Miracle-dz/UniFAR-FTUs huggingface dataset:
Social Capital and Self-Employment

In this article, the author investigates individuals’ social capital, adopting a micro-relational perspective. The definition of social capital adopted is centred on personal contacts and exchanges. Reconstructing individuals’ net-works can precisely depict the network resources utilized by the actors. The study builds on the accumulated knowledge of previous research and literature on social capital, but directs attention to occupational division among the self-employed. The typology of (solo) self-employment that is introduced represents a variety of forms of self-employment activities in advanced economies, ranging from highly educated and profitable professionals to the poorly educated and often precarious unskilled self-employed, and it has been proposed in order to evaluate the role that social capital differentials play in structuring individuals’ work experiences. The article stresses that not ‘any’ network can represent ‘social capital’. It is necessary to single out the important ‘social resources matrix’ that produces effective social capital which can be used by subjects in purposive ways. The article shows how the different amount of social capital among the three types of self-employed workers (professionals/skilled/unskilled) has a strong impact on individuals’ levels of work involvement and psychological distress. By combining the network-operationalization of social capital with a ‘case by variable’ logic of analysis, it is demonstrated that social capital can be quite useful to explain differences in individuals’ well-being. In this sense, the article poses the question about social capital as a factor of social inequality.
Toward a more accurate understanding of the limits of the TLS execution paradigm

Thread-Level Speculation (TLS) facilitates the extraction of parallel threads from sequential applications. Most prior work has focused on developing the compiler and architecture for this execution paradigm. Such studies often narrowly concentrated on a specific design point. On the other hand, other studies have attempted to assess how well TLS performs if some architectural/ compiler constraint is relaxed. Unfortunately, such previous studies have failed to truly assess TLS performance potential, because they have been bound to some specific TLS architecture and have ignored one or another important TLS design choice, such as support for out-of-order task spawn or support for intermediate checkpointing.
Momentum and Contrarian Profits and Macroeconomic Fundamentals

We show that the existence of momentum and contrarian profits imposes restrictions on stochastic discount factors used to price stocks in equity markets. For several widely used asset pricing models, we demonstrate that these restrictions imply testable forms of intertemporal dependence in macroeconomic fundamentals such as consumption growth rate. Extensive empirical analysis provides supporting evidence that the momentum and contrarian profits manifest the short-term continuation and the longterm reversal in the macroeconomic fundamentals. Intuitively, the dynamics of the macroeconomic fundamentals induces a common return persistence for individual stocks. When coupled with the selection of past winners and losers, the return persistence generates the momentum and contrarian profits.
Back-channel feedback generation using linguistic and nonlinguistic information and its application to spoken dialogue system

A conversational system which can generate back-channel feed-back of proper content in proper timing by utilizing FST based early detectable decoder and prosody analysis is proposed. In human conversation, we do not take turns in order, but we give the back-channel feedbacks during the partner’s speech. By receiving these feedbacks, speakers can know the partner’s state and feel comfortable to speak. Therefore, spoken dialogue systems should be able to generate back-channel feedbacks in synchronization with user’s utterances. The appropriateness of these feedbacks depends on the contents and the timings. The contents strongly depend on the contents of the dialogue partner’s utterance, and the timings strongly depend on the prosody of the partner’s utterance. In order to determine the content of the feedback earlier than the end of the utterance, we use ﬁ-nite state transducer based speech recognizer. We used prosody information, especially F 0 and power of the utterance, to extract the proper timing of the feedback. We implemented these modules and applied them to the spoken dialogue system on the humanoid robot ROBISUKE. Experimental results show the effectiveness of our methods.
Evaluating caching and storage options on the Amazon Web Services Cloud

With the promise on-demand compute/storage resources, many users are deploying data-intensive scientific applications onto Clouds. To accelerate these applications, the prospect of caching intermediate data using the elastic compute and storage framework has proved promising. To this end, we believe that an in-depth study of cache placement decisions over various Cloud storage options would be highly beneficial to a large class of users. While tangential analyses have been proposed, ours in contrast focuses on cost-performance tradeoffs of maintaining a data cache with various parameters of any Cloud application. We have compared several Amazon Web Service (AWS Cloud) resources as possible cache placements and found that application dependent attributes like unit-data size, total cache size, and persistence, have far reaching implications on the cost of cache sustenance. Moreover, while instance-based caches expectedly yield higher cost, the performance that they afford may outweigh lower cost options.
Interference Mitigation Based on Partial CSI Feedback and Overhearing in an OFDMA Heterogeneous System

