Miracle-dz/UniFAR-FTUs huggingface dataset:
A Perceptual Image Coding method of High Compression Rate

he compression is an important area of research in image processing and has been widely studied in the last decades. Compression algorithms can restitute the exact information (Lossless methods) or introduce a little distortion (lossy methods). The Lossless image compression is designed to reduce or remove the image’s redundancy. They have weak compression ratio but benefit from an exact reconstruction of the image. The purpose of lossy image compression is to minimize the number of bits needed to represent an image without introducing an important degradation. Natural images have an important redundancy among the space-image pixels. A linear transformation is applied to minimize redundancy in the images since it can decorrelate pixel values in the transform domain. The international standard for still image compression, called Joint Photographic Experts Group or JPEG standard [1]-[2], uses the Discrete Cosine Transform (DCT) [3]-[4]. The JPEG2000 [5] uses The Discrete Wavelet Transforms (DWT). The quantization assigns to each transform coefficient a number of bits according to its position. This step is not conservative and attempts to reduce the number of samples. Finally, an entropy encoder codes these samples [6]-[8]. The main objective of the image compression is to achieve the lowest bit rate without loss of the visual information. It implies a distinction between the visible and invisible information contained in an image. This distinction is done by the exploitation of a human visual model, incorporated within the compressive process, precisely at the quantization stage. The key element of such a model is the Contrast Sensitivity Function (CSF). This Function describes the human visual sensitivity to different spatial frequencies by varying their contrast. Its curve shows essentially that the
A study of proteases and protease-inhibitor complexes in biological fluids

We have (a) screened a variety of cell lines and body fluids for plasminogen activators and (b) studied the activity of proteases bound to α2- macroglobulin after exposing the complexes to partial degradation and/or denaturing procedures to unmask proteolytic activity. The respective results show (a) that the plasminogen activators in urine and cell culture media are generally of lower molecular weight than those in plasma; and (b) that proteases bound to α2-macroglobulin recover the ability to attack macromolecular substrates after exposure to sodium dodecyl sulfate while retaining the electrophoretic mobility of the protease inhibitor complex. This indicates that the protease and inhibitor are probably linked by covalent bonds. In contrast, other complexes formed between proteases and inhibitors of lower molecular weight (such as soybean or Kunitz inhibitors) are fully dissociated by sodium dodecyl sulfate (SDS). The experiments described were based on a new procedure for detecting proteolytic enzyme activity in SDS-polyacrylamide gels. The method relies on solutions of nonionic detergents for extracting SDS, after which the electrophoretic gel is applied to an indicator gel consisting of a fibrin- agar mixture. The method is sensitive, permitting the detection of proteinases in less than 1 μl of fresh plasma, and it is effective for resolving small differences in molecular weight. The procedure can be quantitated and, with minor modifications appropriate to each particular system, it has been applied to a broad spectrum of serine enzymes and proenzymes, including some that function in the pathways of fibrinolysis, coagulation and kinin-generation. Other potential applications appear likely.
A linear-time probabilistic counting algorithm for database applications

We present a probabilistic algorithm for counting the number of unique values in the presence of duplicates. This algorithm has O(q) time complexity, where q is the number of values including duplicates, and produces an estimation with an arbitrary accuracy prespecified by the user using only a small amount of space. Traditionally, accurate counts of unique values were obtained by sorting, which has O(q log q) time complexity. Our technique, called linear counting, is based on hashing. We present a comprehensive theoretical and experimental analysis of linear counting. The analysis reveals an interesting result: A load factor (number of unique values/hash table size) much larger than 1.0 (e.g., 12) can be used for accurate estimation (e.g., 1% of error). We present this technique with two important applications to database problems: namely, (1) obtaining the column cardinality (the number of unique values in a column of a relation) and (2) obtaining the join selectivity (the number of unique values in the join column resulting from an unconditional join divided by the number of unique join column values in the relation to he joined). These two parameters are important statistics that are used in relational query optimization and physical database design.
Exact and approximate inference in graphical models: variable elimination and beyond

Probabilistic graphical models offer a powerful framework to account for the dependence structure between variables, which can be represented as a graph. The dependence between variables may render inference tasks such as computing normalizing constant, marginalization or optimization intractable. The objective of this paper is to review techniques exploiting the graph structure for exact inference borrowed from optimization and computer science. They are not yet standard in the statistician toolkit, and we specify under which conditions they are efficient in practice. They are built on the principle of variable elimination whose complexity is dictated in an intricate way by the order in which variables are eliminated in the graph. The so-called treewidth of the graph characterizes this algorithmic complexity: low-treewidth graphs can be processed efficiently. Algorithmic solutions derived from variable elimination and the notion of treewidth are illustrated on problems of treewidth computation and inference in challenging benchmarks from optimization competitions. We also review how efficient techniques for approximate inference such as loopy belief propagation and variational approaches can be linked to variable elimination and we illustrate them in the context of Expectation-Maximisation procedures for parameter estimation in coupled Hidden Markov Models.
Choline metabolism and risk of breast cancer in a population‐based study

