Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-resolved structural studies with serial crystallography: A new light on retinal proteins

Structural information of the different conformational states of the two prototypical light-sensitive membrane proteins, bacteriorhodopsin and rhodopsin, has been obtained in the past by X-ray cryo-crystallography and cryo-electron microscopy. However, these methods do not allow for the structure determination of most intermediate conformations. Recently, the potential of X-Ray Free Electron Lasers (X-FELs) for tracking the dynamics of light-triggered processes by pump-probe serial femtosecond crystallography has been demonstrated using 3D-micron-sized crystals. In addition, X-FELs provide new opportunities for protein 2D-crystal diffraction, which would allow to observe the course of conformational changes of membrane proteins in a close-to-physiological lipid bilayer environment. Here, we describe the strategies towards structural dynamic studies of retinal proteins at room temperature, using injector or fixed-target based serial femtosecond crystallography at X-FELs. Thanks to recent progress especially in sample delivery methods, serial crystallography is now also feasible at synchrotron X-ray sources, thus expanding the possibilities for time-resolved structure determination.
The Multivariable Parabola Criterion for Robust Controller Synthesis: A Riccati Equation Approach

In 1967 Bergen and Sapiro derived an absolute (frequency domain) stability criterion that unifies the classical circle and Popov criteria. A slightly weaker version of this combined criterion has a graphical interpretation in the Popov (rather than Nyquist) plane in terms of a parabola. Our goal in this paper is to reformulate and generalize the parabola criterion in terms of Riccati equations. Besides providing a multivariable extension, this formulation clarifies connections to state space bounded real and positive real theory and provides the basis for robust controller synthesis.
SVM Based Gender Classification Using Iris Images

These days biometric authentication systems based on human characteristics such as face, finger, voice and iris are becoming popular among researchers. These systems identify an individual as an authentic or an imposter using a database of enrolled individuals. These systems do not provide other information about imposter such as her gender or ethnicity. Various researchers have utilized facial images for gender classification. Iris images have also been used for identification but there exists a very few references reporting the identification of human attributes such as gender with the help of iris images. In this paper gender has been identified using iris images. Statistical features and texture features using wavelets have been extracted from iris images. A classification model based on Support Vector Machine (SVM) has been developed to classify gender and an accuracy of 83.06% has been achieved in this work.
SMAT: an input adaptive auto-tuner for sparse matrix-vector multiplication

Sparse Matrix Vector multiplication (SpMV) is an important kernel in both traditional high performance computing and emerging data-intensive applications. By far, SpMV libraries are optimized by either application-specific or architecture-specific approaches, making the libraries become too complicated to be used extensively in real applications. In this work we develop a Sparse Matrix-vector multiplication Auto-Tuning system (SMAT) to bridge the gap between specific optimizations and general-purpose usage. SMAT provides users with a unified programming interface in compressed sparse row (CSR) format and automatically determines the optimal format and implementation for any input sparse matrix at runtime. For this purpose, SMAT leverages a learning model, which is generated in an off-line stage by a machine learning method with a training set of more than 2000 matrices from the UF sparse matrix collection, to quickly predict the best combination of the matrix feature parameters. Our experiments show that SMAT achieves impressive performance of up to 51GFLOPS in single-precision and 37GFLOPS in double-precision on mainstream x86 multi-core processors, which are both more than 3 times faster than the Intel MKL library. We also demonstrate its adaptability in an algebraic multigrid solver from Hypre library with above 20% performance improvement reported.
Intelligible Language Modeling with Input Switched Affine Networks

The computational mechanisms by which nonlinear recurrent neural networks (RNNs) achieve their goals remains an open question. There exist many problem domains where intelligibility of the network model is crucial for deployment. Here we introduce a recurrent architecture composed of input-switched affine transformations, in other words an RNN without any nonlinearity and with one set of weights per input. We show that this architecture achieves near identical performance to traditional architectures on language modeling of Wikipedia text, for the same number of model parameters. It can obtain this performance with the potential for computational speedup compared to existing methods, by precomputing the composed affine transformations corresponding to longer input sequences. As our architecture is affine, we are able to understand the mechanisms by which it functions using linear methods. For example, we show how the network linearly combines contributions from the past to make predictions at the current time step. We show how representations for words can be combined in order to understand how context is transferred across word boundaries. Finally, we demonstrate how the system can be executed and analyzed in arbitrary bases to aid understanding.
Formulation and evaluation of topical herbal gel for the treatment of arthritis in animal model

