Miracle-dz/UniFAR-FTUs huggingface dataset:
The Congenital Cataract-Linked A2V Mutation Impairs Tetramer Formation and Promotes Aggregation of βB2-Crystallin

β/γ-Crystallins, the major structural proteins in human lens, are highly conserved in their tertiary structures but distinct in the quaternary structures. The N- and C-terminal extensions have been proposed to play a crucial role in mediating the size of β-crystallin assembly. In this research, we investigated the molecular mechanism underlying the congenital hereditary cataract caused by the recently characterized A2V mutation in βB2-crystallin. Spectroscopic experiments indicated that the mutation did not affect the secondary and tertiary structures of βB2-crystallin. The mutation did not affect the formation of βB2/βA3-crystallin heteromer as well as the stability and folding of the heteromer, suggesting that the mutation might not interfere with the protein interacting network in the lens. However, the tetramerization of βB2-crystallin at high protein concentrations was retarded by the A2V mutation. The mutation slightly decreased the thermal stability and promoted the thermal aggregation of βB2-crystallin. Although it did not influence the stability of βB2-crystallin against denaturation induced by chemical denaturants and UV irradiation, the A2V mutant was more prone to be trapped in the off-pathway aggregation process during kinetic refolding. Our results suggested that the A2V mutation might lead to injury of lens optical properties by decreasing βB2-crystallin stability against heat treatment and by impairing βB2-crystallin assembly into high-order homo-oligomers.
Slab morphology in the Cascadia fore arc and its relation to episodic tremor and slip

[1] Episodic tremor and slip (ETS) events in subduction zones occur in the general vicinity of the plate boundary, downdip of the locked zone. In developing an understanding of the ETS phenomenon it is important to relate the spatial occurrence of nonvolcanic tremor to the principal structural elements within the subduction complex. In Cascadia, active and passive source seismic data image a highly reflective, dipping, low‐velocity zone (LVZ) beneath the fore‐arc crust; however, its continuity along the margin is not established with certainty, and its interpretation is debated. In this work we have assembled a large teleseismic body wave data set comprising stations from northern California to northern Vancouver Island. Using stacked receiver functions we demonstrate that the LVZ is well developed along the entire margin from the coast eastward to the fore‐arc basins (Georgia Strait, Puget Sound, and Willamette Valley). Combined with observations and predictions of intraslab seismicity, seismic velocity structure, and tremor hypocenters, our results support the thesis that the LVZ represents the signature of subducted oceanic crust, consistent with thermal‐petrological modeling of subduction zone metamorphism. The location of tremor epicenters along the revised slab contours indicates their occurrence close to but seaward of the wedge corner. Based on evidence for high pore fluid pressure within the oceanic crust and a downdip transition in permeability of the plate interface, we propose a conceptual model for the generation of ETS where the occurrence and recurrence of propagating slow slip and low‐frequency tremor are explained by episodic pore fluid pressure buildup and fluid release into or across the plate boundary.
A novel approach to worm detection systems

Computer worms are a type of malicious malware that prey on networked machines. A number of different detection mechanisms have been presented in the literature to detect worms. However, a common drawback of these mechanisms is that any failure to detect the worms results in damaging the real machines. This study proposes a new approach to detection that goes beyond the currently available signature and behavior-based approaches. In contrast to the traditional worm detection system (WDS) that use signature and behavior-based approaches, our proposed approach is based on detection by the damage caused by worms on dummy machines rather than the real machines. The proposed WDS adds additional security as compared to the currently used systems by allowing worms to conduct their normal behavior in a dummy host, thus protecting the rest of the network from damage. The proposed WDS was designed within a network setting and was capable of sending and receiving files and messages between hosts as part of the overall detection mechanism.
Platelet-activating factor exerts mitogenic activity and stimulates expression of interleukin 6 and interleukin 8 in human lung fibroblasts via binding to its functional receptor

Platelet-activating factor (PAF) is a potent proinflammatory phospholipid mediator of the lung. In this study, we demonstrate that PAF receptor mRNA and protein is expressed by human lung fibroblasts. Interaction of PAF with its specific receptor resulted in increases of tyrosine phosphorylation of several intracellular proteins, indicating that the PAF-receptor might be functionally active. PAF-induced transcription of protooncogenes c-fos and c-jun as well as of interleukin (IL)-6 and IL-8 genes in human fibroblasts. Transcription of the interleukins was followed by secretion of the respective proteins. Moreover, PAF enhanced proliferation of fibroblasts in a concentration-dependent manner. Using signaling inhibitors, we demonstrate that PAF-induced transcription of the c-fos, IL-6, and IL-8 genes, as well as proliferation, require activation of pertussis toxin- sensitive G proteins, tyrosine kinases, and protein kinase C (PKC). In contrast, transcription of c-jun was blocked by pertussis toxin, but not by inhibitors for tyrosine kinases or PKC. These data suggest that PAF stimulates distinct signaling pathways in human lung fibroblasts. In addition, the activation of human fibroblasts by PAF leads to enhanced proliferation and to the expression of proinflammatory cytokines, which may contribute to the pathophysiological changes in pulmonary inflammation.
Computing Fractional Bayes Factor Using the Generalized Savage-dickey Density Ratio 1

