Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Characteristics and Outcomes of Posttransplant Lymphoproliferative Disorders Following Allogeneic Hematopoietic Stem Cell Transplantation in Korea

Between 1995 and 2003, seven cases of posttransplant lymphoproliferative disorder (PTLD) were identified among 1,116 patients who received allogeneic hematopoietic stem cell transplantations (HSCT) at Catholic HSCT Center (overall incidence 0.6%). Five (71.4%) patients had episodes of acute graft-versus-host-disease (GVHD) and were treated with steroids. Cervical lymphadenopathy was observed in most cases (71.4%), but clinical symptoms varied depending on the involved sites. Pathologic findings varied: 1 case of plasmacytic hyperplasia, 3 of polymorphic PTLD, 2 of diffuse large B-cell lymphoma, 1 of large T-cell lymphoma, which proved to be associated with Epstein-Barr virus (EBV). The proportion of EBV-negative PTLD was 33.3%. Five patients demonstrated a good response to treatment (treatment response rate 71.4%). The overall mortality was 42.8%, and one death was directly attributable to PTLD. The incidence of PTLD is expected to increase, based on the rising use of grafts from alternative donors and recent clinical features of PTLD manifested by a disseminated and fulminant nature. It is necessary to have a high level of suspicion when monitoring patients and readily adopt prompt and effective cellular immunotherapy for PTLD.
Adapting a WSJ trained part-of-speech tagger to noisy text: preliminary results

With the increase in the number of people communicating through internet, there has been a steady increase in the amount of text available online. Most such text is different from the standard language, as people try to use various kinds of short forms for words to save time and effort. We call that noisy text. Part-Of-Speech (POS) tagging has reached high levels of accuracy enabling the use of automatic POS tags in various language processing tasks, however, tagging performance on noisy text degrades very fast. This paper is an attempt to adapt a state-of-the-art English POS tagger, which is trained on the Wall-Street-Journal (WSJ) corpus, to noisy text. We classify the noise in text into different types and evaluate the tagger with respect to each type of noise. The problem of tagging noisy text is attacked in two ways; a) Trying to overcome noise as a post processing step to the tagging b) Cleaning the noise and then doing tagging. We propose techniques to solve the problem in both the ways and critically compare them based on the error analysis. We demonstrate the working of the proposed models on a Short Message Service (SMS) dataset which achieve a significant improvement over the baseline accuracy of tagging noisy words by a state-of-the-art English POS tagger.
Witnessing violence: The link to reactive aggression

The purpose of this study is to examine the association between witnessing violence and the development of aggressive behavior. Specifically, this study uses a multiple regression correlational (MRC) analytic approach to examine the association between witnessing violence and reactive aggression. It examines the associations between the participants' reactive aggression and post-traumatic stress and insecure attachment. One hundred adult male participants were recruited through classes at California State University San Bernardino to complete a questionnaire packet made up of 6 different surveys. The measures utilized were the Conflict Tactics Scale, the Adolescent Anger Rating Scale, the Inventory of Parent and Peer Attachment, Child Report of Post Traumatic Symptoms, Conduct Disorder, and the Modified Impact of Events Scales. The findings of this study show a positive correlation between reactive aggression and post-traumatic stress. There were also positive correlations between reactive aggression and insecure attachment in the areas of trust, communication and alienation. This study introduces areas
A third-order range separation imaging algorithm for manoeuvring platform SAR

ABSTRACT Occurrence of various travel trajectories poses a challenge in synthetic aperture radar (SAR) imaging. A method is proposed to solve this problem. After distance compression, the range equation is decomposed into terms that are not related to the position of the target points, and items that are not related to the azimuth parameters, to solve the problem of range migration correction and spatial-variant component correction. Then, the three-dimensional uniformly accelerated motion model is equivalent to the traditional uniformly accelerated linear model. Based on the equivalent model, azimuth bending correction and azimuth compression can be realized simply and quickly. The simulation results show that the proposed algorithm has good imaging effect. It can also get that the algorithm has wider applicability and can be used for SAR imaging in different motion models.
Clock-modulation based watermark for protection of embedded processors

This paper presents a novel watermark generation technique for the protection of embedded processors. In previous work, a load circuit is used to generate detectable watermark patterns in the ASIC power supply. This approach leads to hardware area overheads. We propose removing the dedicated load circuit entirely, instead to compensate the reduced power consumption the watermark power pattern is emulated by reusing existing clock gated sequential logic as a zero-overhead load circuit and modulating the clock-gating enable signal with the watermark sequence. The proposed technique has been validated through experiments using two ASICs in 65nm CMOS, one with an ARM Cortex-M0 microcontroller and one with a Cortex-A5 microprocessor. Silicon measurement results verify the viability of the technique for embedded processors. Furthermore, the proposed clock modulation technique demonstrates a significant area reduction, without compromising the detection performance. In our experiments an area overhead reduction of 98% was achieved. Through reuse of existing logic and reduction of watermark hardware implementation costs, the proposed clock modulation technique offers an improved robustness against removal attacks.
Communicating grief and loss online: Evaluating person-centered support messages

