Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dominant-Negative fur Mutation in Bradyrhizobium japonicum

ABSTRACT In many bacteria, the ferric uptake regulator (Fur) protein plays a central role in the regulation of iron uptake genes. Because iron figures prominently in the agriculturally important symbiosis between soybean and its nitrogen-fixing endosymbiont Bradyrhizobium japonicum, we wanted to assess the role of Fur in the interaction. We identified a fur mutant by selecting for manganese resistance. Manganese interacts with the Fur protein and represses iron uptake genes. In the presence of high levels of manganese, bacteria with a wild-type copy of the fur gene repress iron uptake systems and starve for iron, whereas fur mutants fail to repress iron uptake systems and survive. The B. japonicum fur mutant, as expected, fails to repress iron-regulated outer membrane proteins in the presence of iron. Unexpectedly, a wild-type copy of the fur gene cannot complement the fur mutant. Expression of the fur mutant allele in wild-type cells leads to a fur phenotype. Unlike a B. japonicum fur-null mutant, the strain carrying the dominant-negative fur mutation is unable to form functional, nitrogen-fixing nodules on soybean, mung bean, or cowpea, suggesting a role for a Fur-regulated protein or proteins in the symbiosis.
Investigation on dimensionality reduction of concatenated features with deep neural network for LVCSR systems

The hybrid model, context-dependent deep neural network hidden Markov models (CD-DNN-HMMs), has received significant improvements on various challenging large vocabulary continuous speech recognition (LVCSR) tasks just in these few years. Recently, it is further reported that gains of DNN are almost entirely attributed to using features concatenated from consecutive speech frames as DNN's inputs. This result indicates that DNN has the excellent ability of well mining the high-dimensional features. But for GMM, we must resort to dimensionality reduction techniques to avoid the “curse of high-dimensionality”. In this paper, we attempt to derive compact and informative low-dimensional representations from concatenated features for GMM. Most simply, PCA is first considered about, but it doesn't work well in this situation. Then, we focus on investigating DNN-based bottleneck features. The experiments on a Mandarin LVCSR task and the Switchboard task both show that the recognition performance of GMM-HMMs trained with bottleneck features (BN-GMM-HMMs) can be comparable to that of CD-DNN-HMMs. Moreover, when discriminative training is leveraged, surprisingly it is observed that BN-GMM-HMMs provides nearly 8% relative error reductions over CD-DNN-HMMs on the Mandarin LVCSR task.
A Virtualization-Based Cloud Infrastructure for IMS Core Network

IP Multimedia Subsystem (IMS) has been accepted as the core control platform by 3GPP. It has been recognized as the vision beyond GSM for the Next Generation Network (NGN). The IMS framework delivers IP multimedia to mobile users through Session Initiation Protocol (SIP) and supports heterogeneous networks access. In this paper, we propose a virtualization-based cloud platform for the IMS core network, with a novel load-balance and disaster recovery policy. Experimental results indicate that the proposed mechanism improves system performance by dynamic allocating resources according to current load. The proposed cloud infrastructure is able to recover from a disaster in seconds by using live migration of virtual machines.
Ethylene is involved in strawberry fruit ripening in an organ-specific manner

The fruit of the strawberry Fragaria×ananassa has traditionally been classified as non-climacteric because its ripening process is not governed by ethylene. However, previous studies have reported the timely endogenous production of minor amounts of ethylene by the fruit as well as the differential expression of genes of the ethylene synthesis, reception, and signalling pathways during fruit development. Mining of the Fragaria vesca genome allowed for the identification of the two main ethylene biosynthetic genes, 1-aminocyclopropane-1-carboxylic acid (ACC) synthase and ACC oxidase. Their expression pattern during fruit ripening was found to be stage and organ (achene or receptacle) specific. Strawberry plants with altered sensitivity to ethylene could be employed to unravel the role of ethylene in the ripening process of the strawberry fruit. To this end, independent lines of transgenic strawberry plants were generated that overexpress the Arabidopsis etr1-1 mutant ethylene receptor, which is a dominant negative allele, causing diminished sensitivity to ethylene. Genes involved in ethylene perception as well as in its related downstream processes, such as flavonoid biosynthesis, pectin metabolism, and volatile biosynthesis, were differently expressed in two transgenic tissues, the achene and the receptacle. The different transcriptional responsiveness of the achene and the receptacle to ethylene was also revealed by the metabolic profiling of the primary metabolites in these two organs. The free amino acid content was higher in the transgenic lines compared with the control in the mature achene, while glucose and fructose, and citric and malic acids were at lower levels. In the receptacle, the most conspicuous change in the transgenic lines was the depletion of the tricarboxylic acid cycle intermediates at the white stage of development, most probably as a consequence of diminished respiration. The results are discussed in the context of the importance of ethylene during strawberry fruit ripening.
Migration and Social Protection in China

