Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximate frequent itemsets compression using dynamic clustering method

Frequent-itemsets mining often faces the problem of generating a large collection of frequent itemsets, which is too large to be carefully examined and understood by the users. To reduce the output size of frequent itemsets, we propose using a dynamic clustering method to compress the frequent itemsets approximately in this paper. Concretely, two frequent itemsets intra-cluster similarities, expression similarity and support similarity, are defined according to the specific requirements of frequent itemsets compression. Based on the above two similarity measures, the frequent itemsets clustering criterion and its related clustering algorithm are developed. Specially, our method has two features: 1)users neednpsilat specify the number of frequent itemsets clusters explicitly; 2)userpsilas expectation of compression ratio is incorporated. Our initial experimental results show that our approximate frequent itemsets method is feasible and the compression quality is good.
Organization of connections between the amygdaloid complex and the perirhinal and parahippocampal cortices in macaque monkeys

Neuroanatomical studies in macaque monkeys have demonstrated that the perirhinal and parahippocampal (PRPH) cortices are strongly interconnected with the hippocampal formation. Recent behavioral evidence indicates that these cortical regions are importantly involved in normal recognition memory function. The PRPH cortices are also interconnected with the amygdaloid complex, although comparatively little is known about the precise topography of these connections. We investigated the topographic organization of reciprocal connections between the amygdala and the PRPH cortices by placing anterograde and retrograde tracers throughout these three regions. We found that there was an organized arrangement of connections between the amygdala and the PRPH cortices and that the deep (lateral, basal, and accessory basal) nuclei of the amygdaloid complex were the source of most connections between the amygdala and the PRPH cortices. The temporal polar regions of the perirhinal cortex had the strongest and most widespread interconnections with the amygdala. Connections from more caudal levels of the perirhinal cortex had a more discrete pattern of termination. Perirhinal inputs to the amygdala terminated primarily in the lateral nucleus, the magnocellular and parvicellular divisions of the basal nucleus, and the magnocellular division of the accessory basal nucleus. Return projections originated predominately in the lateral nucleus, the intermediate and parvicellular divisions of the basal nucleus, and the magnocellular division of the accessory basal nucleus. The interconnections between the amygdala and the parahippocampal cortex were substantially less robust than those with the perirhinal cortex and mainly involved the basal nucleus. Area TF was more strongly interconnected with the amygdala than was area TH. Input from the parahippocampal cortex terminated predominantly in the lateral half of the parvicellular division of the basal nucleus but also to a lesser extent in the magnocellular division of the basal nucleus and the lateral nucleus. Return projections originated predominantly in the magnocellular division of the basal nucleus and were directed almost exclusively to area TF. © 1996 Wiley‐Liss, Inc.
An Automatic Debugging Tool Extension for Object Oriented Softwares

-In the process of Software Development and evolution, Developer has to answer multiple questions about how the code or software behaves at runtime. The traditional or classical debugger while debugging gives developer bunch of breakpoints in the source code. Object based debugging offer, interruption when a given or a particular object is accessed or modified. Programmers, who try to find violations in such source code, need new tool that allows them to explore objects in the system effectively. The implementation of the proposed debugging actually offers programmers an effective tool which will allows searching of objects even for programs that have huge number of objects. As stated from traditional tools that, the complexity of object oriented system increases, debugging becomes relatively difficult. Developer needs a dedicated user interface for these operations on objects; this need is fulfilled by facilitating a user interface for the programmer. Object based debugging tool looks forward to analyse the relationship in between the objects during the runtime. So the key behind this is to focus on a particular object instead of the execution stack. This allows functioning operations directly on objects rather than on the execution stack. The presented tool can allow user or a developer, different operations, which going to perform on a particular object. There exists therefore conceptual gap between the interface offered by the debugger and the need of the developer, hence to overcome or fill the gap; there is a need for object based debugger and useful interface for it.
Noncommutative Kaluza-Klein theory

Efforts have been made recently to reformulate traditional Kaluza-Klein theory by using a generalized definition of a higher-dimensional extended space-time. Both electromagnetism and gravity have been studied in this context. We review some of the models which have been proposed, with a special effort to keep the mathematical formalism to a very minimum.
Percutaneous image-guided cutting needle biopsy of the pleura in the diagnosis of malignant mesothelioma.

