Miracle-dz/UniFAR-FTUs huggingface dataset:
A method for establishing class III medical device equivalence: sodium hyaluronate (GenVisc 850) for the treatment of knee osteoarthritis

Although the concept of equivalence for drugs (generics) and biologics (biosimilars) has been readily adopted, the concept of equivalence or indistinguishable characteristics for class III medical devices has yet to be specifically addressed regarding a defined regulatory approval process in the US. In September 2015, GenVisc 850® (sodium hyaluronate), a hyaluronic acid approved for the treatment of knee osteoarthritis, was approved by the US Food and Drug Administration (FDA) based upon indistinguishable characteristics in comparison to an approved branded hyaluronic acid (Supartz®/Supartz FX™). The purpose of this paper is to review the methodology and report the main outcomes used to demonstrate clinical comparability of GenVisc 850 with Supartz/Supartz FX. The FDA approval was collectively attained using prospectively defined methods for preclinical, physical, and chemical testing, as well as noninferiority in clinical performance comparisons. Evidence from five randomized controlled studies of Supartz/Supartz FX vs saline control injections (used for Supartz approval), two randomized controlled trials of GenVisc 850 vs saline control injections, and one randomized controlled study of GenVisc 850 vs Supartz/Supartz FX provided evidence of safety for GenVisc 850. Efficacy was further assessed based on assessment of the same Supartz studies and three prospectively identified GenVisc 850 studies. A Bayesian network meta-analysis was used to demonstrate that the clinical efficacy of GenVisc 850 was noninferior to Supartz/Supartz FX and superior to saline control. Overall, safety of GenVisc 850 was similar to that of Supartz/Supartz FX and saline control injections, while efficacy of GenVisc 850 was noninferior to that of Supartz/Supartz FX and superior to saline control injections.
Reverse Game Theory Approach for Aggregator Nodes Selection with Ant Colony Optimization Based Routing in Wireless Sensor Network

The self -configurable, randomly distributed, adhoc technology based wireless sensor networks can be invaluable in various domestic and military applications for collecting, processing and propagating wide range of complex environmental data. Hierarchical routing has been adopted, where clusters of nodes are formulated based on geographical location of nodes and associate node to aggregator node and other aggregator node to sink or aggregator node to aggregator node to sink routing mechanism is followed. The model work ―Low Energy Adaptive Clustering Hierarchical (LEACH)‖, is the leading work in this direction, whereas it is a complete probabilistic model, which does not achieve the tradeoff between power and QoS parameter optimization. We proposed RGT- AGN-ACO-R (Reverse Game Theory based Aggregator Node Selection and Ant Colony Optimization based Routing), In order to maximize life time of the network. The proposed protocol has been simulated, and the life time assessment, power inconsistency, residual power against number of rounds is evaluated and is compared with LEACH. Simulation results shows a remarkable enhancement as compare to LEACH
Difference detection with encoder adaptability for low complexity surveillance video compression

Video surveillance has been widely applied in broad area to improve the public safety and to protect the residential privacy. Because of the requirements in storing the video data over a period of time for future use and because of the huge size of the raw video data, video compression technique has been integrated into the video camera of the surveillance system. As a state-of-the-art video compression technique, H.264/AVC is generally in use. However, it often leads to high computational complexity, which induces high power dissipation when a tremendous amount of cameras are installed to build a large scale of surveillance system. In this paper, a difference detection algorithm is proposed to work as a preprocessing module before video encoder to reduce the computational complexity of video compression. Because of the independency between the proposed processing and the video encoding scheme, it has high adaptability to work with any existing H.264 video encoder to save the cost in implementation and application. Experimental results demonstrate that an average of over 82% of computational complexity reduction can be achieved by integrating the proposed algorithm either into an encoder with high complexity rate distortion optimization (RDO) coding scheme or an encoder with fast algorithm. Besides the significant reduction in computational complexity, an average of 0.06 dB improvement in PSNR is further achieved against the H.264 Main Profile with high complexity RDO coding scheme.
A NOVEL ALGORITHM FOR ACTIVE CONTOUR MODELS: ADAPTIVE SNAKES

