Miracle-dz/UniFAR-FTUs huggingface dataset:
Ethylene Mediates Response and Tolerance to Potassium Deprivation in Arabidopsis[W]

Potassium deprivation leads to large reductions in plant growth and yields. How plants sense and transduce the stress signals initiated by potassium deprivation is poorly understood. Both ethylene production and the transcription of genes involved in ethylene biosynthesis increase when plants are deprived of potassium. To elucidate the role of ethylene in low potassium signaling pathways, we used both genetic and chemical approaches. Our results showed that ethylene is important in tolerance to low potassium and for changes in both root hair and primary root growth in Arabidopsis thaliana. We show that ethylene acts upstream of reactive oxygen species in response to potassium deprivation. The expression of High-Affinity K+ Transporter5 was used as a marker of potassium deprivation and was found to be dependent on ethylene signaling. In the ethylene insensitive2-1 (ein2-1) mutant, the ethylene-mediated low potassium responses were not completely eliminated, suggesting that some potassium deprivation–induced responses are either ethylene independent or EIN2 independent. Ethylene signaling is a component of the plant's response to low potassium that stimulates the production of reactive oxygen species and is important for changes in root morphology and whole plant tolerance to low potassium conditions.
Performance modelling and bandwidth management of WiMAX systems

Worldwide Interpretability for Microwave Access (WiMAX) is a competitive connection oriented technology for metropolitan broadband wireless access with very high data rate, large service coverage and flexible quality of service (QoS). Due to the large number of connections, the efficient bandwidth management and related channel allocation for the uplink access in WiMAX networks is a very challenging task of the medium access control (MAC) protocol. In order to provide better bandwidth utilization and network throughput, a cost-effective WiMAX bandwidth management scheme is devised, named as the WiMAX partial sharing scheme (WPSS) and compared against a simpler scheme, named as the WiMAX complete sharing scheme (WCPS). An analytic maximum entropy (ME) model is proposed for the cost-effective performance evaluation of the two bandwidth management schemes associated with networks with a large number of stations and/or the connections. In this context, an open queueing network model (QNM) is devised, consisting of interacting queues with multiple service classes and closed form expressions for the state and blocking probability distributions are derived. Typical numerical examples are employed to verify the credibility of the analytic ME solutions against simulation results at 95 % confidence intervals. Moreover, it is shown that the WPSS can significantly improve the networks performance in comparison to that of the WCPS.
Some attitudinal aspects of foreign language learning in northern Ireland: Focus on gender and religious affiliation

Abstract This paper discusses some aspects of foreign language learning within the divided school system of Northern Ireland. It is argued that an improvement of foreign language learning must be seen in a socio‐cultural context whereby a change in attitudes to languages in general, including Irish, may lead not only to a balanced interest among girls and boys in the language classroom, but also to a more tolerant approach to the cultural differences among the Catholic and Protestant communities.
Experimental evaluation of cooperative active safety applications based on V2V communications

Cooperative vehicular systems are expected to improve traffic safety and efficiency through the real-time exchange of information between vehicles and infrastructure nodes. To this aim, cooperative active safety applications are being designed to extend, in space and time, the drivers' awareness of the surrounding environment in order to be able to detect potential road dangers with sufficient time for the driver to react. The strict requirements of cooperative vehicular applications and the challenging vehicular environment require that cooperative active safety applications are extensively tested under real-world conditions. In this context, this paper presents the experimental evaluation of different vehicle-to-vehicle cooperative active safety applications under real world and challenging conditions where cooperative systems need to prove their real effectiveness.
Bilateral Transcranial Direct Current Stimulation Language Treatment Enhances Functional Connectivity in the Left Hemisphere: Preliminary Data from Aphasia

Several studies have already shown that transcranial direct current stimulation (tDCS) is a useful tool for enhancing recovery in aphasia. However, no reports to date have investigated functional connectivity changes on cortical activity because of tDCS language treatment. Here, nine aphasic persons with articulatory disorders underwent an intensive language therapy in two different conditions: bilateral anodic stimulation over the left Broca's area and cathodic contralesional stimulation over the right homologue of Broca's area and a sham condition. The language treatment lasted 3 weeks (Monday to Friday, 15 sessions). In all patients, language measures were collected before (T0) and at the end of treatment (T15). Before and after each treatment condition (real vs. sham), each participant underwent a resting-state fMRI study. Results showed that, after real stimulation, patients exhibited the greatest recovery not only in terms of better accuracy in articulating the treated stimuli but also for untreated items on different tasks of the language test. Moreover, although after the sham condition connectivity changes were confined to the right brain hemisphere, real stimulation yielded to stronger functional connectivity increase in the left hemisphere. In conclusion, our data provide converging evidence from behavioral and functional imaging data that bilateral tDCS determines functional connectivity changes within the lesioned hemisphere, enhancing the language recovery process in stroke patients.
Building Topic Models Based on Anchor Words

