Miracle-dz/UniFAR-FTUs huggingface dataset:
Linguistic, Pragmatic and Evolutionary Factors in Wason Selection Task

In two studies we tested the hypothesis that the appropriate linguistic formulation of a deontic rule – i.e. the formulation which clarifies the monadic nature of deontic operators should produce more correct responses than the conditional formulation in Wason selection task. We tested this assumption by presenting a prescription rule and a prohibition rule in conditional vs. proper deontic formulation. We contrasted this hypothesis with two other hypotheses derived from social contract theory and relevance theory. According to the first theory, a deontic rule expressed in terms of cost-benefit should elicit a cheater detection module, sensible to mental states attributions and thus able to discriminate intentional rule violations from accidental rule violations. We tested this prevision by distinguishing the two types of violations. According to relevance theory, performance in selection task should improve by increasing cognitive effect and decreasing cognitive effort. We tested this prevision by focusing experimental instructions on the rule vs. the action covered by the rule. In study 1, in which 480 undergraduates participated, we tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x rule formulation x type of violation x experimental instructions) between-subjects design. In study 2 – carried out by means of a 2 x 2 (rule formulation x type of violation) between-subjects design we retested the hypothesis of rule formulation vs. the cheaterdetection hypothesis through a new version of selection task in which intentional vs. accidental rule violations were better discriminated. 240 undergraduates participated in this study. Results corroborate our hypothesis and challenge the contrasting assumptions. However, they show that the conditional formulation of deontic rules produces a lower performance than what is reported in literature. Keywords—Deontic reasoning; Evolutionary, linguistic, logical, pragmatic factors; Wason selection task
Iterative Repair Planning for Spacecraft Operations Using the Aspen System

This paper describes the Automated Scheduling and Planning Environment (ASPEN). ASPEN encodes complex spacecraft knowledge of operability constraints, flight rules, spacecraft hardware, science experiments and operations procedures to allow for automated generation of low level spacecraft sequences. Using a technique called iterative repair, ASPEN classifies constraint violations (i.e., conflicts) and attempts to repair each by performing a planning or scheduling operation. It must reason about which conflict to resolve first and what repair method to try for the given conflict. ASPEN is currently being utilized in the development of automated planner/scheduler systems for several spacecraft, including the UFO-1 naval communications satellite and the Citizen Explorer (CX1) satellite, as well as for planetary rover operations and antenna ground systems automation. This paper focuses on the algorithm and search strategies employed by ASPEN to resolve spacecraft operations constraints, as well as the data structures for representing these constraints.
Programming with Logical Queries, Bulk Updates, and Hypothetical Reasoning

The paper presents a language of update programs that integrates logical queries, bulk updates and hypothetical reasoning in a seamless manner. There is no syntactic or semantic distinction between queries and updates. Update programs extend logic programs with negation in both syntax and semantics. They allow bulk updates in which an arbitrary update is applied simultaneously for all answers of an arbitrary query. Hypothetical reasoning is naturally supported by testing the success or failure of an update. We describe an alternating fixpoint semantics of update programs and show that it can express all nondeterministic database transformations.
Crowd visualization on low bandwidth mobile devices based on video analysis

Many applications need the transmission of video, which often require large bandwidth in order to obtain the desired details. However, not every detail is important in every application, e.g., surveillance only needs to capture the target of interest and alert the operator at the critical moment when action is necessary. This study aims to save bandwidth and enable many applications on resource constrained mobile devices, by simulating crowd scenes without transmitting the actual video of a scene. Current research in this area assumes the availability of Motion Capture (MoCap) data to facilitate this process. However, this is unrealistic for videos of real-world scenes captured by cameras, since they only provide a sequence of frames. The goal of this work is to emulate marker-based motion capture on a large group of people by accurately tracking pedestrians and simulating their motions in a 3D environment. The tracked positions can be input into a simulation environment to approximate motions of pedestrian movement. While the general scene is simulated realistically in the background, the target pedestrian trajectory can be tracked and monitored accurately. We describe pedestrian tracking using our own panoramic tracking hardware, as well as using normal video cameras. Our results show that it is possible to detect individuals in a crowd and simulate real world crowds from video.
Exploration of Surfaces for Robot Mobility

This paper presents an overview of ongoing research in surface exploration at the GRASP Lab. The objective of the work presented here is to design a system that will explore an environment that is unknown and unconstrained and will enable a robot to adapt to varying surroundings. We are investigating the necessary components/modules that must be embedded into a robot for it to have exploratory capabilities. We have designed and are implementing exploratory procedures (ep's) to recover the mechanical properties from a surface given minimal a priori information so that a robot or a vehicle can decide whether to and how to move on this surface. The laboratory setup involves a compliant wrist with six degrees of freedom, mounted on a robot arm, and a laser range finder, mounted on another robot arm, as the primary sensors to detect the response of surfaces with varying mechanical properties. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-90-42. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/cis_reports/554 Exploration of Surfaces For Robot Mobility MS-CIS-90-42 GRASP LAB 222 Pramath R. Sinha Ruzena Bajcsy Department of Computer and Information Science School of Engineering and Applied Science University of Pennsylvania Philadelphia, PA 19104
Regulation of matrix metalloproteinase expression by tumor necrosis factor in a murine model of retinal neovascularization.