We present a novel algorithm to optimize deformable contour models. It overcomes an inherent problem of traditional snakes using a dynamic intervention in the evolution of the curve so that leads to better fidelity in contour detection. In practice, the main difference from the traditional GVF snakes is the definition of a feature merit function. The proposed method solves the problem of points bunching together on strong portions of the contour and achieves fuller matching of concavities with external forces. We also show with a set of well-parameterized images that the proposed solution leads to better convergence and matching.
Entropy minimization based robust algorithm for adaptive networks

In this paper, the problem of estimating the impulse responses of individual nodes in a network of nodes is dealt. It was shown by the previous work in literature that when the nodes can interact with each other, fusion based adaptive filtering approaches are more effective than handling nodes independently. Here we are proposing the use of entropy functional based optimization in the adaptive filtering stage. We tested the new method on networks under Gaussian and ε-contaminated Gaussian noise. The results show that the proposed method achieves significant improvements in the error rates in case of ε-contaminated noise.
Linkers Having a Crucial Role in Antibody–Drug Conjugates

Antibody–drug conjugates (ADCs) comprised of a desirable monoclonal antibody, an active cytotoxic drug and an appropriate linker are considered to be an innovative therapeutic approach for targeted treatment of various types of tumors and cancers, enhancing the therapeutic parameter of the cytotoxic drug and reducing the possibility of systemic cytotoxicity. An appropriate linker between the antibody and the cytotoxic drug provides a specific bridge, and thus helps the antibody to selectively deliver the cytotoxic drug to tumor cells and accurately releases the cytotoxic drug at tumor sites. In addition to conjugation, the linkers maintain ADCs’ stability during the preparation and storage stages of the ADCs and during the systemic circulation period. The design of linkers for ADCs is a challenge in terms of extracellular stability and intracellular release, and intracellular circumstances, such as the acid environment, the reducing environment and cathepsin, are considered as the catalysts to activate the triggers for initiating the cleavage of ADCs. This review discusses the linkers used in the clinical and marketing stages for ADCs and details the fracture modes of the linkers for the further development of ADCs.
Novel somatic single nucleotide variants within the RNA binding protein hnRNP A1 in multiple sclerosis patients

Some somatic single nucleotide variants (SNVs) are thought to be pathogenic, leading to neurological disease. We hypothesized that heterogeneous nuclear ribonuclear protein A1 (hnRNP A1), an autoantigen associated with multiple sclerosis (MS) would contain SNVs. MS patients develop antibodies to hnRNP A1 293-304, an epitope within the M9 domain (AA 268-305) of hnRNP A1. M9 is hnRNP A1’s nucleocytoplasmic transport domain, which binds transportin-1 (TPNO-1) and allows for hnRNP A1’s transport into and out of the nucleus. Genomic DNA sequencing of M9 revealed nine novel SNVs that resulted in an amino acid substitution in MS patients that were not present in controls. SNVs occurred within the TPNO-1 binding domain (hnRNP A1 268-289) and the MS IgG epitope (hnRNP A1 293-304), within M9. In contrast to the nuclear localization of wild type (WT) hnRNP A1, mutant hnRNP A1 mis-localized to the cytoplasm, co-localized with stress granules and caused cellular apoptosis. Whilst WT hnRNP A1 bound TPNO-1, mutant hnRNP A1 showed reduced TPNO-1 binding. These data suggest SNVs in hnRNP A1 might contribute to pathogenesis of MS.
Anomaly Detection by Clustering in the Network

Intrusions impose serious security threat to network environment, so it is necessary to detect and cope with them. Many intrusion detection methods focus on signature detection, where models are built to recognize known attacks. However, signature detection, limited by its nature, cannot detect novel attacks. New intrusion types, of which detection systems may not even be aware, are difficult to detect. Anomaly detection focuses on modeling the normal behavior and identifying significant deviations, which could be novel attacks. In this paper we present a clustering algorithm to identify outliers. It performs clustering on feature vectors collected from the network and can automatically detect new types of intrusions without need of manual classification of training data. Experimental results show that our system achieves a satisfactory intrusions detection rate while keeping the false positive rate reasonably low.
Examining the psychological consequences of surviving childhood cancer: systematic review as a research method in pediatric psychology.