We consider the problem of femtocell/macrocell interference mitigation in an OFDMA based Downlink (DL) heterogeneous system. Most conventional methods rely on the information of the interference channel states and Macrocell User (MU) allocation provided by a control channel, causing large overhead increase. In our proposed method, each Femtocell Base Station (FBS) is able to predict the subchannel allocation of MUs based on partial Channel State Information (CSI) feedback and overhearing from the MUs to the Macrocell Base Station (MBS). Based on this estimation, each FBS performs subchannel and power allocation to Femtocell Users (FUs). With this procedure, the proposed method achieves excellent MU/FU sum-rate while greatly reducing required overhead compared to reference schemes.
SAVITR: A System for Real-time Location Extraction from Microblogs during Emergencies

We present SAVITR, a system that leverages the information posted on the Twitter microblogging site to monitor and analyse emergency situations. Given that only a very small percentage of microblogs are geo-tagged, it is essential for such a system to extract locations from the text of the microblogs. We employ natural language processing techniques to infer the locations mentioned in the microblog text, in an unsupervised fashion and display it on a map-based interface. The system is designed for efficient performance, achieving an F-score of 0.81, and is approximately two orders of magnitude faster than other available tools for location extraction.
Constrained parametric min-cuts for automatic object segmentation

We present a novel framework for generating and ranking plausible objects hypotheses in an image using bottom-up processes and mid-level cues. The object hypotheses are represented as figure-ground segmentations, and are extracted automatically, without prior knowledge about properties of individual object classes, by solving a sequence of constrained parametric min-cut problems (CPMC) on a regular image grid. We then learn to rank the object hypotheses by training a continuous model to predict how plausible the segments are, given their mid-level region properties. We show that this algorithm significantly outperforms the state of the art for low-level segmentation in the VOC09 segmentation dataset. It achieves the same average best segmentation covering as the best performing technique to date [2], 0.61 when using just the top 7 ranked segments, instead of the full hierarchy in [2]. Our method achieves 0.78 average best covering using 154 segments. In a companion paper [18], we also show that the algorithm achieves state-of-the art results when used in a segmentation-based recognition pipeline.
Cycling of Etk and Etp Phosphorylation States Is Involved in Formation of Group 4 Capsule by Escherichia coli

Capsules frequently play a key role in bacterial interactions with their environment. Escherichia coli capsules were categorized as groups 1 through 4, each produced by a distinct mechanism. Etk and Etp are members of protein families required for the production of group 1 and group 4 capsules. These members function as a protein tyrosine kinase and protein tyrosine phosphatase, respectively. We show that Etp dephosphorylates Etk in vivo, and mutations rendering Etk or Etp catalytically inactive result in loss of group 4 capsule production, supporting the notion that cyclic phosphorylation and dephosphorylation of Etk is required for capsule formation. Notably, Etp also becomes tyrosine phosphorylated in vivo and catalyzes rapid auto-dephosphorylation. Further analysis identified Tyr121 as the phosphorylated residue of Etp. Etp containing Phe, Glu or Ala in place of Tyr121 retained phosphatase activity and catalyzed dephosphorylation of Etp and Etk. Although EtpY121E and EtpY121A still supported capsule formation, EtpY121F failed to do so. These results suggest that cycles of phosphorylation and dephosphorylation of Etp, as well as Etk, are involved in the formation of group 4 capsule, providing an additional regulatory layer to the complex control of capsule production.
Tor, TorMd: Distributional Profiles of Concepts for Unsupervised Word Sense Disambiguation

Words in the context of a target word have long been used as features by supervised word-sense classifiers. Mohammad and Hirst (2006a) proposed a way to determine the strength of association between a sense or concept and co-occurring words---the distributional profile of a concept (DPC)---without the use of manually annotated data. We implemented an unsupervised naive Bayes word sense classifier using these DPCs that was best or within one percentage point of the best unsupervised systems in the Multilingual Chinese-English Lexical Sample Task (task #5) and the English Lexical Sample Task (task #17). We also created a simple PMI-based classifier to attempt the English Lexical Substitution Task (task #10); however, its performance was poor.
An adaptive constructive solution generator for ship scheduling DSS

It is well known that problems solved by a decision support system (DSS) is often only an approximation to the real problem, simplifying some of the features, to be able to find solutions to the problem. A decision maker, DM, might in these circumstances be equally interested in a set of good, diverse, solutions, than in only the optimal solution as produced by the model. As modern search techniques are able to produce a plethora of solutions, some distinguishing measure based on structural difference between solutions is needed in addition to the quality measure normally used. We present a self-learning restart heuristic for solving ship scheduling problems, adapted to a DSS. The heuristic is based on a set partitioning formulation of the shipping scheduling problem where columns are heuristically generated a priori. The resulting problem is solved repeatedly by a constructive heuristic with learning weights on both ships and cargoes, guiding the solution process towards diverse high quality solutions. A new diversification measure is introduced. Finally, a selection of the solutions from the construction process is subjected to local search.
Soccer Player Characteristics in English Lower-League Development Programmes: The Relationships between Relative Age, Maturation, Anthropometry and Physical Fitness