Suppose you were given a stack of documents, such as all of the articles published in a particular newspaper, and your goal was to make sense of this data, to determine topics that this data may be made up from. To frame this as an unsupervised learning problem, suppose the documents were written in a foreign language and came from a foreign planet. By understanding topics that these documents are about, you would be able to, given a new document, determine what characteristics it shares with other documents and uncover, ultimately, what it is about. In theory, we refer to this as the problem of unsupervised Topic Modeling, first introduced by Dave Blei et al. Of course, instead of taking news articles, this can be framed with genome sequences, audio tracks, images, and all sorts of data. The problem of Topic Modeling informally aims to discover hidden topics in documents, then annotate them according to these in order to summarize the collection of documents. This falls into the modern AI challenge of developing tools for automatic data comprehension. In the 2012 paper Learning Topic Models: Going beyond SVD [1], Sanjeev Arora, Rong Ge, and Ankur Moitra present a new method for unsupervised learning of topics, namely that of NonNegative Matrix Factorization (NMF) and provide provable bounds for the error in learning. Arora et al. motivate NMF as a more naturally derived tool for topic learning than the current approach prevailing in theory that is Singular Value Decomposition (SVD). The authors present a polynomialtime algorithm, building on their previous study on NMF [3], that similar to SVD can be realized mostly in linear algebra operations and thus achieves better running time than other local-search approaches both in theory and in practice, where the number of documents suffices to be
A Novel Industry Grade Dataset for Fault Prediction Based on Model-Driven Developed Automotive Embedded Software

In this paper, we present a novel industry dataset on static software and change metrics for Matlab/Simulink models and their corresponding auto-generated C source code. The data set comprises data of three automotive projects developed and tested accordingly to industry standards and restrictive software development guidelines. We present some background information of the projects, the development process and the issue tracking as well as the creation steps of the dataset and the used tools during development. A specific highlight of the dataset is a low measurement error on change metrics because of the used issue tracking and commit policies.
Sensorless Indirect Stator Field Orientation Speed Control for Single-Phase Induction Motor Drive

The industrial requirements for the control of an induction machine without a mechanical sensor continue to be of interest, as evidenced by the most recent publications. The focus is on improvements of control without a mechanical sensor. A new method for the implementation of a sensorless indirect stator-flux-oriented control (ISFOC) of a single-phase induction motor (SPIM) drive is proposed in this paper. The proposed method of rotor speed estimation is based only on the measurement of the main and auxiliary windings stator currents and that of a reference q-axis current generated by the control algorithm. The error of the measured q-axis current from its reference value feeds the proportional plus integral controller, the output of which is the estimated slip angular frequency. Experimental results for sensorless ISFOC speed control of a SPIM drive are presented and analyzed using a dSPACE system with DS1104 controller board based on the digital signal processor TMS320F240. Digital simulation and experimental results are presented to show the improvement in performance of the proposed sensorless algorithm.
Hopping control for the musculoskeletal bipedal robot: BioBiped

Bipedal locomotion can be divided into primitive tasks, namely repulsive leg behavior (bouncing against gravity), leg swing (protraction and retraction) and body alignment (balancing against gravity). In the bipedal spring-mass model for walking and running, the repulsive leg function is described by a linear prismatic spring. This paper adopts two strategies for swinging and bouncing control from conceptual models for the human-inspired musculoskeletal BioBiped robot. The control approach consists of two layers, velocity based leg adjustment (VBLA) and virtual model control to represent a virtual springy leg between toe and hip. Additionally, the rest length and stiffness of the virtual springy leg are tuned based on events to compensate energy losses due to damping. In order to mimic human locomotion, the trunk is held upright by physical constraints. The controller is implemented on the validated detailed simulation model of BioBiped. In-place as well as forward hopping and switching between these two gaits are easily achieved by tuning the parameters for the leg adjustment, virtual leg stiffness and injected energy. Furthermore, it is shown that the achieved motion performance of in-place hopping agrees well with that of human subjects.
Social exchange theory as an explanation of organizational citizenship behaviour among teachers

