Miracle-dz/UniFAR-FTUs huggingface dataset:
IMA Genome-F 2: Ceratocystis manginecans, Ceratocystis moniliformis, Diplodia sapinea

The draft nuclear genomes of Diplodia sapinea, Ceratocystis moniliformis s. str. , and C. manginecans are presented. Diplodia sapinea is an important shoot-blight and canker pathogen of Pinus spp. , C. moniliformis is a saprobe associated with wounds on a wide range of woody angiosperms and C. manginecans is a serious wilt pathogen of mango and Acacia mangium. The genome size of D. sapinea is estimated at 36.97 Mb and contains 13 020 predicted genes. Ceratocystis moniliformis includes 25.43 Mb and is predicted to encode at least 6 832 genes. This is smaller than that reported for the mango wilt pathogen C. manginecans which is 31.71 Mb and is predicted to encode at least 7 494 genes. The latter is thus more similar to C. fimbriata s.str. , the type species of the genus. The genome sequences presented here provide an important resource to resolve issues pertaining to the taxonomy, biology and evolution of these fungi.
Data Clustering Using Multi-objective Differential Evolution Algorithms

The article considers the task of fuzzy clustering in a multi-objective optimization (MO) framework. It compares the relative performance of four recently developedmulti-objective variants of Differential Evolution (DE) on over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized. The resultant Pareto optimal set of solutions from each algorithm consists of a number of non-dominated solutions, from which the user can choose the most promising ones according to the problem specifications. A real-coded representation for the candidates is used for DE. A comparative study of four DE variants with two most well-known MO clustering techniques, namely the NSGA II (Non Dominated Sorting GA) and MOCK (Multi- Objective Clustering with an unknown number of clusters K) is also undertaken. Experimental results reported for six artificial and four real life datasets (including a microarray dataset of budding yeast) of varying range of complexities indicates that DE can serve as a promising algorithm for devising MO clustering techniques.
The HCV Revolution Did Not Happen Overnight

The progress in HCV therapy in the last three years is similar to the progress that took HIV therapy ∼14 years. We are at the brink of approval for an all-oral drug combination that is dosed once daily as a single pill, has >95% efficacy, and is well tolerated. This article summarizes the path to this success and the challenges still ahead.
Transition-based Dependency Parsing Using Recursive Neural Networks

In this work, we present a general compositional vector framework for transitionbased dependency parsing. The ability to use transition-based algorithms allows for the application of vector composition to a large set of languages where only dependency treebanks are available, as well as handling linguistic phenomena such as non-projectivities which pose problems for previously proposed methods. We introduce the concept of a Transition Directed Acyclic Graph that allows us to apply Recursive Neural Networks for parsing with existing transition-based algorithms. Our framework captures semantic relatedness between phrases similarly to a constituency-based counterpart from the literature, for example predicting that “a financial crisis”, “a cash crunch” and “a bear market” are semantically similar. Currently, a parser based on our framework is capable of achieving 86.25% in Unlabelled Attachment Score for a well-established dependency dataset using only word representations as input, falling less than 2% points short of a previously proposed comparable feature-based model.
Post-purchase recommendations in large-scale online marketplaces

In this paper, we propose a new method for addressing post-purchase recommendations for a dynamic marketplace. The proposed method uses the transactional data as the primary data source to mine co-purchase relationships. The item listings from the transactional data are mapped to their static `cluster' representation and a cluster-cluster directed graph is generated. Clusters have explicit definitions and thus it allows us to compute content similarity between any two nodes in the cluster-cluster graph. A large marketplace will have a long tail with respect to the demand (purchase) of the items. It is a well-known problem that pure collaborative filtering systems will be unable to provide relevant recommendations for the long tail. One of the important features of our method is in addressing the issue of sparse transactional data. In addition to computing cluster-cluster relationships, we also compute category-category relationships. When our system does not have sufficient data to compute related clusters for a given cluster using the cluster-cluster graph, we use category-category graph, to first find related categories for a given cluster. We show experimental A/B test results showing significant improvement over a previously reported system that solves the same complex problem.
Regions of interest extraction based on HSV color space

In this paper, a simple method to extract regions of interest (ROI) from images is proposed. In the field of image processing, intensity, color and orientation are commonly used features for saliency map generation in most visual attention model. However, texture feature can contribute to the guidance of attention in a bottom-up model. We consider texture contrast as a component of final saliency map. Hue, saturation, and value (HSV) color space is also adopted in this paper for its good capability of representing the colors of human perception and simplicity of computation. Moreover, binocular stereo image pair is adopted as source image. The result shows that the proposed saliency computational method can effectively detect salient region, and it is more suitable for environmental perception and cognition, object detection, and mobile robot navigation.
FPGA kernels for classification rule induction

