Miracle-dz/UniFAR-FTUs huggingface dataset:
Citation for Published Item: Use Policy Using a Follow-on Survey to Investigate Why Use of the Visitor, Singleton & Facade Patterns Is Controversial

(2012) 'Using a follow-on survey to investigate why use of the visitor, singleton and facade patterns is controversial. The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full DRO policy for further details. ABSTRACT Context: A previous study has shown that software developers who are experienced with using design patterns hold some conflicting opinions about three of the more popular design patterns: Facade, Singleton and Visitor. Aim: To identify the characteristics of these three patterns that have caused them to generate such differing views. Method: We employed a qualitative follow-on survey of those developers who had taken part in the earlier survey about design patterns. Results: We received 46 usable responses from a possible total of 188, with nearly 85% of respondents having six or more years of experience with design patterns. Of these, 27 also provided comments and descriptions of experiences about the patterns, which we categorised. Conclusions: All three patterns can easily be misused and in each case, the consequences of misuse are regarded as being particularly significant.
Complexes of IgA with FcαRI/CD89 are not specific for primary IgA nephropathy

Complexes of IgA with FcαRI/CD89 are not specific for primary IgA nephropathy. Background The presence of IgA together with the myeloid IgA-receptor FcαRI/CD89 in the circulation of patients with IgA nephropathy (IgAN) has been suggested as a specific pathogenic factor for mesangial deposition. However, in a recent study we found these complexes also in serum samples from healthy subjects. To investigate whether these circulating complexes are specific for IgAN, the levels and characteristics of IgA-CD89 complexes were analyzed in patients with IgAN and healthy controls. Methods Specific ELISAs with different poly- and monoclonal antibodies and a sensitive dot-blot method were used to measure IgA-CD89 levels in serum and purified IgA samples obtained from healthy volunteers ( N = 30) and patients with IgAN ( N = 35). Fractionated samples of purified IgA were used to compare the size characteristics of the IgA-CD89 complexes. Results Almost all CD89 in serum of patients with IgAN and controls was associated with high molecular weight IgA. Quantitative analysis of IgA-CD89 complexes in purified IgA revealed no significant difference between patients with IgAN and controls. No correlation was found between levels of IgA-CD89 complexes and clinical parameters associated with progressive IgAN. Conclusions CD89 in the circulation is found mainly linked to high molecular weight IgA. The presence of these complexes is not specific for IgAN. Therefore, if IgA-CD89 complexes are involved in the pathogenesis of primary IgA nephropathy, additional factors are required to explain the IgA-CD89 complex-mediated renal inflammation.
ACMiner: Extraction and Analysis of Authorization Checks in Android's Middleware

Billions of users rely on the security of the Android platform to protect phones, tablets, and many different types of consumer electronics. While Android's permission model is well studied, the enforcement of the protection policy has received relatively little attention. Much of this enforcement is spread across system services, taking the form of hard-coded checks within their implementations. In this paper, we propose Authorization Check Miner (ACMiner), a framework for evaluating the correctness of Android's access control enforcement through consistency analysis of authorization checks. ACMiner combines program and text analysis techniques to generate a rich set of authorization checks, mines the corresponding protection policy for each service entry point, and uses association rule mining at a service granularity to identify inconsistencies that may correspond to vulnerabilities. We used ACMiner to study the AOSP version of Android 7.1. 1 to identify 28 vulnerabilities relating to missing authorization checks. In doing so, we demonstrate ACMiner's ability to help domain experts process thousands of authorization checks scattered across millions of lines of code.
Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture

This paper addresses the problem of interpolating visual textures. We formulate this problem by requiring (1) by-example controllability and (2) realistic and smooth interpolation among an arbitrary number of texture samples. To solve it we propose a neural network trained simultaneously on a reconstruction task and a generation task, which can project texture examples onto a latent space where they can be linearly interpolated and projected back onto the image domain, thus ensuring both intuitive control and realistic results. We show our method outperforms a number of baselines according to a comprehensive suite of metrics as well as a user study. We further show several applications based on our technique, which include texture brush, texture dissolve, and animal hybridization.
Don't Mine, Wait in Line: Fair and Efficient Blockchain Consensus with Robust Round Robin

