Miracle-dz/UniFAR-FTUs huggingface dataset:
Critical Communities: Intellectual Safety and the Power of Disagreement.

I was involved in p4c Hawai‘i for many years during my graduate studies. It was my first introduction to “teaching,” or, more accurately, the facilitation of philosophical inquiry. I cannot imagine a better way to prepare for a lifetime of such work, though admittedly, the wisdom, imagination, and openness to the world expressed by my young students then has set the bar very high for the men and women I now see on a daily basis. For this reason, I begin each semester anew with the promise of philosophy for children; the promise of a term filled with fruitful dialogue and hard thinking as well as laughter and camaraderie. What I would call the “p4c pedagogy” has become infused into my undergraduate teaching. The Good Thinker’s Toolkit, the model of reflective community inquiry, and the desire to “scratch beneath the surface” are woven into the foundation of my courses, even when p4c is never explicitly discussed. At the beginning of each semester though, there is one concept that stands out as a recurring challenge: intellectual safety. Intellectual safety is often conflated with the feeling of being comfortable. Susan Herbst (2010), in her book Rude Democracy, writes that, “72 percent of students agreed that it was very important for them always to feel comfortable in class. ” I imagine this feeling of comfort as similar to feelings of relaxation and belonging, free of stress and doubt, while being entertained, amused, or satisfied in some way. Herbst adds to this sense by including the students’ desire to remain “unthreatened intellectually. ” While we may all strive to maintain classrooms absent of physical or emotional threats, a college classroom without intellectual challenges is likely one of complacency and mental laziness. It is my claim that intellectual growth, for both an individual and a community, must involve some kind of discomfort. I see this discomfort as a natural by-product of an initiation to interactive, dialogue-driven learning. A Ashby Butnor
A comparison of job satisfaction between it and non-IT women incumbents in clerical, professional, and managerial positions

One explanation for the well-documented underrepresentation of women in IT jobs is that these jobs are somehow less satisfying for women. This study is the most complete investigation to date of whether this is true, and if so, in what aspects are IT jobs less satisfying. We examine facets of job satisfaction that merit employer attention and suggest intervention to increase the attractiveness of IT careers for women. In a representative sample of 9,617 employed women in the U.S., we compared women in IT employed at the clerical, professional, and managerial levels to comparable groups of non-IT employees on six important facets of job satisfaction with: job security, work itself, supervisor, compensation, work/life balance, and advancement/opportunities. For most facet comparisons across job levels, differences were not significant, generally indicating that IT careers are not less satisfying for women than comparable non-IT alternatives. However, satisfaction with work itself and job security were lower for women in professional IT jobs than for those in professional non-IT jobs. We finally discuss the implications of these findings for researchers and those who advise women on career choices.
Improving Financial Inclusion through Communal Financial Orientation: How Financial Service Providers Can Better Engage Consumers in Banking Deserts

Banking deserts, vulnerable communities that lack access to mainstream banks, represent a serious societal problem. Mainstream banks successfully entering banking deserts can help to assuage this problem. Drawing from research on the psychological consequences of poverty, we propose that mainstream banks can more successfully operate in banking deserts by increasing consumers’ perception of communal financial orientation as a bank benefit (i.e., consumers’ perception that engaging with the bank is beneficial for their community’s well-being). Two field studies, comparing customers of a credit union who live in a banking desert and those who do not, show that the perception of communal financial orientation as a bank benefit increases bankingdesert consumers’ beliefs that engaging with the credit union is beneficial and increases their likelihood of patronizing and recommending it; consumers living outside banking deserts do not display these effects. These findings provide novel insights into psychological mechanisms distinctly associated with banking-desert consumers and establish the importance of communal financial orientation. This is a win-win proposal for under-served communities and financial service providers because it helps both improve financial inclusion and increase the viability of serving banking deserts.
Enhancing information lookup privacy through homomorphic encryption

Revealing one’s interests in communication has been recognized as a growing problem in the Internet. We postulate that it is desirable for future information retrieval systems to provide privacy in both what information is requested and what information is received, without raising obstacles to the deployment of accounting and access control mechanisms. This paper outlines a solution that fulfills this requirement in the context of broker-based systems, that is, systems in which brokers facilitate the communication between a consumer and a provider (of information). Broker-assisted communication is a common paradigm used in many settings, including contemporary information-centric networking approaches. We present the design and the evaluation of a solution that conceals consumers’ interests, without hiding consumer identity or location. The developed solution is applied over a system of hierarchically organized brokers; similar systems are used in many information lookup services. Because in these systems, information is distributed in various locations, traditional private information retrieval (PIR) protocols exhibit significant communication overhead. Our solution achieves up to 97% less communication overhead compared with a PIR protocol, without additional computational overhead. Copyright © 2013 John Wiley & Sons, Ltd.
A robust improved Chan-Vese model based on Gaussian regularizing level set

