Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptome Analysis of Breadfruit Across a Domestication Gradient : Identifying Important Genes in a Low-Energy Input Tree Crop

INTRODUCTION Underutilized crops have the potential to economically benefit developing countries, improve global food security, and reduce energy input associated with agriculture. Breadfruit (Artocarpus altilis, Moraceae), a tropical tree crop domesticated in Oceania, is one such crop that can provide essential nutrients and requires low-energy input to maintain (Ragone 1997). Breadfruit is a staple starch crop that requires minimal fertilizer and irrigation and can be grown by local farmers throughout much of the tropics where malnutrition is prevalent (Jones et al. 2011). Local production and consumption reduces the need for expensive fuel associated with transportation of imported foods. Hundreds of breadfruit cultivars have been developed since its domestication began approximately 3,500 years ago, and cultivars throughout Oceania exhibit a wide range of morphological and genetic diversity (Zerega et al. 2004, 2005; Jones et al. 2013). However, this diversity is being threatened as the increase of urbanization and use of non-traditional crops has led to the underuse of breadfruit (Jones et al. 2013). Focus is now being placed on developing superior breadfruit cultivars to increase its use. To best accomplish this goal, it is necessary to understand the genetic basis of the cultivars and the domestication process. Domestication occurred in Oceania in a west to east direction (Zerega et al. 2004), creating a domestication gradient with wild relatives at one end and recently derived breadfruit and hybrids at the other. Although it is thought that humans selected for fewer seeded, smoother-skinned fruit during the domestication of breadfruit, it is unclear which other less obvious or unintended traits may have been influenced by the process. I have been analyzing transcriptomes (sequences of all expressed genes in a particular tissue) of breadfruit cultivars and their wild relatives across a domestication gradient to help identify patterns of change or positive selection in genes belonging to pathways that affect desirable traits (such as salt tolerance or carotenoid production).
Origin, Localization, and Immunoregulatory Properties of Pulmonary Phagocytes in Allergic Asthma

Allergic asthma is a chronic inflammatory disease of the airways that is driven by maladaptive T helper 2 (Th2) and Th17 immune responses against harmless, airborne substances. Pulmonary phagocytes represent the first line of defense in the lung where they constantly sense the local environment for potential threats. They comprise two distinct cell types, i.e., macrophages and dendritic cells (DC) that differ in their origins and functions. Alveolar macrophages quickly take up most of the inhaled allergens, yet do not deliver their cargo to naive T cells sampling in draining lymph nodes. In contrast, pulmonary DCs instruct CD4+ T cells develop into Th2 and Th17 effectors, initiating the maladaptive immune responses toward harmless environmental substances observed in allergic individuals. Unraveling the mechanisms underlying this mistaken identity of harmless, airborne substances by innate immune cells is one of the great challenges in asthma research. The identification of different pulmonary DC subsets, their role in antigen uptake, migration to the draining lymph nodes, and their potential to instruct distinct T cell responses has set the stage to unravel this mystery. However, at this point, a detailed understanding of the spatiotemporal resolution of DC subset localization, allergen uptake, processing, autocrine and paracrine cellular crosstalk, and the humoral factors that define the activation status of DCs is still lacking. In addition to DCs, at least two distinct macrophage populations have been identified in the lung that are either located in the airway/alveolar lumen or in the interstitium. Recent data suggest that such populations can exert either pro- or anti-inflammatory functions. Similar to the DC subsets, detailed insights into the individual roles of alveolar and interstitial macrophages during the different phases of asthma development are still missing. Here, we will provide an update on the current understanding of the origin, localization, and function of the diverse pulmonary antigen-presenting cell subsets, in particular with regard to the development and regulation of allergic asthma. While most data are from mouse models of experimental asthma, we have also included available human data to judge the translational value of the findings obtained in experimental asthma models.
Three Generations of Medical Image Segmentation: Methods and Available Software

Segmentation of medical images is an important step in forming realistic tissue models. To assist in classifying the relevant literature, three generations of development are identified where each generation adds an additional level of algorithmic complexity. The first generation is composed of the simplest forms of image analysis, the second is characterized by the application of uncertainty models and optimization methods, and the third incorporates knowledge into the segmentation process. The progress toward fullyautomatic segmentation is discussed and sources of segmentation software from industry and academia are identified, along with databases for segmentation validation.
Clump : Improving File SystemPerformance Through Adaptive

