Miracle-dz/UniFAR-FTUs huggingface dataset:
The hyperonym problem revisited: Conceptual and lexical hierarchies in language generation

When a lexical item is selected in the language production process, it needs to be explained why none of its superordinates gets selected instead, since their applicability conditions are fulfilled all the same. This question has received much attention in cognitive modelling and not as much in other branches of NLG. This paper describes the various approaches taken, discusses the reasons why they are so different, and argues that production models using symbolic representations should make a distinction between conceptual and lexical hierarchies, which can be organized along fixed levels as studied in (some branches of) lexical semantics.
Increasing virtual samples through loss smoothness determination in large geometric margin minimum classification error training

We propose a new method for automatically determining the smoothness of smooth classification error count loss for the recent Large Geometric Margin Minimum Classification Error (LGM-MCE) training. The method uses the Parzen-estimation-based formalization of MCE training, and it realizes the determination through the maximum likelihood estimation of error count risk in the one-dimensional geometric-margin-based misclassification measure. In the LGM-MCE framework, increase in the loss smoothness directly leads to an effect of producing virtual samples, which are expected to increase the training robustness to unseen samples. Focusing on this point, we also theoretically clarify the mechanism of this virtual sample generation. Through experiments, the utility of the proposed smoothness determination method is demonstrated, and the mechanism of producing virtual samples and its effect in robustness increase are also clearly illustrated.
Co-EM support vector learning

Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms co-training for many problems, but it requires the underlying learner to estimate class probabilities, and to learn from probabilistically labeled data. Therefore, co-EM has so far only been studied with naive Bayesian learners. We cast linear classifiers into a probabilistic framework and develop a co-EM version of the Support Vector Machine. We conduct experiments on text classification problems and compare the family of semi-supervised support vector algorithms under different conditions, including violations of the assumptions underlying multi-view learning. For some problems, such as course web page classification, we observe the most accurate results reported so far.
Usenix Association 10th Usenix Symposium on Networked Systems Design and Implementation (nsdi '13) 427 Improving Availability in Distributed Systems with Failure Informers

This paper addresses a core question in distributed systems: how should applications be notified of failures? When a distributed system acts on failure reports , the system's correctness and availability depend on the granularity and semantics of those reports. The system's availability also depends on coverage (failures are reported), accuracy (reports are justified), and time-liness (reports come quickly). This paper describes Pigeon , a failure reporting service designed to enable high availability in the applications that use it. Pigeon exposes a new abstraction, called a failure informer, which allows applications to take informed, application-specific recovery actions, and which encapsulates uncertainty, allowing applications to proceed safely in the presence of doubt. Pigeon also significantly improves over the previous state of the art in the three-way trade-off among coverage, accuracy, and timeliness.
pH-responsive drug release from functionalized electrospun poly(caprolactone) scaffolds under simulated in vivo environment

Abstract The difference in the tumor environment from the normal healthy tissue can be therapeutically exploited to develop new strategies for controlled and site-specific drug delivery. In the present study, a continuous flow system is designed to represent the in vivo environment of a tumor tissue and drug release is studied at different pH that represents normal tissue pH, tumor tissue pH, and stomach pH. The results obtained from these experiments were translated to a human embryonic kidney cell culture system and the effect of drug released from these functionalized PCL scaffolds on cell viability was studied. A significant decrease in cell viability was observed with the doxorubicin hydrochloride concentration that would be released at acidic pH, either present as a result of tumor extracellular environment or could be achieved via fabrication of a composite scaffold with a polyvinyl alcohol hydrogel containing acid. In the end, a study using zebrafish as an animal model is also undertaken in order to study the drug release from the scaffolds in vivo.
Estimating observer sea day requirements in the Mid-Atlantic region to monitor Loggerhead sea turtle (Caretta caretta) interactions

