Miracle-dz/UniFAR-FTUs huggingface dataset:
The Revolution Might Not Be Televised (But It Will Be Lived Streamed)

Fiery nationwide protests in response to a recent string of dubious police killings of unarmed Black men have sparked a renewed social movement, drawing increased attention to fragile police–minority relations and allegations of racial bias in the criminal justice system. A wealth of research exists concerning African American youths’ accounts of poor treatment at the hands of police. To a lesser extent, prior scholarship reveals the importance of looking beyond citizens’ direct police experiences to family, peer, and mainstream media accounts of negative police encounters. Scholarly examinations of social media regarding how individuals make sense of their own and others’ experiences with, and attitudes toward police are limited, however. This is surprising given that social media has become especially important for youths and represents a new mechanism for the American public to learn about unsettling police behaviors. Moreover, social media represents a largely untapped, but potentially rich data source for researchers and policy makers. Special consideration is given to the role that the Black Lives Matter movement plays for obtaining improved understandings of police–minority relations and informing criminal justice.
A Text Detection and Orientation Restoration System for Mobile Devices

This paper proposes an automated system to detect text regions and correct the orientation of textlines in natural images on mobile devices. Text regions are first detected using an image operator called the Stroke Width Transform. Textlines (text blocks) are then extracted from text regions based on a modified minimum spanning tree algorithm. Finally, the orientations of textlines are corrected according to the way users hold the device. The system provides the users with an interactive interface to select the text blocks which catch their attention. Moreover, the interactive interface allows the users to correct the orientation of the selected text blocks if the results of the automatic correction are wrong. With such a design, wrongly detected text regions or an incorrect orientation of textlines would not confuse the users. The system is implemented on the Android platform and the experimental results demonstrate the feasibility and validity of the proposed system.
Recursive likelihood evaluation and fast search algorithm for polynomial segment model with application to speech recognition

Polynomial segment models (PSMs), which are generalization of the hidden Markov models (HMMs), have opened an alternative research direction for speech recognition. However, they have been limited by their computational complexity. Traditionally, any change in PSM segment boundary requires likelihood recomputation of all the frames within the segment. This makes the PSM's segment likelihood evaluation an order of magnitude more expensive than the HMM's. Furthermore, because recognition using segment models needs to search over all possible segment boundaries, the PSM recognition is computationally unfeasible beyond N-best rescoring. By exploiting the properties of the time normalization in PSM, and by decomposing the PSM segment likelihood into a simple function of "sufficient statistics", in this paper, we show that segment likelihood can be evaluated efficiently in an order of computational complexity similar to HMM. In addition, by reformulating the PSM recognition as a search for the optimal path through a graph, this paper introduces a fast PSM search algorithm that intelligently prunes the number of hypothesized segment boundaries, such that PSM recognition can be performed in an order of complexity similar to HMM. We demonstrate the effectiveness of the proposed algorithms with experiments using a PSM-based recognition system on two different recognition tasks: TIDIGIT digit recognition and the Wall Street Journal dictation task. In both tasks, PSM recognition is feasible and out-performed traditional HMM by more than 14%
Distributed Online En-Route Caching

Content caching at intermediate nodes is an effective way to optimize the operations of Computer networks, so that future requests can be served without going back to the origin of the content. Several caching techniques have been proposed in literature, including techniques that require major changes to the Internet architecture. In this work, we present a low complexity, distributed, and online caching algorithm based on content popularity. Our algorithm performs en-route caching using a simple cost-reward comparison. Therefore, it can be integrated with the current TCP/IP model. We use the concept of competitive ratio to measure the performance of any online caching algorithm, in terms of traffic savings, with respect to the performance of the optimal offline algorithm that has a complete knowledge of the future. We show that under our settings, no online algorithm can achieve a better competitive ratio than Ω(logn), where n is the number of nodes in the network. Furthermore, we show that under realistic scenarios, our algorithm has an asymptotically optimal competitive ratio in terms of the number of nodes in the network. We also study several extensions to the basic algorithm and show their effectiveness through extensive simulations.
Personality Systems, Spirituality, and Existential Well-Being: A Person-Centered Perspective

Recent research on the salutogenic benefits of spirituality and religiosity has yielded inconsistent findings. It is suggested that such discrepancies reflect individual differences in personality, but this cannot be investigated with variable-driven approaches. The present study measured the influence of personality on the relationship between spirituality and existential well-being (EWB) from the perspective of Personality Systems Interaction theory—an approach focused on functional relationships between cognitive and affective systems, using Latent Profile Analysis. Three major results emerged: First, we identified discrete Analytical, Intuitive, and Flexible personality profiles resembling closely the prototypes reported elsewhere. Second, while preferences for intuitive cognitive processing resulted in high scores on all dimensions of spirituality and EWB, the reverse was true for individuals prone to analytical information processing, replicating previous research. Third, EWB operates independently from other spirituality dimensions, and relates differentially to distinct personality profiles.
Face and expression recognition based on bag of words method considering holistic and local image features

