Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Focus Image Fusion Using Sparse Representation and Coupled Dictionary Learning

We address the multi-focus image fusion problem, where multiple images captured with different focal settings are to be fused into an all-in-focus image of higher quality. Algorithms for this problem necessarily admit the source image characteristics along with focused and blurred features. However, most sparsity-based approaches use a single dictionary in focused feature space to describe multi-focus images, and ignore the representations in blurred feature space. We propose a multi-focus image fusion approach based on sparse representation using a coupled dictionary. It exploits the observations that the patches from a given training set can be sparsely represented by a couple of overcomplete dictionaries related to the focused and blurred categories of images and that a sparse approximation based on such coupled dictionary leads to a more flexible and therefore better fusion strategy than the one based on just selecting the sparsest representation in the original image estimate. In addition, to improve the fusion performance, we employ a coupled dictionary learning approach that enforces pairwise correlation between atoms of dictionaries learned to represent the focused and blurred feature spaces. We also discuss the advantages of the fusion approach based on coupled dictionary learning, and present efficient algorithms for fusion based on coupled dictionary learning. Extensive experimental comparisons with state-of-the-art multi-focus image fusion algorithms validate the effectiveness of the proposed approach.
ANFIS based modeling and prediction car following behavior in real traffic flow based on instantaneous reaction delay

Nowadays, car following models, as the most popular microscopic traffic flow modeling, are increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. This paper presents a car-following model that was developed using an adaptive neuro fuzzy inference system (ANFIS) to simulate and predict the future behavior of a Driver-Vehicle-Unit (DVU). This model was developed based on new idea for calculate and estimate the instantaneous reaction of DVU. This idea was used in selection of inputs and outputs in train of ANFIS model. Integration of the driver's reaction time delay and omission of the necessity of regime classification are considered while developing the model. The model's performance was evaluated based on field data and compared to a number of existing car following models. The results showed that new model based on instantaneous reaction delay outperformed the other car-following models. The model was validated at the microscopic level, and the results showed very close agreement between field data and model outputs. The proposed model can be recruited in Drier Assistant devices, Safe Distance Keeping Observers, Collision Prevention systems and other ITS applications.
Cross-Cultural Adaptation Index of Chinese Expatriates in Malaysia: Extended Location-Specific Advantages

"Objective – In the fast changing globalizing and liberalizing world, the concern is not only on the location-specific advantages of a host country but also on how multinational enterprises manage to survive ex-post entry in a different environment. The cultural distance between the home and host countries thus plays an important role in this context. Empirical studies have shown that cultural distance and cross-cultural adaptation are interrelated, and there is a moderating role played by cultural distance on the cross-cultural adaptation. The cross-cultural adaptation is thus an important dimension to be considered in order to extend the L-advantages. Many studies have been conducted to build a cultural distance scale. Yet only a few studies have been conducted to construct a cross-cultural adaptation scale. This study thus aims to build a cross-cultural adaptation index. Methodology/Technique – The index is built based on the data collected from Chinese expatriates through in-depth interviews and questionnaire surveys. Findings – Two simple cross-cultural adaptation scales were built. These are the Simple Sociocultural Adaptation Scale (SSAS) and Psychological Adaptation Scale (SPAS) with seven pillars. An average index score was computed for each pillar. Living (78.79), interaction (69.19), regulative (64.02), work (85.61), psychological well-being (68.33), satisfaction (63.64), and intention to stay (62.12). The sociocultural adaptation index scored 76.57, while the psychological adaptation index scored 65.91. Novelty – This study provides insights for better understanding of Malaysian cultural environment to investors, expatriates, and policymakers as well as to extend and enrich the OLI paradigm. "
Rapid Expectation Adaptation during Syntactic Comprehension

When we read or listen to language, we are faced with the challenge of inferring intended messages from noisy input. This challenge is exacerbated by considerable variability between and within speakers. Focusing on syntactic processing (parsing), we test the hypothesis that language comprehenders rapidly adapt to the syntactic statistics of novel linguistic environments (e.g., speakers or genres). Two self-paced reading experiments investigate changes in readers’ syntactic expectations based on repeated exposure to sentences with temporary syntactic ambiguities (so-called “garden path sentences”). These sentences typically lead to a clear expectation violation signature when the temporary ambiguity is resolved to an a priori less expected structure (e.g., based on the statistics of the lexical context). We find that comprehenders rapidly adapt their syntactic expectations to converge towards the local statistics of novel environments. Specifically, repeated exposure to a priori unexpected structures can reduce, and even completely undo, their processing disadvantage (Experiment 1). The opposite is also observed: a priori expected structures become less expected (even eliciting garden paths) in environments where they are hardly ever observed (Experiment 2). Our findings suggest that, when changes in syntactic statistics are to be expected (e.g., when entering a novel environment), comprehenders can rapidly adapt their expectations, thereby overcoming the processing disadvantage that mistaken expectations would otherwise cause. Our findings take a step towards unifying insights from research in expectation-based models of language processing, syntactic priming, and statistical learning.
“Where’s Your Man?" Intersectionality in the Adoption Stories of Two Black, Single, Female Sociologists

