Miracle-dz/UniFAR-FTUs huggingface dataset:
The Synaptophysin–Synaptobrevin Complex: a Hallmark of Synaptic Vesicle Maturation

Exocytosis of synaptic vesicles requires the formation of a fusion complex consisting of the synaptic vesicle protein synaptobrevin (vesicle-associated membrane protein, or VAMP) and the plasma membrane proteins syntaxin and soluble synaptosomal-associated protein of 25 kDa (or SNAP 25). In search of mechanisms that regulate the assembly of the fusion complex, it was found that synaptobrevin also binds to the vesicle protein synaptophysin and that synaptophysin-bound synaptobrevin cannot enter the fusion complex. Using a combination of immunoprecipitation, cross-linking, and in vitrointeraction experiments, we report here that the synaptophysin–synaptobrevin complex is upregulated during neuronal development. In embryonic rat brain, the complex is not detectable, although synaptophysin and synaptobrevin are expressed and are localized to the same nerve terminals and to the same pool of vesicles. In contrast, the ability of synaptobrevin to participate in the fusion complex is detectable as early as embryonic day 14. The binding of synaptoporin, a closely related homolog of synaptophysin, to synaptobrevin changes in a similar manner during development. Recombinant synaptobrevin binds to synaptophysin derived from adult brain extracts but not to that derived from embryonic brain extracts. Furthermore, the soluble cytosol fraction of adult, but not of embryonic, synaptosomes contains a protein that induces synaptophysin–synaptobrevin complex formation in embryonic vesicle fractions. We conclude that complex formation is regulated during development and is mediated by a posttranslational modification of synaptophysin. Furthermore, we propose that the synaptophysin–synaptobrevin complex is not essential for exocytosis but rather provides a reserve pool of synaptobrevin for exocytosis that can be readily recruited during periods of high synaptic activity.
Special Issue on AI Techniques to Evaluate Economics and Happiness -31-

Topic classification of texts is one of the most interesting challenges in Natural Language Processing (NLP). Topic classifiers commonly use a bag-of-words approach, in which the classifier uses (and is trained with) selected terms from the input texts. In this work we present techniques based on graph similarity to classify short texts by topic. In our classifier we build graphs from the input texts, and then use properties of these graphs to classify them. We have tested the resulting algorithm by classifying Twitter messages in Spanish among a predefined set of topics, achieving more than 70% accuracy.
Tiotropium as a first maintenance drug in COPD: secondary analysis of the UPLIFT® trial

The aim of the present study was investigate the long-term effect of tiotropium as first maintenance respiratory medication in chronic obstructive pulmonary disease (COPD). A 4-yr, randomised, multicentre, double-blind, parallel-group, placebo-controlled trial (Understanding Potential Long-term Impacts on Function with Tiotropium (UPLIFT®)) was conducted. Analysis focused on the effect of tiotropium versus matching placebo in the 810 (13.5%) COPD patients not on other maintenance treatment (long-acting &bgr;-agonists, inhaled corticosteroids, theophyllines or anticholinergics) at randomisation. Spirometry, health-related quality of life (St George’s Respiratory Questionnaire (SGRQ) score), exacerbations of COPD and mortality were also analysed. 403 patients (mean±sd age 63±8 yrs, post-bronchodilator forced expiratory volume in 1 s (FEV1) 53±12% predicted) received tiotropium and 407 (64±8 yrs of age, post-bronchodilator FEV1 51±12% pred) received placebo. Post-bronchodilator FEV1 decline was 42±4 mL·yr−1 in the tiotropium group and 53±4 mL·yr−1 in the placebo group (p = 0.026). At 48 months, the morning pre-dose FEV1 was 134 mL higher in the tiotropium group compared to the placebo group (p<0.001). SGRQ total score declined more slowly in the tiotropium group (difference of 1.05±0.34 units·yr−1; p = 0.002). This was particularly significant for the impact (difference of 1.08±0.37 units·yr−1; p = 0.004) and activity (1.44±0.40 units·yr−1; p<0.001) domains, but not for symptoms (0.26±0.50 units·yr−1; p = 0.6). At 48 months, the difference in total score was 4.6 units (p<0.001) with tiotropium compared to placebo. In patients with COPD who are not on maintenance therapy, tiotropium is associated with significant benefits in disease progression.
Orb3 - Musical robots within an Adaptive Social Composition System