STUDY OBJECTIVES Pleural fluid cytology and non-image-guided Abrams or Cope biopsies have sensitivities of approximately 30% for detecting malignant mesothelioma, and thoracoscopic biopsy has a sensitivity of approximately 90%. The difference between these two probably relates to obtaining adequate tissue. The use of immunohistochemical stains allows a firm diagnosis to be made from relatively small samples. This study explores whether percutaneous image-guided cutting needle biopsy (CNB) combined with immunohistochemistry is accurate in diagnosing pleural thickening due to mesothelioma. DESIGN Retrospective review of image-guided CNB of pleural thickening performed on consecutive patients over 7 years by a single radiologist. SETTING Teaching hospital chest radiology department. PATIENTS Twenty-one adult patients with a final diagnosis of malignant mesothelioma were identified from 53 consecutive patients who underwent percutaneous image-guided CNB. All 21 patients had pleural thickening identified on contrast-enhanced CT, and all had a final histologic diagnosis of mesothelioma confirmed by postmortem examination or thoracoscopy. INTERVENTIONS Fourteen-gauge and 18-gauge cutting needles were used. Biopsy guidance was by ultrasound in 6 patients and by CT in 15 patients. MEASUREMENTS AND RESULTS A correct histologic diagnosis of malignant mesothelioma was made by CNB in 18 patients (86% sensitivity and 100% specificity). Complications included one chest wall hematoma and a small hemoptysis. Four patients with a pleural thickness of < or = 5 mm underwent biopsy, and all specimens were diagnostic for mesothelioma. CONCLUSIONS Image-guided percutaneous CNB of pleural thickening is a safe procedure, with 86% sensitivity for detecting malignant mesothelioma. Pleural thickening of < or = 5 mm may be successfully sampled.
A Parallel Method for Generating Pseudorandom Binary Markovian Sequences

This paper describes a deterministic two-layer cellular array in which many virtual particles move pseudorandomly. The motion of the particles is defined by a two-state Markov chain. A parameter of the cellular array determines the eigenvalue of the transition matrix which defines the Markov chain. Thus, the cellular array can generate pseudorandom binary sequences with exponentially vanishing autocorrelation in parallel. Since such binary sequences can be used for spreading codes with excellent co-channel interference reduction in asynchronous DS/CDMA communications, the cellular array is expected to be applied to the communication systems. Numerical experiments show that the sequences generated by the cellular array have almost the same probability distribution and correlation properties as the sequences generated by truly probabilistic two-state Markovian systems have
Performance Evaluation of Hypervisors in the Private Cloud based on System Information using SIGAR Framework and for System Workloads using Passmark

Hypervisors using virtualization technology enable multiple operating systems to run on one physical server. Cloud computing model is less expensive because it streamlines the delivery of services by providing a stage for optimizing complex IT resources in a scalable manner with the help of virtualization technology and hypervisors. Selecting a suitable hypervisor for their organization’s private cloud is herculean task for modern CIOs. Hypervisor vendors do claim that they have negated virtualization overhead completely compare to native system, but still there exists minute virtualization overhead because virtual machines have to communicate with middle-layer hypervisor to access the underlying physical hardware and also there is an impact of other virtual machines running on the same hypervisor. Hypervisors are developed using different virtualization techniques like full virtualization, para-virtualization and hybrid model virtualization. This paper evaluates the performance of three hypervisors ESXi, XenServer and KVM using SIGAR framework for system information and Passmark for system workloads in the private cloud environment. Private cloud has been designed using open source cloud computing software CloudStack. Hypervisors are deployed as hosts in the CloudStack. This paper recommends best suited hypervisors for respective workloads in the private cloud based on the performance of system information and system workloads.
Quantifying Antimicrobial Resistance at Veal Calf Farms

This study was performed to determine a sampling strategy to quantify the prevalence of antimicrobial resistance on veal calf farms, based on the variation in antimicrobial resistance within and between calves on five farms. Faecal samples from 50 healthy calves (10 calves/farm) were collected. From each individual sample and one pooled faecal sample per farm, 90 selected Escherichia coli isolates were tested for their resistance against 25 mg/L amoxicillin, 25 mg/L tetracycline, 0.5 mg/L cefotaxime, 0.125 mg/L ciprofloxacin and 8/152 mg/L trimethoprim/sulfamethoxazole (tmp/s) by replica plating. From each faecal sample another 10 selected E. coli isolates were tested for their resistance by broth microdilution as a reference. Logistic regression analysis was performed to compare the odds of testing an isolate resistant between both test methods (replica plating vs. broth microdilution) and to evaluate the effect of pooling faecal samples. Bootstrap analysis was used to investigate the precision of the estimated prevalence of resistance to each antimicrobial obtained by several simulated sampling strategies. Replica plating showed similar odds of E. coli isolates tested resistant compared to broth microdilution, except for ciprofloxacin (OR 0.29, p≤0.05). Pooled samples showed in general lower odds of an isolate being resistant compared to individual samples, although these differences were not significant. Bootstrap analysis showed that within each antimicrobial the various compositions of a pooled sample provided consistent estimates for the mean proportion of resistant isolates. Sampling strategies should be based on the variation in resistance among isolates within faecal samples and between faecal samples, which may vary by antimicrobial. In our study, the optimal sampling strategy from the perspective of precision of the estimated levels of resistance and practicality consists of a pooled faecal sample from 20 individual animals, of which 90 isolates are tested for their susceptibility by replica plating.
Physical Disability and Increased Loneliness among Married Older Adults

