Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Arrested and Not Arrested Individuals Using Facebook

Social networking sites, like Facebook, have had an enormous impact on how people form relationships and the type of behavior that is shared with the public. The Social Bond Theory, created by Travis Hirschi (1969), states that individuals who have weak bonds to conventional society are more likely to commit acts of deviance than those who have strong bonds to conventional society. Going further with regards to Social Bond Theory, Hirschi (1960) along with Sampson and Laub (1990) and Salvatore and Taniguchi (2012) believed that strong bonds to the specific institutions of conformity to the norm of society, religion, work, education, activity not considered deviant, nation, military, family, and marriage are what deter an individual from committing deviant behavior. Alternatively, the Differential Association Theory, created by Edwin Sutherland (1947), states that individuals learn techniques, motivations, and attitudes towards deviant behavior from their peers. Both theories were tested against one another through examination of post and picture content of individuals who had and had not been arrested. Participants in this study were between the ages of 18-30, and had either been arrested in Rock Hill, SC within the year 2016 (n = 40) or had graduated from a high school in Rock Hill, SC (n = 38). Posts and pictures were examined and coded as: cannot be determined, conventional, unconventional, both, or moderate. Further, conventional posts and pictures were coded as: conformity to the norm of society, religion, work, education, activity not considered deviant, nation, military, family, and marriage. Results revealed that individuals who were arrested posted more unconventional posts than individuals who had not been arrested, while individuals who had not been arrested posted more conventional posts than individuals who had been arrested. Findings also indicate that the arrested group posted slightly more posts about marriage and family as compared to the not arrested group, suggesting that age plays a role in the importance of specific institutions. Overall, Social Bond Theory was better supported in this study through both posts and pictures collectively.
Driving maneuver prediction using car sensor and driver physiological signals

This study presents the preliminary attempt to investigate the usage of driver physiology signals, including electrocardiography (ECG) and respiration wave signals, to predict driving maneuvers. While most studies on driving maneuver prediction uses direct measurements from vehicle or road scene, we believe the mental state changes from the driver when making plans for maneuver can be reflected from the physiological signals. We extract both time and frequency domain features from the physiological signals, and use them as the features to predict the drivers' future maneuver. We formulate the prediction of driver maneuver as a multi-class classification problem by using the features extracted from signal before the driving maneuvers. The multi classes correspond to various types of driving maneuvers including Start, Stop, Lane Switch and Turn. We use the support vector machine (SVM) as the classifier, and compare the performance of using both physiological and car signals (CAN bus) with the baseline classifier that is trained with only car signal. An improved performance is observed when using the physiological features with 0.04 in F-score on average. This improvement is more obvious as the prediction is made earlier.
GazeLaser: A Hands-Free Highlighting Technique for Presentations

Presentation aids, such as the laser pointer, are commonly used in lectures and public speeches. Their effect on the audience has not been properly studied. We present an experiment that compares several pointer alternatives. One of them is GazeLaser, a new solution that does not need a manually operated pointer, but is based on the lecturers' gaze. It fares well in comparison, but comes second to the pointing tool available in PowerPoint. The experiment brings up issues that need to be taken into account when developing GazeLaser further.
Age-Earning Profiles and the Macroeconomic Impact of Demographic Shocks

This note examines the macroeconomic impact of demographic shocks in a continuous-time overlapping-generations model a la Yaari (1965)-Blanchard (1985)-Buiter (1988), assuming a hump-shaped lifecycle profile of earnings.Compared to the case without age-dependent earnings, an additional heterogeneity between younger workers and older ones are introduced and modifies the outcome of demographic shocks. Thus, the impact of a demographic shock that diminishes both the birth and death rates keeping population growth constant is reversed. Even if the impact of a baby-bust remains qualitatively the same (except for per capita consumption), the size of variations is magnified.
A Bayesian Approach to Reliability-Based Optimization With Incomplete Information

