Miracle-dz/UniFAR-FTUs huggingface dataset:
A study on differential evolution and cellular differential evolution for multilevel color image segmentation

Image segmentation is the process of partitioning an image into multiple regions and is widely utilized in various domains to ease separating and searching particular objects within a given image. Multilevel thresholding is one of the most important techniques used for segmenting images. However, selection of optimum thresholds is still a challenging problem. Since evolutionary algorithms are being applied in literature over the decade for improving the accuracy and computational efficiency of multilevel thresholding methods, in many cases, such stochastic algorithms may prematurely converge into local optima and lack accuracy and stability. Structured Evolutionary Algorithms are proposed to overcome these limitations. Therefore the main aim of this research work is to propose a multilevel thresholding method based on Cellular Differential Evolution for color images segmentation. We present in this paper a comparative performance study to evaluate the efficiency and the accuracy of Standard DE and Cellular DE. We also present the results of this comparative study which shows that the structuring of the population within DE improves its performance in terms of accuracy, robustness and speed convergence. The proposed algorithm is also evaluated by comparing it with three other algorithms using a well-known benchmark images. Such comparison reflects the efficiency of our algorithm.
Bundle Adjustment Rules

In this paper we investigate the status of bundle adjustment as a component of a real-time camera tracking system and show that with current computing hardware a significant amount of bundle adjustment can be performed every time a new frame is added, even under stringent real-time constraints. We also show, by quantifying the failure rate over long video sequences, that the bundle adjustment is able to significantly decrease the rate of gross failures in the camera tracking. Thus, bundle adjustment does not only bring accuracy improvements. The accuracy improvements also suppress error buildup in a way that is crucial for the performance of the camera tracker. Our experimental study is performed in the setting of tracking the trajectory a calibrated camera moving in 3D for various types of motion, showing that bundle adjustment should be considered an important component for a state-of-the-art real-time camera tracking system.
HIV-1-Induced Small T Cell Syncytia Can Transfer Virus Particles to Target Cells through Transient Contacts

HIV-1 Env mediates fusion of viral and target cell membranes, but it can also mediate fusion of infected (producer) and target cells, thus triggering the formation of multinucleated cells, so-called syncytia. Large, round, immobile syncytia are readily observable in cultures of HIV-1-infected T cells, but these fast growing “fusion sinks” are largely regarded as cell culture artifacts. In contrast, small HIV-1-induced syncytia were seen in the paracortex of peripheral lymph nodes and other secondary lymphoid tissue of HIV-1-positive individuals. Further, recent intravital imaging of lymph nodes in humanized mice early after their infection with HIV-1 demonstrated that a significant fraction of infected cells were highly mobile, small syncytia, suggesting that these entities contribute to virus dissemination. Here, we report that the formation of small, migratory syncytia, for which we provide further quantification in humanized mice, can be recapitulated in vitro if HIV-1-infected T cells are placed into 3D extracellular matrix (ECM) hydrogels rather than being kept in traditional suspension culture systems. Intriguingly, live-cell imaging in hydrogels revealed that these syncytia, similar to individual infected cells, can transiently interact with uninfected cells, leading to rapid virus transfer without cell-cell fusion. Infected cells were also observed to deposit large amounts of viral particles into the extracellular space. Altogether, these observations suggest the need to further evaluate the biological significance of small, T cell-based syncytia and to consider the possibility that these entities do indeed contribute to virus spread and pathogenesis.
How to fail at species delimitation

Species delimitation is the act of identifying species‐level biological diversity. In recent years, the field has witnessed a dramatic increase in the number of methods available for delimiting species. However, most recent investigations only utilize a handful (i.e. 2–3) of the available methods, often for unstated reasons. Because the parameter space that is potentially relevant to species delimitation far exceeds the parameterization of any existing method, a given method necessarily makes a number of simplifying assumptions, any one of which could be violated in a particular system. We suggest that researchers should apply a wide range of species delimitation analyses to their data and place their trust in delimitations that are congruent across methods. Incongruence across the results from different methods is evidence of either a difference in the power to detect cryptic lineages across one or more of the approaches used to delimit species and could indicate that assumptions of one or more of the methods have been violated. In either case, the inferences drawn from species delimitation studies should be conservative, for in most contexts it is better to fail to delimit species than it is to falsely delimit entities that do not represent actual evolutionary lineages.
A Fair Solution to DNS Amplification Attacks

