Miracle-dz/UniFAR-FTUs huggingface dataset:
RecMax: exploiting recommender systems for fun and profit

In recent times, collaborative filtering based Recommender Systems (RS) have become extremely popular. While research in recommender systems has mostly focused on improving the accuracy of recommendations, in this paper, we look at the "flip" side of a RS. That is, instead of improving existing recommender algorithms, we ask whether we can use an existing operational RS to launch a targeted marketing campaign. To this end, we propose a novel problem called RecMax that aims to select a set of "seed" users for a marketing campaign for a new product, such that if they endorse the product by providing relatively high ratings, the number of other users to whom the product is recommended by the underlying RS algorithm is maximum. We motivate RecMax with real world applications. We show that seeding can make a substantial difference, if done carefully. We prove that RecMax is not only NP-hard to solve optimally, it is NP-hard to even approximate within any reasonable factor. Given this hardness, we explore several natural heuristics on 3 real world datasets - Movielens, Yahoo! Music and Jester Joke and report our findings. We show that even though RecMax is hard to approximate, simple natural heuristics may provide impressive gains, for targeted marketing using RS.
Expansive Open-Door Cervical Laminoplasty: In Situ Reconstruction of Extensor Muscle Insertion on the C2 Spinous Process Combined With Titanium Miniplates Internal Fixation

AbstractRetrospective cohort study.To evaluate efficacy and relevant problems of in situ reconstruction of extensor muscle insertion on the C2 spinous process combined with titanium miniplates internal fixation in expansive open-door cervical laminoplasty in order to improve surgical treatment effect.Expansive open-door cervical laminoplasty has been widely applied in clinical practice, but there are a series of postoperative problems. Therefore, decreasing postoperative complications in order to more effectively relieve symptoms remains a subject for additional research.From October 2011 to September 2013, a total of 60 patients who suffered cervical canal stenosis were treated by expansive open-door laminoplasty with in situ reconstruction of extensor muscle insertion on the C2 spinous process combined with titanium miniplates internal fixation. Changes of cervical curvature index (CI) and range of motion (ROM) were calculated using data from preoperative and postoperative cervical spine X-ray examinations. Clinical function was scored using the Japanese Orthopedics Association Scoring System (JOA) and the neck disability index (NDI). The mean CI before the operation and at 1-year postoperation were 10.49% ± 3.93% and 14.14 ± 2.85 (P < 0.05). The mean ROM values were 43.35 ± 7.55 before the operation, 34.83 ± 7.41 at 1-year postoperation (P < 0.05). The NDI scores decreased from 19.42 ± 4.12 to 7.37 ± 2.58, and the JOA scores increased from 8.87 ± 1.99 to 13.55 ± 1.72, representing significant improvement (P < 0.05). One patient had postoperative C5 nerve root palsy and completely recovered 1 month later. Neither collapse nor door closure in the open-door side occurred in any of the patients.Expansive open-door cervical laminoplasty with in situ reconstruction of extensor muscle insertion on the C2 spinous process combined with titanium miniplates internal fixation is a safe and effective surgical method, and can effectively decrease postoperative complications and achieve satisfactory clinical results.
Students’ motivation for content and language integrated learning and the role of programme intensity

ABSTRACT The study of motivation in Content and Language Integrated Learning (CLIL) contexts has hitherto one-sidedly been concerned with motivation to learn the foreign language, without regard for CLIL’s eponymous focus on the inextricable connection between language and content. To fill this gap, this article focusses on CLIL learners’ motivation not only towards the foreign language, but towards both content and language learning as an integrated construct, termed ‘CLIL motivation’. To this end, 157 secondary education students enrolled in two bilingual tracks of differing intensity (High- versus Low-intensity) were compared in terms of their CLIL motivation. The results show that participation in either the High- or Low-intensity track has a significant effect on both enjoyment of CLIL and the perception of its usefulness for future purposes. These differences are further discussed in terms of students’ foreign language proficiency and academic achievement.
The Social Bayesian Brain: Does Mentalizing Make a Difference When We Learn?

When it comes to interpreting others' behaviour, we almost irrepressibly engage in the attribution of mental states (beliefs, emotions…). Such "mentalizing" can become very sophisticated, eventually endowing us with highly adaptive skills such as convincing, teaching or deceiving. Here, sophistication can be captured in terms of the depth of our recursive beliefs, as in "I think that you think that I think…" In this work, we test whether such sophisticated recursive beliefs subtend learning in the context of social interaction. We asked participants to play repeated games against artificial (Bayesian) mentalizing agents, which differ in their sophistication. Critically, we made people believe either that they were playing against each other, or that they were gambling like in a casino. Although both framings are similarly deceiving, participants win against the artificial (sophisticated) mentalizing agents in the social framing of the task, and lose in the non-social framing. Moreover, we find that participants' choice sequences are best explained by sophisticated mentalizing Bayesian learning models only in the social framing. This study is the first demonstration of the added-value of mentalizing on learning in the context of repeated social interactions. Importantly, our results show that we would not be able to decipher intentional behaviour without a priori attributing mental states to others.
Deformation Analysis of a Pneumatically-Activated Polydimethylsiloxane (PDMS) Membrane and Potential Micro-Pump Applications

