Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Extinction Risk of Brazilian Atlantic Forest Angiosperms

Understanding how plant life history affects species vulnerability to anthropogenic disturbances and environmental change is a major ecological challenge. We examined how vegetation type, growth form, and geographic range size relate to extinction risk throughout the Brazilian Atlantic Forest domain. We used a database containing species‐level information of 6,929 angiosperms within 112 families and a molecular‐based working phylogeny. We used decision trees, standard regression, and phylogenetic regression to explore the relationships between species attributes and extinction risk. We found a significant phylogenetic signal in extinction risk. Vegetation type, growth form, and geographic range size were related to species extinction risk, but the effect of growth form was not evident after phylogeny was controlled for. Species restricted to either rocky outcrops or scrub vegetation on sandy coastal plains exhibited the highest extinction risk among vegetation types, a finding that supports the hypothesis that species adapted to resource‐limited environments are more vulnerable to extinction. Among growth forms, epiphytes were associated with the highest extinction risk in non‐phylogenetic regression models, followed by trees, whereas shrubs and climbers were associated with lower extinction risk. However, the higher extinction risk of epiphytes was not significant after correcting for phylogenetic relatedness. Our findings provide new indicators of extinction risk and insights into the mechanisms governing plant vulnerability to extinction in a highly diverse flora where human disturbances are both frequent and widespread.
Evolution in Population Parameters: Density-Dependent Selection or Density-Dependent Fitness?

Density-dependent selection is one of earliest topics of joint interest to both ecologists and evolutionary biologists and thus occupies an important position in the histories of these disciplines. This joint interest is driven by the fact that density-dependent selection is the simplest form of feedback between an ecological effect of an organism’s own making (crowding due to sustained population growth) and the selective response to the resulting conditions. This makes density-dependent selection perhaps the simplest process through which we see the full reciprocity between ecology and evolution. In this article, we begin by tracing the history of studying the reciprocity between ecology and evolution, which we see as combining the questions of evolutionary ecology with the assumptions and approaches of ecological genetics. In particular, density-dependent fitness and density-dependent selection were critical concepts underlying ideas about adaptation to biotic selection pressures and the coadaptation of interacting species. However, theory points to a critical distinction between density-dependent fitness and density-dependent selection in their influences on complex evolutionary and ecological interactions among coexisting species. Although density-dependent fitness is manifestly evident in empirical studies, evidence of density-dependent selection is much less common. This leads to the larger question of how prevalent and important density-dependent selection might really be. Life-history variation in the least killifish Heterandria formosa appears to reflect the action of density-dependent selection, and yet compelling evidence is elusive, even in this well-studied system, which suggests some important challenges for understanding density-driven feedbacks between ecology and evolution.
Algorithms and Hardware for Data Compression in Point Rendering Applications

The high storage requirements associated with point rendering applications make the utilization of data compression techniques interesting. Point rendering has been proposed only recently and, consequently, no compression strategies have yet been developed. In this paper we present compression algorithms for two specific data distributions widely used in point rendering: a naive distribution with no specific sorting of the points and a layer distribution which is suitable for incremental algorithms. In this last case points are sorted in layers and the connectivity among them is encoded. The algorithms we propose have a high compression rate (5.0 bits/point for the naive distribution and 7.7 bits/point for the layer distribution). Additionally we present the hardware implementation for the decompression of both algorithms. Both algorithms are implemented in a single hardware unit providing a control to select between them.
Social Bricolage: Theorizing Social Value Creation in Social Enterprises

Current theorizations of bricolage in entrepreneurship studies require refinement and development to be used as a theoretical framework for social entrepreneurship. Our analysis traces bricolage's conceptual underpinnings from various disciplines, identifying its key constructs as making do, a refusal to be constrained by limitations, and improvisation. Although these characteristics appear to epitomize the process of creating social enterprises, our research identifies three further constructs associated with social entrepreneurship: social value creation, stakeholder participation, and persuasion. Using data from a qualitative study of eight U.K. social enterprises, we apply the bricolage concept to social entrepreneurial action and propose an extended theoretical framework of social bricolage.
Do increases in task difficulty lead to corresponding increases in group efficacy, cohesiveness and performance?

