Miracle-dz/UniFAR-FTUs huggingface dataset:
ORCHESTRA: Rapid, Collaborative Sharing of Dynamic Data

Conventional data integration techniques employ a “top-down” design philosophy, starting by assessing requirements and defining a global schema, and then mapping data sources to that schema. This works well if the problem domain is well-understood and relatively static, as with enterprise data. However, it is fundamentally mismatched with the “bottom-up”model of scientific data sharing, in which new data needs to be rapidly developed, published, and then assessed, filtered, and revised by others. We address the need for bottom-up collaborative data sharing, in which independent researchers or groups with different goals, schemas, and data can share information in the absence of global agreement. Each group independently curates, revises, and extends its data; eventually the groups compare and reconcile their changes, but they are not required to agree. This paper describes our initial design and prototype of the ORCHESTRA system, which focuses on managing disagreement among multiple data representations and instances. Our work represents an important evolution of the concepts of peer-to-peer data sharing [23], which considers revision, disagreement, authority, and intermittent participation.
Intelligent Agent to Support Virtual Enterprise for Rapid Tools and Dies Making

With remarkable growth of broadband network and high performance computer systems, the Internet has become the worldwide information platform for sharing of information and data. Information processing is an important challenge in an internet-based manufacturing environment, and must facilitate distribution, heterogeneity, autonomy and cooperation. This paper reviews the developments of intelligent agent in supporting rapid tools and dies making. The agent allows users to submit queries through a user interface and provide users a manufacturing plan, i.e. suitability manufacturing company, cost data, prototype of CAD drawing, etc.
Visions for Logic-Based Natural Language

The purpose of this paper is to outline the requirements that the eld of Natural Language Processing (NLP) has for a declarative successor to Prolog. Logic programming approaches play a major role in NLP, and likewise considerations of NLP have had a strong innuence on We will review the state of the art in NL grammar formalisms and processing algorithms in the logic programming paradigm, from the perspective of research in grammatical theory (Computational Linguistics) and from the perspective of applied NLP (Language Engineering). The relationship to Prolog and to current developments in (C)LP will be discussed. We will outline the requirements for a logic programming language that will both support the current practice in NLP and provide a platform which can accommodate future research results. 1 Motivation The early development of Prolog and logic programming was strongly innuenced by NLP applications (Colmerauer's Q-Systems and Metamorphosis Grammar), and DCGs have been part of Prolog from the very beginning. Today, logic programming is the most important programming paradigm for NLP, and the strong relationship between the two elds is evidenced by regular conferences (e. A large part of the work in NLP is based on Prolog. A key idea is to express a grammar as a set of statements in a logic (e.g. Horn clauses), and to use a theorem prover (e.g. resolution) in order to parse or generate NL sentences. The original slogan parsing as deduction Pereira and Warren, 1983] is nowadays extended to bidirectional linguistic deduction in which the same grammar can be employed both for parsing and generation. However, Prolog has turned out to be insuucient for the purposes of NLP for a number of reasons (ineecient search strategy, unexpressive constraint language). As a consequence, research in grammar formalisms has come up with a number of alternatives, extensions or specialisations of the design choices made in Prolog. One important point is that most grammar formalisms make a clear distinction between declarative speciication (grammars) and execution (NL parsing or generation). The following section gives an overview of the state of the art in grammar formalisms, with special emphasis on those developments that are diierent from developments in logic programming (although there is a large overlap, where the elds have either innuenced each other or the same kinds of approaches have been developed independently). 1 1 Due to space limitations, this paper can only give a very broad overview and …
Recent Studies in Automatic Text Analysis and Document Retrieval

