Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of three clinical environments for pre-clinical clinical skills training

Objectives: Primary health care (PHC), secondary health care (SHC), and tertiary health care (THC) were compared in search of the most suitable setting for clinical skills training of pre-clinical students. Methods: The Dundee Ready Educational Environment Measure questionnaire was presented to 300 clerkship students of the Faculty of Medicine at Gadjah Mada University, Indonesia who were attached to PHC, SHC, and THC settings. Students were asked to assess their current attachment for suitability for training of pre-clinical students. Semi-structured interviews were held with 46 clinical supervisors based on the three types of settings. Results: Clerkship students preferred PHC centers over SHC and THC hospitals for clinical skills training of pre-clinical students (p < 0.05). PHC staff felt their centers to be well-equipped to train pre-clinical students, including availability of supervisors’ time for teaching, adequate physical facilities and equipment, and suitable patient cases. Conclusion: In the developing country context, PHC centers seemed more appropriate for clinical skills training of pre-clinical students than SHC and THC hospitals. However, the skills laboratory must guard that clinical skills are trained and performed in the same way in that facility, in PHC centers and in teaching hospitals.
ESTABLISHING A DIGITAL 3D IMAGING LABORATORY FOR HERITAGE APPLICATIONS: FIRST TRIALS

This paper presents the work leading to the launch of a laboratory for digital 3D imaging dedicated to the establishment of a permanent digital heritage preservation centre in Florence. By applying the latest non-contact 3D technologies and methodologies, this center intends to create a bridge between expectations of art historians and curators, and, the people promoting these new 3D technologies. The results of a pilot project aimed at the creation of lasting digital 3D models for archival purpose of statues present in the “Museo dell’Opera del Duomo” in Florence will be described. A summary of experimental results acquired in the fall of 2000 on the ”Maddalena” (Donatello) and on a Formella of Andrea Pisano are presented.
Semi-supervised co-training and active learning based approach for multi-view intrusion detection

Although there is immense data available from networks and hosts, a very small proportion of this data is labeled due to the cost of obtaining expert labels. This proves to be a significant bottle-neck for developing supervised intrusion detection systems that rely solely on labeled data. In spite of the data being collected from real network environments and hence potentially holding valuable information for intrusion detection, such systems can not exploit the remaining unlabeled data. In this work, we intelligently leverage both labeled and unlabeled data. Also, intrusion detection tasks naturally lend themselves into a multi-view scenario, and can benefit significantly if these multiple views are combined meaningfully. In this paper, we propose a co-training method framework for intrusion detection, which is a semi-supervised learning method and can not only utilize unlabeled data, but can also combine multi-view data. We also employ an active learning framework where statistically ambiguous parts of the unlabeled data are identified, which can then be labeled by an expert. This allows for minimal expert labeling while ensuring that the labels obtained from the expert are most informative. In our experiments, we demonstrate that leveraging the unlabeled data using our proposed method significantly reduces the error rate as compared to using the labeled data alone. In addition, our proposed multi-view method has a lower error rate than using a single view.
Protein pheromone expression levels predict and respond to the formation of social dominance networks

Communication signals are key regulators of social networks and are thought to be under selective pressure to honestly reflect social status, including dominance status. The odours of dominants and nondominants differentially influence behaviour, and identification of the specific pheromones associated with, and predictive of, dominance status is essential for understanding the mechanisms of network formation and maintenance. In mice, major urinary proteins (MUPs) are excreted in extraordinary large quantities and expression level has been hypothesized to provide an honest signal of dominance status. Here, we evaluate whether MUPs are associated with dominance in wild‐derived mice by analysing expression levels before, during and after competition for reproductive resources over 3 days. During competition, dominant males have 24% greater urinary MUP expression than nondominants. The MUP darcin, a pheromone that stimulates female attraction, is predictive of dominance status: dominant males have higher darcin expression before competition. Dominants also have a higher ratio of darcin to other MUPs before and during competition. These differences appear transient, because there are no differences in MUPs or darcin after competition. We also find MUP expression is affected by sire dominance status: socially naive sons of dominant males have lower MUP expression, but this apparent repression is released during competition. A requisite condition for the evolution of communication signals is honesty, and we provide novel insight into pheromones and social networks by showing that MUP and darcin expression is a reliable signal of dominance status, a primary determinant of male fitness in many species.
HE4 Tissue Expression and Serum HE4 Levels in Healthy Individuals and Patients with Benign or Malignant Tumors: A Systematic Review

