Miracle-dz/UniFAR-FTUs huggingface dataset:
PRECISE AIRBORNE LIDAR SURVEYING FOR COASTAL RESEARCH AND GEOHAZARDS APPLICATIONS

The monitoring and analysis of many natural hazards requires repeated measurements of a topographic surface whose change reflects some geologic or hydrologic process. The development of airborne laser surface mapping (ALSM) allows the study of natural hazards over areas tens to hundreds of kilometers in extent with a horizontal resolution of 1 meter or less and a vertical accuracy of 0.10-to-0.15m. Change detection requires that repeated ALSM surveys be precise and accurate. Repeatability is a function of the stability and calibration of the instrument, the accuracy of GPS aircraft trajectories, the density and completeness of ALSM data coverage, the availability of “ground truth” information, and the accuracy and flexibility of ALSM data classification. Since 1997 The University of Texas at Austin (UT) has mapped various portions of the Texas Gulf coast using several small-footprint, scanning ALSM systems developed by Optech, Inc. During summer 2000, UT comprehensively mapped the Texas coast from Sabine Pass on the Texas-Louisiana border to the mouth of the Rio Grande River. These data provide a series of Gulf shorelines for estimating beach erosion rates and computing volumetric sand loss. The high-resolution beach and dune topography derived from ALSM will help characterize the susceptibility of the coast to hurricane overwash and storm-related flooding. In another project UT collaborated with Optech and the U.S. Geological Survey in March 2000 to survey fifteen municipalities in Honduras with ALSM as part of the USAID Hurricane Mitch Recovery program. Digital elevation models produced from these data are being used for flood and landslide hazard analysis. During these and other projects, UT began implementing procedures for instrument calibration, data classification, and ground GPS surveying that enhance the repeatability of our ALSM surveys.
Hypergraph coarsening for image superpixelization

Image segmentation is a hard task and many methods have been developed to alleviate its difficulties. A common preprocessing step designed for this purpose is to compute an over-segmentation of the image, often referred to as superpixels. In this paper, we propose a new approach to superpixels computation. In a first step, a hypergraph-based representation of the image is built. Then, a coarsening approach is operated on the resulting hypergraph to group pixels which belong to the same homogeneous region. This leads to a smaller hypergraph where each component represents a superpixel of the image. Our approach is very fast and can deal with great sized images. Its reliability have been tested on several real images from nature scenes with comparison to other methods. We show in particular that hypergraphs offer a more accurate image representation than graphs.
Cooperative Transmission: A Reality Check Using Experimental Data

Wireless transmission based on cooperation promises to bring performance improvements in multi-node networks. Several cooperative schemes have appeared in the literature, and in most cases have been assessed under simplified assumptions for the channel model. Experimental data for cooperative transmission are difficult to obtain because they should provide simultaneous characterization of at least three links. In this paper we present measurements that involve two access points (APs) and two user terminals, each of which is equipped with 4 antennas, in an indoor office environment. The data indeed allow for the simultaneous characterization of the multiple input-multiple output (MIMO) links from the APs to the user terminals and between the user terminals. We use these measurements to practically assess several schemes for cooperative transmission.
Dynamic-SCFlip Decoding of Polar Codes

This paper proposes a generalization of the recently introduced successive cancellation flip (SCFlip) decoding of polar codes, characterized by a number of extra decoding attempts, where one or several positions are flipped from the standard SC decoding. To make such an approach effective, we first introduce the concept of higher order bit flips and propose a new metric to determine the bit flips that are more likely to correct the trajectory of the SC decoding. We then propose a generalized SCFlip decoding algorithm, referred to as dynamic-SCFlip (D-SCFlip), which dynamically builds a list of candidate bit flips, while guaranteeing that the next attempt has the highest probability of success among the remaining ones. Simulation results show that D-SCFlip is an effective alternative to SC-list decoding of polar codes, by providing very good error correcting performance, with an average computation complexity close to the one of the SC decoder.
Squamous Cell Carcinoma Cause Malignant Conversion in a Mouse Model for to ras Smad 7 but not Smad 6 Cooperates with Oncogenic