This series is a secondary scientific series designed to assure the long-term documentation and to enable the timely transmission of research results by Center and/or non-Center researchers, where such results bear upon the research mission of the Center (see the outside back cover for the mission statement). These documents receive internal scientific review, and most receive copy editing. The National Marine Fisheries Service does not endorse any proprietary material, process, or product mentioned in these documents. All documents issued in this series since April 2001, and several documents issued prior to that date, have been copublished in both paper and electronic versions. To access the electronic version of a document in this series, go to http://www.nefsc. noaa.gov/nefsc/publications/. The electronic version is available in PDF format to permit printing of a paper copy directly from the Internet. If you do not have Internet access, or if a desired document is one of the pre-April Editorial Treatment: To distribute this report quickly, it has not undergone the normal technical and copy editing by the Northeast Fisheries Science Center's (NEFSC's) Editorial Office as have most other issues in the NOAA Technical Memorandum NMFS-NE series. Other than the four covers and first two preliminary pages, all writing and editing have been performed by the authors listed within. Information Quality Act Compliance: In accordance with section 515 of Public Law 106-554, the Northeast Fisheries Science Center completed both technical and policy reviews for this report. These predissemination reviews are on file at the NEFSC Editorial Office.
An adaptive transmitting power technique for energy efficient mm-wave wireless NoCs

Several emerging techniques have been recently proposed for alleviating the communication latency and the energy consumption issues in multi/many-core architectures. One of such emerging communication techniques, namely, WiNoC replaces the traditional wired links with the use of wireless medium. Unfortunately, the energy consumed by the RF transceiver (i.e., the main building block of a WiNoC), and in particular by its transmitter, accounts for a significant fraction of the overall communication energy. In this paper we propose a runtime tunable transmitting power technique for improving the energy efficiency of the transceiver in wireless NoC architectures. The basic idea is tuning the transmitting power based on the location of the recipient of the current communication. The integration of the proposed technique into two known WiNoC architectures, namely, iWise64 and McWiNoC resulted in an energy reduction of 43% and 60%, respectively.
On the Outage Performance of Non-Orthogonal Multiple Access With 1-bit Feedback

In this paper, the outage performance of downlink non-orthogonal multiple access (NOMA) is investigated for the case where each user feeds back only one bit of its channel state information (CSI) to the base station. Conventionally, opportunistic one-bit feedback has been used in fading broadcast channels to select only one user for transmission. In contrast, the considered NOMA scheme adopts superposition coding to serve all users simultaneously in order to improve user fairness. A closed-form expression for the common outage probability (COP) is derived, along with the optimal diversity gains under two types of power constraints. Particularly, it is demonstrated that the diversity gain under a long-term power constraint is twice as large as that under a short-term power constraint. Furthermore, we study dynamic power allocation optimization for minimizing the COP, based on one-bit CSI feedback. This problem is challenging, since the objective function is non-convex; however, under the short-term power constraint, we demonstrate that the original problem can be transformed into a set of convex problems. Under the long-term power constraint, an asymptotically optimal solution is obtained for high signal-to-noise ratio.
Design and implementation of an intelligent vehicle system for autonomous valet parking service

The autonomous vehicle valet parking service (AVP) enables a vehicle to drive and park without any human interaction. The driverless vehicle has to follow the scheduled route and be parked in a parking lot automatically. Most fundamental technologies for autonomous vehicle valet parking service are controlling vehicle driving and parking. For autonomous driving, the path to near goal parking lot has to be generated and control commands to follow the path have to be generated continuously. For autonomous parking, the controlling vehicle steer value has to be found to park the vehicle at slot well. And also the mobile assistant system is needed for driver to select the parking lot and monitoring the state of the vehicle in remote. In this paper, we have designed and implemented of an intelligent vehicle system for autonomous vehicle valet parking service in low speed limited parking area.
Psychometric Properties and Clinical Usefulness of the Youth Self-Report DSM-Oriented Scales: A Field Study among Detained Male Adolescents