OBJECTIVE To report the results of a systematic review to determine the psychological consequences of surviving childhood cancer. METHODS Searches were conducted using Psyclit, Medline, Cinahl, and Bids and articles selected on the basis of predefined criteria. Key information was extracted to data sheets and these were rated by two coders. RESULTS Twenty studies were identified, seventeen from the United States. Survivors did not show deficits in measures of anxiety, depression, or self-esteem when compared with population norms or matched controls. Survivors of some cancers (bone tumors) have poorer outcomes. CONCLUSIONS The results of this review support findings of previous descriptive reviews. Methodological problems include poorly reported medical information (for example, time since diagnosis), heterogeneous samples, self-selection of participants, poorly chosen/lack of suitable measures, and a lack of longitudinal work. Findings are discussed in terms of the need for cross-cultural work on adjustment to childhood cancer, the need for studies to take on a more developmental approach, and for greater national and international collaboration.
Zeros of {-1, 0, 1} Power Series and Connectedness Loci for Self-Affine Sets

We consider the set Ω2 of double zeros in (0, 1) for power series with coefficients in {-1, 0, 1}. We prove that Ω2 is disconnected, and estimate minΩ2 with high accuracy. We also show that [2-1/2 - n, 1) ⊂ Ω2 for some small, but explicit, n > 0 (this was known only for n = 0). These results have applications in the study of infinite Bernoulli convolutions and connectedness properties of self-affine fractals.
The impact of sleepiness and sleep constructs on driving performance

THE IMPACT OF SLEEPINESS AND SLEEP CONSTRUCTS ON DRIVING PERFORMANCE Jennifer Freeman May Old Dominion University, 2012 Director: Dr. Bryan E. Porter Sleepiness causes performance decrements that lead to thousands of crashes and fatalities annually. Research supports the conclusions that sleep duration and circadian rhythms impact sleepiness and affect driving performance. Conflicting in the literature is whether severity of sleep disorders, sleep quality and subjective sleepiness affect driving performance. The correlation between a driver's perception of their sleepiness and their driving performance is also unclear. The primary goal of this study was to create an indepth model demonstrating which measures of sleepiness influence driving performance. It was hypothesized that sleep quality, sleep apnea severity and subjective sleepiness add to a model of how sleep constructs impact driving performance. The secondary goal of this study was to compare trait and state sleepiness to determine which correlates with driving performance. It was hypothesized that participants with state sleepiness would have a greater decline across the 60-minute drive as compared to participants with trait sleepiness. Both sleepiness groups would have increased lane position variability compared to the normal group. The tertiary goal was to examine driving performance decrements of sleep apnea drivers compared with healthy controls. It was hypothesized that the sleep apnea group would perform worse on the driving simulator test compared with the control group. Results indicate that sleep quality and subjective trait sleepiness significantly add to models of sleepiness and driving performance. The model developed here show that years with driver's license, sleep efficiency and trait sleepiness are significant predictors of lane position variability. Also, results show that driving performance is worse for participants high in trait sleepiness. Participants with high state sleepiness had no significant performance differences compared to non-sleepy participants. Sleep apnea participants did not perform significantly worse than controls as hypothesized but there was a significant group by time interaction indicating that sleep apnea participants' performance degraded more quickly over the course of the drive. These results can be generalized to the community members and students, but not necessarily to sleep disorder center patients.
architecture and gene expression genomethe erythrocytic cycle reveals a strong connection between genome during P . falciparum Three-dimensional modeling of the Material Supplemental