In engineering design, information regarding the uncertain variables or parameters is usually in the form of finite samples. Existing methods in optimal design under uncertainty cannot handle this form of incomplete information; they have to either discard some valuable information or postulate existence of additional information. In this article, we present a reliability-based optimization method that is applicable when information of the uncertain variables or parameters is in the form of both finite samples and probability distributions. The method adopts a Bayesian binomial inference technique to estimate reliability, and uses this estimate to maximize the confidence that the design will meet or exceed a target reliability. The method produces a set of Pareto trade-off designs instead of a single design, reflecting the levels of confidence about a design’s reliability given certain incomplete information. As a demonstration, we apply the method to design an optimal piston-ring/cylinder-liner assembly under surface roughness uncertainty. DOI: 10.1115/1.2204969
Analytic simplification of animated characters

Traditionally, levels of detail (LOD) for animated characters are computed from a single pose. Later techniques refined this approach by considering a set of sample poses and evaluating a more representative error metric. A recent approach to the character animation problem, animation space, provides a framework for measuring error analytically. The work presented here uses the animation-space framework to derive two new techniques to improve the quality of LOD approximations. Firstly, we use an animation-space distance metric within a progressive mesh-based LOD scheme, giving results that are reasonable across a range of poses, without requiring that the pose space be sampled. Secondly, we simplify individual vertices by reducing the number of bones that influence them, using a constrained least-squares optimisation. This influence simplification is combined with the progressive mesh to form a single stream of simplifications. Influence simplification reduces the geometric error by up to an order of magnitude, and allows models to be simplified further than is possible with only a progressive mesh. Quantitative (geometric error metrics) and qualititative (user perceptual) experiements confirm that these new extensions provide significant improvements in quality over traditional, naïve simplification; and while there is naturally some impact on the speed of the off-line simplification process, it is not prohibitive.
The Effectiveness of Foreign-Exchange Intervention: Recent Experience

Since the September 1985 Plaza Hotel announcement by the Group of Five industrial countries, a substantial realignment of exchange rates has been achieved. At the same time, foreign exchange market intervention, much of it concerted and much of it sterilized, has been undertaken on a scale not seen since the early 1970s This paper takes a fresh look at the effectiveness of sterilized intervention in the light of recent experience. The paper concludes that sterilized intervention, in itself, has played an unimportant role in promoting exchange-rate realignment. Instead, clear shifts in patterns of monetary and fiscal policy appear to have been the main medium-term policy factors determining currency values. Over certain shorter time periods, intervention has influenced exchange markets through a signalling channel; but this signalling effect has been operative only as a result of authorities' frequent readiness to adjust monetary policies promptly to counteract unwelcome exchange-market pressures. The paper makes some progress in formalizing reasons why intervention might enhance the credibility of messages that governments could convey as well through simple verbal announcements.
Fusion of Multispectral Remote Sensing Image and High Resolution Spatial Panchromatic Image Based on NSCT and IHS

This paper proposes a new method of fusing panchromatic and multispectral images based on NSCT and IHS. The I component is obtained by applying IHS on multispectral images. Then fusing the I component and panchromatic images through NSCT. Substituting the new fusion data performed by inverse NSCT for I component and applying the inverse IHS transform. Experimental results show that the proposed method can effectively preserve spectral information and improve spatial information than traditional IHS and NSCT, and has better subjective visual effect.
Numerical analysis of medium scale PV plants and their power-flow control system with a simple three phase inverter

This paper presents a mathematical analysis of a medium scale Photovoltaic (PV) power generation system connected to the distribution network and of its control system, in which the conversion stage is unique thanks to the absence of a boost chopper. Boost choppers are usually used as actuator for maximum power point tracking (MPPT). The conducted analysis leads to the conclusion that the used inverter presents two degrees of freedom that can be easily exploited in a control system in which the inverter simultaneously realizes the interconnection to the grid and at the same time realizes the MPPT control. The structure of the control system is then presented, discussed and then validated by means of numerical simulation tools.
Exploring Java software vocabulary: A search and mining perspective