Primary processes in schools are hard to pin down despite attempts to measure central aspects of processes and outputs. For this very reason, it is important that teachers are motivated to go above and beyond their formal job responsibilities, a phenomenon called organizational citizenship behaviour. Social exchange theory is a theoretical explanation for organizational citizenship behaviour. This study examines a model of clear leadership and relational building between head and teachers as antecedents, and organizational citizenship behaviour as a consequence of teacher–school exchange. One purpose of this study is to explore the nature of exchanges between parties in the organization of teachers’ work and examine the relative impact of these aspects on organizational citizenship behaviour. The methodology adopted was a cross‐sectional survey of 234 secondary teachers. The structural equation analysis indicates a strong support for the importance of principal–teacher trust on social exchange and indirectly an impact on organizational citizenship behaviours. We also found some moderate support for the importance of clear leadership on organizational citizenship behaviours. This article presents suggestions for future research and possible implications for practice.
Oxidative burden in prediabetic and diabetic individuals: evidence from plasma coenzyme Q10

Aim Individuals with diabetes and prediabetes are at risk of vascular injury. However, the exact mechanisms are unclear. The mitochondria mobile electron carrier coenzyme Q10 (CoQ10) is a potent lipophilic antioxidant. We hypothesize that oxidative stress, detectable as changes in plasma CoQ10 concentrations and composition, plays an important role in vascular disease in diabetes.
Toward perceptual enhancement of multiple intersecting surfaces

Visualizations of 2D scalar fields are often based on the rendering of 3D surfaces. Combinations of standard 3D rendering techniques using color, transparency, texturing, and lighting can be employed to create visualizations for multiple surfaces. However, the transition from foreground to background due to surface intersections can confound accurate surface perception, even for techniques that work well for overlapping non-intersecting surfaces. Our research proposes a generalized method of decomposing and stratifying these surfaces into layered components, allowing complete rendering control of each surface component. We explore different rendering schemes based on stratification values and report initial results from experimentation.
Effects of Polymer Hydrophobicity on Protein Structure and Aggregation Kinetics in Crowded Milieu.

We examined the effects of water-soluble polymers of various degrees of hydrophobicity on the folding and aggregation of proteins. The polymers we chose were polyethylene glycol (PEG) and UCON (1:1 copolymer of ethylene glycol and propylene glycol). The presence of additional methyl groups in UCON makes it more hydrophobic than PEG. Our earlier analysis revealed that similarly sized PEG and UCON produced different changes in the solvent properties of water in their solutions and induced morphologically different α-synuclein aggregates [Ferreira, L. A. , et al. (2015) Role of solvent properties of aqueous media in macromolecular crowding effects. J. Biomol. Struct. Dyn. , in press]. To improve our understanding of molecular mechanisms defining behavior of proteins in a crowded environment, we tested the effects of these polymers on secondary and tertiary structure and aromatic residue solvent accessibility of 10 proteins [five folded proteins, two hybrid proteins; i.e., protein containing ordered and disordered domains, and three intrinsically disordered proteins (IDPs)] and on the aggregation kinetics of insulin and α-synuclein. We found that effects of both polymers on secondary and tertiary structures of folded and hybrid proteins were rather limited with slight unfolding observed in some cases. Solvent accessibility of aromatic residues was significantly increased for the majority of the studied proteins in the presence of UCON but not PEG. PEG also accelerated the aggregation of protein into amyloid fibrils, whereas UCON promoted aggregation to amyloid oligomers instead. These results indicate that even a relatively small change in polymer structure leads to a significant change in the effect of this polymer on protein folding and aggregation. This is an indication that protein folding and especially aggregation are highly sensitive to the presence of other macromolecules, and an excluded volume effect is insufficient to describe their effect.
Thermal learning in the honeybee, Apis mellifera

SUMMARY Honeybee foragers are exposed to thermal stimuli when collecting food outside and receiving food rewards inside the nest. In both contexts, there is an opportunity for foragers to associate warmth with food rewards. However, honeybee thermal learning is poorly understood. Using an associative learning paradigm (the proboscis extension reflex), we show that honeybees can learn to associate a nectar reward with a heated stimulus applied to the antenna to mimic natural contact with a warm flower or nectar-offering forager. Conditioning with longer inter-trial intervals (ITI) significantly improved learning acquisition. We also trained bees to discriminate between temperatures above (warm) and below (cold) ambient air temperature. Learning acquisition improved by 38% per 10°C increase in absolute stimulus intensity (difference between the rewarded temperature and unrewarded ambient air temperature). However, bees learned positive temperature (warm) significantly better than negative temperature (cold) differences, approximately twice as well for 10°C as compared with a −10°C difference. Thus, thermosensation, a sensory modality that is relatively unexplored in honeybees, could play a role in the acquisition of information from nestmates (social learning) and in foraging decisions influenced by associations between floral temperature and nectar rewards.
Spontaneous Emotional Speech Recordings through a Cooperative Online Video Game

