Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Systems Underlying Aversive Conditioning in Humans with Primary and Secondary Reinforcers

Money is a secondary reinforcer commonly used across a range of disciplines in experimental paradigms investigating reward learning and decision-making. The effectiveness of monetary reinforcers during aversive learning and associated neural basis, however, remains a topic of debate. Specifically, it is unclear if the initial acquisition of aversive representations of monetary losses depends on similar neural systems as more traditional aversive conditioning that involves primary reinforcers. This study contrasts the efficacy of a biologically defined primary reinforcer (shock) and a socially defined secondary reinforcer (money) during aversive learning and its associated neural circuitry. During a two-part experiment, participants first played a gambling game where wins and losses were based on performance to gain an experimental bank. Participants were then exposed to two separate aversive conditioning sessions. In one session, a primary reinforcer (mild shock) served as an unconditioned stimulus (US) and was paired with one of two colored squares, the conditioned stimuli (CS+ and CS−, respectively). In another session, a secondary reinforcer (loss of money) served as the US and was paired with one of two different CS. Skin conductance responses were greater for CS+ compared to CS− trials irrespective of type of reinforcer. Neuroimaging results revealed that the striatum, a region typically linked with reward-related processing, was found to be involved in the acquisition of aversive conditioned response irrespective of reinforcer type. In contrast, the amygdala was involved during aversive conditioning with primary reinforcers, as suggested by both an exploratory fMRI analysis and a follow-up case study with a patient with bilateral amygdala damage. Taken together, these results suggest that learning about potential monetary losses may depend on reinforcement learning related systems, rather than on typical structures involved in more biologically based fears.
A hybrid local-global approach for multi-core thermal management

Multi-core processors have become an integral part of mainstream high performance computer systems. In parallel, exponentially increasing power density and packaging costs have necessitated system level thermal management solutions for multi-core systems. Dynamic thermal management (DTM) techniques monitor on-chip temperature continuously and typically employs dynamic voltage and frequency scaling (DVFS) to lower the temperature when it exceeds a pre-defined threshold. State-of-the-art DTM solutions for multi-core systems include distributed DVFS (where each core can scale the voltage/ frequency individually) and global DVFS (where all cores scale voltage/frequency simultaneously). Distributed DVFS generally offers higher performance than global DVFS, but it is hard to implement and has major scalability issues. We propose a hybrid local-global thermal management approach for multi-core systems that offers better performance than distributed DVFS, while maintaining the simplicity of global DVFS. We employ global DVFS across all the cores but locally tune the performance of each core individually through architectural adaptations. We exploit easily reconfigurable micro-architecture parameters such as instruction window size, issue width, and fetch throttling in per-core thermal management. Our hybrid solution is easy to implement and highly effective towards temperature management. The key challenge is appropriate choice of configurations at runtime to provide optimal performance under thermal constraints. We formulate it as a configuration search problem and design an efficient software-based solution that selects the appropriate configuration. Our hybrid method, though simpler to implement, achieves 5% better throughput compared to distributed DVFS.
REQUIREMENTS MANAGEMENT AND ACQUISITION MANAGEMENT EXPERIENCES IN SPANISH PUBLIC ADMINISTRATIONS

As a part of the activities of the first Symposium on Process Improvement Models and Software Quality of the Spanish Public Administration, working groups were formed to discuss the current state of the Requirements Management and Supplier Agreement Management processes. This article presents general results and main contributions of those working groups. The results have allowed the obtention of a preliminary appraisal of the current state of these two processes in the Spanish Public Administration.
Scheduling Reputation Maintenance in Agent-based Communities Using Game Theory

In agent-based systems, agents can be organized within groups, called communities, where members are providing similar or complementary services. Agent-based communities of web services is an example of such systems. Managing reputation of each agent and of the whole community is a key issue towards securing this type of systems, where a controller agent is designed to observe and check the behavior of each member to update and maintain the system’s reputation. Scheduling the maintenance activity by deciding about the moment where the check has to be done is still an open problem. Because it is highly expensive, maintenance cannot be done every moment or based on small history of agents’ behaviors. We propose in this paper a scheduling algorithm that helps the controller agent improve the quality of the reputation mechanism, which increases the trust value of users toward the community. The proposed algorithm is based on a class of games called Bayesian Stackelberg. Our Bayesian Stackelberg game is designed between the controller agent and community members, for example agent-based web services. We simulate and compare the efficiency of our algorithm with other stochastic techniques, namely uniform, normal and Poisson distributions. This research draws the lines for future work in the subject of optimizing reputation mechanisms through maintenance in different time intervals.
Mobile sensing of pedestrian flocks in indoor environments using WiFi signals

