Miracle-dz/UniFAR-FTUs huggingface dataset:
IC-Tagging and Protein Relocation to ARV muNS Inclusions: A Method to Study Protein-Protein Interactions in the Cytoplasm or Nucleus of Living Cells

Background Characterization of protein-protein interactions is essential for understanding cellular functions. Although there are many published methods to analyze protein-protein interactions, most of them present serious limitations. In a different study we have characterized a novel avian reovirus muNS-based protein tagging and inclusion targeting method, and demonstrated its validity to purify free an immobilized protein. Methodology/Principal Findings Here we present a method to identify protein-protein interactions inside living eukaryotic cells (tested in primate and avian cells). When p53 was tagged with Intercoil (IC; muNS residues 477–542), it not only got integrated into muNS cytoplasmic inclusions, but also attracted its known ligand SV40 large T antigen (TAg) to these structures. We have also adapted this system to work within the cell nucleus, by creating muNS-related protein chimeras that form nuclear inclusions. We show that nuclear muNS-derived inclusions are as efficient as cytoplasmic ones in capturing IC-tagged proteins, and that the proteins targeted to nuclear inclusions are able to interact with their known ligands. Conclusions/Significance Our protein redistribution method does not present the architectural requirement of re-constructing a transcription factor as any of the two-hybrid systems do. The method is simple and requires only cell transfection and a fluorescence microscope. Our tagging method can be used either in the cytoplasm or the nucleus of living cells to test protein-protein interactions or to perform functional studies by protein ligand sequestration.
Distributed Systems with Wireless Sensor Networks

Conventional distributed system courses follow a syllabus in which a list of topics is discussed independently and at different levels of abstractions. We propose to use a wireless sensor network environment to pin all topics down to concrete applications and to maintain issues such as fault tolerance and coordination continuously present. We describe a syllabus with eight conceptual modules, each of them associated to a hands-on experience with wireless sensor networks, which may be assigned either as homework or as a hands-on class, depending on the number of classroom hours that are available.
Characterization of submicrometer thickness of copper film on silicon wafer by using pulsed eddy current method

Pulsed eddy current (PEC) method for thickness measurement of metal film has been widely investigated in recent years. In the previous researches, this method has been mainly used in metal thickness measurement in the range from millimeter to centimeter and nondestructive inspection. The effectiveness of the PEC method for measurement of submicrometer thick copper (Cu) film has not been reported. In this experimental study, a prototype transducer based on the PEC principle has been developed for detecting the thickness copper films sputtered on silicon wafer. It has been found that PEC method can be applied to the thickness measurement of copper film down to submicrometer scale.
Strongly Enhanced Inelastic Collisions in a Bose-Einstein Condensate near Feshbach Resonances

The properties of Bose-Einstein condensed gases can be strongly altered by tuning the external magnetic field near a Feshbach resonance. Feshbach resonances affect elastic collisions and lead to the observed modification of the scattering length. However, as we report here, the observed rate of inelastic collisions was strongly enhanced in a sodium Bose-Einstein condensate when the scattering length was tuned to both larger or smaller values than the off-resonant value. These strong losses impose severe limitations for using Feshbach resonances to tune the properties of Bose-Einstein condensates. [S0031-9007(99)08767-0] Most of the properties of Bose-Einstein condensates in dilute alkali gases are dominated by two-body collisions, which can be characterized by the s-wave scattering length a. The sign and the absolute value of the scattering length determine, e.g., stability, internal energy, formation rate, size, and collective excitations of a condensate. Near a Feshbach resonance the scattering length varies dispersively [1,2] covering the whole range of positive and negative values. Thus it should be possible to study strongly interacting, weakly or noninteracting, or collapsing condensates [3], all with the same alkali species and experimental setup. A Feshbach resonance occurs when the energy of a molecular (quasi-) bound state is tuned to the energy of two colliding atoms by applying an external magnetic field. Such resonances have been observed in a BoseEinstein condensate of Na sF › 1, mF › 11) atoms at 853 and 907 G [4,5], and in two experiments with cold clouds of 85 Rb (F › 2, mF › 22) atoms at 164 G [6]. In the sodium experiment, the scattering length a was observed to vary dispersively as a function of the magnetic field B, in agreement with the theoretical prediction [2]:
Perceptually Grounded Selectional Preferences

