Miracle-dz/UniFAR-FTUs huggingface dataset:
Concentration, Spatial Clustering and the Size of Plants: Disentangling the Sources of Co-Location Externalities

Following the model-based approach of Ellison and Glaeser (1997), we develop a framework to test for the link between concentration, spatial clustering and the size of plants. Concentration is an a-spatial concept of variability that can be measured with the standard locational Gini or the more sophisticated Ellison and Glaeser index. By contrast, spatial clustering is directly concerned with distances. Therefore we also use a two-dimensional measure (the Moran index) to identify some specific distance-based patterns. We argue that, in a world where the size of establishments is independent of both concentration and spatial agglomeration, as the standard Dixit-Stiglitz (1977)-Krugman (1980) framework, all the variability in these measures should be accounted for by the variation in the number of plants. Using the Italian 1996 census year data on manufacturing industries, we therefore compare the values and significance of both the EG and Moran indexes computed on an employment and number of plants basis. Our results indicate that, for the majority of Italian manufacturing industries, big plants are much more concentrated than small ones, with size and concentration simultaneously influencing each other. On the other hand, small units are shown to be more spatially correlated, suggesting that different externalities may drive (or may be driven by) concentration and agglomeration patterns according to a size-related basis. These results therefore cast some doubt on the relevance of standard monopolistic frameworks to structurally account for the role of the so-called "pecuniary" externalities compared to more "localized" ones, such as Marshallian, Jacobian or factor endowments based externalities.
Learning to Recognize Animals by Watching Documentaries: Using Subtitles as Weak Supervision

We investigate animal recognition models learned from wildlife video documentaries by using the weak supervision of the textual subtitles. This is a particularly challenging setting, since i) the animals occur in their natural habitat and are often largely occluded and ii) subtitles are to a large degree complementary to the visual content, providing a very weak supervisory signal. This is in contrast to most work on integrated vision and language in the literature, where textual descriptions are tightly linked to the image content, and often generated in a curated fashion for the task at hand. In particular, we investigate different image representations and models, including a support vector machine on top of activations of a pretrained convolutional neural network, as well as a Naive Bayes framework on a ‘bag-of-activations’ image representation, where each element of the bag is considered separately. This representation allows key components in the image to be isolated, in spite of largely varying backgrounds and image clutter, without an object detection or image segmentation step. The methods are evaluated based on how well they transfer to unseen camera-trap images captured across diverse topographical regions under different environmental conditions and illumination settings, involving a large domain shift.
Enhancers facilitate the birth of de novo genes and their integration into regulatory networks

Regulatory networks control the spatiotemporal gene expression patterns that give rise to and define the individual cell types of multicellular organisms. In eumetazoa, distal regulatory elements called enhancers play a key role in determining the structure of such networks, particularly the wiring diagram of “who regulates whom. ” Mutations that affect enhancer activity can therefore rewire regulatory networks, potentially causing changes in gene expression that are adaptive. Here, we use whole-tissue and single-cell transcriptomic and chromatin accessibility data from mouse to show that enhancers play an additional role in the evolution of regulatory networks: They facilitate network growth by creating transcriptionally active regions of open chromatin that are conducive to de novo gene evolution. Specifically, our comparative transcriptomic analysis with three other mammalian species shows that young, mouse-specific intergenic open reading frames are preferentially located near enhancers, whereas older open reading frames are not. Mouse-specific intergenic open reading frames that are proximal to enhancers are more highly and stably transcribed than those that are not proximal to enhancers or promoters, and they are transcribed in a limited diversity of cellular contexts. Furthermore, we report several instances of mouse-specific intergenic open reading frames that are proximal to promoters that show evidence of being repurposed enhancers. We also show that open reading frames gradually acquire specific interactions with enhancers over macro-evolutionary timescales, helping integrate new genes into existing regulatory networks. Taken together, our results highlight a dual role of enhancers in expanding and rewiring gene regulatory networks.
An unnatural base pair system for efficient PCR amplification and functionalization of DNA molecules

Toward the expansion of the genetic alphabet, we present an unnatural base pair system for efficient PCR amplification, enabling the site-specific incorporation of extra functional components into DNA. This system can be applied to conventional PCR protocols employing DNA templates containing unnatural bases, natural and unnatural base triphosphates, and a 3′→5′ exonuclease-proficient DNA polymerase. For highly faithful and efficient PCR amplification involving the unnatural base pairing, we identified the natural-base sequences surrounding the unnatural bases in DNA templates by an in vitro selection technique, using a DNA library containing the unnatural base. The system facilitates the site-specific incorporation of a variety of modified unnatural bases, linked with functional groups of interest, into amplified DNA. DNA fragments (0.15 amol) containing the unnatural base pair can be amplified 107-fold by 30 cycles of PCR, with <1% total mutation rate of the unnatural base pair site. Using the system, we demonstrated efficient PCR amplification and functionalization of DNA fragments for the extremely sensitive detection of zeptomol-scale target DNA molecules from mixtures with excess amounts (pmol scale) of foreign DNA species. This unnatural base pair system will be applicable to a wide range of DNA/RNA-based technologies.
Flatness Based Control of a Gantry Crane