Material Supplemental http://genome.cshlp. org/content/suppl/2014/03/31/gr.169417. 113.DC1. html References http://genome.cshlp. org/content/24/6/974.full. html#ref-list-1 This article cites 46 articles, 15 of which can be accessed free at: License Commons Creative . http://creativecommons.org/licenses/by-nc/4.0/ described at a Creative Commons License (Attribution-NonCommercial 4.0 International), as ). After six months, it is available under http://genome.cshlp. org/site/misc/terms.xhtml first six months after the full-issue publication date (see This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the
( Un-) Decidability Results for Head-Driven Phrase Structure Grammar

Head-driven Phrase Structure Grammar (HPSG, Pollard and Sag (1987, 1994)) is currently one of the most prominent linguistic theories. A grammar for HPSG is given by a set of abstract language universal principles, a set of language specific principles, and a lexicon. A sentence is grammatical, if it is compatible with all of the principles. The data structures underlying HPSG are so-called feature structures. These have always been considered as graphs. In this paper, we formalise feature structures as (hyper-) graphs and use monadic second-order logic (MS2) as a language to talk about these feature graphs. We indicate that HPSG grammar principles can be expressed as MS2-formulae over feature graphs. And we investigate the decidability properties of this framework. Doing so, we show that the MS2theory of HPSG feature graphs is undecidable. Since the general definition of feature graphs we present does not only lead to the undecidability result, but has also other linguistically undesirable properties, we propose to restrict the class of feature graphs to the subclass that can be generated by so-called hyperedge replacement grammars. Under this restriction, the MS2-theory of feature graphs becomes decidable.
Designing hybrid integrative evolutionary approaches to the car sequencing problem

In this paper, we present three new integrative approaches for solving the classical car sequencing problem. These approaches are essentially based on a genetic algorithm which incorporates two crossover operators using an integer linear programming model. The two proposed hybrid crossover are combined efficiently in a genetic algorithm and we show that the hybrid approach outperforms a genetic algorithm with local search on the CSPLib benchmarks. Although that the computations time are long when integrative hybridization is used, this study well illustrates the interest of designing hybrid approaches exploiting the strengths of different methods.
MACHO observations of LMC red giants: Mira and semi-regular pulsators, and contact and semi-detached binaries

The MACHO data base has been used to examine light curves of all red giant stars brighter than Mbol rv -2 in a 0.5 0 x0.5 0 area of the LMC bar. Periods, often multiple, have been searched for in all stars found to be variable. Five distinct period-luminosity sequences have been found on the low mass (M ~ 2.25M0 ) giant branch. Comparison of observed periods, luminosities and period ratios with theoretical models identifies Miras unambiguously as radial fundamental mode pulsators, while semi-regular variables can be pulsating in the 1st, 2nd or 3rd overtone, or even the fundamental. All these variables lie on just 3 of the 5 distinct sequences, and they all appear to be on the AGB. The fourth sequence contains red giants on the first giant branch (FGB) or at the red end of the core-helium burning loops of intermediate mass stars (M ~ 2.25M0 ) . The light curves of these stars strongly suggest that they are contact binaries, and they make up rvO.5% of stars within 1 mag. of the FGB tip. Stars on the fifth sequence show semiregular, eclipse-like light curves. The light curves and periods of these stars suggest that they are in semi-detached binaries, transfering mass to an invisible companion via a stellar wind or Roche lobe overflow. They make up rv25% of AGB stars. If the existence of these red giant contact and semi-detached binaries is confirmed, then extant theories of binary star evolution will require substantial modification. IMount Stromlo and Siding Spring Observatories, Australian National University. 2Center for Particle Astrophysics, University of California, Berkeley. 3Supercomputing Facility, Australian National University. 4Department of Physics, University of California, Davis. 5Lawrence Livermore National Laboratory. 6Departments of Astronomy and Physics, University of Washington. 7Department of Physics, University of Notre Dame. 8Department of Physics, University of California, San Diego. 9Department of Physics, University of Sheffield. lODepartamento de Astronomia, P. Universidad Cat6lica, Santiago. 11 Center for Space Research, MIT. 12European Southern Observatory. 13Department of Physics, University of Oxford. 14Department of Physics and Astronomy, McMaster University.
The cortical component of experience-dependent synaptic plasticity in the rat barrel cortex

