Miracle-dz/UniFAR-FTUs huggingface dataset:
Another Hybrid Algorithm for Nding a Global Mimimum of Mlp Error Functions

This report presents P scg , a new global optimization method for training mul-tilayered perceptrons. Instead of local minima, global minima of the error function are found. This new method is hybrid in the sense that it combines three very diierent optimization techniques: Random Line Search, Scaled Conjugate Gradient and a 1-dimensional minimization algorithm named P. The best points of each component are retained by the hybrid method: simplicity of Random Line Search, eeciency of Scaled Conjugate Gradient, eeciency and convergence toward a global minimum for P. P scg is empirically shown to perform better or much better than three other global random optimization methods and a global deterministic optimization method. The aim of this research is to provide easy-to-use learning methods for several research projects; in particular these methods will be employed by knowledge-based systems. scg variants is more accurate now.
Liquid chromatography-tandem mass spectrometry assay for simultaneous measurement of estradiol and estrone in human plasma.

BACKGROUND Estradiol (E2) and estrone (E1) measurements form an integral part of the assessment of female reproductive function and have expanding roles in other fields. However, many E1 and E2 immunoassays have limited functional sensitivity, suffer from cross-reactivity, and display poor intermethod agreement. To overcome these problems, we developed a sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for the simultaneous measurement of E1 and E2. METHODS After dansyl chloride derivatization, samples were separated by fast gradient chromatography and injected into a tandem mass spectrometer after formation of positive ions with atmospheric pressure chemical ionization. The limits of detection and quantification, recovery, linearity, precision, and reference intervals were determined, and performance was compared with several immunoassays. RESULTS Total run time per sample was 5 min. The multiple-reaction monitoring ion pairs were m/z 506/171 for 3-dansyl-estradiol and m/z 504/171 for 3-dansyl-estrone. The limits of detection for E1 and E2 were 12.9 pmol/L (3.5 ng/L) and 10.3 pmol/L (2.8 ng/L), respectively. Interassay imprecision (CV) was 4-20% (n = 20). The limits of quantification (functional sensitivities) for E1 and E2 were 44.1 pmol/L (11.9 ng/L) and 23.2 pmol/L (6.3 ng/L), respectively. The assay was linear to >2200 pmol/L ( approximately 600 ng/L) for each analyte. Recoveries were 93-108% for E1 and 100-110% for E2. No cross-reactivity was observed. Method comparison with several immunoassays revealed that the latter were inaccurate and prone to interferences at low E1 and E2 concentrations. CONCLUSIONS LC-MS/MS allows rapid, simultaneous, sensitive, and accurate quantification of E1 and E2 in human serum.
Research of the Access and Integration of Grid Database

The integration of grid database is a hot researching field of grid database management nowadays. The middleware of data access and integration then plays an important role in grid database integration. This paper discusses the integration and the access of grid database based on the research and the analysis of OSGA-DAI framework and its internal procedure. We put forward a system framework and model design to extend and improve OGSA-DAI functions. The system presents good performances for the access and the integration of grid database. Finally, combined with the relative key technology and programming skills, we give out a solution of the access and the integration of grid database
End-to-End Security of Information Flow in Web-based Applications

