Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid spot instance based resource provisioning strategy in dynamic cloud environment

Utilization of resources to the maximum extent in large scale distributed cloud environment is a major challenge due to the nature of cloud. Spot Instances in the Amazon Elastic Compute Cloud (EC2) are provisioned based on highest bid with no guarantee of task completion but incurs the overhead of longer task execution time and price. The paper demonstrates the last partial hour and cost overhead that can be avoided by the proposed strategy of Hybrid Spot Instance. It aims to provide reliable service to the ongoing task so as to complete the execution without abruptly interrupting the long running tasks by redefining the bid price. The strategy also considers that on-demand resource services can be acquired when spot price crosses on-demand price and thereby availing high reliability. This will overcome the overhead involved during checkpointing, restarting and workload migration as in the existing system, leading to efficient resources usage for both the providers and users. Service providers revenue is carefully optimized by eliminating the free issue of last partial hour which is a taxing factor for the provider. Simulation carried out based on real time price of various instances considering heterogenous applications shows that the number of out-of-bid scenarios can be reduced largely which leads to the increased number of task completion. Checkpointing is also minimized maximally due to which the overhead associated with it is reduced. This resource provisioning strategy aims to provide preference to existing customers and the task which are nearing the execution completion.
Cernunnos/XLF promotes the ligation of mismatched and noncohesive DNA ends

Nonhomologous end-joining (NHEJ) repairs DNA double-strand breaks created by ionizing radiation or V(D)J recombination of the immunoglobulin genes. The breaks often leave mismatched or nonligatable ends, and NHEJ must repair the breaks with high efficiency and minimal nucleotide loss. Here, the NHEJ proteins Ku, DNA-dependent protein kinase catalytic subunit, XRCC4/Ligase IV, and Cernunnos/XRCC4-like factor joined mismatched and noncohesive DNA ends in the absence of processing factors. Depending on the mismatch, Cernunnos stimulated joining 8- to 150-fold. For substrates with a blunt end and a 3′ overhanging end, Ku, XRCC4/Ligase IV, and Cernunnos ligated the 3′ overhanging hydroxyl group to the 5′ phosphate of the blunt end, leaving the other strand unjoined. This activity provides a mechanism for retaining 3′ overhang sequences, as observed during V(D)J recombination in vivo. Thus, Cernunnos/XRCC4-like factor promotes a mismatched end (MEnd) DNA ligase activity to facilitate joining and to preserve DNA sequence. Furthermore, MEnd ligase activity may have applications in recombinant DNA technology.
Generalized Dix equation and analytic treatment of normal‐moveout velocity for anisotropic media *

Despite the complexity of wave propagation in anisotropic media, reflection moveout on conventional common‐midpoint (CMP) spreads is usually well described by the normal‐moveout (NMO) velocity defined in the zero‐offset limit. In their recent work, Grechka and Tsvankin showed that the azimuthal variation of NMO velocity around a fixed CMP location generally has an elliptical form (i.e. plotting the NMO velocity in each azimuthal direction produces an ellipse) and is determined by the spatial derivatives of the slowness vector evaluated at the CMP location. This formalism is used here to develop exact solutions for the NMO velocity in anisotropic media of arbitrary symmetry.
Asymptomatic Deep Vein Thrombosis in a Patient with Major Depressive Disorder

Pulmonary embolism is a serious, life-threatening condition and most commonly derives from deep vein thrombosis of the lower extremities. Once deep vein thrombosis (DVT) reaches a proximal vein (i.e., popliteal vein or higher), pulmonary embolism reportedly occurs in up to 50% of patients. Case Presentation. We report on an inpatient with major depressive disorder in a catatonic state in whom an asymptomatic proximal deep vein thrombosis of 11 × 70 mm was detected through routine screening, using doppler ultrasound scanning. Anticoagulant therapy was immediately started and continued for three months, which resulted in resolution of the deep vein thrombosis. Discussion. To our knowledge, this is the first description of asymptomatic proximal DVT that was detected in a psychiatric inpatient setting. In light of the reported causal relationship between DVT and pulmonary embolism, screening for DVT can be of high clinical value in patients with psychiatric disorders, especially when their physical activity is highly compromised.
Applying Eecient Techniques for Finding Nearest Neighbours in Gis Applications

Current GIS applications typically involve very large data sets. In order to utilise this wealth of information, new tools capable of handling the increases in data must be developed. In this article, we discuss some methods to nd nearest neighbours eeciently. The results show that the cell method ooers signiicant increase in eeciency over other methods when used to cluster large data sets.
Self-initiated international career transition: a qualitative case study of Pakistani immigrants to Canada