PURPOSE Hypoxia and growth factors are postulated to be involved in the development of retinal neovascularization through the regulation of extracellular proteinase production. It has been shown that matrix metalloproteinases (MMPs) are elevated in the retina during the neovascularization process. However, the factors and mechanisms that regulate the expression of these enzymes are not well characterized. The present study examines the potential role of tumor necrosis factor (TNF)-alpha as a regulator of MMPs in the retinal neovascularization process. METHODS C57/Bl6 mice were treated with 75% oxygen (experimental) or room air (control) from postnatal days (P)7 through P12, followed by room air until P17. Retinas were collected at P13, P15, or P17 and total RNA analyzed for the relative level of TNFalpha, TNF receptor (p55), and TNFalpha-converting enzyme (TACE). Immunostaining was used to identify changes in TNF protein expression as well as to localize TNFalpha within specific retinal cell types. The role of TNFalpha in stimulating retinal microvascular endothelial cell (RMVEC) proteinase production was evaluated using isolated murine RMVECs grown in normoxic or hypoxic conditions. Message expression was analyzed by RT-PCR and protein expression by zymographic analysis. RESULTS TNFalpha mRNA was increased in the retinas of experimental animals on P13 and P15, during the early stages of retinal neovascularization. In addition to being expressed by Müller glial cells and the inner nuclear layer, additional expression was noted in the outer nuclear layer of experimental animals. No significant level of apoptosis was detected in the retina of experimental animals with retinal neovascularization. Isolated RMVECs did not significantly increase MMP production directly in response to a hypoxic stimulus, but required the presence of exogenous TNFalpha. TNFalpha increased the expression of MT1-MMP, MMP-3, and MMP-9 in these cells. The levels of TACE and p55, proteins important in mediating the response of cells to TNFalpha, were found to be increased by the angiogenic protein, vascular endothelial growth factor (VEGF), which was also elevated in the experimental retinas. CONCLUSIONS TNFalpha levels increase in experimental mouse retinas exposed to hypoxic stimuli. Increased production of MMPs by RMVECs does not occur directly in response to a hypoxic stimulus. These cells are responsive, however, to stimulation by TNFalpha, which enhances the production of specific members of the MMP family. VEGF also plays a role in this process through its regulation of TACE and p55 mRNA in the vascular endothelial cells. These findings support the hypothesis that these two growth factors have a role in the regulation of extracellular proteinase expression during retinal neovascularization.
Vehicles relative positioning based on ZigBee and GPS technology

Traditional on-board sensors such as camera, radar and LiDAR (light detection and ranging) cannot fully perceive surrounding environment or function well under severe weather like V2V technology does. For instance, millimeter wave radar based adaptive cruise control system does not perform well when host vehicle is driving from straight line into a curve. Forward collision warning system becomes invalid once encountering heavy fog or heavy snow weather. In contrast, V2V technology is not only applicable to various weather but also with further detecting range than radar and LiDAR, which seems more attractive and feasible to handle more types of driving circumstances. This paper first tested GPS positioning accuracy under campus environment, then used ZigBee to exchange information (speed, heading and brake status, etc.) between vehicles, and eventually this paper accomplished relative positioning by combining GPS and V2V technologies.
The Bias Problem and Language Models in Adaptive Filtering

We used the YFILTER filtering system for experiments on updating profiles and setting thresholds. We developed a new method of using language models for updating profiles that is more focused on picking informative/discriminative words for query. The new method was compared with the well-known Rocchio algorithm. Dissemination thresholds were set based on maximum likelihood estimation that models and compensates for the sampling bias inherent in adaptive filtering. Our experimental results suggest that using what kind of distribution to model the scores of relevant and non- relevant documents is corpus dependant. The experimental results also show the sampling bias problem of training data while filtering makes the final profile learned biased.
A testability-driven optimizer and wrapper generator for embedded memories