Gesture capture, motion tracking and 3D visualisation technologies have generated many new musical forms, often extending the mannerisms or behaviours of a given performer or discipline, providing new compositional frameworks for real time synthesis in response to action. In many cases these approaches are presented within a single domain, a live stage performance, a site specific installation, a shared networked visualisation of collaborative composition. The reality is that these ‘interactivating spaces’ [1] whether haptic, [5] tactile [9] or ubiquitous [11] is that they manifest new forms of interaction, between people, systems and the medium of sound. Free Sound can be understood to be an extension of the ‘open work’ where the base materials for a compositional process are created through a model of exchange, interaction and resynthesis. The resulting output of these activities can be broadcast and disseminated through a range of technologies to both social and private spaces. This research suggests that there are new interaction models and social compositional frameworks to be found in these cybrid spaces, a previously intangible location often dominated by the broadcast and publishing industry. A marketing model defined by revenue streams and a value chain. In the case of socially mediated composition or ‘free sound’ there is still a value chain, it’s investors and beneficiaries are the open source community, the collaborators and participants within such mediated systems and the resulting free sound.
Repulsive Self-Adaptive Acceleration Particle Swarm Optimization Approach

Abstract Adaptive Particle Swarm Optimization (PSO) variants have become popular in recent years. The main idea of these adaptive PSO variants is that they adaptively change their search behavior during the optimization process based on information gathered during the run. Adaptive PSO variants have shown to be able to solve a wide range of difficult optimization problems efficiently and effectively. In this paper we propose a Repulsive Self-adaptive Acceleration PSO (RSAPSO) variant that adaptively optimizes the velocity weights of every particle at every iteration. The velocity weights include the acceleration constants as well as the inertia weight that are responsible for the balance between exploration and exploitation. Our proposed RSAPSO variant optimizes the velocity weights that are then used to search for the optimal solution of the problem (e.g., benchmark function). We compare RSAPSO to four known adaptive PSO variants (decreasing weight PSO, time-varying acceleration coefficients PSO, guaranteed convergence PSO, and attractive and repulsive PSO) on twenty benchmark problems. The results show that RSAPSO achives better results compared to the known PSO variants on difficult optimization problems that require large numbers of function evaluations.
Artificial stereo data generation for speech feature mapping

Feature mapping technique is widely used to eliminate the mismatch between the training and test conditions of speech recognition. In the feature mapping, a target (mismatched) feature vector sequence is mapped closer to the corresponding reference (matched) feature vector stream. The training of the mapping system is usually carried out based on a set of stereo data which consists of simultaneous recordings obtained in both the reference and target conditions. In this paper, we propose a novel approach to blind parameter estimation which does not require the reference feature vectors. The proposed approach is motivated by the hidden Markov model (HMM)-based speech synthesis algorithm.
The MPI Emotional Body Expressions Database for Narrative Scenarios

Emotion expression in human-human interaction takes place via various types of information, including body motion. Research on the perceptual-cognitive mechanisms underlying the processing of natural emotional body language can benefit greatly from datasets of natural emotional body expressions that facilitate stimulus manipulation and analysis. The existing databases have so far focused on few emotion categories which display predominantly prototypical, exaggerated emotion expressions. Moreover, many of these databases consist of video recordings which limit the ability to manipulate and analyse the physical properties of these stimuli. We present a new database consisting of a large set (over 1400) of natural emotional body expressions typical of monologues. To achieve close-to-natural emotional body expressions, amateur actors were narrating coherent stories while their body movements were recorded with motion capture technology. The resulting 3-dimensional motion data recorded at a high frame rate (120 frames per second) provides fine-grained information about body movements and allows the manipulation of movement on a body joint basis. For each expression it gives the positions and orientations in space of 23 body joints for every frame. We report the results of physical motion properties analysis and of an emotion categorisation study. The reactions of observers from the emotion categorisation study are included in the database. Moreover, we recorded the intended emotion expression for each motion sequence from the actor to allow for investigations regarding the link between intended and perceived emotions. The motion sequences along with the accompanying information are made available in a searchable MPI Emotional Body Expression Database. We hope that this database will enable researchers to study expression and perception of naturally occurring emotional body expressions in greater depth.
Greedy steep slope finder: The fast impulsive noise rejection for compressed measurement image signals

Impulsive noise in a compressed measurement signal can be detected by the energy distribution of the reconstructed sparse signal. In this paper, the fast preprocessing for impulsive noise rejection for a compressed measurement image signal is proposed. An image is sparsified by octave-tree wavelet transform with db8 as the mother wavelet. The impulsive noise is detected via the change in the ratio of the energy leaking out of the third level subband to the total energy of the sparse signal. Since the information in the image is redundant, the number of the noisy element is estimated within +g of the actual value. g is defined in the unit of the percent of the size of the compressed measurement signal. The experiment shows that the proposed method effectively rejected noise with large magnitude. It provided the comparable performance to the method that rejected the exact number of noisy elements but required less computational time.
Delegation-based authentication and authorization for the IP-based Internet of Things

