Miracle-dz/UniFAR-FTUs huggingface dataset:
Placement Optimization for Yield Improvement of Switched-Capacitor Analog Integrated Circuits

Capacitor mismatch can generally result from two sources of error: random mismatch and systematic mismatch. Random mismatch is caused by process variation, while systematic mismatch is mainly due to an asymmetrical layout and processing gradients. A common centroid structure may be used to reduce systematic mismatch errors, but not random mismatch errors. Based on the spatial correlation model, this paper formulates the placement optimization problem of analog circuits using switched-capacitor techniques. A placement with higher correlation coefficients of the unit capacitors results in a higher acceptance rate, or chip yield. This paper proposes a heuristic algorithm that quickly and automatically derives the placement of the unit capacitors with the highest, or near-highest, correlation coefficients for yield improvement. Results show that the resultant placement derived from the proposed algorithm achieves better yield improvement than that from a common centroid approach. The proposed heuristic algorithm can be applied for any arbitrary capacitor ratios, i.e., more than two capacitors.
Optimal Vessel Quotas and Capacity of a Danish Trawler Fleet Segment: A Dual Approach

In the period of investigation, 1995-2000, the Danish fishery for species meant for human consumption was managed by individual non-transferable vessel quotas, while the fishery for species meant for fishmeal and fish oil was subject to a total quota. The revenues of the fishermen targeting species for human consumption are therefore fixed on the assumption that they are price takers, and that they will maximize profits by minimizing their costs. To model the economic behaviour of the fishermen in terms of the optimal quota size per vessel and optimal fleet size, a dual cost-function approach is an appropriate choice. This method is applied using a generalized Leontief cost function to model the behaviour of the Danish fleet of trawlers below 50 GRT, targeting species for human consumption solely. The estimated cost function is used to determine the optimal quotas yielding: (i) minimum average cost and (ii) maximum profit. The results of the estimations show that the optimal quotas per vessel should be increased by more than 2.5 times and consequently that the fleet should be reduced by more than 60%. As this has not been the case, a probable explanation is that non-transferable quotas leave the fishermen with the option of quitting the fishery only if a decommissioning programme is in place. There is no option to transfer the quota to another vessel.
Weighted MUSE for Frequent Sub-Graph Pattern Finding in Uncertain DBLP Data

Studies shows that finding frequent sub-graphs in uncertain graphs database is an NP complete problem. Finding the frequency at which these sub-graphs occur in uncertain graph database is also computationally expensive. This paper focus on investigation of mining frequent sub-graph patterns in DBLP uncertain graph data using an approximation based method. The frequent sub-graph pattern mining problem is formalized by using the expected support measure. Here n approximate mining algorithm based Weighted MUSE, is proposed to discover possible frequent sub-graph patterns from uncertain graph data
Framing and counter-framing a Peace March in Russia: the use of Twitter during a hybrid war

ABSTRACT Framing is vital to the capacity of social movements to enlist popular support and sustain contentious collective action. Using the case of a Peace March held in Moscow on 21 September 2014, the article examines how antiwar activists and their opponents framed a protest against Russia’s intervention in Ukraine. The study argues that different interpretations of patriotism underpinned divergent evaluations of the conflict and the construction of opposing identities. An analysis of Twitter posts on the eve of the march shows that peace activists positioned themselves as citizens with high moral standards and a healthy dose of patriotism, criticized the Russian government for military intervention in Ukraine, and called for a peaceful conflict resolution. In turn, opponents of the march considered themselves as real patriots and their adversaries as national traitors, denied Russia’s military presence in Ukraine, and fomented an attack on critics of Russian foreign policy. The study contributes to social movement literature by analyzing the framing of antiwar activism on a social media platform in the midst of a hybrid war, marked by a great deal of ambiguity and deception about causes, dynamics, and consequences of military operations by state and non-state actors.
In Search of the Defensive Function of Sexual Prejudice : Exploring Antigay Bias Through Shorter and Longer Lead Startle Eye Blink

To explore the theory that some men experience antigay bias because of a defensive reaction to uncertainties surrounding their own sexuality (cf. Herek, 1987), we conducted a study (n = 132 men) in which we physiologically measured the affective underpinnings of antigay bias while individuals with different levels of self-reported bias viewed sexually explicit material. Those higher in antigay bias exhibited less positive affect than did others, but did not appear to experience a defensive reaction. Given these results, combined with those of our previous studies, we conclude that evidence for the existence of a group of men who exhibit antigay bias because of a hidden or unconscious attraction toward men is difficult to demonstrate using current methodology. jasp_700 27.44
Reciprocity as a social multiplier: the case of experience goods