A computing method of fractional Bayes factor (FBF) for a point null hypothesis is explained. We propose alternative form of FBF that is the product of density ratio and a quantity using the generalized Savage-Dickey density ratio method. When it is diicult to compute the alternative form of FBF analytically, each term of the proposed form can be estimated by MCMC method. Finally, two examples are given.
4CC: A Framework for Managing Software Product Development

Abstract Managing software product development is challenging, especially for small companies in which a balance has to be struck between development flexibility and management control while working under tight schedule and resource constraints. While there exists several approaches to software process improvement, such as the CMM and SPICE reference frameworks, these models focus on the software process for customer projects in large organizations. Small product-oriented companies require a more holistic and practical view to software engineering management that combines business and development considerations and has a clear product focus. This article presents a general framework for managing software product development in small organizations. The framework combines business and process management through four cycles of control: (1) strategic release management provides the interface between business management and product development; (2) release project management handles the development of individual product versions; (3) iteration management deals with the incremental development of product functionality within release projects, and, (4) mini-milestones are used for daily or weekly task scheduling and monitoring to get an indication of system status during development. The framework can be used both to assess the current state of development in the organization, as well as a blueprint for improving or reengineering product development management.
Coordination by Hierarchical Negotiation within an Enterprise Network

Organization of a project within an Enterprise network raises several key issues in terms of decision and execution control. The distributed nature of the network requires a high level of autonomy in taking decisions and executing tasks, while operational efficiency calls for an optimal use of human and physical resources, and for efficient coordination mechanisms. The different business units involved in the network are analyzed as a hierarchical multiagent system. The task dispatching mechanism relies on an automated negotiation process between the project leader and potential task executers. Network and project entities are represented as UML objects whose dynamic evolution is managed through workflow mechanism. Such a meta-model of hierarchical negotiation and coordination can be used for organizing activities in production complexes such as networks of petroleum reservoirs.
Community structure affects trophic ontogeny in a predatory fish

Abstract While most studies have focused on the timing and nature of ontogenetic niche shifts, information is scarce about the effects of community structure on trophic ontogeny of top predators. We investigated how community structure affects ontogenetic niche shifts (i.e., relationships between body length, trophic position, and individual dietary specialization) of a predatory fish, brown trout (Salmo trutta). We used stable isotope and stomach content analyses to test how functional characteristics of lake fish community compositions (competition and prey availability) modulate niche shifts in terms of (i) piscivorous behavior, (ii) trophic position, and (iii) individual dietary specialization. Northern Scandinavian freshwater fish communities were used as a study system, including nine subarctic lakes with contrasting fish community configurations: (i) trout‐only systems, (ii) two‐species systems (brown trout and Arctic charr [Salvelinus alpinus] coexisting), and (iii) three‐species systems (brown trout, Arctic charr, and three‐spined sticklebacks [Gasterosteus aculeatus] coexisting). We expected that the presence of profitable small prey (stickleback) and mixed competitor–prey fish species (charr) supports early piscivory and high individual dietary specialization among trout in multispecies communities, whereas minor ontogenetic shifts were expected in trout‐only systems. From logistic regression models, the presence of a suitable prey fish species (stickleback) emerged as the principal variable determining the size at ontogenetic niche shifts. Generalized additive mixed models indicated that fish community structure shaped ontogenetic niche shifts in trout, with the strongest positive relationships between body length, trophic position, and individual dietary specialization being observed in three‐species communities. Our findings revealed that the presence of a small‐sized prey fish species (stickleback) rather than a mixed competitor–prey fish species (charr) was an important factor affecting the ontogenetic niche‐shift processes of trout. The study demonstrates that community structure may modulate the ontogenetic diet trajectories of and individual niche specialization within a top predator.
A biophysical model of kiwifruit (Actinidia deliciosa) berry development

