Miracle-dz/UniFAR-FTUs huggingface dataset:
Second Opinion , a Collaborative Online Game for Medical Diagnosis

Information technology has made tremendous impacts on the health care system. This work aims to develop an online intelligent diagnosis system, which will cooperate with human collaborators to improve its machine intelligence to provide fast and accurate diagnosis. We have developed an online interface so that a user can interact with the system as either a diagnoser or a diagnosee. As a diagnosee, the user can interact with the system to provide their symptoms. The system will use its intelligence to plan a strategy of questioning and finally provide a possible diagnosis. As a diagnoser, the user can review stored cases, plan his/her own strategy to interact with the system to learn symptoms of the selected case, and finally give his/her diagnosis. The system encourages the user to compete for points and for a good diagnoser ranking as a component of the game. Using such interaction with human collaborators, we have developed a machine learning algorithm so that the system can automatically improve its questioning strategy and provide faster and more reliable diagnosis. The system now focuses only on sexual transmitted diseases and will be extended to other diseases in future work.
Baseline impedance measured during high‐resolution esophageal impedance manometry reliably discriminates GERD patients

Baseline impedance measured with ambulatory impedance pH monitoring (MII‐pH) and a mucosal impedance catheter detects gastroesophageal reflux disease (GERD). However, these tools are limited by cost or patient tolerance. We investigated whether baseline impedance measured during high‐resolution impedance manometry (HRIM) distinguishes GERD patients from controls.
Practical and secure PCM systems by online detection of malicious write streams

Phase Change Memory (PCM) may become a viable alternative for the design of main memory systems in the next few years. However PCM suffers from limited write endurance. Therefore future adoption of PCM as a technology for main memory will depend on the availability of practical solutions for wear leveling that avoids uneven usage especially in the presence of potentially malicious users. First generation wear leveling algorithms were designed for typical workloads and have significantly reduced lifetime under malicious access patterns that try to write to the same line continuously. Secure wear leveling algorithms were recently proposed. They can handle such malicious attacks, but require that wear leveling is done at a rate that is orders of magnitude higher than what is sufficient for typical applications, thereby incurring significantly high write overhead, potentially impairing overall performance system. This paper proposes a practical wear-leveling framework that can provide years of lifetime under attacks while still incurring negligible (<1%) write overhead for typical applications. It uses a simple and novel Online Attack Detector circuit to adapt the rate of wear leveling depending on the properties of the memory reference stream, thereby obtaining the best of both worlds — low overhead for typical applications and years of lifetime under attacks. The proposed attack detector requires a storage overhead of 68 bytes, is effective at estimating the severity of attacks, is applicable to a wide variety of wear leveling algorithms, and reduces the write overhead of several recently proposed wear leveling algorithms by 16x–128x. The paradigm of online attack detection enables other preventive actions as well.
How does the Mediterranean diet promote cardiovascular health? Current progress toward molecular mechanisms

Epidemiological evidence supports a health‐promoting effect of the Mediterranean Diet (MedDiet), especially in the prevention of cardiovascular diseases. These cardiovascular benefits have been attributed to a number of components of the MedDiet such as monounsaturated fatty acids, antioxidant vitamins and phytochemicals. However, the underlying mechanisms remain unknown. Likewise, little is known about the genes that define inter‐individual variation in response to the MedDiet, although the TCF7L2 gene is emerging as an illustrative candidate for determining relative risk of cardiovascular events in response to the MedDiet. Moreover, omics technologies are providing evidence supporting potential mechanisms, some of them implicating epigenetics (i.e. microRNAs, methylation), and certain data suggest that some traditional foods could contribute via microRNAs possibly acting as exogenous regulators of gene expression. Future research should aim at increasing and consolidating the nutrigenetic and nutrigenomic knowledge of the MedDiet in order to provide sound, personalized and optimized nutritional recommendations.
Compression ratios based on the Universal Similarity Metric still yield protein distances far from CATH distances

Kolmogorov complexity has inspired several alignment-free distance measures, based on the comparison of lengths of compressions, which have been applied successfully in many areas. One of these measures, the socalled Universal Similarity Metric (USM), has been used by Krasnogor and Pelta to compare simple protein contact maps, showing that it yielded good clustering on four small datasets. We report an extensive test of this metric using a much larger and representative protein dataset: the domain dataset used by Sierk and Pearson to evaluate seven protein structure comparison methods and two protein sequence comparison methods. One result is that Krasnogor-Pelta method has less domain discriminant power than any one of the methods considered by Sierk and Pearson when using these simple contact maps. In another test, we found that the USM based distance has low agreement with the CATH tree structure for the same benchmark of Sierk and Pearson. In any case, its agreement is lower than the one of a standard sequential alignment method, SSEARCH. Finally, we manually found lots of small subsets of the database that are better clustered using SSEARCH than USM, to confirm that Krasnogor-Pelta’s conclusions were based on datasets that were too small.
Machine Learning to Design Full-reference Image Quality Assessment Algorithm

