Miracle-dz/UniFAR-FTUs huggingface dataset:
Cortical Plasticity after Cochlear Implantation

The most dramatic progress in the restoration of hearing takes place in the first months after cochlear implantation. To map the brain activity underlying this process, we used positron emission tomography at three time points: within 14 days, three months, and six months after switch-on. Fifteen recently implanted adult implant recipients listened to running speech or speech-like noise in four sequential PET sessions at each milestone. CI listeners with postlingual hearing loss showed differential activation of left superior temporal gyrus during speech and speech-like stimuli, unlike CI listeners with prelingual hearing loss. Furthermore, Broca's area was activated as an effect of time, but only in CI listeners with postlingual hearing loss. The study demonstrates that adaptation to the cochlear implant is highly related to the history of hearing loss. Speech processing in patients whose hearing loss occurred after the acquisition of language involves brain areas associated with speech comprehension, which is not the case for patients whose hearing loss occurred before the acquisition of language. Finally, the findings confirm the key role of Broca's area in restoration of speech perception, but only in individuals in whom Broca's area has been active prior to the loss of hearing.
Cloud-based audio fingerprinting service

Audio Fingerprinting allows the identification of a query audio clip by matching the query audio fingerprints against a reference database. Traditionally, the matching process, which is CPU and memory intensive, is implemented either on a single computer (which is confined by CPU and memory limits for large databases), or on a computer cluster in a proprietary manner (which has limited flexibility in scaling the database). We have implemented audio fingerprinting prototype software that can run in a Cloud environment, specifically Hadoop/MapReduce. Because the MapReduce framework is designed for stream data processing instead of database query, we discuss how we address this challenge as well as other challenges such as appropriate data input format and partitioning. A performance evaluation of the software on a real dataset of ~8500 songs and real Hadoop clusters is presented to illustrate its efficacy, where a batch query of 1000 60sec clips can be completed in ~50sec in addition to ~30sec of database loading time with a 12-node cluster configuration.
RELATING ERS SCATTEROMETER DATA TO GLOBAL VEGETATION MODELS

ERS scatterometer (WSC) measurements provide an ideal source of data for large-scale studies of vegetation dynamics because of their good coverage in a relatively short time. The seasonal backscatter changes of a range of vegetation types are examined and related to the vegetation biophysical properties and weather patterns. Moreover, backscattering coefficient, σ, patterns are compared to the vigour of vegetation as indicated by its Leaf Area Index (LAI) which is based on the SDGVM model (a global vegetation model). Initial comparisons indicate good agreement between WSC data and annually averaged LAI estimations. An important issue in relating the data to the model is the fact that ERS scatterometer data must be referenced to the regular geographic grid of the model. Transforming the data into a georeferenced grid involves averaging the data, which may conceal systematic variability in σ in time, space and across incidence angle. The most useful variability measurement appears to be the coefficient of variation after a model-based correction for incidence angle effects. In general, images of variability indicate that for about 75% of the land surface the mean geo-referenced σ images can be considered representative. However, some cover types display continual, significant variability on short timescales, particularly grasslands and sandy deserts. We also consider the issues involved in using the WSC data to provide the freeze/thaw information which is an important biophysical determinant and affects model predictions.
The New Keynesian Phillips Curve: From Sticky Inflation to Sticky Prices

The New Keynesian Phillips Curve (NKPC) model of inflation dynamics based on forward-looking expectations is of great theoretical significance in monetary policy analysis. Empirical studies, however, often find that inflation inertia, rather than inflation expectations, dominate the dynamics of the short-run aggregate supply curve. This paper examines this inconsistency by investigating multiple structural changes in the NKPC for the US over 1968-2005. Both inflation expectations survey data and a rational expectations approximation are used to capture expectations. We find that forward-looking behavior plays a smaller role during the high and volatile inflation regime to 1981 than in the subsequent period of moderate inflation, providing support for the empirical coherence of sticky prices models over the last two decades. A further break in the intercept of the NKPC is identified around 2001 and this may be associated with monetary policy in the recent period.
A novel method for mining highly imbalanced high-throughput screening data in PubChem

