Miracle-dz/UniFAR-FTUs huggingface dataset:
Rabies and Canine Distemper Virus Epidemics in the Red Fox Population of Northern Italy (2006–2010)

Since 2006 the red fox (Vulpes vulpes) population in north-eastern Italy has experienced an epidemic of canine distemper virus (CDV). Additionally, in 2008, after a thirteen-year absence from Italy, fox rabies was re-introduced in the Udine province at the national border with Slovenia. Disease intervention strategies are being developed and implemented to control rabies in this area and minimise risk to human health. Here we present empirical data and the epidemiological picture relating to these epidemics in the period 2006–2010. Of important significance for epidemiological studies of wild animals, basic mathematical models are developed to exploit information collected from the surveillance program on dead and/or living animals in order to assess the incidence of infection. These models are also used to estimate the rate of transmission of both diseases and the rate of vaccination, while correcting for a bias in early collection of CDV samples. We found that the rate of rabies transmission was roughly twice that of CDV, with an estimated effective contact between infected and susceptible fox leading to a new infection occurring once every 3 days for rabies, and once a week for CDV. We also inferred that during the early stage of the CDV epidemic, a bias in the monitoring protocol resulted in a positive sample being almost 10 times more likely to be collected than a negative sample. We estimated the rate of intake of oral vaccine at 0.006 per day, allowing us to estimate that roughly 68% of the foxes would be immunised. This was confirmed by field observations. Finally we discuss the implications for the eco-epidemiological dynamics of both epidemics in relation to control measures.
Searching for better configurations: a rigorous approach to clone evaluation

Clone detection finds application in many software engineering activities such as comprehension and refactoring. However, the confounding configuration choice problem poses a widely-acknowledged threat to the validity of previous empirical analyses. We introduce desktop and parallelised cloud-deployed versions of a search based solution that finds suitable configurations for empirical studies. We evaluate our approach on 6 widely used clone detection tools applied to the Bellon suite of 8 subject systems. Our evaluation reports the results of 9.3 million total executions of a clone tool; the largest study yet reported. Our approach finds significantly better configurations (p < 0.05) than those currently used, providing evidence that our approach can ameliorate the confounding configuration choice problem.
An Effective Usage and Access Control Scheme for Preventing Permission Leak in a Trusted Execution Environment

In the universal Android system, each application runs in its own sandbox, and the permission mechanism is used to enforce access control to the system APIs and applications. However, permission leak could happen when an application without certain permission illegally gain access to protected resources through other privileged applications. In order to address permission leak in a trusted execution environment, this paper designs security architecture which contains sandbox module, middleware module, usage and access control module, and proposes an effective usage and access control scheme that can prevent permission leak in a trusted execution environment. Security architecture based on the scheme has been implemented on an ARM-Android platform, and the evaluation of the proposed scheme demonstrates its effectiveness in mitigating permission leak vulnerabilities.
Face recognition in a border control environment: non-zero effort attacks' effect on false acceptance rate

Face recognition is a biometric authentication method that has become more and more relevant in the recent years. From being too inaccurate, it is becoming a more mature technology deployed in large scale systems like the new Visa Information System. From the earlier FERET evaluations to the more recent Face Recognition Vendor Test 2000 and 2002 evaluations we have observed significant improvements in face recognition. Systems based on 3D face recognition even claims to distinguish between identical twins. During our research we have seen that even though face recognition have greatly matured since the earliest forms, there still exists several possible attacks against this technology. Some of the attacks reviewed in this report are specific to face recognition, while others apply for all authentication methods. During the deployment process of face recognition, these attacks should be taken in consideration. As Kosmerlj stated in her thesis; there is still work to be done to improve face recognition before it can be applied in high security settings or applied in large scale applications. One method to reduce the number of people being falsely accepted is by combining the face recognition system with human supervision. To survey the additional value of a human supervisor, we conducted an experiment where we investigated whether a human would detect false acceptances made by a computerized system, and the role of hair in human recognition of faces. The study showed that, on average, humans were able to detect almost 80 % of the errors made by the computerized system. More over, the study shows that the ability of an individual to recognize a human face is a function of hair: the false acceptance rate was significantly higher for the image-pairs where the hair was removed compared to where it was present. This indicates that there is in fact a substantial opportunity for an impostor to circumvent the human guard using simple and cheap methods. Hair is a feature that may be easily manipulated, and this is perhaps the easiest and cheapest form of non-zero-effort attack on a face recognition system.
Machine Vision Guided System for Classification and Detection of Plant Diseases using Support Vector Machine