Purpose The purpose of this study is to examine the career transition experiences of three immigrants from Pakistan in Canadian organisations using Nicholson’s four-phase transition cycle. Design/methodology/approach A case study approach was used, and data were collected through three in-depth, semi-structured interviews to determine how immigrants experience career transitions in Canadian organisations. Findings The findings show that all three participants had almost the same level of expectations before coming to Canada; however, there were significant differences in their career transition experiences. These findings demonstrate that immigrants’ career experiences can be understood and examined through the lens of Nicholson’s transition framework; their expectations and experiences at one stage subsequently affected their experiences at later stages. Research limitations/implications A longitudinal research design would be an excellent approach to explore immigrants’ career transition over time. Practical implications Organisations hiring skilled immigrants need to be more supportive of their efforts in reducing immigrants’ feeling of underemployment and discrimination. Originality/value The study contributes to the immigrant literature by presenting a new way of looking at immigrants’ experiences in Canadian organisations. It also contributes to the career literature by extending the application of Nicholson transition cycle to an underrepresented population (i.e. immigrants) in careers research.
Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics

Computer vision systems have demonstrated considerable improvement in recognizing and verifying faces in digital images. Still, recognizing faces appearing in unconstrained, natural conditions remains a challenging task. In this paper, we present a face-image, pair-matching approach primarily developed and tested on the “Labeled Faces in the Wild” (LFW) benchmark that reflects the challenges of face recognition from unconstrained images. The approach we propose makes the following contributions. 1) We present a family of novel face-image descriptors designed to capture statistics of local patch similarities. 2) We demonstrate how unlabeled background samples may be used to better evaluate image similarities. To this end, we describe a number of novel, effective similarity measures. 3) We show how labeled background samples, when available, may further improve classification performance, by employing a unique pair-matching pipeline. We present state-of-the-art results on the LFW pair-matching benchmarks. In addition, we show our system to be well suited for multilabel face classification (recognition) problem, on both the LFW images and on images from the laboratory controlled multi-PIE database.
Spatial Topology Graphs for Feature-Minimal Correspondence

Multiview image matching methods typically require feature point correspondences. We propose a novel spatial topology method that represents the space with a set of connected projective invariant features. Typically, isolated features, such as corners, cannot be matched reliably. Hence, limitations are imposed on viewpoint changes, or projective invariant descriptions are needed. The fundamental matrix is discovered using stochastic optimization requiring a large number of features. In contrast, our enhanced feature set models connectivity in space, forming a unique configuration that can be matched with few features and over large viewpoint changes. Our features are derived from edges, their curvatures, and neighborhood relationships. A probabilistic spatial topology graph models the space using these features and a second graph represents the neighborhood relationships. Probabilistic graph matching is used to find feature correspondences. Our results show robust feature detection and an average 80% discovery rate of feature matches.
Design of lifting permanent magnet based on neural network

A novel and saving energy logistics handling equipment — Rare Earth Lifting Permanent Magnet was designed, which can completely overcome the disadvantages found from lifting electromagnet. The working principle and neural network model of magnetic circuit design were developed. At the same time, a perfect self-acting driving system was invented, which guarantees that the attracted ferromagnetic cargo or products can be lifted or unloaded fast and conveniently without using any electricity at all. Industry prototypes were manufactured, and they verified that the proposed design for Rare Earth Lifting Permanent Magnet was feasible.
Linked models@runtime to ease the administration of pervasive applications

Pervasive applications are often executed in fluctuating conditions and need frequent adaptations to meet requirements. Autonomic computing techniques are frequently used to automate adaptations to changing execution conditions. However, some administration tasks still have to be performed by human administrators. Such tasks are very complex because of a lack of understanding of the system current state. In this paper, we propose to build and link models at runtime of supervised applications in order to ease the administrators' job. Our approach is illustrated on a health application called actimetrics, developed with Orange Labs.
Transmit Power Allocation among PSWF-based Pulse Wavelets in Cognitive UWB Radio

Ultra wideband (UWB) technology has been considered as one of the suitable transmission techniques for implementing a cognitive radio system, where spectrum-agile UWB waveforms achieve adaptation features. One approach for designing such waveforms relies on orthogonally combining PSWF-based pulse wavelets. In a cognitive UWB radio environment with N users, with respect to the case of one sub-band accessed by one user, whose transmitting signal is M-ary pulse shape modulated, we get different eigenvalues by transmitting these pulses in a multipath fading channel, we propose water filling scheme, depending on the different eigenvalues, to optimize the power allocation among them. Simulation results show that the scheme improves the sub-band channel data throughput compared with the scheme that power is equal allocated among these pulse wavelets, when the SNR is low, which is the normal case in UWB communications
An Extended Frequent Pattern Mining for Privacy Preserving transactional data set using