Selectional preferences (SPs) are widely used in NLP as a rich source of semantic information. While SPs have been traditionally induced from textual data, human lexical acquisition is known to rely on both linguistic and perceptual experience. We present the first SP learning method that simultaneously draws knowledge from text, images and videos, using image and video descriptions to obtain visual features. Our results show that it outperforms linguistic and visual models in isolation, as well as the existing SP induction approaches.
Adaline-based approaches for time-varying frequency estimation in power systems

Abstract Abstract Two new neural approaches for on-line frequency estimation of a sinusoidal signal perturbed by harmonic distortions and random noise are presented in this paper. These approaches are based on an iterative formulation of the signal which is learned by Adaline neural networks. Adalines are very simple and efficient artificial neural networks, they can be easily implemented on a digital signal processor. The proposed approaches are therefore suitable for real-time implementations and their performance and robustness are evaluated by numerical simulations and experimentally under different severe operating conditions. The proposed neural estimators are favorably compared to the classical zero-crossing method, to an active notch filter method, and to a previous Adaline based-method. Furthermore, all these methods are also evaluated in terms of computational costs.
In 8100 Again: The Sounds of Students Breaking

In this article, the author uses the sounds of schooling to explore LGBTQ youth experiences as they relate to self-harm and suicide. Although sounds-as-voice and representation is a well-trodden path in scholarly conversations, the author centers her argument on the significance of sounds in the daily lives of LGBTQ students. This is significant as literature predominantly focuses on the signs of suicide as physical and visual rather than residing in sounded epistemologies. Expanding on previous work on the school-to-coffin pipeline, this article theorizes the sounds of students breaking to explore youth suicide and self-harm as they are nested in the everyday interactions of classrooms and corridors. Using a combination of personal narrative and interviews from a year-long sonic ethnography, the author explores how sounds are an important part of the school-to-coffin pipeline for LGBTQ youth and should therefore be regarded as a significant tool for unpacking some of the darkest experiences and notions learned through schooling- depression, self-harm, and suicide.
Ambition and Jealousy: Income Interactions in the ‘Old’ Europe Versus the ‘New’ Europe and the United States

This paper asks how income distribution affects individual well-being and tries to explore the idea that this relation depends on the degree of mobility and uncertainty in the economy. It mostly concentrates on the relation between satisfaction and reference income (defined as the income of one's professional peers), and hinges on the micro-econometric analysis of household survey data (mostly panel), including subjective attitudinal questions. Using over one million observations, it uncovers a divide, in the perception of income inequality, between "old" -low mobility- European countries on the one hand, and "new" European post-Transition countries and the United States, on the other hand. Whereas "jealousy" is dominant in the former, "ambition" is even stronger in the latter.
Learning to Order Natural Language Texts

Ordering texts is an important task for many NLP applications. Most previous works on summary sentence ordering rely on the contextual information (e.g. adjacent sentences) of each sentence in the source document. In this paper, we investigate a more challenging task of ordering a set of unordered sentences without any contextual information. We introduce a set of features to characterize the order and coherence of natural language texts, and use the learning to rank technique to determine the order of any two sentences. We also propose to use the genetic algorithm to determine the total order of all sentences. Evaluation results on a news corpus show the effectiveness of our proposed method.
Mediation and Moderation of Intergenerational Epigenetic Effects of Trauma