A crucial step in image compression is the evaluation of its performance, and more precisely, available ways to measure the quality of compressed images. In this paper, based on a learned classiﬁcation process in order to respect human observers， a method namely Machine Learning-based Image Quality Measure (MLIQM) is proposed，which classiﬁes the quality using multi-Support Vector Machine (SVM) classiﬁcation according to the quality scale recommended by the ITU. Then, the classiﬁcation process is performed to provide the ﬁnal quality class of the considered image. Finally, once a quality class is associated to the considered image, a speciﬁc SVM regression is performed to score its quality. Obtained results are compared with the one obtained applying classical Full-Reference Image Quality Assessment (FR-IQA) algorithms to judge the efﬁciency of the proposed method. DOI: http://dx.doi. org/10.11591/telkomnika.v11i6. 2716
Tuberin-deficiency downregulates N-cadherin and upregulates vimentin in kidney tumor of TSC patients

Angiomyolipomas (AMLs) are associated with cell fibrosis in kidney of Tuberous Sclerosis Complex patients. The mechanism by which the fibrotic proteins accumulated in AMLs has not been explored. In the present study, we investigated the role of Akt/tuberin/mTOR pathway in the regulation cell fibrosis proteins. AML cells that expressed low levels of tuberin showed less expression of N-cadherin and higher of vimentin proteins compared to HEK293 cells. AML cells infected with Ad-tuberin showed a significant decrease in vimentin and an increase in N-cadherin protein expression. In addition, cells treated with rapamycin showed a significant increase in p-Akt and a decrease in p-p70S6K that was associated with a decrease expression of vimentin and a slight increase expression in N-cadherin. On the other hand, cells treated with Akt inhibitor revealed a significant decrease in p-Akt and p-p70S6K that was associated with a significant decrease in vimentin and an increase in N-cadherin expression. In addition, cells transfected with DN-Akt or DN-S6K show significant increase expression in N-cadherin and a decrease in vimentin. Moreover, cells transfected with siRNA against rictor or siRNA against raptor resulted in a decrease in vimentin and an increase N-cadherin expression. Kidney tumors from TSC patients showed significant decrease in N-cadherin and significant increased in vimentin protein expression compared to control kidney tissues. These data comprise the first report to provide the role of Akt/tuberin/mTORC1/2 in the regulation of N-cadherin and vimentin that are involved in the progression of fibrosis in kidney tumor of TSC patients.
Differential ligand-signaling network of CCL19/CCL21-CCR7 system

Chemokine (C-C motif) receptor 7 (CCR7), a class A subtype G-Protein Coupled Receptor (GPCR), is involved in the migration, activation and survival of multiple cell types including dendritic cells, T cells, eosinophils, B cells, endothelial cells and different cancer cells. Together, CCR7 signaling system has been implicated in diverse biological processes such as lymph node homeostasis, T cell activation, immune tolerance, inflammatory response and cancer metastasis. CCL19 and CCL21, the two well-characterized CCR7 ligands, have been established to be differential in their signaling through CCR7 in multiple cell types. Although the differential ligand signaling through single receptor have been suggested for many receptors including GPCRs, there exists no resource or platform to analyse them globally. Here, first of its kind, we present the cell-type-specific differential signaling network of CCL19/CCL21-CCR7 system for effective visualization and differential analysis of chemokine/GPCR signaling. Database URL: http:// www. netpath. org/ pathways? path_ id= NetPath_ 46.
A STUDY OF THE FLAMMABILITY OF MAGNESIUM

Abstract : An investigation of the ignition and burning characteristics was conducted on prepared specimens of four common magnesium alloys. In addition, typical reciprocating engine castings were tested to determine ignition and burning characteristics under fire conditions closely representing the intensity of an aircraft power plant fire. The major results of the prepared specimen tests are presented as a family of curves which indicate that time to ignition did not vary significantly among the alloys tested, but varied directly with thickness of specimen and airflow over the specimen. After ignition, the airflow accelerated the alloy's burning rate. Tests on the castings revealed a minimum time to ignition of 2 minutes for the smallest (23 pounds) and 4 minutes for the largest (91 pounds). In general, tests indicated that it would be good practice to eliminate sharp edges and protrusions from magnesium alloy castings where possible since these areas were observed to be more susceptible to ignition. Small magnesium components that are not an integral part of the engine could represent a substantial fire hazard in that they will ignite in a short period of time under intense fire conditions.
Analysis and Detection of DoS Attacks in Cloud Computing by Using QSE Algorithm

