Miracle-dz/UniFAR-FTUs huggingface dataset:
Early failure characterization of cantilever snap assemblies using the PA-RCBHT

Failure detection and correction is essential in robust systems. In robotics, failure detection has focused on traditional parts assembly, tool breakage, and threaded fastener assembly. However, not much work has focused on sub-mode failure classification. This is an important step in order to provide accurate failure recovery. Our work implemented a novel failure characterization scheme for cantilever snap assemblies. The approach identified exemplars that characterized salient features for specific deviations from a nominal trajectory. Then, a rule based approach with statistical measures was used to identify failure and classify failure sub-modes. Failure sub-mode classification was evaluated by using a reliability measure. Our work classified failure deviations with 88% accuracy. Varying success was experienced in correlating failure deviation modes. Cases with only 1-deviation had 86% accuracy, cases with 2-deviations had 67% accuracy, and cases with 3 deviations had 55% accuracy. Our work is an important step in failure characterization of complex geometrical parts and serves as a stepping stone to enact failure recovery.
TIME: Supporting topology independent mobility with energy efficient routing in WSNs

Wireless sensor networks consist of small battery powered devices with limited energy resources. The small sensor nodes are usually inaccessible to the users due to their remote deployment. Non functioning of any sensor due to its loss of battery power not only deteriorates the network performance but also a challenging job for replacement of energy source. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. The efficiency of sensor networks strongly depends on the routing protocol used. Various clustering algorithms have been proposed in the literature to increase the lifetime of network. In all algorithms data processing is done at the cluster head (CH) which consumes large amount of energy because energy consumption depends upon the distance between the node and the base station (BS). In this paper, Low Energy Adaptive Clustering Hierarchy (LEACH) has been extended by considering the chaining system in different clusters. Our proposed model- Topology Independent Mobility with Energy Efficient Routing algorithm (TIME), reduces the distance between two consecutive nodes and node to base station by using multiple clusters. The Chain Monitor (CM) aggregates all the data of its own cluster and sends to the base station. The performance of TIME algorithm has been investigated by several simulations by considering uniform sensing range of the sensors. From the simulation results it has been observed that even with large sensing range of the sensors the performance of our model TIME is superior than LEACH. The important aspect about this model is achieving uniform energy efficiency of all the sensors in the network irrespective of topological variations, through multiple clustering technique.
SOCS3-Mediated Blockade Reveals Major Contribution of JAK2/STAT5 Signaling Pathway to Lactation and Proliferation of Dairy Cow Mammary Epithelial Cells in Vitro

Suppressor of cytokine signaling 3 (SOCS3) is a cytokine-induced negative feedback-loop regulator of cytokine signaling. More and more evidence has proved it to be an inhibitor of signal transducers and activators of transcription 5 (STAT5). Here, we used dairy cow mammary epithelial cells (DCMECs) to analyze the function of SOCS3 and the interaction between SOCS3 and STAT5a. The expression of SOCS3 was found in cytoplasm and nucleus of DCMECs by fluorescent immunostaining. Overexpression and inhibition of SOCS3 brought a remarkable milk protein synthesis change through the regulation of JAK2/STAT5a pathway activity, and SOCS3 expression also decreased SREBP-1c expression and fatty acid synthesis. Inhibited STAT5a activation correlated with reduced SOCS3 expression, which indicated that SOCS3 gene might be one of the targets of STAT5a activation, DCMECs treated with L-methionine (Met) resulted in a decrease of SOCS3 expression. SOCS3 could also decrease cell proliferation and viability by CASY-TT detection. Together, our findings indicate that SOCS3 acts as an inhibitor of JAK2/STAT5a pathway and disturbs fatty acid synthesis by decreasing SREBP-1c expression, which validates its involvement in both milk protein synthesis and fat synthesis. In aggregate, these results reveal that low SOCS3 expression is required for milk synthesis and proliferation of DCMECs in vitro.
The CRAL/TRIO and GOLD Domain Protein CGR-1 Promotes Induction of Vulval Cell Fates in Caenorhabditis elegans and Interacts Genetically With the Ras Signaling Pathway