Plant diseases have turned into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products. We propose and experimentally evaluate a software solution for automatic detection and classification of plant leaf diseases (ClassifierSupport Vector Machines) using a machine vision guided system. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively expensive, especially in developing countries. Providing fast, automatic, cheap and accurate image processing based solutions for that task can be of great realistic significance. The proposed system is a combination of robotics and image processing a step towards automation. The robotic system is used for real time crop monitoring and image acquisition, it is a complete wireless system controlled by the laptop using Bluetooth device and a T.V. tuner for video processing. The acquired image will be transferred to the host laptop. The developed processing scheme consists of using color transform followed by the segmentation phase. In the first step we identify the mostly green colored pixels. Next, these pixels are masked based on specific threshold values. The other additional step is that the pixels with zeros red, green and blue values and the pixels on the boundaries of the infected cluster (object) are completely removed. Using color segmentation the diseased part is segmented and an algorithm is developed for feature extraction. Acquired features are used as criteria for identification of the disease. Further we train samples and test them using SVM classifier and identify the diseases. Additional feature is the GUI with a voice output in Marathi which includes the name of the identified disease and its probable solution according to the database. For experimental purpose we use Mango plant. The technique is a robust technique for the detection of plant diseases.
Understanding the impact of CUDA tuning techniques for Fermi

While the correctness of an NVIDIA CUDA program is easy to achieve, exploiting the GPU capabilities to obtain the best performance possible is a task for CUDA experienced programmers. Typical code tuning strategies, like choosing an appropriate size and shape for the thread-blocks, programming a good coalescing, or maximize occupancy, are inter-dependent. Moreover, the choices are also dependent on the underlying architecture details, and the global-memory access pattern of the designed solution. For example, the size and shapes of threadblocks are usually chosen to facilitate encoding (e.g. square shapes), while maximizing the multiprocessors' occupancy. However, this simple choice does not usually provide the best performance results. In this paper we discuss important relations between the size and shapes of threadblocks, occupancy, global memory access patterns, and other Fermi architecture features, such as the configuration of the new transparent cache. We present an insight based approach to tuning techniques, providing lines to understand the complex relations, and to easily avoid bad tuning settings.
Memory matrix: a novel user experience for home video

Nowadays, various efforts have sprung up aiming to automatically analyze home videos and provide users satisfactory experiences. In this paper, we present a novel user experience for home video called Memory Matrix, which could facilitate users to re-experience the joy of their memories, travelling along not only the time axis but also the space axis. In other words, the video clips (sub-shots) are organized both by taken times and taken locations, which further allows the user to browse home videos taken at similar locations. Moreover, given a specific query in Memory Matrix (row, column), it can also provide the user optional summaries along the time axis or space axis. The summarization scheme in this paper is based on a top-down interest score generation algorithm which automatically propagates the pre-labeled video level interest scores to sub-shot level interest scores. Firstly, the user is asked to provide interest scores to all the video sequences in the home video collection. Then, the video sequences are decomposed into sub-shots which are represented by keyframes. Consequently, we employ multi-scale spatial saliency analysis to remove the foregrounds and model the background scenes based on histogram of visual words. Finally, the interest scores are propagated from video level to sub-shot level by using gradient descent algorithm. Experimental results demonstrate the effectiveness, efficiency, and robustness of our framework.
Revealing the High-Redshift Star Formation Rate with Gamma-Ray Bursts

While the high-z frontier of star formation rate (SFR) studies has advanced rapidly, direct measurements beyond z ∼ 4 remain difficult, as shown by significant disagreements among different results. Gamma-ray bursts, owing to their brightness and association with massive stars, offer hope of clarifying this situation, provided that the GRB rate can be properly related to the SFR. The Swift GRB data reveal an increasing evolution in the GRB rate relative to the SFR at intermediate z; taking this into account, we use the highest-z GRB data to make a new determination of the SFR at z = 4–7. Our results exceed the lowest direct SFR measurements and imply that no steep drop exists in the SFR up to at least z ∼ 6.5. We discuss the implications of our result for cosmic reionization, the efficiency of the universe in producing stellar-mass black holes, and “GRB feedback” in star-forming hosts.
Combining Perceptions and Prescriptions in Requirements Engineering Process Assessment: An Industrial Case Study