In this paper, a new robust improved Chan-Vese (ICV) model is proposed for image segmentation, which is built based on the techniques of curve evolution, signed pressure force (SPF) function and level set method. Compared with the ICV model, the proposed method is more robust to the location of the initial contour. Similar to the ICV model, a Gaussian regularizing level set method (GRLSM) is used to reduce the computational cost. Experimental results on some synthetic and real images show that our model is efficiency. Moreover, comparisons with the ICV model show that our model is more robust to the location of the initial contour.
A Note on Empirical Likelihood Inference of Residual Life Regression

Mean residual life function, or life expectancy, is an important function to characterize distribution of residual life. The proportional mean residual life model by Oakes and Dasu (1990) is a regression tool to study the association between life expectancy and its associated covariates. Although semiparametric inference procedures have been proposed in the literature, the accuracy of such procedures may be low when the censoring proportion is relatively large. In this paper, the semiparametric inference procedures are studied with an empirical likelihood ratio method. An empirical likelihood confidence region is constructed for the regression parameters. The proposed method is further compared with the normal approximation based method through a simulation study.
Enterprise IT value engineering: A proposed method and case study

The paper proposes an IT value engineering method for private sector organization. With defined organization performances and/or strategic directions, the method gives guidance for finding optimal IT resources needed by the organization to reach the organization performances. The method was developed based on the engineering philosophies and concepts that already exist for computer/electronic engineering, software engineering and systems engineering. Literature review and synthesis comprising IT Value research and Resource-Based View (RBV) theory were conducted in method development. We apply the novel IT value engineering method in case study of plantation sector companies in Indonesia to test the proposed method. Discussion and managerial implication are provided.
Protection and Utilization of Privacy Information via Sensing

Our society has been getting more privacy-sensitive. Diverse information is given by users to information and communications technology (ICT) systems such as IC cards benefiting them. The information is stored as so-called big data, and there is concern over privacy violation. Visual information such as images and videos is also considered privacy-sensitive. The growing deployment of surveillance cameras and social network services has caused a privacy problem of information given from various sensors. To protect privacy of subjects presented in visual information, their face or figure is processed by means of pixelization or blurring. As image analysis technologies have made considerable progress, many attempts to automatically process flexible privacy protection have been made since 2000, and utilization of privacy information under some restrictions has been taken into account in recent years. This paper addresses the recent progress of privacy protection for visual information, showing our research projects: PriSurv, Digital Diorama (DD), and Mobile Privacy Protection (MPP). Furthermore, we discuss Harmonized Information Field (HIFI) for appropriate utilization of protected privacy information in a specific area. key words: privacy information, sensing, visual abstraction, privacy protection, information disclosure and utilization
Blockade of PSGL‐1 attenuates CD14+ monocytic cell recruitment in intestinal mucosa and ameliorates ileitis in SAMP1/Yit mice

The pathogenesis of Crohn’s disease (CD) is not known. However, monocytes and macrophages are thought to play important roles in the development of mucosal inflammation. Therefore, in this study, we examined the role of monocyte‐endothelial cell interactions in senescence‐accelerated mouse P1 (SAMP1)/Yit mice, a murine model of spontaneous ileitis. Fluorescence‐labeled CD14+ monocytic cells isolated from the spleen and mesenteric lymph nodes of AKR/J (control) mice were injected into the tail veins of recipient (AKR/J and SAMP1/Yit) mice, and migration in the postcapillary venules (PCV) of Peyer’s patches, submucosal venules, and villus microvessels of the terminal ileum was monitored by using an intravital microscope. Rolling and adhesion of CD14+ monocytic cells in the PCV of Peyer’s patches and microvessels of the terminal ileum were increased in SAMP1/Yit mice. An imunohistochemical study showed increased expression of P‐selectin glycoprotein‐1 (PSGL‐1), P‐selectin, and vascular cell adhesion molecule‐1 in the terminal ileum of SAMP1/Yit mice. Antibodies against these three adhesion molecules significantly inhibited adhesion of CD14+ monocytic cells to the PCV of Peyer’s patches and microvessels of the terminal ileum, treatment with an anti‐PSGL‐1 monoclonal antibody (mAb) showing the strongest suppressive effect. Anti‐PSGL‐1 mAb also attenuated T cell adhesion in microvessels of intestinal mucosa. In addition, periodical administration of an anti‐PSGL‐1 mAb for 7 weeks significantly ameliorated ileitis of SAMP1/Yit mice. The results suggest that PSGL‐1‐P‐selectin interaction plays an important role in monocyte‐endothelial cell interactions and the development of ileitis in a murine model of CD and that the blockade of this adhesion molecule may be a novel strategy for treating CD.
LSVT LOUD and LSVT BIG: Behavioral Treatment Programs for Speech and Body Movement in Parkinson Disease