The relative age effect (RAE) and its relationships with maturation, anthropometry, and physical performance characteristics were examined across a representative sample of English youth soccer development programmes. Birth dates of 1,212 players, chronologically age-grouped (i.e., U9’s-U18’s), representing 17 professional clubs (i.e., playing in Leagues 1 & 2) were obtained and categorised into relative age quartiles from the start of the selection year (Q1 = Sep-Nov; Q2 = Dec-Feb; Q3 = Mar-May; Q4 = Jun-Aug). Players were measured for somatic maturation and performed a battery of physical tests to determine aerobic fitness (Multi-Stage Fitness Test [MSFT]), Maximal Vertical Jump (MVJ), sprint (10 & 20m), and agility (T-Test) performance capabilities. Odds ratio’s (OR) revealed Q1 players were 5.3 times (95% confidence intervals [CI]: 4.08–6.83) more likely to be selected than Q4’s, with a particularly strong RAE bias observed in U9 (OR: 5.56) and U13-U16 squads (OR: 5.45–6.13). Multivariate statistical models identified few between quartile differences in anthropometric and fitness characteristics, and confirmed chronological age-group and estimated age at peak height velocity (APHV) as covariates. Assessment of practical significance using magnitude-based inferences demonstrated body size advantages in relatively older players (Q1 vs. Q4) that were very-likely small (Effect Size [ES]: 0.53–0.57), and likely to very-likely moderate (ES: 0.62–0.72) in U12 and U14 squads, respectively. Relatively older U12-U14 players also demonstrated small advantages in 10m (ES: 0.31–0.45) and 20m sprint performance (ES: 0.36–0.46). The data identify a strong RAE bias at the entry-point to English soccer developmental programmes. RAE was also stronger circa-PHV, and relatively older players demonstrated anaerobic performance advantages during the pubescent period. Talent selectors should consider motor function and maturation status assessments to avoid premature and unwarranted drop-out of soccer players within youth development programmes.
Isolation via next-generation sequencing of microsatellites from the Tasmanian macroalgae Lessonia corrugata (Lessoniaceae)

Premise of the study: Microsatellite markers for the macroalgae Lessonia corrugata (Lessoniaceae) were developed, for the first time, to enable population genetic assessment of this important foundation species. Methods and Results: Ion Torrent sequencing identified 16,622 loci, 29 of which were trialed in L. corrugata. Seven loci were found to be polymorphic and screened for variation in 76 individuals from two populations in Tasmania, Australia. Observed heterozygosity ranged from 0.086 to 0.686 (mean 0.386) and the number of alleles per locus ranged from two to five (mean 2.57). Heterozygosity was not significantly different from expected values. Conclusions: These loci can be used to study the population genetics of L. corrugata, a key habitat-forming species in the Tasmanian marine ecosystem, and will help to assess gene flow among spatially discrete populations such as those in marine protected areas.
Time-jerk optimal trajectory planning for robotic manipulators

This paper proposes a time and jerk optimal trajectory planning method to find an efficient and sufficiently smooth trajectory. The objective function of the proposed method consists of two parts: the execution time and the smoothness of the trajectory in the joint space. The latter part enables one to get a smoother trajectory and reduce the tracking error. Moreover, the kinematic constraints of the robot are also taken into consideration by setting boundary on the absolute value of kinematical constraints. A newly devised cubic spline is presented to ensure the starting and ending values of the velocity and acceleration controllable without requiring extra points. The method is tested on an EAST Tokamak inspection robot.
Design and implementation of fefet-based lookup table

Ferroelectric random access memory (FeRAM) is a promising candidate to substitute static random access memory (SRAM) in lookup table (LUT) design due to its high density, high speed operation, anti-radiation and non-volatility. Ferroelectric gate field effect transistors (FeFETs) have been extensively studied and its usage in memory elements and basic analog circuit configurations has gained much interests. Here, we propose a novel architecture of FeFET-based LUT. An improved timing mode of FeRAM chip is analyzed to satisfy the performance of the FeFET-based LUT. Decoder, driver circuit and sensitive amplifier for FeFET array are also proposed. Every design process is simulated by Sentarus TCAD. All the simulation results show that the proposed LUT works properly when the frequency reaches 500 MHz at 0.3 V differential input.
Consistent Depth Maps Recovery from a Video Sequence