This paper proposes a new framework for extracting facial features based on the bag of words method, and applies it to face and facial expression recognition. Recently, the bag of words method has been successfully used in object recognition. However, for recognition problems of facial images, the orderless collection of local patches in bag of words method cannot provide strongly distinctive information since the object category (face image) is the same. In our work, a new framework based on bag of words is presented to extract discriminative local facial features while maintaining holistic spatial information at the same time. The new method is applied to both face and facial expression recognition. Experimental results show that only using one neutral expression frame per person for training, our method can obtain the best face recognition performance ever on face images of AR database with extreme expressions, variant illuminations, and partial occlusions. For facial expression recognition, the average rate on the Cohn-Kanade database is 96.33%, which also outperforms the state of the arts.
Costs of Inflation as the Area Under the Money Demand Curve

Most people recognize that inflation is something to be avoided, but the popular public perception of inflation’s harmful effects can be rather vague. In responses to survey questions about inflation, for example, most people express concerns about prices rising (defining inflation itself) or that it somehow erodes standards of living.1 When economists discuss the costs of inflation, however, they have more specific concerns in mind. One general class of inflationary consequences is sometimes referred to as the “shoe-leather” costs of inflation: In an effort to minimize the effect that inflation has on eroding the purchasing power of money, people have to spend more time and effort protecting the value of their nominal assets—wearing out their shoes on the way back and forth to the bank. Of course, this quaint notion represents a much broader and more serious problem than simply the cost of wearing out ones shoes. To protect assets against inflation, societal resources are channeled away from productive activities and toward inflationhedging activities. In countries that have experienced hyperinflation, these resource misallocations are readily apparent; but they are also present for less extreme cases of inflation. This article discusses the nature of shoe-leather costs in the context of a theoretical model economy. The shoe-leather costs themselves are represented by a “shopping-time” feature embedded in the model: It is assumed that individuals must spend time conducting transactions and that carrying money reduces the time required. The incentive to economize on money balances in the face of high inflation then implies that individuals incur a time-cost that rises in response to an increase in the inflation rate. Using the U.S. experience of the postWorld War II (WWII) era to calibrate the model, I show that the shopping-time model implies shoe-leather costs that are broadly consistent with estimates derived by other researchers using a variety of approaches. In the previous literature, these costs have been presented as a comparison between two specific long-run inflation rates. In this article, I use the shopping-time model to take this analysis a step further, demonstrating how the transition from one inflation rate to another might be expected to proceed, and evaluating the importance of uncertainty about the commitment of the monetary authority to keep inflation in check. This analysis suggests that the credibility of the monetary authority is an important factor in evaluating the welfare gains that accrue from policies to reduce inflation.
The Planetary Mass Companion 2MASS 1207–3932B: Temperature, Mass, and Evidence for an Edge-on Disk

We present J-band imaging and H+K-band low-resolution spectroscopy of 2MASS 1207-3932AB, obtained with VLT NACO. For the putative planetary mass secondary, we find J = 20.0 ± 0.2 mag. The HK spectra of both components imply low gravity and a dusty atmosphere for the secondary. Comparisons to synthetic spectra yield Teff,A ≈ 2550 ± 150 K and Teff,B ≈ 1600 ± 100 K, consistent with their late-M and mid- to late-L types. For these Teff and an age of 5-10 Myr, evolutionary models imply MA ≈ 24 ± 6 MJup and MB ≈ 8 ± 2 MJup. Independent comparisons of these models to the observed colors, spanning ~I to L', also yield the same masses and temperatures. Our primary mass agrees with other recent analyses; however, our secondary mass, while still in the planetary regime, is 2-3 times larger than claimed previously. This discrepancy can be traced to the luminosities: while the absolute photometry and Mbol of the primary agree with theoretical predictions, the secondary is ~2.5 ± 0.5 mag fainter than expected in all bands from I to L' and in Mbol. This accounts for the much lower secondary mass (and temperature) derived earlier. We argue that this effect is highly unlikely to result from a variety of model-related problems and is instead real. This conclusion is bolstered by the absence of any luminosity problems in either the primary or AB Pic B, which we also analyze. We therefore suggest gray extinction in 2M1207B, due to occlusion by an edge-on circumsecondary disk. This is consistent with the observed properties of edge-on disks around T Tauri stars and with the known presence of a high-inclination evolved disk around the primary. Finally, the system's implied mass ratio of ~0.3 suggests a binary-like formation scenario.
Distinguishing Topic from Genre