Ras-mediated signaling is necessary for the induction of vulval cell fates during Caenorhabditis elegans development. We identified cgr-1 by screening for suppressors of the ectopic vulval cell fates caused by a gain-of-function mutation of the let-60 ras gene. Analysis of two cgr-1 loss-of-function mutations indicates that cgr-1 positively regulates induction of vulval cell fates. cgr-1 is likely to function at a step in the Ras signaling pathway that is downstream of let-60, which encodes Ras, and upstream of lin-1, which encodes a transcription factor, if these genes function in a linear signaling pathway. These genetic studies are also consistent with the model that cgr-1 functions in a parallel pathway that promotes vulval cell fates. Localized expression studies suggest that cgr-1 functions cell autonomously to affect vulval cell fates. cgr-1 also functions early in development, since cgr-1 is necessary for larval viability. CGR-1 contains a CRAL/TRIO domain likely to bind a small hydrophobic ligand and a GOLD domain that may mediate interactions with proteins. A bioinformatic analysis revealed that there is a conserved family of CRAL/TRIO and GOLD domain-containing proteins that includes members from vertebrates and Drosophila. The analysis of cgr-1 identifies a novel in vivo function for a member of this family and a potential new regulator of Ras-mediated signaling.
Public Participation in Local Policy Decision-making: The Role of Web-based Mapping

Abstract New methods of using on-line interactive mapping are reported with a specific focus on how citizens can participate in the delivery and management of everyday services in their neighbourhood. Particular emphasis will be placed on how ICTs can be used to facilitate the regeneration of inner city neighbourhoods through more integrated approaches to spatial data management. The paper examines how internet mapping is used by the public through an interactive Public Participation GIS and illustrates how public access to on-line maps can help deliver improved services to local communities through the integration of GIS with a range of public services. This has raised some interesting issues in relation to how people understand mapping and their methods of navigation using such a system. With governments across the globe investing heavily in e-Government which includes on-line mapping facilities it is interesting to examine how the public actually perceive and use such systems.
Poisson Difference Integer Valued Autoregressive Model of Order one

This paper aims to model integer valued time series with possible negative values and either positive or negative correlations by introducing the Poisson difference integer valued autoregressive model of order one. This model has Poisson difference marginal distribution and is defined by a new operator called the extended binomial thinning operator. It includes previous integer valued autoregressive of order one model as special cases. The model can be used as a tool to model non-stationary count data. The model is applied to data from the Saudi stock exchange.
Characterization of extracellular circulating microRNA

MicroRNAs (miRNAs), a class of post-transcriptional gene expression regulators, have recently been detected in human body fluids, including peripheral blood plasma as extracellular nuclease resistant entities. However, the origin and function of extracellular circulating miRNA remain essentially unknown. Here, we confirmed that circulating mature miRNA in contrast to mRNA or snRNA is strikingly stable in blood plasma and cell culture media. Furthermore, we found that most miRNA in plasma and cell culture media completely passed through 0.22 µm filters but remained in the supernatant after ultracentrifugation at 110 000g indicating the non-vesicular origin of the extracellular miRNA. Furthermore, western blot immunoassay revealed that extracellular miRNA ultrafiltrated together with the 96 kDa Ago2 protein, a part of RNA-induced silencing complex. Moreover, miRNAs in both blood plasma and cell culture media co-immunoprecipited with anti-Ago2 antibody in a detergent free environment. This is the first study to show that extracellular miRNAs are predominantly exosomes/microvesicles free and are associated with Ago proteins. We hypothesize that extracellular miRNAs are in the most part by-products of dead cells that remain in extracellular space due to the high stability of the Ago2 protein and Ago2-miRNA complex. Nevertheless, our data does not reject the possibility that some miRNAs can be associated with exosomes.
An alternate pathophysiologic paradigm of sepsis and septic shock