The objective of the study is to formulate and evaluate a topical herbal gel containing Cardiospermum halicacabum and Vitex negundo leaf extracts for their anti-arthritic activity in rats. Twelve herbal gel formulations were prepared using 1.5% of gelling agents carbopol 934 (F1-F6) and carbopol 940 (F6-F12) and they were evaluated for physical appearance, net content, viscosity, extrudability, pH, spreadability, in vitro diffusion profile and primary skin irritation tests. The stability study for the topical herbal gel formulation was done as per ICH guidelines and anti-arthritic activity was evaluated by Freund's Complete Adjuvant (FCA) induced arthritis method. Assessment of body weight, paw volume, hematological and biochemical parameters, histopathological examination and In vitro determination of serum biomarkers were also carried out. Formulated gels were homogenous, stable and complied with the guidelines. Among the formulations, F4 showed better release (98.4 %) characteristics than other formulations. No erythema or edema was observed in the skin irritation test confirming the gel was non-toxic and safe. Topical application of the herbal gel F4 containing carbopol 934 displayed significant (p < 0.001) anti-arthritic activity compared to diseased rats. Reduction in paw volume, no agglutination in C - reactive protein and rheumatic factor, reduction in TNF level, regaining of normal hematological, and biochemical parameters, reduction in spleen and thymus weight and histopathological examination supported the anti-arthritic activity of the gel formulation.
Learning to Smell: Olfactory Perception from Neurobiology to Behavior

Written by a neurobiologist and a psychologist, this volume presents a new theory of olfactory perception. Drawing on research in neuroscience, physiology, and ethology, Donald A. Wilson and Richard J. Stevenson address the fundamental question of how we navigate through a world of chemical encounters and provide a compelling alternative to the "reception-centric" view of olfaction. The major research challenge in olfaction is determining how the brain discriminates one smell from another. Here, the authors hold that olfaction is generally not a simple physiochemical process, but rather a plastic process that is strongly tied to memory. They find the traditional approach-which involves identifying how particular features of a chemical stimulus are represented in the olfactory system-to be at odds with historical data and with a growing body of neurobiological and psychological evidence that places primary emphasis on synthetic processing and experiential factors. Wilson and Stevenson propose that experience and cortical plasticity not only are important for traditional associative olfactory memory but also play a critical, defining role in odor perception and that current views are insufficient to account for current and past data. The book includes a broad comparative overview of the structure and function of olfactory systems, an exploration into the mechanisms of odor detection and olfactory perception, and a discussion of the implications of the authors' theory. Learning to Smell will serve as an important reference for workers within the field of chemical senses and those interested in sensory processing and perception.
Skeletal Muscle Characterization of Japanese Quail Line Selectively Bred for Lower Body Weight as an Avian Model of Delayed Muscle Growth with Hypoplasia

This study was designed to extensively characterize the skeletal muscle development in the low weight (LW) quail selected from random bred control (RBC) Japanese quail in order to provide a new avian model of impaired and delayed growth in physically normal animals. The LW line had smaller embryo and body weights than the RBC line in all age groups (P<0.05). During 3 to 42 d post-hatch, the LW line exhibited approximately 60% smaller weight of pectoralis major muscle (PM), mainly resulting from lower fiber numbers compared to the RBC line (P<0.05). During early post-hatch period when myotubes are still actively forming, the LW line showed impaired PM growth with prolonged expression of Pax7 and lower expression levels of MyoD, Myf-5, and myogenin (P<0.05), likely leading to impairment of myogenic differentiation and consequently, reduced muscle fiber formation. Additionally, the LW line had delayed transition of neonatal to adult myosin heavy chain isoform, suggesting delayed muscle maturation. This is further supported by the finding that the LW line continued to grow unlike the RBC line; difference in the percentages of PMW to body weights between both quail lines diminished with increasing age from 42 to 75 d post-hatch. This delayed muscle growth in the LW line is accompanied by higher levels of myogenin expression at 42 d (P<0.05), higher percentage of centered nuclei at 42 d (P<0.01), and greater rate of increase in fiber size between 42 and 75 d post-hatch (P<0.001) compared to the RBC line. Analysis of physiological, morphological, and developmental parameters during muscle development of the LW quail line provided a well-characterized avian model for future identification of the responsible genes and for studying mechanisms of hypoplasia and delayed muscle growth.
The Future of Action Video Games in Psychological Research and Application

In recent years, much research has been conducted in order to understand the effects of action video games on mind and behavior. For example, it has been tried to investigate potential links between playing action video games and aggressive behavior (Anderson and Bushman, 2001; Ferguson, 2011), visual selective attention (Green and Bavelier, 2003) or gender differences in spatial cognition (Feng et al., 2007). What we see is that playing certain types of video games in the right doses might enhance several cognitive skills. This can be used in the long run to help those with deficits in these areas, for example the elderly. This article shall emphasize the importance of a holistic and unbiased view in regards to the impact of video games and their possible use. Therefore, it is essential that we desist from antiquated concepts of “typical gamers,” understand the advantages and disadvantages of playing action video games and try to step up efforts in application-oriented research. From our understanding, any physically challenging video game in which reaction time plays a crucial role can be described as an action video game. While there is no generally accepted definition, others define action video games as characterized by the use of violence within these games.
Evolution of Broad Spectrum β-Lactam Resistance in an Engineered Metallo-β-lactamase*