We conduct a large-scale analysis of Java source code vocabulary for 12,151 open source projects from Source-Forge and Apache, a corpus substantially larger than considered previously. Simple statistical analysis demonstrates robust power-law behavior for word count distributions across multiple program entities. We then identify salient vocabulary trends for classes, interfaces, methods, and fields. Our results provide low-level insight into the vocabulary space governing Java software development, with direct application to program comprehension and software search. Supplementary material may be found at: http://sourcerer.ics. uci.edu/suite2009/suite.html.
Magnifico: A Platform For Expert Mining Using Metadata

In this paper, a modified TF-IDF approach is proposed to recommend experts by inferring search query topics using metadata. A multi-disciplinary reputation metric is also introduced to select people with specific expertise. The approach is validated on Mendeley corpus using a prototypal expert mining platform, Magnifico. The user interface of the platform is also discussed.
Riemannian Optimization for Elastic Shape Analysis

In elastic shape analysis, a representation of a shape is invariant to translation, scaling, rotation and reparameterization and important problems (such as computing the distance and geodesic between two curves, the mean of a set of curves, and other statistical analyses) require finding a best rotation and re-parameterization between two curves. In this paper, we focus on this key subproblem and study different tools for optimizations on the joint group of rotations and re-parameterizations. In this conference paper, we give a first account of a novel Riemannian optimization approach and evaluate its use in computing the distance between two curves and classification using two public data sets. Experiments show significant advantages in computational time and reliability in performance compared to the current state-of-the-art method. Further information will become available in a forthcoming full version of this conference paper.
Robust and Balanced Immune Responses to All 4 Dengue Virus Serotypes Following Administration of a Single Dose of a Live Attenuated Tetravalent Dengue Vaccine to Healthy, Flavivirus-Naive Adults.

BACKGROUND The 4 serotypes of dengue virus, DENV-1-4, are the leading cause of arboviral disease globally. The ideal dengue vaccine would provide protection against all serotypes after a single dose. METHODS Two randomized, placebo-controlled trials were performed with 168 flavivirus-naive adults to demonstrate the safety and immunogenicity of a live attenuated tetravalent dengue vaccine (TV003), compared with those of a second tetravalent vaccine with an enhanced DENV-2 component (TV005), and to evaluate the benefit of a booster dose at 6 months. Safety data, viremia, and neutralizing antibody titers were evaluated. RESULTS A single dose of TV005 elicited a tetravalent response in 90% of vaccinees by 3 months after vaccination and a trivalent response in 98%. Compared with TV003, the higher-dose DENV-2 component increased the observed frequency of immunogenicity to DENV-2 in the TV005 trial. Both the first and second doses were well tolerated. Neither vaccine viremia, rash, nor a significant antibody boost were observed following a second dose. CONCLUSIONS A single subcutaneous dose of TV005 dengue vaccine is safe and induces a tetravalent antibody response at an unprecedented frequency among vaccinees. A second dose has limited benefit and appears to be unnecessary. Studies to confirm these findings and assess vaccine efficacy will now move to populations in regions where DENV transmission is endemic. CLINICAL TRIALS REGISTRATION NCT01072786 and NCT01436422.
Prognostic Value of Tissue Inhibitor of Metalloproteinase-2 Expression in Patients with Non–Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Background and Objectives Tissue inhibitor of metalloproteinase-2 (TIMP-2) is a small secretory glycoprotein with anti–matrix metalloproteinase activity. Data on the value of TIMP-2 as a prognostic factor in non–small cell lung cancer (NSCLC) are discordant and remain controversial. A systematic review and meta-analysis was performed to explore this issue. Methods We identified the relevant literature by searching the PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure, SinoMed, and Wanfang Data databases (search terms: “non-small cell lung cancer” or “NSCLC” or “Lung Carcinoma, Non-Small-Cell”, “Tissue Inhibitor of Metalloproteinase-2” or “TIMP-2”, and “prognosis” or “prognostic” or “survive”) for updates prior to March 1, 2014. The pooled hazard ratio (HR) of overall survival with a 95% confidence interval (95% CI) was used to evaluate the strength of the association between positive TIMP-2 expression and survival in patients with NSCLC. Results We included 12 studies in our systematic review; five studies involving 399 patients with NSCLC were meta-analyzed. The pooled HR of all included patients was 0.57 (95% CI: 0.43–0.77), and the HRs of subgroup analysis according to stage (I–IV), testing method (immunohistochemistry) and high TIMP-2 expression percentage (<50%) were 0.63 (95% CI: 0.43–0.92), 0.55 (95% CI: 0.41–0.74), and 0.50 (95% CI: 0.28–0.88), respectively. These data suggested that high TIMP-2 expression is associated with favorable prognosis in NSCLC. The meta-analysis did not reveal heterogeneity or publication bias. Conclusions TIMP-2 expression indicates favorable prognosis in patients with NSCLC; as a protective factor, it could help predict outcome and may guide clinical therapy in the future.
From Crash to Byzantine Consensus with 2 f + 1 Processes ∗