Trauma has been found to exert significant influence on mental and physical health throughout the lifespan. Furthermore, we now know that our experience can influence our genes’ activity with potential to generate effects on development, health, and behavior. This study sought to investigate the potential for trauma experiences to influence gene regulation across generations. Specifically, does the mothers’ trauma history predict DNA methylation or gene expression in her newborn. The results indicate that the mothers’ trauma history can predict DNA methylation and expression in her newborn. Moreover, the type of trauma experienced by the mother generates different influence on gene regulation in her offspring on genes involved in androgen receptors (HOXD4), monitoring protein transport through cells (HSPA5), and neurogenesis and synaptogenesis (BDNF). Further research should consider the potential for historical trauma experiences to influence DNA methylation and gene expression in offspring that could predispose risk or resilience to adversity throughout life.
Delegation-Based Roaming Payment Protocol with Location and Purchasing Privacy Protection

We proposed a new delegation-based roaming payment protocol for portable communication systems (PCS), by leveraging the good performance of blind signature in the regard of user privacy, which can provide unlink ability between PCS and service providers. However, the ability to discover the malicious user's identification is still remained. Home agents can detect the misbehavior and identify the mobile user if she/he doubly spends the e-cash in roaming. Due to the delegation-based authentication, the foreign agent can validate the communication without needing to reveal the real identity of the mobile user. Moreover, the computational cost can be reduced by using elliptic curve operations.
Practice of Epidemiology Bayesian Time-Series Analysis of a Repeated-Measures Poisson Outcome With Excess Zeroes

In this article, the authors demonstrate a time-series analysis based on a hierarchical Bayesianmodel of a Poisson outcomewith an excessive number of zeroes. Themotivating example for this analysis comes from the intensive care unit (ICU) of an urban university teaching hospital (New Haven, Connecticut, 2002–2004). Studies of medication use among older patients in the ICU are complicated by statistical factors such as an excessive number of zero doses, periodicity, and within-person autocorrelation. Whereas time-series techniques adjust for autocorrelation and periodicity in outcome measurements, Bayesian analysis provides greater precision for small samples and the flexibility to conduct posterior predictive simulations. By applying elements of time-series analysis within both frequentist and Bayesian frameworks, the authors evaluate differences in shift-based dosing ofmedication in amedical ICU. From a small sample and with adjustment for excess zeroes, linear trend, autocorrelation, and clinical covariates, both frequentist and Bayesian models provide evidence of a significant association between a specific nursing shift and dosing level of a sedative medication. Furthermore, the posterior distributions from a Bayesian random-effects Poisson model permit posterior predictive simulations of related results that are potentially difficult to model.
An algorithm for image edge detection using improved PCNN

A calculated method is proposed which uses the region areas to modulate the pulse of the corresponding neurons in PCNN. The edge detection for the blurred Image with noise can reduce the noise and obtain a precise edge value of the image. First, based on the analysis of the difference between the edge pixels and the noise pixels, it proposes a method, which suppresses the noise by the region areas. Second, it suggests that image segmentation uses the pulse of the corresponding neurons in PCNN. The experimental results show that this method is effective and feasible.
A swarm intelligence approach to path synthesis of mechanism

Mechanism path synthesis can be viewed as a pattern-matching problem in essence. Some key techniques related to its implementation such as the generation of the training path curves, the digital description of mechanism path and the clustering of path curves are discussed in detail. After generating amounts of training curves, the moment invariants of them are computed, which are defined as the attributes of the curves. By modifying the distance metric in LF model, these moment invariants are clustered based on ant clustering method. When the mechanism corresponding to the expected curve is needed, all the curves are discretized and the problem of pattern matching is solved. All these operations are integrated into a pattern-matching framework for mechanism path synthesis. A practical example of four-bar linkage path synthesis demonstrates that the ant-clustering algorithm is efficient and the proposed method is effective.
Non-linearity and statistics - implications of hormesis on dose-response analysis

In medical applications of statistics, such as drug testing or risk assessment, most investigators usually expects linear dose-response pattern and is rather surprised finding that the effects on some individuals are even opposite than those expected from the assumption of linearity. We provide several examples of the non-linear doseresponse pattern, the phenomenon called hormesis, both chemical and radiation hormesis. We also discuss possible explanation of hormesis based on cybernetic regulation mechanism or on chaotic attractor hypothesis, as well as consequences of hormesis for epidemiology and medical statistics.
Exploiting redundancy in closed-loop inverse kinematics for dexterous object manipulation

