Miracle-dz/UniFAR-FTUs huggingface dataset:
Supporting Online Material Materials and Methods Figs. S1 to S3 Tables S1 and S2 References Movie S1 the Structure of the Ribosome with Elongation Factor G Trapped in the Posttranslocational State

V.R. holds stock options and is on the Scientific Advisory Board of Rib-X Pharmaceuticals, a company dedicated to making antibiotics that target the ribosome. The structure has been deposited at the Protein Data Bank with accession codes 2WRN, 2WRO, 2WRQ, and 2WRR. Elongation factor G (EF-G) is a guanosine triphosphatase (GTPase) that plays a crucial role in the translocation of transfer RNAs (tRNAs) and messenger RNA (mRNA) during translation by the ribosome. We report a crystal structure refined to 3.6 angstrom resolution of the ribosome trapped with EF-G in the posttranslocational state using the antibiotic fusidic acid. Fusidic acid traps EF-G in a conformation intermediate between the guanosine triphosphate and guanosine diphosphate forms. The interaction of EF-G with ribosomal elements implicated in stimulating catalysis, such as the L10-L12 stalk and the L11 region, and of domain IV of EF-G with the tRNA at the peptidyl-tRNA binding site (P site) and with mRNA shed light on the role of these elements in EF-G function. The stabilization of the mobile stalks of the ribosome also results in a more complete description of its structure. T he ribosome is the large molecular machine that uses an mRNA template to synthesize proteins, in a process referred to as translation. Ribosomes from all species consist of a large and a small subunit, which are termed 50S and 30S subunits in bacteria and consist of roughly two-thirds RNA and one-third protein. The last decade has seen a revolutionary change in our understanding of translation, largely as a result of the determination of high-resolution structures of the ribosomal subunits, as well as, more recently, the entire ribosome (1). Protein factors play crucial roles in all stages of translation, which can be divided roughly into initiation, elongation, and termination. The hy-drolysis of guanosine 5′-triphosphate (GTP) by factors is required in all three stages of translation. At the heart of translation is the elongation cycle, which consists of sequential addition of amino acids to the growing polypeptide chain directed by the mRNA codons. This process is cat-alyzed by two guanosine triphosphatase (GTPase) factors, elongation factors Tu (EF-Tu) and G (EF-G). At the beginning of the cycle, a nascent peptide chain linked to a tRNA is bound in the peptidyl-tRNA binding site (P site) of the ribosome, whereas the A site remains empty. The incoming aminoacyl-tRNA is delivered to the aminoacyl-tRNA site (A site) of the ribosome as a ternary …
Ischemic stroke subtypes : a population-based study of functional outcome, survival, and recurrence.

BACKGROUND AND PURPOSE There is scant population-based information on functional outcome, survival, and recurrence for ischemic stroke subtypes. METHODS We identified all residents of Rochester, Minnesota, with a first ischemic stroke from 1985 through 1989 using the resources of the Rochester Epidemiology Project medical records linkage system. After reviewing medical records and imaging studies, we assigned patients to 4 major ischemic stroke categories based on National Institute of Neurological Diseases and Stroke Data Bank criteria: large-vessel cervical or intracranial atherosclerosis with stenosis (ATH, n=74), cardioembolic (CE, n=132), lacunar (LAC, n=72), and infarct of uncertain cause (IUC, n=164). We used the Rankin disability score to assess functional outcome and the Kaplan-Meier product-limit method and Cox proportional hazards regression analysis with bootstrap validation to estimate rates and identify predictors of survival and recurrent stroke among these patients. RESULTS Rankin disabilities were different across stroke subtypes at the time of stroke and 3 months and 1 year later (P=0.001). LAC was associated with milder deficits compared with other subtypes. Mean follow-up among the 442 patients in the cohort was 3.2 years. Estimated rates of recurrent stroke at 30 days were significantly different (P<0.001): ATH, 18.5% (95% CI 9.4% to 27.5%); CE, 5.3% (95% CI 1.2% to 9.6%); LAC, 1.4% (95% CI 0.0% to 4.1%); and IUC, 3. 3% (95% CI 0.4% to 6.2%). After adjusting for age, sex, and stroke severity, infarct subtype was an independent determinant of recurrent stroke within 30 days (P=0.0006; eg, risk ratio for ATH compared with CE=3.3, 95% CI 1.2 to 9.3) but not long term (P=0.07). Four of 25 recurrent strokes within 30 days were procedure-related, each in patients with ATH. Five-year death rates were significantly different (P<0.001): ATH, 32.2% (95% CI 21.1% to 43.2%); CE, 80.4% (95% CI 73.1% to 87.6%); LAC, 35.1% (95% CI 23.6% to 46.0%); and IUC, 48.6% (95% CI 40.5% to 56.7%). With adjustment for age, sex, cardiac comorbidity, and stroke severity, the subtype of ischemic stroke was an independent determinant of long-term (P=0.018; eg, risk ratio for ATH compared with cardioembolic=0.47, 95% CI 0.29 to 0.77) but not 30-day survival (P=0.2). CONCLUSIONS Early recurrence rates for ischemic stroke caused by ATH are higher than those for other subtypes and higher than previous non-population-based studies have reported. Some of the increased risk of early recurrence among patients with ATH may be iatrogenic. Patients with LAC have better poststroke functional status than those with other subtypes. Survival is poorest among those with ischemic stroke with a cardiac source of embolism.
The detection of faulty code violating implicit coding rules