Choline is an essential nutrient required for methyl group metabolism, but its role in carcino genesis and tumor progression is not well understood. By utilizing a population‐based study of 1508 cases and 1556 controls, we investigated the associations of di etary intake of choline and two related micronutrients, methionine and betaine, and risk of breast cancer. The highest quintile of choline consumption was associated with a lower risk of breast cancer [odds ratio (OR): 0.76;95% confidence interval (CI): 0.58–1.00] com pared with the lowest quintile. Two putatively functional single nucleotide polymorphisms of choline‐ metabolizing genes, PEMT ‐774G>C (rs12325817) and CHDH +432G>T (rs12676), were also found be related to breast cancer risk. Compared with the PEMT GG genotype, the variant CC genotype was associated with an increased risk of breast cancer (OR: 1.30;95% CI: 1.01–1.67). The CHDH minor T allele was also associated with an increased risk (OR: 1.19;95% CI: 1.00‐–1.41) compared with the major G allele. The BHMTrs3733890 polymorphism was also examined but was found not to be associated with breast cancer risk. We observed a significant interaction between dietary betaine intake and the PEMT rs7926 polymorphism (Pinteraction = 0.04). OUR finding suggest that cholin metabolism may play an important role in breast cancer etiology. — Xu, X. , Gammon, M. D. , Zeisel, S. H. , Lee, Y. L. , Wetmur, J. G. , Teitelbaum, S. L. , Bradshaw, P. T. , Neugut, A. I. , Santella, R. M. , Chen, J. Choline metab olism and risk of breast cancer in a population‐based study. FASEB J. 22, 2045–2052 (2008)
CloudGenius: A Hybrid Decision Support Method for Automating the Migration of Web Application Clusters to Public Clouds

With the increase in cloud service providers, and the increasing number of compute services offered, a migration of information systems to the cloud demands selecting the best mix of compute services and virtual machine (VM ) images from an abundance of possibilities. Therefore, a migration process for web applications has to automate evaluation and, in doing so, ensure that Quality of Service (QoS) requirements are met, while satisfying conflicting selection criteria like throughput and cost. When selecting compute services for multiple connected software components, web application engineers must consider heterogeneous sets of criteria and complex dependencies across multiple layers, which is impossible to resolve manually. The previously proposed CloudGenius framework has proven its capability to support migrations of single-component web applications. In this paper, we expand on the additional complexity of facilitating migration support for multi-component web applications. In particular, we present an evolutionary migration process for web application clusters distributed over multiple locations, and clearly identify the most important criteria relevant to the selection problem. Moreover, we present a multi-criteria-based selection algorithm based on Analytic Hierarchy Process (AHP). Because the solution space grows exponentially, we developed a Genetic Algorithm (GA)-based approach to cope with computational complexities in a growing cloud market. Furthermore, a use case example proofs CloudGenius' applicability. To conduct experiments, we implemented CumulusGenius, a prototype of the selection algorithm and the GA deployable on hadoop clusters. Experiments with CumulusGenius give insights on time complexities and the quality of the GA.
Volume‐Surface Trees

Many algorithms in computer graphics improve their efficiency by using Hierarchical Space Subdivision Schemes (HS3), such as octrees, kD‐trees or BSP trees. Such HS3 usually provide an axis‐aligned subdivision of the 3D space embedding a scene or an object. However, the purely volume‐based behavior of these schemes often leads to strongly imbalanced surface clustering. In this article, we introduce the VS‐Tree, an alternative HS3 providing efficient and accurate surface‐based hierarchical clustering via a combination of a global 3D decomposition at coarse subdivision levels, and a local 2D decomposition at fine levels near the surface. First, we show how to efficiently construct VS‐Trees over meshes and point‐based surfaces, and analyze the improvement it offers for cluster‐based surface simplification methods. Then we propose a new surface reconstruction algorithm based on the volume‐surface classification of the VS‐Tree. This new algorithm is faster than state‐of‐the‐art reconstruction methods and provides a final semi‐regular mesh comparable to the output of remeshing algorithms.
The effect of terminal movement to the physical layer performance of the IEEE 802.11b wireless LAN systems in simulated UMTS vehicular channel

