Miracle-dz/UniFAR-FTUs huggingface dataset:
he role of rostral prefrontal cortex in prospective memory : A voxel-based esion study

Patients with lesions in rostral prefrontal cortex (PFC) often experience problems in everyday-life situations requiring multitasking. A key cognitive component that is critical in multitasking situations is prospective memory, defined as the ability to carry out an intended action after a delay period filled with unrelated activity. The few functional imaging studies investigating prospective memory have shown consistent activation in both medial and lateral rostral PFC but also in more posterior prefrontal regions and non-frontal regions. The aim of this study was to determine regions that are necessary for prospective memory performance, using the human lesion approach. We designed an experimental paradigm allowing us to assess time-based (remembering to do something at a particular time) and event-based (remembering to do something in a particular situation) prospective memory, using two types of material, words and pictures. Time estimation tasks and tasks controlling for basic attention, inhibition and multiple instructions processing were also administered. We examined brain-behaviour relationships with a voxelwise lesion method in 45 patients with focal brain lesions and 107 control subjects using this paradigm. The results showed that lesions in the right polar prefrontal region (in Brodmann area 10) were specifically associated with a deficit in time-based prospective memory tasks for both words and pictures. This deficit could not be explained by impairments in basic attention, detection, inhibition or multiple instruction processing, and there was also no deficit in event-based prospective memory conditions. In addition to their prospective memory difficulties, these polar prefrontal patients were significantly impaired in time estimation ability compared to other patients. The same region was found to be involved using both words and pictures, suggesting that right rostral PFC plays a material nonspecific role in prospective memory. This is the first lesion study showing that rostral PFC is crucial for time-based prospective memory. The findings suggest that time-based and event-based prospective memory might be supported at least in part by distinct brain regions. Two particularly plausible explanations for the deficit rest upon a possible role for polar prefrontal structures in supporting in time estimation, and/or in retrieving an intention to act. More broadly, the results are consistent with the view that the deficit of rostral patients in multitasking situations might at least in part be explained by a deficit in prospective memory.
Observations of a deep‐mixing event in Crater Lake, Oregon

We present observations of the evolution of a deep‐mixing event in a deep, temperate lake. The observations were obtained from thermistors mounted on a long‐term mooring in the lake. The event seems to have originated near 150‐m depth and resulted in a plume or layer of cold water from the upper half of the lake that descended to the lake bottom (590 m) over a 3‐d period. Net mixing associated with this event resulted in an overall vertical heat exchange of nearly 1015 J and a volume exchange of 0.7–3.2 km3 (4–18% of the lake volume) between the upper and lower portions of the lake. The deep water displaced during the event is estimated to have carried 0.3–2.5 × 106 mol of nitrate to the upper lake, which accounts for a significant portion of the average annual nitrate flux (∼2–4 × 106 mol yr−1) thought to be upwelled in this highly oligotrophic system.
New Segmentation Approach to Extract Human Mandible Bones Based on Actual Computed Tomography Data

In this paper, a new approach for segmenting different anato mical regions in dental Com puted Tomography (CT) studies is presented. The approach consists of three st eps: Hounsfield unit's threshold (HU) based on gray -level segmentation, multi-object with texture extraction and anatomical regions identification. First, a HU threshold window sets to separate between different regions upon their gray-level values; second, a set of objects are generated by and texture descriptors are calculated for selected windows from the image data sample. Finally, identification of different anatomical regions set for mandible bones cortical and cancellous. It is expected that the proposed approach will also help automate different semi-automatic segm entation techniques by providing initial boundary points for deformable models or seed points for split and merge segmentation algorithms. Preliminary results obtained for dental CT studies of human-mandible are presented.
Adherence to consensus-based diagnosis and treatment guidelines in adult soft-tissue sarcoma patients: a French prospective population-based study.