Human epididymis protein 4 (HE4) has received major attention as a potential tumor marker in epithelial ovarian cancer; however, evidence of significant overexpression of HE4 in several other human cancers is expanding. To assess the possible limitations or benefits of HE4 in a clinical setting, this review aims to systematically outline published results of HE4 tissue expression and serum HE4 levels in healthy individuals and patients with benign or malignant tumors. Our findings suggest scientific basis for a potential diagnostic ability of HE4 in gynecologic cancer and lung cancer, and further research is needed regarding other cancers. Yet, it is important to recognize that other malignancies can cause increased HE4 levels. Furthermore, attention should be paid to the influence of age and renal function on HE4 serum levels in future studies as well as in the clinic for proper interpretation of serum HE4 test results. Cancer Epidemiol Biomarkers Prev; 23(11); 2285–95. ©2014 AACR.
A Semantics‐based Approach for the Design and Implementation of Interaction Objects

Although tools for developing graphical user interfaces are becoming increasingly popular, they do not usually highlight precisely which key elements developers should take into account. This still entails considerable expertise in developing user interfaces. In this paper we present an approach to overcome these problems. Our approach is based on a model for interaction objects and a corresponding design space. This is supported by a toolkit where the available interaction objects are initially classified by their semantics whereas in most current toolkits they are investigated by their appearance. This facilitates designers and developers in identifying the interactors needed in order to obtain an Interactive System supporting user tasks.
The Tea Party at the Election

This article is an examination of the Tea Party movement's effects on the 2010 midterm elections. The Tea Party proves to be a grassroots movement that was initially spurred by economic crisis and gradually pulled within the Republican Party. While a handful of experienced conservative interest groupsand the Republican Party itselfmanaged to use the energies of Tea Party sentiment to effect a Republican takeover of the House of Representatives, the movement's decentralized and independent nature prevented grassroots Tea Party groups from being a significant force in the election. While Tea Party supporters continue to resist organization, the effective translation of their political concerns into policy change seems very unlikely. Moreover, in the absence of severe economic crisis, their fortunes seem certain to be determined by the Republican Party.
Using the 802.11e EDCF to achieve TCP upload fairness over WLAN links

We investigate the use of the 802.11e MAC EDCF to address transport layer unfairness in WLANs. A simple solution is developed that uses the 802.11e AIFS and CW/sub min/ parameters to ensure fairness between competing TCP uploads. An analytic model of TCP transport over the modified channel is developed in order to analyse the fairness properties of the proposed scheme. In addition to fairness between competing TCP flows, consideration is extended to include characteristics of TCP flows such as RTT unfairness and responsiveness and we observe that TCP flows with a wireless bottleneck link exhibit quite different properties from flows with a wired bottleneck.
The Dual-Specific Binding of Dengue Virus and Target Cells for the Antibody-Dependent Enhancement of Dengue Virus Infection1