Requirements engineering (RE) is a key discipline in software development and several methods are available to help assess and improve RE processes. However, these methods rely on prescriptive models of RE; they do not, like other disciplines within software engineering, draw directly on stakeholder perceptions and subjective judgments. Given this backdrop, we present an empirical study in RE process assessment. Our aim was to investigate how stakeholder perceptions and process prescriptions can be combined during assessments to effectively inform RE process improvement. We first describe existing methods for RE process assessment and the role played by stakeholder perceptions and subjective judgments in the software engineering and management literature. We then present a method that combines perceptions and prescriptions in RE assessments together with an industrial case study in which the method was applied and evaluated over a three-year period at TelSoft. The data suggest that the combined method led to a comprehensive and rich assessment and it helped TelSoft consider RE as an important and integral part of the broader engineering context. This, in turn, led to improvements that combined plan-driven and adaptive principles for RE. Overall, the combined method helped TelSoft move from Level 1 to Level 2 in RE maturity, and the employees perceived the resulting engineering practices to be improved. Based on these results, we suggest that software managers and researchers combine stakeholder perceptions and process prescriptions as one way to effectively balance the specificity, comparability, and accuracy of software process assessments.
Old Wine in New Bottles? The Case of Self–Compassion and Neuroticism

Research on self–compassion, which is defined as being understanding and kind to oneself when confronted with negative experiences, has produced an impressive number of articles in recent years. This research shows that individual differences in self–compassion, as measured by the Self–Compassion Scale (SCS), are positively related to life satisfaction, health and social functioning. However, a critical and systematic test of self–compassion from a personality perspective has not yet conducted so far. In the present study (N = 576), we (i) tested the factor structure of the SCS, (ii) examined the distinctiveness of self–compassion with regard to the five–factor model of personality, focusing on neuroticism, and (iii) tested the incremental predictive power of self–compassion beyond the five–factor model in the context of life satisfaction. Confirmatory factor analyses supported a two–factor plus six facets solution of self–compassion (a positive factor and a negative factor). Additional analyses revealed that the negative factor was redundant with facets of neuroticism (rs ≥ .85), whereas the positive factor had some unique variance left. However, neither the negative factor nor the positive factor could explain substantial incremental variance in life satisfaction beyond neuroticism. Recommendations for how to use the SCS are provided, and the future of research on self–compassion is discussed. Copyright © 2017 European Association of Personality Psychology
Design, Analysis and Experiment of MEMS based Micropump by a Piezoelectric stack actuator for bio-medical Application

In this paper, we present the design, analysis and fabrication of MEMS based silicon micro-needles for insertion of fluid into the dermis and subcutaneous fat layer of human skin. Micro-electromechanical systems (MEMS) are uncovered to an assortment of liquid environments in applications such as chemical and biological sensors and microfluidic devices. In this paper, the design and fabrication of a multi- material high-performance micropump is presented. The fabrication process using MEMS fabrication techniques comprised of silicon and Pyrex micromachining and bonding. Manufacturing steps such as three small bulk cylindrical piezoelectric material elements that are integrated with micro-fabricated silicon-on-insulator (SOI) and glass micromachined substrates using eutectic bonding and anodic bonding processes were successfully realized and provide a robust and scalable production technique for the micro pump. Exceptional flow rates of 0.1 ml/min with 1 W power consumption based on piezoelectric stack actuation achieved by appropriate design optimization. The analysis forecasts that the resultant stresses due to applied meandering and axial loads are in the safe range below the acquiesce strength of the material.
Eliminating Range Checks using Static Single Assignment

We propose a new method of eliminating range checks in connection with array index expressions and assignments to variables of subrange types. Contrary to the approaches documented in the literature, we work on an extended static single assignment form (XSA) very near the target level. This gives signiicant advantages over previous attempts since many questions don't occur at all or else in a simpler form in the XSA. The technique has been implemented in a family of Modula-2 and Oberon-2 compilers.
Recognition memory across the lifespan: the impact of word frequency and study-test interval on estimates of familiarity and recollection

The goal of this study was to investigate recognition memory performance across the lifespan and to determine how estimates of recollection and familiarity contribute to performance. In each of three experiments, participants from five groups from 14 up to 85 years of age (children, young adults, middle-aged adults, young-old adults, and old-old adults) were presented with high- and low-frequency words in a study phase and were tested immediately afterwards and/or after a one day retention interval. The results showed that word frequency and retention interval affected recognition memory performance as well as estimates of recollection and familiarity. Across the lifespan, the trajectory of recognition memory followed an inverse u-shape function that was neither affected by word frequency nor by retention interval. The trajectory of estimates of recollection also followed an inverse u-shape function, and was especially pronounced for low-frequency words. In contrast, estimates of familiarity did not differ across the lifespan. The results indicate that age differences in recognition memory are mainly due to differences in processes related to recollection while the contribution of familiarity-based processes seems to be age-invariant.
Trust Enhanced Anonymous Routing in Mobile Ad-Hoc Networks