The three Royal Air Force Development Training Centres (RAFDTCs) have been established to provide personal and team development training for all ranks. Outdoor activities are used at the centres as a catalyst to promote learning and exploration. Anecdotal evidence suggests there is a training effect from the centre activities however, a link to a specific effect remains elusive. The study, conducted at RAFDTC Fairbourne, explored whether increases in task difficulty (easy, moderate & hard), correspond with increases in group efficacy, group cohesion and performance time to complete the task. Additionally, following literature surrounding mediating and moderating variables (Kim, Kay, & Wright, 2001), research explored whether a triadic reciprocal causation between efficacy, cohesion and performance could be established (Bandura, 2001). The study participants were teams of 6 adults, randomly assigned to training groups for centre activities [12 (pilot) & 68 (main)]. To explore relationships between task difficulty, group efficacy, cohesiveness and group performance, a Leonardo`s Bridge Building exercise (Metalogs, 2010) was set. A small pilot study compared efficacy collection methods and was adjusted accordingly. Both pilot and main studies confirmed that, as task difficulty increases, there is a corresponding increase in time to complete the task (pilot study, pearson’s r (12) = . 968*, p= . 000 (1 tailed) & main study pearson’s r (68) = . 642*, p= . 000 (1 tailed)). The pilot study results indicated time was a significant predictor of pre and post task efficacy F(1.000,9.000)=5.880,p=. 038, ηp2=. 395 and that task level F(2.000,9.000)=12.000,p=. 003, ηp2=. 727 interacted with time to predict task efficacy. However, the larger sample in the main study did not confirm either of these findings. Results do not support a triadic reciprocal relationship between group efficacy, cohesion and performance. Group efficacy and cohesion (i.e., Group Integration Task) only appeared as an effect of performance.
Foldable augmented papers with a relaxed constraint

This paper presents an interaction approach for augmented reality using the folding with a relaxed constraint. In our approach, the user can fold a paper and see virtual contents overlaid on the paper. The paper can be folded in horizontal, vertical, and diagonal direction. The folded surface is defined as two polygonal planes that are connected in the folding line. The main contribution of this paper are the automatic detection of the folding line and the plane segmentation based on the extended folding model. In addition, the virtual contents can be overlaid on each segment planes by estimating the camera pose of each plane. We develop two interactive augmented reality applications that overlay the virtual contents dynamically when the user fold the paper.
Capturing more world knowledge in the requirements specification

The view is adopted that software requirements involve the representation (modeling) of considerable real-world knowledge, not just functional specifications. A framework (RMF) for requirements models is presented and its main features are illustrated. RMF allows information about three types of conceptual entities (objects, activities, and assertions) to be recorded uniformly using the notion of properties. By grouping all entities into classes or metaclasses, and by organizing classes into generalization (specialization) hierarchies, RMF supports three abstraction principles (classification, aggregation, and generalization) which appear to be of universal importance in the development and organization of complex descriptions. Finally, by providing a mathematical model underlying our terminology, we achieve both unambiguity and the potential to verify consistency of the model.
Synergistic Effects of Combined Phytochemicals and Skin Cancer Prevention in SENCAR Mice

The purpose of our study was to determine the inhibitory effect of combined phytochemicals on chemically induced murine skin tumorigenesis. Our hypothesis was that concurrent topical and dietary treatment with selected compounds would lead to more efficient prevention of skin cancer. We tested ellagic acid and calcium D-glucarate as components of diets, while resveratrol was applied topically; grape seed extract was applied topically or in the diet. The 4-week inflammatory-hyperplasia assay based on the 7,12-dimethylbenz[a]anthracene (DMBA)–induced skin carcinogenesis model in SENCAR mice was used. We have found that all the selected combinations caused a marked decrease of epidermal thickness compared with the DMBA-treated group and also with groups treated with a single compound and DMBA. All combinations of resveratrol with other compounds showed a synergistic effect on hyperplasia and Ha-ras mutations. Skin tissue of mice receiving the combinations showed decreased cell proliferation and Bcl2 expression; decreased p21, a regulator of cell cycle; and decreased marker of inflammation cyclooxygenase-2. All the selected combinations diminished the DMBA-induced mRNA expression of the CYP1B1 level, and also caused a marked decrease of proto-oncogenes c-jun and c-fos, components of transcription factor activator protein. In conclusion, all combinations showed either additive or synergistic effects and their joint actions allowed for decreasing the doses of the compounds. Especially, resveratrol combinations with ellagic acid, grape seed extract, and other phytochemicals are very potent inhibitors of skin tumorgenesis, based on the suppression of epidermal hyperplasia as well as on the modulation of intermediate biomarkers of cell proliferation, cell survival, inflammation, oncogene mutation, and apoptosis. Cancer Prev Res; 3(2); 170–8
Single and Multi-Person Face Recognition Using the Enhanced Eigenfaces Method 23

This research studies and analyzes the possibility of single-person and multi-person face detection and recognition. Face detection is performed by the Viola-Jones face detection method and recognition is performed by the Eigenfaces method. Unchanged face detection and recognition methods are explained and tested to their limits. Improvement in face recognition is achieved by observing the flaws of the Eigenfaces method and their enhancement.
Collaborative Assessment for Employment Planning