Privacy preservation of transactional data set has more influence in business solutions where the transactional data set of any organization can be used by many others for different purposes. Hiding sensitive information about the customers of any organization becomes the responsibility of the organization which implicates the trustworthy of organization on customers. We propose a new extended frequent pattern mining technique for the preservation of sensitive information about the customers. The general support count based frequent pattern mining technique is used to identify the sensitive transactions and based on that a probabilistic solution is used to generate the sanitized data set. The sanitized data set preserves the originality of the transactional data and the user could compute much information for their purpose. The probabilistic model computes the probability of sensitive attributes and used to generate the sanitized data set. We used random selection of attribute in the sensitive transaction to generate sanitized data set.
Estimating Sparse Precision Matrix: Optimal Rates of Convergence and Adaptive Estimation

Precision matrix is of significant importance in a wide range of applications in multivariate analysis. This paper considers adaptive minimax estimation of sparse precision matrices in the high dimensional setting. Optimal rates of convergence are established for a range of matrix norm losses. A fully data driven estimator based on adaptive constrained l1 minimization is proposed and its rate of convergence is obtained over a collection of parameter spaces. The estimator, called ACLIME, is easy to implement and performs well numerically. A major step in establishing the minimax rate of convergence is the derivation of a rate-sharp lower bound. A “two-directional” lower bound technique is applied to obtain the minimax lower bound. The upper and lower bounds together yield the optimal rates of convergence for sparse precision matrix estimation and show that the ACLIME estimator is adaptively minimax rate optimal for a collection of parameter spaces and a range of matrix norm losses simultaneously.
Risk factors for the onset of prostatic cancer: age, location, and behavioral correlates

At present, only three risk factors for prostate cancer have been firmly established; these are all nonmodifiable: age, race, and a positive family history of prostate cancer. However, numerous modifiable factors have also been implicated in the development of prostate cancer. In the current review, we summarize the epidemiologic data for age, location, and selected behavioral factors in relation to the onset of prostate cancer. Although the available data are not entirely consistent, possible preventative behavioral factors include increased physical activity, intakes of tomatoes, cruciferous vegetables, and soy. Factors that may enhance prostate cancer risk include frequent consumption of dairy products and, possibly, meat. By comparison, alcohol probably exerts no important influence on prostate cancer development. Similarly, dietary supplements are unlikely to protect against the onset of prostate cancer in healthy men. Several factors, such as smoking and obesity, show a weak association with prostate cancer incidence but a positive relation with prostate cancer mortality. Other factors, such as fish intake, also appear to be unassociated with incident prostate cancer but show an inverse relation with fatal prostate cancer. Such heterogeneity in the relationship between behavioral factors and nonadvanced, advanced, or fatal prostate cancers helps shed light on the carcinogenetic process because it discerns the impact of exposure on early and late stages of prostate cancer development. Inconsistent associations between behavioral factors and prostate cancer risk seen in previous studies may in part be due to uncontrolled detection bias because of current widespread use of prostate-specific antigen testing for prostate cancer, and the possibility that certain behavioral factors are systematically related to the likelihood of undergoing screening examinations. In addition, several genes may modify the study results, but data concerning specific gene–environment interactions are currently sparse. Despite large improvements in our understanding of prostate cancer risk factors in the past two decades, present knowledge does not allow definitive recommendations for specific preventative behavioral interventions.
The Influence of Technological Links, Social Ties, and Incumbent Firm Opportunistic Propensity on the Formation of Corporate Venture Capital Deals

New ventures often innovate by building on the technology of incumbent firms. The resulting technological links that form between new ventures and incumbents can open up valuable collaborative opportunities between them. Nonetheless, because these technological links also increase incumbents’ abilities to misappropriate the knowledge of new ventures, such collaboration can render new ventures particularly susceptible to the opportunistic whims of their incumbent partners. Whether technological links promote or impede corporate venture capital (CVC) deal formation may depend on incumbent firms’ propensities to behave opportunistically and how aware new ventures are of such propensities. We argue that when new ventures have social ties to incumbent firms that have opportunistic tendencies, technological links between them strongly impede CVC deal formation. In such cases, social ties substantiate new ventures’ fears of knowledge misappropriation that might occur. In contrast, when new ventures have social ties to incumbent firms that lack opportunistic tendencies, technological links between them strongly promote CVC deal formation as social ties validate the incumbent firm’s trustworthiness and the potential for productive collaboration as a result of technological links. Using a data set that integrates patent citations, hand-collected career histories, and infringement lawsuits, we tracked the investment pattern between 29 incumbents and 402 new ventures in the U.S. information technology industry and found support for our arguments.
Recurrent Inhibitory Network among Striatal Cholinergic Interneurons