BACKGROUND Soft-tissue sarcomas (STSs) are rare tumors with varied histological presentations. Management and treatment are thus complex, but crucial for patient outcomes. We assess adherence to adult STS management guidelines across two French regions (10% of the French population). We also report standardized incidence. PATIENTS AND METHODS STS patients diagnosed from 1 November 2006 to 31 December 2007 were identified from pathology reports, medical hospital records, and cancer registries. Guideline adherence was assessed by 23 criteria (validated by Delphi consensus method), and age and sex-standardized incidence rates estimated. Associations between patient, treatment, and institutional factors and adherence with three major composite criteria relating to diagnostic imaging and biopsy as well as multidisciplinary team (MDT) case-review are reported. RESULTS Two hundred and seventy-four patients were included (57.7% male, mean age 60.8 years). Practices were relatively compliant overall, with over 70% adherence for 10 criteria. Three criteria with perfect Delphi consensus had low adherence: receiving histological diagnosis before surgery, adequacy of histological diagnosis (adherence around 50% for both), and MDT discussion before surgery (adherence <30%). Treatment outside of specialized centers was associated with lower adherence for all three composite criteria, and specific tumor sites and/or features were associated with lower adherence for diagnostic imaging, methods, and MDT meetings. STS standardized incidence rates were 4.09 (European population) and 3.33 (World) /100 000 inhabitants. CONCLUSIONS Initial STS diagnosis and treatment across all stages (imaging, biopsy, and MDT meetings) need improving, particularly outside specialized centers. Educational interventions to increase surgeon's sarcoma awareness and knowledge and to raise patients' awareness of the importance of seeking expert care are necessary.
Containing Pandemic Influenza at the Source

Highly pathogenic avian influenza A (subtype H5N1) is threatening to cause a human pandemic of potentially devastating proportions. We used a stochastic influenza simulation model for rural Southeast Asia to investigate the effectiveness of targeted antiviral prophylaxis, quarantine, and pre-vaccination in containing an emerging influenza strain at the source. If the basic reproductive number (R0) was below 1.60, our simulations showed that a prepared response with targeted antivirals would have a high probability of containing the disease. In that case, an antiviral agent stockpile on the order of 100,000 to 1 million courses for treatment and prophylaxis would be sufficient. If pre-vaccination occurred, then targeted antiviral prophylaxis could be effective for containing strains with an R0 as high as 2.1. Combinations of targeted antiviral prophylaxis, pre-vaccination, and quarantine could contain strains with an R0 as high as 2.4.
Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data

Medical diagnostics is often a multi-attribute problem, necessitating sophisticated tools for analyzing high-dimensional biomedical data. Mining this data often results in two crucial bottlenecks: 1) high dimensionality of features used to represent rich biological data and 2) small amounts of labelled training data due to the expense of consulting highly specific medical expertise necessary to assess each study. Currently, no approach that we are aware of has attempted to use active learning in the context of dimensionality reduction approaches for improving the construction of low dimensional representations. We present our novel methodology, AdDReSS (Adaptive Dimensionality Reduction with Semi-Supervision), to demonstrate that fewer labeled instances identified via AL in embedding space are needed for creating a more discriminative embedding representation compared to randomly selected instances. We tested our methodology on a wide variety of domains ranging from prostate gene expression, ovarian proteomic spectra, brain magnetic resonance imaging, and breast histopathology. Across these various high dimensional biomedical datasets with 100+ observations each and all parameters considered, the median classification accuracy across all experiments showed AdDReSS (88.7%) to outperform SSAGE, a SSDR method using random sampling (85.5%), and Graph Embedding (81.5%). Furthermore, we found that embeddings generated via AdDReSS achieved a mean 35.95% improvement in Raghavan efficiency, a measure of learning rate, over SSAGE. Our results demonstrate the value of AdDReSS to provide low dimensional representations of high dimensional biomedical data while achieving higher classification rates with fewer labelled examples as compared to without active learning.
Trajectory-based video retrieval by string matching