Migration and Social Protection in China, edited by Ingrid Nielsen and Russell Smyth. Singapore: World Scientific, 2008. + 265 pp. US$69.00 (hardcover). This edited volume focuses on an important issue which the current financial crisis has made even more pressing. China's export of manufactured goods and the rebuilding of its cities have fueled its boom over the last three decades, and both have relied on massive inflows of rural migrants. In turn, the combination of the household registration system and reforms allowing mobility have produced a population living without any social safety net beyond the possibility of returning to their villages. As the editors and many of the chapter contributors stress, the resulting contradictions are problematic for the migrants themselves, for China's continued growth, and for the acceptability of China's exports in global markets. One aspect of the problem is the reduced flow of migrants to the booming coastal areas, producing a labor shortage in factories and construction sites, as discussed in David Kelly's chapter. Social protections such as unemployment insurance and pensions help factories to respond to accusations of sweatshopping and to retain workers. In addition, limits to continued growth based primarily on exports means that accumulation strategies will require greater emphasis on domestic consumption, as in the classic Fordist system. In the context of the current financial crunch, domestic consumption becomes even more crucial for maintaining growth and the social stability which many believe relies on growth rates of 8 per cent or above. Social insurance plays a central role in moving to a domestic growth strategy, because insecurity results in extremely high savings rates. As in the West, attempts to increase spending will probably be more effective if they target the poor, since the affluent are more likely to pay down debt or increase savings. This approach is consistent with the leadership's recent emphasis on a harmonious society, as the chapter by Gloria Davies and Scott Grant stresses. One of the book's strengths is that it delivers a wealth of quantitative data on the situation of migrants and their participation in various insurance schemes. The chapters by Lina Song and Simon Appleton, Dewen Wang, and Fei Guo and Wenshu Gao do a good job of exploring the very low rates of participation in different schemes and how these rates are influenced by gender, age, education and other demographic variables. …
Shape-based Discrimination and Classification of Cortical Surfaces

Advances in medical imaging technique make it possible to study shape variations of neuroanatomical structures in vivo, which has been proved useful in the study of neuropathology and neurodevelopment. In this paper, we propose the use of spherical wavelet transformation to extract shape features, as it can characterize the underlying functions in a local fashion in both space and frequency, in contrast to spherical harmonics that have a noncompact basis set. The extracted shape features can be used to statistically detect and visualize group shape differences from a coarse to fine resolution, and facilitate shape-based classification. A procedure is developed to apply this method to cortical surface models, and promising results are acquired on synthetic and real data
Nonextensive entropy and regularization for adaptive learning

A challenging situation gradient-based learning algorithms encounter is an occasional converge to undesired local minima. To alleviate this situation, this paper builds on the theory of nonextensive statistical mechanics to develop a new adaptive gradient-based learning scheme that applies a sign-based weight adjustment, inspired from the Rprop algorithm, on a perturbed version of the original error function. The perturbations are characterized by the q entropic index of the nonextensive entropy, and their impact is controlled by means of regularization. This approach modifies the error landscape at each iteration allowing the algorithm to explore previously unavailable regions of the error surface, and possibly escape undesired local minima. The performance of the adaptive scheme is empirically evaluated using problems from the UCI repository of machine learning databases and other classic benchmarks.
Passive and Active Kinesthetic Perception Just-noticeable-difference for Natural Frequency of Virtual Dynamic Systems

This paper investigates the just-noticeable-difference (JND) for natural frequency of virtual second order dynamic systems. Using a one degree-of-freedom haptic device, visual and/or haptic sensory feedback were presented during interactions with the system. Participants were instructed to either perceive passively or actively excite the system in order to discriminate natural frequencies. The JND for this virtual resonance task ranged from 3.99 % to 6.96 % for reference frequencies of 1 Hz and 2 Hz. Results show that sensory feedback has a significant effect on JND in passive perception, with combined visual and haptic feedback enabling the best discrimination performance. In active perception, there is no significant difference on JND with haptic and combined visual and haptic feedback. There is also no significant difference between active perception and passive perception for this JND experiment. The presentation of systems with equivalent natural frequencies but different spring stiffness resulted in no large bias toward larger stiffness and no significant difference in JND for equivalent systems. This finding indicates that human participants do not discriminate natural frequency based on the maximum force magnitude perceived, as indicated by prior studies.
A Glutathione-Nrf2-Thioredoxin Cross-Talk Ensures Keratinocyte Survival and Efficient Wound Repair

