Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Infection in Allogenic Hematopoietic Stem Cell Transplantation in Patients with Acute Myeloid Leukemia

Background: Allogeneic hematopoietic stem cell transplantation (HSCT) is a potentially cure for acute myeloid leukemia (AML). Patients who undergone HSCT are at increased risk of infection due to impaired immunity. Objective: To evaluate the rate of bacterial, viral and fungal infection and its relationship with 2-year overall survival of AML patients who had undergone HSCT. Methods: This was a retrospective cross-sectional study of 49 patients who underwent allogenic bone marrow transplantation (BMT) from full-matched donors at BMT Center, Imam Khomeini Hospital Complex, Tehran, Iran, from 2006 to 2013. All autologous transplantations and promyelocytic leukemia (PML) transplantations were excluded. Results: All patients, except for one, had fever for a mean of 7 days post-transplantation and received broad-spectrum antibiotic. The rate of severe sepsis was 6.1%. None of the patients developed fungal infection during admission. The rate of admission due to sepsis after discharge was 27% in the alive group (mean onset of 54 days), and 73% in the deceased group (mean onset of 52 days) (p<0.05). The most common site of infection was lung (70%). The rate of cytomegalovirus (CMV) antigenemia (positive PP65) was 20% during the 2-year period after HSCT. Conclusion: The rate of infection was a negative prognostic factor for 2-year overall survival. The rate of CMV antigenemia is less than similar studies (51%), which could be due to full-matched donor-recipients requiring less immunosuppression.
Towards change validation in dynamic system updating frameworks

Dynamic Software Updating (DSU) provides mechanisms to update a program without stopping its execution. An indiscriminate update that does not consider the current state of the computation, potentially undermines the stability of the running application. Determining automatically a safe moment, the time that the updating process could be started, is still an open crux that usually neglected from the existing DSU systems. The program developer is the best one who knows the program semantics and the logical relations between two successive versions as well as the constraints which should be respected in order to proceed with the update. Therefore, a set of meta-data has been introduced that could be exploited to explain the constraints of the update. These constraints should be considered at the dynamic update time. Thus, a runtime validator has been designed and implemented to verify these constraints before starting the update process. The validator is independent of existing DSU systems and can be plugged into DSUs as a pre-update component. An architecture for validation has been proposed that includes the DSU, the running program, the validator, and their communications. Along with the ability to describe the restrictions by using meta-data, a method has been presented to extract some constraints automatically. The gradual transition from the old version to the new version requires that the running application frequently switches between executing old and new code for a transient period. Although this swinging execution phenomenon is inevitable, its beginning can be selected. Considering this issue, an automatic method has been proposed to determine which part of the code is unsafe to participate in the swinging execution. The method has been implemented as a static analyzer which can annotate the unsafe part of the code as constraints. This approach is demonstrated in the evolution of the various versions of three different longrunning software systems and compared to other approaches. Although the approach has been evaluated by evolving various programs, the impact of different changes in the dynamic update is not entirely clear. In addition, the study of the effect of these changes can identify code smells on the program, regarding the dynamic update issue. For the first time, the code smells have been introduced that may cause a run-time or syntax error on the dynamic update process. A set of candidate error-prone patterns has been developed based on programming language features and possible changes for each item. This set of 75 patterns is inspected by three distinct DSUs to identify problematic cases as code smells. Additionally, error-prone patterns set can be exploited as a reference set by other DSUs to measure own flexibility.
A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification

Supervised topic classifiers for Twitter and other media sources are important in a variety of long-term topic tracking tasks. Unfortunately, over long periods of time, features that are predictive during the training period may prove ephemeral and fail to generalize to prediction at future times. For example, if we trained a classifier to identify tweets concerning the topic of “Celebrity Death”, individual celebrity names and terms associated with these celebrities such as “Nelson Mandela” or “South Africa” would prove to be temporally unstable since they would not generalize over long periods of time; in contrast, terms like “RIP” (rest in peace) would prove to be temporally stable predictors of this topic over long periods of time. In this paper, we aim to design supervised learning methods for Twitter topic classifiers that are capable of automatically downweighting temporally unstable features to improve future generalization. To do this, we first begin with an oracular approach that chooses temporally stable features based on knowledge of both train and test data labels. We then search for feature metrics evaluated on only the training data that are capable of recovering the temporally stable features identified by our oracular definition. We next embed the top-performing metric as a temporal stability regularizer in logistic regression with the important property that the overall training objective retains convexity, hence enabling a globally optimal solution. Finally, we train our topic classifiers on 6 Twitter topics over roughly one year of data and evaluate on the following year of data, showing that logistic regression with our temporal stability regularizer generally outperforms logistic regression without such regularization across the full precision-recall continuum. Overall, these results establish a novel regularizer for training longterm temporally stable topic classifiers for Twitter and beyond.
Compensação Total e Parcial de Distorções Harmônicas de Corrente Utilizando Controlador Proporcional Ressonante

