Miracle-dz/UniFAR-FTUs huggingface dataset:
Substance use among municipal solid waste workers in Mumbai: a cross-sectional comparative study

ABSTRACT Background: Smoking, alcohol consumption and chewing of tobacco affect the health of people as well as the socioeconomic structure of families, communities and eventually the nation. This study assesses the prevalence of substance use among municipal solid waste workers of Mumbai. Methods: To conduct the study, information was collected from 540 municipal workers of Mumbai with regard to substance use as well as their socioeconomic and occupational characteristics. To draw inferential statistics, the data was processed through multivariate logistic regression (MLR) and ordered logistics regression (OLR). Results: Multivariate regression suggests that waste loaders and street sweepers are significantly more likely to smoke, consume alcohol and chew tobacco with reference to the comparison group. Workers with more working years and morbid health status are significantly more likely to get involved with substance use. The results of OLR reveal that municipal waste workers are significantly more likely to consume alcohol on a daily basis (β = 0.220, p < 0.001). Conclusion: Socioeconomic characteristics significantly contribute in increasing the risk of substance use among workers. Workers defend their habit of substance use by considering it as a mechanism for coping with the filthy nature of their occupation. Evidence-based preventive measures need to be developed in order to reduce substance use among municipal solid waste workers.
Kostas Daniilidis: Research and Teaching Statement

My motivation has always been to understand the intrinsic difficulties of motion and space perception by machines in order to be able to create provably working systems. In the late 90’s, research in the recovery of 3D-motion and structure from images had reached a level allowing already successful applications, in particularly in well constrained domains. Advances in camera technology had given a new impetus towards the solution of hard problems like navigation on complex terrains or the rendering of dynamic scenes from novel viewpoints. This availability of infrastructure motivated me to study the space perception problem in novel sensor setups: omnidirectional cameras and camera clusters. The common underlying principle of these setups is that they are both samplings of the set of all possible viewing rays in space – called also the plenoptic function. I will describe here only research results conducted during the last five years at Penn:
Who's Allowed to Ride the Short Bus? Un-Defining Disability

This article uses personal testimony as a vehicle for deconstructing the theory and literature of disability studies. The definition of disability is traced from the term’s origins to its present-day representations in popular culture, and I end with a look toward the future of the subject in academic settings and in society at large. The fictional character of Artie Abrams is considered alongside the real-life figure of Oscar Pistorius in an attempt to analyze the dangers and motives behind stereotypes surrounding the “disabled character. ” Throughout the article, anecdotal excerpts are included to emphasize the importance of the personal perspective in better understanding the disabled experience. The ultimate goal is to turn the disabled figure from object into subject by un-defining what it means to be disabled. * * * * * Think back to the day that you received your driver’s license. Maybe you felt an unsettling sense of responsibility, but I would wager that most of you were thrilled. It took a bit of work: a written test that you had to study for and a road test you had to practice for and hours at your after-school job, trudged through in hopes of saving up enough to get a used clunker. Otherwise, it was a relatively painless experience. There were no identity crises or self-assessments or any of the strangeness you’re about to hear. I started working toward my license at the usual age, but a few years passed before I received it. I scored perfectly on my written test, so that wasn’t the issue. The problem arose when I wanted to take driving lessons. You see, not many Driver’s Education establishments own vehicles that are modified for wheelchair users. What’s more, the places that do have the equipment don’t trust fledgling permit holders with their expensive automobiles. So I had to be trained for training. But first, I had to be approved to be trained for training. And that’s when I was sent to the Columbia office of the South Carolina Vocational
An Analogical Parser for Restricted Domains

This note describes the current development of an approach to parsing designed to overcome some of the problems of existing parsers, particularly with respect to their utility as language models. The parser combines lexical and grammatical constraints into a uniform grammatical representation, is readily trainable (since the parser output is indistinguishable from the grammar input), and uses analogy to guess about the likelihood of constructions outside the grammar.
Bits-back coding software guideBrendan

| In this document, I rst review the theory behind bits-back coding (aka. free energy coding) (Frey and Hinton 1996) and then describe the interface to C-language software that can be used for bits-back coding. This method is a new approach to the problem of optimal compression when a source code produces multiple codewords for a given symbol. It may seem that the most sensible codeword to use in this case is the shortest one. However, in the proposed bits-back approach, random codeword selection yields an eeective codeword length that can be less than the shortest codeword length. If the random choices are Boltzmann distributed, the eeective length is optimal for the given source code. The software which I describe in this guide is easy to use and the source code is only a few pages long. I illustrate the bits-back coding software on a simple quantized Gaussian mixture problem.
Maternal Responses to Children’s Exposure to Violent/Tragic News Media in a Sample of Multiply-Traumatized, African-American, Low-Income Youth

