Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a unified model of Pavlovian conditioning : Solution to the extinction problem

We are proposing an oscillatory habituation mechanism of extinction that can integrate and reconcile some computational and behavior mechanisms in the unified model of Pavlovin conditioning. The suggested unified model explains most of the recent data on extinction, including renewal, reinstatement, reacquisition, and spontaneous recovery and predicts that extinction can incorporate new learning with some unlearning. This model is the same as the “Neurolocator” model [23] with some minor modifications to account for timing and trace conditioning. The main characteristics of this model are as follows: oscillatory binding of CS-US representation; non-Hebbian learning by synchrony; novelty guided attention; parallel character of interaction between all brain structures through the septal pacemaker, and global control from the septo-hippocampal system. This model offers viable answers to a number of questions on the extinction problem, posed in current literature. and suggests a new neurocognitive mechanism of anxiety. Key-Words: Extinction, habituation, attention, renewal, reinstatement, reacquisition, spontaneous recovery, anxiety
Conceptual model for obfuscated TRUST induced from web analytics data for content-driven websites

Besides e-commerce, infobahn has become an imperative mediocre to provide significant content on services such as academics, medical, legal, relationships, meteorological, general knowledge, etc. to users in a judicious manner. To fascinate additional users to various content providers on the Web, it is essential to build a relationship of trust with them by meritoriously achieving online content optimization by estimating content items' attractiveness and relevance to users' interests. But more than building, the long term sustenance of TRUST is necessary to bind users with the website forever. The perseverance of the present study is to contribute in the effective measurement of TRUST evolved and maintained for Web mediated Information Exchange (W-MIE) or content websites over a long run.
Unionism in Canada and the United States in the 21st Century : The Prospects for Revival

Based on a review and comparison of recent developments in organizing, collective bargaining and political action, this paper considers the potential for union revival in Canada and the United States. Although unions have devoted considerable energy and resources to new initiatives, the overall evidence leads us to generally pessimistic conclusions. The level and direction of union density rates indicates the two labour movements lack the institutional frameworks and public policies to achieve sustained revival. Significant gains in union membership and density levels will require nothing less than a paradigm shift in the industrial relations systems—a broadening of the scope and depth of membership recruitment, workplace representation and political activities.
Decentralized intrusion detection in wireless sensor networks

Wireless sensor networks (WSNs) have many potential applications. Furthermore, in many scenarios WSNs are of interest to adversaries and they become susceptible to some types of attacks since they are deployed in open and unprotected environments and are constituted of cheap small devices. Preventive mechanisms can be applied to protect WSNs against some types of attacks. However, there are some attacks for which there is no known prevention methods. For these cases, it is necessary to use some mechanism of intrusion detection. Besides preventing the intruder from causing damages to the network, the intrusion detection system (IDS) can acquire information related to the attack techniques, helping in the development of prevention systems. In this work we propose an IDS that fits the demands and restrictions of WSNs. Simulation results reveal that the proposed IDS is efficient and accurate in detecting different kinds of simulated attacks.
Palm-based Interaction with Head-mounted Displays

Head-mounted displays (HMDs) are an emerging class of wearable devices that allow users to access and alter information right in front of their eyes. However, due to their size and shape, traditional input modalities (e.g., multi-touch sensing on the device) are not practical. In this position paper, we argue that palm-based interactions have a great potential to ease the interaction with HMDs. We outline two interaction concepts and present directions for future research that can lead to more enjoyable and usable interfaces for HMDs.
Random Projections Imaging With Extended Space-Bandwidth Product

We propose a novel approach to imaging that is not based on traditional optical imaging architecture. With the new approach, the image is reconstructed and visualized from random projections of the input object. The random projections are implemented within a single exposure by using a random phase mask which can be placed on a lens. For objects that have sparse representation in some known domain (e.g., Fourier or wavelet), the novel imaging systems have larger effective space - bandwidth product than conventional imaging systems. This implies, for example, that more object pixels may be reconstructed and visualized than the number of pixels of the image sensor. We present simulation results on the utility of the new approach. The proposed approach can have broad applications in efficient imaging capture, visualization, and display given ever increasing demands for larger and higher resolution images, faster image communications, and multidimensional image communications such as 3-D TV and display.
Real-Time Stereo within the VIDET Project