Recent advances in neuroscience have suggested that exercise-based behavioral treatments may improve function and possibly slow progression of motor symptoms in individuals with Parkinson disease (PD). The LSVT (Lee Silverman Voice Treatment) Programs for individuals with PD have been developed and researched over the past 20 years beginning with a focus on the speech motor system (LSVT LOUD) and more recently have been extended to address limb motor systems (LSVT BIG). The unique aspects of the LSVT Programs include the combination of (a) an exclusive target on increasing amplitude (loudness in the speech motor system; bigger movements in the limb motor system), (b) a focus on sensory recalibration to help patients recognize that movements with increased amplitude are within normal limits, even if they feel “too loud” or “too big,” and (c) training self-cueing and attention to action to facilitate long-term maintenance of treatment outcomes. In addition, the intensive mode of delivery is consistent with principles that drive activity-dependent neuroplasticity and motor learning. The purpose of this paper is to provide an integrative discussion of the LSVT Programs including the rationale for their fundamentals, a summary of efficacy data, and a discussion of limitations and future directions for research.
A novel rapid approach for elevator equilibrium coefficient inspection based on no-load technology

Based on the energy conservation related to elevator's load, motor power, elevator's velocity and machinery efficiency, a mathematical model for solving the elevator equilibrium coefficient was proposed in detail. In order to realize the proposed method, through real-time sampled data including the operating power in no-load mode and speed of the elevator, test results of the equilibrium coefficient were collected and calculated automatically by central processing device to avoid being complex loaded operation. Besides, it would take just ten minutes or less to complete the whole operation due to convenient installation.
Probabilistic modeling of bowing gestures for gesture-based violin sound synthesis

We present a probabilistic approach to modeling violin bowing gestures, for the purpose of synthesizing violin sound from a musical score. The gesture models are based on Gaussian processes, a principled probabilistic framework. Models for bow velocity, bow-bridge distance and bow force during a stroke are learned from training data of recorded bowing motion. From the models of bow motion during a stroke, slightly novel bow motion can be synthesized, varying in a random manner along the main modes of variation learned from the data. Such synthesized bow strokes can be stitched together to form a continuous bowing motion, which can drive a physical violin model, producing naturalistic violin sound. Listening tests show that the sound produced from the synthetic bowing motion is perceived as very similar to sound produced from real bowing motion, recorded with motion capture. Even more importantly, the Gaussian process framework allows modeling short and long range temporal dependencies, as well as learning latent style parameters from the training data in an unsupervised manner.
Cubature Particle Filter with MCMC and Applications to Re-entry Ballistic Target Tracking

Monte Carlo process (CPF-MC) is proposed in order to alleviate the degeneracy and impoverishment problems existing in the particle filter, and the CPF-MC algorithm is improved from two aspects. On the one hand, CPF-MC uses the square root cubature Kalman filter (SRCKF) as proposal distribution that integrates the latest measurement into the particle filter and approximates the optimal posterior probability distribution more accurately. On the other hand, after resampling, a SRCKF based Markovian Chain Monte Carlo (MCMC) process is used to make the particles diversity and suppress the impoverish phenomenon. The CPF-MC algorithm is applied to re-entry ballistic target tracking; simulation results demonstrate that the CPF-MC achieves the better performance and is superior to generic particle filter with MCMC (GPF-MC), extended particle filter with MCMC (EPF-MC) and unscented particle filter with MCMC (UPF-MC), furthermore, the CPF-MC run faster.
Analysis of Supervised Machine Learning Algorithms for Heart Disease Prediction with Reduced Number of Attributes using Principal Component Analysis

research on causes of death due to heart disease has shown that it is the number one cause of death. If current trends are allowed to continue, 23.6 million people will die from heart disease in coming 2030. The healthcare industry gathers enormous amounts of heart disease data which unfortunately, are not "mined" to discover hidden information for effective decision making. In this paper, study of PCA has been done which finds the minimum number of attributes required to increase the accuracy of various supervised machine learning algorithms. The objective of this research is to analyze supervised machine learning algorithms to predict heart disease.
Enterobius vermicularis ancient DNA In Pre-Columbian Human Populations