IP technology for resource-constrained devices enables transparent end-to-end connections between a vast variety of devices and services in the Internet of Things (IoT). To protect these connections, several variants of traditional IP security protocols have recently been proposed for standardization, most notably the DTLS protocol. In this paper, we identify significant resource requirements for the DTLS handshake when employing public-key cryptography for peer authentication and key agreement purposes. These overheads particularly hamper secure communication for memory-constrained devices. To alleviate these limitations, we propose a delegation architecture that offloads the expensive DTLS connection establishment to a delegation server. By handing over the established security context to the constrained device, our delegation architecture significantly reduces the resource requirements of DTLS-protected communication for constrained devices. Additionally, our delegation architecture naturally provides authorization functionality when leveraging the central role of the delegation server in the initial connection establishment. Hence, in this paper, we present a comprehensive, yet compact solution for authentication, authorization, and secure data transmission in the IP-based IoT. The evaluation results show that compared to a public-key-based DTLS handshake our delegation architecture reduces the memory overhead by 64 %, computations by 97 %, network transmissions by 68 %.
Validation of the Spanish version of the Therapeutic Alliance Negotiation Scale / Validación de la versión en español de la Escala de Negociación de la Alianza Terapéutica

Abstract The objectives of this research study were to validate a Spanish version of The Alliance Negotiation Scale with Mexican patients and contrast relevant variables from the therapy and negotiation of the alliance. The sample was composed of 199 participants of both sexes. Exploratory factor analysis grouped three factors related to the therapeutic alliance negotiation, which are: therapist’s flexibility; therapist’s negotiating stance; and being comfortable expressing negative feelings. This factorial structure differs from the English version. It was found that clients’ sex and age did not influence the negotiation of the alliance, while time in therapy and the reason for attendance did offer differences; it was determined that negotiations depend largely on the therapist being flexible and their negotiating stance during the process.
On Polynomial Time Approximation Bounded Solution for TSP and NP Complete Problems

The question of whether all problems in NP class are also in P class is generally considered one of the most important open questions in mathematics and theoretical computer science as it has far-reaching consequences to other problems in mathematics, computer science, biology, philosophy and cryptography. There are intensive research on proving `NP not equal to P' and `NP equals to P'. However, none of the `proved' results is commonly accepted by the research community up to date. In this paper, motived by approximability of traveling salesman problem (TSP) in polynomial time, we aim to provide a new perspective: showing that NP=P from polynomial time approximation-bounded solutions of TSP in Euclidean space.
Metabolite Profiles in Starved Diporeia spp. using Liquid Chromatography-Mass Spectrometry (Lc-Ms) Based Metabolomics

ABSTRACT The holarctic amphipod Diporeia spp. was historically the most abundant benthic macroinvertebrate in the offshore region of the Laurentian Great Lakes basin. However, since the 1990's, the numbers of Diporeia have declined precipitously throughout the region. Competition for food with introduced dreissenid mussels may be partly to blame for this decline. Thus, a better understanding of how Diporeia responds and adjust to starvation is needed. For this purpose, we used liquid chromatography (LC) coupled with time-of-flight mass spectrometry (TOFMS) to study the metabolite profiles of Diporeia during starvation. Diporeia were collected from Lake Michigan, brought to the laboratory and starved for up to 60 days. During the starvation period, metabolite levels were determined at 12-day intervals and compared to those of day 0. Principal component and cluster analyses revealed differential abundance of metabolite profiles across groups. Significantly down-regulated metabolites included polyunsaturated fatty acids, phospholipids, and amino acids and their derivatives. Overall, starved organisms relied predominantly on glycerophospolipid metabolism and protein based catabolism for energy production. This research demonstrates that LC-MS based metabolomics can be used to assess physiological status and has shown that unique metabolite profiles are distinguishable over several weeks of starvation in this freshwater amphipod. More importantly these unique metabolites could be used to gain insights into the underlying cause(s) of Diporeia's decline in the Laurentian Great Lakes.
Sailing through the Global Financial Storm: Brazil's recent experience with monetary and macroprudential policies to lean against the financial cycle and deal with systemic risks