ABSTRACT This single-class activity expands current literature on person-centered messages by providing attention to message quality in mediated contexts. Students begin the activity by reviewing a hypothetical scenario in which a friend has posted about a family death loss on social media. After reviewing this scenario, students then create sample supportive messages that they could share with a grieving friend. Students are also asked to apply their knowledge about person-centered messages to evaluate other fictional support messages. Students who participate in this activity will be provided with additional skills for comforting grieving friends effectively. Courses: This single-class activity can be implemented in several courses, including interpersonal communication, the dark side of interpersonal communication, and family communication. Objectives: Students who complete this activity should be able to: (1) outline what qualities comprise a person-centered support message; (2) discuss why highly person-centered messages are effective in providing support to others; and (3) evaluate death loss support messages across levels of person centeredness.
Dynamic Adaptation of Projected Imperceptible Codes

In this paper we present an innovative adaptive imperceptible pattern projection technique that takes into account parameters of human visual perception. A coded image is temporally integrated into the projected image, which is invisible to the human eye but can be reconstructed by a synchronized camera. The embedded code is dynamically adjusted on the fly to guarantee its imperceptibility and to adapt it to the current camera pose. Linked with real-time flash keying, for instance, this enables in-shot optical tracking using a dynamic multi-resolution marker technique. A sample prototype has been realized that demonstrates the application of our method in the context of augmentations in television studios.
Challenges in Processing Colloquial Arabic

Processing of Colloquial Arabic is a relatively new area of research, and a number of interesting challenges pertaining to spoken Arabic dialects arise. On the one hand, a whole continuum of Arabic dialects exists, with linguistic differences on phonological, morphological, syntactic, and lexical levels. On the other hand, there are inter-dialectal similarities that need be explored. Furthermore, due to scarcity of dialect-specific linguistic resources and availability of a wide range of resources for Modern Standard Arabic (MSA), it is desirable to explore the possibility of exploiting MSA tools when working on dialects. This paper describes challenges in processing of Colloquial Arabic in the context of language modeling for Automatic Speech Recognition. Using data from Egyptian Colloquial Arabic and MSA, we investigate the question of improving language modeling of Egyptian Arabic with MSA data and resources. As part of the project, we address the problem of linguistic variation between Egyptian Arabic and MSA. To account for differences between MSA and Colloquial Arabic, we experiment with the following techniques of data transformation: morphological simplification (stemming), lexical transductions, and syntactic transformations. While the best performing model remains the one built using only dialectal data, these techniques allow us to obtain an improvement over the baseline MSA model. More specifically, while the effect on perplexity of syntactic transformations is not very significant, stemming of the training and testing data improves the baseline perplexity of the MSA model trained on words by 51%, and lexical transductions yield an 82% perplexity reduction. Although the focus of the present work is on language modeling, we believe the findings of the study will be useful for researchers involved in other areas of processing Arabic dialects, such as parsing and machine translation.
Spectropolarimetric imaging for object recognition

We have built an all-electronic spectro-polarimetric imaging camera utilizing an acousto-optic tunable filter and a liquid crystal variable retardation plate. This combination of rapidly adjustable parameters allows operations at 30/sec. frame rate, and near real time adaptability to changing target signatures. The spectral capability of the AOTF permits us to apply simultaneous, multiple wavelength filtering which greatly increases selectivity. Electronically agile polarization analysis adds a valuable signature feature for many scenarios. The adjustable retardation gives the capability to analyze and display not only linear polarization, but more generally, elliptical polarization as well. We have developed background suppression algorithms based on spectral and polarization signatures so that a wide variety of targets may be displayed with greatly enhanced contrast.
A Hybrid Genetic Algorithm Approach for Protein Secondary Structures

The importance of secondary protein structures is to help us to recognize many biological features, such as the structure and function of a protein, the evolutionary relation between proteins, and protein classification. Unfortunately, the secondary protein structures are hard to get from experimental analysis, and most researchers usually use predictive information instead of real structures. However, we want to look at the natures of protein secondary structures rather than putting too much focus on current approaches to protein secondary structure prediction. For the regularity of secondary protein structures, we define a schema and adopt an approach of evolutionary computation. The approach combines a clustering method and genetic algorithms to produce the schemata for the visible natures of protein secondary structures. There are two major roles of clustering algorithm, one is to generate part of the initial chromosomes in the genetic algorithms and the other is to assist schemata in predicting secondary protein structures. By performing the new approach, the accuracy of Q3 can be improved 12% more than the previous researches. Finally, we will demonstrate some schemata with interesting biological meaning
Population size, age structure and life cycle of Levant water frog, Pelophylax bedriagae (Camerano, 1882) (Amphibia: Anura: Ranidae) in Lake Sülüklü (Manisa)