As the Workforce Innovation and Opportunities Act (WIOA) is implemented across the nation, special education and vocational rehabilitation professionals will need to increase their level of collaboration. One area of potential collaboration is assessment—transition assessment for the field of special education and the discovery process for adult service providers. The purpose of this article is to describe both processes, highlighting similarities and differences, and make recommendations for practice.
A New Support Vector Machine with Fuzzy Hyper-Plane and Its Application to Evaluate Credit Risk

Due to recent financial crises and regulatory concerns, financial intermediaries' credit risk assessment is an area of renewed interest in both the academic world and business community. Because in credit scoring areas we usually cannot label on customer as absolutely good who is sure to repay in time, or absolutely bad who will default certainly, in this paper, we apply a fuzzy membership to each input point and reformulate the optimization problem of SVM such that different input points can make different contributions to the learning of decision surface. Besides, the parameters to be identified in the SVM, such as the components within the weight vector and the bias term, are fuzzy numbers. This integration preserves the benefits of SVM learning theory and fuzzy set theory, where the SVM learning theory characterizes the properties of learning machines which enable them to effectively generalize the unseen data and the fuzzy set theory might be very useful for finding a fuzzy structure in an evaluation system.
Adherence to antiretroviral therapy in adolescents living with HIV: systematic review and meta-analysis

Objective:Adolescent and young adult (AYA) populations (12–24 years) represent over 40% of new HIV infections globally. Adolescence is sometimes characterized by high-risk sexual behaviour and a lack of engagement with healthcare services that can affect adherence to antiretroviral therapy (ART). Despite adherence to ART being critical in controlling viral replication, maintaining health and reducing onward viral transmission, there are limited data on ART adherence amongst AYA globally. We undertook a systematic review and meta-analysis of published studies reporting adherence to ART for AYA living with HIV. Design and methods:Searches included Embase, Medline and PsychINFO databases up to 14 August 2013. Eligible studies defined adequate adherence as at least 85% on self-report or undetectable blood plasma virus levels. A random effects meta-analysis was performed and heterogeneity examined using meta-regression. Results:We identified 50 eligible articles reporting data from 53 countries and 10 725 patients. Using a pooled analysis of all eligible studies, 62.3% [95% confidence interval (CI) 57.1–67.6; I2 : 97.2%] of the AYA population were adherent to therapy. The lowest average ART adherence was in North America [53% (95% CI 46–59; I2 : 91%)], Europe [62% (95% CI 51–73; I2 : 97%)] and South America [63% (95% CI 47–77; I2 : 85%] and, with higher levels in Africa [84% (95% CI 79–89; I2 : 93%)] and Asia [84% (95% CI 77–91; I2 : 0%]. Conclusion:Review of published literature from Africa and Asia indicate more than 70% of HIV-positive AYA populations receiving ART are adherent to therapy and lower rates of adherence were shown in Europe and North America at 50–60%. The global discrepancy is probably multifactorial reflecting differences between focused and generalised epidemics, access to healthcare and funding.
Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients

Objective To develop and validate practical prognostic models for death at 14 days and for death or severe disability six months after traumatic brain injury. Design Multivariable logistic regression to select variables that were independently associated with two patient outcomes. Two models designed: “basic” model (demographic and clinical variables only) and “CT” model (basic model plus results of computed tomography). The models were subsequently developed for high and low-middle income countries separately. Setting Medical Research Council (MRC) CRASH Trial. Subjects 10 008 patients with traumatic brain injury. Models externally validated in a cohort of 8509. Results The basic model included four predictors: age, Glasgow coma scale, pupil reactivity, and the presence of major extracranial injury. The CT model also included the presence of petechial haemorrhages, obliteration of the third ventricle or basal cisterns, subarachnoid bleeding, midline shift, and non-evacuated haematoma. In the derivation sample the models showed excellent discrimination (C statistic above 0.80). The models showed good calibration graphically. The Hosmer-Lemeshow test also indicated good calibration, except for the CT model in low-middle income countries. External validation for unfavourable outcome at six months in high income countries showed that basic and CT models had good discrimination (C statistic 0.77 for both models) but poorer calibration. Conclusion Simple prognostic models can be used to obtain valid predictions of relevant outcomes in patients with traumatic brain injury.
On the HTTP segment streaming potentials and performance improvements