Using flow cytometric assay and monoclonal anti-dengue Ab, we observed that both anti-E and anti-prM Abs could enhance dengue virus infection in a concentration-dependent but serotype-independent manner. Increases were found in both the percentage of dengue-infected cells and the expression of dengue E and NS1 protein per cell. Dengue virion binding and infection were enhanced on FcR-bearing cells via the Fc-FcγRII pathway. Furthermore, anti-prM Ab also enhanced dengue virion binding and infection on cells lacking FcR, such as BHK-21 or A549 cells, by the mechanism of peptide (CPFLKQNEPEDIDCW)-specific binding. Anti-prM Ab cross-reacted with BHK-21 or A549 cells and recognized self-Ags such as heat shock protein 60. In summary, a novel mechanism of anti-prM Ab-mediated enhancement on dengue virus infection was found to be mediated by dual specific binding to dengue virion and to target cells, in addition to the traditional enhancement on FcR-bearing cells.
Easy real object insertion tool for composite photographs

In this paper, we present a tool for easily creating natural composite photographs with just a few mouse clicks. The proposed tool works with three simple steps: 1) draw a bounding box around reference object of background photograph for object height estimation; 2) draw a trimap on the object photograph with mouse drag; 3) move a mouse in location to place an object. We present automatic algorithm for object height estimation in single image and matting technique for extracting object in detail. Experimental results show that our results are created easily and naturally using our tool.
Antirepression System Associated with the Life Cycle Switch in the Temperate Podoviridae Phage SPC32H

ABSTRACT Prophages switch from lysogenic to lytic mode in response to the host SOS response. The primary factor that governs this switch is a phage repressor, which is typically a host RecA-dependent autocleavable protein. Here, in an effort to reveal the mechanism underlying the phenotypic differences between the Salmonella temperate phages SPC32H and SPC32N, whose genome sequences differ by only two nucleotides, we identified a new class of Podoviridae phage lytic switch antirepressor that is structurally distinct from the previously reported Sipho- and Myoviridae phage antirepressors. The SPC32H repressor (Rep) is not cleaved by the SOS response but instead is inactivated by a small antirepressor (Ant), the expression of which is negatively controlled by host LexA. A single nucleotide mutation in the consensus sequence of the LexA-binding site, which overlaps with the ant promoter, results in constitutive Ant synthesis and consequently induces SPC32N to enter the lytic cycle. Numerous potential Ant homologues were identified in a variety of putative prophages and temperate Podoviridae phages, indicating that antirepressors may be widespread among temperate phages in the order Caudovirales to mediate a prudent prophage induction.
Human immunodeficiency virus reverse transcriptase and protease sequence database

The HIV reverse transcriptase and protease sequence database is an on-line relational database that catalogues evolutionary and drug-related sequence variation in the human immunodeficiency virus (HIV) reverse transcriptase (RT) and protease enzymes, the molecular targets of antiretroviral therapy (http://hivdb.stanford.edu). The database contains a compilation of nearly all published HIV RT and protease sequences, including submissions to GenBank, sequences published in journal articles and sequences of HIV isolates from persons participating in clinical trials. Sequences are linked to data about the source of the sequence, the antiretroviral drug treatment history of the person from whom the sequence was obtained and the results of in vitro drug susceptibility testing. Sequence data on two new molecular targets of HIV drug therapy--gp41 (cell fusion) and integrase--will be added to the database in 2003.
Estimating speech from lip dynamics

The goal of this project is to develop a limited lip reading algorithm for a subset of the English language. We consider a scenario in which no audio information is available. The raw video is processed and the position of the lips in each frame is extracted. We then prepare the lip data for processing and classify the lips into visemes and phonemes. Hidden Markov Models are used to predict the words the speaker is saying based on the sequences of classified phonemes and visemes. The GRID audiovisual sentence corpus [10][11] database is used for our study.
Expression of Cdx2 and Hepatocyte Antigen in Gastric Carcinoma: Correlation with Histologic Type and Implications for Prognosis