Smad7 and Smad6 are inhibitory Smads that block transforming growth factor(TGF) superfamily signal transduction. Smad7 is overexpressed in chemically induced mouse epidermal tumors, where oncogenic activation of c-ras is a frequent event. To test the role of Smad7 overexpression in tumor progression, we used retroviruses to transduce Smad7 or Smad6 and v-ras into primary mouse keratinocytes. By itself, Smad7 transiently enhanced keratinocyte proliferation, blocked normal differentiation, and induced keratin 8, a marker of malignant conversion, but did not cause tumor formation. Smad7 extended the in vitro life span, suppressed senescence, and increased transformation frequency 3-fold of primary keratinocytes coexpressing v-ras. Smad7/v-ras coinfected keratinocytes rapidly progressed to squamous cell carcinomas in vivo, whereas pBabe/v-rasor Smad6/v-ras-transduced keratinocytes formed only benign papillomas. Smad7/v-ras tumors had elevated proliferation and defective nuclear localizaton of Smad2, Smad3, and Smad5, whereas only Smad5 was altered in Smad6/v-ras tumors. Smad7 overexpression in vitro induced epidermal growth factor (EGF)-like growth factors TGF, heparin binding-EGF, amphiregulin, and EGF receptor tyrosine phosphorylation as well as the EGF-CFC growth factor cripto-1. TGFand cripto-1 were also overexpressed in Smad7/v-ras tumors. These results suggest that Smad7 overexpression accelerates tumor progression through inhibition of TGFsuperfamily signaling and upregulation of the EGF-like superfamily of growth factors. This is the first demonstration that Smad7 overexpression can cause malignant conversion in a multistage cancer model and suggests that it may have an important role in the pathogenesis of human cancer.
Job recommendation with Hawkes process: an effective solution for RecSys Challenge 2016

The RecSys Challenge 2016 focuses on the prediction of users' interest in clicking a job posting in the career-oriented social networking site Xing. Given users' profile, the content of the job posting, as well as the historical activities of users, we aim in recommending top job postings to users for the coming week. This paper introduces the winning strategy for such a recommendation task. We summarize several key components that result in our leading position in this contest. First, we build a hierarchical pairwise model with ensemble learning as the overall prediction framework. Second, we integrate both content and behavior information in our feature engineering process. In particular, we model the temporal activity pattern using a self-exciting point process, namely Hawkes Process, to generate the most relevant recommendation at the right moment. Finally, we also tackle the challenging cold start issue using a semantic based strategy that is built on the topic modeling with the users profiling information. Our approach achieved the highest leader-board and full scores among all the submissions.
A dynamic bandwidth pricing mechanism based on trust management in P2P streaming systems

Peer-to-peer (P2P) streaming systems rely on that peers voluntarily share their bandwidth to maintain high performance. Credit-based incentive mechanisms are widely used to encourage peers to share more bandwidth. However, in credit-based mechanisms, how to set a suitable bandwidth price is a critical issue. In this paper, we propose a new dynamic bandwidth pricing mechanism based on Stackelberg game and trust management. This mechanism can dynamically adjust the bandwidth price based on peers' trust values: the lower trust a peer has, the higher price the peer pays. A Stackelberg game is formulated to obtain peers' optimal bandwidth pricing and purchasing strategies. Through mathematical analysis, we derive the equilibrium of our proposed game and an algorithm to obtain equilibrium is also proposed. Extensive simulations show that our proposed mechanism can effectively induce peers to share more bandwidth, maintain system fairness and defend typical data pollution attack to guarantee the robustness of the system.
On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning

Temporal-difference-based deep-reinforcement learning methods have typically been driven by off-policy, bootstrap Q-Learning updates. In this paper, we investigate the effects of using on-policy, Monte Carlo updates. Our empirical results show that for the DDPG algorithm in a continuous action space, mixing on-policy and off-policy update targets exhibits superior performance and stability compared to using exclusively one or the other. The same technique applied to DQN in a discrete action space drastically slows down learning. Our findings raise questions about the nature of on-policy and off-policy bootstrap and Monte Carlo updates and their relationship to deep reinforcement learning methods.
Using salient region constraints on Active Appearance Model initialization for facial feature extraction

Due to the high robustness, Active Appearance Model algorithm (AAM) has been adopted to find face feature points. However, if the initial position of the AAM does not properly cover these feature points, AAM will converge to an illogical location. To resolve this problem, this paper develops salient region constraints on AAM initialization for facial feature extraction. In this approach, we first identify the mouth region and adopt a mouth-constrained mean model as the initialization of the AAM. By this approach, the initial position can be placed closer to the target. The experiments show that the method is effective.
Recycling Secondary Index Structures

Several important database reorganization techniques move tuples in a table from one location to another in a single pass. For example, the Mariposa distributed database system frequently moves or copies tables between sites. However, moving a table generally invalidates the pointers contained in its secondary indices. Because index reconstruction is extremely resource-intensive, table movement has been considered a expensive operation. In this paper, we present simple, efficient mechanisms for translating index pointers. We also demonstrate their effectiveness using performance measurements of an implementation in Mariposa. Use of these mechanisms will enable parallel and distributed systems like Mariposa to move tables more freely, pro viding many more options for performance-enhancing reorganizations of the database.
Literature from the MEDLINE Database Using Keyword Scoring

MOTIVATION: It would be useful to be able to retrieve a ranked publication list relevant to topics of interest. METHODOLOGY: This novel approach uses semantics built into the Medical SubHeading (MeSH) hierarchy. A training set of papers is constructed, each annotated with MeSH terms of interest (e.g. Stem Cell or some child in its subtree). Frequencies of nouns are computed, and ratios calculated of noun frequencies in the training set to frequencies in MEDLINE. Ratios scored abstracts in the training set, and on an equal number of papers randomly selected from MEDLINE. Performance of the relevance-prediction algorithm was benchmarked by counting Stem Cell papers retrieved after merging ranked lists of scored papers and selecting increasing numbers of top papers. RESULTS: 16 MeSH keywords were used to build a training set of 99,020 papers known to be relevant to Stem Cells. 43,328 and 11,773 nouns were extracted from MEDLINE and the training set, respectively. From the training set, 2,078 keywords occurred more than 100 times in the literature, and top-scoring keywords were verified to be relevant to stem cells. Benchmarking the relevance-prediction algorithm reported an 88% recall and precision of stem cell papers when half of the merged list was selected. 3 Acknowledgments I would like to thank my advisors Dr. Miguel Andrade and Dr. Tony White for their guidance and advice; my colleagues Dr. for their patience with my infinite stream of newbie questions; my parents for bringing me into this world and always encouraging me towards becoming an outstanding member of society; and last but not least Ms. Evelyne Chevrier, for inspiring me when I need it most. 4 Table of Contents 1 Introduction 6 1.1 Goals of Literature Mining 6 1.2 Progress in the field of Literature Mining 7 1.3 Use of Keywords and Hierarchies 13 1. Methodology 16 2.1 Gather databases: 16 2.2 Generate a list of stem cell MeSH keywords: 16 2.3 Extract papers about stem cells: 16 2.4 XML document validation: 17 2.5 Moving a range of files: 17 2.6 Robustly extract papers about stem cells: 17 2.7 Combine lists of stem cell papers: 17 2.8 Extract nouns from MEDLINE papers. 18 2.9 Extract nouns from stem cell papers: 18 2.10 Compute the contrast between stem cell papers and the rest of MEDLINE: 18 2.11 Score papers: 18 2.12 Benchmarking: 19 3 Results 20 3.2 Generate a list of stem cell MeSH keywords: 20 3.7 …
Curricular Exposure to Postgraduate Residency Training Through an Introductory Pharmacy Practice Experience