Even if the cloud computing provides a wide variety of resources to its clients, the security issues like Denial of Service (DoS) attacks, loss of important data and sensitive data compromising lead to crucial problems. From the recent survey on protection of sensitive data, there is paucity of security in DoS attacks. In this paper, we have studied the Quantum algorithm approach and focused on the Quantum Swarm Evolutionary (QSE) algorithm and the Quantum-inspired Evolutionary Algorithm (QEA). The main aim of our work is to apply QSE algorithm with comparison of QEA on cloud computing to detect DoS attacks. We conducted an experiment methodology that shows that QSE is step above than the traditional QEA in this context.
Verification Methodology for a Complex System-on-a-Chip

Semiconductor technology has progressed to the point where it is now possible to implement system-level functions on a single LSI chip. However, traditional LSI verification becomes less and less powerful as the scale and complexity increase. In fact, more than half of the time required to develop a System-on-a-Chip (SOC) is used for function verification. A new verification methodology for SOCs should therefore be established. We developed a system-level simulation technology to verify the specification and architecture of an SOC and a logic emulation technology to verify the logic function of an entire SOC. By combining these technologies, we established a powerful verification methodology for an SOC. We applied the verification methodology to develop a high-definition MPEG2 decoder LSI for a digital TV broadcasting system. The LSI was successfully developed on schedule and worked in the first silicon implementation completely according to the specifications.
Electroless Plating of Metallic Coatings On Fabric

ERETOFORE COTTON FIBERS and fabrics have displayed the disadvantages of Hessentially no electrical conductivity, limited thermal conductivity, little or no paramagnetic or ferromagnetic susceptibility, and an acoustical absorption coefficient primarily dependent on the fibrous configuration. The elimination of these suggests a number of completely new applications for cotton fibers and fabrics. Establishing electrical conductivity would provide a method of reducing the nuisances and hazards associated with the electrification of textiles. Increased thermal conductivity would increase the use of these materials in the area of flame retardance and heat dissipation. Making cotton fibers susceptible to magnetic forces would be a unique method for manipulating and transporting fibers in association with textile processing. Increasing acoustical properties allows for the use of these cotton fibers and fabrics in areas where noise abatement is
Inequality and Growth: The Dual Role of Human Capital in Development

To examine how human capital accumulation influences both economic growth and income inequality, we carefully endogenize the demand and supply of skills. We explicitly introduce the costs and externalities in education, and examine how both relate to learning-by-doing and R&D intensity. In addition, we endogenize the determinants of the skill-bias of labor demand: the complementarity between technology and skilled and unskilled labor. Our results identify parameters that are central to the evolution of inequality during the development process. We characterise development thresholds when countries switch endogenously from pure learning to directed R&D, and we show that technical change can generate multiple steady states that are consistent with the cross-country data on inequality and skill-premia.
Understanding Visualization: A Formal Approach Using Category Theory and Semiotics

This paper combines the vocabulary of semiotics and category theory to provide a formal analysis of visualization. It shows how familiar processes of visualization fit the semiotic frameworks of both Saussure and Peirce, and extends these structures using the tools of category theory to provide a general framework for understanding visualization in practice, including: Relationships between systems, data collected from those systems, renderings of those data in the form of representations, the reading of those representations to create visualizations, and the use of those visualizations to create knowledge and understanding of the system under inspection. The resulting framework is validated by demonstrating how familiar information visualization concepts (such as literalness, sensitivity, redundancy, ambiguity, generalizability, and chart junk) arise naturally from it and can be defined formally and precisely. This paper generalizes previous work on the formal characterization of visualization by, inter alia, Ziemkiewicz and Kosara and allows us to formally distinguish properties of the visualization process that previous work does not.
Prediction of ozone-induced lung function responses in humans