Rats were raised with altered tactile experience from P0 by removing all but one vibrissa (D1) from one side of the face (D1-spared animals). This procedure (univibrissa rearing) has previously been shown to cause neurons in cortical barrels surrounding D1 to develop greater than normal responses to D1 vibrissa stimulation and smaller than normal responses to principal vibrissa stimulation (Fox, 1992). In this study, it was found that the potentiated D1 responses could be attenuated by acute microlesions placed in the D1 barrel, while principal vibrissa responses were unchanged or even slightly elevated for the same cases. The ratio of the average D1 to principal vibrissa response was approximately proportional to the volume of tissue damaged in the D1 barrel. This result implies that the synaptic plasticity seen in cortex of D1-spared animals is due to synaptic changes that take place within the barrel cortex rather than to relay of changes occurring at a subcortical level. In addition, lesions aimed at the septum between D1 and an adjacent barrel almost completely abolished responses to D1 stimulation in that barrel, including short-latency responses (5–10 msec). Only neurons severed horizontally from D1 were affected. Neurons that maintained a connection with the D1 barrel via a bridge of septal tissue preserved their usual elevated levels of response to D1 stimulation and their aberrant short-latency responses. This result implies that pathways radiating out from the D1 barrel/column, and connecting neurons in the D1 barrel to cells in surrounding barrels, undergo synaptic plasticity induced by univibrissa rearing.
Confidential 1 Simplified Automated Material Handling System : Magnetic Wheels based Overhead Transportation Concept

Automation in various forms constitutes the backbone of most major industries. An increase in production volume, product variety and manufacturing process complexity necessitates automation to ensure consistency and profitable production. Automated material handling becomes a crucial aspect of factory automation because it frees up manual labor, streamlines the flow of material, allows for complexity management, reduces work in progress (WIP) and improves the utilization of expensive equipment. Existing material handling solutions typically cater to specific industries and can also be exorbitantly expensive. There is an emerging need for affordable automated material handling in smaller industries, and in hitherto unconventional settings like homes, offices and hospitals. The keys for an automation technology that can meet the widespread demands of such varied customers are simplicity, flexibility and integrability. With this in mind, we present a very simple yet versatile material transportation concept. We propose an overhead ceiling-based trackless transportation system that uses vehicles with magnetic wheels. The concept is developed following the principles of deterministic mechatronic design. Due to its inherent simplicity and judging from its extremely wide applicability, we propose an 'open hardware' environment so that the concept can be developed in a manner similar to the Linux Operating System. Introduction and Background Automation is becoming a growing need across various industries. It has assumed significant levels to meet the trends of everincreasing production volume and product variety. At the same time, products have become more and more sophisticated and hence demand complex and multiple-stage manufacturing processes. Added to these challenges is the pressing need to maintain high profitability, which in turn requires high yields, lower lead times and improved equipment utilization. In such a scenario, automated material transportation becomes a crucial aspect of factory automation because it frees up manual labor, streamlines the production processes, allows for complexity management, reduces inventory and improves the payback on expensive equipment before they become obsolete. Manual operations can go only so far, beyond which it becomes impossible to make any further improvements in the productivity and profits. Furthermore, ergonomic as well as labor considerations limit the indiscriminate use of manual force. Consequently, as they grow in size many industries tend to seek simple and efficient material handling (MH) solutions. 1 Professor of Mechanical Engineering, Precision Engineering Research Group, Massachusetts Institute of Technology 2 Doctoral Candidate, Precision Engineering Research Group, Massachusetts Institute of Technology