Classification is one of the core tasks in machine learning data mining. One of several models of classification are classification rules, which use a set of if-then rules to describe a classification model. In this paper we present a set of FPGA-based compute kernels for accelerating classification rule induction. The kernels can be combined to perform specific procedures in rule induction process, such as evaluating rule coverage, or estimating out-of-bag-error. Since classification problems are getting increasingly larger, there is a need for faster implementations of classification rule induction. One of the platforms that offer great potential for accelerating data mining tasks is FPGA (field programmable gate array), which provides the means for implementing application specific accelerators.
Peer-to-Peer Live Streaming

Live streaming is used in today’s Internet to broadcast TV channels and radio stations, usually by deploying streaming servers. Peer-to-peer applications have become popular in recent years to overcome the limitations of centralized servers. This thesis proposes StreamTorrent, a peer-to-peer-based live streaming protocol. In contrast to most protocols, StreamTorrent provides robustness, efficiency, and scalability by combining different strategies. StreamTorrent has the efficiency of typical tree-based and the robustness of more random protocols. An overlay with small diameter and localityawareness reduces latency and network load. And because peer-to-peer computing is about collaboration among peers, incentives are given to peers to share their resources to ensure good playback quality. The StreamTorrent protocol has been implemented and can be used both to perform simulations and to stream in the real world. The simulations allow to evaluate the protocol and to perform automated tests for a large number of peers. The StreamTorrent Player is a real world application supporting live audio and video streaming.
Substructure in the Andromeda Galaxy Globular Cluster System

In the most prominent current scenario of galaxy formation, galaxies form hierarchically through the merger of smaller systems. Such mergers could leave behind dynamical signatures that may linger long after the event. In particular, the globular cluster system (GCS) of a merging satellite galaxy may remain as a distinct subpopulation within the GCS of a massive galaxy. Using the latest available globular cluster velocities and metallicities, we present the results of a search for grouping in the GCS of our nearest large spiral galaxy neighbor, M31. A modified friends-of-friends algorithm is used to identify a number of possible merger remnants in projected position, radial velocity, and [Fe/H] parameter space. Numerical simulations are used to check that such merger remnants are indeed plausible over the timescales of interest. The identification of stellar streams associated with these groups is required in order to confirm that they represent merger remnants.
Effect of Local Search on Edge Histogram Based Sampling Algorithms for Permutation Problems

One of the most promising research directions that focus on eliminating the drawbacks of fixed, problem-independent genetic algorithms, is to look at the generation of new candidate solutions as a learning problem, and use a probabilistic model of selected solutions to generate the new ones [5,9,10]. The algorithms based on learning and sampling a probabilistic model of promising solutions to generate new candidate solutions are called probabilistic model-building genetic algorithms (PMBGAs) [9,10], estimation of distribution algorithms (EDAs) [7], or iterated density estimation algorithms (IDEAs) [1].
A New Hybrid Farsi Text Summarization Technique Based on Term Co-Occurrence and Conceptual Property of the Text

The importance of text summarization grows rapidly as the amount of information increases exponentially. This paper presents a new hybrid summarization technique that combines statistical properties of documents with Farsi linguistic features. The originality of the technique lies on the use of term co-occurrence property of the text. It could detect the number of subjects. The proposed technique summarizes the document in proportion to the subject treated in a document. It considers the conceptual property of the text algorithm and based on word synonymy prevents similar sentences to be included in the summary. It also preserves the cohesion of the summarized text. Our results show better performance in comparison with FarsiSum, well known Farsi Summarizer, which is based only on the heuristic property of the text and do not consider the Farsi challenges.
Circuit solutions on ESD protection design for mixed-voltage I/O buffers in nanoscale CMOS

Electrostatic discharge (ESD) protection for mixedvoltage I/O interfaces has been one of the major challenges of system-on-a-chip (SOC) implementation in nanoscale CMOS processes. Moreover, the gate leakage current across thin gateoxide devices has serious degradation on circuit performance while circuits implementing in nanoscale CMOS processes. The on-chip ESD protection circuit for mixed-voltage I/O buffers should meet the gate-oxide reliability constraints and be designed with consideration of gate leakage current. This paper presents the effective ESD protection scheme with circuit solutions to protect the mixed-voltage I/O buffers in nanoscale CMOS processes against ESD stresses. The proposed ESD protection scheme and the specific ESD clamp circuits with low standby leakage current have been successfully verified in nanoscale CMOS processes. Effective on-chip ESD protection scheme should be early planed and started in the beginning phase of chip design in order to achieve good enough ESD robustness for IC products.
Causality in the United Kingdom: Results from an Open Economy