Given children’s ready access to media, particularly to sensationalized media reports of violent/tragic news (Pew Research Center, 2013), it is important to understand whether and how exposure to this news affects children’s psychological functioning. Studies in the general population have found that media exposure to violence correlates positively with anxiety and posttraumatic stress (PTS) symptoms in children (Becker-Blease, Finkelhor, & Turner, 2008). However, little is known about the impact such exposure may have on children who are vulnerable to myriad health and mental health problems as a consequence of multiple traumas (Fowler, Tompsett, Braceiszewski, Jaques-Tiura, & Baltes, 2009). Moreover, given evidence
Object Tracking for Calibration of Distributed Sensors in Intelligent Space

In recent years, the research field on smart environments, which are spaces with multiple embedded and networked sensors and actuators, has been expanding (Cook & Das, 2004). The main purpose for the introduction of smart environments is to support humans in both physical and informative ways (Johanson et al., 2002), (Mynatt et al., 2004), (Mizoguchi et al., 1999). In smart environments, the distributed sensor nodes observe the spaces, extract useful information from the obtained data and the actuators including mobile robots provide various services to users. Moreover, robots in the space can get necessary information from the smart environment and operate without restrictions due to the capability of on-board sensors and computers. In fact, mobile robot control is easier in smart environments since the global positions can be directly measured by using distributed sensors and Simultaneous Localization And Mapping (SLAM) problem (Durrant-Whyte & Bailey, 2006), where the robot tries to simultaneously estimate its own location and build a map of the environment, can be completely avoided (Lee & Hashimoto, 2003). However, one of the major problems in developing smart environments is calibration of the sensors. Calibration is needed for proper calculation from the local (sensor's) coordinate system to the world (smart environment's) coordinate system and it is usually done by using calibration objects that are objects with known positions, shapes and so on. For example, researches on camera calibration based on geometrical features including 3D points (Tsai, R. Y., 1987), 2D points (Sturm & Maybank, 1999), (Zhang, 2000), lines (Zhang, 2004), circles (Wu et al., 2004), and spheres (Agrawal & Davis, 2003) are being pursued actively. Several researchers extended such a single camera calibration algorithm to a multiple-camera calibration algorithm. An extension of a planar point pattern based calibration algorithm to the multi-camera systems with an arbitrary number of cameras is presented in (Ueshiba & Tomita, 2003). The algorithm is based on factorization of homography matrices between the model and image planes, which is expressed as a composition of a camera projection matrix and a plane parameter matrix. If a calibration object is put in three or more places, the relative positions and orientations between cameras as well as the intrinsic camera parameters are determined. Another work also utilized a known 2D calibration object for stereo camera calibration (Malm & Heyden, 2001). The technique uses both stereo camera constraints and single camera constraints, and therefore noise-robust calibration is realized. In the case of smart environments, it takes a great deal of time and efforts to calibrate the sensors since multiple sensors are distributed in the space. Although the researches
Psychological Security Traps

DURING MY CAREER OF ATTACKING SOFTWARE AND THE FACILITIES THEY POWER, many colleagues have remarked that I have a somewhat nonstandard approach. I tended to be surprised to hear this, as the approach seemed logical and straightforward to me. In contrast, I felt that academic approaches were too abstract to realize wide success in real-world applications. These more conventional disciplines were taking an almost completely random tack with no focus or, on the opposite end of the spectrum, spending hundreds of hours reverse-engineering and tracing applications to (hopefully) discover their vulnerabilities before they were exploited out in the field.
Precoloring extension for K4‐minor‐free graphs

Let G=(V, E) be a graph where every vertex v∈V is assigned a list of available colors L(v). We say that G is list colorable for a given list assignment if we can color every vertex using its list such that adjacent vertices get different colors. If L(v)={1, …, k} for all v∈V then a corresponding list coloring is nothing other than an ordinary k‐coloring of G. Assume that W⊆V is a subset of V such that G[W] is bipartite and each component of G[W] is precolored with two colors taken from a set of four. The minimum distance between the components of G[W] is denoted by d(W). We will show that if G is K4‐minor‐free and d(W)≥7, then such a precoloring of W can be extended to a 4‐coloring of all of V. This result clarifies a question posed in 10. Moreover, we will show that such a precoloring is extendable to a list coloring of G for outerplanar graphs, provided that |L(v)|=4 for all v∈V\W and d(W)≥7. In both cases the bound for d(W) is best possible. © 2009 Wiley Periodicals, Inc. J Graph Theory 60: 284‐294, 2009
A scalable goal-oriented approach to software variability recovery