In the field of legacy software maintenance, there unexpectedly arises a large number of implicit coding rules, which we regard as a cancer in software evolution. Since such rules are usually undocumented and each of them is recognized only by a few members in a maintenance team, a person who is not aware of a rule often violates it while doing various maintenance activities such as adding a new functionality or repairing faults. The problem here is not only such a violation introduces a new fault but also the same kind of fault will be generated again and again in the future by different maintainers. This paper proposes a method for detecting code fragments that violate implicit coding rules. In the method, an expert maintainer, firstly, investigates the cause of each failure, described in the past failure reports, and identifies all the implicit coding rules that lie behind the faults. Then, the code patterns violating the rules (which we call "faulty code patterns") are described in a pattern description language. Finally, the potential faulty code fragments are automatically detected by a pattern matching technique. The result of a case study with large legacy software showed that 32.7% of the failures, which have been reported during a maintenance process, were due to the violation of implicit coding rules. Moreover, 152 faults existed in 772 code fragments detected by the prototype matching system, while 111 of them were not reported.
Quelles stratégies pour gérer les asymétries d’interdépendance ?

S’appuyant sur la theorie de la dependance des ressources, cet article analyse les asymetries d’interdependance au sein des relations dyadiques verticales. L’objectif est d’identifier les strategies permettant aux PME de gerer les asymetries de pouvoir et de dependance. Les resultats, bases sur l’analyse qualitative de quatre relations d’interdependance symbiotique entre studio et editeur de jeu video, montrent que les asymetries peuvent etre maitrisees par la mise en place de strategie de cooperation horizontale ou d’integration de ressources et competences verticales.
Jinja: Towards a Comprehensive Formal Semantics for a Java-like Language

Jinja is a Java-like programming language with a formal semantics designed to exhibit core features of Java. It is a compromise between realism of the language and tractability and clarity of the formal semantics. A big and a small step operational semantics are defined and shown equivalent. A type system and a definite initialization analysis are defined and type safety of the small step semantics is shown. The whole development has been carried out in the theorem prover Isabelle/HOL.
Group Decision-Making Model With Incomplete Fuzzy Preference Relations Based on Additive Consistency

In decision-making problems there may be cases in which experts do not have an in-depth knowledge of the problem to be solved. In such cases, experts may not put their opinion forward about certain aspects of the problem, and as a result they may present incomplete preferences, i.e., some preference values may not be given or may be missing. In this paper, we present a new model for group decision making in which experts' preferences can be expressed as incomplete fuzzy preference relations. As part of this decision model, we propose an iterative procedure to estimate the missing information in an expert's incomplete fuzzy preference relation. This procedure is guided by the additive-consistency (AC) property and only uses the preference values the expert provides. The AC property is also used to measure the level of consistency of the information provided by the experts and also to propose a new induced ordered weighted averaging (IOWA) operator, the AC-IOWA operator, which permits the aggregation of the experts' preferences in such a way that more importance is given to the most consistent ones. Finally, the selection of the solution set of alternatives according to the fuzzy majority of the experts is based on two quantifier-guided choice degrees: the dominance and the nondominance degree
Modeling the self-organization of directional selectivity in the primary visual cortex