The proposed architecture relies on end-to-end crosslayer signaling and control for video streaming optimization. The architecture supports extensive context information collection and transfer in heterogeneous networks; thus, enabling the efficient management of video stream adaptation and user terminal mobility in a diverse and dynamic network environment. The thesis also studies and proposes cross-layer enhancements for adaptive video streaming and mobility management functions enabled by the cross-layer architecture. These include cross-layer video adaptation, congestion-triggered handovers, and concurrent utilization of multiple access networks in the video stream transport. For the video adaptation and multipath transmission, the flexible adaptation and transmission capabilities of the novel scalable video coding technology are used. Regarding the mobility management, the proposed solutions essentially enhance the handover decision-making of the Mobile IP protocol to better support QoS-sensitive video streaming. Finally, the thesis takes a holistic view on the application adaptation and mobility management, and proposes a solution for coordinated control of these two operations in order to achieve end-to-end optimization.
Perceived legitimacy of intergroup status differences: its prediction by relative ingroup prototypicality

Research demonstrates that the perceived legitimacy of intergroup status differences has profound effects on intergroup attitudes, emotions and behavior. However, there has only been little intergroup research that predicts the perception of legitimacy. We hypothesize that the perception of legitimate or illegitime status relations depends upon the perceived relative prototypicality of the ingroup for the inclusive category. Since the prototype of the inclusive category provides a normative comparison standard for subgroup evaluation, similarity to this standard (i.e. prototypicality) should be positively evaluated and used to justify high status. A first study in a natural intergroup context (N = 67) offered correlational data in support of the predicted relationship. The second study (N = 60), using Germans as ingroup with Poles as outgroup and Europe as inclusive category, demonstrated that the link between prototypicality and legitimacy is contingent upon the valence of the inclusive category. In order to elucidate the causal direction, the third study manipulated relative prototypicality in an artificial intergroup context (N = 94) and introduced status as a moderator variable. Overall, we found strong support for the hypothesis that legitimacy is related to prototypicality and that this relation is moderated by ingroup status and valence of the inclusive category. Copyright © 2002 John Wiley & Sons, Ltd.
Wait-free reference counting and memory management

We present a practical wait-free implementation of a garbage collection scheme based on reference counting that uses atomic primitivism, which are available in modern computer systems. To the best of our knowledge, this is the first wait-free algorithm of a reference counting scheme that can support dynamic concurrent data structures. As all operations of wait-free algorithms are guaranteed to always finish in a finite number of their own steps independently of the other operations' actions, the new algorithm is especially suitable for real-time systems where execution time guarantees are of significant importance. We also present a wait-free algorithm of a free-list, for supporting concurrent allocation and freeing of memory blocks. The new algorithms are linearizable and are compatible to previous implementations of non-blocking dynamic data structures.
Similarity clustering of dimensions for an enhanced visualization of multidimensional data

The order and arrangement of dimensions (variates) is crucial for the effectiveness of a large number of visualization techniques such as parallel coordinates, scatterplots, recursive pattern, and many others. We describe a systematic approach to arrange the dimensions according to their similarity. The basic idea is to rearrange the data dimensions such that dimensions showing a similar behavior are positioned next to each other. For the similarity clustering of dimensions, we need to define similarity measures which determine the partial or global similarity of dimensions. We then consider the problem of finding an optimal one- or two-dimensional arrangement of the dimensions based on their similarity. Theoretical considerations show that both, the one- and the two-dimensional arrangement problem are surprisingly hard problems, i.e. they are NP complete. Our solution of the problem is therefore based on heuristic algorithms. An empirical evaluation using a number of different visualization techniques shows the high impact of our similarity clustering of dimensions on the visualization results.
Trial-by-TrialCouplingofConcurrentElectroencephalogram andFunctionalMagneticResonanceImagingIdentifiesthe DynamicsofPerformanceMonitoring

Goal-directed behavior requires the continuous monitoring and dynamic adjustment of ongoing actions. Here, we report a direct couplingbetweentheevent-relatedelectroencephalogram(EEG),functionalmagneticresonanceimaging(fMRI),andbehavioralmeasures ofperformancemonitoringinhumans.ByapplyingindependentcomponentanalysistoEEGsignalsrecordedsimultaneouslywithfMRI, we found the single-trial error-related negativity of the EEG to be systematically related to behavior in the subsequent trial, thereby reflectingimmediatebehavioraladjustmentsofacognitiveperformancemonitoringsystem.Moreover,thistrial-by-trialEEGmeasureof performancemonitoringpredictedthefMRIactivityintherostralcingulatezone,abrainregionthoughttoplayakeyroleinprocessing ofresponseerrors.WeconcludethatinvestigationsofthedynamiccouplingbetweenEEGandfMRIprovideapowerfulapproachforthe studyofhigherorderbrainfunctions.