VIDET is a research project active at the University of Bologna and aimed at the development of a mobility aid for the visually impaired. VIDET's approach consists in the conversion of depth data gathered through a stereo-vision system into a 3D model perceivable by the user by means of a wire-actuated haptic interface. In this paper we describe VIDET's PC-based, real-time, stereo-vision system. As for system's description, we outline the structure of the stereo-matching algorithm and address in more detail the optimization strategies that lead us to a fast PC-based implementation. These involve massive reduction of redundant calculations and use of the parallel multimedia instructions available in current general-purpose microprocessors. We provide experimental results showing that the system is capable of recovering correctly the 3D structure of the observed scene and allows for prompt perception of the depth changes generated by moving objects. We also report execution time measurements and compare our stereo system with the PC-based systems from SRI and Point Grey Research.
Brains That Are out of Tune but in Time

It is estimated that about 4% of the general population may have amusia (or tone deafness). Congenital amusia is a lifelong disability for processing music despite normal intellectual, memory, and language skills. Here we present evidence that the disorder stems from a deficit in fine-grained pitch perception. Amusic and control adults were presented with monotonic and isochronous sequences of five tones (i.e., constant pitch and intertone interval). They were required to detect when the fourth tone was displaced in pitch or time. All amusic participants were impaired in detecting the pitch changes, and showed no sign of improvement with practice. In contrast, they detected time changes as well as control adults and exhibited similar improvements with practice. Thus, the degraded pitch perception seen in the amusic individuals cannot be ascribed to nonspecific problems with the task or to poor hearing in general. Rather, the data point to the presence of a congenital neural anomaly that selectively impairs pitch processing.
Competition between recombination and epistasis can cause a transition from allele to genotype selection

Biochemical and regulatory interactions central to biological networks are expected to cause extensive genetic interactions or epistasis affecting the heritability of complex traits and the distribution of genotypes in populations. However, the inference of epistasis from the observed phenotype–genotype correlation is impeded by statistical difficulties, while the theoretical understanding of the effects of epistasis remains limited, in turn limiting our ability to interpret data. Of particular interest is the biologically relevant situation of numerous interacting genetic loci with small individual contributions to fitness. Here, we present a computational model of selection dynamics involving many epistatic loci in a recombining population. We demonstrate that a large number of polymorphic interacting loci can, despite frequent recombination, exhibit cooperative behavior that locks alleles into favorable genotypes leading to a population consisting of a set of competing clones. When the recombination rate exceeds a certain critical value that depends on the strength of epistasis, this “genotype selection” regime disappears in an abrupt transition, giving way to “allele selection”—the regime where different loci are only weakly correlated as expected in sexually reproducing populations. We show that large populations attain highest fitness at a recombination rate just below critical. Clustering of interacting sets of genes on a chromosome leads to the emergence of an intermediate regime, where blocks of cooperating alleles lock into genetic modules. These haplotype blocks disappear in a second transition to pure allele selection. Our results demonstrate that the collective effect of many weak epistatic interactions can have dramatic effects on the population structure.
Learning Techniques for Automatic Algorithm Portfolio Selection

The purpose of this paper is to show that a well known machine learning technique based on Decision Trees can be effectively used to select the best approach (in terms of efficiency) in an algorithm portfolio for a particular case study: the Bid Evaluation Problem (BEP) in Combinatorial Auctions. In particular, we are interested in deciding when to use a Constraint Programming (CP) approach and when an Integer Programming (IP) approach, on the basis of the structure of the instance considered. Different instances of the same problem present a different structure, and one aspect (e.g. feasibility or optimality) can prevail on the other. We have extracted from a set of BEP instances, a number of parameters representing the instance structure. Some of them (few indeed) precisely identify the best strategy and its corresponding tuning to be used to face that instance. We will show that this approach is very promising, since it identifies the most efficient algorithm in the 90% of the cases.
Involvement of Cannabinoid Receptors in the Regulation of Neurotransmitter Release in the Rodent Striatum: A Combined Immunochemical and Pharmacological Analysis