Background: Microbial multidrug resistance is a major global problem. Results: Evolution of enhanced β-lactamase activity in engineered metalloenzyme mutants was demonstrated with seven different β-lactam antibiotics and cross-resistance to alternative antibiotics was observed. Conclusion: Resistance against a single antibiotic can develop with collateral resistance to additional drugs. Significance: Cataloging the substrate specificity of enzyme variants could lead to a more tailored use of antibiotics in clinical settings. The extensive use and misuse of antibiotics during the last seven decades has led to the evolution and global spread of a variety of resistance mechanisms in bacteria. Of high medical importance are β-lactamases, a group of enzymes inactivating β-lactam antibiotics. Metallo-β-lactamases (MBLs) are particularly problematic because of their ability to act on virtually all classes of β-lactam antibiotics. An engineered MBL (evMBL9) characterized by low level activity with several β-lactam antibiotics was constructed and employed as a parental MBL in an experiment to examine how an enzyme can evolve toward increased activity with a variety of β-lactam antibiotics. We designed and synthesized a mutant library in which the substrate activity profile was varied by randomizing six active site amino acid residues. The library was expressed in Salmonella typhimurium, clones with increased resistance against seven different β-lactam antibiotics (penicillin G, ampicillin, cephalothin, cefaclor, cefuroxime, cefoperazone, and cefotaxime) were isolated, and the MBL variants were characterized. For the majority of the mutants, bacterial resistance was significantly increased despite marked reductions in both mRNA and protein levels relative to those of parental evMBL9, indicating that the catalytic activities of these mutant MBLs were highly increased. Multivariate analysis showed that the majority of the mutant enzymes were generalists, conferring increased resistance against most of the examined β-lactams.
Foundations of Intelligent Additive Manufacturing

During the last decade, additive manufacturing has become increasingly popular for rapid prototyping, but has remained relatively marginal beyond the scope of prototyping when it comes to applications with tight tolerance specifications, such as in aerospace. Despite a strong desire to supplant many aerospace structures with printed builds, additive manufacturing has largely remained limited to prototyping, tooling, fixtures, and non-critical components. There are numerous fundamental challenges inherent to additive processing to be addressed before this promise is realized. One ubiquitous challenge across all AM motifs is to develop processing-property relationships through precise, in situ monitoring coupled with formal methods and feedback control. We suggest a significant component of this vision is a set of semantic layers within 3D printing files relevant to the desired material specifications. This semantic layer provides the feedback laws of the control system, which then evaluates the component during processing and intelligently evolves the build parameters within boundaries defined by semantic specifications. This evaluation and correction loop requires on-the-fly coupling of finite element analysis and topology optimization. The required parameters for this analysis are all extracted from the semantic layer and can be modified in situ to satisfy the global specifications. Therefore, the representation of what is printed changes during the printing process to compensate for eventual imprecision or drift arising during the manufacturing process.
A Workflow Scheduling Technique Using Genetic Algorithm in Spot Instance-Based Cloud

Cloud computing is a computing paradigm in which users can rent computing resources from service providers according to their requirements. A spot instance in cloud computing helps a user to obtain resources at a lower cost. However, a crucial weakness of spot instances is that the resources can be unreliable anytime due to the fluctuation of instance prices, resulting in increasing the failure time of users’ job. In this paper, we propose a Genetic Algorithm (GA)-based workflow scheduling scheme that can find the optimal task size of each instance in a spot instance-based cloud computing environment without increasing users’ budgets. Our scheme reduces total task execution time even if an out-of-bid situation occurs in an instance. The simulation results, based on a before-and-after GA comparison, reveal that our scheme achieves performance improvements in terms of reducing the task execution time on average by 7.06%. Additionally, the cost in our scheme is similar to that when GA is not applied. Therefore, our scheme can achieve better performance than the existing scheme, by optimizing the task size allocated to each available instance throughout the evolutionary process of GA.
Influential Relationships Questionnaire: Data from a Nonclinical Population

The Influential Relationships Questionnaire, a state measure of the perceived characteristics of care, overprotection, and criticism of significant others, was administered to 99 staff of a provincial psychiatric hospital. The relationship of scores to sex, marital status, and amount of weekly contact with two most influential people was examined. Analysis indicated that scores are independent of sex, marital status, and amount of weekly contact for the most influential person. The implication of normative data in relation to perceived attitudes and psychopathology is discussed.
Subband-based Drum Transcription for Audio Signals