O disturbio harmonico e um problema que pode ser resolvido utilizando filtros ativos conectados ao ponto de acoplamento comum (PAC). Os sistemas de geracao distribuida (GD) baseados em inversores depotencia podem operar como filtros ativos alem de fornecer energia a rede eletrica. Este trabalho propoe odesenvolvimento de um controlador proporcional ressonante (PR) adaptativo para os inversores trifasicos que operam como fontes de tensao controlados por corrente, como forma de controlar a potencia injetada na rede eletrica, alem de realizar a compensacao parcial ou total de componentes harmonicas de corrente no PAC. Os resultados mostraram que o controlador PR adaptativo poderia mitigar parcialmente ou totalmente a distorcao harmonica de corrente causada por uma carga nao linear local conectada ao PAC, mantendo a distorcao harmonica total (DHT) e individual (DHI) dentro de valores maximos aceitaveis.
The design of an online classroom and implementation of an activity

In the international academic library world there are many changes taking place. Information literacy classes are run by libraries in order to assist students to effectively manage the vast amounts of information and their different formats that are now available. The IL courses are designed to enable students to " locate, manage, critically evaluate, and use information for problem solving, research, decision making, and continued professional development" (Orr, Appleton and Wallin as cited in Kasowitz-Scheer and Pasqualoni, 2002).
Efficient DES Key Search

Abstract. Despite recent improvements in analytic techniques for attacking the Data Encryption Standard (DES), exhaustive key search remains the most practical and efficient attack. Key search is becoming alarmingly practical. We show how to build an exhaustive DES key search machine for $1 million that can find a key in 3.5 hours on average. The design for such a machine is described in detail for the purpose of assessing the resistance of DES to an exhaustive attack. This design is based on mature technology to avoid making guesses about future capabilities. With this approach, DES keys can be found one to two orders of magnitude faster than other recently proposed designs. The basic machine design can be adapted to attack the standard DES modes of operation for a small penalty in running time. The issues of development cost and machine reliability are examined as well. In light of this work, it would be prudent in many applications to use DES in a triple-encryption mode.
Aesthetic Theory and Aesthetic Science

There is currently a great deal of fundamental disagreement in research into aesthetic response. The remedy is ideally integration, wherein researchers in the different aesthetic sciences and humanistic studies converge on a common conception of what they are trying to explain, even if they continue to disagree about how to explain it. If it is to be successful, this convergence will require that researchers in both the scientific and humanistic disciplines be sensitive to the limitations that are inherent in each of these two different approaches. On the one hand, we should not expect a conception of aesthetic response that is productive for research across disciplines to be given a precise a priori definition. On the other hand, aesthetic science must acknowledge that aesthetic response is embedded in critical practice, about which the humanities have a lot to say.
Kinect Projection Mapping

Spatial augmented reality allows users to create a projected virtual environment on irregular surfaces. This demands an accurate Camera-Projector calibration process in order to produce precise 3D information to match the real object. This paper presents a framework to process data achieved from a calibration of a Kinect-Projector system in visualization applications, allowing the user to create an augmented reality environment without having extensive process of the Camera-Projector calibration, while maintaining a precise calibration to the projection on irregular surfaces. Additionally, different calibration techniques were evaluated in order to demonstrate the better approaches.
Bayesian Parameter Estimation in LDA

Latent Dirichlet Allocation (LDA) probabilistic topic model is widely used in text mining, natural language processing and so on. But LDA's mathematical theory is particularly complex, thus it is very difficult to understand LDA for a novice. In order to more quickly and easily learn LDA, and further promote its application, this paper will deeply analyze LDA from the perspective of Bayesian parameter estimation. At first we explain the advantage of Bayesian parameter estimation by an instance, and then introduce a simple Bayesian Unigram model. Next based on the simple Bayesian Unigram model and PLSA model, a full Bayesian probabilistic topic model—LDA is presented. In order to more quickly understand LDA model, and further promote its application, this paper will start from Bayesian parameter estimation, and then analyze the mathematical theory of LDA model from the perspective of Bayesian parameter estimation. This paper is organized as follows. In Section 2 we introduce Bayesian parameter estimation based on an illustrative example. Compared to related PLSA model, LDA model with Bayesian parameter estimation is presented in Section 3. Finally, Section 4 presents summary.
A Onipresença do Design