Although there is a small, but growing literature on Single Mothers by Choice (SMC) and adoption, sociological research on adoption by single Black middleclass women remains sparse. In this paper, we, as single, Black, female sociologists, offer an insider view of our journeys through the state and private adoption systems. This paper has three purposes: to (1) draw awareness to the raced, classed, and gendered aspects of the adoption experience, (2) explore the emotional challenges inherent in forming a family through adoption, and (3) examine social notions of “family” and how and why some families are systemically (de)valued within the U.S. It is our hope that the layers of our experience as Black single adoptive mothers by choice will help inform conversations about changing family dynamics in the U.S.
Identifying cryptographic functionality in Android applications

Mobile devices in corporate IT infrastructures are frequently used to process security-critical data. Over the past few years powerful security features have been added to mobile platforms. However, for legal and organisational reasons it is difficult to pervasively enforce using these features in consumer applications or Bring-Your-Own-Device (BYOD) scenarios. Thus application developers need to integrate custom implementations of security features such as encryption in security-critical applications. Our manual analysis of container applications and password managers has shown that custom implementations of cryptographic functionality often suffer from critical mistakes. During manual analysis, finding the custom cryptographic code was especially time consuming. Therefore, we present the Semdroid framework for simplifying application analysis of Android applications. Here, we use Semdroid to apply machine-learning techniques for detecting non-standard symmetric and asymmetric cryptography implementations. The identified code fragments can be used as starting points for subsequent manual analysis. Thus manual analysis time is greatly reduced. The capabilities of Semdroid have been evaluated on 98 password-safe applications downloaded from Google Play. Our evaluation shows the applicability of Semdroid and its potential to significantly improve future application analysis processes.
Investigating the Effectiveness of Mindfulness- Based Intervention on Self-confidence and Levels of Cognitive and Physical Anxiety of Shooters

Introduction: Mindfulness-based intervention (MBI) has been used by many psychologists as a new therapeutic package in many studies. However, this package is less used in sport filed. Therefore, the aim of this study was to investigate the effectiveness of six weeks of mindfulness-based intervention on self-confidence and levels of cognitive and physical anxiety of shooters. Methods: In this semi-experimental research, 17 male professional shooters aging 1722 years old from Yazd province who had a history of shooting for at least two years were randomly assigned to two groups, including (1) mindfulness strategies training and (2) control. The training of mindfulness strategies training group comprised 6 sessions (one session per week) and daily homework practice. The instrument used was a CSAI-2 questionnaire. In pre-test, both groups completed the questionnaire 20 minutes before an official match. Then the mindfulness strategies training according to a formerly prepared protocol was held for the intervention group. After intervention, the questionnaire was again completed 20 minutes before the official match with the same conditions by both groups in the post-test. Data were analyzed using independent and paired samples t-test and SPSS-20 software. Results: The results of this study showed that mindfulness strategies training increased self-confidence (P=0.002) and decreased cognitive anxiety (P=0.04). However, it did not significantly changed the physical anxiety (P=0.8). Conclusion: It appears that that mindfulness training can be used as a new promising method to increase self-confidence and reduce cognitive anxiety in shooters.
Insights into the activation of the helicase Prp43 by biochemical studies and structural mass spectrometry

Splicing of precursor messenger RNA is a hallmark of eukaryotic cells, which is carried out by the spliceosome, a multi-megadalton ribonucleoprotein machinery. The splicing reaction removes non-coding regions (introns) and ligates coding regions (exons). The spliceosome is a highly dynamic ribonucleoprotein complex that undergoes dramatic structural changes during its assembly, the catalysis and its disassembly. The transitions between the different steps during the splicing cycle are promoted by eight conserved DExD/H box ATPases. The DEAH-box protein Prp43 is responsible for the disassembly of the intron-lariat spliceosome and its helicase activity is activated by the G-patch protein Ntr1. Here, we investigate the activation of Prp43 by Ntr1 in the presence and absence of RNA substrate by functional assays and structural proteomics. Residues 51–110 of Ntr1 were identified to be the minimal fragment that induces full activation. We found protein–protein cross-links that indicate that Prp43 interacts with the G-patch motif of Ntr1 through its C-terminal domains. Additionally, we report on functionally important RNA binding residues in both proteins and propose a model for the activation of the helicase.
Nonredundant Role of Bax and Bak in Bid-Mediated Apoptosis