Motivation: The comprehensive information of small molecules and their biological activities in PubChem brings great opportunities for academic researchers. However, mining high-throughput screening (HTS) assay data remains a great challenge given the very large data volume and the highly imbalanced nature with only small number of active compounds compared to inactive compounds. Therefore, there is currently a need for better strategies to work with HTS assay data. Moreover, as luciferase-based HTS technology is frequently exploited in the assays deposited in PubChem, constructing a computational model to distinguish and filter out potential interference compounds for these assays is another motivation. Results: We used the granular support vector machines (SVMs) repetitive under sampling method (GSVM-RU) to construct an SVM from luciferase inhibition bioassay data that the imbalance ratio of active/inactive is high (1/377). The best model recognized the active and inactive compounds at the accuracies of 86.60% and 88.89 with a total accuracy of 87.74%, by cross-validation test and blind test. These results demonstrate the robustness of the model in handling the intrinsic imbalance problem in HTS data and it can be used as a virtual screening tool to identify potential interference compounds in luciferase-based HTS experiments. Additionally, this method has also proved computationally efficient by greatly reducing the computational cost and can be easily adopted in the analysis of HTS data for other biological systems. Availability: Data are publicly available in PubChem with AIDs of 773, 1006 and 1379. Contact: ywang@ncbi.nlm. nih.gov; bryant@ncbi.nlm. nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.
Statistical Comparison of Classifiers Using Area Under the ROC Curve

Statistical tests in the literature mainly use error rate for comparison. Receiver Operating Characteristics (ROC) curves and/or Area Under the ROC Curve (AUC) can also be used for comparing classifier performances under a spectrum of loss values. A ROC curve and hence an AUC value is calculated from one training/test pair and to average over randomness in folds, we propose to use k-fold cross-validation to generate a set of ROC curves and AUC values to which we can fit a distribution and test hypotheses on. Experiment results on 15 datasets using 5 different classification algorithms show that our proposed test using AUC values is to be preferred over the usual paired t test on misclassification errors because it can detect equivalences and differences which the error test cannot.
Proactive Data Filtering Algorithm for Aggregation in Wireless Sensor Networks

In this paper, proactive data filtering (PDF) algorithm is proposed for data aggregation (or data fusion) in wireless sensor networks. The objective of the algorithm is to further reduce the energy consumption when sensor nodes perform data aggregation. In many applications, the sensor field will be overwhelmed by unnecessary and redundant sensory information when the sink node disseminates a query throughout the sensor field. In order to reduce the energy consumption, our scheme employs intelligent decision logic in the sensor node which delays or deactivates the transmission of its response. A performance evaluation shows that data aggregation with the PDF significantly improves energy-efficiency.
Stories of Wisdom: A Qualitative Analysis of Autobiographical Narratives of Relatively Wise and Unwise Individuals

The science of wisdom is a contentious field. There is little agreement among dominant research programs concerning how to conceptualize and measure this elusive phenomenon. The current study argues for a narrative analysis of wisdom given that autobiographical stories offer a contextually rich vista into real-life manifestations of wisdom. Presented here is a qualitative investigation of autobiographical wisdom narratives of 8 individuals, equally distributed across parameters of age, gender, and degree of wisdom. Results point to the possibility that relatively wise persons define wisdom more elaborately, participate in more sophisticated autobiographical reasoning processes, and engage with master narratives in a more evaluative and critical manner than relatively unwise individuals. These features did not appear to differ across levels of age and gender. This study validates a narrative approach to the science of wisdom, and suggests that stories may be central to advancing our understanding of this concept.
Critical Contribution of Ox40 Ligand to T Helper Cell Type 2 Differentiation in Experimental Leishmaniasis