Este artigo discute os desdobramentos do conceito e das práticas do design a partir de seu núcleo semântico que se encontra na noção de projeto.Assim considerado, os inumeráveis níveis e facetas de materialização e operacionalidade do design derivariam da fonte primeira que reside na projeção mental do ato de conceber, uma projeção que é colocada à prova no teste de sua realização tendo em vista os matérias, meios e técnicas de que cada momento histórico dispõe. Tomando como base a pirâmide de Mensvoort dos degraus ascendentes que são percorridos por uma invenção tecnológica, são explorados os níveis de penetração e aceitação dos designs na vida social.
The Role of Reuse in Introducing Software Engineering Principles in a Computer Science Second Course

ii ACKNOWLEDGMENTS In the effort to complete this final degree requirement, I find myself indebted to my adviser, Murali Sitaraman. Over the past year, his willingness to assist me in the preparation of various papers, as well as this report, has been invaluable and very much appreciated. Apart from his guidance in these endeavors, I am also grateful for his introducing me to the many current topics in the area of software reuse. My gratitude is also expressed toward Frances VanScoy and Doug Harms, members of my project committee. I consider it an honor to have them participate in this capacity.
Windows NT Server基础知识

ＷｉｎｄｏｗｓＮＴＳｅｒｖｅｒ基础知识●王立丰ＷｉｎｄｏｗｓＮＴＳｅｒｖｅｒ是一种网络操作系统，它可以管理网络上的各种资源。 这里的资源包括：网络上的计算机、应用程序以及与网络操作系统所在的计算机相连的各种硬件设备，如打印机、硬盘等。 正如早期的Ｎｅｔｗ.
Semantic integration in Iranian digital libraries: proposing a model

The main purpose of this study is presenting a conceptual model to integrate Iranian digital libraries. This research has been done in three steps. Documentary research method is used in the first step. All the related documents were research population and content analysis techniques is used to analyze documents. Analytical survey research method is used in the second step of the research. All the active Iranian digital libraries were the research population in this step. In fact there are 32 active digital libraries that just 26 of them participated in this study. Researcher-made questionnaire is used to collect data in this step. Finally system analyzing research method is used in the third step. Findings of the study demonstrated that elements such as technological infrastructure, Coding and identifier systems, Metadata standards, Legal and organizational issues, Semantic knowledge-based databases, and Knowledge Organizing Systems are needed in semantic integration. Also methods such as translators and making semantic relations can be used in semantic integration. Moreover tools such as ontology, knowledge organizing system, knowledgebase databases, translators, and descriptive and analytical languages should be used in semantic integration. Other findings related to Question 2 of the study showed that the studied digital libraries are not in suitable situation in covering digital materials and filling metadata fields. Also documenting metadata fields is not in good mood. Therefore, it is needed to strengthen all the identified weaknesses in order to make semantic integration ability. Finally, proposed model of this study presented in three layers entitled data, inference machine, and application.
Compensating for Bias in the SDM Fast Activation Mechanism

The Kanerva Sparse Distributed Memory (SDM) is a mechanism for implementing a memory with a huge address space. The physical memory consists of substantially fewer locations than the virtual address space. The plain Kanerva SDM memory assumes address and data to be random bit vectors with equal probability for 0 and 1. To compensate for any bias in address or data, several more or less elaborate methods can be used. In this paper we describe one simple method for achieving this compensation within the framework of the ``Fast activation Mechanism'' for SDM.
Evidence for strong fixation bias at 4-fold degenerate sites across genes in the great tit genome

It is well established that GC content varies across the genome in many species and that GC biased gene conversion, one form of meiotic recombination, is likely to contribute to this heterogeneity. Bird genomes provide an extraordinary system to study the impact of GC biased gene conversion owed to their specific genomic features. They are characterised by a high karyotype conservation with substantial heterogeneity in chromosome sizes, with up to a dozen large macrochromosomes and many smaller microchromosomes common across all bird species. This heterogeneity in chromosome morphology is also reflected by other genomic features, such as smaller chromosomes being gene denser, more compact and more GC rich relative to their macrochromosomal counterparts - illustrating that the intensity of GC biased gene conversion varies across the genome. Here we study whether it is possible to infer heterogeneity in GC biased gene conversion rates across the genome using a recently published method that accounts for GC biased gene conversion when estimating branch lengths in a phylogenetic context. To infer the strength of GC biased gene conversion we contrast branch length estimates across the genome both taking and not taking non-stationary GC composition into account. Using simulations we show that this approach works well when GC fixation bias is strong and note that the number of substitutions along a branch is consistently overestimated when GC biased gene conversion is not accounted for. We use this predictable feature to infer the strength of GC dynamics across the great tit genome by applying our new test statistic to data at 4-fold degenerate sites from three bird species - great tit, zebra finch and chicken - three species that are among the best annotated bird genomes to date. We show that using a simple one-dimensional binning we fail to capture a signal of fixation bias as observed in our simulations. However, using a multidimensional binning strategy, we find evidence for heterogeneity in the strength of fixation bias, including AT fixation bias. This highlights the difficulties when combining sequence data across different regions in the genome.
Perception des soins de sante primaires chez les parents d’enfants consultant au niveau des centres de sante de Marrakech