Anonymous routing is a value-added technique used in mobile ad hoc networks for the purposes of security and privacy concerns. It has inspired lot of research interest, but very few measures exist to trust-aware routing for anonymity protection. This paper proposes a reliable anonymous MANET routing protocol in the sense that the communicating parties are capable of choosing a secure end-to-end route free of any untrustworthy node during the anonymous route discovery process. The key features of our scheme are including of accomplishment of anonymity-related goals, trust-aware anonymous routing, effective pseudonym management and lightweight overhead in computation, communication and storage.
“It All Has to Do with Poor Parental Care”: Exploring the Predisposing Factors of Juvenile Delinquency in Ghana

The upsurge in the rate of juvenile delinquency over the past decades and scanty literature in the area of juvenile delinquency in Ghana necessitated this study. Accordingly, the study employed Travis Hirschi’s social bonding theory to explore the factors that predisposed the inmates of the Ghana Senior Correctional Center to delinquency. A qualitative research design was used and the researchers conducted 20 individual in-depth interviews to collect data from participants. The findings of the study revealed that juveniles at the Senior Correctional Center had weak attachment with parents and caregivers prior to their arrest. Weak parent-child attachment resulted from poor parenting (single parenting, weak socialization, weak supervision, child abuse and neglect and poverty). Additionally, the study found that weak parent-child attachment impacted negatively on the other elements of the social bonding theory (commitment, involvement, and belief). Based on the findings, the researchers suggested the need for the government and other stakeholders to implement strategies aimed at enhancing proper parenting.
Place Recognition using Near and Far Visual Information

Abstract In this paper we show how to carry out robust place recognition using both near and far information provided by a stereo camera. Visual appearance is known to be very useful in place recognition tasks. In recent years, it has been shown that taking geometric information also into account further improves system robustness. Stereo visual systems provide 3D information and texture of nearby regions, as well as an image of far regions. In order to make use of all this information, our system builds two probabilistic undirected graphs, each considering either near or far information. Inference is carried out in the framework of conditional random fields. We evaluate our algorithm in public indoor and outdoor datasets from the RAWSEEDS project and in an outdoor dataset obtained at the MIT campus. Results show that this combination of information is very useful to solve challenging cases of perceptual aliasing.
Latest Advances in the Generation of Single Photons in Silicon Carbide

The major barrier for optical quantum information technologies is the absence of reliable single photons sources providing non-classical light states on demand which can be easily and reliably integrated with standard processing protocols for quantum device fabrication. New methods of generation at room temperature of single photons are therefore needed. Heralded single photon sources are presently being sought based on different methods built on different materials. Silicon Carbide (SiC) has the potentials to serve as the preferred material for quantum applications. Here, we review the latest advances in single photon generation at room temperatures based on SiC.
Essential Role of the Coxsackie - and Adenovirus Receptor (CAR) in Development of the Lymphatic System in Mice

The coxsackie- and adenovirus receptor (CAR) is a cell adhesion molecule predominantly associated with epithelial tight junctions in adult tissues. CAR is also expressed in cardiomyocytes and essential for heart development up to embryonic day 11.5, but not thereafter. CAR is not expressed in vascular endothelial cells but was recently detected in neonatal lymphatic vessels, suggesting that CAR could play a role in the development of the lymphatic system. To address this, we generated mice carrying a conditional deletion of the CAR gene (Cxadr) and knocked out CAR in the mouse embryo at different time points during post-cardiac development. Deletion of Cxadr from E12.5, but not from E13.5, resulted in subcutaneous edema, hemorrhage and embryonic death. Subcutaneous lymphatic vessels were dilated and structurally abnormal with gaps and holes present at lymphatic endothelial cell-cell junctions. Furthermore, lymphatic vessels were filled with erythrocytes showing a defect in the separation between the blood and lymphatic systems. Regionally, erythrocytes leaked out into the interstitium from leaky lymphatic vessels explaining the hemorrhage detected in CAR-deficient mouse embryos. The results show that CAR plays an essential role in development of the lymphatic vasculature in the mouse embryo by promoting appropriate formation of lymphatic endothelial cell-cell junctions.
A Binary Classification of Beatles Song Authorship

MACHINE learning algorithms have a long history with the problem of text classification which has been used extensively for a variety of applications including spam classification as well as the identification of the disputed authorship of several Federalist Papers [1][2]. In our project, we attempt to use the tools of machine learning to identify the primary author of a given Beatles’ song using the lyrics as features. Since a large majority of Beatles songs were written by either John Lennon or Paul McCartney, we restricted the scope of our project to a simple binary classification problem. Though text classification is a well known and widely used application of machine learning, the aim of this project is to analyze the performance of various classification algorithms and quantify their suitability for this problem.