criteria that arise in practical applications in more detail. Both are based on a given univariate attribute function f over the domain of the trajectory. We say a segment satisfies an outlier-tolerant criterion if the value of f lies within a certain range for at least a given percentage of the length of the segment. We say a segment satisfies a standard deviation criterion if the standard deviation of f over the length of the segment lies below a given threshold. We show that both criteria satisfy the properties that make the segmentation problem tractable. In particular, we compute an optimal segmentation of a trajectory based on the outlier-tolerant criterion in O(n2log n + kn2) time and on the standard deviation criterion in O(kn2) time, where n is the number of vertices of the input trajectory and k is the number of segments in an optimal solution.