ABSTRACT Animal models suggest that Bax and Bak play an essential role in the implementation of apoptosis and as a result can hinder tumorigenesis. We analyzed the expression of these proteins in 50 human glioblastoma multiforme (GBM) tumors. We found that all the tumors expressed Bak, while three did not express Bax. In vitro, Bax-deficient GBM (BdGBM) exhibited an important resistance to various apoptogenic stimuli (e.g., UV, staurosporine, and doxorubicin) compared to the Bax-expressing GBM (BeGBM). Using an antisense strategy, we generated Bak− BeGBM and Bak− BdGBM, which enabled us to show that the remaining sensitivity of the BdGBM to apoptosis was due to the overexpression of Bak. Bax/Bak single or double deficiency had no influence on either the clonogenicity or the growth of tumors in Swiss nude mice. Of note, Bak− BeGBM cells were resistant to apoptosis induced by caspase 8 (C8) but not to that induced by granzyme B (GrB). Cells lacking both Bax and Bak (i.e., Bak− BdGBM) were completely resistant to all stimuli including the microinjection of C8 and GrB. We show that GrB-cleaved Bid and C8-cleaved Bid differ in size and utilize preferentially Bax and Bak, respectively, to promote cytochrome c release from mitochondria. Our results suggest that Bax deficiency is compensated by an increase of the expression of Bak in GBM and show, for the first time in human cancer, that the double Bax and Bak deficiency severely impairs the apoptotic program.
Serum AdenosineDeaminase : Isoenzymesand DiagnosticApplication

Human adenosine deaminase (ADA; EC 3.5.4.4) consists of three isoenzymes: ADA1, ADA1+p, and ADA2. We developed an electrophoretic technique to distinguish between these three isoenzymes. The isoenzyme pattern was studied in tissue and cell homogenates, as well as in serum from normal subjects and from patients with Increased serum ADA who had either hepatitis, infectious mononucleosis, tuberculosis, pneumonia, rheumatoid arthritis,or acute lymphoblasticleukemia (ALL). The highest ADA activity was found in lymphocytes and monocytes. ADA2 could be detected only in monocytes (18% of total ADA activity). It was also the predominant isoenzyme in the sera of controls and all disease groups, except for ALL-the only condition evaluated that is not of an inflammatory nature. We conclude that serum ADA reflects monocyte/macrophage activity or turnover in most diseases studied. The exception is ALL, where serum ADA most probably originates from lymphocyte precursors.
Type-Checking AHEAD ∗

Ubiquitous computing increases the pressure on the software industry to produce ever more and error-free code. As an answer, generative programming increases the level of abstraction in software development by describing problems in high-level domain-specific languages and translating these to executable code. AHEAD (Algebraic Hierarchical Equations for Application Design) is a framework for generative programming that achieves additional productivity gains by recognizing that in many areas, we need a family of programs that are very similar. It avoids duplication of work by generating programs out of a common base of features that can be freely composed. Our contribution is Graft, a calculus that gives a formal foundation to AHEAD and provides several mechanisms for making sure that feature combinations are legal and that features in themselves are consistent.
Working Papers in Economics and Statistics on the Channel and Type of International Disaster Aid on the Channel and Type of International Disaster Aid

Research suggests that a donor country's decision to provide post-disaster assistance is not only driven by the severity of a disaster and the resulting humanitarian needs in the recipient country but also by strategic considerations. We argue that the identification of the determinants of the size of disaster assistance is a first step in the analysis of the donor's behavior. Since all aid is not motivated by the same reasons, the evaluation of the donor country's behavior requires a second step accounting for the type and the channel of aid provided. Using data on international disaster assistance between 2000 and 2007 one can examine both the donor countries' decision on the channel (bilateral vs. multilateral) and the type of disaster relief (cash vs. in-kind). The empirical results suggest that international disaster relief is not as much driven by the needs of the recipient country but also by strategic interests (e.g. oil, trade relationships) of the donor country. Bilateral and cash transfers are used as a vehicle to signal strategic interests, while multilateral and in-kind transfers are chosen to control for misuse in badly governed recipient countries.Hannemann as well as participants of a workshop in Zurich 2008 and a seminar at the Worldbank in 2009 for their useful comments.
Integrating qualitative and quantitative object representations in the recovery and tracking of 3-D shape

Data-driven models such as active contours in 2-D and deformable surfaces in 3-D have become prevalent in the computer vision community, particularly in the areas of shape tracking and shape recovery. They provide an important alternative to typical model-based recognition and tracking approaches that assume knowledge of the exact geometry of the object. Despite the power of these approaches, data-driven models often encode too little model information. As a consequence, active 3-D model recovery schemes often require manual segmentation or good model initialization, and active contour trackers have been able to track only an object's translation in the image. To overcome these problems requires bridging the representational gap between overconstrained geometric models and underconstrained active models. In previous work, we introduced a qualitative object representation integrating object-centered and viewer-centered models. In this paper, we (cid:12)rst show how this representation provides the missing constraints on the recovery of quantitative 3-D deformable models from 2-D images. We then show how this same representation provides the missing constraints needed to qualitatively track an object's rotation in depth or to quantitatively track an object's pose. (cid:3) To appear in: L. Harris and M. Jenkin (eds.), Computational and Psychophysical Mechanisms of Visual Coding, Cambridge University Press, New York, NY.
Can testedness be effectively measured?