Introduction Consensus is an important distributed computing problem that consists in making a set of processes agree on one of the values that each one of them proposes. Consensus in the asynchronous Byzantine message-passing model (the model we consider in the abstract) has been shown to require n ≥ 3f + 1 processes to be solvable in several variations of the basic system model, where f is the maximum number of faulty processes. Reducing the ratio n/f is important both theoretically, since achieving lower bounds has been always a goal in distributed computing, and in practice, as reducing the number of processes reduces the cost of a real system. Recently a few solutions to implement Byzantine fault-tolerant state machine replication, which involves solving consensus, with only 2f + 1 replicas have appeared [3, 2]. This reduction from 3f + 1 to 2f + 1 is possible by extending the system model with a trusted/trustworthy component that constrains the power of faulty processes to have certain behaviors. These components have been called wormholes [6]. State machine replication consists in replicating a service in a set of n servers, f of which may be faulty. Correia et al. use a wormhole called TTCB to help define an order for the execution of the clients’ requests with only 2f + 1 servers [3]. More recently, Chun et al. used an attested append-only memory (A2M) abstraction with the same purpose [2]. The main objective of this work is to contribute to a better understanding of the problem of consensus with only 2f + 1 processes. Despite these important results, the problem of solving asynchronous Byzantine consensus with only 2f + 1 processes is still far from being well understood. There are several reasons for this state of affairs: the related works we cited are only two and very recent; they solve consensus but have the solution for this problem submerged in the complications of a larger problem (state machine replication); they are based on special-purpose, reasonably complex, abstractions/wormholes (TTCB, A2M)
Feasibility Study of Port Scan Detection on Encrypted Data

We explore the feasibility of implementing port scan detection on encrypted data to protect confidentiality of sensitive network data. We experiment with four popular Port Scan detection algorithms namely Classic Version (and its Time Variant), Threshold Random Walk (TRW), Bayesian Logistic Regression (BLR). We also provide experimental results on performance and storage of our query based implementation on network flow data. Our key observation is that for complex operations on encrypted data Onion-layered encryption system like Crypt DB does not scale well.
Reasoning with qualified cardinality restrictions in fuzzy Description Logics

Description logics (DLs) are modern knowledge representation formalisms which are used today in many applications for reasoning with structured knowledge. Moreover, they are used in the semantic web (an extension of the current web) through the ontology language OWL. On the other hand fuzzy description logics (fuzzy-DLs) have been proposed as expressive logical formalisms capable of capturing and reasoning with vague and imprecise knowledge in the semantic web. In the current paper we investigate on the problem of reasoning with qualified cardinality restrictions (QCRs) in fuzzy DLs, extending previous results on simple number restrictions, thus we present a tableaux algorithm for the the fuzzy-DL fKD-ALCIQ.
A dynamic programming algorithm for resolving transmit-ambiguities in the localization of WSN