This paper proposes a trajectory-based video retrieval system to retrieve desired videos from a video database through string matching. First, in order to represent each trajectory, a hybrid technique is proposed for representing its semantic meanings and geometrical properties. At this scheme, we use the Bezier basis functions to interpolate some lost control points of each represented trajectory. Then, the distance between any two trajectories can be measured by comparing the positions of sampling points extracted along their Bezier approximations. In addition, this hybrid method uses a novel labeling technique for converting a trajectory into a string. This string representation can give more semantic information in interpreting a trajectory and make important improvements in video classification. More importantly, the problem of partial matching will become easy and can be efficiently solved by a string matching technique. Experimental results have proved the superiority of our proposed method.
Collabrative Education UI in Augmented Reality from Remote to Local

The goal of this paper is to provide a easy way for manipulating 3D graphical object in remote education system. We describe a remote collaborative framework running in an augmented reality environment. It provides a nature operation interface for manipulating graphics object in the web browser or applications from different locations. A Jabber like protocol is designed to translate geometry information and transformation status which reduce the total amount of data transmission. We will discuss the structure of this method, and demonstrate its usability with practical applications.
A QoS App-SLO Manager for Virtualized Infrastructure

The management of infrastructure for supporting Cloud Computing presents the challenge of automated service provisioning, which addresses the problem of mapping high-level requirements expressed in end-user terms to low-level resources such as CPU, memory, and network bandwidth. Current infrastructure is supported through virtualization via hypervisors. In this paper, we describe the formal specification of a high-level component for enhancing hypervisors. With this component, applications running in a Virtual Machine can receive a Quality of Service defined by Service Level Objectives. The manager is aware of the application's needs and requests the CPU resources through the lifetime of the Virtual Machine. The implementation of our proposal achieves to manage computing-oriented and net-oriented applications.
A Packet Loss Salvation Scheme for Voice over MANET

This paper experiments a hybrid of mobile ad hoc wireless network (MANET) and fixed land network. We analyze the issues of transferring voice over such networks, and provide a packet loss salvation scheme to reduce packet loss rate. We also provide a new estimation mechanism by utilizing information gleaned from the upstream intermediate node. We take jitter into consideration and analyze how jitter exerts its influence. According to this packet transmission metrics decisions could be made on whether or not a packet should be transmitted at a particular time. Our protocol algorithm was implemented on ad hoc on-demand distance vector (AODV) routing protocol. From our simulation results and analysis it is shown that our scheme can reduce packet loss rate in voice over MANET compared to that of the original AODV
Top Incomes in France: booming inequalities?

I study the evolution of top incomes in France, using income tax tabulations, and confronting them with data from a large sample of households with exhaustive sampling at the upper end of the income distribution, issued by the French tax administration. Results exhibit a strong increase in market income inequalities measured by top income shares since the late 1990s. The surge in top wages at the top 1% and top 0.1% of the wage distribution is predominantly responsible for the explosion of top income shares, and puts an end to 30 years of stability of the French wage hierarchy. I show that top income and top wage mobility is low, stable, and comparable to that in Canada (where income concentration is 2 times higher) and cannot be responsible for this surge in top income and top wage shares. Neither can the decline of top marginal income tax rates fully explain this evolution through effects on reported incomes. However, in a context of strengthened European tax competition and increased high-skilled labor mobility, my results suggest that France, along with other European countries may be on its way to bridging part of its “top income gap” with English-speaking countries. Paris School of Economics. Contact:48 Bv Jourdan, 75014 Paris, Tel:+33(0)1 43 13 63 37. E-mail: camille.landais(at)ens.fr. Acknowledgements: I am grateful to Thomas Piketty, Emmanuel Saez, Tony Atkinson, Eric Maurin, Facundo Alvaredo, Pierre-Yves Cabannes, Clement Carbonnier, Gabrielle Fack, Julien Grenet, Antoine Bozio, Laurent Bach and participants of the Lunch Seminar at Paris School of Economics for their helpful comments. All errors, of course, are mine alone.
Image Correction for UWB Through-wall Imaging Radar