The advent of modern antimicrobial therapy following the discovery of penicillin during the 1940s yielded remarkable improvements in case fatality rate of serious infections including septic shock. Since then, pathogens have continuously evolved under selective antimicrobial pressure resulting in a lack of significant improvement in clinical effectiveness in the antimicrobial therapy of septic shock despite ever more broad-spectrum and potent drugs. In addition, although substantial effort and money has been expended on the development novel non-antimicrobial therapies of sepsis in the past 30 years, clinical progress in this regard has been limited. This review explores the possibility that the current pathophysiologic paradigm of septic shock fails to appropriately consider the primacy of the microbial burden of infection as the primary driver of septic organ dysfunction. An alternate paradigm is offered that suggests that has substantial implications for optimizing antimicrobial therapy in septic shock. This model of disease progression suggests the key to significant improvement in the outcome of septic shock may lie, in great part, with improvements in delivery of existing antimicrobials and other anti-infectious strategies. Recognition of the role of delays in administration of antimicrobial therapy in the poor outcomes of septic shock is central to this effort. However, therapeutic strategies that improve the degree of antimicrobial cidality likely also have a crucial role.
Journal of Modern Applied Statistical Methods Robust Regression Analysis for Non-normal Situations under Symmetric Distributions Arising in Medical Research Robust Regression Analysis for Non-normal Situations under Symmetric Distributions Arising in Medical Research

In medical research, while carrying out regression analysis, it is usually assumed that the independent (covariates) and dependent (response) variables follow a multivariate normal distribution. In some situations, the covariates may not have normal distribution and instead may have some symmetric distribution. In such a situation, the estimation of the regression parameters using Tiku's Modified Maximum Likelihood (MML) method may be more appropriate. The method of estimating the parameters is discussed and the applications of the method are illustrated using real sets of data from the field of public health.
Dynamic sprites: artistic authoring of interactive animations

Traditional methods for creating dynamic objects and characters from static drawings involve careful tweaking of animation curves and/or simulation parameters. Sprite sheets offer a more drawing‐centric solution, but they do not encode timing information or the logic that determines how objects should transition between poses and cannot generalize outside the given drawings. We present an approach for creating dynamic sprites that leverages sprite sheets while addressing these limitations. In our system, artists create a drawing, deform it to specify a small number of example poses, and indicate which poses can be interpolated. To make the object move, we design a procedural simulation to navigate the pose manifold in response to external or user‐controlled forces. Powerful artistic control is achieved by allowing the artist to specify both the pose manifold and how it is navigated, while physics is leveraged to provide timing and generality. We used our method to create sprites with a range of different dynamic properties. Copyright © 2014 John Wiley & Sons, Ltd.
Real-time tomography from magnetoencephalography (MEG)? experimental and theoretical challenges, possible physiological basis and evidence from the analysis of real data

Magnetoencephalography (MEG) and electroencephalography (EEG) were the Cinderellas of neuroimaging. On the one hand they are endowed with unparallel temporal resolution, while on the other they are in theory unable to uniquely determine the generators, even when a complete and exact set of measurements is available. Yet, study after study from our laboratories and others demonstrate that with modern hardware and software a very accurate estimate for the generators can be derived, at least from the MEG data. In this work we first review briefly theoretical arguments and the methods of source reconstruction. We then list experimental evidence for localization accuracy of a few millimeters from real MEG data using magnetic field tomography and a recent phantom study where a number of these techniques have been compared. We then put in context the accepted view of the electrophysiological basis of the EEG and MEG signal generation, adding caveats that must be considered given our incomplete knowledge of the anatomy and electrophysiology. We finally present results for processing of facial information that link the localization measures derived from MEG to the fMRI data at one end and invasive electrophysiology at the other and put them in the proper neurophysiological context.
PaTac: Urban, Ubiquitous, Personalized Services for Citizens and Tourists