Infection of inbred mouse strains with Leishmania major is a well characterized model for analysis of T helper (Th)1 and Th2 cell development in vivo. In this study, to address the role of costimulatory molecules CD27, CD30, 4-1BB, and OX40, which belong to the tumor necrosis factor receptor superfamily, in the development of Th1 and Th2 cells in vivo, we administered monoclonal antibody (mAb) against their ligands, CD70, CD30 ligand (L), 4-1BBL, and OX40L, to mice infected with L. major. Whereas anti-CD70, anti-CD30L, and anti–4-1BBL mAb exhibited no effect in either susceptible BALB/c or resistant C57BL/6 mice, the administration of anti-OX40L mAb abrogated progressive disease in BALB/c mice. Flow cytometric analysis indicated that OX40 was expressed on CD4+ T cells and OX40L was expressed on CD11c+ dendritic cells in the popliteal lymph nodes of L. major–infected BALB/c mice. In vitro stimulation of these CD4+ T cells showed that anti-OX40L mAb treatment resulted in substantially reduced production of Th2 cytokines. Moreover, this change in cytokine levels was associated with reduced levels of anti–L. major immunoglobulin (Ig)G1 and serum IgE. These results indicate that anti-OX40L mAb abrogated progressive leishmaniasis in BALB/c mice by suppressing the development of Th2 responses, substantiating a critical role of OX40–OX40L interaction in Th2 development in vivo.
Sensorless control of PMSM based on state observer in the steady and transient state operations without phase lag

This paper proposes a suite of sensorless control method based on the state observer for the permanent magnet synchronous motor (PMSM) running either in the steady state or in the transient state. The state observer is firstly designed for the PMSM running in the steady state. Then the paper proposes a transient algorithm based on state observer suitable for the motor in the transient state without phase lag. Besides, the load torque observer is designed when the load torque of the motor is unknown. Finally, simulation results are presented, and verify the effectiveness of the paper's design.
Abdominal Fat and Sleep Apnea: the Chicken or the Egg?

Obstructive sleep apnea (OSA) syndrome is a disorder characterized by repetitive episodes of upper airway obstruction that occur during sleep. Associated features include loud snoring, fragmented sleep, repetitive hypoxemia/hypercapnia, daytime sleepiness, and cardiovascular complications. The prevalence of OSA is 2-3% and 4-5% in middle-aged women and men, respectively. The prevalence of OSA among obese patients exceeds 30%, reaching as high as 50-98% in the morbidly obese population. Obesity is probably the most important risk factor for the development of OSA. Some 60-90% of adults with OSA are overweight, and the relative risk of OSA in obesity (BMI >29 kg/m(2)) is >or=10. Numerous studies have shown the development or worsening of OSA with increasing weight, as opposed to substantial improvement with weight reduction. There are several mechanisms responsible for the increased risk of OSA with obesity. These include reduced pharyngeal lumen size due to fatty tissue within the airway or in its lateral walls, decreased upper airway muscle protective force due to fatty deposits in the muscle, and reduced upper airway size secondary to mass effect of the large abdomen on the chest wall and tracheal traction. These mechanisms emphasize the great importance of fat accumulated in the abdomen and neck regions compared with the peripheral one. It is the abdomen much more than the thighs that affect the upper airway size and function. Hence, obesity is associated with increased upper airway collapsibility (even in nonapneic subjects), with dramatic improvement after weight reduction. Conversely, OSA may itself predispose individuals to worsening obesity because of sleep deprivation, daytime somnolence, and disrupted metabolism. OSA is associated with increased sympathetic activation, sleep fragmentation, ineffective sleep, and insulin resistance, potentially leading to diabetes and aggravation of obesity. Furthermore, OSA may be associated with changes in leptin, ghrelin, and orexin levels; increased appetite and caloric intake; and again exacerbating obesity. Thus, it appears that obesity and OSA form a vicious cycle where each results in worsening of the other.
Genetic Evidence for the Association between the Early Growth Response 3 (EGR3) Gene and Schizophrenia

