Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of G Protein α (Gα) Signaling by the Regulator of G Protein Signaling 14 (RGS14)*

Background: RGS14 binds distinct forms of active and inactive Gα proteins through its RGS domain and GPR motif. Results: Inactive Gαi1-GDP binding of the GPR motif does not preclude RGS action on active Gαo-GTP. Conclusion: RGS14 simultaneously binds active Gαo and inactive Gαi1 while retaining GAP activity. Significance: These findings clarify our understanding of how RGS14 integrates signaling by distinct G protein subunits. RGS14 contains distinct binding sites for both active (GTP-bound) and inactive (GDP-bound) forms of Gα subunits. The N-terminal regulator of G protein signaling (RGS) domain binds active Gαi/o-GTP, whereas the C-terminal G protein regulatory (GPR) motif binds inactive Gαi1/3-GDP. The molecular basis for how RGS14 binds different activation states of Gα proteins to integrate G protein signaling is unknown. Here we explored the intramolecular communication between the GPR motif and the RGS domain upon G protein binding and examined whether RGS14 can functionally interact with two distinct forms of Gα subunits simultaneously. Using complementary cellular and biochemical approaches, we demonstrate that RGS14 forms a stable complex with inactive Gαi1-GDP at the plasma membrane and that free cytosolic RGS14 is recruited to the plasma membrane by activated Gαo-AlF4−. Bioluminescence resonance energy transfer studies showed that RGS14 adopts different conformations in live cells when bound to Gα in different activation states. Hydrogen/deuterium exchange mass spectrometry revealed that RGS14 is a very dynamic protein that undergoes allosteric conformational changes when inactive Gαi1-GDP binds the GPR motif. Pure RGS14 forms a ternary complex with Gαo-AlF4− and an AlF4−-insensitive mutant (G42R) of Gαi1-GDP, as observed by size exclusion chromatography and differential hydrogen/deuterium exchange. Finally, a preformed RGS14·Gαi1-GDP complex exhibits full capacity to stimulate the GTPase activity of Gαo-GTP, demonstrating that RGS14 can functionally engage two distinct forms of Gα subunits simultaneously. Based on these findings, we propose a working model for how RGS14 integrates multiple G protein signals in host CA2 hippocampal neurons to modulate synaptic plasticity.
An Investigation of National Culture's Influence on Relationship and Knowledge Resources in Interorganizational Relationships between Japan and the United States

The increasing globalization of business has heightened the importance of understanding national cultural influences in interorganizational relationships from both a cross-cultural and an intercultural perspective. The authors use Hofstede's (2001) multidimensional national cultural framework to theorize differences in the relationships between key firm resources. Specifically, they explore relationship resources (i.e., the influence of trust on commitment), knowledge resources (i.e., the influence of information sharing on problem resolution), and their linkage (i.e., the influence of commitment on information sharing) both cross-culturally and interculturally from the perspective of Japanese and U.S. firms. The authors use a sample of Japanese and U.S. firms that report on their primary intra-and intercultural business partners to test the hypotheses. The results indicate that national culture influences relationship resources (i.e., the relationship between trust and commitment) and the linkage of relationship resources to knowledge resources (i.e., the relationship between commitment and information sharing). The authors address implications for both academics and practitioners.
Robust Control of an Islanded Microgrid Under Unbalanced and Nonlinear Load Conditions

This paper presents a robust control strategy for the autonomous operation of a microgrid consisting of electronically coupled distributed generation (DG) units. The DG units are connected to a point of common coupling, and supply a load, which can be unbalanced and/or nonlinear. In practice, the load is usually unknown in terms of network topology and parameters. However, it is assumed that the load current is measurable and bounded. In this case, considering the load current as a measurable disturbance signal, the controller design is formulated to an H∞ optimization problem in order to minimize the adverse impact of harmonics and negative-sequence voltage due to nonlinear and unbalanced loads. The optimization problem is then converted into a convex linear matrix inequality (LMI) condition, which is simply solved using MATLAB LMI toolbox. The performance of the proposed controller is verified using hardware-in-the-loop (HIL) real-time simulations carried out in OPAL-RT technologies. The HIL results show that the proposed controller provides the load with a set of sinusoidal, three-phase balanced voltages despite several unbalanced and nonlinear load conditions.
Interplay between the NADP-Linked Thioredoxin and Glutathione Systems in Arabidopsis Auxin Signaling[C][W]