Recent serious security incidents reported several attackers employing IP spoofing to massively exploit recursive name servers to amplify DDoS attacks against numerous networks. DNS amplification attack scenarios utilize DNS servers mainly for performing bandwidth consumption DoS attacks. This kind of attack takes advantage of the fact that DNS response messages may be substantially larger than DNS query messages. In this paper we present a novel, simple and practical scheme that enable administrators to distinguish between genuine and falsified DNS replies. The proposed scheme, acts proactively by monitoring in real time DNS traffic and alerting security supervisors when necessary. It also acts reactively in co-operation with the firewalls by automatically updating rules to ban bogus packets. Our analysis and the corresponding experimental results show that the proposed scheme offers an effective solution, when the specific attack unfolds.
Finding Consistency in an Inconsistent World: Towards Deep Semantic Understanding of Scale-out Distributed Databases

We present a new problem in data storage: how to build efficient backup and restore tools for increasingly popular Next-generation Eventually Consistent STorage systems (NECST). We show that the lack of a concise, consistent, logical view of data at a point-in-time is the key underlying problem; we suggest a deep semantic understanding of the data stored within the system of interest as a solution. We discuss research and productization challenges in this new domain, and present the status of our platform, Datos CODR (Consistent Orchestrated Distributed Recovery), which can extract consistent and deduplicated backups from NECST systems such as Cassandra, MongoDB, and many others.
An automated semantic-based approach for creating task structures

This work is settled in the area of safety-critical embedded systems and presents a formally funded approach for automatically creating an optimized task structure from a Simulink model. Based on an extended task network formalism, in a first step, a formal translation scheme on Simulink block level is defined. Because the resulting tasks are very fine-grained and unbalanced with respect to their required computation demand (denoted as task weight), in a second step, an optimized task structure is created by formally merging tasks with each other. Here, the optimization goal is to minimize inter-task communication and to balance the weights of tasks. Additionally, it is formally proven that both the translation and the merging of tasks preserves the formal execution semantics of Simulink. The whole approach was implemented as an automated tool-chain and evaluated with the help of a case study.
Outage performance of relay-assisted co-existing MIMO downlinks that exploit interference

We investigate the outage performance of relay assisted transmissions of coexisting radio systems. Employing simple linear precoding designs, we explore the potential of utilising the cross-interference between the two coexisting systems to mutually improve performance. While conventionally the aim of the relay is to isolate the two concurrent transmissions by completely removing the interference between them, we make use of interference energy when the interference between the two systems is mutually constructive. In this direction two adaptive linear precoding techniques are proposed for the relay and compared to conventional precoding. We use the cognitive radio paradigm to illustrate the associated benefits. It is shown by theoretical analysis and simulation that the constructive interference provides a source of additional green signal energy that benefits the outage performance of both communication links.
Robust prediction-based control for unstable delay systems

We present a discrete-time prediction based state-feedback controller. It is shown that this controller stabilizes possibly unstable continuous-time delay systems. The stability is shown to be robust with respect to uncertainties in the knowledge on the plant parameters, the system delay and the sampling period. The proposed prediction based controller has been tested in a real-time application to control the yaw angular displacement of a 4-rotor mini-helicopter.
Globalization and Public Policy Analysis: A Case Study of Foreign Policy of ASEAN Member States

This study has an objective to analyze foreign policy of member states in globalization current, aiming to answer that the foreign policy of member states have been changed or remained the same and there are any factors affecting changing of foreign policy of the member states. From the study results, it is found that the foreign policy of Thailand is a friendly foreign policy with all states. The policy of Indonesia is more opened because of a change in leader, allowing more democratic development in the country; the government has proceeded with friendly foreign policy with the states in order to bring funds into the state. The foreign policy of Malaysia is not much changed as there is no changing in the leader; the policy of Malaysia has reconciled relations with main city of Indian and Chinese residing in the country in order to bring investments into the country and to relieve tensions in the country. The foreign policy of the Philippines has proceeded with policy under the ASEAN framework and emphasized on international Islam communities. The foreign policy of Singapore has the least changed as the Singapore's policy focuses on internal trade since the state was found. As for the foreign policy of Brunei Darussalam, Brunei has a little role in the international stage; the state having closest relationship as from the view of history is Singapore as the Singaporean has invested in retailing business in Brunei. The foreign policy of Vietnam has emphasized on an omnidirectional foreign policy in order to compete with several states in global stage. The foreign policy of Myanmar has proceeded with a friendly foreign policy with all ASEAN member states, the East-west Corridor transportation line from Myanmar through Thailand and Lao to Vietnam has been developed. As for the foreign policy of Lao, In 2001, the Thai government and Lao government held a discussion which Thailand reaffirmed the position not to support the anti-Lao group. The foreign policy of Cambodia has proceeded with more openness, having good relation with China, Russia and USA as these states has invested in the state, especially the US company. Keywords—Globalization, Public Policy Analysis, Foreign Policy, ASEAN Member States.
Recruitment of the Nucleolar Remodeling Complex NoRC Establishes Ribosomal DNA Silencing in Chromatin