A model of kiwifruit berry development is presented, building on the model of Fishman and Génard used for peach fruit. That model has been extended to incorporate a number of important features of kiwifruit growth. First, the kiwifruit berry is attached to the stem through a pedicel/receptacle complex which contributes significantly to the hydraulic resistance between the stem and the fruit, and this resistance changes considerably during the season. Second, much of the carbohydrate in kiwifruit berries is stored as starch until the fruit matures late in the season, when the starch hydrolyses to soluble sugars. This starch storage has a major effect on the osmotic potential of the fruit, so an existing model of kiwifruit starch dynamics was included in the model. Using previously published approaches, we also included elasticity and extended the modelling period to cover both the cell division and cell expansion phases of growth. The resulting model showed close simulation of field observations of fresh weight, dry matter, starch, and soluble solids in kiwifruit. Comparison with continuous measurements of fruit diameter confirmed that elasticity was needed to adequately simulate observed diurnal variation in fruit size. Sensitivity analyses suggested that the model is particularly sensitive to variation in inputs relating to water (stem water potential and the humidity of the air), and to parameters controlling cell expansion (cell wall extensibility). Some limitations in the model structure were identified, suggesting that a revised model including current apoplastic/symplastic concepts needs to be developed.
Caveat Mercator in Electronic Commerce : A Gaming Example

Electronic commerce has opened new opportunities for buyers and sellers. Consumers can do things in an on-line environment that are simply not possible in face-to-face transactions. In this paper we examine a novel setting where consumers can gain a dramatic advantage over a seller of an on-line service. Recently on-line casino gaming has appeared on the Internet. One game offered is blackjack – a game known to have a positive expected value for the player if played optimally. In on-line casino gambling, one can employ computer-assisted play and optimal betting with impunity, both of which are not permitted in real casinos. This paper formulates and solves the optimal blackjack betting problem – a problem not adequately solved in the literature. This problem is exceedingly hard to solve for realistic settings. We propose and test a number of solution strategies. Please do not copy or quote without permission from an author.
An LALR Extension for DCGs in Dynamic Programming

We propose a parsing model for DCGs. Our work embodies in a common frame a dynamic programming construction developed for logical push-down automata, and techniques that restrict the computation to a useful part of the search space, inspired by LALR parsing. Unlike preceding approaches, our proposal avoids backtracking in all cases, providing computational sharing and operational completeness for DCGs without functional symbols.
A Variational Bayesian approach for the Joint Detection Estimation of Brain Activity in functional MRI

Nous abordons dans cet article le probleme de la detection-estimation jointe de l'activite cerebrale en IRM fonctionnelle. Pour ce faire, nous adoptons le cadre JDE d'eveloppe dans [1] et etendu dans [2] avec un modele de champ de Markov cache afin de considerer les dependances spatiales entre les voxels. Cette extension est essentielle mais induit une grande complexite operatoire qui a ete contournee dans [2] en utilisant des methodes de simulation stochastique (MCMC) qui sont tres couteuses en temps de calcul. Nous proposons ici une alternative pour lever cette limitation en reformulant le cadre JDE en un probleme a donnees manquantes en utilisant pour l'inference un algorithme EM dans lequel nous mettons en oeuvre des techniques d'approximation variationnelle. Des illustrations sur des donnees artificielles realistes montrent que l'algorithme EM variationnel permet de d'epasser les performances de l'approche MCMC.
Entity Disambiguation for Multi-Source Knowledge Discovery

This paper describes the experimental results of applying a new approach for entity disambiguation in large Resource Description Framework (RDF) triple stores. Our approach combines data mining algorithms and the application of domain rules to reduce the ambiguity in large RDF graphs derived from real-world observational event data. Initial results have shown that significant reductions in ambiguity are achievable when combining data mining along multiple dimensions with domain rules that narrow that entity space that is necessary to disambiguate. The data mining algorithms incorporate relational, social network and process feature sets to compute proximity scores between pairs of entities. The application of domain rules is used to identify high-confidence distinct entities. Combining these methods will improve the quality, fidelity and utility of large-scale RDF graphs derived from real-world data. Our approach avoids the traditional manually intensive and time-consuming process of developing a rule base for inferring missing relationships and resolving ambiguous entities.
Identification of mercurian volcanism: Resolution effects and implications for MESSENGER

Abstract— The possibility of volcanism on Mercury has been a topic of discussion since Mariner 10 returned images of half the planet's surface showing widespread plains material. These plains could be volcanic or lobate crater ejecta. An assessment of the mechanics of the ascent and eruption of magma shows that it is possible to have widespread volcanism, no volcanism on the surface whatsoever, or some range in between. It is difficult to distinguish between a lava flow and lobate crater ejecta based on morphology and morphometry. No definite volcanic features have been identified on Mercury. However, known lunar volcanic features cannot be identified in images with similar resolutions and viewing geometries as the Mariner 10 dataset. Examination of high‐resolution, low Sun angle Mariner 10 images reveals several features which are interpreted to be flow fronts; it is unclear if these are volcanic flows or ejecta flows. This analysis implies that a clear assessment of volcanism on Mercury must wait for better data. MESSENGER (MErcury: Surface, Space ENvironment, GEochemistry, Ranging) will take images with viewing geometries and resolutions appropriate for the identification of such features.
A Semi-Automated Pipeline for the Segmentation of Rhesus Macaque Hippocampus: Validation across a Wide Age Range