A model is proposed to demonstrate how neurons in the primary visual cortex could self-organize to represent the direction of motion. The model is based on a temporal extension of the self-organizing map where neurons act as leaky integrators. The map is trained with moving Gaussian inputs, and it develops a retinotopic map with orientation columns that divide into areas of opposite direction selectivity, as found in the visual cortex.
Budget Planning for Coupled Campaigns in Sponsored Search Auctions

Budget-related decisions in sponsored search auctions are recognized as a structured decision problem rather than a simple constraint. Budget planning over several coupled campaigns (e.g., substitution and complementarity) remains a challenging but important task for advertisers. In this paper, we propose a dynamic multicampaign budget planning approach using optimal control techniques, with consideration of the substitution relationship between advertising campaigns. A three-dimensional measure of substitution relationships between campaigns is presented, namely, the overlapping degree in terms of campaign contents, promotional periods, and target regions. We also study some desirable properties and possible solutions to our budget model. Computational simulations and experiments are conducted to evaluate our model using real-world data from practical campaigns in sponsored search auctions. Experimental results show that (1) our approach outperforms the baseline strategy that is commonly used in practice; (2) coupled campaigns with a higher overlapping degree in between reduce the optimal total budget level, then reduce the optimal payoff, and reach the budgeting cap earlier than those with a less overlapping degree; and (3) the advertising effort can be seriously weakened by ignoring the degree of overlapping between campaigns.
Hallway monitoring with sensor networks

We present a sensor network that monitors a hallway. It consists of 180 load sensors connected to 30 wireless sensor nodes, where the setup is of extremely low cost and easily transferred to other settings. Our network serves as a testbed for in-network data processing algorithms, for which it is highly suitable due to the many correlated sensors.
Robust Visualization for Web-based Control of Mobile Robots

The World Wide Web provides a unique opportunity to connect robots to the Internet. Easy to use Web interfaces enable people all over the world to control mobile robots and to monitor their operation from the distance. Additionally, connecting a robot to the Internet offers distributed research groups the opportunity to perform joint experiments. In this context visualizing the robot’s actions plays a key role. In this paper we present different techniques designed to provide robust visualizations of Web-controlled mobile robots in dynamic environments. These techniques address two major drawbacks of the Internet, the limited bandwidth and the unreliability of connections resulting in packet loss. Our technique uses a 3Dmodel of the environment and visualizes the robot s actions using this model. It employs predictive simulation to bridge transmission gaps and applies probabilistic techniques to estimate the state of dynamic objects which influence the behavior of the robot. This way accurate visualizations of the actions of a mobile robot and of relevant aspects of its environment can be achieved.
Acyl-Homoserine Lactone Production in Nitrifying Bacteria of the Genera Nitrosospira, Nitrobacter, and Nitrospira Identified via a Survey of Putative Quorum-Sensing Genes

