Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple-quality of protection classes including dual-failure survivable services in p-cycle networks

We develop design theory and related operating concepts to support multiple differentiated levels of survivability assurances for individual demands in a transport network that uses p-cycles as the basic protection method. Notably this includes an ultra-high availability (dual span failure protected) service class that is based on principles that are unique to p-cycles for dual failure protection without dynamic reconfiguration of p-cycles. Results show that p-cycle based networks operating this way could offer dual failure protection to as much as 30% of all demands in the test cases with essentially the same redundancy as the single-failure protected design. These ideas and methods can enhance the cost-competitiveness of transport network operators and enable a range of service offerings to best suit actual customer requirements on transport survivability.
Incongruence between workload and occupational norms for time pressure predicts depressive symptoms

In light of recent scholarship on the role of fairness and legitimacy in occupational strain, we tested in two studies the hypothesis that workload is more strongly associated with depressive symptoms when it exceeds occupational norms for time pressure. First, analyses of an occupationally heterogeneous sample revealed that when workers reported workload levels that exceeded occupational norms for time pressure they were more likely to report depressive symptoms, even after controlling for depressive symptoms from a prior assessment approximately 10 years earlier. A second cross-sectional study found similar results, with some of the effect accounted for by psychological contract violation. These findings suggest that workload is most strongly associated with depressive symptoms to the extent that it exceeds occupational norms for time pressure. Psychological contract violation may explain some of these effects.
Connectomics: A New Direction in Research to Understand the Mechanism of Acupuncture

Acupuncture has been used to treat various disorders in China and some other eastern countries for thousands of years. Nowadays, acupuncture is gradually accepted as an alternative and complementary method in western countries for its undeniable therapeutic effects. However, its central mechanism is still unclear. It is especially difficult to reveal how different regions in the brain influence one another and how the relationship is among these regions responding to acupuncture treatment. Recently, by applying neuroimaging techniques and network theory, acupuncture studies can make further efforts to investigate the influence of acupuncture on regional cerebral functional connectivity (FC) and the modulation on “acupuncture-related” networks. Connectomics appears to be a new direction in research to further understand the central mechanism underlying acupuncture. In this paper, an overview of connectomics application in acupuncture research will be discussed, with special emphasis on present findings of acupuncture and its influence on cerebral FC. Firstly, the connectomics concept and its significance on acupuncture will be outlined. Secondly, the commonly used brain imaging techniques will be briefly introduced. Thirdly, the influence of acupuncture on FC will be discussed in greater detail. Finally, the possible direction in forthcoming research will be reviewed by analyzing the limitation of present studies.
A Portfolio Approach for Enforcing Minimality in a Tree Decomposition

Minimality, a highly desirable consistency property of Constraint Satisfaction Problems (CSPs), is in general too expensive to enforce. Previous work has shown the practical benefits of restricting minimality to the clusters of a tree decomposition, allowing us to solve many difficult problems in a backtrack-free manner. We explore two alternative algorithms for enforcing minimality whose performance widely vary from one instance to another. We advocate a fine-grain portfolio approach to dynamically choose, during lookahead, the most appropriate algorithm for a cluster. Our strategy operates by selecting among two algorithms for enforcing minimality and an algorithm that enforces the lowest-level of consistency, which, in our setting, is Generalized Arc Consistency. Empirical evaluation on benchmark problems shows a significant improvement both in terms of the number of instances solved and CPU time.
Using learning content management systems as highly adaptive and efficient supporting tool for (recurrent) training — an applied perspective

The nature of the daily security business at airports (e.g. fast changing regulations) demands more and more flexible training and communication solutions for security officers at airports. Classical classroom training is a proven way for (re− training, but alternative tools, in particular e-solutions, could be taken into account more often to support the classical method of training.
Routing protocol for ad hoc mobile networks using mobility prediction

Over the lasts years there has been a growing interest on Mobile Ad Hoc Networks (MANET). Since the nodes can move freely, mobility became an important characteristic of the MANET. In this work we propose a novel prediction method to forecast the future node position. The method was derived using pedestrian tracked data. Using this method we propose a novel geographical routing protocol that uses the predicted position in the routing decision process. The method prediction performance is contrasted against a real trajectory and the routing protocol performance is tested by computer simulations against others geographical routing protocols.
Imitation Learning with Recurrent Neural Networks

We present a novel view that unifies two frameworks that aim to solve sequential prediction problems: learning to search (L2S) and recurrent neural networks (RNN). We point out equivalences between elements of the two frameworks. By complementing what is missing from one framework comparing to the other, we introduce a more advanced imitation learning framework that, on one hand, augments L2S s notion of search space and, on the other hand, enhances RNNs training procedure to be more robust to compounding errors arising from training on highly correlated examples.
Experiences with experimental clinical evaluation of a computerized drug delivery system for regulation of mean arterial blood pressure