This report outlines a neuroimaging pipeline that allows a robust, high-throughput, semi-automated, template-based protocol for segmenting the hippocampus in rhesus macaque (Macaca mulatta) monkeys ranging from 1 week to 260 weeks of age. The semiautomated component of this approach minimizes user effort while concurrently maximizing the benefit of human expertise by requiring as few as 10 landmarks to be placed on images of each hippocampus to guide registration. Any systematic errors in the normalization process are corrected using a machine-learning algorithm that has been trained by comparing manual and automated segmentations to identify systematic errors. These methods result in high spatial overlap and reliability when compared with the results of manual tracing protocols. They also dramatically reduce the time to acquire data, an important consideration in large-scale neuroradiological studies involving hundreds of MRI scans. Importantly, other than the initial generation of the unbiased template, this approach requires only modest neuroanatomical training. It has been validated for high-throughput studies of rhesus macaque hippocampal anatomy across a broad age range.
Time domain multiplexed TAM: implementation and comparison

One of the difficult problems which core-based system-on-chip (SoC) designs face is test access. For testing the cores in a SoC, a special mechanism is required, since they are not directly accessible via chip inputs and outputs. In this paper we introduce a novel Test Access Mechanism (TAM) based on time domain multiplexing (TDM-TAM). This TAM is P1500 compatible and uses a P1500 wrapper The TAM characteristics are its flexibility, scalability, and reconfigurability. The proposed TAM is compared with two other approaches: a serial threading approach analogous to the IEEE] 149.1 standard (Serial TAM) and a packet-switching test network (NIMA). A network-processing engine SoC is used as a platform to compare the different TAMs. Results show that in most cases, TDM is the most effective TAM in both test time and overhead area.
On the Projection of PLLRs for Unbounded Feature Distributions in Spoken Language Recognition

The so called Phone Log-Likelihood Ratio (PLLR) features have been recently introduced as a novel and effective way of retrieving acoustic-phonetic information in spoken language and speaker recognition systems. In this letter, an in-depth insight into the PLLR feature space is provided and the multidimensional distribution of these features is analyzed in a language recognition system. The study reveals that PLLR features are confined into a subspace that strongly bounds PLLR distributions. To enhance the information retrieved by the system, PLLR features are projected into a hyper-plane that provides a more suitable representation of the subspace where the features lie. After applying the projection method, PCA is used to decorrelate the features. Gains attained on each step of the proposed approach are outlined and compared to simple PCA projection. Experiments carried out on NIST 2007, 2009 and 2011 LRE datasets demonstrate the effectiveness of the proposed method, which yields up to a 27% relative improvement with regard to the system based on the original features.
On the classification of degree 1 elliptic threefolds with constant $j$-invariant

We describe the possible Mordell-Weil groups for degree 1 elliptic threefold with rational base and constant $j$-invariant. Moreover, we classify all such elliptic threefolds if the $j$-invariant is nonzero. We can use this classification to describe a class of singular hypersurfaces in $\Ps(2,3,1,1,1)$ that admit no variation of Hodge structure.
Spectral registration of volume data for 6-DOF spatial transformations plus scale

This paper presents a robust spectral based 6 Degrees Of Freedoms (DOF) registration method for 3D data which is in addition capable to determine the scaling of the registered object. The principle is based on decoupling 3D rotation from 3D translation by a corresponding resampling process of the spectral magnitude using a 3D Fast Fourier Transform (FFT), a SO(3) Fourier transform and an integrated Mellin transform for a scale determination. The registration is then subsequently carried out, first the registration of rotation is done, in a second step the scale is determined and finally the translation is calculated. Results are presented with generated test series on public available data and data recorded with Laser Range Finders (LRF). Furthermore one example of a scan pair recorded under realistic conditions showing the robustness of this method is given.
Early cortical specialization for face-to-face communication in human infants

This study examined the brain bases of early human social cognitive abilities. Specifically, we investigated whether cortical regions implicated in adults' perception of facial communication signals are functionally active in early human development. Four-month-old infants watched two kinds of dynamic scenarios in which a face either established mutual gaze or averted its gaze, both of which were followed by an eyebrow raise with accompanying smile. Haemodynamic responses were measured by near-infrared spectroscopy, permitting spatial localization of brain activation (experiment 1), and gamma-band oscillatory brain activity was analysed from electroencephalography to provide temporal information about the underlying cortical processes (experiment 2). The results revealed that perceiving facial communication signals activates areas in the infant temporal and prefrontal cortex that correspond to the brain regions implicated in these processes in adults. In addition, mutual gaze itself, and the eyebrow raise with accompanying smile in the context of mutual gaze, produce similar cortical activations. This pattern of results suggests an early specialization of the cortical network involved in the perception of facial communication cues, which is essential for infants' interactions with, and learning from, others.