It is unknown if the DSM-oriented (DSM) scales of the Youth Self-Report (YSR) are useful to determine what kind of narrowly-focused psychiatric assessment is needed, and how well these scales serve as a triage tool in real-world forensic settings. To address this knowledge gap, the YSR and diagnostic interviews were administered to 405 detained boys as part of a clinical protocol. Continuous DSM scale scores (e.g., Conduct Problems) were moderately to highly accurate in predicting their corresponding disorder (e.g., conduct disorder), whereas dichotomized DSM scale scores were not. To test the DSM scales’ usefulness for triage purposes, the sensitivity and specificity of being in the borderline range of one or more DSM scales were calculated. Almost all boys who did not have a disorder were in the normal range of at least one DSM scale (high specificity). However, many boys with a disorder would have been missed if such a decision rule was used for triage purposes (low sensitivity). In conclusion, their relations with the corresponding disorders support the construct validity of the DSM scales in an applied forensic setting. Nevertheless, the findings also warrant against the use of these scales for planning further narrowly-focused assessment or for triage purposes.
Therapeutic evaluation of microRNA-15a and microRNA-16 in ovarian cancer

Treatment of chemo-resistant ovarian cancer (OvCa) remains clinically challenging and there is a pressing need to identify novel therapeutic strategies. Here we report that multiple mechanisms that promote OvCa progression and chemo-resistance could be inhibited by ectopic expression of miR-15a and miR-16. Significant correlations between low expression of miR-16, high expression of BMI1 and shortened overall survival (OS) were noted in high grade serous (HGS) OvCa patients upon analysis of The Cancer Genome Atlas (TCGA). Targeting BMI1, in vitro with either microRNA reduced clonal growth of OvCa cells. Additionally, epithelial to mesenchymal transition (EMT) as well as expression of the cisplatin transporter ATP7B were inhibited by miR-15a and miR-16 resulting in decreased degradation of the extra-cellular matrix and enhanced sensitization of OvCa cells to cisplatin. Nanoliposomal delivery of the miR-15a and miR-16 combination, in a pre-clinical chemo-resistant orthotopic mouse model of OvCa, demonstrated striking reduction in tumor burden compared to cisplatin alone. Thus, with the advent of miR replacement therapy some of which are in Phase 2 clinical trials, miR-15a and miR-16 represent novel ammunition in the anti-OvCa arsenal.
Ecogeographic genetic epidemiology

Complex diseases such as cancer and heart disease result from interactions between an individual's genetics and environment, i.e. their human ecology. Rates of complex diseases have consistently demonstrated geographic patterns of incidence, or spatial “clusters” of increased incidence relative to the general population. Likewise, genetic subpopulations and environmental influences are not evenly distributed across space. Merging appropriate methods from genetic epidemiology, ecology and geography will provide a more complete understanding of the spatial interactions between genetics and environment that result in spatial patterning of disease rates. Geographic information systems (GIS), which are tools designed specifically for dealing with geographic data and performing spatial analyses to determine their relationship, are key to this kind of data integration. Here the authors introduce a new interdisciplinary paradigm, ecogeographic genetic epidemiology, which uses GIS and spatial statistical analyses to layer genetic subpopulation and environmental data with disease rates and thereby discern the complex gene‐environment interactions which result in spatial patterns of incidence. Genet. Epidemiol. 2009. © 2008 Wiley‐Liss, Inc.
Identification of POMC Exonic Variants Associated with Substance Dependence and Body Mass Index