The tripeptide glutathione is the most abundant cellular antioxidant with high medical relevance, and it is also required as a co-factor for various enzymes involved in the detoxification of reactive oxygen species and toxic compounds. However, its cell-type specific functions and its interaction with other cytoprotective molecules are largely unknown. Using a combination of mouse genetics, functional cell biology and pharmacology, we unraveled the function of glutathione in keratinocytes and its cross-talk with other antioxidant defense systems. Mice with keratinocyte-specific deficiency in glutamate cysteine ligase, which catalyzes the rate-limiting step in glutathione biosynthesis, showed a strong reduction in keratinocyte viability in vitro and in the skin in vivo. The cells died predominantly by apoptosis, but also showed features of ferroptosis and necroptosis. The increased cell death was associated with increased levels of reactive oxygen and nitrogen species, which caused DNA and mitochondrial damage. However, epidermal architecture, and even healing of excisional skin wounds were only mildly affected in the mutant mice. The cytoprotective transcription factor Nrf2 was strongly activated in glutathione-deficient keratinocytes, but additional loss of Nrf2 did not aggravate the phenotype, demonstrating that the cytoprotective effect of Nrf2 is glutathione dependent. However, we show that deficiency in glutathione biosynthesis is efficiently compensated in keratinocytes by the cysteine/cystine and thioredoxin systems. Therefore, our study highlights a remarkable antioxidant capacity of the epidermis that ensures skin integrity and efficient wound healing.
Multi-objective traffic light control system based on Bayesian probability interpretation

Traffic light control is a challenging problem in modern societies. This is due to the huge number of vehicles and the high dynamics of the traffic system. Poor traffic management causes a high rate of accidents, time losses, and negative impact on the economy as well as the environment. In this paper, we develop a multiagent traffic light control system based on a multi-objective sequential decision making framework. In order to respond effectively to the changing environment and the non-stationarity of the road network, the proposed traffic light controller is based on the Bayesian interpretation of probability. We use the open source Green Light District (GLD) vehicle traffic simulator as a testbed framework. The change in road conditions is modeled by varying the vehicles generation probability distributions and adapting the Intelligent Driver Model (IDM) parameters to the adverse weather conditions. We have added a set of new performance indices in GLD based on collaborative learning to better evaluate the performance of the proposed multi-objective traffic light controller. The results show that the proposed multi-objective controller outperforms the single-objective controller.
A Fair Scheduling Model for Centralized Cognitive Radio Networks

We formulate throughput maximizing, max-min fair, weighted max-min fair, and proportionally fair scheduling problems for cognitive radio networks managed by a centralized cognitive base station. We propose a very general scheduling model accomplishing goals such as making frequency, time slot, and data rate allocation to secondary users with possibly multiple antennas, in a heterogenous multi-channel and multi-user scenario. Moreover, our schedulers ensure that reliable communication between the cognitive base station and secondary users are maintained, no collisions occur among secondary users, and primary users in the service area of the cognitive base station are not disturbed. Two distinctive features of our fair schedulers are that they provide joint temporal and throughput fairness, and take throughput values experienced by secondary users in the recent past, referred to as window size, into account and use this information in the current scheduling decision. We also propose a heuristic algorithm for our fair schedulers and demonstrate through simulations that our proposed heuristic yields very close solutions to the values obtained from the optimization softwares. Furthermore, we make extensive simulations to evaluate our schedulers' performance in terms of both total throughput and fairness for varying number of secondary users, frequencies, antennas, and window size.
Recognizing Names by the Meaning of Defining Syntactic Structures

We present a named entity recognition system that relies on interpreting the meaning of the syntactic structures that define named entities. The syntactic heads of the defining structures are learned from the training data and are later used to interpret the meaning of the syntactic structures in the test data. Semantic features are extracted based on the interpretations and are used to build a decision tree classifier. The mapping phase iteratively matches previously labeled names with aliases and conjunctions in the same document. Evaluation on two test sets shows this system can generalize to some extent and perform moderately well.
Right inflight?: a dataset for exploring the automatic prediction of movies suitable for a watching situation