Proof-of-Stake systems randomly choose, on each round, one of the participants as a consensus leader that extends the chain with the next block such that the selection probability is proportional to the owned stake. However, distributed random number generation is notoriously difficult. Systems that derive randomness from the previous blocks are completely insecure; solutions that provide secure random selection are inefficient due to their high communication complexity; and approaches that balance security and performance exhibit selection bias. When block creation is rewarded with new stake, even a minor bias can have a severe cumulative effect. In this paper, we propose Robust Round Robin, a new consensus scheme that addresses this selection problem. We create reliable long-term identities by bootstrapping from an existing infrastructure, such as Intel's SGX processors, or by mining them starting from an initial fair distribution. For leader selection we use a deterministic approach. On each round, we select a set of the previously created identities as consensus leader candidates in round robin manner. Because simple round-robin alone is vulnerable to attacks and offers poor liveness, we complement such deterministic selection policy with a lightweight endorsement mechanism that is an interactive protocol between the leader candidates and a small subset of other system participants. Our solution has low good efficiency as it requires no expensive distributed randomness generation and it provides block creation fairness which is crucial in deployments that reward it with new stake.
No-regret Bayesian Optimization with Unknown Hyperparameters

Bayesian optimization (BO) based on Gaussian process models is a powerful paradigm to optimize black-box functions that are expensive to evaluate. While several BO algorithms provably converge to the global optimum of the unknown function, they assume that the hyperparameters of the kernel are known in advance. This is not the case in practice and misspecification often causes these algorithms to converge to poor local optima. In this paper, we present the first BO algorithm that is provably no-regret and converges to the optimum without knowledge of the hyperparameters. During optimization we slowly adapt the hyperparameters of stationary kernels and thereby expand the associated function class over time, so that the BO algorithm considers more complex function candidates. Based on the theoretical insights, we propose several practical algorithms that achieve the empirical sample efficiency of BO with online hyperparameter estimation, but retain theoretical convergence guarantees. We evaluate our method on several benchmark problems.
A survey on acoustic sensing

The rise of Internet-of-Things (IoT) has brought many new sensing mechanisms. Among these mechanisms, acoustic sensing attracts much attention in recent years. Acoustic sensing exploits acoustic sensors beyond their primary uses, namely recording and playing, to enable interesting applications and new user experience. In this paper, we present the first survey of recent advances in acoustic sensing using commodity hardware. We propose a general framework that categorizes main building blocks of acoustic sensing systems. This framework consists of three layers, i.e., the physical layer, processing layer, and application layer. We highlight different sensing approaches in the processing layer and fundamental design considerations in the physical layer. Many existing and potential applications including context-aware applications, human-computer interface, and aerial acoustic communications are presented in depth. Challenges and future research trends are also discussed.
Real-Time Human-Robot Interaction for a Service Robot Based on 3D Human Activity Recognition and Human-Mimicking Decision Mechanism

In this paper, we present a real-time Human-Robot Interaction (HRI)system for a service robot based on 3D human activity recognition and human-mimicking decision mechanism. A three-layer Long-Short-Term Memory (LSTM)network is trained to recognize human activity. The input of this network is the 3D skeleton joints information captured by Kinect V1 and the output of this network is the class label of human activity. Moreover, the human-mimicking decision mechanism is also fused into the online test process of human activity recognition, which allows the robot to instinctively decide whether to interrupt the current task according to task priority. The robot can make appropriate responses based on aforementioned analytical results. The system framework is realized on the Robot Operating System (ROS). The real-life activity interaction between our service robot and the user was conducted to demonstrate the effectiveness of developed HRI system.
Hand Segmentation and Fingertip Tracking from Depth Camera Images Using Deep Convolutional Neural Network and Multi-task SegNet

Hand segmentation and fingertip detection play an indispensable role in hand gesture-based human-machine interaction systems. In this study, we propose a method to discriminate hand components and to locate fingertips in RGB-D images. The system consists of three main steps: hand detection using RGB images providing regions which are considered as promising areas for further processing, hand segmentation, and fingertip detection using depth image and our modified SegNet, a single lightweight architecture that can process two independent tasks at the same time. The experimental results show that our system is a promising method for hand segmentation and fingertip detection which achieves a comparable performance while model complexity is suitable for real-time applications.
Communication in multilingual society

This paper examines willingness to communicate and self-perceived communication competence of Italian-Croatian bilingual and Croatian monolingual students in two languages, Croatian and English. The study was conducted on the sample of 77 monolingual and 38 bilingual students at the University of Pula. The examination of the reported data has shown several facts. Firstly, bilingual students obtain higher scores in communication competence and willingness to communicate in both languages in comparison to the monolingual students. Secondly, it has also shown that it is easier for both groups of students to talk in Croatian language than in English as a foreign language.
Tumor-infiltrating human CD4+ regulatory T cells display a distinct TCR repertoire and exhibit tumor and neoantigen reactivity