In Pervasive Computing research, substantial work has been directed towards radio-based sensing of human movement patterns. This research has, however, mainly been focused on movements of individuals. This paper addresses the joint identification of the movement indoors of multiple persons forming a cohesive whole - specifically flocks - with clustering approaches operating on three different feature sets derived from WiFi signals which are comparatively analysed. Automatic detection of flocks has several important applications, including social and psychological sensing and emergency research studies. We use a dataset comprising 16 subjects forming one to four flocks walking in a building on single and multiple floors. For the detection of flocks we achieved an average F-measure accuracy of up to 85 percent. We report on the advantages and drawbacks of the three different types of feature sets considering their suitability for use “in the wild” or in well-defined environments.
Investigations on the postnatal development of the foliate papillae using light and scanning electron microscopy in the porcupine (Hystrix cristata).

In this study SEM and light microscopy were used to investigate the structure of the foliate papillae in the porcupine. The foliate papillae consisted of about 10 or 11 clefts. The length of the foliate papillae averaged 2.79 mm and its width averaged 863 µm. Taste buds were located intraepithelial in the basal half of the papilla grooves ( sulcus papillae). Every wall on each fold harboured from five to nine taste buds. There were two different cell types of taste buds: one stained light ( epitheliocytus sensorius gustatorius), and the other dark ( epitheliocytus sustentans). The length and width of the taste buds averaged 190.5 µm and 86 µm, respectively. The ratio of the length to the width of taste buds was 2.21. The average depth of the papilla groves was 1763 µm and its epithelial thickness was 235.5 µm. In scanning electron microscopy, the thickness of the epithelial cell borders was appar -
HomeLab: a platform for conducting experiments with connected devices in the home

The downward spiral in the cost of connected devices and sensors (e.g., cameras, motion sensors, remote controlled light switches) has generated a vast amount of interest towards using them in the home environments. Companies and researchers are developing technologies that employ these devices in a diverse range of ways. These include improving energy efficiency, increasing comfort and convenience through automation, implementing security and monitoring, and providing in-home healthcare. However, conducting experimental work in this domain is extremely challenging today. Evaluating the effectiveness of research prototypes typically requires some form of deployment in real homes. This task is riddled with not only social and legal constraints, but also logistical and technical hurdles. Examples include recruiting participants, hardware and software setup in the home, training participants and residents who typically possess varying levels of technical expertise, and diverse security and privacy concerns. Because of these challenges, individual research groups rarely manage to deploy their prototypes on more than a dozen or so homes concentrated in their geographic area. Such deployments tend to lack the scale and diversity that is needed to confidently answer the research hypothesis. Our goal is to lower the barrier towards deploying experimental technology in a large number of geographically distributed homes.
Association of two polymorphisms in MSH2 and XRCC1 genes with multiple sclerosis in Iranian population

Introduction: To protect genomes of all organisms from internal and external damages and maintain the genome integrity and the continuity of life, repair system has been developed in all living cells. Defects in repair system are responsible for various kinds of disease including cancers and neurodegenerative diseases such as Multiple sclerosis (MS). The relationship between various components of the repair system and MS has been confirmed by investigations on separate cohorts in independent research. The main aim of this study was to discover the genetic association of two functional polymorphisms of rs1799782 in XRCC1 and rs2303425 in MSH2 genes as the key players in DNA repair system; with MS. Methods: The genotypes of 105 MS patients and 102 age and sex matched healthy controls for these polymorphisms were determined by a PCR-RFLP technique. Results: Genotype and allele frequencies of rs1799782 in patients with MS compared to the control group demonstrated a significant difference and a possible role for this polymorphism in MS pathogenesis (P value (0.02) and OR (3.4)). The rs2303425 polymorphism showed no significant correlation (P value = 0.41 and OR=1.5) with the risk of MS in Iranian population. Conclusion: Our results suggest a possible role for repair system genes and their significance in the pathogenesis of multiple sclerosis.
A Framework for Improving Target Marketing Using Collaborative Data Mining Approach

Marketing is one of the most prominent issues of modern trading culture. E-marketing refers to the advertisements published on World Wide Web. Advertising to the right user in the right way at the right moment is critical to the success of any e-marketing campaign. Social network can provide a link structure which can be explored to target a specific group of customers with their appropriate interest on the product rather than irrelevant popping up user’s web page for the advertisement. In this paper, an approach is used for mining the interest of users from their profile and determining the groups they belong to.
Regulation of 22S dynein by a 29-kD light chain