Web-based applications and services are increasingly being used in security-sensitive tasks. Current security protocols rely on two crucial assumptions to protect the confidentiality and integrity of information: First, they assume that end-point software used to handle security-sensitive information is free from vulnerabilities. Secondly, these protocols assume point-to-point communication between a client and a service provider. However, these assumptions do not hold true with large and complex vulnerable end point software such as the Internet browser or web services middleware or in web service compositions where there can be multiple value-adding service providers interposed between a client and the original service provider. To address the problem of large and complex end-point software, we present the AppCore approach which uses manual analysis of information flow, as opposed to purely automated approaches, to split existing software into two parts: a simplified trusted part that handles security-sensitive information and a legacy, untrusted part that handles non-sensitive information without access to sensitive information. Not only does this approach avoid many common and well-known vulnerabilities in the legacy software that compromised sensitive information, it also greatly reduces the size and complexity of the trusted code, thereby making exhaustive testing or formal analysis more feasible. We demonstrate the feasibility of the AppCore approach by constructing AppCores for two real-world applications: a client-side AppCore for https-based applications and an AppCore for web service platforms. Our evaluation shows that security improvements and complexity reductions (over a factor of five) can be attained with minimal modifications to existing software (a few tens of lines of code, and proxy settings of a browser) and an acceptable performance overhead (a few percent). To protect the communication of sensitive information between the clients and service providers in web service compositions, we present an end-to-end security framework called WS-FESec that provides end-to-end security properties even in the presence of misbehaving intermediate services. We show that WS-FESec is flexible enough to support the lattice model of secure information flow and it guarantees precise security properties for each component service at a modest cost of a few milliseconds per signature or encrypted field.
Participation Overload in Physical Rehabilitation

In this paper, we discuss the merits and difficulties of establishing a culture of participation in the context of physical rehabilitation. We describe our own efforts in and experiences from deploying an end-user extensible technology for rehabilitation in a clinical setting. Finally, we discuss how some of the challenges that we have faced could be resolved, and how they are applicable to a wider range of domains.
Choice of Oxygen-Conserving Treatment Regimen Determines the Inflammatory Response and Outcome of Photodynamic Therapy of Tumors

The rate of light delivery (fluence rate) plays a critical role in photodynamic therapy (PDT) through its control of tumor oxygenation. This study tests the hypothesis that fluence rate also influences the inflammatory responses associated with PDT. PDT regimens of two different fluences (48 and 128 J/cm2) were designed for the Colo 26 murine tumor that either conserved or depleted tissue oxygen during PDT using two fluence rates (14 and 112 mW/cm2). Tumor oxygenation, extent and regional distribution of tumor damage, and vascular damage were correlated with induction of inflammation as measured by interleukin 6, macrophage inflammatory protein 1 and 2 expression, presence of inflammatory cells, and treatment outcome. Oxygen-conserving low fluence rate PDT of 14 mW/cm2 at a fluence of 128 J/cm2 yielded ∼70–80% tumor cures, whereas the same fluence at the oxygen-depleting fluence rate of 112 mW/cm2 yielded ∼10–15% tumor cures. Low fluence rate induced higher levels of apoptosis than high fluence rate PDT as indicated by caspase-3 activity and terminal deoxynucleotidyl transferase-mediated nick end labeling analysis. The latter revealed PDT-protected tumor regions distant from vessels in the high fluence rate conditions, confirming regional tumor hypoxia shown by 2-(2-nitroimidazol-1[H]-yl)-N-(3,3,3-trifluoropropyl) acetamide staining. High fluence at a low fluence rate led to ablation of CD31-stained endothelium, whereas the same fluence at a high fluence rate maintained vessel endothelium. The highest levels of inflammatory cytokines and chemokines and neutrophilic infiltrates were measured with 48 J/cm2 delivered at 14 mW/cm2 (∼10–20% cures). The optimally curative PDT regimen (128 J/cm2 at 14 mW/cm2) produced minimal inflammation. Depletion of neutrophils did not significantly change the high cure rates of that regimen but abolished curability in the maximally inflammatory regimen. The data show that a strong inflammatory response can contribute substantially to local tumor control when the PDT regimen is suboptimal. Local inflammation is not a critical factor for tumor control under optimal PDT treatment conditions.
Temporal and Spatial Expression Patterns of miR-302 and miR-367 During Early Embryonic Chick Development