Many experts in mechanized text processing now agree that useful automatic language analysis procedures are largely unavailable and that the existing linguistic methodologies generally produce disappointing results. An attempt is made in the present study to identify those automatic procedures which appear most effective as a replacement for the missing language analysis. A series of computer experiments is described, designed to simulate a conventional document retrieval environment. It is found that a simple duplication, by automatic means, of the standard, manual document indexing and retrieval operations will not produce acceptable output results. New mechanized approaches to document handling are proposed, including document ranking methods, automatic dictionary and word list generation, and user feedback searches. It is shown that the fully automatic methodology is superior in effectiveness to the conventional procedures in normal use.
Crowding Oot: The Effect of Government Grants on Donors, Fundraisers, and Foundations in Canada

Using data from charitable organizations in the US, authors have established that government grants to charities largely crowd out giving from other sources, but that this reduction is due mostly to reduced fundraising activities of the charity itself. We use much more detailed data from over 13,000 charities in Canada, measured for up to 15 years, to provide valuable new insights into this phenomenon. In particular, dollars received from individuals would increase with an increase in government grants if fundraising expenditures were held constant. Non-tax receipted giving from fundraising would decrease. A good portion of the crowd-out is attributable to giving from other institutions, such as foundations and other charities. The effect from this measure, about one-third of the measured crowding out—represents a potential loss of dollars to the charitable sector as a result of government grants.
Direct BRLF1 binding is required for cooperative BZLF1/BRLF1 activation of the Epstein-Barr virus early promoter, BMRF1.

Disruption of Epstein-Barr virus (EBV) latency is mediated through the activation of the viral immediate-early proteins, BZLF1 (Z) and BRLF1 (R). i. ; (Chevallier-Greco, A., et al., (1986) EMBO J., 5, 3243-9; Countryman, and Miller, G. (1985) Proc. Natl. Acad. Sci. USA, 82, 4085-4089). We have previously demonstrated that these proteins cooperatively activate the EBV early promoter BMRF1 in lymphoid cells but not in epithelial cells. Although cooperative transactivation by these proteins has been demonstrated with a number of EBV promoters, the mechanism of this interaction is not well understood. We now show that the cooperative activation of the BMRF1 promoter by Z-plus-R requires an intact R binding site and at least one functional Z response element (ZRE). Despite the presence of an R binding site, the BMRF1 promoter is only moderately responsive to R alone in either HeLa or Jurkat cells. Efficient activation of the BMRF1 promoter by Z alone in HeLa cells requires two ZREs (located at -59 and -106), whereas two additional Z binding sites (located at -42 and -170) contribute very little to Z-induced activation. In the absence of ZREs, Z acted as a repressor of R-induced transactivation. These observations, along with observations made by other investigators (Giot, J.F. et al., (1991) Nucleic Acids Res., 19, 1251-8), suggest that Z-plus-R cooperative activation is dependent upon 1) direct binding by R and Z to responsive promoter elements and 2) contributions by cell-specific factors.
Extension of joint diagonalization for moving targets

Joint diagonalization algorithm is extended for a time-varying mixing matrix. A new method termed “differential joint diagonalization (DJD)” is introduced to calculate the time-difference of the demixing matrix from the time-difference of the time-delayed correlations and applied to BSS algorithm based on joint diagonalization of time-delayed correlations. An alternate algorithm of differential joint diagonalization (DJD) and joint diagonalization (JD) for tracking a time-varying mixing matrix is proposed.
Directed by Directionality: Benefiting from the Gain Pattern of Active RFID Badges

Tracking of people via active badges is important for location-aware computing and for security applications. However, the human body has a major effect on the antenna gain pattern of the device that the person is wearing. In this paper, the gain pattern due to the effect of the human body is experimentally measured and represented by a first-order directional gain pattern model. A method is presented to estimate the model parameters from multiple received signal strength (RSS) measurements. An alternating gain and position estimation (AGAPE) algorithm is proposed to jointly estimate the orientation and the position of the badge using RSS measurements at known-position anchor nodes. Lower bounds on mean squared error (MSE) and experimental results are presented that both show that the accuracy of position estimates can be greatly improved by including orientation estimates in the localization system. Next, we propose a new tracking filter that accepts orientation estimates as input, which we call the orientation-enhanced extended Kalman filter (OE-EKF), which improves tracking accuracy in active RFID tracking systems.
Sadism and Cyber Aggression: Moral Identity as a Possible Moderator