Reciprocal customers may disproportionately improve the performance of markets for experience goods. Reciprocal customers reward (punish) firms for providing good (bad) quality by upholding (terminating) the customer relation. This may induce firms to provide good quality. Reciprocal customers can be social multipliers in two ways. First, reciprocal customers cause a positive externality for non-reciprocal customers, inducing them to also engage in customer relations. Second, reciprocity provides firms with additional incentives to provide good quality if customers have social ties among each other. Hence, reciprocity induces customer relations and makes social ties among customers e¤ective in mitigating market failure.
Impact of Maternal Mental Health on Pediatric Asthma Control

Background Asthma like other chronic diseases is a stressful condition not only for children but also for their parents. Caring for a child with asthma combines the demands of parenting with the emotional and physical burdens of the child's chronic illness. Some studies have assessed the relations between parental mental health and asthma severity in children. This study aims to evaluate the mental health of mothers of asthmatic children and associations between maternal mental health and childhood levels of asthma control. Materials and Methods Eighty mothers with asthmatic children aged 7-12 yrs. completed a General Health Questionnaire (GHQ.28) containing questions about somatic symptoms, anxiety, social dysfunction, and severe depression. Level of asthma control in children was classified as “well controlled”,” partly controlled” and “uncontrolled” by an asthma specialist. Results The results showed that mothers of asthmatic children reported the depression symptoms significantly more than the community cut-off point (p<0.001); also GHQ scores were not significantly different in three levels of asthma control in children (i.e. well controlled, partly controlled and uncontrolled). The results revealed that caring for a child with asthma had an impact on the mother's mental health and depression was prevalent among mothers of asthmatic children. In addition, improving asthma control level did not promote maternal mental health. Conclusion Inclusion of mental health and quality of life of parents in the classification of pediatric asthma control may be helpful. Our findings suggest that the physician's awareness of maternal depression and the presence of a psychotherapist for diagnosing and treating depression in mothers of children with asthma may be important for guiding effective interventions.
On an additive arithmetic function.

We discuss in this paper arithmetic properties of the function A(n) = Σ p a Un ap. Asymptotic estimates of A(n) reveal the connection between A(n) and large prime factors of n. The distribution modulo 2 of A(n) turns out to be an interesting study and congruences involving A(n) are con-sidered. Moreover the very intimate connection between A(n) and the partition of integers into primes provides a natural motivation for its study.
A Three-mode, Variable Velocity Jet Model for HH 34

Variable ejection velocity jet models can qualitatively explain the appearance of successive working surfaces in Herbig-Haro (HH) jets. This paper presents an attempt to explore which features of the HH 34 jet can indeed be reproduced by such a model. From previously published data on this object, we find evidence for the existence of a three-mode ejection velocity variability and then explore the implications of such a variability. From simple, analytic considerations it is possible to show that the longer period modes produce a modulation of the shorter period modes, resulting in the formation of "trains" of multiple knots. The knots observed close to the source of HH 34 could correspond to such a structure. Finally, a numerical simulation with the ejection velocity variability deduced from the HH 34 data is computed. This numerical simulation shows a quite remarkable resemblance with the observed properties of the HH 34 jet.
Assistive visual framing in 3D dense points cloud

Recent progress in digital technology and its popularity in the context of cultural heritage are contributing to the emergence of several applications using a very large and dense digitization of archaeological sites or historical monuments. Navigation in such virtual environment is difficult especially for novice users. In this paper, we propose a new approach in order to make easier the navigation process by performing an assistive visual framing. This approach exploits a new visual feature: the image saliency-based Gaussian mixture. We applied our method on many different environments and we present the example of the Saint Sébastien chapel of the cathedral Notre Dame of Amiens. In order to evaluate our method, we present user evaluation and comparison between manual, assistive and automatic framing.
Effect of Certolizumab Pegol Over Ninety-Six Weeks in Patients With Axial Spondyloarthritis: Results from a Phase III Randomized Trial

Previous reports of the RAPID‐axSpA trial (NCT01087762) described the efficacy and safety of certolizumab pegol (CZP) over 24 weeks in patients with axial spondyloarthritis (SpA), including ankylosing spondylitis (AS) and nonradiographic axial SpA. We report efficacy and safety data up to week 96 of the study.
State estimation in Networked Control Systems

We consider the problem of state estimation in a Networked Control System, where measurements and control inputs are transmitted via a communication network. The network is subject to time-varying delays and stochastic data losses and does not provide acknowledgments of successfully transmitted data packets. A challenge that arises in this configuration is that the estimator has only uncertain information about the actually applied control inputs. In this paper, we derive a multiple-model based estimator that uses the state measurements to estimate the applied control inputs so that the overall state estimation is improved. The efficiency of the proposed approach is demonstrated by means of Monte-Carlo-Simulation runs with an inverted pendulum on a cart.
Population-Based Incremental Learning to Solve the FAP Problem