Memory cores (especially SRAM cores) used on a system chip usually come from a memory compiler. Commercial memory compilers have their limitation-a large memory may need to be implemented with multiple small memories, if generated by memory compilers. In this paper we introduce a testability-driven memory optimizer and wrapper generator that generates BISTed embedded memories by using a commercial memory compiler. We describe one of its key components called MORE (for Memory Optimization and REconfiguration). The approach is cost effective for designing embedded memories. By configuring small memory cores into the large one specified by the user and providing the BIST circuits, MORE allows the user to combine the commercial memory compiler and our memory BIST compiler into a cost-effective testability-driven memory generator. The resulting memory has a shorter test time, since the small memory cores can be tested in parallel, so far as the power and geometry constraints are considered. As an example, the test time of a typical 256 K/spl times/32 memory generated by MORE is reduced by about 75%.
Understanding the longevity of code smells: preliminary results of an explanatory survey

There is growing empirical evidence that some (patterns of) code smells seem to be, either deliberately or not, ignored. More importantly, there is little knowledge about the factors that are likely to influence the longevity of smell occurrences in software projects. Some of them might be related to limitations of tool support, while others might be not. This paper presents the preliminary results of an explanatory survey aimed at better understanding the longevity of code smells in software projects. A questionnaire was elaborated and distributed to developers, and 33 answers were collected up to now. Our preliminary observations reveal, for instance, that smell removal with refactoring tools is often avoided when maintaining frameworks or product lines.
A design of a miniaturized prosthetic wrist based on repetition rate of human wrist daily tasks

A design of miniaturized prosthetic wrist is proposed in this paper. Firstly, based on the wrist function, we divided daily activities into 4 scenarios, 12 behaviors and 30 wrist daily tasks in total. Secondly, according to the motion classification and the prerequisite of independent rotational DoF of the wrist, the 4 simplified trajectory, wrist repetition patterns(WRP), were obtained. Then, we presented a method of estimating repetition rate of human wrist daily tasks(RHWDT) direct at one certain WRP using collection data from questionnaires. With the guideline of RHWDT, we finally obtained a mechanical structure and the design was verified by analyzing the performance of the structure.
Nonnegative Tucker Decomposition

Nonnegative tensor factorization (NTF) is a recent multiway (multilinear) extension of nonnegative matrix factorization (NMF), where nonnegativity constraints are imposed on the CANDECOMP/PARAFAC model. In this paper we consider the Tucker model with nonnegativity constraints and develop a new tensor factorization method, referred to as nonnegative Tucker decomposition (NTD). The main contributions of this paper include: (1) multiplicative updating algorithms for NTD; (2) an initialization method for speeding up convergence; (3) a sparseness control method in tensor factorization. Through several computer vision examples, we show the useful behavior of the NTD, over existing NTF and NMF methods.
The Efficient Use of Storage Resources in SAN for Storage Tiering and Caching

With the rapid growth of the Hyper Convergence (HC) the use of the Solid State Device (SSDs) as the intelligent Storage Tiering and caching has increased immensely. It plays an important role to provide high throughput and performance with maximum utilization of the SSD storage space considering the life cycle of SSDs and workload. Efficient Utilization of such resources is one of the main criterion of the virtualization technology. By considering the rise of the VDI workload the proposed implementation of a sequential write detection algorithm, we try to maximize the utilization of higher tier storage such as SSDs (Tier 0) by placing the data which fall under the category of sequential writes into the lower tier disks (Tier 1, 2 - n) such as SAS (serial attached SCSI) / SATA (serial advanced technology attachment).
Irbesartan in patients with heart failure and preserved ejection fraction.

BACKGROUND Approximately 50% of patients with heart failure have a left ventricular ejection fraction of at least 45%, but no therapies have been shown to improve the outcome of these patients. Therefore, we studied the effects of irbesartan in patients with this syndrome. METHODS We enrolled 4128 patients who were at least 60 years of age and had New York Heart Association class II, III, or IV heart failure and an ejection fraction of at least 45% and randomly assigned them to receive 300 mg of irbesartan or placebo per day. The primary composite outcome was death from any cause or hospitalization for a cardiovascular cause (heart failure, myocardial infarction, unstable angina, arrhythmia, or stroke). Secondary outcomes included death from heart failure or hospitalization for heart failure, death from any cause and from cardiovascular causes, and quality of life. RESULTS During a mean follow-up of 49.5 months, the primary outcome occurred in 742 patients in the irbesartan group and 763 in the placebo group. Primary event rates in the irbesartan and placebo groups were 100.4 and 105.4 per 1000 patient-years, respectively (hazard ratio, 0.95; 95% confidence interval [CI], 0.86 to 1.05; P=0.35). Overall rates of death were 52.6 and 52.3 per 1000 patient-years, respectively (hazard ratio, 1.00; 95% CI, 0.88 to 1.14; P=0.98). Rates of hospitalization for cardiovascular causes that contributed to the primary outcome were 70.6 and 74.3 per 1000 patient-years, respectively (hazard ratio, 0.95; 95% CI, 0.85 to 1.08; P=0.44). There were no significant differences in the other prespecified outcomes. CONCLUSIONS Irbesartan did not improve the outcomes of patients with heart failure and a preserved left ventricular ejection fraction. (ClinicalTrials.gov number, NCT00095238.)
A Lévy HJM multiple-curve model with application to CVA computation