ABSTRACT The rRNA gene cluster consists of multiple transcription units. Half of these are active, while the other half are transcriptionally inactive. Previously, in vivo studies have demonstrated that silencing of ribosomal DNA (rDNA) is mediated by the chromatin remodeling NoRC (nucleolar remodeling complex). To explore the mechanisms underlying NoRC-directed silencing of rDNA transcription, we investigated the effect of recombinant NoRC on RNA polymerase I transcription on reconstituted chromatin templates. We show that NoRC interacts with the transcription terminator factor (TTF-I), and this interaction is required both for the binding of TTF-I to its promoter-proximal target site and for the recruitment of NoRC to the promoter. After association with the rDNA promoter, NoRC alters the position of the promoter-bound nucleosome, thereby repressing RNA polymerase I transcription. This NoRC-directed rDNA repression requires the N terminus of histone H4. Repression is effective before preinitiation complex formation and as such is unable to exert an effect upon activated rDNA genes. Furthermore, the early steps of rDNA repression do not depend on DNA and histone modifications. These results reveal an important role for TTF-I in recruiting NoRC to rDNA and an active role for NoRC in the establishment of rDNA silencing.
Mycobacterial infections in lung transplant recipients.

BACKGROUND Immunosuppression and chronic lung disease are known risk factors for mycobacterial infection and might be expected to develop with an increased frequency in lung transplant recipients. We therefore sought to document the incidence and type of mycobacterial infections in a large lung transplant program. METHODS A retrospective review of 219 transplant procedures (60 single lung transplants and 159 double lung transplants) in 210 patients was conducted. All patients had scheduled surveillance bronchoscopies at 3, 6, 9, 12, 18, and 24 months, and yearly thereafter. BAL samples were processed routinely for mycobacterium. RESULTS Eight patients (3.8%) had evidence of infection (5 men, 3 women; age range, 26 to 63 years). The reasons for transplant were obstructive lung disease (six), cystic fibrosis (one), and pulmonary fibrosis (one). Five recipients had infection in their native lungs; two of five cultured mycobacterium from BAL following transplantation. At least four of five patients had nontuberculous mycobacterium (one showed acid fast bacilli and granuloma on a biopsy specimen that was not sent for culture). None of the five developed disease (mean follow-up = 22 months; range, 3 to 30 months). The organisms were Mycobacterium avium complex (three), Mycobacterium xenopi (one), and unidentified (one). Of the three remaining patients who developed infection after transplantation, one grew Mycobacterium chelonae and the others grew Mycobacterium tuberculosis (both received double lung transplants and had no evidence of mycobacterium in their native lungs). The only definite symptomatic disease occurred in the patients with M tuberculosis, one of whom had evidence of dissemination. The patients with M tuberculosis responded to standard treatment. There have been no deaths due to mycobacterium. CONCLUSION Mycobacterial disease rarely occurs following lung transplantation. Cultures for mycobacterium in surveillance BALs in the absence of symptoms are likely unnecessary.
Simultaneous Mobile Robot and Radio Node Localization in Wireless Sensor Networks

1 Summary Accurate and cost effective localization is a basic issue in the field of mobile robotics. This work shows how it can be solved by using wireless radio nodes as landmarks. Mechanical scanning is employed at the mobile robot to measure the angle of arrival of radio signals. A measurement integrity check is realized by means of normalized cross correlation. This enables the recognition of multi path propagation and radio interferers, thereby ensuring high robustness. A simultaneous localization and mapping approach is implemented to localize the robot and to build a map of static radio nodes simultaneously. This allows localizing the robot in unknown environments in an ad hoc and unobtrusive fashion. 2 Method to measure the angle of arrival The foundation of this work is a new method to measure the angle of arrival in wireless networks based on the received signal strength indicator (RSSI). It requires the antenna on the robot to be rotated about a vertical axis while recording the RSSI. This results in a radiation pattern in the azimuth plane. Its cross correlation with the known reference radiation pattern of the antenna allows to determine the relative angle. A detailed description of the method and a thorough error analysis are given in [1] and [2]. A schematic of the setup is shown in figure 1. To ensure a distinct radiation pattern, a monopole antenna is slightly modified by the attachment of a reflector plate. This increases the uniqueness of the angle given by the cross correlation. The advantages of this method are its robustness to antenna anisotropy of the static nodes and the possibility for measurement integrity by the consideration of the maximum correlation coefficient, which is a measure for the similarity between the recorded and the reference radiation patterns. Thereby the localization is robust in multipath environments. Further the presented method does not require any modification of the sensor network and thus allows the use of commodity radio hardware. It also does not assume any propagation models and therefore does not require any parameters to be known in advance enabling localization in completely unknown environments. Figure 19: Setup for the determination of the relative angle: a ϕ is the rotation angle of the antenna, r ϕ is the relative angle to the static node with position n x. 338 3 SLAM Based on this measurement method we apply the SLAM approach to simultaneously localize …
An Automated algorithm for the identification of artifacts in mottled and noisy images