Recent years have seen a meteoric rise in microprocessor performance. Overall computer system performance, however, has not kept pace with that of its most glamorous component. One key bottleneck in system performance is le system I/O 17]. This paper investigates methods for improving le system performance by reducing or hiding disk latency. These methods monitor le accesses and infer relationships about the accessed les. Based on this continuously updated information, the system makes decisions about how to improve le system performance. Two optimization techniques are examined: reorganizing the disk to colocate related les and prefetching les in anticipation of future requests. An algorithm for selecting les to prefetch based on second-order correlations despite the presence of noise is presented. Cluster-based disk reorganization was unable to achieve any beneet over traditional block and cylinder shuf-ing 21, 24, 23, 1]. Our prefetching systems were able to predict les to prefetch with over 50% accuracy.
AN ANALYSIS OF STUDENTS SPEAKING FLUENCY OF ENGLISH LANGUAGE EDUCATION DEPARTMENT AT FOURTH SEMESTER OF UNIVERSITY OF MUHAMMADIYAH MALANG

English is a compulsory subject to learn here in Indonesia and one of the skills that have to master is speaking. When English language is taught in educational institution such as schools and universities, speaking will be part of the main skills to learn. One of the aspects in speaking is the ability to speak fluently. Therefore, many schools and universities employed native speakers to teach English with the expectation that the students will be able to speak as fluent as the natives. Further, English Language Education Department (ELED) UMM also have lecturers from abroad teaching speaking course for three consecutive semester and one locale lecturer teaching in the fourth semester or the last semester of speaking course. As a result, the researcher would like to analyze the ELED students speaking fluency at fourth semester. This research is aimed to know the fluency level of the students and the problem faced by them regarding their fluency. So, the objective of this research is knowing the students speaking fluency and their problems regarding fluency. In this study, the researcher used descriptive qualitative. The research data obtained by conducting observation and interview. The research subject in this study is students from A class taking advanced speaking course and consist of 27 students. The observation was conducted during the advanced speaking class with the students doing presentation about international conference. The researcher used speaking fluency scale to determine students’ fluency. Then, the researcher took 10 respondents from A class for the interview session. The result of the research showed that the students had good fluency with two respondent achieved scale 5, four respondent achieved scale 4 and the last four respondents achieved scale 3. The researcher also found that their problems regarding their fluency were anxiety, feeling nervous, limited vocabulary and lack of confidence.
Multicasting with untrusted relays: A noncoherent secure network coding approach

We consider the problem of multicasting information from a source to a destination over a multihop network of intermediate relays. However, some of the relays are untrustworthy and may be subject to eavesdropping. The source wishes to enlist their help while keeping the message secret against the eavesdropper. By employing random linear network coding at the relays, the problem is modeled as a noncoherent wiretap channel and is examined in terms of its secrecy capacity. The input distribution is optimized using an efficient projection-based gradient decent algorithm. The untrusted relay recruitment problem is also examined based on the derived secrecy capacity. An interesting scenario is analyzed where each potentially insecure relay may be randomly eavesdropped with a certain probability. Our asymptotic analysis reveals that, with enough untrusted relays, there exists a threshold on the eavesdropping probability below which all untrusted relays should be recruited.
Techniques for Reducing the Complexity of Object-Oriented Execution Traces

Understanding the behavior of object-oriented systems is almost impossible by merely performing static analysis of the source code. Dynamic analysis approaches are better suited for this purpose. Run time information is typically represented in the form of execution traces that contain object interactions. However, traces can be very large and hard to comprehend. Visualization tools need to implement efficient filtering techniques to remove unnecessary data and present only information that adds value to the comprehension process. This paper addresses this issue by presenting different filtering techniques. These techniques are based on removing utility methods and the use of object-oriented concepts such as polymorphism and inheritance to hide low-level implementation details. We also experiment with 12 execution traces of an object-oriented system called WEKA and study the gain attained by these filtering techniques
Iterative monaural audio source separation for subspace grouping

Monaural blind audio source separation usually separates a mixture into more signals than active sources. Therefore, a clustering of the separated signals is needed to reconstruct the sources. We propose a new iterative clustering and show that this approach outperforms classical clustering approaches which use features of the separated signals for clustering. The iterative clustering starts with the separation into two source estimates. Based on this, at each iteration the squared error between the source estimates of the former iteration and a linear superposition of the separated signals of the current iteration is minimized. The corresponding linear superposition generates new source estimates. The algorithm is evaluated on a large test set regarding melodies of different instruments, singing, and speech from the EBU.
An effective heuristic for the smallest grammar problem