Objective. To evaluate the impact of a residency-focused introductory pharmacy practice experience (IPPE) on student perceived knowledge of and attitudes toward postgraduate residency training. Methods. Second- and third-year student pharmacists completed a required four-hour experience at a residency training site. Students completed a five-item survey before and after the experience, indicating their perceived knowledge of residency training components as well as their own postgraduate plans. Students also submitted a written reflection following the experience. Paired t tests were used to compare pre- and post-survey responses. Qualitative analysis was completed to identify common themes in student reflections and code for positive, neutral, or negative student experience. Results. A total of 276 students completed the Introduction to Postgraduate Residency Training IPPE in summer 2016. Post-experience survey responses indicated a significant increase in students’ perceived knowledge of residency programs; however, plans to pursue residency training did not significantly change after completing the experience. Twenty-five independent themes were identified in reading student reflections, with the most common theme (included in 55% of reflections) being that the experience “clarified resident day-to-day responsibilities. ” The majority (95%) of students perceived the experience as valuable. Conclusion. A residency-focused IPPE increased student pharmacists’ perceptions of knowledge about postgraduate residency training and was viewed by students as a beneficial experience.
A global transformation approach to RBF neural network learning

In this paper we propose to train the RBF neural network using a global descent method. Essentially, the method imposes a monotonic transformation on the training objective to improve numerical sensitivity without altering the relative orders of all local extrema. A gradient descent search which inherits the global descent property is derived to locate the global solution of an error objective. Numerical examples comparing the global descent algorithm with a gradient-based line-search algorithm shows superiority of the proposed global descent algorithm in terms of speed of convergence and quality of solution achieved.
Reliability evaluation of Web-based software applications

In diverse industrial and academic environments, the quality of software has been evaluated (validated) using different analytic studies. It is common practice in these environments to use statistical models for the assurance, control and evaluation of the quality of a software product or process. A number of industries in the safety-critical sector are forced nowadays to use such processes by industry-specific standards (e.g., the DO-178B standard for airborne software systems). The contribution of the present work is focused on the development of a methodology for the evaluation and analysis of the reliability of Web-based software applications. We tested our methodology in a Web-based software system and used statistical modeling theory for the analysis and evaluation of the reliability. The behavior of the system under ideal conditions was evaluated and compared against the operation of the system executing under real conditions. The results obtained demonstrated the effectiveness and applicability of our methodology.
Skin Electroporation: Effects on Transgene Expression, DNA Persistence and Local Tissue Environment

Background Electrical pulses have been used to enhance uptake of molecules into living cells for decades. This technique, often referred to as electroporation, has become an increasingly popular method to enhance in vivo DNA delivery for both gene therapy applications as well as for delivery of vaccines against both infectious diseases and cancer. In vivo electrovaccination (gene delivery followed by electroporation) is currently being investigated in several clinical trials, including DNA delivery to healthy volunteers. However, the mode of action at molecular level is not yet fully understood. Methodology/Principal Findings This study investigates intradermal DNA electrovaccination in detail and describes the effects on expression of the vaccine antigen, plasmid persistence and the local tissue environment. Gene profiling of the vaccination site showed that the combination of DNA and electroporation induced a significant up-regulation of pro-inflammatory genes. In vivo imaging of luciferase activity after electrovaccination demonstrated a rapid onset (minutes) and a long duration (months) of transgene expression. However, when the more immunogenic prostate specific antigen (PSA) was co-administered, PSA-specific T cells were induced and concurrently the luciferase expression became undetectable. Electroporation did not affect the long-term persistence of the PSA-expressing plasmid. Conclusions/Significance This study provides important insights to how DNA delivery by intradermal electrovaccination affects the local immunological responses of the skin, transgene expression and clearance of the plasmid. As the described vaccination approach is currently being evaluated in clinical trials, the data provided will be of high significance.
The Charge Plasma P-N Diode