For through-wall imaging radar, the slowing down and refraction of the wave as it propagates through a dielectric wall are important factors that must be taken into account for effective and accurate imaging. In this paper, a closed form method is proposed to compensate the slowing down and refraction of the wave. Simulation results verifying the proposed approach are presented.
Toward Genome-Wide Identification of Bateson–Dobzhansky–Muller Incompatibilities in Yeast: A Simulation Study

The Bateson–Dobzhansky–Muller (BDM) model of reproductive isolation by genetic incompatibility is a widely accepted model of speciation. Because of the exceptionally rich biological information about the budding yeast Saccharomyces cerevisiae, the identification of BDM incompatibilities in yeast would greatly deepen our understanding of the molecular genetic basis of reproductive isolation and speciation. However, despite repeated efforts, BDM incompatibilities between nuclear genes have never been identified between S. cerevisiae and its sister species S. paradoxus. Such negative results have led to the belief that simple nuclear BDM incompatibilities do not exist between the two yeast species. Here, we explore an alternative explanation that such incompatibilities exist but were undetectable due to limited statistical power. We discover that previously employed statistical methods were not ideal and that a redesigned method improves the statistical power. We determine, under various sample sizes, the probabilities of identifying BDM incompatibilities that cause F1 spore inviability with incomplete penetrance, and confirm that the previously used samples were too small to detect such incompatibilities. Our findings call for an expanded experimental search for yeast BDM incompatibilities, which has become possible with the decreasing cost of genome sequencing. The improved methodology developed here is, in principle, applicable to other organisms and can help detect epistasis in general.
Successful Schools for Young Adolescents

At a time when the public, researchers, and policymakers are losing confidence in public schooling, this presentation of case studies of four schools offers solutions and concrete models of diverse ways in which excellence can be attained in middle-grade schools. Asking what "effectiveness" means for the young adolescent age group (a hitherto unexplored area in research literature), how effective schools come about, and how they achieve acceptance in their communities, Lipsitz identifies and examines successful middle-grade schools, noting that the major problem in schooling is meeting the massive individual differences in the development of early adolescents.
Aggregation and sparsity via 1 penalized least squares

This paper shows that near optimal rates of aggregation and adaptation to unknown sparsity can be simultaneously achieved via ‘ 1 penalized least squares in a nonparametric regression setting. The main tool is a novel oracle inequality on the sum between the empirical squared loss of the penalized least squares estimate and a term reﬂecting the sparsity of the unknown regression function.
Understanding Teachers' Efficacy Beliefs: The Role of Professional Community

Title of dissertation: UNDERSTANDING TEACHERS’ EFFICACY BELIEFS: THE ROLE OF PROFESSIONAL COMMUNITY Lisa Looney, Doctor of Philosophy, 2003 Dissertation directed by: Professor Kathryn R. Wentzel Department of Human Development In this study, the relationship between teachers’ perceptions of a departmental professional community and teachers’ sense of efficacy was examined, along with the degree to which vicarious experience and verbal persuasion might mediate this relationship. The definition of professional community within this study was partially modeled after the work of Louis, Kruse, and Bryk (1995), reflecting teachers’ perceptions of the presence of reflective dialogue, deprivatized practice, collaboration, and shared norms within their academic departments. It was expected that teachers who perceived opportunities to talk with one another about student learning (reflective dialogue), observe other teachers during their work in the classroom (deprivatized practice), and collaborate with other teachers would have a higher sense of efficacy than those teachers who did not perceive these features of a departmental professional community. Furthermore, teachers who believed they worked within a department in which colleagues shared norms and values regarding student learning were also expected to experience higher levels of efficacy than those who did not. Finally, it was expected that the relationship between teacher efficacy and professional community would be mediated by vicarious experience and verbal persuasion, two of the four principal sources of information discussed in Bandura’s (1977) self-efficacy theory. A total of 229 teachers from nine high schools in a middle-class school district participated in the study. Results from hierarchical regression analyses indicate that: perception of a departmental professional community was a significant and positive predictor of teachers’ overall efficacy and efficacy for classroom management, instructional practices, and student engagement; of the four community features, teachers’ perception of shared norms and values within the department was the strongest and most consistent predictor of efficacy; deprivatized practice was a significant and positive predictor of teachers’ efficacy for instructional practices; and the mediation model was not significant. Furthermore, teachers’ view of ability as incremental or fixed was a consistent negative predictor of efficacy, while teachers’ years of experience was a significant positive predictor. Teachers’ perceptions of student performance emerged as the strongest predictor of teachers’ efficacy beliefs. Implications of findings and directions for future research are discussed. UNDERSTANDING TEACHERS’ EFFICACY BELIEFS: THE ROLE OF PROFESSIONAL COMMUNITY
Adaptive Modulation with Space-Time Block Coding for MIMO-OFDM Systems