This paper contributes to a facet from the area of Web Information Retrieval that has recently received much attention: The satisfaction of a user's personal information need with respect to text type, presentation type, or information quality. We imply that such properties can be quantied for all kinds of Web documents, and we subsume them under the term iWeb genrei or igenrei. Recent surveys show that there is, to a certain degree, a common understanding of Web genre. However, the strictness by which genre and non-genre aspects of a document are experienced is an individual matter. To get a better understanding of the challenges of Web genre identication and its possible limits we investigate in this paper a very interesting question, which has not been posed by now: Given a categorization C of documents (or bookmarks, links, document identier s), can we provide a reliable assessment whether C is governed by topic or by genre considerations? We present instruments to answer this question as well as to make a distinct statement about the homogeneity of a categorization.
Tree genera classification using airborne LiDAR data by ensemble methods

We propose an ensemble classification method for classifying tree genus by using LiDAR (Light Detection and Ranging) data. We have developed a set of descriptors (features) related to the geometric information given by the point cloud. The second set of features is derived from a more conventional method and is related to the vertical point distribution of the point cloud. We built two classifiers separately (geometric classifier and vertical profile classifier) using the two sets of features and then combine the classifiers for improving overall classification accuracy. Our study area is located north of Thessalon, Ontario, Canada and we are classify trees into three genera (pine, poplar and maple) within our study sites. Result show that the average classification accuracy for the geometric classifier is 88.0% and 88.8% for vertical profile classifier. When the classifiers are combined, the overall accuracy improved to 91.2%.
Antibody recognition of histone post-translational modifications: emerging issues and future prospects.

" …it is fair to say that much of the advancement in our understanding of chromatin modifications and chromatin structure would not have been possible without the development of post-translational modification-specific antibodies. " Antibody recognition of histone post-translational modifications: emerging issues and future prospects Last year marked the 10-year anniversary of the 'histone code' hypothesis, which formally proposed that combinatorial post-translational modifications (PTMs) on histone proteins govern the diverse activities associated with eukary-otic DNA [1,2]. In the intervening decade, significant advancements have been made in our understanding of chromatin biology. For example, more than 60 sites of modification on histones have been identified (which include acetylation, phosphorylation, ubiquitination, methylation and others), as have a variety of specialized effector domains that recognize these histone PTMs [3,4]. The collective results of many studies show that histone PTMs contribute to a wide range of biological processes, including gene transcription, DNA replication and DNA repair. These advances, however, would not have been possible without the creation of PTM-specific histone antibodies [5,6]. Histone antibodies have become the predominant tool for chromatin research, and are ubiquitously used to understand how histone PTMs regulate chromatin structure and function. While histone antibodies are integral tools for chromatin research, several issues regarding their future utility have emerged. More than 1000 different antibodies raised against histone PTMs are commercially available. The process of choosing the right antibody for a particular application can be both daunting and expensive. Often, minimal information is available regarding the substrate against which these reagents were developed, and the long-term reliability of polyclonal antibodies is most often limited by the nonrenewability of particularly effective lots. To further complicate matters, recent findings have highlighted the influence of combinatorial PTMs on the recognition and binding of these antibodies [7–9]. How then do we begin to assess antibody specificity, and will future technologies be developed to aid in the detection and study of histone PTMs? Below, we summarize some of the recent lessons learned and future technological advances that will likely improve antibody-mediated histone PTM studies. Researchers have long known that histone antibodies are not always specific for their intended PTM targets, and often recognize 'off-target' proteins and PTMs. Until recently, the primary approaches used to characterize the specificity of histone antibodies were ELISAs, western blot analyses, chromatin immunoprecip-itation (ChIP) and immunofluorescence-based assays. Typically, PTM-specific antibodies are first screened in ELISAs with the PTM-modified immunogenic peptide and further validated …
Comparing Intraoral Radiography and Computed Tomography for Detecting Radiographic Signs of Periodontitis and Endodontic Disease in Dogs: An Agreement Study