NADP-linked thioredoxin and glutathione systems are key reduction pathways in living organisms. Based on a genetic approach, this study shows that these pathways interfere with auxin transport and metabolism, defining a link between redox regulation and auxin signaling. Intracellular redox status is a critical parameter determining plant development in response to biotic and abiotic stress. Thioredoxin (TRX) and glutathione are key regulators of redox homeostasis, and the TRX and glutathione pathways are essential for postembryonic meristematic activities. Here, we show by associating TRX reductases (ntra ntrb) and glutathione biosynthesis (cad2) mutations that these two thiol reduction pathways interfere with developmental processes through modulation of auxin signaling. The triple ntra ntrb cad2 mutant develops normally at the rosette stage, undergoes the floral transition, but produces almost naked stems, reminiscent of the phenotype of several mutants affected in auxin transport or biosynthesis. In addition, the ntra ntrb cad2 mutant shows a loss of apical dominance, vasculature defects, and reduced secondary root production, several phenotypes tightly regulated by auxin. We further show that auxin transport capacities and auxin levels are perturbed in the mutant, suggesting that the NTR-glutathione pathways alter both auxin transport and metabolism. Analysis of ntr and glutathione biosynthesis mutants suggests that glutathione homeostasis plays a major role in auxin transport as both NTR and glutathione pathways are involved in auxin homeostasis.
Asymmetric Contribution of the Conserved Disulfide Loop to Subunit Oligomerization and Assembly of the Nicotinic Acetylcholine Receptor*

The acetylcholine receptor (AChR) at the motor synapse is a pentamer of homologous subunits with the composition α2βγδ. Owing to the circular arrangement of subunits that forms a central ion channel, each subunit interface contains contributions from opposite faces of each subunit, designated + and −. Common to all subunits of the AChR and members of its superfamily is a disulfide loop formed between cysteines 128 and 142 of the major extracellular domain. To gain insight into the structural contribution of the disulfide loop and its possible location, we mutated the invariant proline at position 136 to glycine (P136G) and examined subunit assembly. When introduced into any AChR subunit, P136G disrupted assembly by affecting the − face of the subunit, suggesting equivalent positioning of the loop in each subunit and localization to the − face. Also, the contribution of the loop in the overall assembly process differed for each subunit. In the β and γ subunits, P136G prevented assembly of higher order heteroligomers, whereas in the α and δ subunits, P136G prevented transport of assembled pentamers to the cell surface. The results demonstrate asymmetry in the contribution of the disulfide loop to formation of subunit interfaces, and that the loop in each subunit contributes at different stages of assembly.
Laughter: Nature's Epileptoid Catharsis

The ability to laugh, like other favored behavioral traits, may have evolved over many generations in response to environmental stresses favoring reproduction among successfully adapted people. This speculative overview depicts laughter as a symbolically-triggered release mechanism that unleashes instinctive drive energies associated with survival, in the process lowering anxiety. The use of humor to trigger the laugh reflex has become a cultural activity in which unacceptable impulses are expressed in an acceptable manner. As this occurs, there is an emancipatory release of repressed energies and assorted conflicts are “resolved. ” An attempt is made to examine the neurological events of laughter; here, there is a suspension of cortical-diencephalic inhibitory control, and tensions are discharged from lower centers, the presumed custodians for some of the encoded programs of instinct and emotion.
Coalition formation for cooperative spectrum sharing in cognitive radio wireless networks using Gale Shapley algorithm