A simulation study on a new rectifier concept is presented. This device basically consists of two gates with different workfunctions on top of a thin intrinsic or lowly doped silicon body. The workfunctions and layer thicknesses are chosen such that an electron plasma is formed on one side of the silicon body and a hole plasma on the other, i.e., a charge plasma p-n diode is formed in which no doping is required. Simulation results reveal a good rectifying behavior for well-chosen gate workfunctions and device dimensions. This concept could be applied for other semiconductor devices and materials as well in which doping is an issue.
Towards Summarizing Popular Information from Massive Tourism Blogs

In this work, we propose a research method to summarize popular information from massive tourism blog data. First, we crawl blog contents from website and segment each of them into a semantic word vector separately. Then, we select the geographical terms in each word vector into a corresponding geographical term vector and present a new method to explore the hot tourism locations and, especially, their frequent sequential relations from a set of geographical term vectors. Third, we propose a novel word vector subdividing method to collect the local features for each hot location, and introduce the metric of max-confidence to identify the Things of Interest (ToI) associated to the location from the collected data. We illustrate the benefits of this approach by applying it to a Chinese online tourism blog data set. The experiment results show that the proposed method can be used to explore the hot locations, as well as their sequential relations and corresponding ToI, efficiently.
Human Neuroscience

In addition, a number of researchers have suggested that these lateral PFC defi cits may be the result of – at least in part – dysregulated input from the midbrain dopamine (DA) system (Braver and Cohen, 2000; Braver et al., 1999). In our work, we have developed a theoretical framework variously termed context processing, goal maintenance, or guided activation, which suggests that goal-related information is represented and maintained in lateral PFC to guide, bias, and constrain ongoing task processing (Cohen et al. Further, we have argued that dysfunction in lateral PFC, and more specifi cally disrupted DA-PFC interactions , results in patients with schizophrenia having impairments in their ability to activate, update, and maintain goal-information based on contextual cues (Braver et al., 1999). More recently, we have refi ned this idea through the Dual Mechanisms of Control (DMC) account, which postulates two distinct modes of cognitive control: proactive and reactive (Braver et al., 2007, 2009). Proactive control depends upon the active maintenance of goal-related information in a sustained/anticipatory manner prior to the occurrence of cognitively demanding events. In contrast, reactive control is late-acting and is mobilized only as needed, such as in response to the detection of a high-interference event. The reactive form of
No Association of BDNF, COMT, MAOA, SLC6A3, and SLC6A4 Genes and Depressive Symptoms in a Sample of Healthy Colombian Subjects

Background. Major depressive disorder (MDD) is the second cause of years lived with disability around the world. A large number of studies have been carried out to identify genetic risk factors for MDD and related endophenotypes, mainly in populations of European and Asian descent, with conflicting results. The main aim of the current study was to analyze the possible association of five candidate genes and depressive symptoms in a Colombian sample of healthy subjects. Methods and Materials. The Spanish adaptation of the Hospital Anxiety and Depression Scale (HADS) was applied to one hundred eighty-eight healthy Colombian subjects. Five functional polymorphisms were genotyped using PCR-based assays: BDNF-Val66Met (rs6265), COMT-Val158Met (rs4680), SLC6A4-HTTLPR (rs4795541), MAOA-uVNTR, and SLC6A3-VNTR (rs28363170). Result. We did not find significant associations with scores of depressive symptoms, derived from the HADS, for any of the five candidate genes (nominal p values >0.05). In addition, we did not find evidence of significant gene-gene interactions. Conclusion. This work is one of the first studies of candidate genes for depressive symptoms in a Latin American sample. Study of additional genetic and epigenetic variants, taking into account other pathophysiological theories, will help to identify novel candidates for MDD in populations around the world.