Bu calismada, Levanten su kurbagasinin (Pelophylax bedriagae) Suluklu Gol’deki bazi populasyon parametreleri, yas yapisi ve ureme ekolojisi hakkinda bilgi edinilmesi amaclanmistir. Bu kapsamda Eylul 2014 - Agustos 2015 arasinda araliklarla arazi calismalari yapilmistir. Elde edilen verilere gore; P. bedriagae populasyonunun buyuklugu 6346 birey (5595–7199), yakalanma olasiligi 0,24, hayatta kalma orani 0,72 ve populasyona katilim orani 0,09 olarak hesaplanmistir. Populasyonda ortalama yas 3,6 yil (1 - 9) olup, genclerde 1 yil, erkeklerde 3,5 yil (1-7) ve disilerde 4,3 yil (1-9) olarak tespit edilmistir. Bireyler Şubat’in ikinci yarisindan itibaren hibernasyondan cikmakta ve Nisan ayinin ikinci yarisindan itibaren ampleksuslar gozlenmeye baslanmaktadir. En yuksek aktivite Nisan – Haziran arasinda olup, Temmuz ayindan itibaren kademeli olarak azalma gozlenmektedir. Laboratuvarda takip edilen yumurtalar 3–6 gun araliginda acilmis, metamorfozun laboratuvar kosullarinda 45–60 gunde, dogal ortaminda ise 75 gunde tamamlandigi gozlenmistir. Pelophylax bedriagae’yi tehdit eden baslica faktorler tarimsal amacli sulamaya bagli su seviyesindeki dusus, tarimsal ilaclarin gole karismasi ve predasyon baskisidir.
Topological Map Building for Mobile Robots Using Omnidirectional Vision ∗

The long term aim of our research is to find an on-line, probabilistic mapping algorithm for mobile robot navigation in both indoor and outdoor environments. Needless to say, there are many challenges. Outdoor environments can be huge, unstructured and dynamic. Many of the existing solutions to the robotic mapping problem indoors will not be applicable outdoors [1], simply because the methods employed do not scale well to larger and more complex environments. Our first approach is to use a topological representation of the world. Later, metric information or additional topologies could be added to form a hybrid map, which would allow the robot to perform specialized tasks. Topological approaches to the robotic mapping problem use landmarks to define the nodes (places) of the map. The gathering of landmarks into distinct places is a largely unsolved problem. Existing approaches include defining the places by hand, unsupervised clustering algorithms [2], and detection of “distinctive places” [3]. If the whole set of landmarks is available, the mapping problem can be viewed as a search problem to find the best topological map that fits the observed landmarks (and other sensor data, such as odometry). The landmarks can be artificial landmarks such as beacons, or natural occurring features extracted by sensors such as laser range finders, sonars or cameras. When building the topological map, one must also consider the correspondence problem and perceptual aliasing (multiple places have similar appearance); we wish to maintain a one-to-one correspondence between nodes in our map representation and places in the real world. The classical – and very successful – approaches to this problem are various probabilistic techniques [1]. However, probabilistic approaches can be computationally expensive, often growing exponentially with the size of the map [4]. The method we propose can be considered probabilistic (because the link likelihood is determined by visual similarity of image sequences) and avoids the computational problem of considering multiple hypotheses.
Processing complex RDF queries over P2P networks

In large-scale distributed systems, information is typically generated decentralized. However, for many applications it is desirable to have a unified view on this knowledge, allowing to reason about it and to query it without regarding the heterogeneity of the underlying systems. In this context, two main requirements have to be fulfilled. On the one hand, a retrieval system has to be semantically rich, in order to be able to cope with and mediate between different schemas, and on the other hand it has to be scalable to large numbers of information sources. The dynamic nature of information makes the problem even worse.Within this paper, we propose a solution to this problem. We describe a DHT-based peer-2-peer network storing knowledge in the form of RDF triples. The query evaluation algorithm allows to use arbitrary query patterns, and evaluates the query with respect to taxonomical reasoning. Thus the system combines expressivity and scalability. Although we describe the whole system, the focus of this paper is the query evaluation.The system is generic by nature and suitable for numerous different applications. We describe an example application stemming from the Semantic Grid.
Virtual Sense of Community in a World of Warcraft® Storytelling Open Forum Thread