A number of closed-loop control systems have been investigated and developed for the regulation of physiological variables by automatic administration of therapeutic agents. This paper reflects on several years of practical experience, by the authors, in this area including the development of an adaptive computerized drug delivery system. A computerized adaptive drug delivery system has been designed and tested for automatic regulation of mean arterial blood pressure (MAP) of patients by infusion of a vasodilator (sodium nitroprusside). A limited pilot study using the system to perform closed-loop regulation of MAP in two patients undergoing coronary artery bypass surgery was performed. At all times the drug infusion was monitored by an expert supervisor. The trial results show that without human intervention, patients' MAP was kept within /spl plusmn/10 mmHg of the set-point for more than 70% of the time even in the presence of significant natural and unmeasurable disturbances.
Monoclonal antibodies identify a group of nuclear pore complex glycoproteins

Using monoclonal antibodies we identified a group of eight polypeptides of rat liver nuclear envelopes that have common epitopes. Most or all of these proteins are structurally distinct, as shown by tryptic peptide mapping and analysis with polyclonal antibodies. While these polypeptides are relatively tightly bound to nuclear membranes, only one is an integral membrane protein. The eight antigens cofractionate with the nuclear pore complex under various conditions of ionic strength and detergent. It can be seen by immunofluorescence microscopy that the monoclonal antibodies reacting with these antigens stain the nuclear surface of interphase cells in a finely punctate pattern. When the nuclear envelope is disassembled and subsequently reformed during mitosis, the proteins are reversibly dispersed throughout the cytoplasm in the form of minute foci. By EM immunogold localization on isolated nuclear envelopes, the monoclonal antibodies label exclusively the nuclear pore complex, at both its nucleoplasmic and cytoplasmic margins. Considered together, our biochemical and localization data indicate that the eight nuclear envelope polypeptides are pore complex components. As shown in the accompanying paper (Holt, G. D., C. M. Snow, A. Senior, R. S. Haltiwanger, L. Gerace, and G. W. Hart, J. Cell Biol., 104:1157-1164) these eight polypeptides contain a novel form of glycosylation, O-linked N-acetylglucosamine. The relative abundance and disposition of these O-linked glycoproteins in the pore complex are consistent with their having a role in nucleocytoplasmic transport.
Development of an application for mobile devices to identify the frailty phenotype among the elderly

Objective: to develop a mobile app to quickly and safely identify frailty syndrome features among the elderly. Method: a cross-sectional study was conducted. The application was developed for the Android platform in the Java programming language and XML markup. The study instrument was based on five frailty phenotype criteria. The tests were conducted with 20 elderly persons living in a long-term care facility. Results: the twenty elderly persons had a mean age of 76.55 (±9.5) years. Thirteen were identified as frail, five were pre-frail and two were non-frail. The comparison of the results of the instruments of analysis coincided in the general evaluation of frailty and in the individual identification of the five criteria. Conclusion: the data suggests that the use of the application for the evaluation of frailty among the elderly was performed safely, with the advantage of quick access to allow the monitoring of the clinical status and prognosis of the patient.
Environmental sound classification using log-Gabor filter

This paper presents novel approaches for efficient feature extraction using environmental sound magnitude spectrogram. We propose approaches based on the visual domain, the spectrogram is passed through a bank of 12 log-Gabor filters, followed by an averaged operation and passed through an optimal feature selection procedure based on mutual information. The proposed methods were tested on a database of 10 sound classes. The evaluation system is realized by using the multiclass support vector machines (SVM's) that gave rise to a recognition rate of the order 89.62 %.
Tensor Reduction for User Profiling in Personalized Recommender Systems

User profiling is the process of constructing user models which represent personal characteristics and preferences of customers. User profiles play a central role in many recommender systems. Recommender systems recommend items to users based on user profiles, in which the items can be any objects which the users are interested in, such as documents, web pages, books, movies, etc. In recent years, multidimensional data are getting more and more attention for creating better recommender systems from both academia and industry. Additional metadata provides algorithms with more details for better understanding the interactions between users and items. However, most of the existing user/item profiling techniques for multidimensional data analyze data through splitting the multidimensional relations, which causes information loss of the multidimensionality. In this paper, we propose a user profiling approach using a tensor reduction algorithm, which we will show is based on a Tucker2 model. The proposed profiling approach incorporates latent interactions between all dimensions into user profiles, which significantly benefits the quality of neighborhood formation. We further propose to integrate the profiling approach into neighborhood-based collaborative filtering recommender algorithms. Experimental results show significant improvements in terms of recommendation accuracy.
Age and Choice in Swiss Health Insurance