Purpose: This study was designed to (a) analyze the correlation between the expression of Cdx2 and Hep and the clinicopathologic features of patients with gastric carcinoma, and (b) determine the value of combined analysis of Cdx2 and Hep expression in distinguishing histologic types and prognoses of gastric carcinomas. Experimental Design: The expression of Cdx2 and Hep were studied using immunohistochemistry of paraffin-embedded tumor specimens from 109 patients who underwent D2 resection for gastric adenocarcinoma from 1995 to 1998. Results: Nuclear Cdx2 and Hep expression was detected in 36.7% (40 of 109) and 54.1% (59 of 109) of gastric carcinoma cases, respectively. Expression of Cdx2 and Hep was significantly higher in intestinal-type carcinomas than in diffuse-type carcinomas (P = 0.027 and P = 0.037, respectively). There was a clear negative correlation between Cdx2 expression and lymph node metastasis (P = 0.029), as well as between Hep expression and depth of wall invasion (P = 0.011). The patients with Cdx2-positive or Hep-positive expression shows higher survival rate than those with Cdx2-negative or Hep-negative expression (P = 0.0008 and P = 0.003, respectively). Multivariate analysis revealed that the expression of Cdx2 and Hep were independent prognostic indicators of gastric carcinoma. The combination of Cdx2 and Hep expression was significantly lower in diffuse-type carcinoma than in intestinal or mixed-type carcinoma. Multivariate analysis revealed that Cdx2 and Hep expression was an independent prognostic indicator of gastric carcinoma (P < 0.001). Conclusions: These data suggest that combined analysis of Cdx2 and Hep has significant value in distinguishing histologic types and in predicting the prognosis of gastric carcinoma.
The Child's Understanding of Number

1. Focus on the Preschooler 2. Training Studies Reconsidered 3. More Capacity Than Meets the Eye: Direct Evidence 4. Number Concepts in the Preschooler? 5. What Numerosities Can the Young Child Represent? 6. How Do Young Children Obtain Their Representations of Numerosity? 7. The Counting Model 8. The Development of the How-To-Count Principles 9. The Abstraction and Order-Irrelevance Counting Principles 10. Reasoning about Number 11. Formal Arithmetic and the Young Child's Understanding of Number 12. What Develops and How Conclusions References Index
Platform for Multimodal Signal Acquisition for the Control of Lower Limb Rehabilitation Devices

Patients with some sort of motor disability may benefit from robotic rehabilitation since it can provide more control, accuracy and variety of training modes. This enhances the efficiency of the rehabilitation and, therefore, the recovery of the patient. Assistive devices, like exoskeletons or orthoses, can make use of physiological data, such as electromyography (EMG) and electroencephalography (EEG), in order to detect the movement intention. Combination of data can potentially improve the adaptability of assistive devices with respect to the individual demands. Different methods can be applied depending on the neuromuscular disorder, therapy or assistive device. In this work, we present a multimodal interface which integrates EEG, EMG and inertial sensors (IMU) signals. Experiments were conducted with healthy subjects performing lower limb motor tasks. The aim of the proposed system is to analyze the movement intention (EEG signal), the muscle activation (EMG signal) and the limb motion onset (IMU signal). An experimental protocol is proposed. The results obtained showed that the system is capable to acquire and process the biological signals synchronously. Results indicated that the system is able to identify the movement intention, based on the EEG signal, the movement anticipation, based on the muscle activation, and the limb motion onset.
Web-based GeneChip analysis system for large-scale collaborative projects

UNLABELLED The Web-Based GeneChip Analysis System (WGAS) is developed to overcome limitations in analysis setup efficiency, data and procedure sharing, as well as security issues in existing commercial and public domain solutions. It also incorporates unique functions and resources for more accurate and flexible GeneChip analysis. AVAILABILITY WGAS is freely available at: http://arrayanalysis.mbni. med.umich. edu/arrayanalysis.html.
Amazonian foods and implications for human biology