Background Risk of substance dependence (SD) and obesity has been linked to the function of melanocortin peptides encoded by the proopiomelanocortin gene (POMC). Methods and Results POMC exons were Sanger sequenced in 280 African Americans (AAs) and 308 European Americans (EAs). Among them, 311 (167 AAs and 114 EAs) were affected with substance (alcohol, cocaine, opioid and/or marijuana) dependence and 277 (113 AAs and164 EAs) were screened controls. We identified 23 variants, including two common polymorphisms (rs10654394 and rs1042571) and 21 rare variants; 12 of which were novel. We used logistic regression to analyze the association between the two common variants and SD or body mass index (BMI), with sex, age, and ancestry proportion as covariates. The common variant rs1042571 in the 3′UTR was significantly associated with BMI in EAs (Overweight: P adj = 0.005; Obese: P adj = 0.018; Overweight+Obese: P adj = 0.002) but not in AAs. The common variant, rs10654394, was not associated with BMI and neither common variant was associated with SD in either population. To evaluate the association between the rare variants and SD or BMI, we collapsed rare variants and tested their prevalence using Fisher’s exact test. In AAs, rare variants were nominally associated with SD overall and with specific SD traits (SD: P FET,1df = 0.026; alcohol dependence: P FET,1df = 0.027; cocaine dependence: P FET,1df = 0.007; marijuana dependence: P FET,1df = 0.050) (the P-value from cocaine dependence analysis survived Bonferroni correction). There was no such effect in EAs. Although the frequency of the rare variants did not differ significantly between the normal-weight group and the overweight or obese group in either population, certain rare exonic variants occurred only in overweight or obese subjects without SD. Conclusion These findings suggest that POMC exonic variants may influence risk for both SD and elevated BMI, in a population-specific manner. However, common and rare variants in this gene may exert different effects on these two phenotypes.
The physiological significance of β-actin mRNA localization in determining cell polarity and directional motility

β-actin mRNA is localized near the leading edge in several cell types, where actin polymerization is actively promoting forward protrusion. The localization of the β-actin mRNA near the leading edge is facilitated by a short sequence in the 3′ untranslated region, the “zip code. ” Localization of the mRNA at this region is important physiologically. Treatment of chicken embryo fibroblasts with antisense oligonucleotides complementary to the localization sequence (zip code) in the 3′ untranslated region leads to delocalization of β-actin mRNA, alteration of cell phenotype, and a decrease in cell motility. To determine the components of this process responsible for the change in cell behavior after β-actin mRNA delocalization, the Dynamic Image Analysis System was used to quantify movement of cells in the presence of sense and antisense oligonucleotides to the zip code. It was found that net path length and average speed of antisense-treated cells were significantly lower than in sense-treated cells. Total path length and the velocity of protrusion of antisense-treated cells were not affected compared with those of control cells. These results suggest that a decrease in persistence of direction of movement and not in velocity results from treatment of cells with zip code-directed antisense oligonucleotides. To test this, direct analysis of directionality was performed on antisense-treated cells and showed a decrease in directionality (net path/total path) and persistence of movement. Less directional movement of antisense-treated cells correlated with a unpolarized and discontinuous distribution of free barbed ends of actin filaments and of β-actin protein. These results indicate that delocalization of β-actin mRNA results in delocalization of nucleation sites and β-actin protein from the leading edge followed by loss of cell polarity and directional movement.
Distribution of Circumstellar Disk Masses in the Young Cluster NGC 2024