This study examines money-income causality in the United Kingdom. Unlike most previous studies, this study finds unidirectional causality running from U.K. M1 to U.K. income. Furthermore, U.S. M1 is found to cause U.K. M1 only weakly and does not cause U.K. income. These findings are inconsistent with the view that the United Kingdom functions as a small, open economy. The standard result is that movements in the money supply of the reserve currency country, the United States, leads to movements in the money supply and nominal income of other countries, while the domestic money supply has no impact on domestic income.
Probabilistic Complex Event Recognition

Complex event recognition (CER) applications exhibit various types of uncertainty, ranging from incomplete and erroneous data streams to imperfect complex event patterns. We review CER techniques that handle, to some extent, uncertainty. We examine techniques based on automata, probabilistic graphical models, and first-order logic, which are the most common ones, and approaches based on Petri nets and grammars, which are less frequently used. Several limitations are identified with respect to the employed languages, their probabilistic models, and their performance, as compared to the purely deterministic cases. Based on those limitations, we highlight promising directions for future work.
Optimal reduced-order quadratic solution for the non-Gaussian finite-horizon regulator problem

We consider the optimal regulator for non-Gaussian discrete-time stochastic systems with a quadratic cost function. We improve the method of [1], where the optimal control is derived from the classical LQG solution by substituting the linear filtering part with a quadratic optimal filter. In this paper we delete the unobservable part of the augmented state space, thus guaranteeing the internal stability of the resulting closed-loop system.
Tissue transglutaminase‐catalysed cross‐linking induces Apolipoprotein E multimers inhibiting Apolipoprotein E's protective effects towards amyloid‐beta‐induced toxicity

Cerebral amyloid angiopathy (CAA) is a pathological hallmark of Alzheimer's disease (AD) and characterized by deposition of amyloid‐β (Aβ) protein and smooth muscle cell (SMC) death in cerebral vessel walls. Apolipoprotein E (ApoE) is of importance in both Aβ accumulation and Aβ‐mediated toxicity towards SMCs in the cerebral vessel wall, although its exact role in CAA pathogenesis remains unclear. Tissue transglutaminase (tTG) is an enzyme capable of inducing both protein complexes and altered protein bioactivity via post‐translational cross‐linking. In CAA, tTG and its catalytic activity are associated with deposited Aβ. Furthermore, several apolipoproteins are known substrates of tTG. We therefore investigated whether ApoE is a substrate for tTG and if this affects ApoE's bioactivity. We found strong binding of different ApoE isoforms with tTG and demonstrated tTG‐catalysed ApoE multimers. In post‐mortem human AD cases, ApoE colocalized with in situ active tTG in CAA. Moreover, human brain SMCs treated with Aβ demonstrated enhanced secretion of both ApoE and tTG, and of TG cross‐links in the extracellular matrix. Interestingly, tTG‐catalysed cross‐linked ApoE failed to protect SMCs against Aβ‐mediated cytotoxicity. Together, our data demonstrate a novel tTG‐driven post‐translational modification of ApoE that might play an important role in CAA.
Self-annuitization, ruin risk in retirement and asset allocation: the annuity benchmark

The present paper considers a retiree of a certain age with an initial endowment of investable wealth facing the following alternative investment opportunities. One possibility is to buy a single premium immediate annuity-contract. This insurance contract pays a life-long constant pension payment of a certain amount, depending e.g. on the age of the retiree, the operating cost of the insurance company and the return the company is able to realize from its investments. The alternative possibility is to invest the single premium into a portfolio of mutual funds and to periodically withdraw a fixed amount, in the present paper chosen to be equivalent to the consumption stream generated by the annuity . The particular advantage of this self annuitization strategy compared to the life annuity is its greater liquidity. However, the risk of the second opportunity is to outlive the income stream generated by this investment. The risk in this sense is specified by considering the probability of running out of money before the uncertain date of death. The determination of this personal ruin probability with respect to German mortality and capital market conditions is the objective of the following paper.
Successive interference cancellation for multiuser asynchronous DS/CDMA detectors in multipath fading links

There has been an increasing interest in the use of code-division multiple access (CDMA) in cellular mobile and wireless personal communications. The choice of such multiaccess technique is attractive because of its potential capacity increases and other technical factors such as privacy and multipath rejection capabilities. However, it is well known that the performance of CDMA can be significantly degraded due to cochannel interference (CI) and the near-far effects. We consider the performance of direct-sequence (DS)-based CDMA over fading channels that are modeled as slowly varying Rayleigh-fading discrete multipath channels. Specifically, we propose and analyze an adaptive multistage interference cancellation strategy for the demodulation of asynchronous DS spread-spectrum multiple-access signals. Numerical results show that the proposed multistage detector, which alleviates the detrimental effects of the near-far problem, can significantly improve the system performance.
Application of higher order GLCM features on mammograms