Objective To determine whether computed tomography (CT) and intraoral radiography are interchangeable for detecting signs of periodontitis and endodontic disease in dogs. Materials and methods An agreement study was performed using 40 dogs that previously underwent intraoral radiography and CT during the same anesthetic episode. Images of each tooth were examined by two blinded observers for signs of periodontitis and/or endodontic disease. Agreement between imaging modalities and between observers was assessed using the Kappa statistic. Results Agreement between modalities for detecting periodontitis in the maxillae ranged from poor to very good (κ 0.07–1.00) with 16/20 (80%) of the teeth having a score of moderate or better (κ ≥ 0.41). Agreement between modalities for detecting signs consistent with periodontitis in the mandibles ranged from poor to very good (κ 0.01–1.00) with 10/22 (45%) of the teeth having a score of good or better (κ ≥ 0.61); 50% of the disagreement was present in the incisors. Agreement between modalities for detecting signs consistent with endodontic disease in the whole mouth ranged from fair to very good (κ 0.21–1.00) with 30/42 (71%) of the teeth having a score of moderate or better (κ ≥ 0.41). Agreement between observers evaluating intraoral radiology ranged from poor to very good (κ 0.05–1) for detecting signs consistent with periodontitis and from fair to very good (κ 0.36–1) for detecting signs consistent with endodontic disease, in the whole mouth. Agreement between observers evaluating CT ranged from fair to very good (κ 0.35–1) for detecting signs consistent with periodontitis and from fair to very good (κ 0.36–1) for detecting signs consistent with endodontic disease, in the whole mouth. Conclusion Performing both CT and intraoral radiography may be unnecessary to detect signs consistent with periodontitis and endodontic disease in dogs based on the amount of agreement between modalities and observers when CT images are acquired and reconstructed in 0.5 or 1 mm slice thickness, except for diagnosing periodontitis in the mandibular incisors.
Uncovering the genomic basis of local adaptation by coherent synthesis of associations with phenotypes and home environments

20 Running title: Genomic basis of G×E and local adaptation. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not. Abstract A substantial portion of intraspecific diversity is associated with local adaptation to environment, which is driven by genotype-by-environment interactions (G×E) for fitness. 25 Local adaptation is often studied via 1) multiple common garden experiments comparing performance of genotypes in different environments and 2) sequencing genotypes from multiple locations and characterizing geographic patterns in allele frequency. Both approaches aim to identify the same pattern (local adaptation), yet the complementary information from each approach has not been coherently integrated into a modeling 30 framework. Here, we develop a genome-wide association model of genotype interactions with continuous environmental gradients (G×E). We employ an imputation approach to synthesize evidence from common garden and genome-environment associations, allowing us to identify loci exhibiting climatic clines where alleles are associated with higher fitness in home environments. We apply this model to published data on natural 35 Arabidopsis thaliana accessions. Our approach reveals candidate genes for local adaptation based on known involvement in environmental stress response. Most outlier SNPs exhibit home allele advantage and fitness tradeoffs along climate gradients, suggesting selective gradients may maintain allelic clines. SNPs exhibiting G×E associations with fitness are enriched in genic regions, putative partial selective sweeps, 40 and G×E associations with an important adaptive phenotype (flowering time). We discuss extensions for situations where only adaptive phenotypes other than fitness are available. Many types of data may point toward the loci underlying G×E and local adaptation; coherent models of these diverse data provide a principled basis for synthesis. 45. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not .
Blind dereverberation using short‐time cepstrum frame subtraction

A blind dereverberation method that can be used to separate reverberant speech into an impulse response and a dry speech contribution is presented by the authors. This method is based on the assumption that the contribution of an impulse response to reverberant speech varies slowly compared to that of the dry speech. Processing the reverberant signal for short‐time frames and using the special properties of the cepstrum domain, allows a recursive scheme to remove the equal impulse response contributions. Although short‐time frames are processed, the effects of an amply longer impulse response can be separated from the dry speech. The assumption of a constant impulse response in only two frames and the iterative processing make the method inherently robust to changes in the impulse response. An ambiguous linear phase addition when calculating the inverse cepstrum constitutes one of the problems to limit the dereverberation performance.
A framework of autonomous knowledge transfer for robot navigation task

This paper proposes a framework of knowledge transfer used in the robot navigation problem, in order to speedup the learning process when the robot meets new or more complex task. Take the graph of source navigation maps as the template library, Principal Component Analysis method is adopted to match the target graph with source template. Then, the robot recognizes the similar source task. The value-function of the selected source task, which correlates the cumulative rewards with the sensory information corresponding to the generalized distance information to each beacon, is transferred to the target task. With this approach, the robot can choose the most related knowledge from the source tasks and transfer the generalized knowledge to the target navigation task automatically without handed code mapping between tasks. Experimental results demonstrate that the presented transfer method can yield a remarkable speedup for learning process in the robot navigation task.