The smallest grammar problem is the problem of finding the smallest context-free grammar that generates exactly one given sequence. Approximating the problem with a ratio of less than 8569/8568 is known to be NP-hard. Most work on this problem has focused on finding decent solutions fast (mostly in linear time), rather than on good heuristic algorithms. Inspired by a new perspective on the problem presented by Carrascosa et al.\ (2010), we investigate the performance of different heuristics on the problem. The aim is to find a good solution on large instances by allowing more than linear time. We propose a hybrid of a max-min ant system and a genetic algorithm that in combination with a novel local search outperforms the state of the art on all files of the Canterbury corpus, a standard benchmark suite. Furthermore, this hybrid performs well on a standard DNA corpus.
Time-Domain Large Signal Investigation on Dynamic Responses of the GDCC Quarterly Wavelength Shifted Distributed Feedback Semiconductor Laser

A numerical investigation on the dynamic large-signal analysis using a time-domain traveling wave model of quarter wave-shifted distributed feedback semiconductor lasers diode with a Gaussian distribution of the coupling coefficient (GDCC) is presented. It is found that the single-mode behavior and the more hole-burning effect corrections of quarter wave-shifted distributed feedback laser with large coupling coefficient can be improved significantly by this new proposed light source.
A First Study on the Use of Fuzzy Rule Based Classification Systems for Problems with Imbalanced Data Sets ?

In this work a preliminary study on the use of classification systems based on fuzzy reasoning in classification problems with nonbalanced classes is carried out. The objective of this study is to evaluate the cooperation with pre-processing mechanisms of instances and the use of different granularity levels (5 and 7 labels) in the fuzzy partition considered. To do so, we will use simple fuzzy rule based models obtained with the Chi (and co-authors’) method that extends the wellknown Wang and Mendel method to classification problems. The results obtained show that the previous step of instance selection and/or over sampling is needed. We have observed that a high overfitting exists when we use 7 labels per variable. We will analyze this fact and we will discuss some proposals on the subject.
Multidimensional treatment of photon emission from accretion discs around black holes

We consider photon emission from a supercritical accretion disc in which photons in the inner regions are trapped and advected in towards the centre. Such discs are believed to be present in failed supernovae and gamma-ray bursts, and possibly also in ultraluminous X-ray sources. We show that the luminosity from a supercritical accretion disc is proportional to the logarithm of the mass accretion rate when the vertical profile of the matter density is exponential. We obtain analytical results also for other density profiles, but the dependence of the luminosity on the accretion rate is no longer logarithmic.
Essays on Industrial Organization.

This paper investigates market e ects of the Brazilian biodiesel law, which made the use of biodiesel, blended with petroleum diesel, mandatory in Brazil. The study estimates the demand curve for diesel fuel (biodiesel and petroleum diesel) and the industry supply curve of biodiesel. These two pieces of information have been used in a static analysis to draw scenarios with di erent biodiesel mandates. The results show that the current proportion of biodiesel in the diesel mixture (5%) increases consumers' price by 1.7% and decreases the consumption by 1.5% compared to the scenario without biodiesel. Also, an increase in the biodiesel percentage to 10% would raise the price by 3.5% and reduce the consumption by 3%.
Virtual Community Life Cycle: a Model to Develop Systems with Fluid Requirements

This paper reports the results of an investigation into the life cycle model needed to develop information systems for group of people with fluid requirements. For this purpose, we developed a modified spiral model and applied to the analysis, design and implementation of a virtual community for a group of researchers and organizations that collaborated in a research project and had changing system requirements? The virtual knowledge community was dedicated to support mobilization and dissemination of evidence-based knowledge produced by the Disability Rights Promotion International Canada (DRPI-Canada) project.
Region-of-Interest Image Coding Based on Perceptually Optimized Bitplane Realignment

Region-of-interest (ROI) image coding is one of the new features included in the JPEG2000 image coding standard. Two methods are defined in the standard: the Maxshift method and the generic scaling based method. In this paper, a new region-of-interest coding method called Perceptually Optimized Shift (POShift) is proposed. Unlike other proposed methods, the POShift method realigns the bitplanes based on perceptually optimized order, which makes the visually most important bitplanes (in both ROI and BG) to be coded firstly. Experimental results indicate that the proposed method significantly outperforms the previous ROI coding schemes in overall ROI coding performance.
Esaim: Mathematical Modelling and Numerical Analysis a Fortin Operator for Two-dimensional Taylor-hood Elements * , * *

A standard method for proving the inf-sup condition implying stability of finite element approximations for the stationary Stokes equations is to construct a Fortin operator. In this paper, we show how this can be done for two-dimensional triangular and rectangular Taylor-Hood methods, which use continuous piecewise polynomial approximations for both velocity and pressure.
The Design and Implementation on Chinese E-commerce Semantic Lexicon ECNET