We determine the distribution of circumstellar disk masses in the young (~0.3 Myr) cluster NGC 2024 by imaging a 2. ′5 × 2. ′5 region in 3 mm continuum emission to an rms noise level of ~0.75 mJy beam-1 with the Owens Valley Millimeter Array. The mosaic encompasses 147 K-band sources, as well as the molecular ridge seen previously in dust continuum emission. We detect 10 pointlike sources in 3 mm continuum emission above the level of 5 σ within the unit gain region of the mosaic. One of these sources corresponds to the near-IR source IRS 2, an early B-type star. Two other sources are tentatively associated with low-mass near-IR cluster members, and the remaining seven sources have no K-band counterparts. Assuming the millimeter continuum point sources represent emission from circumstellar disks and/or envelopes, then ~6% of the total population (infrared and millimeter sources) in the NGC 2024 mosaic have a circumstellar mass in excess of ~0.06 M☉. We obtain further constraints on the average circumstellar disk mass by considering the mean millimeter continuum flux observed toward a sample of 140 K-band sources that likely have stellar masses ≲1-2 M☉. While none of these sources are detected individually above the 3 σ limit of ~0.035 M☉, the ensemble of sources are detected in the mean at the 5 σ level with a mean disk mass of ~0.005 M☉. Compared with the older (~2 Myr) cluster IC 348, NGC 2024 contains a higher frequency of massive disks or envelopes and has a higher mean disk mass by a factor of 2.5 ± 1.3 among K-band sources, suggesting that the mean circumstellar mass is decreasing with cluster age. We also compare the results for the NGC 2024 and IC 348 clusters with those for the lower density Taurus star-forming region. Finally, we compare our detection limits with the minimum mass estimate for the proto-solar nebula and discuss possible implications for planet formation.
A fuzzy-logic-based approach for soft data constrained multiple-model PHD filter

Tracking multiple targets with non-linear dynamics is a challenging problem. One of the popular solutions, Sequential Monte Carlo-Probability Hypothesis Density (SMC-PHD) filter, deploys a Random Set (RS) theoretic formulation along with the Sequential Monte Carlo approximation, which is a variant of Bayes filtering. The performance of Bayesian filtering-based methods can be enhanced by using extra information incorporated as specific constraints into the filtering process. Following the same principle, this paper proposes a constrained variant of the SMC-PHD filter, in which the inherently vague human-generated data are transformed into a set of constraints using a fuzzy logic approach. These constraints are enforced to the filtering process by applying coefficients to the particles' weights. The Soft Data (SD) reports on target agility level; wherein, the agility refers to the case in which the observed dynamics of the targets deviates from its given probabilistic characterization. Consequently, the proposed constrained filtering approach enables dealing with multitarget tracking scenarios in presence of target agility, as demonstrated by the experimental results presented in this paper.
One Class Support Vector Machines for Detecting Anomalous Windows Registry Accesses

We present a new Host-based Intrusion Detection System (IDS) that monitors accesses to the Microsoft Windows Registry using Registry Anomaly Detection (RAD). Our system uses a one class Support Vector Machine (OCSVM) to detect anomalous registry behavior by training on a dataset of normal registry accesses. It then uses this model to detect outliers in new (unclassified) data generated from the same system. Given the success of OCSVMs in other applications, we apply them to the Windows Registry anomaly detection problem. We compare our system to the RAD system using the Probabilistic Anomaly Detection (PAD) algorithm on the same dataset. Surprisingly, we find that PAD outperforms our OCSVM system due to properties of the hierarchical prior incorporated in the PAD algorithm. In the future, these properties may be used to develop an improved kernel and increase the performance of the OCSVM system.
On Optimal Cooperator Selection Policies for Multi-Hop Ad Hoc Networks

In this paper we consider wireless cooperative multihop networks, where nodes that have decoded the message at the previous hop cooperate in the transmission toward the next hop, realizing a distributed space-time coding scheme. Our objective is finding optimal cooperator selection policies for arbitrary topologies with links affected by path loss and multipath fading. To this end, we model the network behavior through a suitable Markov chain and we formulate the cooperator selection process as a stochastic shortest path problem (SSP). Further, we reduce the complexity of the SSP through a novel pruning technique that, starting from the original problem, obtains a reduced Markov chain which is finally embedded into a solver based on focused real time dynamic programming (FRTDP). Our algorithm can find cooperator selection policies for large state spaces and has a bounded (and small) additional cost with respect to that of optimal solutions. Finally, for selected network topologies, we show results which are relevant to the design of practical network protocols and discuss the impact of the set of nodes that are allowed to cooperate at each hop, the optimization criterion and the maximum number of cooperating nodes.