Abstract This contribution deals with flatness based control of a laboratory model of a gantry crane. The mechanical model has 3DOFs, where a trolley can be moved on a rail, the load is fixed at the end of a rope and can be lifted or lowered by coiling or uncoiling this rope on a cylinder. Under the assumption that the rope is always stretched, the underactuated system is not input to state linearisable but it is flat with the coordinates of the load as flat output. Since the flat output coincides with the variables to be controlled, a flatness based design for trajectory tracking and stabilisation is indicated. The design of the tracking control is accomplished in two steps. First, the system is exactly linearised by a quasi-static state feedback. Subsequently, for the linear system a feedback with integral parts is designed such that the motion of the load is stabilised about the reference trajectories. Moreover, the control law is extended by terms which approximately compensate for the friction occurring at the gantry crane. Finally, the setting of the controller parameters is discussed and measurement results are presented, which demonstrate an excellent tracking behaviour and disturbance attenuation.
Honeypots: catching the insider threat

In the past several years there has been extensive research into honeypot technologies, primarily for detection and information gathering against external threats. However, little research has been done for one of the most dangerous threats, the advance insider, the trusted individual who knows our internal organization. These individuals are not after our systems, they are after our information. We discuss how honeypot technologies can be used to detect, identify, and gather information on these specific threats.
Does self-compassion covary with minority stress? Examining group differences at the intersection of marginalized identities

ABSTRACT Informed by the minority-stress hypothesis and intersectionality theory, this study examines differences in dispositional self-compassion across diverse youth subject to varying levels of structural and interpersonal discrimination. A secondary analysis of survey data from two suburban high schools in a Midwestern state (n = 1872) found significant differences in rates of exposures to stigma processes in accordance to rates of marginalization as estimated by sexual and/or gender status and racial category (minority vs majority), with a large effect. Sexual and/or gender minority students of color (SGmin) reported the highest rates of stigma experiences including exposure to economic hardship, having an incarcerated parent, not trusting the police, assignment of an IEP and exclusionary discipline. However, white SGmin students reported the highest rates of mental health concerns. Sexual gender majority (SGmaj) students of color reported the highest rates of self-compassion while white SGmin students reported the lowest and the negative relation between bullying and self-compassion was stronger for white SGmin students than for SGmin students of color, suggesting that the latter may have developed ways of coping with multiple stigmatized identities that reflect kindness to the self. As scholars seek to understand the role of self-compassion in resilience processes, we suggest emphasizing the strengths of marginalized youth as well as protecting them from the ill effects of bullying.
CS 229 Final Project : Divergent Recommendations for Yelp Users

The objective of this project is to make a recommendation for a Yelp user that is significantly different from what the user has tried in the past. We refer to such recommendations as “divergent recommendations”. For this goal, we leveraged machine learning methodologies and used various regressionbased models and collaborative filtering to predict ratings and user-restaurant similarity. By combining these two predictions, we made "divergent recommendations" based on user and restaurant profiles. In addition, we implemented methods in solving constraint satisfaction problems (CSPs) to ensure the diversity of recommendations.
Effects of trauma reminders on memory and attention processes : the role of associated emotional distress and unsupportive social interactions

Stressful life events and traumatic experiences have been associated with adverse psychological outcomes. Beyond their pronounced immediate effects, stressors may proactively influence physiological and emotional responses to subsequently encountered stressors (sensitization). These proactive stressor effects appear to extend to cognitive functioning and may be particularly prominent in situations reminiscent of the initial stressor experience. The present investigation examined the influence of trauma reminders, and the ensuing emotional responses, on memory and attention functioning. As coping methods and social support (or conversely 'unsupport") may influence the distress individuals experienced, particular consideration was given to the potential moderating effects of unsupportive social interactions individuals encountered during their most distressful experience. In Study 1 {n = 65) exposure to trauma images and previous trauma altered memory performance and these effects were most prominent among traumatized individuals that were exposed to trauma related stimuli. These variations were less pronounced in Study 2{n= 157), but decreased memory functioning was associated with increased distress and Cortisol reactivity following trauma reminders. Study 3 (n = 195) indicated that traumatized individuals having more negative social interactions during their most distressing experience, exhibited greater attention bias toward trauma-related material than traumatized individuals without such social interactions. These findings highlight the dynamic effects of trauma reminders on cognitive processes. Additional studies with clinical populations are required to obtain a more detailed understanding of the processes involved in the relationships between trauma experiences and cognitive functioning.
Probabilistic Matching Algorithm for Keypoint Based Object Tracking Using a Delaunay Triangulation