Recently, two genome scan meta-analysis studies have found strong evidence for the association of loci on chromosome 8p with schizophrenia. The early growth response 3 (EGR3) gene located in chromosome 8p21.3 was also found to be involved in the etiology of schizophrenia. However, subsequent studies failed to replicate this finding. To investigate the genetic role of EGR3 in Chinese patients, we genotyped four SNPs (average interval ∼2.3 kb) in the chromosome region of EGR3 in 470 Chinese schizophrenia patients and 480 healthy control subjects. The SNP rs35201266 (located in intron 1 of EGR3) showed significant differences between cases and controls in both genotype frequency distribution (P = 0.016) and allele frequency distribution (P = 0.009). Analysis of the haplotype rs35201266-rs3750192 provided significant evidence for association with schizophrenia (P = 0.0012); a significant difference was found for the common haplotype AG (P = 0.0005). Furthermore, significant associations were also found in several other two-, and three-SNP tests of haplotype analyses. The meta-analysis revealed a statistically significant association between rs35201266 and schizophrenia (P = 0.0001). In summary, our study supports the association of EGR3 with schizophrenia in our Han Chinese sample, and further functional exploration of the EGR3 gene will contribute to the molecular basis for the complex network underlying schizophrenia pathogenesis.
SCHAUFELİ VE BAKKER TARAFINDAN GELİŞTİRİLMİŞ OLAN İŞE ANGAJE OLMA ÖLÇEĞİNİN TÜRKÇE’DE GÜVENİLİRLİK VE GEÇERLİLİĞİNİN ANALİZİ

Arastirmada Schaufeli ve Bakker (2003) tarafindan gelistirilmis olan Ise Angaje Olma Olcegi’nin kisa versiyonu ceviri ve geri-ceviri yontemiyle Turkce’ye tercume edilerek 146 supermarket calisaninin olusturdugu bir orneklemden veri toplanmistir. Orgutsel ozdeslesme, is tatmini, duygusal orgutsel baglilik ve isten ayrilma niyeti olcekleri kullanilarak tercume olcegin yakinsak ve iraksak gecerliligi test edilmistir. Elde edilen veri seti uzerinde yurutulen analizler, 9 maddelik tercume olcegin guvenilir ve gecerli bir olcum araci oldugunu gostermektedir. Kisitlar ve gelecek calismalar icin oneriler ayrica tartisilmistir.
SCM, the M Protein of Streptococcus canis Binds Immunoglobulin G

The M protein of Streptococcus canis (SCM) is a virulence factor and serves as a surface-associated receptor with a particular affinity for mini-plasminogen, a cleavage product of the broad-spectrum serine protease plasmin. Here, we report that SCM has an additional high-affinity immunoglobulin G (IgG) binding activity. The ability of a particular S. canis isolate to bind to IgG significantly correlates with a scm-positive phenotype, suggesting a dominant role of SCM as an IgG receptor. Subsequent heterologous expression of SCM in non-IgG binding S. gordonii and Western Blot analysis with purified recombinant SCM proteins confirmed its IgG receptor function. As expected for a zoonotic agent, the SCM-IgG interaction is species-unspecific, with a particular affinity of SCM for IgGs derived from human, cats, dogs, horses, mice, and rabbits, but not from cows and goats. Similar to other streptococcal IgG-binding proteins, the interaction between SCM and IgG occurs via the conserved Fc domain and is, therefore, non-opsonic. Interestingly, the interaction between SCM and IgG-Fc on the bacterial surface specifically prevents opsonization by C1q, which might constitute another anti-phagocytic mechanism of SCM. Extensive binding analyses with a variety of different truncated SCM fragments defined a region of 52 amino acids located in the central part of the mature SCM protein which is important for IgG binding. This binding region is highly conserved among SCM proteins derived from different S. canis isolates but differs significantly from IgG-Fc receptors of S. pyogenes and S. dysgalactiae sub. equisimilis, respectively. In summary, we present an additional role of SCM in the pathogen-host interaction of S. canis. The detailed analysis of the SCM-IgG interaction should contribute to a better understanding of the complex roles of M proteins in streptococcal pathogenesis.
Spin-liquid phase in the pyrochlore anti-ferromagnet