World of Warcraft® (WoW), a massive multiplayer online role-playing game (MMORPG) extends to its members a virtual landscape of live gaming opportunities through such platforms as “dice” rolled character stats, open-ended story development, and interactive AI. These affordances are underpinned by a kind of virtual sense of community bringing players together in order to develop relationships and the self, adventure together, build up wealth, and overcome obstacles in order to complete quests. In addition to live game-play (or “in-world”) communities, WoW residents create alternative communities through rich online forums—here, new members are recruited into guilds, disputes are spawned and slayed, and seasoned warriors reminisce over worlds and lives that once- were. However, a third type of community is also evident through particular threads crafted within forums specifically for collaborative storytelling (or roleplaying). This paper examines sense of community—a sense of “belonging to, importance of, and identification with a community”—through one particular thread, “The Darkening Grove Tavern” under the forum World’s End Tavern using an adaptation of McMillan and Chavis’ theory and Boellstorff, Nardi, Pearce & Taylor’s ethnographic data collection methodology for qualitative analysis of virtual worlds . Findings from players’ story text (or “turns”) suggest that online storytelling forum threads exhibit a linguistically and semiotically branded sense of virtual community.
Social Cohesion, Social Capital and the Neighbourhood

In current theoretical and policy debates concerning social cohesion, the neighbourhood has re-emerged as an important setting for many of the processes which supposedly shape social identity and life-chances. It is in this context of a renewal of interest in local social relations and particularly the deployment of notions of social capital that this paper offers a critical review of a wide-ranging literature. The paper explores initially and briefly the idea that societies face a new crisis of social cohesion and outlines the key dimensions of societal cohesion. The core of the paper is then devoted to an examination of where the contemporary residential neighbourhood fits into these wider debates, particularly in relation to the interaction between social cohesion and social capital. In this context, some of the key debates around the concept of social capital are outlined. In moving beyond abstraction, the paper also shows how social capital can be broken down into relevant domains for policy action at the neighbourhood level and how concepts such as social cohesion and social capital can be operationalised for research purposes.
The Aging Human Brain

The human brain weighs on average about three pounds, consists of 200 billion cells. Surprisingly, there are only two categories of brain cells, neurons and glia, but more than 50 different cellular subtypes. Nerve cells or neurons are specialized cells that are electrically excitable, and processes and transmit information to other neurons and cells through electrochemical signaling via membrane‐to‐membrane junctions. Neurons are the basic structural and functional units of the human nervous system. There are about 100 billion neurons, and these make an additional 100 trillion connections to other cells at a velocity up to 250 miles per hour.
Aging Monitoring Methodology for Built-In Self-Test Applications

The high integration level, complexity and performance achieved in new nanometer technologies make IC (Integrated Circuits) products very difficult to test. Moreover, long-term operation brings aging cumulative degradations, and new processes and materials lead to emerging defect phenomena. The consequence is obtaining products with increased variability in their behavior, more susceptible to delay faults and with reduced expected lifecycle. The main purpose of this work is twofold, as explained in the following. First, a new software tool is presented to generate HDL (Hardware Description Language) BIST (Built-In Self-Test) structures, aiming delay faults, and insert the new auto-test functionality in generic sequential CMOS circuits. The BIST methodology used implements a scan based BIST approach, using a new BIST controller to implement the delay-fault techniques Launch-On-Shift (LOS) and Launch-On-Capture (LOC). Second, it will be shown that multi-VDD tests in circuits with BIST infra-structures can be used to detect gross delay faults during on-field operations, and consequently can be used as an aging sensor methodology during circuits’ lifecycle. The discrete set of multi-VDD BIST sessions generates a Voltage Signature Collection (VSC), and the presence of a delayfault (or a physical defect) modifies the VSC collection, allowing the aging sensor capability. The proposed Design for Testability (DFT) method and tool are demonstrated with extensive SPICE simulations using benchmark circuits.
Towards Multi-paper Summarization Using Reference Information

This paper presents a system to support writing a survey of a specific domain. The system utilizes reference information that consists of reference relationships between papers and the information derived from the description around citations. We think the following are inevitable for writing a survey : collecting papers of the specific domain, and understanding their essence and differences among them. Therefore, we firstly extract fragments of papers where the author describes the essence of a referred paper and the differences between his paper and it (we call them reference areas). Then with the information of reference areas, we identify the types of reference relationships that indicate the reasons for citations(we call them reference types). These types make it possible to collect papers in the same domain. The system can display the collection of the papers. It can also show abstracts and reference areas of the collected papers. With the system, we can understand the relationships between the collected papers.
Information Reconstruction via Discrete Optimization for Agricultural Census Data

In the case of large-scale surveys, such as a Census, data may contain errors or missing values. An automatic error detection and correction procedure is therefore needed. We propose here an approach to this problem based on Discrete Optimization. The treatment of each data record is converted into a mixed integer linear programming model and solved by means of state-of-the-art branch and cut procedures. Results on real-world Agricultural Census data show the effectiveness of the proposed procedure.