Research on semantic lexicon has started many years ago in China and in abroad. But most of these researches are based on nature language process (NLP). As so far, research on specialized areas oriented semantic lexicon, especially lexicon in Chinese, was still in the early stage of development interiorly. A Chinese E-commerce semantic lexicon ECNET is oriented to application in the area of E-commerce and logistics. ECNET was designed and built for solving the heterogeneous data share in different companies. This paper introduced the lexion database structure and application software of ECNET, described the future research target of ECNET.
Predicting the perceived spaciousness of stereophonic music recordings

In a stereophonic music production, music producers seek to impart impressions of one or more virtual spaces upon the recording with two channels of audio. Our goal is to map spaciousness in stereophonic music to objective signal attributes. This is accomplished by building predictive functions by exemplar-based learning. First, spaciousness of recorded stereophonic music is parameterized by three discrete dimensions of perception—the width of the source ensemble, the extent of reverberation, and the extent of immersion. A data set of 50 song excerpts is collected and annotated by humans for each dimension of spaciousness. A verbose feature set is generated on the music recordings and correlation-based feature selection is used to reduce the feature spaces. Exemplar-based support vector regression maps the feature sets to perceived spaciousness. We show that the predictive algorithms perform well on all dimensions and that perceived spaciousness can be successfully mapped to objective attributes of the audio signal.
What Is Left Unsaid About Semantic, Episodic and Working Memory: L2 Cognitive Control Accounts for Individual Differences and Gender Differences

Background: Prefrontal cortex (PFC) is believed to manipulate cognitive control and mnemonic process to overcome interference. The interaction among memory, cognitive control, and language learning is still under debate. Objectives: This study investigated how episodic, semantic, and working memory (WM) as linguistically dependent retrieval cues can entail the interference process among EFL (English as a foreign language ) individuals. Methods: Combining the samples from five testing sectors in Shiraz, Iran, yielded data from 78 adult participants (33 males; 52 EFL independent users; 26 basic users; mean age 34.63). The participants took the test package of selection mechanism measures in resolving interference (SMMRI), including selection in semantic/episodic memory and WM/priming (backward printed reading comprehension). Both descriptive statistics (mean scores, standard deviations) and inferential statistics (Correlations, t-tests, interface resolution (IR)) were performed using SPSS software version 25.0. Results: There was a downward trend in the order of magnitude from episodic (OLD-NEW) toward semantic (high-selection) toward WM/priming. Also, there was a moderate/high correlation among the aforementioned memories. There was a significant difference in IR-scores between basic and independent users. Conclusions: Hierarchical process of compromises between L2 (Second language) memories indicated that the interactions of different cognitive sub-components played a central executive role. The difference between IR-scores revealed that training on WM tasks, which demanded higher activations in the PFC, could enhance the ability in resolving interference. Retrieval cues have limited concomitant memory capacity that integrate morphological, semantic, and syntactic features. However, men outperformed females in semantic selection, no significant gender difference was seen in episodic selection.
Synchronous Path Analysis in MOS Circuit Simulator

For verifying the timing performance of synchronous MOS circuits a path analysis facility has been developed in the MOTIS (MOS Timing Simulator) system. This path analysis traces the clock signals to the latches in the circuit, computes the clock skews and then performs a path search analysis between all latches. For the paths between clocked latches, the timing constraints are determined using the clock skews and the operating frequency. The paths that do not satisfy these constraints are identified as problem paths. Such an analysis does not require a prior generation of circuit stimuli that are necessary for simulation. In terms of complexity also, it is simpler than simulation.
Relevant Feature Selection Model Using Data Mining for Intrusion Detection System

Abstract — Network intrusions have become a significant threat in recent years as a result of the increased demand of computer networks for critical systems. Intrusion detection system (IDS) has been widely deployed as a defense measure for computer networks. Features extracted from network traffic can be used as sign to detect anomalies. However with the huge amount of network traffic, collected data contains irrelevant and redundant features that affect the detection rate of the IDS, consumes high amount of system resources, and slowdown the training and testing process of the IDS. In this paper, a new feature selection model is proposed; this model can effectively select the most relevant features for intrusion detection. Our goal is to build a lightweight intrusion detection system by using a reduced features set. Deleting irrelevant and redundant features helps to build a faster training and testing process, to have less resource consumption as well as to maintain high detection rates. The effectiveness and the feasibility of our feature selection model were verified by several experiments on KDD intrusion detection dataset. The experimental results strongly showed that our model is not only able to yield high detection rates but also to speed up the detection process.