Intratumoral Treg cells are tumor/neoantigen reactive. Neoantigen reactivity Elevated frequencies of intratumoral CD4+ regulatory T (Treg) cells have typically been associated with more rapid tumor progression, but the antigen specificity of these Treg cells within tumors is not well understood. Here, Ahmadzadeh et al. characterized the TCR repertoire of intratumoral Treg cells from patients with metastatic melanoma, gastrointestinal, and ovarian cancers. These Treg cells had a unique TCR repertoire different from other intratumoral CD4+ T cells, and dominant TCRs were specific to tumor/neoantigens. These tumor/neoantigen-specific Treg cells were also found in the periphery, indicating that these Treg cells may be expanding from both compartments. Together, these data provide insight into the tumor specificity of Treg cells and how they have the potential to be activated and expand within tumors. CD4+ regulatory T (Treg) cells have an essential function in maintaining self-tolerance; however, they may also play a detrimental role in antitumor immune responses. The presence of elevated frequencies of Treg cells in tumors correlates with disease progression and poor survival in patients with cancer. The antigen specificity of Treg cells that have expanded in the tumor microenvironment is poorly understood; answering this question may provide important insights for immunotherapeutic approaches. To address this, we used a novel combinatorial approach to characterizing the T cell receptor (TCR) profiles of intratumoral Treg cells from patients with metastatic melanoma, gastrointestinal, and ovarian cancers and elucidated their antigen specificities. The TCR repertoires of tumor-resident Treg cells were diverse yet displayed significant overlap with circulating Treg cells but not with conventional T cells in tumor or blood. TCRs isolated from Treg cells displayed specific reactivity against autologous tumors and mutated neoantigens, suggesting that intratumoral Treg cells act in a tumor antigen–selective manner leading to their activation and clonal expansion in the tumor microenvironment. Tumor antigen–specific Treg-derived TCRs resided in the tumor and in the circulation, suggesting that both Treg cell compartments may serve as a source for tumor-specific TCRs. These findings provide insights into the TCR specificity of tumor-infiltrating human Treg cells that may have potential implications for cancer immunotherapy.
How fast are the oceans warming?

Observational records of ocean heat content show that ocean warming is accelerating Climate change from human activities mainly results from the energy imbalance in Earth's climate system caused by rising concentrations of heat-trapping gases. About 93% of the energy imbalance accumulates in the ocean as increased ocean heat content (OHC). The ocean record of this imbalance is much less affected by internal variability and is thus better suited for detecting and attributing human influences (1) than more commonly used surface temperature records. Recent observation-based estimates show rapid warming of Earth's oceans over the past few decades (see the figure) (1, 2). This warming has contributed to increases in rainfall intensity, rising sea levels, the destruction of coral reefs, declining ocean oxygen levels, and declines in ice sheets; glaciers; and ice caps in the polar regions (3, 4). Recent estimates of observed warming resemble those seen in models, indicating that models reliably project changes in OHC.
OBJECT-ORIENTED APPROACH FOR 3D ARCHAEOLOGICAL DOCUMENTATION

Abstract. Documentation on archaeological fieldworks needs to be accurate and time-effective. Many features unveiled during excavations can be recorded just once, since the archaeological workflow physically removes most of the stratigraphic elements. Some of them have peculiar characteristics which make them hardly recognizable as objects and prevent a full 3D documentation. The paper presents a suitable feature-based method to carry on archaeological documentation with a three-dimensional approach, tested on the archaeological site of S. Calocero in Albenga (Italy). The method is based on one hand on the use of structure from motion techniques for on-site recording and 3D Modelling to represent the three-dimensional complexity of stratigraphy. The entire documentation workflow is carried out through digital tools, assuring better accuracy and interoperability. Outputs can be used in GIS to perform spatial analysis; moreover, a more effective dissemination of fieldworks results can be assured with the spreading of datasets and other information through web-services.
Flexible learning in a digital world: Experiences and expectations

1: The place of flexible learning 2: A new model for understanding how to use educational technology: the three-space model 3: Lessons learned 4: How successful has educational technology been? 5: The instructor and flexible learning 6: The department and flexible learning 7: The University and flexible learning 8: The multi-site institution and flexible learning 9: Government and flexible learning 10: Instructional design and flexible learning 11: The future of flexible learning.
Screening Diabetic Retinopathy in Developing Countries using Retinal Images