ABSTRACT The genomes of many bacteria that participate in nitrogen cycling through the process of nitrification contain putative genes associated with acyl-homoserine lactone (AHL) quorum sensing (QS). AHL QS or bacterial cell-cell signaling is a method of bacterial communication and gene regulation and may be involved in nitrogen oxide fluxes or other important phenotypes in nitrifying bacteria. Here, we carried out a broad survey of AHL production in nitrifying bacteria in three steps. First, we analyzed the evolutionary history of AHL synthase and AHL receptor homologs in sequenced genomes and metagenomes of nitrifying bacteria to identify AHL synthase homologs in ammonia-oxidizing bacteria (AOB) of the genus Nitrosospira and nitrite-oxidizing bacteria (NOB) of the genera Nitrococcus, Nitrobacter, and Nitrospira. Next, we screened cultures of both AOB and NOB with uncharacterized AHL synthase genes and AHL synthase-negative nitrifiers by a bioassay. Our results suggest that an AHL synthase gene is required for, but does not guarantee, cell density-dependent AHL production under the conditions tested. Finally, we utilized mass spectrometry to identify the AHLs produced by the AOB Nitrosospira multiformis and Nitrosospira briensis and the NOB Nitrobacter vulgaris and Nitrospira moscoviensis as N-decanoyl-l-homoserine lactone (C10-HSL), N-3-hydroxy-tetradecanoyl-l-homoserine lactone (3-OH-C14-HSL), a monounsaturated AHL (C10:1-HSL), and N-octanoyl-l-homoserine lactone (C8-HSL), respectively. Our survey expands the list of AHL-producing nitrifiers to include a representative of Nitrospira lineage II and suggests that AHL production is widespread in nitrifying bacteria. IMPORTANCE Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite by nitrifying microorganisms, plays an important role in environmental nitrogen cycling from agricultural fertilization to wastewater treatment. The genomes of many nitrifying bacteria contain genes associated with bacterial cell-cell signaling or quorum sensing (QS). QS is a method of bacterial communication and gene regulation that is well studied in bacterial pathogens, but less is known about QS in environmental systems. Our previous work suggested that QS might be involved in the regulation of nitrogen oxide gas production during nitrite metabolism. This study characterized putative QS signals produced by different genera and species of nitrifiers. Our work lays the foundation for future experiments investigating communication between nitrifying bacteria, the purpose of QS in these microorganisms, and the manipulation of QS during nitrification.
WAP: Models and metrics for the assessment of critical-infrastructure-targeted malware campaigns

Ensuring system survivability in the wake of advanced persistent threats is a big challenge that the security community is facing to ensure critical infrastructure protection. In this paper, we define metrics and models for the assessment of coordinated massive malware campaigns targeting critical infrastructure sectors. First, we develop an analytical model that allows us to capture the effect of neighborhood on different metrics (infection probability and contagion probability). Then, we assess the impact of putting operational but possibly infected nodes into quarantine. Finally, we study the implications of scanning nodes for early detection of malware (e.g., worms), accounting for false positives and false negatives. Evaluating our methodology using a small four-node topology, we find that malware infections can be effectively contained by using quarantine and appropriate rates of scanning for soft impacts.
Predictive Threat Assessment via Reachability Analysis and Set Invariance Theory

We propose two model-based threat assessment methods for semi-autonomous vehicles, i.e., human-driven vehicles with autonomous driving capabilities. Based on information about the surrounding environment, we introduce a set of constraints on the vehicle states, which are satisfied under “safe” driving conditions. Then, we formulate the threat assessment problem as a constraint satisfaction problem. Vehicle and driver mathematical models are used to predict future constraint violation, indicating the possibility of accident or loss of vehicle control, hence, the need to assist the driver. The two proposed methods differ in the models used to predict vehicle motion within the surrounding environment. We demonstrate the proposed methods in a roadway departure application and validate them through experimental data.
Power-efficient ASIC synthesis of cryptographic sboxes

In this paper we present a novel methodology that can be used to design efficient hardware structures for a certain class of combinatorial functions. The methodology is primarily intended to achieve low-power synthesis of non-linear one-to-one functions on ASIC technology libraries and fits well for the synthesis of small cryptographic substitution box (Sbox) functional components; the latter are found in most secret key cryptographic algorithms, and usually represent their most relevant part in terms of required computational power. We also describe an extension that allows us to apply the method to general vectorial Boolean functions.
Alltagswissen über soziale Probleme