Wireless local area network (WLAN) systems are typically designed to provide fixed or nomadic access. Using WLAN systems for military purposes raises the question of how WLAN terminals can be utilized in a fully mobile outdoor environment. In these environments, there typically exists multipath propagation with a large delay spread in the radio channel. This paper investigates the effect of terminal movement on the physical layer performance and capacity of IEEE 802.11b WLAN systems in a realistic outdoor mobile environment. Several wireless network interface cards are measured in laboratory conditions using a simulated radio channel. The measurement results indicate that WLAN systems can operate in mobile outdoor environment up to a certain mobile speed, and there are significant differences between equipment from product vendors
Exploiting action categories in learning complex games

This paper presents a model for planning in a highly complex game, where certain action types are more common than others and cyclic behaviour can also easily arise. These issues are addressed by exploiting the inherent structure among the possible options to enhance the online learning algorithm: sampling during Monte Carlo Tree Search becomes a two step process, by first sampling from a distribution over the types of legal actions followed by sampling from individual actions of the chosen type. This policy drastically reduces the breadth of the rollout as well as its depth by avoiding redundant sampling behaviour. The result is a large increase in both the performance and efficiency of the model. Another contribution of this paper is assessing the benefits of a parallel implementation and afterstates in complex games. Evaluation is done via agent simulations in the board game Settlers of Catan. The resulting agent is the first based on purely online learning strategies that can handle the full set of legal actions of the game. The evaluation shows that our model outperforms previous state-of-the-art agents while taking decisions in a time threshold tolerated by human opponents.
The Impact of Public Financing on Electoral Competition: Evidence from Arizona and Maine

Does complete public financing of campaigns enhance electoral competition? Arizona and Maine implemented similar clean elections programs for state-level races in 2000, providing an opportunity to examine the consequences of public financing. Employing two measures of competitiveness, I find that clean elections programs in both states significantly increased competition in districts where challengers accepted public funding. These findings suggest that public monies do not simply attract low-quality challengers and that access to campaign funds is an important determinant of competitiveness. As a result, while public financing programs are not panaceas for uncompetitive elections, such programs can enhance competition in races where money is accepted.
Clinical, Cosmetic and Investigational Dermatology Dovepress a New Dermocosmetic Containing Retinaldehyde, Delta-tocopherol Glucoside and Glycylglycine Oleamide for Managing Naturally Aged Skin: Results from in Vitro to Clinical Studies

you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms Introduction: Natural aging of skin tissues, the addition of the cumulative action of the time and radiation exposure result in skin atrophy, wrinkles and degeneration of the extracellular matrix (ECM). The aim of the study was to investigate the beneficial effect of a combination containing retinaldehyde (RAL), delta-tocopherol glucoside (delta-TC) and glycylglycine ole-amide (GGO) and of a dermocosmetic containing the combination. Materials and methods: The protective effect of the combination was assessed through in vitro gene expression of ultraviolet (UV)-irradiated fibroblasts. A skin aging assay using UV light on ex vivo skin samples and a clinical study conducted in 36 women aged from 35 to 55 years with a minimum of level 4 to a maximum of level 6 on the crow's feet photoscale assessed the antiaging effect of the dermocosmetic. Results: When added to UV-irradiated fibroblasts, the combination substantially improved the ECM in activating the elastin fiber production (fibrillin 2, fibulin 1 and 5 and lysyl oxidase-like 2) as well as that of proteins involved in the cellular ECM interactions (integrin b1, paxillin and actin a2). An ex vivo photodamaged human skin model showed that the dermocosmetic formulation containing the combination of the active ingredients protected the elastic network against UV-induced alterations including both elastin and fibrillin-rich fibers in the dermis. A daily application of the dermocosmetic for 2 months on naturally aged skin resulted in a statistically significant improvement (p<0.05) of visible signs of aging comprising crow's feet, wrinkles and periocular fine lines. Finally, the formulation was well tolerated. Conclusion: The dermocosmetic containing RAL, delta-TC and GGO provides a substantial benefit in the daily care of naturally aged skin in women aged 35–55 years.
A systematic search for novae in M 31 on a large set of digitized archival Schmidt plates