This study presents a double-side diaphragm peristaltic pump for efficient medium transport without the unwanted backflow and the lagging effect of a diaphragm. A theoretical model was derived to predict the important parameter of the micropump, i.e., the motion of the valves at large deformations, for a variety of air pressures. Accordingly, we proposed an easy and robust design to fabricate a Polydimethylsiloxane (PDMS)-based micropump. The theoretical model agrees with a numerical model and experimental data for the deformations of the PDMS membrane. Furthermore, variations of the generated flow rate, including pneumatic frequencies, actuated air pressures, and operation modes were evaluated experimentally for the proposed micropumps. In future, the theoretical equation could provide the optimal parameters for the scientists working on the fabrication of the diaphragm peristaltic pump for applications of cell-culture.
Sharing across Multiple MapReduce Jobs

Large-scale data analysis lies in the core of modern enterprises and scientific research. With the emergence of cloud computing, the use of an analytical query processing infrastructure can be directly associated with monetary cost. MapReduce has been a popular framework in the context of cloud computing, designed to serve long-running queries (jobs) which can be processed in batch mode. Taking into account that different jobs often perform similar work, there are many opportunities for sharing. In principle, sharing similar work reduces the overall amount of work, which can lead to reducing monetary charges for utilizing the processing infrastructure. In this article we present a sharing framework tailored to MapReduce, namely, MRShare. Our framework, MRShare, transforms a batch of queries into a new batch that will be executed more efficiently, by merging jobs into groups and evaluating each group as a single query. Based on our cost model for MapReduce, we define an optimization problem and we provide a solution that derives the optimal grouping of queries. Given the query grouping, we merge jobs appropriately and submit them to MapReduce for processing. A key property of MRShare is that it is independent of the MapReduce implementation. Experiments with our prototype, built on top of Hadoop, demonstrate the overall effectiveness of our approach. MRShare is primarily designed for handling I/O-intensive queries. However, with the development of high-level languages operating on top of MapReduce, user queries executed in this model become more complex and CPU intensive. Commonly, executed queries can be modeled as evaluating pipelines of CPU-expensive filters over the input stream. Examples of such filters include, but are not limited to, index probes, or certain types of joins. In this article we adapt some of the standard techniques for filter ordering used in relational and stream databases, propose their extensions, and implement them through MRAdaptiveFilter, an extension of MRShare for expensive filter ordering tailored to MapReduce, which allows one to handle both single- and batch-query execution modes. We present an experimental evaluation that demonstrates additional benefits of MRAdaptiveFilter, when executing CPU-intensive queries in MRShare.
Distance Estimation in a VR Application : Interindividual Differences and Intraindividual Stabilities from a Psychological Point of View

Virtual environments (VE) open up a wide range of experimental possibilities in psychological research (Loomis & Blaskovich, 1999). However, when using Virtual Reality (VR) applications it is often neither possible nor useful to use environments with many secondary depth cues though those are essential for depth perception in virtual worlds (Gobbetti & Scateni, 1998). Depth-cue deprived experimental setups are often necessary to avoid visual overload in experiments where attention is supposed to be focused on single targets e.g. when simple reactions to stimuli are required or when virtual targets have to be grasped or pointed at. Some studies investigated the role of depth cues in VE (e.g. Gaggioli & Breining, 2001; Hu, Gooch, Creem-Regehr & Thomson, 2002), but only one single evidence was found for interindividual differences (Lampton, McDonald & Singer, 1995) and none for stability of depth perception within persons. Yet, these aspects are relevant for psychological research conducted in VE to create expedient setups and because of their importance in obtaining valid results. Therefore two studies were carried out to investigate whether distance estimations are stable within subjects’ own frame of reference and whether interindividual differences exist when a geometrically simple virtual environment is used. The first experiment was conducted in a VR application (3D) and the second one on a standard CRT screen (2D). Results reveal systematic underestimations but also indicate intraindividual stabilities. Furthermore it seems to be useful to enrich the environments with reference objects to enable “more accurate” distance estimations.
Correlation of In Vivo and Ex Vivo ADC and T2 of In Situ and Invasive Murine Mammary Cancers