Brazil sailed well through the global financial storm, using counter-cyclical policies to engineer its fast V-shaped recovery in 2010. In order to deal with inflationary pressures arising from its strong recovery, after the peak of the crisis, it used standard aggregate demand management instruments (tight fiscal and monetary policies). Brazil had also to deal with the post-QE global environment of excess liquidity in 2010-2011 where excessive capital inflows were exacerbating domestic credit growth with potentially destabilizing effects for price and financial stability. In that front, Brazil maintained and strengthened its strong financial sector regulation and supervision to continue to ensure financial stability, in particular, using a set of macroprudential instruments. While combining monetary and macroprudential instruments to lean against the financial cycle, the Central Bank of Brazil has always made clear that macroprudential measures are not a substitute for monetary policy action and are primarily geared at addressing financial stability risks. In fact, many policy makers after the global financial crisis seem to see now a complementarity between macroprudential measures and monetary policy. Accordingly, the (new) separation principle seems to evolve into using two instruments (the central bank’s base rate and a set of macroprudential tools) to address two objectives (the inflation target and a composite set of financial stability indicators). Brazil’s recent experience with monetary and macroprudential policies is a successful example of this new approach. More time and other countries’ experiences are needed to assess properly if this policy option can be generalized and replicated with similar results elsewhere.
Permutation-free clustering of relative transfer function features for blind source separation

This paper describes an application of relative transfer functions (RTFs) to underdetermined blind source separation (BSS). A clustering-based BSS approach has the advantage that it can even deal with the underdetermined case, where the sources outnumber the microphones. Among others, clustering of a normalized observation vector (NOV) has proven effective for BSS even under reverberation. We here point out that the NOV gives information about RTFs of the dominant source, and hence call it the RTF features. Most of the previous BSS methods are limited in that they undergo significant performance degradation when the number of sources is not known precisely. This paper introduces our recently developed method for joint BSS and source counting based on permutation-free clustering of the RTF features. We demonstrate the effectiveness of the method in experiments with reverberant mixtures of an unknown number of sources with a reverberation time of up to 440 ms.
Seizing the Ethical High Ground: Ethical Reputation Building in Corrupt Environments

We study how ethical behavior by firms leads to ethical reputation building. Based on our in-depth studies of two firms in India and Zimbabwe that resisted corruption and survived for extended time periods, we propose that in addition to behaving ethically, firms need to elicit favorable responses from a critical mass of stakeholders from both strong and weak tie networks in order for their ethical reputations to diffuse quickly and widely. We find that the strength of stakeholder responses to ethical behavior is moderated by firm level and contextual factors: high status affiliations, industry characteristics, the nature of corruption resisted, the presence of a plural press, the potential for collective action, and the presence of an independent judiciary. These antecedents also influence the pattern of stakeholder resource commitments that firms are able to enjoy as a result of having built ethical reputations.
The effect of DC coefficient on mMFCC and mIMFCC for robust speaker recognition

In Speaker Recognition (SR) system, feature extraction is one of the crucial steps where the particular speaker related information is extracted. The state of the art algorithm for this purpose is Mel Frequency Cepstral Coefficient (MFCC), and its complementary feature, Inverted Mel Frequency Cepstral Coefficient (IMFCC). MFCC is based on mel scale and IMFCC is based on inverted mel (imel) scale. There are two another set of features we proposed as mMFCC and mIMFCC. In state-of-the-art system, we neglect the DC co-efficient of DCT from the feature set. In this paper, the DC coefficient and its effect on recognition accuracy on MFCC-IMFCC, as well as, mMFCC-mIMFCC has been studied. This has been verified on two standard different types of databases, like, YOHO for clean speech signal and POLYCOST for telephone based speech. The recognition accuracy of the proposed feature is better than their respective baseline feature when the DC coefficient was included, as well as, when it was not included.
A chemical screen to identify inducers of the mitochondrial unfolded protein response in C. elegans

We previously showed that inhibition of the mevalonate pathway in C. elegans causes inhibition of protein prenylation, developmental arrest and lethality. We also showed that constitutive activation of the mitochondrial unfolded protein response, UPRmt, is an effective way for C. elegans to become resistant to the negative effects of mevalonate pathway inhibition. This was an important finding since statins, a drug class prescribed to lower cholesterol levels in patients, act by inhibiting the mevalonate pathway, and it is therefore possible that some of their undesirable side effects could be alleviated by activating the UPRmt. Here, we screened a chemical library and identified 4 compounds that specifically activated the UPRmt. One of these compounds, methacycline hydrochloride (a tetracycline antibiotic) also protected C. elegans and mammalian cells from statin toxicity. Methacycline hydrochloride and ethidium bromide, a known UPRmt activator, were also tested in mice: only ethidium bromide significantly activate the UPRmt in skeletal muscles.
Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.