ABSTRACT The present study aimed to establish the construct validity of short sadistic impulse scale (SSIS) in the Indian context. The relationship between sadism and cyber aggression was explored outside the western world directly as well as through the moderation of moral self-identity. Finally, the study investigated the relationship between moral identity and cyber aggression. The sample of study was comprised of 308 adolescents aged 16–19 years. Participants completed the SSIC, cyber aggression questionnaire, and moral identity scale to measure sadism, cyber aggression, and moral identity, respectively. Pearson correlation and moderation regression analysis were used to investigate the relationships among them. Results show that SSIS is a valid tool in the Indian context, sadism has a direct relationship with cyber aggression and moral identity internalization moderates the relationship between sadism and cyber aggression. Moral identity was found to be positively correlated with cyber aggression.
Signal and image processing techniques for VLSI failure analysis

For VLSI, internal electrical measurements are key steps to solve design debug issues and to perform failure analysis. Due to multiple metal layers, active areas of the chip are only accessible from the backside of the die. The ability of optical contactless techniques to operate through the silicon substrate and the few sample preparation required have widely contributed to promote them as unavoidable tools of the defect localization workflow. Timing issue or unusual consumption can be detected by static and dynamic photon emission analysis and Electro Optical Probing. The identification of the emission spots is an essential step of the process. Due to scaling, more and more emission nodes are located within the acquisition area so that large variations of emission intensity can exist and it is difficult to recover a signal with a good Signal to Noise Ratio (SNR). In this paper, automated techniques are reported to locate spots in these complex areas and to recover electrical waveforms with a good SNR. We will underline the challenge and define applications boundaries of these techniques. These techniques gives some perspectives for probing applications and allows FA community to use signal processing methods instead of expensive devices.
Achievement goal pursuit during the transition from middle school to high school: its antecedents and consequences from a self-determination perspective

Abstract The purpose of the study was to investigate the longitudinal reciprocal relationship between achievement goals and self-determined motivation of students transitioning from middle school to high school. Participants were 3343 students from 9th to 11th grade. The overall results showed that varying degrees of self-determined motivation from middle school (9th grade) influenced the adoption of achievement goals in the first year of high school (10th grade) and the pursuit of achievement goal in the 10th grade influenced subsequent degrees of self-determined motivation in the 11th grade. One of the notable findings is that while the initial pursuit of mastery-approach goals might begin with various degrees of self-determined motivation, involvement in the pursuit of mastery-approach goals strengthened autonomous motivation while weakening controlled motivation. The current study consolidates the theoretical and practical utility of mastery-approach goals in strengthening intrinsic motivation and internalizing external values.
The effects of rapamycin on lens epithelial cell proliferation, migration, and matrix formation: An in vitro study

Purpose The objective of the present study was to investigate the efficacy of rapamycin on rabbit lens epithelial cell proliferation, migration, and secrcetion of extracellular matrix fibronectin (Fn). Methods Rabbit lens epithelium cells (rLECs) were isolated from 1 month old rabbit. rLECs were either cultured for 24, 48, or 72 h with different doses of rapamycin (0.1, 1, and 10 ng/ml). The proliferation kinetics, proliferating cell nuclear antigen (PCNA) expression, and basic fibroblast growth factor (bFGF)-induced migration of rLEC was determined by methyl thiazol tetrazolium (MTT) assay, western blotting and transwell chamber assay, respectively. The effect of rapamycin on the synthesis of Fn was examined via immunofluorescence. Results Rapamycin significantly inhibited rLEC proliferation and PCNA protein expression when administered doses and time periods except for 0.1 ng/ml for 24 h. bFGF-induced migration rLECs was inhibited by pretreatment with rapamycin for 48 h. Extracellular matrix Fn formation of rLECs was also reduced by rapamycin. Conclusions In our study, rapamycin strongly inhibited rLEC proliferation, bFGF-induced migration, and extracellular matrix Fn formation. Thus, rapamycin may have a potential inhibition of posterior capsule opacificatin (PCO) and needs further study.
Polymer Multichip Module Process Using 3-D Printing Technologies for D-Band Applications