The main purpose of this study was to evaluate the ability of a human exposure-response model, which describes ozone-induced changes in forced expiratory volume in 1 second (FEV1) across a wide range of dynamic exposure conditions, to predict responses in independent data. We first conducted an n-fold cross-validation of the model using samples of the original EPA data from which the model was developed. We then identified seven more recently published studies with controlled exposures to a wide range of ozone exposure patterns relevant to the current ambient ozone health standard and used the model to calculate the mean predicted responses for the exposure conditions of the individual studies that we compared to the mean observed responses reported in these studies. The n-fold cross-validation indicated good internal agreement between mean predicted and mean observed responses in the original data used to develop the model. The model accurately captured the patterns of response in each of the seven independent studies with a tendency to overpredict the observed responses by about 1 percentage point of FEV1 decrement on average. We conclude that the model is currently capable of predicting human FEV1 responses across a wide range of dynamic exposure conditions and anticipate further improvements in predictions with the addition of low-concentration exposure data.
Refinement of Seafloor Elevation Using Acoustic Backscatter

Abstract : We propose an algorithm for the reconstruction of elevation and material property maps of the seafloor using a sidescan sonar backscatter image and sparse bathymetric points co-registered within the image. Given a path for the sensor; the reconstruction is corrected for the movement of the fish during the image generation process. To perform reconstruction, an arbitrary but computable scattering model is assumed for the seafloor backscatter. The algorithm uses the sparse bathymetric data to generate an initial estimate for the elevation map which is then iteratively refined to fit the backscatter image by minimizing a global error functional. Concurrently, the parameters of the scattering model are determined on a coarse grid in the image by fitting the assumed scattering model to the backscatter data. The elevation surface and the scattering parameter maps converge to their best fit shape and values given the backscatter data. The reconstruction is corrected for the movement of the sensor by initially doing local reconstructions in sensor coordinates and then transforming the local reconstructions to a global coordinate system and performing the reconstruction again. The algorithm supports different scattering models, so it can be applied to different underwater environments and sonar sensors. In addition to the elevation map of the seafloor, the parameters of the scattering model at every point in the image are generated. Since these parameters describe material properties of the seafloor, the maps of the scattering model parameters can be used to segment the seafloor by material type. (MM)
Genetic Studies on Rheumatoid Arthritis

Though there has been much speculation on the causes of rheumatoid arthritis, the fundamental mechanism remains obscure. There have, however, been indications that a hereditary factor is present (Falls, 1953). Kroner reported four generations of rheumatoid arthritis in one family, the disease being apparently transmitted by the females. Papp and Tepperberg (1937), in another family, recorded eleven persons with rheumatoid arthritis in four generations. Kaufmann and Scheerer (1928) found a greater concordance in monozygotic than in dizygotic twins. Short, Abrams, and Sartwell (1952) recorded a prevalence of 12 per cent. in rheumatoid arthritic families, but of only 5 per cent. in controls and in the series of Stecher, Solomon, and Wolpaw (1952), the prevalence was 5 and 0 1 per cent. in rheumatoid families and controls respectively. In the Empire Rheumatism Council's Report on aetiological factors in rheumatoid arthritis (Lewis-Faning, 1950), 7 per cent. of the fathers of patients as compared with 3 per cent. of the fathers of controls and 15 per cent. of the mothers of patients as opposed to 9 per cent. of the mothers of controls had arthritis. For siblings the figures were 4 per cent. against 2 per cent. Similar figures were obtained by Barter (1952) in a comparison of the family histories of 100 rheumatoids with 100 controls who were non-rheumatic hospital patients. Miall (1955) noted a prevalence of 3 per cent. in the parents and siblings of 59 males with rheumatoid arthritis taken from a population sample in South Wales, but only 0 6 per cent. in the parents and siblings of controls of the same age, taken at random from the local population. De Blecourt (1957) examined over 2,000 relatives of persons with rheumatoid arthritis and a similar number of controls; prevalences ranged from 0 6 per cent. in male cousins to 10 per cent. in mothers of persons with rheumatoid arthritis (average 2-3 per cent.). In the controls the prevalence of rheumatoid arthritis varied from 0-2 per cent. in male cousins to 3 per cent. in mothers (average 0-8 per cent.). These figures, though they give clear evidence of a hereditary influence, do not indicate that this is very important, since the prevalence in other members of the family is not much greater than in the controls. Several factors may, however, have tended to obscure the genetic effect in these studies. Rheumatoid arthritis as diagnosed in the propositi may not have been homogeneous, but may have included a number of diseases with similar clinical features, only one of which had a genetic basis. Furthermore, the disease in the hereditary form may be of low expressivity so that in its milder forms it is not recognized as such by the relatives of the rheumatoids, or it may indeed be completely symptomless. With a view to obtaining more definite information on these points a more detailed survey has been made of the families of persons found to have rheumatoid arthritis in the survey of rheumatic diseases in the town of Leigh, Lancashire.
Semantic support for hypothesis-based research from smart environment monitoring and analysis technologies

Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.