We consider the problem of valuation of interest rate derivatives in the post-crisis set-up. We develop a multiple-curve model, set in the HJM framework and driven by a Lévy process. We proceed with joint calibration to OTM swaptions and co-terminal ATM swaptions of different tenors, the calibration to OTM swaptions guaranteeing that the model correctly captures volatility smile effects and the calibration to co-terminal ATM swaptions ensuring an appropriate term structure of the volatility in the model. To account for counterparty risk and funding issues, we use the calibrated multiple-curve model as an underlying model for CVA computation. We follow a reduced-form methodology through which the problem of pricing the counterparty risk and funding costs can be reduced to a pre-default Markovian BSDE, or an equivalent semi-linear PDE. As an illustration, we study the case of a basis swap and a related swaption, for which we compute the counterparty risk and funding adjustments.
Path planner for unmanned aerial vehicles based on modified PSO algorithm

Most path planning algorithms existed have disadvantages in space representation, constraints handling or computation efficiency. Combining particle swarm optimization with path planning problem for unmanned aerial vehicles (UAVs), a new path planner for aerial vehicles based on modified PSO algorithm is presented. Path planning problem is modeled as a 5-element array. Incorporating constraints into fitness evaluation reduces search space while a modified PSO algorithm is introduced to improve global optimization performance. Experiment results demonstrate that the proposed method is able to solve path planning problem effectively and provide a feasible path in a short time.
A study on spoofing attack in state-of-the-art speaker verification: the telephone speech case

Voice conversion technique, which modifies one speaker's (source) voice to sound like another speaker (target), presents a threat to automatic speaker verification. In this paper, we first present new results of evaluating the vulnerability of current state-of-the-art speaker verification systems: Gaussian mixture model with joint factor analysis (GMM-JFA) and probabilistic linear discriminant analysis (PLDA) systems, against spoofing attacks. The spoofing attacks are simulated by two voice conversion techniques: Gaussian mixture model based conversion and unit selection based conversion. To reduce false acceptance rate caused by spoofing attack, we propose a general anti-spoofing attack framework for the speaker verification systems, where a converted speech detector is adopted as a post-processing module for the speaker verification system's acceptance decision. The detector decides whether the accepted claim is human speech or converted speech. A subset of the core task in the NIST SRE 2006 corpus is used to evaluate the vulnerability of speaker verification system and the performance of converted speech detector. The results indicate that both conversion techniques can increase the false acceptance rate of GMM-JFA and PLDA system, while the converted speech detector can reduce the false acceptance rate from 31.54% and 41.25% to 1.64% and 1.71% for GMM-JFA and PLDA system on unit-selection based converted speech, respectively.
Participatory Design Process with Older Users

This paper reflects on two months of conducting intensive participatory design with a team of five senior citizens, with the purpose of transforming an off-the-shelf mobile phone into a specially-designed memory aid. We discuss the activities we used to engage the seniors, and how we used a combination of sources to influence the needs analysis phase. We also reflect on three selected themes that emerged during the process.
Viability and predictive control for safe locomotion

The problem of safe locomotion of legged and wheeled robots, when trying to avoid falling, tipping over or hitting obstacles, appears to be a problem of viability and not of Lyapunov stability. Theoretically speaking, viability and model predictive control are unquestionably related, but both can quickly lead to untractable numerical problems. We present here a promising approach for the problem of avoiding to fall in the case of legged locomotion that elegantly solves this difficulty. We propose then a brief discussion about what makes this approach successful with respect to the approaches proposed for the other problems where viability is at stake. This paper should be considered therefore mostly as a prospective reflection on the general problem of safe robotic locomotion.
A two‐stage model for incidence and prevalence in point‐level spatial count data

We consider the problem of modeling point‐level spatial count data with a large number of zeros. We develop a model that is compatible with scientific assumptions about the underlying data‐generating process. We utilize a two‐stage spatial generalized linear mixed model framework for the counts, modeling incidence, resulting in 0–1 outcomes, and prevalence, resulting in positive counts, as separate but dependent processes and utilize a Gaussian process model for characterizing the underlying spatial dependence. We describe a Bayesian approach and study several variants of our two‐stage model. We fit the models via Markov chain Monte Carlo methods. We study several Markov chain Monte Carlo algorithms, including a version of the Langevin–Hastings algorithm, for exploring the complicated posterior distribution efficiently and recommend an algorithm that is fairly efficient. Finally, we demonstrate the application of our modeling and computational approach on both simulated data and real data from an ecological field survey. Copyright © 2011 John Wiley & Sons, Ltd.