The microRNAs (miRNAs) are small, non-coding RNAs that modulate protein expression by interfering with target mRNA translation or stability. miRNAs play crucial roles in various functions such as cellular, developmental, and physiological processes. The spatial expression patterns of miRNAs are very essential for identifying their functions. The expressions of miR-302 and miR-367 are critical in maintaining stemness of pluripotent stem cells, including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) but their functions in early development are not fully elucidated. So, we used Locked Nucleic Acid (LNA) probes to perform in situ hybridization and confirmed the temporal and spatial distribution patterns during early chick development. As a result, we found that miR-302 and miR-367 were expressed in various tissues such as primitive steak, neural ectoderm, neural plate, neural fold, neural tube, notochord, and oral cavity. Specially, we confirmed that miR-302 and miR-367 were strongly expressed in neural folds in HH8 to HH10. miR-302 was expressed on dorsal part of the neural tube but miR-367 was expressed on lateral and ventral parts of the neural tube. And also we performed quantitative stem-loop real-time PCR to analyze global expression level of miR-302 and miR-367. miR-302 and miR-367 expression was sustained before Hamburger and Hamilton stage (HH) 14. Thus, the temporal and spatial expression patterns of miR-302 and miR-367 may provide us information of the role of these miRNAs on tissue formation during early chick development.
Segmentation of retinal blood vessels based on divergence and bot-hat transform

A vessel segmentation algorithm for pathological retina images is proposed. Firstly, the vessel centerlines are extracted by using the divergence of the normalized gradient vector field. Secondly, the main vessels are segmented by a sequence of bot-hat operators with different scales and directions. Thirdly, the skeleton lines of main vessels are generated after a skeletonization procedure. The distances from each extracted vessel pixel to vessel centerline and to skeleton line are compared. The noisy pixels with larger distance to the centerline than to the skeleton are removed. Finally, a repair procedure is performed to regain the pixels at the positions of vascular intersections and bifurcations. Experimental evaluation on the publicly available DRIVE database and STARE database shows that the proposed algorithm shows a global performance improvement not only for pathological retinal images but also for healthy retinal images.
Point-context descriptor based region search for logo recognition

We propose a novel approach for logo recognition in this paper. Firstly, we adopt a point-context descriptor for region modeling, which is a highly correlated integration of three kinds of features: point, shape, and patch. Secondly, after the query image is segmented into region trees, an asymmetric region-to-image search approach is utilized to visual logo recognition. A weak geometric constraint based on regions is encoded into the inverted file structures to accelerate the search speed. Then we apply global features to refine the results in the re-ranking stage. Finally, we combine each region score both in max-response mode and accumulate-response mode to obtain the final results. To evaluate the performance, we test the proposed approach both on our challenging logo dataset and the Flickr_Logos dataset. Experiments and comparisons show that our approach is superior to the state-of-the-art approaches.
ProperPLACE: a portable parallel algorithm for standard cell placement

Parallel algorithms developed for CAD problems today suffer from three important drawbacks. First, they are machine specific and tend to perform poorly on architectures other than the one for which they were designed. Second, they cannot use the latest advances in improved versions of the sequential algorithms for solving the problem. Third, the quality of results degrade significantly during parallel execution. We address these three problems for an important CAD application: standard cell placement. We have developed a parallel placement algorithm that is portable across a range of MIMD parallel architectures. The algorithm is part of the ProperCAD project which allows the development and implementation of a parallel algorithm such that it can be executed on a wide variety of parallel machines without any change to the source. The parallel placement algorithm is based on an existing implementation of the sequential simulated annealing algorithm, TimberWolfSC 6.0 (C. Sechen and A. Sangiovanni-Vincentelli, 1985). <<ETX>>
Towards a Semantics-Based, End-User-Centered Information Visualization Process