Previously, a 29-kD axonemal polypeptide (p29) that copurifies with 22S dynein has been shown to be phosphorylated in a cAMP- and Ca(2+)- sensitive manner, consistent with a role for this molecule in the signal transduction cascade leading to fast forward swimming in Paramecium tetraurelia (Hamasaki, T., K. Barkalow, J. Richmond, and P. Satir. 1991. Proc. Natl. Acad. Sci. USA. 88:7912-7922). This study demonstrates the nature of the relationship between p29 and 22S dynein. Chaotropic agents can be used to separate p29 fractions from 22S dynein. When extracted p29 is exchanged into physiological buffers, it regains the ability to recombine with 22S dynein with an apparent dissociation constant of 25 nM; no recombination is seen with 14S dynein or with unrelated control proteins. p29 from Paramecium will also recombine with Tetrahymena 22 but not 14S dynein. After chymotryptic digestion of 22S dynein, p29 preferentially binds to a single-headed fragment, homologous to the alpha H chain of Tetrahymena 22S dynein. 22S dynein treated in vitro by Paramecium protein kinase A in the presence of cAMP and ATP to phosphorylate p29 translocates bovine brain microtubules significantly (1.53x; p < 0.001) faster than before phosphorylation. Similarly, 22S dynein reconstituted in vitro with thiophosphorylated p29 translocates microtubules significantly (1.31x; p < 0.001) faster than controls reconstituted with nonthiophosphorylated p29. p29 is the only moiety thiophosphorylated in the reconstituted dynein. We conclude that p29 functions as a 22S dynein regulatory light chain in that it alone is sufficient to control the rate of microtubule translocation by changes in its phosphorylation state.
Functional postnatal changes in avian brain regions responsive to retinal slip: a 2-deoxy-D-glucose study

The postnatal development of two avian brain areas, the nucleus of the basal optic root (nBOR) and the lentiform nucleus of the mesencephalon (LM), was studied using the 2-deoxy-D-glucose (2-DG) method. Previous studies have shown that these nuclei respond to whole field visual motion, which is used for optokinetic eye movements. In the present study vertical whole field visual motion presented to one eye resulted in the accumulation of 2-DG label in the contralateral nBOR in both hatchlings and 3-week or older chicks. In hatchlings the nBOR was diffusely labeled whether upward or downward motion was used as the test stimulus, whereas in older birds the label was localized within different subdivisions of the nBOR depending on the direction of vertical motion: upward motion resulted in concentration of 2-DG label in the dorsal nBOR, whereas downward motion resulted in label in the ventral nBOR. Horizontal whole field visual motion presented to one eye resulted in 2-DG label in the contralateral LM and in the lateral portion of the contralateral nBOR in animals of both ages. In hatchlings, visual motion in both temporal-to-nasal and nasal-to- temporal directions resulted in labeling of both subdivisions of the LM, LM magnocellularis (LMmc) and LM parvocellularis. In older birds, temporal-to-nasal motion resulted in labeling of only the LMmc, whereas nasal-to-temporal motion produced labeling in both subdivisions. These results strongly suggest that the nBOR and LM continue to develop their response properties postnatally and that different functional units become separated within particular subdivisions of the nuclei. Conceivably, the functional segregation within the nBOR is due to an intrinsic reorganization, whereas functional changes in the LM may be due to the postnatal development of a projection from the telencephalon.
Packet-Pair Flow Control

This paper presents the packet-pair rate-based feedback flow control scheme. This scheme is designed for networks where individual connections do not reserve bandwidth and for the available bitrate (best-effort) component of integrated networks. We assume a round-robin-like queue service discipline in the output queues of the network’s switches, and propose a linear stochastic model for a single conversation in a network of such switches. These model motivates the Packet-Pair rate probing technique, which forms the basis for provably stable discrete and continuous time rate-based flow control schemes. We present a novel state estimation scheme based on fuzzy logic. We then address several practical concerns: dealing with system startup, retransmission and timeout strategy, and dynamic setpoint probing. We present a finite state machine as well as source code for a model implementation. The dynamics of a single source, the interactions of multiple sources, and the behavior of packet-pair sources in a variety of benchmark scenarios are evaluated by means of detailed simulations. We close with some remarks about possible extensions to packet-pair, limitations of this work, and an outline of related work.
Experiments with Measuring Time in PRISM 4 . 0 ( Addendum ) ∗

In our previous paper “Experiments with Measuring Time in PRISM 4.0” we have reported on experiments with the probabilistic symbol model checker PRISM 4.0 on evaluating the response times of client/server system models. In that report some questions remained unresolved, in particular an unexpected result in the analysis of Probabilistic Timed Automata (PTA) in PRISM, and an unexplained discrepancy between explicit time measurement and results derived from queueing theory (by application of Little’s Law) in the analysis of a simple client/server model. In this addendum to that paper these open questions are addressed and (essentially) solved. In particular, it is shown that expected time analysis by explicit time measurement in PRISM is more complex than previously thought such that the application of Little’s Law still has its merit. ∗Supported by the project HU 10/2012 of the Austrian Academic Exchange Service (ÖAD).
Ensemble margin framework for image classification