Despite the profound effect of cannabinoids on motor function, and their therapeutic potential in Parkinson's and Huntington's diseases, the cellular and subcellular distributions of striatal CB1 receptors are not well defined. Here, we show that CB1 receptors are primarily located on GABAergic (vesicular GABA transporter-positive) and glutamatergic [vesicular glutamate transporter-1 (VGLUT-1)- and VGLUT-2-positive] striatal nerve terminals and are present in the presynaptic active zone, in the postsynaptic density, as well as in the extrasynaptic membrane. Both the nonselective agonist WIN55212-2 [(R)-(+)-[2,3-dihydro-5-methyl-3[(4-morpholinyl)methyl] pyrrolo[1,2,3-de]-1,4-benzoxazinyl]-(1-naphthalenyl)methanone mesylate salt] (EC50, 32 nm) and the CB1-selective agonist ACEA [N-(2-chloroethyl)-5Z,8Z,11Z,14Z-eicosatetraenamide] inhibited [3H]GABA release from rat striatal slices. The effect of these agonists was prevented by the CB1-selective antagonists SR141716A [N-(piperidin-1-yl)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide] (1 μm) and AM251 [1-(2,4-dichlorophenyl)-5-(4-iodophenyl)-4-methyl-N-1-piperidinyl-1H-pyrazole-3-carboxamide trifluoroacetate salt] (1 μm), indicating that cannabinoids inhibit the release of GABA via activation of presynaptic CB1 receptors. Cannabinoids modulated glutamate release via both CB1 and non-CB1 mechanisms. Cannabinoid agonists and antagonists inhibited 25 mm K+-evoked [3H]glutamate release and sodium-dependent [3H]glutamate uptake. Partial involvement of CB1 receptors is suggested because low concentrations of SR141716A partly and AM251 fully prevented the effect of WIN55212-2 and CP55940 [5-(1,1-dimethylheptyl)-2-[5-hydroxy-2-(3-hydroxypropyl)cyclohexyl]phenol]. However, the effect of CB1 agonists and antagonists persisted in CB1 knock-out mice, indicating the involvement of non-CB1,CB1-like receptors. In contrast, cannabinoids did not modulate [3H]dopamine release or [3H]dopamine and [3H]GABA uptake. Our results indicate distinct modulation of striatal GABAergic and glutamatergic transmission by cannabinoids and will facilitate the understanding of the role and importance of the cannabinoid system in normal and pathological motor function.
Ja n 20 01 RELATIVISTIC SUPERFLUID MODELS FOR ROTATING NEUTRON STARS

This article starts by providing an introductory overview of the theoretical mechanics of rotating neutron stars as developped to account for the frequency variations, and particularly the discontinuous glitches, observed in pulsars. The theory suggests, and the observations seem to confirm, that an essential role is played by the interaction between the solid crust and inner layers whose superfluid nature allows them to rotate independently. However many significant details remain to be clarified, even in much studied cases such as the Crab and Vela. The second part of this article is more technical, concentrating on just one of the many physical aspects that needs further development, namely the provision of a satisfactorily relativistic (local but not microscopic) treatment of the effects of the neutron superfluidity that is involved.
Doctoral Dissertation Proposal Design Verification of Advanced Pipelined Machines

We have developed formal verification techniques for the high-level design of pipelined microprocessors. Our technique represents the instruction stream in such a way that pipeline properties, such as RAW hazards do not exist, can be directly expressed. This approach allows us to prove the correctness of the machine design incrementally, which reduces the computational cost of the verification. Thus, we believe we can apply our techniques to designs with more complex pipeline control than those previously verified. We are enhancing our techniques to permit the verification of microprocessors containing advanced pipeline features, such as precise exception handling and the out-of-order issue of instructions.
The Analysis of Hashing Techniques That Exhibit k-ary Clustering

In this paper we relate the performance of hashmg algonthms to the notion of clustering, that is, the pile-up phenomenon that occurs because many keys may probe the table locations m the same sequence We will say that a hashmg technique exhibits k-ary clustering if the search for a key begins with k independent random probes and the subsequent sequence of probes is completely determined by the location of the k initial probes Such techniques may be very bad, for instance, the average number of probes necessary for mseruon may grow linearly with the table size However, on the average (that is if the permutations describing the method are randomly chosen), k-ary clustering techniques for k > 1 are very good. In fact the average performance is asymptotically equivalent to the performance of umform probing, a method that exhibits no clustering and is known to be optimal in a certain sense.
Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.
Improving energy efficient using novel sleep scheduling approach for wireless ad-hoc network