This paper presents the general design of an architecture, based on software agents and oriented to the semantic Web, for the development and deployment of urban, ubiquitous services for citizens and tourist. The goal is to create a platform able to provide personalized services based on recommendation algorithms, and users' location, profile and preferences. The motivating scenario behind the design and development of these services is one in which citizens and tourists use mobile devices to interoperate confidently with the surrounding environment.
The Demographics of Public Participation Access When Communicating Environmental Risk

The interaction between humans and their environment is epitomized by climate change issues. Public engagement is essential to communicating anticipated changes and shifting risks. We investigated one such risk—flooding in the mid-Atlantic region of the United States. We examined the demographics of flood risk management meeting participants and found they were significantly older, English-only speakers, better educated, more affluent, and more likely to be homeowners than the United States Census Bureau data indicate for the region’s population. The aggregate gender and ethnic representation of all communities reflected that of the region’s population, but individual communities were much less diverse. These findings show that it is important for risk managers to organize meetings in many local communities in their jurisdiction to capture all demographically diverse sectors. Outreach efforts should adapt to target younger community members, non-English speakers, lower-wage earners, and renters.
Grid-based directed diffusion for wireless sensor networks

In this paper, we propose a grid-based directed diffusion (GDD) to save the energy of nodes in wireless sensor networks. Based on virtual grids which are set up according to routing fidelity, small clusters are formed. In GDD, the flooding of sensed data is limited in . clusters, which can save energy and decrease delay.
A 3D stacked high performance scalable architecture for 3D Fourier Transform

This paper proposes and evaluates a novel high-performance systolic architecture for 3D Fourier Transform specially tailored for 3D stacking integration with Through Silicon Vias. Our cuboid-shaped systolic network of orthogonally connected processing elements makes use of the DFT algorithm to compute an N<sub>1</sub>×N<sub>2</sub>×N<sub>3</sub>-point 3D-FT with an asymptotic time complexity of O(N<sub>1</sub>+N<sub>2</sub>+N<sub>3</sub>) multiplications. When compared with state-of-the-art 3D-FFT implementation on the Anton machine, a physical synthesized implementation of our architecture on the same 90nm technology node achieves 7.73× and 5.88× speed improvement when computing 16×1 6×16 and 32×3 2×32 FT, respectively.
TOF-range image sensor in 0.18μm CMOS technology based on current assisted photonic demodulators

We report on a 0. 18μm CMOS range image sensor with 120×160 array of 10×10μm<sup>2</sup> photonic demodulation pixels allowing for real-time 3D imaging with a worst-case accuracy of 3.3% in the distance interval [1.2–3.7] m.
Water diffusion in brain cortex closely tracks underlying neuronal activity

Neuronal activity results in a local increase in blood flow. This concept serves as the basis for functional MRI. Still, this approach remains indirect and may fail in situations interfering with the neurovascular coupling mechanisms (drugs, anesthesia). Here we establish that water molecular diffusion is directly modulated by underlying neuronal activity using a rat forepaw stimulation model under different conditions of neuronal stimulation and neurovascular coupling. Under nitroprusside infusion, a neurovascular-coupling inhibitor, the diffusion response and local field potentials were maintained, whereas the hemodynamic response was abolished. As diffusion MRI reflects interactions of water molecules with obstacles (e.g., cell membranes), the observed changes point to a dynamic modulation of the neural tissue structure upon activation, which remains to be investigated. These findings represent a significant shift in concept from the current electrochemical and neurovascular coupling principles used for brain imaging, and open unique avenues to investigate mechanisms underlying brain function.
Local and Global Stability of Delayed Congestion Control Systems