Space-time block coding (STBC) scheme has proved to be efficient in enhancing the performance of communication systems in terms of both bit-error-rate (BER) and symbol-error-rate (SER). Adaptive bit and power allocation (ABPA), on the other hand, is an adaptive modulation scheme that assigns an optimum symbol constellation and power to all subcarriers in a multi-carrier system to improve spectral and power efficiency. In this work, we combine a lookup matrix based ABPA algorithm with subchannel grouping (LM-SG-ABPA) and STBC for orthogonal frequency division multiplexing (OFDM) systems to further enhance the performance and support high data rate applications. Numerical results showed that the proposed transmission structure achieves not only a significantly higher spectral and power efficiency over systems that do not employ any ABPA schemes, but also a better error probability performance in a multiple-input multiple-output (MIMO) channel
Regulation of Inflorescence Branch Development in Rice Through a Novel Pathway Involving the Pentatricopeptide Repeat Protein sped1-D

Panicle type has a direct bearing on rice yield. Here, we characterized a rice clustered-spikelet mutant, sped1-D, with shortened pedicels and/or secondary branches, which exhibits decreased pollen fertility. We cloned sped1-D and found that it encodes a pentatricopeptide repeat protein. We investigated the global expression profiles of wild-type, 9311, and sped1-D plants using Illumina RNA sequencing. The expression of several GID1L2 family members was downregulated in the sped1-D mutant, suggesting that the gibberellin (GA) pathway is involved in the elongation of pedicels and/or secondary branches. When we overexpressed one GID1L2, AK070299, in sped1-D plants, the panicle phenotype was restored to varying degrees. In addition, we analyzed the expression of genes that function in floral meristems and found that RFL and WOX3 were severely downregulated in sped1-D. These results suggest that sped1-D may prompt the shortening of pedicels and secondary branches by blocking the action of GID1L2, RFL, and Wox3. Moreover, overexpression of sped1-D in Arabidopsis resulted in the shortening of pedicels and clusters of siliques, which indicates that the function of sped1-D is highly conserved in monocotyledonous and dicotyledonous plants.
Is Machine Translation Getting Better over Time?

Recent human evaluation of machine translation has focused on relative preference judgments of translation quality, making it difficult to track longitudinal improvements over time. We carry out a large-scale crowd-sourcing experiment to estimate the degree to which state-of-theart performance in machine translation has increased over the past five years. To facilitate longitudinal evaluation, we move away from relative preference judgments and instead ask human judges to provide direct estimates of the quality of individual translations in isolation from alternate outputs. For seven European language pairs, our evaluation estimates an average 10-point improvement to state-of-theart machine translation between 2007 and 2012, with Czech-to-English translation standing out as the language pair achieving most substantial gains. Our method of human evaluation offers an economically feasible and robust means of performing ongoing longitudinal evaluation of machine translation.