In this paper we consider the problem of increasing the throughput of cognitive radio in a cognitive radio network by forming coalitions among cognitive radio users. Recently there have been numerous studies exploring the benefits of the cooperation in a cognitive radio network. The cooperation tends to increase the spectrum sensing performance which in turn results in increased transmission opportunities. In this paper we use the concepts from matching theory, specifically we use gale-shapely algorithm, to form the coalition among cognitive radio user for collaborative spectrum sensing under target detection probability constraint. In the proposed model we modify gale-shapely algorithm for the cognitive radio users to form coalitions of varying size to increase their individual gains (.e.g. throughput and probability of false alarm). We show using simulation that using the modified gale shapely algorithm for coalition formation yields significant gains in term of reduced false alarm probability and increased throughput per cognitive radio user as compared to non-cooperative cognitive radio user.
Determination of picomolar concentrations of proteins using novel amino reactive chameleon labels and capillary electrophoresis laser‐induced fluorescence detection

Py‐1 and Py‐6 are novel amino‐reactive fluorescent reagents. The names given to them reflect that they consist of a pyrylium group attached to small aromatic moieties. Upon reaction with a primary amine there is a large spectral shift in the reagent, rendering them effectively fluorogenic. In this study, these reagents were used to label a test protein, (human serum albumin), and the sample was analyzed by capillary electrophoresis and laser‐induced fluorescence detection. Detection limits after a 60 min labeling reaction at 22°C (Py‐1) and 50°C (Py‐6) were 6.5 ng/mL (98 pM) for Py‐1 and 1.2 ng/mL (18 pM) for Py‐6. Separation of immunoglobulin G (IgG), human serum albumin, lipase, and myoglobin after labeling with Py‐6 were performed. The method was further modified to make it amenable to automation. Unlike many other amino reactive reagents used to label protein amino groups, reaction with Py‐1 and Py‐6 do not alter the charge of the protein and the advantage of this with respect to electrophoretic separations is discussed.
Variable-Bit-Rate Transmission Schedule Generation in Green Vehicular Roadside Units

Smart traffic scheduling can be used to reduce downlink roadside unit (RSU) energy use in green vehicular roadside infrastructure. In this paper, we consider the problem of downlink schedule generation when the RSU-to-vehicle radios use a variable bit rate (VBR) air interface. We first present offline scheduling formulations that provide lower bounds on the energy required to fulfill vehicle requests. An integer linear program is introduced that can be solved to find optimal offline VBR time slot schedules. We then prove that this problem is NP-complete by a reduction from the well-known Santa Claus problem. Two flow-graph-based models are then used to solve the minimum energy VBR scheduling problem. The first uses generalized flow (GF) graphs that represent time slots as individual graph nodes. The second uses time-expanded graphs (TEGs) that model the temporal evolution of the system. Both of these models can be used to compute lower bounds on energy performance and provide the basis for energy-efficient online schedulers. The first scheduler introduced, i.e., First-Come First-Serve (FCFS), is very simple and treats all vehicles equally and in the order of arrival. Since the time spent in energy-favorable locations decreases with higher vehicle speed, the second scheduler, i.e., Fastest First (FF), gives priority to faster moving vehicles. The greedy GF (G-GF) and greedy TEG (G-TEG) schedulers are then introduced, which are motivated by the two flow-graph-based models. The proposed algorithm performance is examined under different traffic scenarios, and they are found to perform well compared with the lower bound. Our results show that the less computationally intensive algorithms, i.e., FCFS and FF, can perform well under light load, but G-GF and G-TEG, while more complex, can provide near-optimal energy consumption and with reasonable demand dropping rates. The results also show that the G-GF and G-TEG algorithms are much more fair than the simpler algorithms in heavy-load situations.
The North-South divide and house price islands: the case of CÓrdoba (Spain)