Software reuse approaches, such as software product lines, can help to achieve considerable effort and cost savings in product development for sets of software systems with a significant overlap in functionality. However, in the practice many organizations at first develop a number of similar software products without explicitly planning for strategic reuse. In consequence, subsequent attempts to introduce reuse require a significant restructuring of the existing products. The restructuring is difficult because the precise information about the distribution of commonality and variability in the source code of the variants is often not available. The ongoing PhD thesis presented in this paper contributes to easing the task of extractive software reuse adoption: it proposes a reverse engineering approach for extracting the variability information from the source code of similar software products and outlines a method that guides the organization towards optimal use of this information in the process of planning and introducing software reuse.
Leveraging Social Foci for Information Seeking in Social Media

The rise of social media provides a great opportunity for people to reach out to their social connections to satisfy their information needs. However, generic social media platforms are not explicitly designed to assist information seeking of users. In this paper, we propose a novel framework to identify the social connections of a user able to satisfy his information needs. The information need of a social media user is subjective and personal, and we investigate the utility of his social context to identify people able to satisfy it. We present questions users post on Twitter as instances of information seeking activities in social media. We infer soft community memberships of the asker and his social connections by integrating network and content information. Drawing concepts from the social foci theory, we identify answerers whose community memberships in the question domain overlap with that of the asker. Our experiments demonstrate that the framework is effective in identifying answerers to social media questions.
Quantitative Measures of Presence in Virtual Environments: The Roles of Attention and Spatial Comprehension

Given that the best measures of presence currently available are subjective self-assessments, it is desirable to attempt to develop reliable, repeatable, quantitative measures. We present the results of two experiments intended to separate presence into measurable subcomponents: attention and spatial comprehension. The first experiment was a conventional dual-task study where we measured attentional demands of competing.virtual and real world experiences. The results suggest that attention may be a reasonable quantitative measure of presence. The study also showed that the use of sound increased the level of engagement experienced by participants. The second study attempted to correlate spatial knowledge acquisition with presence. The only component of spatial knowledge acquisition that was positively affected was landmark knowledge that improved with the addition of semantic verbal information. The data does not generally support a relationship between spatial comprehension and presence, but, again, it was found that the use of sound increased participants' sense of engagement in the virtual world. There are certainly other candidate subcomponents of presence, but we began our investigation here. An expanded investigation toward the development of an aggregate quantitative measure of presence is suggested.
Image matching based on SIFT features and kd-tree

This paper uses the specific SIFT (Scale Invariant Feature Transform) feature and a fast kd-tree matching strategy combined with invariant feature to solve single face recognition problems. It transforms face image data into scale-invariant coordinates relative to local features. The similarity was computed using Euclidean distance and kd-tree search. Experiments show that the features are invariant to image scaling, translation, rotation, and change in viewpoint.
FieldWise: a mobile knowledge management architecture

The paper presents results of a research project that has aimed at developing a knowledge management architecture for mobile work domains. The architecture developed, called FieldWise, was based on fieldwork in two organisations and feedback from users of prototype systems. This paper describes the empirically grounded requirements of FieldWise, how these have been realised in the architecture, and how the architecture has been implemented in the news journalism domain. FieldWise adds to the field of CSCW by offering an empirically grounded architecture with a set of novel features that have not been previously reported in the literature.
Toward Imitating Object Manipulation Tasks Using Sequences of Movement Dependency Graphs

This extended abstract describes a new representation that can be used for recognizing and imitating object manipulation tasks, which is based on detecting the co-movement patterns between visual features. The representation consists of a sequence of graphs that evolve over time as the activity progresses. The nodes in these graphs correspond to the features that are tracked by the robot. The edges correspond to the movement dependencies between pairs of tracked visual features. The representation was tested on two manipulation tasks in which a human attempted to insert small blocks inside container and non-container objects. The results show that the robot was able to use the graph-based representation to distinguish between these two tasks. Furthermore, the robot was able to relate its own actions with these objects to the human actions through the similarities in the resulting graph sequences.
Robust Tests of the Lower Partial Moment Asset Pricing Model in Emerging Markets