Using and understanding Semantic Web data is almost impossible for lay-users as skills in Semantic Web technologies are required. The information visualization (InfoVis) of this data is one possible approach to address this problem. However, convenient solutions are missing as existing tools like Tableau do not support Semantic Web data or users necessitate programming and visualization skills. In this paper, we propose a novel approach towards a generic InfoVis workbench called VizBoard which enables users to visualize arbitrary Semantic Web data without expert skills in Semantic Web Technologies, programming, and visualization. More precisely, we deﬁne a semantics-based,user-centered InfoVis workﬂow and present a corresponding workbench architecture based on the mashup paradigm, which actively supports lay-users in gaining insights from Semantic Web data, thus proving the practicability and validity of our approach.
Acta Universitatis Upsaliensis Uppsala 2012

The clinical success of a bone-anchored implant is controlled by many factors such as implant shape, chemical composition, mechanical and surface properties. The surface properties (e.g. charge, wettability and roughness) are considered to be important parameters for the biological acceptance of the biomaterial, whereas the bulk properties control the biomechanical behaviour. For implants designed to be used in load-bearing applications in the skeletal system, the biomaterial should preferably integrate into bone tissue for a long lasting function. Lack of integration between the implant and bone increases the risk of micromotions, infections, soft tissue encapsulation, which all reduces the survival rate of the implant and makes revision surgery necessary. Coatings and surface modifications can be used to tailor properties of implant surfaces, and further improve the potential bone bonding and bone in-growth, compared to unmodified surfaces. A biomimetic method, developed by Kokubo, can be used to prepare a hydroxyapatite coating on to titanium substrates. The method is based on a solution based process where the compositions of the soaking medium and thus the formed coatings can be controlled. In this thesis, titanium (oxide) surfaces have been tailored via deposition of ion substituted hydroxyapatite coatings. Biologically relevant ions like strontium, silicon and fluoride were incorporated into apatite coatings. The substrates included well-defined rutile single crystals, as well as poly-crystalline titanium oxide surfaces and experimental Ti implants. The results showed that incorporation of substitute ions alters the morphology, crystallinity, composition and dissolution rates of apatite coatings. The in vivo effects of the ion substituted apatite coatings were also studied. The results showed that the ion substituted apatite coatings have good biocompatibility and can promote early bone formation. Till Mamma o Pappa o resten av min familj List of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. Engqvist. Studies of early growth mechanisms of hydroxyapa-tite on single crystalline rutile: a model system for bioactive surfaces. Influence of surface treatments on the bioactivity of titanium. strontium substituted apatite/titanium dioxide coating on titanium surfaces. Changes of surface composition and morphology after incorporation of ions into biomimetic apatite coating.poration of active ions into calcium phosphate coatings, their release behavior and mechanism. Bone tissue reactions to biomimetic ion-substituted apatite surfaces on titanium implants. Reprints were made with permission from the respective publishers. My contribution to the papers included in the thesis was: Paper I. I took …
Impact of MWE Resources on Multiword Recognition

In this paper, we demonstrate the impact of Multiword Expression (MWE) resources in the task of MWE recognition in text. We present results based on the Wiki50 corpus for MWE resources, generated using unsupervised methods from raw text and resources that are extracted using manual text markup and lexical resources. We show that resources acquired from manual annotation yield the best MWE tagging performance. However, a more finegrained analysis that differentiates MWEs according to their part of speech (POS) reveals that automatically acquired MWE lists outperform the resources generated from human knowledge for three out of four classes.
On-demand Data Numerosity Reduction for Learning Artifacts

In domains in which single agent learning is a more natural metaphor for an artifact-embedded agent, Exemplar-Based Learning (EBL) requires significantly large sets of training examples for it to be applicable. Obviously large sets of training examples contradict resource capabilities of artifacts. To make EBL a possibility for these artifacts, sets of training examples must be reduced in size in a way that does not compromise learning performance in order to relieve artifacts' resources (e.g. memory). In this paper, we investigate training sets requirements for artifacts learning and propose a ranking-based Stratified Ordered Selection (SOS) method to scale them down. Contrary to reduction approaches in mainstream learning, this method has been designed with resource constraint nature of artifacts in mind. Artifacts shall use an intermediary which implements SOS to, dynamically and on-demand, retrieve training subsets based on their resource capacities (e.g. memory, CPU). SOS uses a new Level Order (LO) ranking scheme which has been designed to broaden representation of classes of examples, to quicken data retrieval, and to allow for retrieval of subsets of varying sizes while ensuring same or near same learning performance. We present how SOS evaluates on various well known machine learning datasets and how it compares to some of the best performing data reduction approaches.
A Statistical modelling and analysis of residential electric vehicles' charging demand in smart grids