Content-based analysis of music can help manage the increasing amounts of music information available digitally and is becoming an important part of multimedia research. The use of drums and percussive sounds is pervasive to popular and world music. In this paper we describe an automatic system for detecting and transcribing low and medium-high frequency drum events from audio signals. Two different subband front-ends are utilized. The first is based on bandpass filters and the second is based on wavelet analysis. Experimental results utilizing music, drum loops and Indian tabla thekas as signals are provided. The proposed system can be used as a preprocessing step for rhythm-based music classification and retrieval. In addition it can be used for pedagogical purposes
Security issues in online games

The traditional target of computer game security is mainly copy protection. The emergence of online games fundamentally changes the security requirements for computer games. Although computer game development often utilizes cutting edge technology in computer graphics, artificial intelligence, human computer interaction and programming, game providers (developers or operators) do not pay much attention to security techniques. In this paper, we look into security failures that have happened or might happen in online games, and discuss some key security issues that have to concern online game providers. Specifically, we look into various kinds of online cheating, and introduce security techniques to deal with cheating prevention, though meanwhile other security issues are also discussed.
(Small) Enterpreneurs first!: Analysis of the economic discourse of the Vlaams Belang

A large body of research on political parties is devoted to the family of extreme rightparties. Yet, systematic analyses of extreme right parties discourse remain scarce. Thepresent study addresses this gap in the literature by providing a discourse analysis of the VlaamsBelang, one of the most successful extreme right-wing parties in Europe. Moreover, by focusing onthis partys economic discourse, the study also sheds new light on the ongoing debate aboutthe economic viewpoints of the new extreme right parties. We conclude that the VlaamsBelangs economic rhetoric is in line with its ethno-linguistic, nationalist standpoints andpleas for a Flemish economic policy. The partys economic programme is built on liberalpoints of view and seems particularly aimed at attracting (dissatisfied) liberal voters.Importantly, as economic issues remain subordinated to the partys ideological core, itappears that the Vlaams Belang has largely instrumentalised its programme to expand itselectorate.
What can free money tell us on the virtual black market?

"Real money trading" or "Gold farming" refers to a set of illicit practices for gathering and distributing virtual goods in online games for real money. Unlike previous work, we use network-wide economic interactions among in-game characters as a lens to monitor, detect and identify gold farming networks. Our work is based on a set of real in-game trade activity logs collected for one month in year 2010 from the world's second largest MMORPG called AION (with 3.4 million subscribers). This is the first work that empirically (i) shows that "free money network" is a promising measure/approximation for detecting and characterizing gold farming networks, and (ii) measures the size of the free money net and in-game virtual economy in a large-scale MMORPG in terms of the cash flow.
Melatonin interactions with blood pressure and vascular function during l‐NAME‐induced hypertension

Abstract: The mechanisms responsible for the antihypertensive effect of melatonin are not completely understood. To elucidate the possible role of the nitric oxide (NO) pathway in the hemodynamic actions of melatonin, the effects of this indolamine on vascular function during hypertension induced by the NO‐synthase (NOS) inhibitor, Nω‐nitro‐l‐arginine‐methyl ester (l‐NAME) were investigated. Four groups of male adult Wistar rats were employed: control, L‐NAME (40 mg/kg), melatonin (10 mg/kg) and l‐NAME + melatonin for 5 wks. Systolic and diastolic blood pressure were measured invasively in the carotid artery. Conjugated dienes concentration (an oxidative load marker), NOS RNA expression and its activity and RNA expression of cyclooxygenase‐(COX)‐1 and COX‐2 were determined in the aorta. Acetylcholine‐induced responses and their NO‐mediated component were evaluated in femoral and mesenteric artery. Moreover, endothelium‐derived constricting factor (EDCF)‐dependent vasoconstriction and inner diameter were determined in the femoral artery. Chronic l‐NAME treatment induced hypertension, elevated the oxidative load and inhibited NOS activity. Moreover, impaired NO‐dependent relaxation, augmented EDCF‐constriction, increased COX‐2 expression and reduced arterial inner diameter were observed. Melatonin added to l‐NAME treatment completely prevented elevation of the oxidative load in the aorta. However, melatonin was not able to prevent NOS activity decline, elevation of COX‐2 expression or the impairment of vascular responses (except moderate improvement in relaxation of small mesenteric arteries) and it exerted only slight antihypertensive effect. In conclusion, in addition to the reduction of the oxidative load, the restoration of the NO pathway seems to play an important role in the antihypertensive effect of melatonin.