This paper uses the theory of hedonic prices for housing services. The classical approach in this field of urban economics is the monocentric model. The model is often criticized due to the restrictiveness of its assumptions. The most important hypothesis is that the rental value per unit of housing service declines with the distance from the central business district (CBD). We consider some other physical and geographical information in an econometric model for the estimation of house prices. The results indicate that the most significant variables are the physical attributes of the houses and the existence of North-South differences.
An accurate segmentation method for white blood cell images

A part of our research work on an Automated Cell Count project is described. A major requirement for this project is an efficient method to segment cell images. This work presents an accurate segmentation method for an automatic count of white blood cells. First a simple thresholding approach is applied to give initial labels to pixels in the blood cell images. The algorithm is based on priori information about blood smear images. Then the labels are adjusted with a shape detection method based on large regional context information to produce meaningful results. This approach makes use of knowledge of the blood cell structure. The experimental result shows that this method is more powerful than traditional methods that use only local context information. It can perform accurate segmentation of white blood cells even if they have unsharp boundaries.
Dynamic Composition of Functionalities of Networked Devices in the Semantic Web. (Composition Dynamique de Functionnalités de Dispositifs en Réseau dans le Web Sémantique)

In opportunistic networks — which topology is dynamic — of smart devices, we address the problem of looking for functionalities and of building a composition of functionalities with a logical description of the devices. We define a first order logic language in which the devices, their functionalities and their properties are expressed using taxonomies of classes to constrain the type of resources. We jointly define a query language based on the description language, allowing us to use a reasoner like P ROLOG to answer to the queries. Those answers are instanciations of the variables of interest which belong to the query. They represent composed functionalities. Next, to deal with the dynamicity of the network, the platform S OME W HERE — that make reasoning in propositional logic in a totally distributed manner — is used as a lookup service retrieving a subset of resources which descriptions are necessary to obtain all the answers to a certain query. For that purpose, we use an encoding of the descriptions and of the query, both written in first order logic, into propositional logic so that some good properties of the descriptions are kept.
Detection of breathing segments in respiratory signals

The typical approach for analysis of respiratory records consists of detection of respiratory pauses and elimination of segments corrupted by movement artifacts. This is motivated by established rules used for manual scoring of respiratory events, which focus on pause segmentation and do not define criteria to identify breathing segments. With this strategy, breathing segments can only be inferred indirectly from the absence of abnormalities, yielding an unclear and ambiguous definition. In this work we present novel detectors for synchronous and asynchronous breathing, and compare them with AUREA, a novel system for Automated Unsupervised Respiratory Event Analysis, which performs indirect classification of breathing. Results from analysis of real infant respiratory data show an improvement in the identification of synchronous and asynchronous breathing of 9% and 27% respectively, demonstrating that direct detection of breathing enhances the classification performance.
Foreign Direct Investment and Exports: Complementarity or Substitutability An Empirical Investigation

The relationship between trade and direct investment, which is one of the main features of globalization, is complex and cannot be deducted from a purely theoretical analysis. The present paper seeks to lay the analytical foundation that would define the nature of the relationship – be it complementary or substitutive - between exports and foreign direct investment (FDI). The purpose of our use of disaggregate sectoral database is to explore these issues econometrically while analyzing and decomposing the nature of the relationship between FDI and exports. The estimation results showed a complementary effect or a ripple effect between exports and FDI at the macro level for both manufactured and non-manufacturing sectors. Our findings have also been supported by predominant literature which finds positive relationships between FDI and exports.
Adversarial Auto-Encoders for Speech Based Emotion Recognition