Frequency assignment problem (FAP) is a very important issue in the field of telecommunications (especially in GSM-Global System for Mobile-Networks). In this work, we present the Population-Based Incremental Learning (PBIL) algorithm to solve a particular branch of the FAP problem (MS-FAP). MS-FAP (Minimum Span Frequency Assignment Problem) tries to minimize the range of frequencies which is necessary in a certain area to cover the communications which take place there. In this paper it is presented the problem and it is explained the methodology which solve it. We have performed tests with a complete set of experiments using seven well known variations of PBIL and 7 types of MS-FAP problems. At the end, the results are presented and we compare them to conclude which variation of PBIL provides the best solution to the MS-FAP problem.
Computationally Efficient Convolved Multiple Output Gaussian Processes

Recently there has been an increasing interest in regression methods that deal with multiple outputs. This has been motivated partly by frameworks like multitask learning, multisensor networks or structured output data. From a Gaussian processes perspective, the problem reduces to specifying an appropriate covariance function that, whilst being positive semi-definite, captures the dependencies between all the data points and across all the outputs. One approach to account for non-trivial correlations between outputs employs convolution processes. Under a latent function interpretation of the convolution transform we establish dependencies between output variables. The main drawbacks of this approach are the associated computational and storage demands. In this paper we address these issues. We present different efficient approximations for dependent output Gaussian processes constructed through the convolution formalism. We exploit the conditional independencies present naturally in the model. This leads to a form of the covariance similar in spirit to the so called PITC and FITC approximations for a single output. We show experimental results with synthetic and real data, in particular, we show results in school exams score prediction, pollution prediction and gene expression data.
Induction of neoplasia in vitro with a virus; experiments with rabbit skin grown in tissue culture and treated with Shope papilloma virus.

Since neoplasia has been induced in tissue culture by means of a chemical carcinogen (5), the question arises whether similar neoplastic transformation of cells in vitro can be brought about by other types of carcinogens, such as viruses. This question was answered by successfully growing epidermis of the domestic rabbit in tissue culture and then inoculating it with the Shope papilloma virus. The experiments to be reported show that under these conditions, neoplastic transformation of epithelial cells occurs in vitro.
Training Simulation of the Manipulator Vehicle tEODor for Explosive Ordnance Disposal ( EOD ) and Improvised Explosive Device Disposal ( IEDD )

The simulation of manipulator vehicles is a challenge in the field of EOD and IED disposal training. The focus in such vehicle simulations is to reproduce the behavior of the vehicle in terms of control and movement and also to simulate interactions with the environment in order to prepare the user for real operations. In this contribution an approach will be presented to ensure the quality of the implemented robot simulation for IED disposal training purposes. Classification: I.2. 9, I.6. 1, J2
Academic help seeking and peer interactions of high school girls in computer science classes

Through interviews and classroom observations, this study investigated the academic help-seeking and interactions of high school girls with their computer science classmates in both a private school and a public school setting. The study explored five aspects of this help-seeking interaction: (1) females as a gender minority in computer science; (2) determinants of peer interaction; (3) teacher versus peer assistance; (4) factors detracting from willingness to assist peers; and (5) preference for group interaction. A key finding was that physical proximity was an important determinant of help-seeking behaviors in a high school computer lab. Another finding was that girls in the sample often asked their peers for help even when they preferred the teacher's help and believed that the teacher was more knowledgeable. One counter-intuitive finding was that most girls preferred to work individually in a setting in which there was already substantial peer interaction. One implication of this study is that teachers should be wary of applying the general finding that girls prefer group work to every girl in the class and should instead respect the preference of the individual. If the findings are found in other settings, then a recommendation might be that in order to maximize help-seeking, talented programming students should be evenly distributed throughout the classroom. (Contains 33 references.) (Author/MES) Reproductions supplied by EDRS are the best that can be made from the original document. Academic Help Seeking and Peer Interactions of High School Girls in Computer Science Classes Paul S. Oberman Division of Educational Studies Emory University 1748 N. Decatur Building, Suite 240 Atlanta, GA 30322 For the unabridged version, contact: Poberma@emory.edu Paper presented at the American Educational Research Association April 2000 New Orleans, Louisiana PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
Forecast evaluation with Stata United Kingdom Stata Users Group Conference London School of Hygiene and Tropical Medicine