A novel all-in-polymer multichip module (MCM-P) process is presented for applications at D-band (110-170 GHz). The unique manufacturing approach is an additive 3-D printing approach based on a gradual photo-induced polymerization in the z-direction with metallized interconnection layers in between. The package design integrates a broadband waveguide transition nearly covering the entire D-band. Different transmission-line types for chip interconnections were characterized up to 170 GHz. In prior research, a millimeter-wave monolithic integrated circuit (MMIC) amplifier using a 50-nm metamorphic high electron-mobility transistor technology was designed. In this study, the co-design with the package is presented. The amplifier MMIC was bond-wire free embedded in an MCM-P test structure and contacted with coplanar measurement probes. A gain of more than 20 dB within 100-170 GHz was measured. Based on those results, an amplifier MCM-P with integrated waveguide transitions of size 6 mm × 4.5 mm was developed. The MCM-P was surface mounted on a printed circuit board and flipped into a waveguide test fixture. A gain of more than 20 dB remained from 125 to 155 GHz with an input and output matching better than 10 dB.
Norm Monitoring Under Partial Action Observability

In the context of using norms for controlling multiagent systems, a vitally important question that has not yet been addressed in the literature is the development of mechanisms for monitoring norm compliance under partial action observability. This paper proposes the reconstruction of unobserved actions to tackle this problem. In particular, we formalize the problem of reconstructing unobserved actions, and propose an information model and algorithms for monitoring norms under partial action observability using two different processes for reconstructing unobserved actions. Our evaluation shows that reconstructing unobserved actions increases significantly the number of norm violations and fulfilments detected.
Path Set Relaxation for Mobile Robot Navigation

This paper addresses autonomous navigation and goal acquisition for mobile robots operating in difficult, cluttered environments. In particular a hierarchical approach to navigation is of interest, which subdivides the problem into global and local components. Local planners attempt to search the continuum of actions for a best (safest, efficient) route towards a goal. To achieve real-time performance, the search space is often sampled in lowdimensional action or state space. This paper explores a relaxation-based approach that optimizes the sampled action space for the perceived environment. The gradientbased approach minimizes the cost of each motion in the path set until convergence into a local optimum is reached. Simulation experiments show that relaxed arc sets offer better approximations of the acceptable path continuum and lead to safer navigation in rough terrain and dense obstacle fields. Additional experiments explore the benefits of sampled action spaces composed of higher-order action primitives (clothoids) and a graduated fidelity inspired lookahead technique.
Information Technology in Critical Care: Review of Monitoring and Data Acquisition Systems for Patient Care and Research

There is a broad consensus that 21st century health care will require intensive use of information technology to acquire and analyze data and then manage and disseminate information extracted from the data. No area is more data intensive than the intensive care unit. While there have been major improvements in intensive care monitoring, the medical industry, for the most part, has not incorporated many of the advances in computer science, biomedical engineering, signal processing, and mathematics that many other industries have embraced. Acquiring, synchronizing, integrating, and analyzing patient data remain frustratingly difficult because of incompatibilities among monitoring equipment, proprietary limitations from industry, and the absence of standard data formatting. In this paper, we will review the history of computers in the intensive care unit along with commonly used monitoring and data acquisition systems, both those commercially available and those being developed for research purposes.
Corpus Co-Occurrence, Dictionary and Wikipedia Entries as Resources for Semantic Relatedness Information