Among the major questions that a practicing tester faces are deciding where to focus additional testing effort, and deciding when to stop testing. Test the least-tested code, and stop when all code is well-tested, is a reasonable answer. Many measures of "testedness" have been proposed; unfortunately, we do not know whether these are truly effective. In this paper we propose a novel evaluation of two of the most important and widely-used measures of test suite quality. The first measure is statement coverage, the simplest and best-known code coverage measure. The second measure is mutation score, a supposedly more powerful, though expensive, measure. We evaluate these measures using the actual criteria of interest: if a program element is (by these measures) well tested at a given point in time, it should require fewer future bug-fixes than a "poorly tested" element. If not, then it seems likely that we are not effectively measuring testedness. Using a large number of open source Java programs from Github and Apache, we show that both statement coverage and mutation score have only a weak negative correlation with bug-fixes. Despite the lack of strong correlation, there are statistically and practically significant differences between program elements for various binary criteria. Program elements (other than classes) covered by any test case see about half as many bug-fixes as those not covered, and a similar line can be drawn for mutation score thresholds. Our results have important implications for both software engineering practice and research evaluation.
Design and Implementation of a Sort-Free K-Best Sphere Decoder

This paper describes the design and very-large-scale integration (VLSI) architecture for a 4 × 4 breadth-first K-best multiple-input-multiple-output (MIMO) decoder using a 64 quadrature-amplitude modulation (QAM) scheme. A novel sort-free approach to path extension, as well as quantized metrics result in a high-throughput VLSI architecture with lower power and area consumption compared to state-of-the-art published systems. Functionality is confirmed via a field-programmable gate array (FPGA) implementation on a Xilinx Virtex II Pro FPGA. Comparison of simulation and measurements are given, and FPGA utilization figures are provided. Finally, VLSI architectural tradeoffs are explored for a synthesized application-specific IC (ASIC) implementation in a 65-nm CMOS technology.
The Lemur’s Tale - Story-Telling in Primates and Other Socially Intelligent Agents

This paper addresses the relationship between social intelligence and narrative intelligence, with a particular emphasis on 1) the phylogenetic origins of primate (narrative) intelligence, and 2) the ontogenetic origin of autobiographical stories. The ‘Narrative Intelligence Hypothesis‘ (NIH) is introduced according to which the evolutionary origin of stories and narrativity was correlated with increasing social dynamics in primate societies, in particular the need to communicate about third-party relationships. Requirements for artificial socially intelligent story-tellers are outlined, and the issue of testing social intelligence is dis-
Isolated Chinese lyrics with accompaniment recognition based on SVM

The speech recognition technology is one of the hot spots in the field of audio technology. For the recognition of the lyrics with the accompaniment, there are two commonly used methods, one is applying automatic speech recognition technology to singing recognition, the other way is using sound classification, extracting audio features, and then using pattern matching classifier for classification. In this paper, we use sound classification method, adopt self-built experimental database where 31 classes Chinese isolated lyrics (Total 4650) are intercepted from different songs. And then use these words as the units. Considering speaking and singing sharing similar mechanism, we extract 39-dimensional MFCC feature parameters which are widely used in speech recognition. Combined with training materials, adjust kernel parameters and choose functions to train SVM classifier. After that, the trained SVM classification system is used to recognize the lyrics, and the average recognition accuracy rate is 42.80%.
Analyzing Performance for Complex Protocol using Validated CP-nets Models

Performance improvements are quite significant for a complex protocol, such as BitTorrent protocol, but should take no harm to its functionality correctness as an inevitable precondition. In current performance analysis studies, various formal models are usually utilized to perform corresponding evaluations. However, most of those models do not support specifying and verifying the functionality for protocol systems, where above precondition may not be guaranteed before performance analysis executes. Therefore, how to analysis performance for complex protocols based on functional validated models becomes a challenging but significant topic. In this paper, colored Petri nets (CP-nets) is well utilized as basic models to integrate functional validation and performance analysis for complex protocols. The CP-nets models used in functional validation and performance analysis procedures are closely related, where every occurrence sequence in the performance model corresponds to a behavioral equivalent occurrence sequence in its functional model, so it is guaranteed that models used in performance analysis also satisfy the functionality requirements of the protocol. An integrated analysis process of BitTorrent protocol is taken as an example to illustrate the practical effectiveness of our method.