Ex vivo MRI may aid in the evaluation of surgical specimens, and provide valuable information regarding the micro-anatomy of mammary/breast cancer. The use of ex vivo MRI to study mouse mammary cancer would be enhanced if there is a strong correlation between parameters derived from in vivo and ex vivo scans. Here, we report the correlation between apparent diffusion coefficient (ADC) and T2 values measured in vivo and ex vivo in mouse mammary glands with in situ cancers (mammary intraepithelial neoplasia (MIN)) and invasive cancers (those which spread outside the ducts into surrounding tissue). MRI experiments were performed on the Polyoma middle T oncoprotein breast cancer mouse model (n = 15) in a 9.4T scanner. For in vivo experiments, T2-weighted (T2W) images were acquired to identify abnormal regions, then ADC and T2 values were measured for nine selected slices. For ex vivo experiments, a midline incision was made along the spine, and then skin, glands, and tumors were gently peeled from the body. Tissue was fixed in formalin, placed around a mouse-sized sponge, and sutured together mimicking the geometry of the gland when attached to the mouse. The same pulse sequences used for in vivo experiments were repeated for ex vivo scans at room temperature. Regions of interest were manually traced on T2W images defining features that could be identified on in vivo and ex vivo images. The results demonstrate a strong positive correlations between in vivo and ex vivo invasive cancers for ADC (r = 0.89, p <0.0001) and T2 (r = 0.89, p <0.0001) values; and weak to moderate positive correlations between in vivo and ex vivo in situ cancers for ADC (r = 0.61, p <0.0001) and T2 (r = 0.79, p <0.0001) values. The average ex vivo ADC value was about 54% of the in vivo value; and the average ex vivo T2 was similar to the in vivo value for cancers. Although motion, fixation, and temperature differences affect ADC and T2, these results show a reliable relationship between ADC and T2 in vivo and ex vivo. As a result ex vivo images can provide valuable information with clinical and research applications.
Adenovirally Expressed Noggin and Brain-Derived Neurotrophic Factor Cooperate to Induce New Medium Spiny Neurons from Resident Progenitor Cells in the Adult Striatal Ventricular Zone

Neurogenesis from endogenous progenitor cells in the adult forebrain ventricular wall may be induced by the local viral overexpression of cognate neuronal differentiation agents, in particular BDNF. Here, we show that the overexpression of noggin, by acting to inhibit glial differentiation by subependymal progenitor cells, can potentiate adenoviral BDNF-mediated recruitment of new neurons to the adult rat neostriatum. The new neurons survive at least 2 months after their genesis in the subependymal zone and are recruited primarily as GABAergic DARPP-32+ medium spiny neurons in the caudate-putamen. The new medium spiny neurons successfully project to the globus pallidus, their usual developmental target, extending processes over several millimeters of the normal adult striatum. Thus, concurrent suppression of subependymal glial differentiation and promotion of neuronal differentiation can mobilize endogenous subependymal progenitor cells to achieve substantial neuronal addition to otherwise non-neurogenic regions of the adult brain.
Development of simple setup for model identification using Matlab Data Acquisition

This paper presents a simple acquisition setup to obtain a dynamic model of a real system from input-output experimental data. A data acquisition module with a sampling rate of 1.25MS/s is communicated to the personal computer via USB interface. Matlab Data Acquisition are used to acquire the input output data from the plant, and System Identification toolbox will then generate the plant transfer function. The plant presented in this paper is a DC motor. The validation of transfer function in the Simulink shows that the proposed setup able to model a second-order system. This setup is targeted to assist in the teaching of classical control system for undergraduate students specifically in the subtopic System Modeling. It has advantages in terms of low-cost and portability as well as provides good introductory practical experience for the beginner to Control System.
SYNTHESIS OF MUSICAL SOURCES

The composition of a soundfield containing complex nearfield sources has interesting musical applications. A method is presented here using freefield expansions about exterior points of a harmonic multipole field. A derivation and verification are included. Binaural rendering is the natural method for displaying such soundfields. Some possible musical applications are discussed .
Performance Analysis of Sliding Window Based Erasure Correction for Real-Time Traffic

We propose a fountain-coding-like erasure correction method for streaming traffic with real-time requirements. A sliding window defines the range of non-expired data. Each new block entering the window is once sent as such, followed by probabilistically sending a repair packet, formed as a random combination of the blocks in the current window using a degree distribution as in LT-coding. The decoding of repair packets is based on an iterative algorithm. The performance of the method with a given channel loss probability is analyzed using an exact Markov chain model. The state space, however, has to be truncated for computational tractability. The truncation error is verified to be small enough by simulations. By using the analytical model the optimal degree distribution Is fonnd to be of single-degree type. Both analytical and simulation results on the performance with the optimal repalr packet degree are presented and the effectiveness of the method demonstrated.
DA Φ NE DEVELOPMENTS FOR THE KLOE-2 EXPERIMENTAL RUN C . Milardi for the DA Φ NE Commissioning Team