This article presents a matching algorithm developed for a generic object tracking system. Matching is a critical part for the effectiveness of tracking. The proposed method is a probabilistic algorithm inspired from the emerging "discriminative random fields". Points are associated according to their visual similarity and to spatial relations in their neighborhood, based on a Delaunay triangulation. Experimental results are presented to validate this contribution.
HIV-1 subtype E progression among northern Thai couples: traditional and non-traditional predictors of survival.

BACKGROUND In the continuing effort to introduce antiretroviral therapy in resource-limited settings, there is a need to understand differences between natural history of HIV in different populations and to identify feasible clinical measures predictive of survival. METHODS We examined predictors of survival among 836 heterosexuals who were infected with HIV subtype CRF01_AE in Thailand. RESULTS From 1993 to 1999, 269 (49.4%) men and 65 (25.7%) women died. The median time from the estimated seroconversion to death was 7.8 years (95% confidence interval 7.0-9.1). Men and women with enrolment CD4 counts <200 cells/microl had about 2 and 11 times greater risk of death than those with CD4 counts of 200-500 and >500, respectively. Measurements available in resource-limited settings, including total lymphocyte count (TLC), anaemia, and low body mass index (BMI), also predicted survival. Men with two or more of these predictors had a median survival of 0.8 (0.5-1.8) years, compared with 2.7 (1.9-3.3) years for one predictor and 4.9 (4.1-5.2) years for no predictors. CONCLUSIONS The time from HIV infection to death appears shorter among this Thai population than among antiretroviral naive Western populations. CD4 count and viral load (VL) were strong, independent predictors of survival. When CD4 count and VL are unavailable, individuals at high risk for shortened HIV survival may be identified by a combination of low TLC, anaemia, and low BMI. This combination of accessible clinical measures of the disease stage may be useful for medical management in resource-limited settings.
A COMBINED AGILE METHODOLOGY FOR THE EVALUATION OF WEB ACCESSIBILITY

To assure and certify the fulfillment of web accessibility guidelines ( WCAG 1.0 & 2.0) and to guarantee accessibility to all disabled users, various accessibility evaluation methods have been proposed, basically classified in two types: qualitative methods (analytical and empirical) and quantitative methods (metric-based methods). As no method by itself is enough to guarantee full accessibility, many studies advice to combine these methods between each other in order to guarantee better results. Some recent studies present combined evaluation methods between qualitative methods only, thus leaving behind the great power of metrics that guarantee objective results and task diversity. To achieve this goal, the current paper proposes a systematic combined agile accessibility evaluation method based both on qualitative and quantitative evaluation methods. This proposal presents an evaluation methodology that combines between the essential analytical evaluation methods and the empirical user test methods. Finally, WAB metric (Web Accessibility Barrier) is included to summarize objectively the final results and amplify the use of this method to cover all types of evaluations tasks, like validating, certifying and comparing processes.
Feature-based piecewise rigid registration in 2-D medical images

Piecewise rigid registration is a fundamental problem in medical imaging involving intra-patient pose differences in multiple medical images, mostly due to articulated motion. In this paper, we propose a method to extract multiple rigid transformations in 2D medical images in the presence of outliers. First, points of interest in the images are extracted and matched with the SIFT algorithm. Secondly, multiple rigid motions are sampled and clustered by the mean shift algorithm in the special Euclidean group SE(2), a smooth manifold of 2-D rigid transformation matrices. The method proposed is evaluated for intra-subject registrations of knee fluoroscopy images, demonstrating a mean angular and translational error on the estimated motion of 0.39° and 6.65 pixels, respectively.
First-line immune-chemotherapy combination: the right strategy to fight squamous non-small cell lung cancer?