In this paper, a kinematic model for motion coordination of a redundant multi-fingered robotic hand is derived, which allows to compute the object pose from the joint variables of each finger as well as from a suitable set of contact variables. Then, a prioritized inverse kinematics scheme with redundancy resolution, both with inverse and transpose Jacobian matrix, is developed. This algorithm can be used for kinematic control as well as a local planning method for dexterous manipulation. A simulation case study is presented to demonstrate the effectiveness of the proposed approach.
Universit a Di Pisa Routing with Minimum Fragmentation Cost Routing with Minimum Fragmentation Cost

One of the greatest diiculties involved in communication networks project is the need to interconnect diierent networks to form a unique internetwork. A major headache is the diiering maximum packet sizes allowed by each network, which causes oversize packets to be broken up into appropriately sized fragments. Unfortunately, the fragmentation process implies additional costs, tightly bounded up with routing and fragmentation strategies in use. The approach commonly used in IP protocols provides two separated functions which operate in a completely indipendent way. This adversely aaects network performance measures, both quantitatively (throughput) and qualitatively (average packet delay), whereas some form of cooperation between the two functions could result in a reduction of this eeciency loss. This paper presents a pseudo-polynomial algorithm for solving the combined fragmentation and routing problem. The method of solution is based on the concept of bicriterion shortest path problem, where two distinct objective functions must be minimized: the path length (in accordance with many classic routing algorithm) and the number of fragments received by the destination host. Besides, the paper deals with the problem of the eeective fragments-hops minimization. An algorithm aimed at this purpose is provided together with the analysis of the possibility to reduce its running time under appropriate considerations on the generated fragment sizes.
A review of hilevel authorized deduplication method for cloud storage system

The data storage management is the biggest problem in the cloud computing environment. To reduce the storing space and save the bandwidth share the data with others in cloud storage using public-key cryptosystems that produce constant-size cipher texts such that the active delegation of decoding rights for any set of cipher texts but it lead to many privacy problems. To avoid this problem the private and public cloud combine and form a hybrid cloud. In this the confidential data can be stored in private cloud and other data are stored in public cloud. Even though, the exponential growth of ever-increasing volume of data in the cloud has raised many storage challenges. To overcome these challenges we proposed a deduplication technique. It is specialized and resent data compression technique which eliminates redundant data as well as improves the cloud storage and bandwidth utilization. We also present several new deduplication constructions which are supporting authorized duplicate check in hybrid cloud architecture. To protect the confidentiality of sensitive data, whereas supporting deduplication, the convergent encryption technique has been proposed to encrypt the data before outsourcing. To provide the highest data security, this paper makes the first attempt to formally address the problem of authorized data deduplication. We also proposed many new deduplication constructions supporting authorized duplicate check in hybrid cloud architecture, which incurs nominal overhead compared to conventional operation.
OBEY: Optimal Batched Refactoring Plan Execution for Class Responsibility Redistribution

The redistribution of class responsibilities is a common reengineering practice in object-oriented (OO) software evolution. During the redistribution, developers frequently construct batched refactoring plans for moving multiple methods and fields among various classes. With an objective of carefully maintaining the cohesion and coupling degree of the class design, executing a batched refactoring plan without introducing any objective-violating side effect into the refactored code is essential. However, using most refactoring engines for batched refactoring plan execution introduces coupling-increasing Middle Man bad smell in the final refactored code and therefore makes the refactoring execution suboptimal in achieving the redistribution objective. This work proposes Obey, a methodology for optimal batched refactoring plan execution. Obey analyzes a batched refactoring plan, identifies Middle Man symptoms that cause suboptimal execution, and renovates the plan for optimal execution. We have conducted an empirical study on three open-source software projects to confirm the effectiveness of Obey in a practical context.
Advanced glycation end‐products increase monocyte adhesion to retinal endothelial cells through vascular endothelial growth factor‐induced ICAM‐1 expression: inhibitory effect of antioxidants