Elements of regulation inherent in all social health insurance systems are a uniform package of bene ts and uniform cost sharing. Both elements risk to burden the population with a welfare loss if preferences di¤er. Since the debate about rationing importantly involves age as a criterion, this study examines the relationship between age and willingness-to-pay (WTP) for modi cations in Swiss social health insurance. Through discrete choice experiments, a marked diversity of preferences with regard to health insurance parameters can be established. The ndings suggest ine¢ ciency of age-based rationing but also potential for self-rationing.
An Adaptive Collision-Free MAC protocol based on TDMA for Inter-Vehicular communication

Inter-Vehicular communication is considered to be a promising way to improve traffic safety. Among this, it is a key technology to delivery urgent messages and periodical beacons to neighbors successfully. In this paper, we propose an Adaptive Collision-Free MAC (ACFM) protocol tailored to vehicular networks, based on dynamic TDMA mechanism. In our protocol, RoadSide Units (RSUs) are exploited to schedule time slots assignment and disseminate control information, while the data are spread among vehicles. Each RSU maintains a dynamical slots assignment cycle for vehicles in its coverage adaptively. A cycle consists of N frames, where N varies from 1 to 5 according to the number of vehicles. Under the scenario of light traffic, ACFM controls the excessive increase of unassigned slots through shrinking slots assignment cycle frame by frame. When there are a mass of vehicles on roads, ACFM provides more available slots by expanding cycle which ensures the fairness of channel access for every vehicle. Channel utilization and fairness can be achieved together in ACFM We implement the protocol on NS-2 for a comparative evaluation against conventional protocols under realistic VANET scenarios. Simulation results show that the ACFM scheme outperforms the conventional protocols in terms of packet loss ratio and delay.
Disparate Effects of Atorvastatin Compared With Simvastatin on C-Reactive Protein Concentrations in Patients With Type 2 Diabetes

OBJECTIVE Reduction in LDL and high sensitivity (hs) C-reactive protein (CRP) are independent indicators of successful cardiovascular risk reduction with statins. This study compared the effect of equivalent LDL-lowering doses of simvastatin and atorvastatin on hsCRP in type 2 diabetic patients. RESEARCH DESIGN AND METHODS A crossover study of 26 patients with type 2 diabetes taking either 40 mg simvastatin or 10 mg atorvastatin was undertaken. After 3 months on one statin, lipids and hsCRP were measured on 10 occasions over a 5-week period. The same procedure was then followed taking the other statin. RESULTS LDL was comparable on either treatment: atorvastatin 2.2 ± 0.2 vs. 2.1 ± 0.3 mmol/l (mean ± SD; P = 0.19). CRP of individuals taking atorvastatin was significantly lower than when they were taking simvastatin (median 1.08 vs. 1.47 mg/l, P = 0.0002) and was less variable (median SD of logCRP 0.0036 vs. 0.178, P = 0.0001). CONCLUSIONS Compared with simvastatin, atorvastatin reduced hsCRP and its variability in type 2 diabetic patients. This enhanced anti-inflammatory effect may prove beneficial if lower CRP is associated with improved cardiovascular risk.
Relationship of Activity in the Subthalamic Nucleus–Globus Pallidus Network to Cortical Electroencephalogram

One of the functions of the excitatory subthalamic nucleus (STN) is to relay cortical activity to other basal ganglia structures. The response of the STN to cortical input is shaped by inhibition from the reciprocally connected globus pallidus (GP). To examine the activity in the STN–GP network in relation to cortical activity, we recorded single and multiple unit activity in STN and/or GP together with cortical electroencephalogram in anesthetized rats during various states of cortical activation. During cortical slow-wave activity (SWA), STN and GP neurons fired bursts of action potentials at frequencies that were similar to those of coincident slow (∼1 Hz) and spindle (7–14 Hz) cortical oscillations. Spontaneous or sensory-driven global activation was associated with a reduction of SWA and a shift in STN–GP activity from burst- to tonic- or irregular-firing. Rhythmic activity in STN and GP neurons was lost when the cortex was inactivated by spreading depression and did not resume until SWA had recovered. Although rhythmic STN–GP activity was correlated with SWA, the phase relationships of activities of neurons within the STN and GP and between the nuclei were variable. Even when neurons displayed synchronous bursting activity, correlations on the millisecond time scale, which might indicate shared synaptic input, were not observed. These data indicate that (1) STN and GP activity is intimately related to cortical activity and hence the sleep–wake cycle; (2) rhythmic oscillatory activity in the STN–GP network in disease states may be driven by the cortex; and (3) activity of the STN–GP network is regulated in space in a complex manner.
Automated Probabilistic Address Standardisation and Verification