Recently, generative adversarial networks and adversarial autoencoders have gained a lot of attention in machine learning community due to their exceptional performance in tasks such as digit classification and face recognition. They map the autoencoder's bottleneck layer output (termed as code vectors) to different noise Probability Distribution Functions (PDFs), that can be further regularized to cluster based on class information. In addition, they also allow a generation of synthetic samples by sampling the code vectors from the mapped PDFs. Inspired by these properties, we investigate the application of adversarial autoencoders to the domain of emotion recognition. Specifically, we conduct experiments on the following two aspects: (i) their ability to encode high dimensional feature vector representations for emotional utterances into a compressed space (with a minimal loss of emotion class discriminability in the compressed space), and (ii) their ability to regenerate synthetic samples in the original feature space, to be later used for purposes such as training emotion recognition classifiers. We demonstrate the promise of adversarial autoencoders with regards to these aspects on the Interactive Emotional Dyadic Motion Capture (IEMOCAP) corpus and present our analysis.
Incorporating Asset Liquidity Effects in Risk-Capital Modeling

Recent turmoil in financial markets endorses the need for rigorous handling and integration of asset liquidity risk into Value-at-Risk (VaR) models. In this work we develop and test measures of certain kinds of asset liquidity risk that is useful for completing the definition of market risk and for predicting liquidity-adjusted VaR under adverse market conditions. This paper presents a practical simulation framework for the modeling of asset liquidity risk for portfolios that consist of multiple long and short trading assets. We put forward a method whereby the holding periods are adjusted according to the specific needs of each trading portfolio by explicitly modeling a linearly-distributed liquidation scheme by means of a pertinent scaling multiplier. The empirical testing is achieved using daily return data of emerging Gulf-Cooperation-Council (GCC) stock markets. We simulate and analyze different relevant portfolios (of both long and short-sales trading positions) and determine the risk-capital exposure under varied illiquid and adverse market conditions.
Genomic characterization of human papillomavirus-positive and -negative human squamous cell cancer cell lines

Human cancer cell lines are the most frequently used preclinical models in the study of cancer biology and the development of therapeutics. Although anatomically diverse, human papillomavirus (HPV)-driven cancers have a common etiology and similar mutations that overlap with but are distinct from those found in HPV-negative cancers. Building on prior studies that have characterized subsets of head and neck squamous cell carcinoma (HNSCC) and cervical squamous cell carcinoma (CESC) cell lines separately, we performed genomic, viral gene expression, and viral integration analyses on 74 cell lines that include all readily-available HPV-positive (9 HNSCC, 8 CESC) and CESC (8 HPV-positive, 2 HPV-negative) cell lines and 55 HPV-negative HNSCC cell lines. We used over 700 human tumors for comparison. Mutation patterns in the cell lines were similar to those of human tumors. We confirmed HPV viral protein and mRNA expression in the HPV-positive cell lines. We found HPV types in three CESC cell lines that are distinct from those previously reported. We found that cell lines and tumors had similar patterns of viral gene expression; there were few sites of recurrent HPV integration. As seen in tumors, HPV integration did appear to alter host gene expression in cell lines. The HPV-positive cell lines had higher levels of p16 and lower levels of Rb protein expression than did the HPV-negative lines. Although the number of HPV-positive cell lines is limited, our results suggest that these cell lines represent suitable models for studying HNSCC and CESC, both of which are common and lethal.
Innovation ecology as a precursor to entrepreneurial growth

Purpose – The purpose of this paper is to examine the governmental, economic, and technological factors contributing to a country's innovation ecology that have an impact on sustainable economic growth.Design/methodology/approach – This paper investigates governmental, economic, and technological supports that comprise the innovation ecology of 34 nations using ordinary least squares, discriminant analysis, and mediated regression. It is proposed that the strength of a country's innovation ecology is associated with greater sustainable entrepreneurial growth opportunities. Innovation indicators and trend analyses were collected from Eurostat Yearbook 2007, Science and Technology, and Global Financial Data over the 1995‐2005 period.Findings – The results reveal that while the influence of government and the economic environment encourage innovation ecology, having resources at the research and development levels, human capital, and early seed funding were key indicators of innovation. The greater the degre.