Distributional, corpus-based descriptions have frequently been applied to model aspects of word meaning. However, distributional models that use corpus data as their basis have one well-known disadvantage: even though the distributional features based on corpus co-occurrence were often successful in capturing meaning aspects of the words to be described, they generally fail to capture those meaning aspects that refer to world knowledge, because coherent texts tend not to provide redundant information that is presumably available knowledge. The question we ask in this paper is whether dictionary and encyclopaedic resources might complement the distributional information in corpus data, and provide world knowledge that is missing in corpora. As test case for meaning aspects, we rely on a collection of semantic associates to German verbs and nouns. Our results indicate that a combination of the knowledge resources should be helpful in work on distributional descriptions.
A Novel Approach to Generate Face Biometric Template Using Binary Discriminating Analysis

In identity management system, commonly used biometric recognition system needs attention towards issue of biometric template protection as far as more reliable solution is concerned. In view of this biometric template protection algorithm should satisfy security, discriminability and cancelability. As no single template protection method is capable of satisfying the basic requirements, a novel technique for face biometric template generation and protection is proposed. The novel approach is proposed to provide security and accuracy in new user enrolment as well as verification process. This novel technique takes advantage of both the hybrid approach and the binary discriminant analysis algorithm. This algorithm is designed on the basis of random projection, binary discriminant analysis and fuzzy commitment scheme. Three publicly available benchmark face databases (FERET, FRGC, CMU-PIE) are used for evaluation. The proposed novel technique enhances the discriminability and recognition accuracy in terms of matching score of the face images and provides high security. This paper discusses the corresponding results.
The n ature of submillimetre galaxies in cosmological hydrodynamic simulations

We study the nature of rapidly star-forming galaxies at z= 2 in cosmological hydrodynamic simulations, and compare their properties to observations of submillimetre galaxies (SMGs). We identify simulated SMGs as the most rapidly star-forming systems that match the observed number density of SMGs. In our models, SMGs are massive galaxies sitting at the centres of large potential wells, being fed by smooth infall and gas-rich satellites at rates comparable to their star formation rates (SFRs). They are not typically undergoing major mergers that significantly boost their quiescent SFR, but they still often show complex gas morphologies and kinematics. Our simulated SMGs have stellar masses of M*∼ 1011−11.7 M⊙, SFRs of ∼180–500 M⊙ yr−1, a clustering length of ∼10 h−1 Mpc and solar metallicities. The SFRs are lower than those inferred from far-infrared (far-IR) data by ∼×3, which we suggest may owe to one or more systematic effects in the SFR calibrations. SMGs at z= 2 live in ∼1013 M⊙ haloes, and by z= 0 they mostly end up as brightest group galaxies in ∼1014 M⊙ haloes. We predict that higher M* SMGs should have on average lower specific SFRs, less disturbed morphologies and higher clustering. We also predict that deeper far-IR surveys will smoothly join SMGs on to the massive end of the SFR–M* relationship defined by lower mass z∼ 2 galaxies. Overall, our simulated rapid star-formers provide as good a match to available SMG data as merger-based scenarios, offering an alternative scenario that emerges naturally from cosmological simulations.
Direct adaptive NN control of ship course autopilot with input saturation

In this paper, a novel direct adaptive NN control algorithm is proposed for a class of ship course autopilot with input saturation. Neural networks (NNs) are used to tackle unknown nonlinear function, and then an adaptive NN controller is constructed by combining Lyapunov function and the backstepping technique. By utilizing a special property of the affine term, the developed scheme avoids the controller singularity problem completely, and the stability analysis subject to the effect of input saturation constrains is conducted by employing an auxiliary design system. It is also proved that the proposed algorithm could guarantee the closed-loop system to be uniformly ultimately bounded and the output of the system is proven to converge to a small neighborhood of the desired trajectory. Finally, simulation studies are given to illustrate the effectiveness and the performance of the proposed scheme.