Electric vehicles (EVs) add significant load on the power grid as they become widespread. The characteristics of this extra load follow the patterns of people's driving behaviours. In particular, random parameters such as arrival time and charging time of the vehicles determine their expected charging demand profile from the power grid. In this paper, we first develop a model for uncoordinated charging power demand of an EV based on a stochastic process in order to characterize its expected daily power demand profile. Next, we illustrate it for different charging time distributions through simulations. This gives us useful insights into the long-term planning for upgrading the power systems' infrastructure to accommodate EVs. Then, we incorporate departure time as another random variable into this modelling and introduce an autonomous demand response (DR) technique to manage the EVs' charging demand. Our results show that, it is possible to accommodate a large number of EVs and achieve the same peak-to-average ratio (PAR) in daily aggregated power consumption of the grid as when there is no EV in the system without any change in the users' commuting behaviours. We also show that this peak value can be further decreased significantly when we add vehicle-to-grid (V2G) capability in the system.
A Practical Framework for Sharing and Rendering Real-World Bidirectional Scattering Distribution Functions

The utilization of real-world materials has been hindered by a lack of standards for sharing and interpreting measured data. This paper presents an XML representation and an Open Source C library to support bidirectional scattering distribution functions (BSDFs) in data-driven lighting simulation and rendering applications.The library provides for the efficient representation, query, and Monte Carlo sampling of arbitrary BSDFs in amodel-free framework. Currently, we support two BSDF data representations: one using a fixed subdivision of thehemisphere, and one with adaptive density. The fixed type has advantages for certain matrix operations, while theadaptive type can more accurately represent highly peaked data. We discuss advanced methods for data-drivenBSDF rendering for both types, including the proxy of detailed geometry to enhance appearance and accuracy.We also present an advanced interpolation method to reduce measured data into these standard representations.We end with our plan for future extensions and sharing of BSDF data.
Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models

Time series subject to parameter shifts of random magnitude and timing are commonly modeled with a change-point approach using Chib's algorithm to draw the break dates. We outline some advantages of an alternative approach in which breaks come through mixture distributions in state innovations, and for which the sampler of Gerlach, Carter, and Kohn allows reliable and efficient inference. We show how the same sampler can be used to model shifts in variance that occur independently of shifts in other parameters and how to draw the break dates efficiently when regime durations follow a Poisson process. Finally, we introduce to the time series literature the concept of adaptive Metropolis–Hastings sampling for discrete latent variable models. We develop an easily implemented adaptive algorithm that improves on the work of Gerlach et al. and promises to significantly reduce computing time in a variety of problems including mixture innovation, change-point, regime switching, and outlier detection. The efficiency gains on two models for U.S. inflation and real interest rates are 257% and 341%.
Institutions and the Environment

This volume contains the definitive contributions to the institutional foundations of environmental issues. It covers the foundations of welfare economics, externalities, market failure, and the central nexus of law and economics. Each contribution illustrates the fundamental importance of institutions â€“ the legal scaffolding of an economy â€“ to environmental problems. This understanding of the institutions of an economy then leads into extensive coverage of how to diagnose environmental problems and then to formulate policy solutions to deforestation, degraded fisheries and pastoral regimes, pollution, land-use conflicts, contested property rights, the tragedy of open-access natural resources and general development problems in sub-Saharan Africa.