In developing countries, diabetic retinopathy (DR) is the leading cause of blindness in diabetic patients due to intraocular hypertension or high glucose level. Its detection in an earlier stage is essential to prevent vision loss in type 2 diabetic patients. In this paper, the computer aided automatic screening system for diabetic retinopathy is proposed. DR can be diagnosed by detecting the abnormal lesions such as hemorrhages in retinal images and analyzing its relationship with the fovea region. The proposed method consists of the following stages, namely: retinal image enhancement and classification, hemorrhages detection and segmentation, fovea localization and Diabetic Retinopathy classification. The multi directional local histogram equalization is used to enhance the retinal image for better classification rate. The Gabor transform and Support vector machine (SVM) classifier is used for retinal image classifications. The proposed method is tested on publicly available HRFand DIARETDB1datasets. The sensitivity and specificity of hemorrhages detection are 94.76% and 99.85%, respectively. Thus, the severity of Diabetic Retinopathy in Type 2 diabetic patients can be easily identified by detecting fovea region and hemorrhage lesions and analyzing the relation between them to prevent vision loss in diabetic patients.
Heterogeneity in Community Size Effects: Exploring Variations in the Production of National Hockey League Draftees Between Canadian Cities

Previous research has explored ‘community size effects’ in a multitude of sporting and regional contexts and has shown that athletes are more likely to originate from small-medium population size categories, and less likely to originate from very small or large ones. However, it is not clear whether the production of athletes is homogenous within population size categories. Place of birth data were collected for all Canadian born hockey players drafted into the National Hockey League (NHL) from 2000–2014 from British Columbia (N = 192), Alberta (N = 218), Saskatchewan and Manitoba (N = 216), Ontario (N = 561), Quebec (N = 241), and the Atlantic Provinces (N = 74). To explore variations in the production of draftees within population size categories, proportions of productive cities, population mean (μ), population standard deviation (σ), as well as minimum/maximum values of the number of draftees were calculated for the different categories (<2,500; 2,500–4,999; 5,000–9,999; 10,000–29,999; 30,000–99,999; 100,000–249,999; 250,000–499,999; 500,000–999,999; >1,000,000). In addition, the number of draftees produced per 1,000 residents (i.e., yield) was calculated for each city within all categories. Results showed substantial intra-categorical variability in NHL talent development; moreover, heterogeneity in draftee production existed in various degrees across provincial regions of Canada. Intra-categorical variability suggests that a single homogenous community size effect may not exist for Canadian NHL draftees, and that future research may benefit from exploring other environmental constraints on athlete development such as income, population density, and proximity to local sport clubs.
Protective Factors for Early Psychotic Phenomena Among Children of Mothers With Psychosis

Background: Early identification of sub-clinical psychotic experiences in at-risk individuals is vital to prevent the development of psychosis, even before prodromal symptoms emerge. A widely-replicated risk factor is having a family member with psychosis. The Environmental Risk (E-Risk) Longitudinal Twin Study has shown that better cognitive functioning, a stimulating family environment, and a cohesive community, are protective against psychotic experiences among children; while engaging in physical activity, social support, and a cohesive community are protective for adolescents. In the current study we investigate whether these factors also protect against the development of sub-clinical psychotic phenomena among children and adolescents in this cohort who are at high-risk of psychosis by having a mother with psychosis. Methods: Data were utilized from the E-Risk Longitudinal Twin Study, a nationally-representative cohort of 2,232 twin children born in England and Wales in 1994–1995 followed to age 18. Psychotic phenomena were assessed in private interviews with children at ages 12 and 18, and mothers were interviewed about their own experiences of psychosis when children were aged 10 and 12. Bivariate and multivariate logistic regression analyses explored associations between individual, family, and community-level putative protective factors and absence of age-12 psychotic symptoms and age-18 psychotic experiences in children whose mothers had a diagnosis of a psychosis-spectrum disorder and/or reported psychotic symptoms. Results: Higher IQ (OR = 0.97, 95% CI 0.94–1.00, P = 0.036) and living in a more socially cohesive neighborhood (OR = 0.88, 95% CI 0.79–0.98, P = 0.023) were independently protective against age-12 psychotic symptoms among children of mothers with psychosis. Higher levels of perceived social support were independently protective against age-18 psychotic experiences among children of mothers with psychosis (OR = 0.92, 95% CI 0.87–0.98, P = 0.006). However, there were no significant interactions between these protective factors and maternal psychosis in relation to an absence of childhood or adolescent psychotic phenomena in the full sample, indicating that protective effects were not specific to this group of high-risk children. Conclusions: These findings provide preliminary evidence that preventive interventions for early psychotic phenomena could focus on improving cognition, social support, and cohesiveness of the local community. Given scarce resources these might usefully be targeted at high-risk children.