Examining the social context of disablement, we investigated how changes in social relations affect loneliness among married older men and women. With longitudinal data on 914 married persons from the National Social Life, Health, and Aging Project (NSHAP), we found that changes in the quality of marital and nonmarital relations moderate the effect of disability on loneliness in unexpected ways. Increases in negative marital quality buffer the effect of physical disability, while increases in nonmarital support exacerbate it. Although not predicted by existing theory, these findings are consistent with some prior work suggesting that health-related stressors, like physical disability, condition the meaning of changes in social relations. We find, however, that negative social relations ameliorate loneliness only among disabled married men; disabled married women experience increased loneliness under similar circumstances. These differences have not been previously identified. We conclude by discussing the gendered nature of the social context of disablement.
An efficient sequential procedure for detecting changes in multichannel and distributed systems

In the conventional formulation of the change-point detection problem, there is a sequence of observations whose distribution changes at some unknown point in time, and the goal is to detect this change as quickly as possible, subject to false alarm constraints. It is known that in the case where the observations are i.i. d. and the change point is modeled as deterministic but unknown, the cumulative sum (CUSUM) detection procedure of Page (1954) and the randomized Shiryaev-Roberts detection procedure proposed by Pollak (1985) minimize the expected detection lag, subject to a constraint on the false alarm rate. In this paper, we are interested in the two generalizations of this problem. The first is the generalization regarding multichannel systems. Here all the channels are either statistically identical or the change occurs in one of them at unknown point in time. It is necessary to detect the change in distribution as soon as possible after it occurs, while controlling the rate of false alarms at a given level. The second generalization corresponds to the multi-sensor situation where the information available for decision-making is distributed across a set of sensors. The sensors send quantized versions of their observations to a fusion center where the change detection is performed based on all the sensor messages. We propose multi-channel and distributed versions of the CUSUM procedure and prove that they are asymptotically optimal as the average frequency of false alarms goes to zero. The general results are applied to the two important application areas-target detection in surveillance systems and attack/intrusion detection in distributed computer networks. Experimental results show that the proposed detection methods are highly efficient.
ORGANIZATIONAL KNOWLEDGE ABOUT INNOVATION : LESSONS FROM INNOVATIVE SCHOOL PRACTICES

This paper reports on findings from a qualitative inquiry about the basis on which innovative schools have sustained changes over time. Participant schools were reported by external advisers as they had institutionalized a recognisable dynamic of changes. The focus of the inquiry includes: organizational culture, informal structures of power; leadership practices and styles and relationship patterns among internal and external educational agents. A relevant local knowledge that shapes innovation practices was also identified. This practice based knowledge allows us to discuss some common assumptions of the theory of educational change.
UNDERSTANDING PRIME-TO-BEHAVIOR EFFECTS: INSIGHTS FROM THE ACTIVE-SELF ACCOUNT

In this paper, we provide a brief review of prime-to-behavior effects and discuss our theoretical model for such effects: the Active-Self Account. We also address recent discussions in the literature regarding the replicability of prime-to-behavior effects and outline features that can affect their existence and the likelihood of detecting such effects experimentally.
A Game Theory Based WiMAX Uplink Power Control Algorithm

The power control is a crucial technology in wireless communication. IEEE 802.16 protocol suggests that WiMAX system should adopt power control technology on the uplink channel, and requires its performance, which will ensure the quality of communications and suppress the co-channel interference. However, the exact algorithm is vendor-specific. In this paper, the game theory was applied to WiMAX uplink power control. All co-channel users were game participants, and their uplink power was used as a strategy to achieve Nash equilibrium. The simulation results show that this algorithm can control uplink power and ensure communications quality, at the same time, the pricing factor λ will affect the convergence speed and convergence power of algorithm.
Random polymatroid flow problems