In The New England Journal of Medicine , Paz-Ares and colleagues published the results of KEYNOTE-407, a randomized phase III placebo-controlled trial, investigating the addition of pembrolizumab or placebo to first-line carboplatin-taxane chemotherapy, in patients with advanced squamous non-small cell lung cancer (NSCLC) (1). The study met its co-primary end-points, since immune-chemotherapy combination led to a significant longer overall survival (OS) and progression-free survival (PFS) as compared to placebo combination.
Isoflurane and Sevoflurane Induce Severe Hepatic Insulin Resistance in a Canine Model

Introduction Anesthesia induces insulin resistance, which may contribute to elevated blood glucose and adverse post-operative outcomes in critically ill patients, and impair glycemic control in surgical patients with diabetes. However, little is known about the mechanisms by which anesthesia impairs insulin sensitivity. Here we investigate the effects of anesthesia on insulin sensitivity in metabolic tissues. Methods Hyperinsulinemic-euglycemic clamps were performed in 32 lean (control diet; n = 16 conscious versus n = 16 anesthetized) and 24 fat-fed (6 weeks fat-feeding; n = 16 conscious versus n = 8 anesthetized) adult male mongrel dogs in conjunction with tracer methodology to differentiate hepatic versus peripheral insulin sensitivity. Propofol was administered as an intravenous bolus (3mg/kg) to initiate anesthesia, which was then maintained with inhaled sevoflurane or isoflurane (2–3%) for the duration of the procedure. Results Anesthesia reduced peripheral insulin sensitivity by approximately 50% in both lean and fat-fed animals as compared to conscious animals, and insulin action at the liver was almost completely suppressed during anesthesia such that hepatic insulin sensitivity was decreased by 75.5% and; 116.2% in lean and fat-fed groups, respectively. Conclusion Inhaled anesthesia induces severe hepatic insulin resistance in a canine model. Countermeasures that preserve hepatic insulin sensitivity may represent a therapeutic target that could improve surgical outcomes in both diabetic and healthy patients.
Solving Symmetrical CSPs with an Asymmetrical Cost Function

Many CSPs contain a combination of symmetrical and asymmetrical constraints. We present a global approach that allows to apply any usual methods for breaking symmetries on the symmetrical part of a CSP and then to search for a global solution by integrating afterwards the asymmetrical constraints. Then, we focus on optimization problems where only the cost function is asymmetrical
Maspin expression profile in human prostate cancer (CaP) and in vitro induction of Maspin expression by androgen ablation.

PURPOSE Expression of tumor suppressor gene, MASPIN, is associated with inhibition of tumor cell invasion and metastasis. Loss of or decreased expression of Maspin is found frequently in breast and prostate cancer cells. The objective of this study is to investigate Maspin expression in prostate tumor specimens and explore the mechanisms of hormonal regulation of Maspin expression in prostate tumors. EXPERIMENTAL DESIGN Immunohistochemical staining of Maspin expression was performed on surgical whole-mounted prostate specimens. The expression of Maspin was scored on individual tumors. Correlation of Maspin expression with clinicopathological features was analyzed for statistical significance. Androgen ablation-induced Maspin expression was analyzed by Maspin promoter luciferase reporter assay and quantitative reverse transcription-PCR analysis of endogenous Maspin expression in LNCaP cells in vitro and in animal model. RESULTS Comprehensive evaluation of Maspin expression profile in multiple tumor foci from whole mounted prostate specimens of prostate cancer patients revealed absence of Maspin expression in a significant fraction (63%). However, Maspin expression is significantly higher in tumor specimens (92%) of patients treated with neoadjuvant androgen ablation therapy before radical prostatectomy. LNCaP cells cultured in androgen-depleted medium show induction of Maspin promoter activity in a promoter luciferase reporter assay. In addition, Maspin expression is increased after castration in LNCaP prostate cancer cells derived tumors in nude mice. CONCLUSIONS Maspin expression is frequently absent in primary prostate cancers. Up-regulation of MASPIN in response to androgen ablation strongly suggests a physiological role of Maspin in growth inhibition and/or apoptosis of prostate cancer cells during androgen ablation.
Electricity theft detection using smart meter data

Electricity theft is a major concern for the utilities. With the advent of smart meters, the frequency of collecting household energy consumption data has increased, making it possible for advanced data analysis, which was not possible earlier. We have proposed a temperature dependent predictive model which uses smart meter data and data from distribution transformer to detect electricity theft in an area. The model was tested for varying amounts of power thefts and also for different types of circuit approximations. The results are encouraging and the model can be used for real world application.
Color-line vector field and local color component decomposition for smoothing and denoising of color images

Most conventional smoothing and denoising methods for color images deal with each color channel independently, which results in discolorations due to unbalancing the relation between the color components. In this paper, we propose a smoothing algorithm to reduce discolorations based on ”color-lines”. Our iterative algorithm consists of a local color decomposition step by color-line vectors and an iterative filtering step. Our numerical simulation shows that the method improves image quality with less discolorations while keeping the smoothing capability.