In addition to the people at Stata –particularly, Bill Gould, Vince Wiggins, David Draper, Brian Poi, Robert Guiterrez, Jef Pitblado, Kerry Kammire, Ryman Tiu, Bill Rising, Alan Riley, Alan Acock – who have been very supportive and helpful, I am very grateful to the help and support of my dear friend Ana Timberlake who actually began the Stata Users Group conference in the United Kingdom. I also would like to thank Sir David Hendry, Jürgen Doornik, Neil Ericsson, Andrew C. Harvey, Siem-Jan Koopman and Sebastien Laurent for their intellectual support and guidance. I also need to thank David Corbett and Teresa Timberlake, Ashley Dyer, and Noelia Germino for their indispensable logistical support and encouragement.
Cooperative MAC protocol with distributed relay selection and physical rate adaptation

In this paper, a new cooperative MAC protocol with distributed relay selection and rate adaptation is proposed in the context of multi-rate ad hoc networks. When the wireless link between a source and a destination nodes experiences poor channel conditions, a relay station is selected in the vicinity of both nodes so that the low data rate direct link is replaced by a two-hop path with a higher data rate. The relay station is selected through a distributed contention process. The procedure requires no topology knowledge and no communication among potential relays. A data rate adaptation is also performed without any additional signaling. The best-relay selection and the rate adaptation are based on instantaneous channel measurements to adapt to dynamic channel conditions. Results show that cooperative transmissions significantly outperform conventional non-cooperative transmissions in terms of throughput, delay and energy consumption.
Learning Causal Models via Progressive Alignment & Qualitative Modeling : A Simulation

Learning causal models is one of the central problems of cognitive science. We describe a simulation of early learning in physical domains from observations that uses progressive alignment and qualitative modeling to derive plausible causal models from observations. We show how protohistories can be created via progressive alignment and used with covariance algorithms to infer causality. The result, a causal corpus described using qualitative representations, can make simple predictions and set the stage for more sophisticated later models. The simulation has been successfully tested with three learning problems, with encouraging results.
Face recognition based on Second Generation of Curvelet Transform and Kernel Principal Component Analysis

A new face recognition method is proposed by adopting the Second Generation of Curvelet Transform (SGCT) and Kernel Principal Component Analysis (KPCA). Based on KPCA, the face recognition algorithm can extract nonlinear image features and show better performance under the conditions of small sample training. However, the disadvantage of KPCA is the image information redundancy, which reduces the recognition performance. Traditional wavelet transform method of preprocessing removes irrelevant details of identification, but in high-dimensional image signal, the wavelet analysis is not the optimal method. In this paper, the new multi-scale geometric analysis, SGCT, is proposed to preprocess the image in order to reduce the high dimensional operators and improve accuracy of KPCA. Based on ORL database, experimental results show that the proposed method has a faster recognition speed and higher recognition accuracy than the traditional methods.
Differential Variability of Test Scores among Schools: A Multilevel Analysis of the Fifth-Grade INVALSI Test Using Heteroscedastic Random Effects.

The performance of a school system can be evaluated through the learning levels of the pupils, usually summarized by school mean scores. The variability of the mean scores among schools is rarely studied in detail, though it is a crucial issue especially in primary schools: in fact, a high variability among schools raises doubts on the capacity of the system to guarantee equal educational opportunities. To investigate the patterns of variability in Italy, we analyse data from INVALSI, the Italian national institute for the evaluation of the school system, which regularly carries out standardized tests to assess the learning levels of the pupils at various grades. We consider the mathematics test administered to fifth-grade pupils at the end of the 2008/2009 year, along with a pupil's questionnaire for measuring socio-economic factors. The analysis is performed using a random intercept linear model on the Rasch score of the mathematics test, with pupil-level errors depending on gender and school-level errors depending on the geographical area. The model includes several demographic and socioeconomic explanatory variables and some compositional variables obtained as school means of pupil variables. The results show a considerable increase in the residual variance among schools when going from North to South, pointing out a serious issue of fairness in Southern Italy. The situation is mitigated by the finding that a substantial part of the residual variance among schools is due to a few schools with exceptionally positive results.
Review of Data Mining Techniques in Cloud Computing Database

Data mining is the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. It is the extraction of information from huge volume of data or set through the use of various data mining techniques. The data mining techniques like clustering, classification, neural network, genetic algorithms help in finding the hidden and previously unknown information from the database. Cloud Computing is a web-based technology whereby the resources are provided as shared services. The large volume of business data can be stored in Cloud Data centres with low cost. Both Data Mining techniques and Cloud Computing helps the business organizations to achieve maximized profit and cut costs in different possible ways. The main aim of the work is to implement data mining technique in cloud computing using Google App Engine and Cloud SQL.