The striatum plays a central role in sensorimotor learning and action selection. Tonically active cholinergic interneurons in the striatum give rise to dense axonal arborizations and significantly shape striatal output. However, it is not clear how the activity of these neurons is regulated within the striatal microcircuitry. In this study, using rat brain slices, we find that stimulation of intrastriatal cholinergic fibers evokes polysynaptic GABAA IPSCs in cholinergic interneurons. These polysynaptic GABAA IPSCs were abolished by general nicotinic acetylcholine receptor antagonists and also by a specific antagonist of nicotinic receptors containing β2 subunits. Dopamine receptor antagonists or dopamine depletion failed to block polysynaptic IPSCs, indicating that phasic dopamine release does not directly mediate the polysynaptic transmission. Dual recording from pairs of cholinergic interneurons revealed that activation of a single cholinergic interneuron is capable of eliciting polysynaptic GABAA IPSCs both in itself and in nearby cholinergic interneurons. Although polysynaptic transmission arising from a single cholinergic interneuron was depressed during repetitive 2 Hz firing, intrastriatal stimulation reliably evoked large polysynaptic IPSCs by recruiting many cholinergic fibers. We also show that polysynaptic GABAergic inhibition leads to a transient suppression of tonic cholinergic interneuron firing. We propose a novel microcircuit in the striatum, in which cholinergic interneurons are connected to one another through GABAergic interneurons. This may provide a mechanism to convert activation of cholinergic interneurons into widespread recurrent inhibition of these neurons via nicotinic excitation of striatal GABAergic neurons.
Automated Schematic Mapping for MobileGIS: Technical developments and Human Factors requirements

This paper looks at how human factors requirements can be considered in the context of graphic conflict reduction for mobile GIS applications. Currently this reduction is achieved by using schematic mapping techniques. With the advent of high-end miniature technology as well as digital geographic data products like OSMasterMap and OSCAR, it is essential to devise proper methodologies for map generalization specifically tailored for MobileGIS applications. This paper is concerned with the problem of producing schematic maps suitable for rendering on mobile display devices (e.g. PDAs). The application of schematic mapping can be thought of as a data reduction technique for large scale datasets to make it suitable for rendering in mobile applications. These techniques have been based on computation and have not incorporated any understanding of how the simplification affects the ease of use of the maps. It is therefore desirable to devise suitable generalization techniques incorporating human factors considerations for generating schematic maps from large scale datasets for display on small display devices to be used for MobileGIS applications
Two Novel 802.1x Denial of Service Attacks

Denial of Service (DoS) attacks are among the most common security issues threatening today's 802.11 networks. In this paper, we have proposed two 802.1x DoS attacks, EAP-NAK and EAP-Notification flooding attacks. These effectively disrupt the authentication process between the legitimate wireless supplicants and the network authentication server. The evaluation of these attacks against EAP is performed using well-suited metrics which highlight their impact on the targeted network in practice. Furthermore, we discuss possible techniques to detect these attacks, such as configuring the WIDS to create a performance baseline of the wireless network. Lastly, several techniques and solutions were discussed which can be applied to the 802.11i standard in order to enhance the security of the 802.1x for dealing with DoS attacks, such as the use of a process delay time technique.
Specialization in habitat use by coral reef damselfishes and their susceptibility to habitat loss

While it is generally assumed that specialist species are more vulnerable to disturbance compared with generalist counterparts, this has rarely been tested in coastal marine ecosystems, which are increasingly subject to a wide range of natural and anthropogenic disturbances. Habitat specialists are expected to be more vulnerable to habitat loss because habitat availability exerts a greater limitation on population size, but it is also possible that specialist species may escape effects of disturbance if they use habitats that are generally resilient to disturbance. This study quantified specificity in use of different coral species by six coral-dwelling damselfishes (Chromis viridis, C. atripectoralis, Dascyllus aruanus, D. reticulatus, Pomacentrus moluccensis, and P. amboinensis) and related habitat specialization to proportional declines in their abundance following habitat degradation caused by outbreaks of the coral eating starfish, Acanthaster planci. The coral species preferred by most coral-dwelling damselfishes (e.g., Pocillopora damicornis) were frequently consumed by coral eating crown-of-thorns starfish, such that highly specialized damselfishes were disproportionately affected by coral depletion, despite using a narrower range of different coral species. Vulnerability of damselfishes to this disturbance was strongly correlated with both their reliance on corals and their degree of habitat specialization. Ongoing disturbances to coral reef ecosystems are expected, therefore, to lead to fundamental shifts in the community structure of fish communities where generalists are favored over highly specialist species.