This paper presents a novel method for recovering consistent depth maps from a video sequence. We propose a bundle optimization framework to address the major difficulties in stereo reconstruction, such as dealing with image noise, occlusions, and outliers. Different from the typical multi-view stereo methods, our approach not only imposes the photo-consistency constraint, but also explicitly associates the geometric coherence with multiple frames in a statistical way. It thus can naturally maintain the temporal coherence of the recovered dense depth maps without over-smoothing. To make the inference tractable, we introduce an iterative optimization scheme by first initializing the disparity maps using a segmentation prior and then refining the disparities by means of bundle optimization. Instead of defining the visibility parameters, our method implicitly models the reconstruction noise as well as the probabilistic visibility. After bundle optimization, we introduce an efficient space-time fusion algorithm to further reduce the reconstruction noise. Our automatic depth recovery is evaluated using a variety of challenging video examples.
The Formation of Topographic Maps That Maximize the Average Mutual Information of the Output Responses to Noiseless Input Signals

This article introduces an extremely simple and local learning rule for to pographic map formation. The rule, called the maximum entropy learning rule (MER), maximizes the unconditional entropy of the map's output for any type of input distribution. The aim of this article is to show that MER is a viable strategy for building topographic maps that maximize the average mutual information of the output responses to noiseless input signals when only input noise and noise-added input signals are available.
Beyond the Hundred Dollar Genome – Drug Discovery Futures

The advent of silicon chip based technologies for genome sequencing promises continuing exponential falls in the reagent costs of sequencing. When every patient has a full genome sequence as part of their medical records the science of drug discovery and drug design must adapt and improve to meet this challenge. This series covers computational, and experimental approaches for small molecules and biologics. From the virtual patient – a computational model of a complete human being, through in silico screening to RNA editing and antibody directed therapies.
Use of the GRP1 PH domain as a tool to measure the relative levels of PtdIns(3,4,5)P3 through a protein-lipid overlay approach Published, JLR Papers in Press, November 27, 2006.

We describe a novel approach to the relative quantification of phosphatidylinositol (3,4,5)-trisphosphate [PtdIns(3,4,5)P3] and its application to measure, in neutrophils, the activation of phosphoinositide 3-kinase (PI3K). This protein-lipid overlay-based assay allowed us to confirm and extend the observations, first, that N-formyl-methionyl-leucyl-phenylalanine (fMLP) stimulation of primed human neutrophils leads to a transient and biphasic increase in PtdIns(3,4,5)P3 levels and, second, that the ability of fMLP to stimulate PtdIns(3,4,5)P3 accumulation in neutrophils isolated from mice carrying a Ras-insensitive (‘DASAA’) knock-in of PI3Kγ (p110γDASAA/DASAA) is substantially dependent on the Ras binding domain of PI3Kγ.
Altered Microenvironment Promotes Progression of Preinvasive Breast Cancer: Myoepithelial Expression of αvβ6 Integrin in DCIS Identifies High-risk Patients and Predicts Recurrence

Purpose: This study investigated the functional and clinical significance of integrin αvβ6 upregulation in myoepithelial cells of ductal carcinoma in situ (DCIS). Experimental Design: Archival samples of DCIS and DCIS with associated invasion (n = 532) were analyzed for expression of αvβ6 by immunohistochemistry and ability to predict recurrence and progression assessed in an independent, unique cohort of DCIS cases with long-term follow-up. Primary myoepithelial cells and myoepithelial cell lines, with and without αvβ6 expression, were used to measure the effect of αvβ6 on growth and invasion of tumor cell lines in vitro and in a xenograft mouse model. Involvement of TGFβ signaling was established using mink lung epithelial cell (MLEC) assay and antibody inhibition, and expression and activation of matrix metalloproteinase (MMP)-9 established by Real Time-PCR and zymography. Results: Expression of αvβ6 is significantly associated with progression to invasive cancer (P < 0.006) and with recurrence over a median follow-up of 114 months in a series of matched DCIS cases treated with local excision. We show that expression of αvβ6 drives myoepithelial cells to promote tumor cell invasion in vitro and enhances mammary tumor growth in vivo. The tumor-promoting effect of αvβ6-positive myoepithelial cells is dependent on TGFβ-driven upregulation of MMP9 and can be abrogated by inhibiting this pathway. Conclusion: These findings indicate that altered myoepithelial cells in DCIS predict disease progression and recurrence and show that upregulation of αvβ6 on myoepithelial cells generates a tumor promoter function through TGFβ upregulation of MMP-9. These data suggest that expression of αvβ6 may be used to stratify patients with DCIS. Clin Cancer Res; 20(2); 344–57. ©2013 AACR.