Most of emotional speech databases are recorded by actors and some of spontaneous databases are not free of charge. To progress in emotional recognition, it is necessary to carry out a big data acquisition task. The current work gives a methodology to capture spontaneous emotions through a cooperative video game. Our methodology is based on three new concepts: novelty, reproducibility and ubiquity. Moreover, we have developed an experiment to capture spontaneous speech and video recordings in a controlled environment in order to obtain high quality samples.
Vector analysis on the fault-tolerant abilities of combined analog circuit systems

Fault-tolerant mechanisms have been an essential part of electronic equipments in extreme environments these years. The combined analog circuit system can work properly when one or several parts of it break down. Then, what factors affect the fault-tolerant performance of such systems? System function is the most direct reflection of the output of a circuit, it can necessarily give us much useful information. From the perspective of vectors,this paper analyzed the phase angle of the combined circuit system based on system functions and furthermore inferred the relation between angle and fault-tolerant abilities. Experimental results show that, the larger angle a combined circuit system has, the better its fault-tolerant performance is, which will provide great benefit for designing analog circuit with better fault tolerance.
Construction of discriminative Kernels from known and unknown non-targets for PLDA-SVM scoring

Conventional PLDA scoring in i-vector speaker verification involves the i-vectors of target speakers and claimants only. We have previously demonstrated that better performance can be achieved by incorporating the information of background speakers in the scoring process via speaker-dependent SVMs. This is achieved by defining a PLDA score space with dimension equal to the number of training i-vectors for each target speaker. The new protocol in NIST 2012 SRE permits systems to use the information of other target-speakers (called known non-targets) in each verification trial. In this paper, we exploit this new protocol to enhance the performance of PLDA-SVM scoring by using the score vectors of both known and unknown non-targets as the impostor class data to train the speaker-dependent SVMs. Because some target speakers have one enrollment utterance only, which results in severe imbalance in the speaker- and impostor-class data for SVM training. This paper shows that if the enrollment utterance is sufficiently long, a number of target-speaker i-vectors can be generated by an utterance partitioning and resampling technique, resulting in much better scoring SVMs. Results on NIST 2012 SRE demonstrate the advantages of pooling the known and unknown non-targets for training the SVMs and that the resampling techniques can help the SVM training algorithm to find better decision boundaries for those speakers with only a small number of enrollment utterances.
Plant defense pathways subverted by Agrobacterium for genetic transformation

The soil phytopathogen Agrobacterium has the unique ability to introduce single-stranded transferred DNA (T-DNA) from its tumor-inducing (Ti) plasmid into the host cell in a process known as horizontal gene transfer. Following its entry into the host cell cytoplasm, the T-DNA associates with the bacterial virulence (Vir) E2 protein, also exported from Agrobacterium, creating the T-DNA nucleoprotein complex (T-complex), which is then translocated into the nucleus where the DNA is integrated into the host chromatin. VirE2 protects the T-DNA from the host DNase activities, packages it into a helical filament and interacts with the host proteins, one of which, VIP1, facilitates nuclear import of the T-complex and its subsequent targeting to the host chromatin. Although the VirE2 and VIP1 protein components of the T-complex are vital for its intracellular transport, they must be removed to expose the T-DNA for integration. Our recent work demonstrated that this task is aided by an host defense-related F-box protein VBF that is induced by Agrobacterium infection and that recognizes and binds VIP1. VBF destabilizes VirE2 and VIP1 in yeast and plant cells, presumably via SCF-mediated proteasomal degradation. VBF expression in and export from the Agrobacterium cell lead to increased tumorigenesis. Here, we discuss these findings in the context of the “arms race” between Agrobacterium infectivity and plant defense.
Towards A Method Of Programming With Assertions

Embedded assertions have long been recognized as a Po- tentially powerful tool for automatic runtime detection of software faults during debugging, testing and maintenance. Yet despite the richness of the notations and the maturity of the techniques and tools that have been developed for programming with assertions, assertions are a development tool that has seen little widespread use in practice. The main reasons seem to be that (1) previous assertion processing tools did not integrate easily with existing programming environments, and (2) it is not well understood what kinds of assertions are most effective at detecting software faults. This paper describes experience using an assertion processing tool that was built to address the concerns of ease-of-use and effectiveness. The tool is called App, an Annotation Pre- Processor for C programs developed in UNIX-based de- velopment environments. APP has been used to develop a number of software systems over the past three years Based on this experience, the paper presents a classification of the assertions that were most effective at detecting faults. While the assertions that are described guard against many common kinds of faults and errors, the very commonness of such faults demonstrates the need for an explicit, high-level, automatically check-able specification of required behavior. It is hoped that the classification presented in this paper will prove to be a useful first step in developing a method of programming with assertions.