This paper tests and compares the CAPM of Black (1972) and the Mean Lower Partial Moment (MLPM) Capital Asset Pricing Model of Bawa and Lindenberg (1977) and Harlow and Rao (1989) in the context of emerging markets. It is well known that returns in emerging markets are non-normal and have greater predictability than in the developed markets. Considering these stylized facts the paper extends the Harlow-Rao Likelihood Ratio test of a Black (1972) type version of the MLPM model and develops a Wald test that allow for non-normality of the returns. The paper also formulates a GMM test that is valid under the conditions of heteroskedasticity and serial dependence. For the test of the CAPM hypothesis against the MLPM alternative the paper remedies an econometric problem of testing in presence of a nuisance parameter. In the empirical application on an emerging market data it is shown that the conclusion on the validity of the asset pricing model are reversed when the correct p-values obtained through the bootstrap test are employed. We demonstrate that the empirical results appear to support both the Black version of the CAPM and the MLPM model when performed against unspecified alternative but the CAPM is supported when an MLPM alternative is specified.
Design and performance analysis of network code division multiplexing for wireless sensor networks

In this paper, we investigate the performance of a wireless sensor network, in which multiple groups of source nodes communicate with their respective destination nodes with the help of a common relay network. A network code division multiplexing (NCDM) scheme is proposed to remove the inter-session interference among multiple transmission sessions at each destination. We focus on analyzing the soft processing algorithm of the NCDM scheme. Based on the analysis results, a new code design criteria for the construction of the generator matrix is proposed. Simulation results show that by following the proposed code design criteria, the bit error ratio (BER) performance gap between the scheme we studied and the serial session scheme can be managed effectively. In serial session scheme, source nodes in a number of groups communicate with their respective destinations in a time division manner.
Daily Evaporative Fraction Parameterization Scheme Driven by Day-Night Differences in Surface Parameters: Improvement and Validation

In a previous study, a daily evaporative fraction (EF) parameterization scheme was derived based on day–night differences in surface temperature, air temperature, and net radiation. Considering the advantage that incoming solar radiation can be readily retrieved from remotely sensed data in comparison with surface net radiation, this study simplified the daily EF parameterization scheme using incoming solar radiation as an input. Daily EF estimates from the simplified scheme were nearly equivalent to the results from the original scheme. In situ measurements from six Ameriflux sites with different land covers were used to validate the new simplified EF parameterization scheme. Results showed that daily EF estimates for clear skies were consistent with the in situ EF corrected by the residual energy method, showing a coefficient of determination of 0.586 and a root mean square error of 0.152. Similar results were also obtained for partly clear sky conditions. The non-closure of the measured energy and heat fluxes and the uncertainty in determining fractional vegetation cover were likely to cause discrepancies in estimated daily EF and measured counterparts. The daily EF estimates of different land covers indicate that the constant coefficients in the simplified EF parameterization scheme are not strongly site-specific.
A Biphasic and Brain-Region Selective Down-Regulation of Cyclic Adenosine Monophosphate Concentrations Supports Object Recognition in the Rat

Background We aimed to further understand the relationship between cAMP concentration and mnesic performance. Methods and Findings Rats were injected with milrinone (PDE3 inhibitor, 0.3 mg/kg, i.p.), rolipram (PDE4 inhibitor, 0.3 mg/kg, i.p.) and/or the selective 5-HT4R agonist RS 67333 (1 mg/kg, i.p.) before testing in the object recognition paradigm. Cyclic AMP concentrations were measured in brain structures linked to episodic-like memory (i.e. hippocampus, prefrontal and perirhinal cortices) before or after either the sample or the testing phase. Except in the hippocampus of rolipram treated-rats, all treatment increased cAMP levels in each brain sub-region studied before the sample phase. After the sample phase, cAMP levels were significantly increased in hippocampus (1.8 fold), prefrontal (1.3 fold) and perirhinal (1.3 fold) cortices from controls rat while decreased in prefrontal cortex (∼0.83 to 0.62 fold) from drug-treated rats (except for milrinone+RS 67333 treatment). After the testing phase, cAMP concentrations were still increased in both the hippocampus (2.76 fold) and the perirhinal cortex (2.1 fold) from controls animals. Minor increase were reported in hippocampus and perirhinal cortex from both rolipram (respectively, 1.44 fold and 1.70 fold) and milrinone (respectively 1.46 fold and 1.56 fold)-treated rat. Following the paradigm, cAMP levels were significantly lower in the hippocampus, prefrontal and perirhinal cortices from drug-treated rat when compared to controls animals, however, only drug-treated rats spent longer time exploring the novel object during the testing phase (inter-phase interval of 4 h). Conclusions Our results strongly suggest that a “pre-sample” early increase in cAMP levels followed by a specific lowering of cAMP concentrations in each brain sub-region linked to the object recognition paradigm support learning efficacy after a middle-term delay.