We generalize the so-called random assignment problem to a setting where we impose a polymatroid structure on the two vertex-sets of a complete bipartite graph, and ask for an edge set of prescribed size connecting independent sets. As an application, we show that under independent exponential edge-costs, the cost of the cheapest edge set covering all vertices of annbynbipartite graph is asymptotically W(1) 2 +2 W(1)! 1.456, whereWis the LambertW-function. In particular it is essentially cheaper than the cheapest perfect matching, whose cost is asymptotically! 2 /6! 1.645.
Community structure in P2P networks

Community structure is a very important property of complex networks. Detecting communities in networks is of great importance in biology, computer science, sociology and so on. In recent years, peer-to-peer (P2P) networks have gained a lot of popularity, but it is still quite difficult to acquire global statistical information. Studying community structure will help researchers use partial statistical information to estimate the global statistical information. This paper reviews some basic concepts, new progress, important algorithms and significant results in the current studies of community structure in P2P networks.
Fault-Tolerant Design for Systems-on-Chip with Early Error Detection �

In this paper we propose a new method for the design of duplex fault-tolerant systems with early error detection and high availability. All the scannable memory elements (FlipFlops) of the duplicated system are implemented as multimode memory elements according to [1] allowing during normal operation to accumulate a signature of its states in its scan-paths. By continously comparing a 1-bit sequence of the compacted scan-out outputs of the accumulated signatures of the duplicated systems an error can be already detected and a recovery procedure started before an erroneous result appears at the system outputs when a computations is completed.
SVM-Based Spam Filter with Active and Online Learning

A realistic classification model for spam filtering should not only take account of the fact that spam evolves over time, but also that labeling a large number of examples for initial training can be expensive in terms of both time and money. This paper address the problem of separating legitimate emails from unsolicited ones with active and online learning algorithm, using a Support Vector Machines (SVM) as the base classifier. We evaluate its effectiveness using a set of goodness criteria on TREC2006 spam filtering benchmark datasets, and promising results are reported.
A New Methodology for 3D Target Detection in Automotive Radar Applications

Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS). In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS) theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach.
Residue packing in proteins: Uniform distribution on a coarse-grained scale

The high packing density of residues in proteins ought to be manifested in some order; to date this packing order has not been thoroughly characterized. The packing regularity in proteins is important because the internal organization of proteins can have a dominant effect on functional dynamics, and it can aid in the design, simulation and evaluation of structures. Packing metrics could also inform us about normal sequence variability, an issue that, with the accumulating genome data, becomes increasingly important. Other studies, indicating a possible correlation between packing density, sequence conservation, and folding nucleation [O. B. Ptitsyn, J. Mol. Biol. 278, 655 (1998)], have emphasized the importance of packing. Here, residue clusters from protein databank structures, each comprised of a central residue and all neighbors located within the first coordination shell, have been rigidly re-oriented and superimposed in a self-consistent optimization. About two-thirds of residues are found to follow.
Distance based Clustering for Categorical Data

Learning distances from categorical attributes is a very useful data mining task that allows to perform distance-based techniques, such as clustering and classification by similarity. In this article we propose a new context-based similarity measure that learns distances between the values of a categorical attribute (DILCA DIstance Learning of Categorical Attributes). We couple our similarity measure with a famous hierarchical distance-based clustering algorithm (Ward’s hierarchical clustering) and compare the results with the results obtained from methods of the state of the art for this research field.
A Diarylheptanoid Exhibits Protective effects against Amyloid-β Induced Cytotoxicity

Alzheimer’s disease (AD) is a severe neurodegenerative disorder characterized by β-amyloid (Aβ) plaques, neurofibrillary tangles, neuronal death, progressive cognitive impairment and memory loss. β-amyloid peptides (Aβ) are major compositions of so-called senile plaques, which are hallmarks of AD and contribute to AD progression. Therefore, it is important to discover therapeutics against Aβ-induced toxicity. Here, we report that 7(4Hydroxyphenyl)1phenyl-4E-hepten-3-one (AO-1), a diarylheptanoid extracted from the rhizomes of Alpinia officinarum, showed effects against Aβ-induced cytotoxicity. The results demonstrated that AO-1 possesses neuroprotective activities which are capable of maintaining normal cell viability of PC12 cells and primary cortical neurons after Aβ insult.