In application cases where millimeter-sized (≤ 5mm diameter) sensor motes are inevitable to gather environmental data, the motes' inherent energy constraints require a radical change in the communication procedure. For application cases like the surveying of hardly permeable underground structures, as they exist e.g. in mining areas of oil sands, ten-thousands of miniature sensors are needed to examine e.g. the oil-resource wealth of the area. This combination of extremely resource limited sensor motes and the need to communicate with several ten-thousands of motes requires changes with respect to the normal communication procedure. As reducing the DS-CDMA code length, which is used for the identification of the motes, saves signification amount of energy, we consider the scenario where a localization of sensor motes is required by means of non-relatable distance measurements. The resulting ambiguities in the distance measurements are due to the reassigning of DS-CDMA codes. In this work, we consider the problem of re-enabling the localization, i.e. of resolving the ambiguities due to non-unique identification of the sensor motes, to allow classical localization algorithms to obtain a positioning of the motes. For this problem, which has already been shown to be NP-hard in general, we present an algorithm that is capable of solving this problem optimally in the maximum a posteriori sense. Further, we show that our algorithm offers significant complexity reductions for large problem instances.
Spot Counting for Automated Analysis of Unmixed Hyper-Spectral M-FISH Images

Abstract—Fluorescence microscopy plays an important role in theclassiﬁcation of cancerous tissue. Fluorescent in situ hybridization(FISH) is a common method for marking different cell components(e.g. nucleus, cytoplasm, proteins) as well as speciﬁc DNA positionsor whole DNA sequences. The FISH method/variant used in thispaper facilitates a special combination of ﬁlters (DAPI/Orange/Green)and corresponding ﬂuorescent dyes to discriminate between thedifferent parts of a cell. FITC marks chromosome 17, SpectrumOrange R marks HER-2/neu receptors and DAPI is used to coun-terstain the cell nucleus. Upon excitation, each marked chromosomeemits a ﬂuorescent signal (spot). A common problem with multi-color FISH (M-FISH) preparations is the crosstalk between thechannels caused by the overlap of the emission spectra of the differentﬂuorophores. This crosstalk is one of the reasons that the evaluationand classiﬁcation of M-FISH preparations is difﬁcult and requires ex-perienced experts. The crosstalk cannot be resolved on the ﬁlter level(excitation/emission), and not by specialized ﬂuorophores (whichhave different emission spectra). However, the crosstalk can beeliminated if spectral imaging techniques are used to acquire hyper-spectral image data of M-FISH preparations and employ spectralunmixing methods to ”algorithmically reduce” the spectral overlap ofthe emission spectra. Spectral imaging is the combination of computervision and spectroscopy. And due to the fact that every object ofinterest consists of more than one pixel, every pixel is dependent onits neighboring pixels. Thus the spatial context of the image containsuseful information for a classiﬁcation and increase the sensitivity andspeciﬁcity of a spectral classiﬁcation. Keywords—spectral imaging (SI), ﬂuorescence microscopy, ﬂuo-rescent in situ hybridization (FISH), contextual classiﬁcation.
Predicate Matrix: extending SemLink through WordNet mappings

This paper presents the Predicate Matrix v1.1, a new lexical resource resulting from the integration of multiple sources of predicate information including FrameNet, VerbNet, PropBank and WordNet. We start from the basis of SemLink. Then, we use advanced graph-based algorithms to further extend the mapping coverage of SemLink. Second, we also exploit the current content of SemLink to infer new role mappings among the different predicate schemas. As a result, we have obtained a new version of the Predicate Matrix which largely extends the current coverage of SemLink and the previous version of the Predicate Matrix.