Stability proofs of nonlinear congestion control systems under heterogeneous feedback delays are usually difficult and involve a fair amount of effort. In this paper, we show that there exist a class of congestion control methods that admit very simple proofs of asymptotic stability and allow control equations to be delay-independent. This is in contrast to most previous work, which requires that each flow (and sometimes each router) adapt its control-loop constants based on the feedback delay and/or the length of the corresponding end-to-end path. Our new congestion control method, which we call Max-Min Kelly Control (MKC), builds upon Kelly's original work in and allows end-flows to be stable and fair regardless of network feedback delays or the number of hops in their end-to-end paths. Using basic matrix algebra and discrete control theory, we show MKC's local asymptotic stability under heterogeneous, directional feedback delays. We also offer a simple proof of its global asymptotic stability assuming constant feedback delay.
Development of the Large-Scale Oligonucleotide Chip for the Diagnosis of Plant Viruses and its Practical Use

A large-scale oligonucleotide (LSON) chip was developed for the detection of the plant viruses with known genetic information. The LSON chip contains two sets of 3,978 probes for 538 species of targets including plant viruses, satellite RNAs and viroids. A hundred forty thousand probes, consisting of isolate-, species- and genus-specific probes respectively, are designed from 20,000 of independent nucleotide sequence of plant viruses. Based on the economic importance, the amount of genome information, and the number of strains and/or isolates, one to fifty-one probes for each target virus are selected and spotted on the chip. The standard and field samples for the analysis of the LSON chip have been prepared and tested by RT-PCR. The probe’s specific and/or nonspecific reaction patterns by LSON chip allow us to diagnose the unidentified viruses. Thus, the LSON chip in this study could be highly useful for the detection of unexpected plant viruses, the monitoring of emerging viruses and the fluctuation of the population of major viruses in each plant.
RootSet: A Distributed Trust-based Knowledge Representation Framework For Collaborative Data Exchange

In a collaborative setting, several organizations need to exchange data with each other. Trust management is a major hindrance for inter-organizational collaborations. Organizations show reluctance towards replication of data outside their own datacenters. This work demonstrates a distributed trust-based platform for data exchange, called RootSet, among several collaborating organizations. RootSet enables organizations to share data without replication. It provides credential-based access control to manage data access by users throughout the platform using access rules. This work showcases several features of this tool.
Efficient Contents Sharing Using Differences between Versions in Peer-to-Peer Networks

This paper proposes an efficient contents sharing strategy using differences between their versions in Peer-to-Peer (P2P) networks. In this strategy, when a user requests a content item, he/she can get it by retrieving the other version of the content item and the difference from the requested version of the item, if the obtaining cost of the requested version of the content item is expensive. Furthermore, each content item is divided into several small blocks in order to be stored in the storages of peers without small and futile empty spaces.
Requirements reflection: requirements as runtime entities

Computational reflection is a well-established technique that gives a program the ability to dynamically observe and possibly modify its behaviour. To date, however, reflection is mainly applied either to the software architecture or its implementation. We know of no approach that fully supports requirements reflection- that is, making requirements available as runtime objects. Although there is a body of literature on requirements monitoring, such work typically generates runtime artefacts from requirements and so the requirements themselves are not directly accessible at runtime. In this paper, we define requirements reflection and a set of research challenges. Requirements reflection is important because software systems of the future will be self-managing and will need to adapt continuously to changing environmental conditions. We argue requirements reflection can support such self-adaptive systems by making requirements first-class runtime entities, thus endowing software systems with the ability to reason about, understand, explain and modify requirements at runtime.
9 81 02 55 v 1 2 0 O ct 1 99 8 Noise Dressing of Financial Correlation Matrices

We show that results from the theory of random matrices are potentially of great interest to understand the statistical structure of the empirical correlation matrices appearing in the study of price fluctuations. The central result of the present study is the remarkable agreement between the theoretical prediction (based on the assumption that the correlation matrix is random) and empirical data concerning the density of eigenvalues associated to the time series of the different stocks of the S&P500 (or other major markets). In particular the present study raises serious doubts on the blind use of empirical correlation matrices for risk management.