Zusammenfassung Hauptziele der Untersuchung sind eine dimensionale und kausale Analyse alltagstheoretischer Konzepte über Drogen-, Alkohol-, Kriminalitäts- und Jugendprobleme. Die Studie, welche 1984/85 in drei Gemeinden der Innerschweiz bei 576 Befragten durchgeführt wurde, knüpft an konkrete öffentliche Auseinandersetzungen um therapeutische Drogenwohngemeinschaften an, um so der postulierten grundlegenden Praxis-/Situationsorientierung von Laientheorien gerecht zu werden. Als Analyseinstrument kommt die computerunterstützte Inhaltsanalyse zum Einsatz. Die Ergebnisse weisen darauf hin, daß ein komplexes Wissen über soziale Probleme besteht, welches gleichzeitig durchgängig normativ besetzt ist und zum einen durch Schichtzugehörigkeit, zum anderen vor allem aber über die Vermittlung von Problemwissen durch relevante Bezugsgruppen beeinflußt wird. Konsequenzen für praktische Präventionspolitik ergeben sich vor allem hinsichtlich der Notwendigkeit, Botschaften an der „Logik“ der Adressaten auszurichten, Zielgruppen aufgrund der identifizierten strukturellen Bedingungen zu definieren und den Multiplikatoreffekt glaubwürdiger, informeller Bezugsgruppen auszunutzen.
HIGH-GAIN CMOS LOW NOISE AMPLIFIER FOR ULTRA WIDE-BAND WIRELESS RECEIVER

A 3-5 GHz broadband CMOS single-ended LNA with a new theoretical approach based on least-square algorithm is presented in this paper. The design consists of a wideband input impedance matching network, a cascoded amplifier with inductively-degenerated LNA, and an output impedance matching network. It is simulated in TSMC 0. 18µm standard RF CMOS process. The optimum matching network is designed to minimize the noise figure (NF) and maximize the power gain. The elements values of optimum matching network have been obtained using the least-square algorithm. The proposed LNA exhibits a gain in range of 19.9-18.9 dB, over the UWB low-band (3 to 5 GHz). Moreover, the noise figure is obtained in range of 0.6- 0.8 dB. Besides, the input P1-dB and IIP3 are −10.5 dBm and 18 dBm, respectively. The proposed method has minimum 4 dB power gain improvement in relative to similar works with constant noise figure. Also, the DC supply is considered to be 1.8 V.
Recent advances in efficient decoding combining on-line transducer composition and smoothed language model incorporation

This paper presents and evaluates our recent efforts on efficient decoding for Large Vocabulary Continuous Speech Recognition in the framework of Weighted Finite State Transducers. We evaluate on-the-fly transducer composition for reduced memory consumption combined with weight smearing for a more time-synchronous language model incorporation. It turns out that in the on-line composition mode weight smoothing within the static part of the network is even more beneficial on run-time to accuracy ratio than in the fully precompiled case. Evaluations are carried out on a state-of-the-art recognition system of 10k words, cross-word triphone acoustic models and trigram language model. In this scenario, the Viterbi-search is carried out fully time-synchronously in only a single pass. The combination of on-the-fly network composition with only the unigram part of the language model smoothly compiled into the network achieves a remarkably good run-time to accuracy ratio with only moderate memory requirements.
Reinforcement Learning for RARS

This paper presents the results of reinforcement learning experiments for the Robot Auto Racing Simulator (RARS). We compare three different drivers, each taking a different approach to function approximation and reinforcement learning in this continuous-action problem. We report moderate success learning optimal paths around an oval track with simple learners, and we discuss difficulties encountered by more complex learners.
Lysine demethylase KDM4A associates with translation machinery and regulates protein synthesis.

UNLABELLED Chromatin-modifying enzymes are predominantly nuclear; however, these factors are also localized to the cytoplasm, and very little is known about their role in this compartment. In this report, we reveal a non-chromatin-linked role for the lysine-specific demethylase KDM4A. We demonstrate that KDM4A interacts with the translation initiation complex and affects the distribution of translation initiation factors within polysome fractions. Furthermore, KDM4A depletion reduced protein synthesis and enhanced the protein synthesis suppression observed with mTOR inhibitors, which paralleled an increased sensitivity to these drugs. Finally, we demonstrate that JIB-04, a JmjC demethylase inhibitor, suppresses translation initiation and enhances mTOR inhibitor sensitivity. These data highlight an unexpected cytoplasmic role for KDM4A in regulating protein synthesis and suggest novel potential therapeutic applications for this class of enzyme. SIGNIFICANCE This report documents an unexpected cytoplasmic role for the lysine demethylase KDM4A. We demonstrate that KDM4A interacts with the translation initiation machinery, regulates protein synthesis and, upon coinhibition with mTOR inhibitors, enhances the translation suppression and cell sensitivity to these therapeutics.