Accumulating evidence indicates a role for advanced glycation end‐products (AGEs) in the development of diabetic retinopathy. In the present study, we examined the in vitro effect of AGEs on human monocyte adhesion to bovine retinal endothelial cells (BRECs) and the molecular mechanisms involved in this effect. Treatment of cultured BRECs with AGEs led to a significant increase in monocyte adhesion and intercellular cell adhesion molecule‐1 (ICAM‐1) expression. These effects were inhibited by antioxidants including gliclazide and vitamins C and E. On the basis of the stimulatory effect of AGEs on vascular endothelial growth factor (VEGF) secretion by retinal endothelial cells, the role of this growth factor as mediator of AGE‐induced monocyte adhesion to BRECs was next investigated. Incubation of BRECs with VEGF increased monocyte adhesion to these cells and enhanced ICAM‐1 expression. Treatment of BRECs with an anti‐VEGF antibody abrogated AGE‐induced monocyte adhesion and ICAM‐1 expression. Finally, incubation of BRECs with protein kinase C (PKC) and nuclear factor (NF)‐κB inhibitors suppressed monocyte adhesion and ICAM‐1 expression elicited by AGEs and VEGF. Taken together, these data indicate that AGEs increase monocyte adhesion to BRECs and that this effect is mediated through VEGF‐induced ICAM‐1 expression. They also demonstrate that this effect is oxidative stress‐sensitive and involves PKC and NF‐κB‐dependent signaling pathways.
A class of hybrid mortar finite element methods for interface problems with non-matching meshes

In this paper, we propose and analyze a family of hybrid finite element methods for interface problems with possibly non-matching meshes. These methods are related to hybrid mixed finite element methods and discontinuous Galerkin methods, as well as Nitsche-type mortaring techniques, but overcome some of the disadvantages of these. By introducing the additional hybrid variable, we obtain methods that allow for subassembling on the subdomain level yielding positive definite global systems. Moreover, the primal unknowns can be eliminated by solving local Dirichlet problems on the subdomains, yielding Schur complement systems for the hybrid variables only. In contrast to dual domain decomposition and mortar methods, the space for the hybrid variable can be chosen with great flexibility without perturbing the stability. We derive the basic a-priori error estimates in energy and L-norm, and confirm the theoretical results by numerical tests.
The Ca2+ Sensor Protein Swiprosin-1/EFhd2 Is Present in Neurites and Involved in Kinesin-Mediated Transport in Neurons

Swiprosin-1/EFhd2 (EFhd2) is a cytoskeletal Ca2+ sensor protein strongly expressed in the brain. It has been shown to interact with mutant tau, which can promote neurodegeneration, but nothing is known about the physiological function of EFhd2 in the nervous system. To elucidate this question, we analyzed EFhd2−/−/lacZ reporter mice and showed that lacZ was strongly expressed in the cortex, the dentate gyrus, the CA1 and CA2 regions of the hippocampus, the thalamus, and the olfactory bulb. Immunohistochemistry and western blotting confirmed this pattern and revealed expression of EFhd2 during neuronal maturation. In cortical neurons, EFhd2 was detected in neurites marked by MAP2 and co-localized with pre- and post-synaptic markers. Approximately one third of EFhd2 associated with a biochemically isolated synaptosome preparation. There, EFhd2 was mostly confined to the cytosolic and plasma membrane fractions. Both synaptic endocytosis and exocytosis in primary hippocampal EFhd2−/− neurons were unaltered but transport of synaptophysin-GFP containing vesicles was enhanced in EFhd2−/− primary hippocampal neurons, and notably, EFhd2 inhibited kinesin mediated microtubule gliding. Therefore, we found that EFhd2 is a neuronal protein that interferes with kinesin-mediated transport.