Recently the peak luminosity achieved on the DAΦNE collider has been improved by almost a factor three by implementing a novel collision scheme based on large Piwinski angle and Crab-Waist. This encouraging result opened new perspectives for physics research and a new run with the KLOE-2 detector has been scheduled to start by spring 2010. The KLOE-2 installation is a complex operation requiring a careful design effort and a several months long shutdown. The high luminosity interaction region has been deeply revised in order to take into account the effect on the beam caused by the solenoidal field of the experimental detector and to ensure background rejection. The shutdown has been also used to implement several other modifications aimed at improving beam dynamics: the wiggler poles have been displaced from the magnet axis in order to cancel high order terms in the field, the feedback systems have been equipped with stronger power supplies and more efficient kickers and electrodes have been inserted inside the wiggler and the dipole vacuum chambers, in the positron ring, to avoid the e-cloud formation. A low level RF feedback has been added to the cavity control in both rings.
Improved Multidimensional Color Image Fusion Based on the Multi-Wavelets

Image fusion refers to the process of combining the visual information present in two or more images into a single high information content image. This study proposes the concept of fusing the Multi-dimensional images using the YCbCr color model based on the Multi-Wavelet Transform (MWT). Initially the source images namely the visible, Infra Red (IR) and Ultra Violet (UV) images are transformed from RGB color model to YCbCr color space and then MWT is applied to the Y, Cb and Cr components of the respective images. Finally the transform coefficients obtained are fused using the different fusion techniques. The performance of the color image fusion process is analyzed using the performance measures-Entropy (H), Peak Signal to Noise Ratio (PSNR), Root Mean Square Error (RMSE) and Correlation Coefficient (CC).
DYNAMIC STABILITY OF THE SOLAR SYSTEM: STATISTICALLY INCONCLUSIVE RESULTS FROM ENSEMBLE INTEGRATIONS

Due to the chaotic nature of the solar system, the question of its long-term stability can only be answered in a statistical sense, for instance, based on numerical ensemble integrations of nearby orbits. Destabilization of the inner planets, leading to close encounters and/or collisions can be initiated through a large increase in Mercury's eccentricity, with a currently assumed likelihood of ∼1%. However, little is known at present about the robustness of this number. Here I report ensemble integrations of the full equations of motion of the eight planets and Pluto over 5 Gyr, including contributions from general relativity. The results show that different numerical algorithms lead to statistically different results for the evolution of Mercury's eccentricity (). For instance, starting at present initial conditions (), Mercury's maximum eccentricity achieved over 5 Gyr is, on average, significantly higher in symplectic ensemble integrations using heliocentric rather than Jacobi coordinates and stricter error control. In contrast, starting at a possible future configuration (), Mercury's maximum eccentricity achieved over the subsequent 500 Myr is, on average, significantly lower using heliocentric rather than Jacobi coordinates. For example, the probability for to increase beyond 0.53 over 500 Myr is >90% (Jacobi) versus only 40%–55% (heliocentric). This poses a dilemma because the physical evolution of the real system—and its probabilistic behavior—cannot depend on the coordinate system or the numerical algorithm chosen to describe it. Some tests of the numerical algorithms suggest that symplectic integrators using heliocentric coordinates underestimate the odds for destabilization of Mercury's orbit at high initial .
Digital watermarking for ROI medical images by using compressed signature image

In medical images, ROI (Region Of Interest) is an area which contains important information and must be stored without any distortion. We propose a digital watermarking method which avoids the distortion of the image data in ROI by embedding signature information into other area than the ROI. Signature image compressed by a progressive coding algorithm is used as the signature information. The most significant information of the signature information is embedded in the nearest area to the ROI. The proposed method can detect the signature image with moderate quality from a clipped image including the ROI. Furthermore, by dividing the contour of the ROI into several regions and embedding the signature information in the regions respectively, the signature image with moderate quality can be acquired from a clipped image including only part of the ROI.
Predicting Asthma-Related Emergency Department Visits Using Big Data

Asthma is one of the most prevalent and costly chronic conditions in the United States, which cannot be cured. However, accurate and timely surveillance data could allow for timely and targeted interventions at the community or individual level. Current national asthma disease surveillance systems can have data availability lags of up to two weeks. Rapid progress has been made in gathering nontraditional, digital information to perform disease surveillance. We introduce a novel method of using multiple data sources for predicting the number of asthma-related emergency department (ED) visits in a specific area. Twitter data, Google search interests, and environmental sensor data were collected for this purpose. Our preliminary findings show that our model can predict the number of asthma ED visits based on near-real-time environmental and social media data with approximately 70% precision. The results can be helpful for public health surveillance, ED preparedness, and targeted patient interventions.