Abstract Context: Diets of subsistence-based Amazonian populations have been linked to local resources, but are changing with market penetration. Objective: To review the available data on traditional Amazonian foods and diets and evaluate their implications for human biology as a step toward understanding nutrition transitions in the region. Methods: This study used the Human Relations Area Files for information on the diets of Amerindian groups in the Amazon Basin from 1950 to the present, and used other published sources and the authors’ own data. Results: Data on food use was identified for only nine groups and dietary intake data for individuals in only three of the groups. A diet based on starchy staples (manioc and plantains) and fish, supplemented with a limited variety of other plant and animal foods, was found. Bitter manioc-based foods were associated with the consumption of cyanogens and fish with the consumption of mercury. Diets of adults appear to be adequate in energy and protein and low in fats. Children’s diets were not well documented. Conclusion: Based on the limited available data, Amazonian diets are restricted in variety, but appear to be adequate in energy and protein for adults, but likely insufficiently nutrient-dense for children.
Skin sheriff: a machine learning solution for detecting explicit images

Digital forensics experts are increasingly confronted with investigating large amounts of data and judging if it contains digital contraband. In this paper, we present an adaptable solution for detecting nudity or pornography in color images. We combine a novel skin detection approach with machine learning techniques to alleviate manual image screening. We upgrade previous approaches by leveraging machine learning and introducing several novel methods to enhance detection rates. Our nudity assessment uses skin detection and positioning of skin areas within a picture. Sizes, shapes and placements of detected skin regions as well as the total amount of skin in an image are used as features for a support vector machine that finally classifies the image as non-pornographic or pornographic. With a recall of 65.7% and 6.4% false positive rate, our approach outperforms the best reported detection approaches.
Complexity Analysis of Real-Time Reinforcement Learning

This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of reaching a goal state in deterministic domains. Previous work had concluded that, in many cases, tabula rasa reinforcement learning was exponential for such problems, or was tractable only if the learning algorithm was augmented. We show that, to the contrary, the algorithms are tractable with only a simple change in the task representation or initialization. We provide tight bounds on the worst-case complexity, and show how the complexity is even smaller if the reinforcement learning algorithms have initial knowledge of the topology of the state space or the domain has certain special properties. We also present a novel bidirectional Q-learning algorithm to find optimal paths from all states to a goal state and show that it is no more complex than the other algorithms.
Exit Chart Analysis for Slepian-Wolf Turbo Compression

The main objective of this paper is to extend EXIT charts performance analysis technique from turbo channel codes to compressive turbo codes used for the Slepian-Wolf problem. We present the methodology on using EXIT charts in this problem and illustrate its results for several pairs of correlated memoryless sources and turbo compression schemes, observing a good match between numerical EXIT results and BER simulations. Consequently, the generalized EXIT charts presented in this paper allow one to predict behavior of the iterative decoding process for Slepian-Wolf turbo compression.
Scalability implications of virtual private networks

This article gives an overview of the most promising technologies for service providers to offer virtual private network services. The focus is on the analysis of the scalability implications of these virtual private network mechanisms on existing service provider backbone networks. Very often, when deploying VPN services, service providers will be confronted with a trade-off between scalability and security. VPNs that require site-to-site interconnectivity without strong (cryptographic) security can be deployed in a scalable way based on the network-based VPN model, as long as the interaction between the customer and provider routing dynamics are controlled. VPNs that require strong (end-to-end) cryptographic security should be deployed according to the CPE-based VPN model, using the available IPsec protocol suite.
A multiple kernel learning approach to multi-modal pedestrian classification

Pedestrian detection is a key problem in many computer vision applications, especially in surveillance and security systems. To this end, information integration from different imaging modalities, such as thermal infrared and visible spectrum, can significantly improve the detection rate in respect to mono-modal strategies. For this reason, an effective fusion scheme is necessary to combine the information presented by multiple sensors. In this paper, we propose a pedestrian classification method based on the multiple kernel learning framework; standard pixel features (such as spatial derivatives) from both imaging modalities are employed to learn several feature-related basic kernels and a compound kernel is found as an optimized linear combination of basic kernels. Finally the compound kernel is used to train an SVM. Experiments performed on the OTCBVS dataset [1], demonstrate that our recipe definitely outclasses a wide set of literature fusion modalities.