Wireless Adhoc networks are deployed in emergency situations, military kind of applications, surveillance monitoring and in healthcare industry. The Nodes are dynamic and can accommodate themselves in any existing infrastructures, placed randomly in the network. Every node can easily communicate with any other node through the base station directly. Since entire node communicates simultaneously there are chances for collision or jamming can occur in the network. Various approaches are available in the existing literatures which are concentrating only in avoiding collision or jamming. In this paper, [Novel Sleep Scheduling] NSS approach is introduced to save the energy efficiently. NSS follows an ESR-MAC protocol which is derived from TDMA and CSMA based slot allocation. ESR utilizes the slot allocation method from CSMA and utilizes scheduling methodology from TDMA. NSS improves the energy efficiency by changing the states of the node with level by level offset way and collision and Jamming is avoided by scheduling method. The simulation result shows the best performance of Novel Sleep Scheduling approach is better than the existing approach in terms of throughput, delay and energy.
Sentiment Analysis based on User Tag for Traditional Chinese Medicine in Weibo

With the acceptance of Western culture and science, Traditional Chinese Medicine (TCM) has become a controversial issue in China. So, it's important to study the public's sentiment and opinion on TCM. The rapid development of online social network, such as twitter, make it convenient and efficient to sample hundreds of millions of people for the aforementioned sentiment study. To the best of our knowledge, the present work is the first attempt that applies sentiment analysis to the domain of TCM on Sina Weibo (a twitter-like microblogging service in China). In our work, firstly we collect tweets topic about TCM from Sina Weibo, and label the tweets as supporting TCM and opposing TCM automatically based on user tag. Then, a support vector machine classifier has been built to predict the sentiment of TCM tweets without labels. Finally, we present a method to adjust the classifier result. The performance of F-measure attained with our method is 97%.
Finite-Time Consensus for Multiagent Systems With Cooperative and Antagonistic Interactions

This paper deals with finite-time consensus problems for multiagent systems that are subject to hybrid cooperative and antagonistic interactions. Two consensus protocols are constructed by employing the nearest neighbor rule. It is shown that under the presented protocols, the states of all agents can be guaranteed to reach an agreement in a finite time regarding consensus values that are the same in modulus but may not be the same in sign. In particular, the second protocol can enable all agents to reach a finite-time consensus with a settling time that is not dependent upon the initial states of agents. Simulation results are given to demonstrate the effectiveness and finite-time convergence of the proposed consensus protocols.
Cross-Saturation Effects in IPM Motors and Related Impact on Sensorless Control

Permanent-magnet-assisted synchronous reluctance motors are well suited to zero-speed sensorless control because of their inherently salient behavior. However, the cross-saturation effect can lead to large errors on the position estimate, which is based on the differential anisotropy. These errors are quantified in this paper as a function of the working point. The errors that are calculated are then found to be in good accordance with the purposely obtained experimental measurements
Climate, Deer, Rodents, and Acorns as Determinants of Variation in Lyme-Disease Risk

Risk of human exposure to vector-borne zoonotic pathogens is a function of the abundance and infection prevalence of vectors. We assessed the determinants of Lyme-disease risk (density and Borrelia burgdorferi-infection prevalence of nymphal Ixodes scapularis ticks) over 13 y on several field plots within eastern deciduous forests in the epicenter of US Lyme disease (Dutchess County, New York). We used a model comparison approach to simultaneously test the importance of ambient growing-season temperature, precipitation, two indices of deer (Odocoileus virginianus) abundance, and densities of white-footed mice (Peromyscus leucopus), eastern chipmunks (Tamias striatus), and acorns ( Quercus spp.), in both simple and multiple regression models, in predicting entomological risk. Indices of deer abundance had no predictive power, and precipitation in the current year and temperature in the prior year had only weak effects on entomological risk. The strongest predictors of a current year's risk were the prior year's abundance of mice and chipmunks and abundance of acorns 2 y previously. In no case did inclusion of deer or climate variables improve the predictive power of models based on rodents, acorns, or both. We conclude that interannual variation in entomological risk of exposure to Lyme disease is correlated positively with prior abundance of key hosts for the immature stages of the tick vector and with critical food resources for those hosts.
Pediatric Adapted Physical Education for Infants, Toddlers, and Preschoolers: Meeting IDEA-H and IDEA-B Challenges

PL 99-457 and PL 101-176 have presented a new challenge for adapted physical education. Federal legislation has provided financial incentive for states to increase the intensity and duration of early intervention programs for the infant/toddler/preschool child with disabilities (ITPCD). The present article proposes a conceptual framework for a new subfield, pediatric adapted physical education (PAPE). The origins and essence of federal legislation affecting infants, toddlers, and preschoolers is explained. Because the legislation requires a multi-agency/multidisciplined approach, the role of adapted physical education within the larger context is explained, as is the professional preparation of practitioners of the new subfield. Finally, one state’s initiative is explained to serve as an action plan for other adapted physical education leaders.