This thesis proposes an algorithm for automatically classifying a specific set of image quality (IQ) defects on noisy and mottled printed documents. A rough initial estimate of the defects' location i.e. defect detection is manually provided with a scanned image. The approach then proceeds to derive a more accurate segmentation by performing several image processing routines on the digital image. This reveals regions of interest from which discriminatory features are extracted. A classification of four defects is achieved via a customized tree classifier which employs a combination of size, shape and region attributes at corresponding nodes to yield appropriate binary decisions. Applications of this process include automated/assisted diagnosis and repair of printers or copiers in the field in a timely fashion. The proposed algorithm is tested on a database of 261 scanned images provided by Xerox Corporation and several synthetic defects yielding a 96.6% classification rate.
Learning to rank with combinatorial Hodge theory

We propose a number of techniques for learning a global ranking from data that may be incomplete and imbalanced — characteristics that are almost universal to modern datasets coming from e-commerce and internet applications. We are primarily interested in cardinal data based on scores or ratings though our methods also give specific insights on ordinal data. From raw ranking data, we construct pairwise rankings, represented as edge flows on an appropriate graph. Our rank learning method exploits the graph Helmholtzian, which is the graph theoretic analogue of the Helmholtz operator or vector Laplacian, in much the same way the graph Laplacian is an analogue of the Laplace operator or scalar Laplacian. We shall study the graph Helmholtzian using combinatorial Hodge theory, which provides a way to unravel ranking information from edge flows. In particular, we show that every edge flow representing pairwise ranking can be resolved into two orthogonal components, a gradient flow that represents the l2-optimal global ranking and a divergence-free flow (cyclic) that measures the validity of the global ranking obtained — if this is large, then it indicates that the data does not have a good global ranking. This divergence-free flow can be further decomposed orthogonally into a curl flow (locally cyclic) and a harmonic flow (locally acyclic but globally cyclic); these provides information on whether inconsistency in the ranking data arises locally or globally. When applied to the problem of rank learning, Hodge decomposition sheds light on whether a given dataset may be globally ranked in a meaningful way or if the data is inherently inconsistent and thus could not have any reasonable global ranking; in the latter case it provides information on the nature of the inconsistencies. An obvious advantage over the NP-hardness of Kemeny optimization is that the discrete Hodge decomposition may be easily computed via a linear least squares regression. We also investigated the l1-projection of edge flows, showing that this has a dual given by correlation maximization over bounded divergence-free flows, and the l1-approximate sparse cyclic ranking, showing that this has a dual given by correlation maximization over bounded curl-free flows. We discuss connections with well-known ordinal ranking techniques such as Kemeny optimization and Borda count from social choice theory.
A Unifying Framework for Sparse Gaussian Process Approximation using Power Expectation Propagation

Gaussian processes (GPs) are flexible distributions over functions that enable high-level assumptions about unknown functions to be encoded in a parsimonious, flexible and general way. Although elegant, the application of GPs is limited by computational and analytical intractabilities that arise when data are sufficiently numerous or when employing non-Gaussian models. Consequently, a wealth of GP approximation schemes have been developed over the last 15 years to address these key limitations. Many of these schemes employ a small set of pseudo data points to summarise the actual data. In this paper we develop a new pseudo-point approximation framework using Power Expectation Propagation (Power EP) that unifies a large number of these pseudo-point approximations. Unlike much of the previous venerable work in this area, the new framework is built on standard methods for approximate inference (variational free-energy, EP and power EP methods) rather than employing approximations to the probabilistic generative model itself. In this way all of approximation is performed at `inference time' rather than at `modelling time' resolving awkward philosophical and empirical questions that trouble previous approaches. Crucially, we demonstrate that the new framework includes new pseudo-point approximation methods that outperform current approaches on regression, classification and state space modelling tasks.
An Optimal Speculative Transactional Replication Protocol

In this paper we investigate the problem of speculative processing in a replicated transactional system layered on top of an optimistic atomic broadcast service. We consider a realistic model in which transactions' read/write sets are not known a-priori, and transactions' data access patterns may vary depending on the observed snapshot. We formalize a set of correctness and optimality properties aimed at ensuring that transactions are not activated on inconsistent snapshots, as well as the minimality and completeness of the set of explored serialization orders. Finally, an optimal speculative transaction replication protocol is presented.