Ensemble methods have been successfully used as a classification scheme. This work focuses on exploiting the margin theory to design better ensemble classifiers. We show that low margin instances have a major influence in building reliable classifiers. The margin paradigm is at the core of a new ordering-based mislabeled instance elimination method. The same margin framework, relying on an alternative definition of ensemble margin, is used to derive a novel ensemble diversity measure that has the property of revealing sources of diversity at data level. Our work has been successfully applied to image data.
The Pennsylvania State University The Graduate School The Mary Jean and Frank P. Smeal College of Business Administration DEVELOPMENT OF A PROTOTYPE COURSE SCHEDULING DSS A Thesis in Business Administration by

This paper presents the development of a decision support system for solving a timetabling problem in the Department of Management Science and Information Systems at the Pennsylvania State University. Currently the problem is solved by hand and this solution procedure is highly time consuming. Although several papers concerning this topic have been published, no solution technique exists for our case, since this kind of problem is extremely variable. In this paper I propose a computerized approach to support the timetabling process and to reduce the time required to solve the problem. This system consists of a graphical user interface (GUI) for the user front-end and an automated solution procedure based on an ant colony optimization algorithm to construct a timetable guided by the scheduling individual’s objectives. Test runs on an actual problem data set indicate, that the solution algorithm is indeed able to solve the instance producing implementable timetables while considering the scheduler’s given objective preferences. The required computational effort is reasonable low.
Entropy-based strategies for physical exploration of the environment's degrees of freedom

Physical exploration refers to the challenge of autonomously discovering and learning how to manipulate the environment's degrees of freedom (DOF)-by identifying promising points of interaction and pushing or pulling object parts to reveal DOF and their properties. Recent existing work focused on sub-problems like estimating DOF parameters from given data. Here, we address the integrated problem, focusing on the higher-level strategy to iteratively decide on the next exploration point before applying motion generation methods to execute the explorative action and data analysis methods to interpret the feedback. We propose to decide on exploration points based on the expected information gain, or change in entropy in the robot's current belief (uncertain knowledge) about the DOF. To this end, we first define how we represent such a belief. This requires dealing with the fact that the robot initially does not know which random variables (which DOF, and depending on their type, which DOF properties) actually exist. We then propose methods to estimate the expected information gain for an exploratory action. We analyze these strategies in simple environments and evaluate them in combination with full motion planning and data analysis in a physical simulation environment.
Distributed Deep Learning Using Synchronous Stochastic Gradient Descent

We design and implement a distributed multinode synchronous SGD algorithm, without altering hyper parameters, or compressing data, or altering algorithmic behavior. We perform a detailed analysis of scaling, and identify optimal design points for different networks. We demonstrate scaling of CNNs on 100s of nodes, and present what we believe to be record training throughputs. A 512 minibatch VGG-A CNN training run is scaled 90X on 128 nodes. Also 256 minibatch VGG-A and OverFeat-FAST networks are scaled 53X and 42X respectively on a 64 node cluster. We also demonstrate the generality of our approach via best-in-class 6.5X scaling for a 7-layer DNN on 16 nodes. Thereafter we attempt to democratize deep-learning by training on an Ethernet based AWS cluster and show ~14X scaling on 16 nodes.
Differential Privacy for Sum Queries without External Noise ∗ † Yitao

We consider privacy issues in statistical database and data mining where queries are executed on data collected from a large number of individuals. It is generally established that a strong notion of privacy is guaranteed if the results are perturbed by random noise with sufficient variance (e.g., [5, 27, 44]). In this paper, we point out a vulnerability in such an approach and show that for some types of queries, when the dataset is sufficiently large, the inherent uncertainty associated with unknown quantities is enough to provide similar perturbation and the same privacy can be obtained without external noise. One type of such queries is sum queries which aggregate across all records. This is a surprisingly general primitive supporting various data mining algorithms, including many non-linear ones such as SVD, PCA, k-means, ID3, SVM, EM, and all the algorithms in the statistical query model. We derive privacy conditions for sum queries and, for the first time, provide mathematical proof for the intuition that aggregates across a large number of individuals is private using a widely accepted notion of privacy. Our results are also relevant in query auditing and we show how they can be used to construct simulatable query auditing algorithms that handle online and offline auditing in a uniform way with stronger privacy than ever achieved before.
Chinese word similarity computing

This paper studies Chinese word similarity computing. A 3D model is proposed for representing word meaning based on different points of view. The first one is the view of primitive from Hownet, the second one is the view of words' occurrence in sentences from a specific corpus, and the third one is the view of well known background knowledge from online resources. A Chinese content word is represented in a 3D model. Similarity of two words is computed according to it. Experiments on Chinese news have shown that this method could perform better than existed ones based only on one point of view.