RÉSUMÉ:Les soins de santé primaires constituent le pilier de l’offre des soins d’un système de santé. Leur évaluation par les bénéficiaires permet d’approcher la perception du système de soins, d’en estimer la qualité afin de proposer des recommandations en vue d’améliorer les services des soins de santé primaires.
COLOR RECOGNITION OF RETROREFLECTIVE TRAFFIC SIGNS UNDER VARIOUS LIGHTING CONDITIONS

Depending on the spectral distribution of the light produced by the various types of sign lights and headlamps, the chromaticity of illuminated signs will shift markedly with light. This study assessed the possible improvement in driver recognition of traffic sign colors to be achieved by changing from the Federal Highway Administration highway colors to the ANSI (American National Standards Institute) safety colors. Sign color appearance under daylight and various nigttime viewing conditions was investigated. Although some lighting color combinations improved correct color recognition when viewing the ANSI safety colors, these improvements were marginal and applied only to some of the signing material colors and types. The details of the study and its results are described and discussed.
Trajectory-based Learning for Ball-in-Maze Games

Deep Reinforcement Learning has shown tremendous success in solving several games and tasks in robotics. However, unlike humans, it generally requires a lot of training instances. Trajectories imitating to solve the task at hand can help to increase sample-efficiency of deep RL methods. In this paper, we present a simple approach to use such trajectories, applied to the challenging Ball-in-Maze Games, recently introduced in the literature. We show that in spite of not using human-generated trajectories and just using the simulator as a model to generate a limited number of trajectories, we can get a speed-up of about 2-3x in the learning process. We also discuss some challenges we observed while using trajectory-based learning for very sparse reward functions.
High Classification Accuracy of a Motor Imagery Based Brain-Computer Interface for Stroke Rehabilitation Training

Motor imagery (MI) based brain-computer interfaces (BCI) extract commands in real-time and can be used to control a cursor, a robot or functional electrical stimulation (FES) devices. The control of FES devices is especially interesting for stroke rehabilitation, when a patient can use motor imagery to stimulate specific muscles in real-time. However, damage to motor areas resulting from stroke or other causes might impair control of a motor imagery BCI for rehabilitation. The current work presents a comparative evaluation of the MI-based BCI control accuracy between stroke patients and healthy subjects. Five patients who had a stroke that affected the motor system participated in the current study, and were trained across 10–24 sessions lasting about 1 h each with the recoveriX system. The participants' EEG data were classified while they imagined left or right hand movements, and real-time feedback was provided on a monitor. If the correct imagination was detected, the FES was also activated to move the left or right hand. The grand average mean accuracy was 87.4% for all patients and sessions. All patients were able to achieve at least one session with a maximum accuracy above 96%. Both the mean accuracy and the maximum accuracy were surprisingly high and above results seen with healthy controls in prior studies. Importantly, the study showed that stroke patients can control a MI BCI system with high accuracy relative to healthy persons. This may occur because these patients are highly motivated to participate in a study to improve their motor functions. Participants often reported early in the training of motor improvements and this caused additional motivation. However, it also reflects the efficacy of combining motor imagination, seeing continuous bar feedback, and real hand movement that also activates the tactile and proprioceptive systems. Results also suggested that motor function could improve even if classification accuracy did not, and suggest other new questions to explore in future work. Future studies will also be done with a first-person view 3D avatar to provide improved feedback and thereby increase each patients' sense of engagement.
Response of Pre and Post-Harvest Chemical Applications on Storage Life, Quality and Cost Economics of Mango cv. Dashehari in Tarai Region of Uttarakhand

Mango is well established for international trade due to its superb quality. The export market for mango has become highly lucrative. Domestic and international trade of fresh mango has been limited by its highly perishable nature and susceptibility to postharvest diseases and physical injuries. Postharvest losses have been estimated in developed countries from 5-25%, while in developing countries it is near to 20-50% (Cisneros-Zevallos, 2003). The losses after harvesting of fruits are more due to mismanagement of produce and unfavourable physiological, biological and environmental factors. Therefore, it is essential to overcome the problems associated with the produce by proper handling and care after harvesting of fruits. Many attempts have been made to increase the shelf life and maintain the postharvest health of fruit which includes hot water treatment, irradiation, use of fungicides, growth regulators, nutrients, packaging and storage at low temperature.