Addresses are a key part of many records containing information about people and organisations, and it is therefore important that accurate address information is available before such data is mined or stored in data warehouses. Unfortunately, addresses are often captured in non-standard and free-text formats, usually with some degree of spelling and typographical errors. Additionally, addresses change over time, for example when people move, when streets are renamed, or when new suburbs are built. Cleaning and standardising addresses, as well as verifying if they really exist, are therefore important steps in data mining pre-processing. In this paper we present an automated probabilistic approach based on a hidden Markov model (HMM), which uses national address guidelines and a comprehensive national address database to clean, standardise and verify raw input addresses. Initial experiments show that our system can correctly standardise even complex and unusual addresses.
MULTI-LOUDSPEAKER REVERBERATION SYSTEM

A shielding blanket for racing engines includes a bag constructed of a lamination of materials including several plies of a high-strength ballistic textile material laminate having a high melting point. The blanket is shaped to fit closely over the cylinder block and oil pan of the engine, and between the block and the exhaust headers. Oil-absorbent pads are secured within the bag for capturing engine oil. Two of the pads face the sides of the cylinder block to prevent oil from escaping through either the engine block or the oil pan from reaching the exhaust headers.
Beta-eigenspaces for autonomous mobile robotic trajectory outlier detection

This paper addresses the problem of robotics trajectory building for efficient navigation and consequently exploration. A concept of beta-eigenvector has been introduced to find an outlier for the existing non-point based trajectory obtained from raw laser data. We have used our paradigm of “free configuration eigenspaces” method [1], with specific focus on outlier detection. The key idea proposed in this paper is to replace the Gaussian distribution utilized by the probabilistic principal component analysis (PPCA) with the beta-distribution. It is a well known issue that the conventional PCA is sensitive to anomalous observations because the calculation of sample mean and covari-ance matrix can be significantly influenced by a small number of outliers. Similarly, PPCA is not robust to outliers since the data are assumed to follow a multivariate Gaussian distribution that is easily affected by deviant observations. An outlier detection is done using Beta-Probabilistic Principal Component Analysis (BPPCA), further more an analysis is proposed to identify which variables contribute the most to the occurrence of outliers. The proposed technique is applied on real-time robotics sensor data as well as on the real-time robotics simulation environment.
An Image Retrieval Method Based on Content Self-Organized and Interactive

How to find the image we need expediently in the tremendous database is one of the most important issues in content-based image retrieval (CBIR). In this paper, we presented an image retrieval system based on image content using fuzzy logic and proposed a new concept on partition the entire database based on content self-organized. In detail, we used modified fuzzy c-means (MFCM) clustering scheme to cluster the database before retrieval and defined a new method to determine the fuzzy weight. To improve the retrieval effectiveness more, this paper also used interactive query (IQ) and presented a new relevance feedback (RF) framework. On all accounts, we designed and implemented a content-based self-organized and interactive retrieval system. Experiments show that it contributes to improving retrieval effectiveness and will be applied in the E-government.
Hormonal regulation impact on regeneration of Acacia nilotica L. a nitrogen fixing tree.

An efficient regeneration protocol was developed for the establishment of Acacia nilotica L. , a nitrogen fixing, multipurpose leguminous tree, through indirect organogenesis. Present investigation was the first attempt to obtained indirect organogenesis in Acacia nilotica L. through cotyledonary node explant of in vitro grown plants. Cotyledonary node (1.0 cm) explant excised from 20 day old in vitro seedling cultured on MS medium supplemented with various concentrations of 2, 4- D alone and in combination with BAP for callus induction. However, hormonal regulation and their concentrations played crucial role in obtaining the callus. Under the optimized conditions, maximum and rapid growth of green callus was obtained after the 25 days of inoculation on MS medium with 2, 4- D (2.0 mg/l) alone or in combination with of 2, 4- D (0.40 mg/l) and BAP (0.20 mg/l ) in combination. Combination of auxin and cytokinin proved to be more effective for callus induction. Shoot induction was also obtained on the same medium after subculturing twice at the time interval of 21 days. The highest number and their elongation of adventitious shoots achieved when activated charcoal (200 mg/l) added on MS medium fortified with 2, 4- D (0.40 mg/l) and BAP (0.2 mg/l). However, the elongated adventitious shoots were rooted on half strength MS medium with IBA (0.5 mg/l) after 20 days. Rooted plantlets were hardened and successfully established in soil with 75% survival rate.
Peer Effects, Pupil Teacher Ratios and Teacher Incentives

The introduction of free primary education has raised primary school enrollment in many developing countries, but the resulting overcrowding of schools and influx of students with little preparation poses new challenges to policymakers. Researchers evaluated three interventions that addressed the large class sizes and heterogeneity in student preparation in the Kenyan school system. They found that hiring additional local contract teachers helped reduce classroom overcrowding and improved student learning outcomes. The biggest gains came when local school committees were empowered to oversee the recruitment process and to effectively monitor teachers, and when classes were structured to target instruction to students’ initial achievement level.