Correlation functions (CFs) of the classical Heisenberg anti-ferromagnet on the pyrochlore lattice are studied by solving exactly the infinite-component spin-vector model. As in many fully frustrated lattices, the constraint due to the minimization of the energy and the particular structure based on corner-sharing tetrahedra both contribute to the creation of local degrees of freedom. The resulting degeneracy destroys any magnetic order at all temperatures and we obtain no sign of criticality, even at T = 0. Calculated neutron-scattering cross sections have their maxima beyond the first Brillouin zone and reproduce experimental results obtained on Y(Sc)Mn2 and CsCrNiF6 as well as theoretical predictions previously obtained by classical Monte Carlo simulations. Evidences for thermal and spatial decoupling of the magnetic modes are found so that the magnetic fluctuations in this system can be approximated by S(q,T) f(q) h(T). PACS Nos.: 75.10Hk, 75.50Ee, 75.40Cx, 75.40-s
Bayesian Policy Gradient

Policy gradient methods are reinforcement learning algorithms that adapt a parameterized policy by following a performance gradient estimate. Many conventional policy gradient methods use Monte-Carlo techniques to estimate this gradient. The policy is improved by adjusting the parameters in the direction of the gradient estimate. Since Monte Carlo methods tend to have high variance, a large number of samples is required to attain accurate estimates, resulting in slow convergence. In this paper, we propose a Bayesian framework for policy gradient, by modeling the policy gradient as a Gaussian process. This reduces the number of samples needed to obtain accurate gradient estimates. Moreover, estimates of the natural gradient and the gradient covariance are provided at little extra cost. We perform experimental comparisons of the suggested algorithm with classic Monte-Carlo based algorithms on two simple problem domains.
Constrained PSO algorithm for single satellite passive localization form Doppler shift measurements

In this paper, passive localization from a single satellite is addressed. Passive localization is a typical nonlinear filtering and optimal estimation problem, and usually suffers large initial estimation error and low observability. When localizing an emitter located at the surface of the earth, the localization problem needs to satisfy the constraint condition of the earth surface. Particle swarm optimization(PSO) provides an evolutionary computation method to solve the constrained nonlinear optimal problem. However, it is not applicable straightforwardly to constrained optimal problem. Considering the constraint in single satellite passive localization, a new algorithm based on PSO is proposed. This algorithm can reduce the PSO searching dimension using the nonlinear constraint condition. Computer simulation experiments are performed to show the effectiveness of the proposed algorithm.
Optimal Training, Employee Preferences and Moral Hazard

We study an agency model with moral hazard, when the employer ofiers complementary training/development programs that will increase the productivity of the employee’s efiort. Since it is costly for an employer to ofier training and development opportunities and given that employees are not identical, how will an employer choose the quantity and allocation of such programs? Does the quantity and type of training ofiered, vary with the employee’s aversion to efiort? Does more \sincerity" necessarily translate into more employee development? Does more training in fact induce the employee to work harder? In theory the answer could go either way. On the one hand, an employer may wish to leverage the use of such programs to motivate a lazy employee to work harder. Conversely, especially because efiort is unobservable, one can argue that she may be better ofi rewarding a sincere employee with more development opportunities. This work reaches a deflnite and perhaps unpredictable conclusion. We flnd that there is an inverse relationship between the optimal quantity of the training program and increased aversion to efiort for both a relatively lazy and a relatively sincere employee. This is also true regardless of whether the program is relatively cheap or relatively expensive for the employer to ofier. Perhaps surprisingly, there is no qualitative change in the comparative statics results, if the employer can monitor or observe efiort.
Social Capital, the Economy and Well-being

In this chapter, John Helliwell sets the scene for many of the papers that follow by providing an up-to-date and lucid survey of the literature on the impact of social capital on both the economy or economic performance and well-being. This latter term is closely related to the concept of social progress used in this volume. He begins by defining social capital as the networks and norms that facilitate cooperative activities within groups (bonding social capital) and between groups (bridging social capital). Helliwell documents a number of studies that show that social capital actually saves lives. He surveys the literature on subjective well-being, pointing out that unemployment lowers subjective well-being by more than the usual measure of economic cost and certainly more than inflation.