Aims. This paper reports on the detection of optical novae in our neighbour galaxy M 31 based on digitized historical Tautenburg Schmidt plates. The accurate positions of the detected novae lead to a much larger database when searching for recurrent novae in M 31. Methods. We conducted a systematic search for novae on 306 digitized Tautenburg Schmidt plates covering a time span of 36 years from 1960 to 1996. From the database of both∼ 3× 10 5 light curves and& 10 6 detections on only one plate per colour band, nova candidates were effi ciently selected by automated algorithms and subsequently individually inspected by eye. Results. We report the detection of 84 nova candidates. We found 55 nova candidates from the automated analysis of the light curves. Among these, 22 were previously unknown, 12 were known but not identified on Tautenburg Schmidt plates before, and 21 nova e had been discovered previously on Tautenburg plates. An additional 29 known novae could be confirmed by the detailed inve stigation of single detections. One of our newly discovered nova candidates shows a high position coincidence with a nova detected about 30 years earlier. Therefore, this object is likely to be a recur rent nova. Furthermore, we re-investigated all 41 nova candidates previously found on Tautenburg plates and confirm all but two. Positions are given for all nova candidates with a typical accuracy of∼ 0. 4. We present light curves and finding charts as online material. Conclusions. The analysis of the plates has shown the wealth of information still buried in old plate archives. Extrapolating from thi s survey, digitization of other historical M 31 plate archive s (e.g. from the Mount Wilson or Asiago observatories) for a systematic nova search looks very promising.
Retention of the cyanobacterial neurotoxin β‐N‐methylamino‐l‐alanine in melanin and neuromelanin‐containing cells – a possible link between Parkinson‐dementia complex and pigmentary retinopathy

β‐N‐methylamino‐l‐alanine (BMAA), a neurotoxic amino acid produced by cyanobacteria, has been suggested to be involved in the etiology of a neurodegenerative disease complex which includes Parkinson‐dementia complex (PDC). In PDC, neuromelanin‐containing neurons in substantia nigra are degenerated. Many PDC patients also have an uncommon pigmentary retinopathy. The aim of this study was to investigate the distribution of 3H‐BMAA in mice and frogs, with emphasis on pigment‐containing tissues. Using autoradiography, a distinct retention of 3H‐BMAA was observed in melanin‐containing tissues such as the eye and neuromelanin‐containing neurons in frog brain. Analysis of the binding of 3H‐BMAA to Sepia melanin in vitro demonstrated two apparent binding sites. In vitro‐studies with synthetic melanin revealed a stronger interaction of 3H‐BMAA with melanin during synthesis than the binding to preformed melanin. Long‐term exposure to BMAA may lead to bioaccumulation in melanin‐ and neuromelanin‐containing cells causing high intracellular levels, and potentially changed melanin characteristics via incorporation of BMAA into the melanin polymer. Interaction of BMAA with melanin may be a possible link between PDC and pigmentary retinopathy.
Holsworth 1 Comparison of QIAcube® Differential to Manual Differential Extraction When Purified Using the QIAamp® DNA Blood Mini Kit

In a 2008-2012 survey performed by the U.S. Department of Justice, an average of 237,868 victims reported being sexually assaulted each year, which calculates to an occurrence roughly every two minutes. (10) Although only about half of all sexual assaults are reported, a great deal of time and effort goes into processing evidence from these cases due to the potential of samples containing female-male mixtures on which differential extractions must be performed. In forensic casework, a differential extraction is a method that incorporates the combination of phase separation with differential centrifugation to isolate sperm cells from other cell types in order to generate two distinct profiles of the victim and the assailant. Traditionally, differential extractions have been performed manually, requiring an analyst to undergo repeated pipetting and multiple centrifugation steps. Due to the hands-on nature of the approach the quality and consistency of the separations tend to be variable from analyst to analyst. A combination of the number of sexual assault cases reported along with the time required to analyze samples from these cases has caused backlogs to become commonplace among many crime labs across the country. Bringing an automated differential extraction procedure online would benefit analysts by not only reducing the backlog of the laboratory but also by streamlining the workflow of a lengthy process and removing analyst to analyst variability. This study focused on determining the utility of Qiagen’s (Hilden, Germany) QIAcube® for differential extraction of samples and compared it to the Qiagen QIAamp® DNA Blood Mini manual method currently being used by the Washoe County Sheriff’s Office (WCSO). The QIAcube®, introduced in 2007, was originally designed to extract nucleic acids and proteins and, therefore, is capable of centrifuging, vortexing,
Optimization and Simulation of Orthopedic Spine Surgery Practice at Mayo Clinic

S surgeries tend to be lengthy (mean time of 4 hours) and highly variable (with some surgeries lasting 18 hours or more). This variability along with patient preferences driving scheduling decisions resulted in both low operating room (OR) utilization and significant overtime for surgical teams at Mayo Clinic. In this paper we discuss the development of an improved scheduling approach for spine surgeries over a rolling planning horizon. First, data mining and statistical analysis was performed using a large data set to identify categories of surgeries that could be grouped together based on surgical time distributions and could be categorized at the time of case scheduling. These surgical categories are then used in a hierarchical optimization approach with the objective of maximizing a weighted combination of OR utilization and net profit. The optimization model is explored to consider trade-offs and relationships among utilization levels, financial performance, overtime allowance, and case mix. The new scheduling approach was implemented via a custom web-based application that allowed the surgeons and schedulers to interactively identify best surgical days with patients. A pilot implementation resulted in a utilization increase of 19% and a reduction in overtime by 10%.