In this paper, we present the dataset Right Inflight developed to support the exploration of the match between video content and the situation in which that content is watched. Specifically, we look at videos that are suitable to be watched on an airplane, where the main assumption is that that viewers watch movies with the intent of relaxing themselves and letting time pass quickly, despite the inconvenience and discomfort of flight. The aim of the dataset is to support the development of recommender systems, as well as computer vision and multimedia retrieval algorithms capable of automatically predicting which videos are suitable for inflight consumption. Our ultimate goal is to promote a deeper understanding of how people experience video content, and of how technology can support people in finding or selecting video content that supports them in regulating their internal states in certain situations. Right Inflight consists of 318 human-annotated movies, for which we provide links to trailers, a set of pre-computed low-level visual, audio and text features as well as user ratings. The annotation was performed by crowdsourcing workers, who were asked to judge the appropriateness of movies for inflight consumption.
Pen computing: a technology overview and a vision

This work gives an overview of a new technology that is attracting growing interest in public as well as in the computer industry itself. The visible difference from other technologies is in the use of a pen or pencil as the primary means of interaction between a user and a machine, picking up the familiar pen and paper interface metaphor. From this follows a set of consequences that will be analyzed and put into context with other emerging technologies and visions.Starting with a short historical background and the technical advances that begin making Pen Computing a reality, the new paradigms created by Pen Computing will be explained and discussed. Handwriting recognition, mobility and global information access are other central topics. This is followed by a categorization and an overview of current and future systems using pens as their primary user interface component.
Strategic Reactions to Infants: Female Self-Presentation in a Romantic Context

Research has demonstrated that humans engage in various self-presentational behaviours in the context of mate attraction. We build and expand on these efforts by showing that female facial behaviour also responds to the manipulation of romantic motivation in ways congruent with the logic of evolutionary theory. Given that childbearing is an important goal of human courtship, we hypothesized that during the initial stages of romantic encounters one way that women can advertize their quality is through their emotional reactions to children. Two studies were conducted to determine whether women would self-present in the context of romance by augmenting positive reactions (e.g., smiling more) or by attenuating negative reactions (e.g., frowning less). In both studies participants were undergraduate psychology students. Study 1 was an online study; it examined reported facial expressions towards and cognitive evaluations of infants. Study 2 was a laboratory study in which participants' spontaneous facial behavior was videotaped while they watched a video of infants (vs. a neutral film). In both studies we found support only for the hypothesis that, when in a romantic context, women attenuate negative reactions. Such attenuation was found for facial expressions, but not for cognitive or affective evaluations of infants.
Dispersion behavior of torsional guided waves in a small diameter steel gas pipe

Condition monitoring of gas pipes has been an important issue for gas companies. Failure to accurately identify condition of gas pipes result in numerous problems. Also, producing a condition monitoring system for buried pipelines is challenging. Small pipes (with diameters less than 50 mm) are considered here as most of the literature focuses on larger pipes. Guided wave theory will be introduced alongside a numerical simulation of the relevant dispersion curves of the system. This paper investigates the feasibility of using torsional guided waves for inspecting defects in buried pipes with small diameters. The pipes are assumed to be lossless and hence the effect of attenuation is ignored in the calculations. Upon finding the theoretical guided wave characteristics, experiments were conducted to see if the aim could be achieved in a realistic scenario. A steel pipe with a diameter of 34 mm and wall thickness of 5.5 mm is considered. High reverberation levels at high frequency propagations due to mode conversion are studied. Having only a limited number of transducers could be a reason for high reverberation at high frequencies.
Effect of Education and Performance Feedback on Rates of Catheter-Associated Urinary Tract Infection in Intensive Care Units in Argentina

Abstract Objective: To evaluate the effect of education and performance feedback regarding compliance with catheter care and handwashing on rates of catheter-associated urinary tract infection (UTI) in intensive care units (ICUs). Setting: Two level III adult ICUs in a private healthcare facility in Argentina. Patients: All adult patients admitted to the study units who had a urinary catheter in place for at least 24 hours. Methods: A prospective, open trial in which rates of catheter-associated UTI determined during a baseline period of active surveillance without education and performance feedback were compared with rates of catheter-associated UTI after imple-menting education and performance feedback. Results: There were 1,779 catheter-days during the baseline period and 5,568 catheter-days during the intervention period. Compliance regarding prevention of compression of the tubing by a leg improved (from 83% to 96%; relative risk [RR], 1.15; 95% confidence interval [CI95], 1.03 to 1.28; P = .01) and so did compliance with handwashing (from 23.1% to 65.2%; RR, 2.82; CI95, 2.49 to 3.20; P<.0001). Catheter-associated UTI rates decreased significantly from 21.3 to 12.39 per 1,000 catheter-days (RR, 0.58; CI95, 0.39 to 0.86; P = .006). Conclusion: Implementing education and performance feedback regarding catheter care measures and handwashing compliance was associated with a significant reduction in catheter-associated UTI rates. Similar programs may help reduce catheter-associated UTI rates in other Latin American hospitals.