Photographing the changes in internal breast structure due to formation of masses and microcalcification for detection of Breast Cancer is known as Mammogram, which are low dose x-ray images. These images play a very significant role in early detection of breast cancer. Usually in pattern recognition texture analysis is used for classification based on content of image or in image segmentation based on variation of intensities of gray scale levels or colours. Similarly texture analysis can also be used to identify masses and microcalcification in mammograms. However Grey Level Co-occurrence Matrices (GLCM) technique introduced by Haralick was initially used in study of remote sensing images. Up till now in breast cancer detection only first and second order GLCM features were mostly used, to the best of our knowledge there is no evidence of use of higher order GLCM features for detection of malignant masses in breast tissue images. In this paper we attempted up to 7th order and observed the results by analyzing the effects of higher order features in recognition of malignancy in breast mammograms.
The Circumstellar Structure and Excitation Effects around the Massive Protostar Cepheus A HW 2

We report SMA 335 GHz continuum observations with angular resolution of ~0.3'', together with VLA ammonia observations with ~1'' resolution toward Cep A HW 2. We find that the flattened disk structure of the dust emission observed by Patel et al. is preserved at the 0.3'' scale, showing an elongated structure of ~0.6'' size (450 AU) peaking on HW 2. In addition, two ammonia cores are observed, one associated with a hot core previously reported and an elongated core with a double peak separated by ~1.3'', with signs of heating at the inner edges of the gas facing HW 2. The double-peaked ammonia structure, as well as the double-peaked CH3CN structure reported previously (and proposed to be two independent hot cores), surround both the dust emission as well as the double-peaked SO2 disk structure found by Jiménez-Serra et al. All these results argue against the interpretation of the elongated dust-gas structure as due to a chance superposition of different cores; instead, they imply that it is physically related to the central massive object within a "disk-protostar-jet " system.
Mediolateral Compartmentalization of the Cerebellum Is Determined on the “Birth Date” of Purkinje Cells

The adult cerebellum is functionally compartmentalized into clusters along the mediolateral axis (M-L clusters), and a variety of molecular makers are expressed in specific subsets of M-L clusters. These M-L clusters appear to be the basic structure in which cerebellar functions are performed, but the mechanisms by which cerebellar mediolateral compartmentalization is established are still unclear. To address these questions, we examined the development of M-L clusters using replication-defective adenoviral vectors. The adenoviral vectors effectively introduced foreign genes into the neuronal progenitor cells of the cerebellum in a birth date-specific manner, allowing us to observe the native behavior of each cohort of birth date-related progenitor cells. When the adenoviral vectors were injected into the midbrain ventricle of mouse embryos on embryonic days 10.5 (E10.5), E11.5, and E12.5, the virally infected cerebellar progenitor cells developed into Purkinje cells. Notably, the Purkinje cells that shared the same birth date formed specific subsets of M-L clusters in the cerebellum. Each subset of M-L clusters displayed nested and, in part, mutually complementary patterns, and these patterns were unchanged from the late embryonic stage to adulthood, suggesting that Purkinje cell progenitors are fated to form specific subsets of M-L clusters after their birth between E10.5 and E12.5. This study represents the first such direct observation of Purkinje cell development. Moreover, we also show that there is a correlation between the M-L clusters established by the birth date-related Purkinje cells and the domains of engrailed-2, Wnt-7B, L7/pcp2, and EphA4 receptor tyrosine kinase expression.
EFFICIENT TRAJECTORY PROTOCOL FOR MULTICASTING IN VEHICULAR AD HOC

Vehicular ad hoc network is a wireless ad hoc network which carries some important functions such as message forwarding and route determination. In areas where there is sparse density of vehicles the network gets disconnected which affects the communication between the vehicles. In the existing system position based forwarding scheme have been used in which the data will be forwarded based on its position. Initially network will be dividing into small zones. Routing will select by the nodes which are placed in the same zone. Dynamically zones will change, because of node mobility in the network. Hence it is difficult to monitor the zone nodes periodically and Over Head will be high. In this paper multicasting technique is introduced based on trajectories. Here the information will be forwarded to group of destinations. Each node estimate the delivery delay to the access point (AP) based on trajectory. Also predict the future position of the nodes. Finally the source will determine which route has less delay and then it predicts route for data forwarding. Multiple nodes are involved in network for route selection. So easily we can select better route for data forwarding in a multicast way and hence the delay is reduced.