In prehistoric populations the paleoparasitological findings show an Enterobius vennicularis homogeneous distribution among North American hunter-gatherers intensified with the advent of agriculture. The same occurred in the transition from nomad hunter-gatherers to sedentary farmers in South America, although E. vermicularis infection encompasses only the ancient Andean peoples. Since molecular techniques are sensitive in detecting ancient DNA (aDNA), in this work we have performed a molecular paleoparasitological study ofE. vermicularis. aDNA was recovered from North and South American coprolites (4110 BC-AD 900). Human (cox 2 and HVR) and pinworm (5S rRNA spacer) sequences were determined. The sequence analysis confirmedE. vermicularis identity and revealed polymorphisms in independent coprolite samples from Tulan, San Pedro de Atacama, Chile (1080950 BC). We were successful in detecting E. vermicularis aDNA even in coprolites without direct microscopic evidence of the eggs, improving the diagnosis of helminth infections in the past and further pinworm paleoepidemiological studies. KEYwORDs: Ancient DNA; Enterobius vermicularis; Coprolites; 5S rRNA spacer; Paleoparasitology. PAIABRAS CLAVE: ADN antiguo; Enterobius vermicularis; coprolitos; regi6n intergenica 5S rRNA; Paleoparasitologia.
Chromatin Insulators and Topological Domains: Adding New Dimensions to 3D Genome Architecture

The spatial organization of metazoan genomes has a direct influence on fundamental nuclear processes that include transcription, replication, and DNA repair. It is imperative to understand the mechanisms that shape the 3D organization of the eukaryotic genomes. Chromatin insulators have emerged as one of the central components of the genome organization tool-kit across species. Recent advancements in chromatin conformation capture technologies have provided important insights into the architectural role of insulators in genomic structuring. Insulators are involved in 3D genome organization at multiple spatial scales and are important for dynamic reorganization of chromatin structure during reprogramming and differentiation. In this review, we will discuss the classical view and our renewed understanding of insulators as global genome organizers. We will also discuss the plasticity of chromatin structure and its re-organization during pluripotency and differentiation and in situations of cellular stress.
Multiple Observations HMM Learning by Aggregating Ensemble Models

Hidden Markov Model (HMM) is a widespread statistical model used in cases where the system involves not fully observable data sequences such as temporal pattern recognition and signal processing. The most difficult problem in dealing with HMMs is the training procedure, or parameter learning, for which several approaches has been proposed. Nevertheless, these methods suffer from trapping in local maxima and still no tractable algorithm is present to overcome this problem. On the other hand, good performances of ensemble methods, where multiple models are employed to obtain the target model, lead to considering ensemble learning in the HMM training problem. Until now, just a few ensemble methods have been proposed for HMMs which lack strong theoretical background, or do not involve all the basic models to construct the final model. Hence in this paper a new ensemble learning method for HMMs is proposed which takes advantage of information theory measures, specifically Rényi entropy, and addresses the mentioned problems of previous methods. In agreement with this claim, the results show superiority of the proposed method over other compared methods for both synthetic and real-world datasets. Besides, the proposed ensemble method succeeded to meet the performance of other methods with much lower required training samples.
20 Interception and Rendezvous Between Autonomous Vehicles Yechiel

The problem of pursuit and evasion is a classic problem that has intrigued mathematicians for many generations. Suppose a target or evader is moving along a given curve in the plane. A pursuer or chaser is moving such that its line of sight is always pointing towards the target. The classic problem is to determine the trajectory of the pursuer such that it eventually captures the target. There is extensive literature on this problem, see for example the recent book by Nahin (Nahin, 2007). A special case of the pursuit problem is the case where the curve of the target is a circle. This is a classic problem which was first treated by Hathaway (Hathaway, 1921), see also the book by Davis (Davis, 1962). In the classic problems, the line of sight is always pointing towards the target. This method of pursuit is also known as 'pure pursuit' or 'dog pursuit' or 'courbe de chien' in French. Although there have been some modern works on extensions of the classic problem of pursuit, see for example (Marshall, 2005), here we completely abandon the 'pure pursuit' restriction and we treat the problem where the pursuer is required to capture or intercept the target in a given prescribed time or in minimum time. Also, in the classic problem, the velocities of the target and pursuer are assumed constant and there is no consideration of the physics of the motion, such as thrust forces, hydrodynamic or aerodynamic drag and other forces that might be acting on the target and pursuer. In an active-passive rendezvous problem between two vehicles, the passive or target vehicle moves passively along its trajectory. The active or chaser vehicle is controlled or guided such as to meet the passive vehicle at a later time, matching both the location and the velocity of the target vehicle. An interception problem is similar to the rendezvous problem, except that there is no need to match the final velocities of the two vehicles. On the other hand, in a cooperative rendezvous problem, the two vehicles are active and maneuver such as to meet at a later time, at the same location with the same velocity. The two vehicles start the motion from different initial locations and might have different initial velocities. An optimal control problem consists of finding the control histories, i.e., the controls as a function of time, and the state variables of the dynamical system such as to minimize a performance index. The differential equations of motion of the vehicles are treated as dynamical constraints. One possible approach to the solution of the rendezvous problem is to formulate it as an optimal control problem in which one is seeking the controls such as to O pe n A cc es s D at ab as e w w w . ite ch on lin e. co m