Miracle-dz/UniFAR-FTUs huggingface dataset:
MIMiS: Minimally Intrusive Mining of Smartphone User Behaviors

The proliferation of smartphones has lead researchers towards using them as an observational tool in psychological science. However, there is little effort towards protecting user privacy in these analyses. The overarching question of our work is: Given a set of sensitive user features, what is the minimum amount of information required to group similar users? Our contributions are two fold: we introduce privacy surfaces that combine sensitive user data at different levels of temporal granularity. Second, we introduce MIMiS, an unsupervised privacy-aware framework that clusters users as homogeneous groups with respect to their temporal signature. In addition, we explore the trade-off between intrusiveness and prediction accuracy. We extensively evaluate MIMiS on real data across a variety of privacy surfaces. MIMiS identified groups that are highly homogeneous w.r. t. user mental health scores and their academic performance.
Brief Behavioural Activation Treatment of Chronic Anxiety in an Older Adult

Abstract A 64-year-old male who met criteria for social and generalised anxiety was treated using a brief behavioural activation (BA) approach. The intervention was delivered in twelve weekly 60-minute individual sessions. The effects of the intervention were assessed using a simple A-B-C phase change with repeated measurement design. Change in reported anxiety was recorded across phases. Decreased scores in self-reported anxiety measures were obtained and significant clinical improvement was maintained during a 4-month no treatment maintenance phase. This preliminary investigation suggests BA could be an efficient and effective treatment for anxiety and that replications are warranted.
Social and emotional wellbeing programs: the nexus between sustainability and quality assurance

When social-emotional wellbeing programs are well-implemented, positive changes in students' mental health and self-regulatory social-emotional capabilities can eventuate. However, a problematic area of program implementation is sustainability once the supports and resources of the 'startup' phases of new initiatives fade away. It is increasingly recognised that quality assurance procedures are necessary during the delivery of new programs. However, it appears that procedures for quality assurance of the sustainability components of programs have been relatively neglected. In this paper we investigate whether and why the KidsMatter Primary Mental Health Promotion initiative in Australia was sustained in schools one year after completion of the pilot phase. Thematic analysis indicated a range of facilitators and barriers to sustainability, and that many, but not all, schools continued to identify themselves as ‘KidsMatter’ schools. We propose a framework to guide a continuous cycle of quality assurance processes, with a specific focus on assuring program sustainability. We argue that more practical and conceptual work needs to be undertaken to develop tools and processes for explicit quality assurance of the sustainability components of mental health promotion and social-emotional wellbeing initiatives in educational settings.
An Efficient Design for Reduction of Power Dissipation in Johnson Counter using Clock Gating

: In this paper, a new method for minimizing power dissipation in 4-bit Johnson up-down counter is proposed. In this design, we have used a dual dynamic pulsed flip-flop (DDFF) [1], which supports embedding a logic module (DDFF-ELM) and a power saving technique, namely, clock gating [2] is used. We have used DDFF because it is power efficient compared to other flip-flops in the literature. We have used digital schematic editor (DSCH) for designing; simulation and layout generation is done using Microwind. From the simulation results, it is observed that power dissipation is reduced by 33.9 %.
Improvement in prediction of prostate cancer prognosis with somatic mutational signatures

Prostate cancer is a leading male malignancy worldwide, while the prognosis prediction remains quite inaccurate. The study aimed to observe whether there was an association between the prognosis of prostate cancer and genetic mutation profile, and to build an accurate prognostic predictor based on the genetic signatures. The patients diagnosed of prostate cancer from The Cancer Genomic Atlas were used for prognostic stratification, while the somatic gene mutation profiles were compared between different prognostic groups. The genetic features were further used for training machine-learning models to predict prostate cancer prognosis. No significant gene with somatic mutation rate difference was found between prognostic groups of prostate cancer. Total 43 atypical genes were screened for building a support vector machine model to predict prostate cancer prognosis, with an average accuracy of 66% and 64% for 5-fold cross-validation or training-testing evaluation respectively. When combined with the National Institute for Health and Care Excellence (NICE) features, the model could be further improved, with the 5-fold cross-validation accuracy of ~71%, much better than NICE itself (62%). To our knowledge, for the first time, the research studied the relationship of genome-wide somatic mutations with prostate prognosis, and developed an effective prognostic prediction model with the atypical genetic signatures.
A Cost-Effective Framework for Preference Elicitation and Aggregation

We propose a cost-effective framework for preference elicitation and aggregation under the Plackett-Luce model with features. Given a budget, our framework iteratively computes the most cost-effective elicitation questions in order to help the agents make a better group decision. We illustrate the viability of the framework with experiments on Amazon Mechanical Turk, which we use to estimate the cost of answering different types of elicitation questions. We compare the prediction accuracy of our framework when adopting various information criteria that evaluate the expected information gain from a question. Our experiments show carefully designed information criteria are much more efficient, i.e., they arrive at the correct answer using fewer queries, than randomly asking questions given the budget constraint.
Neural bases of social communicative intentions in speech

Abstract Our ability to understand others’ communicative intentions in speech is key to successful social interaction. Indeed, misunderstanding an ‘excuse me’ as apology, while meant as criticism, may have important consequences. Recent behavioural studies have provided evidence that prosody, that is, vocal tone, is an important indicator for speakers’ intentions. Using a novel audio-morphing paradigm, the present functional magnetic resonance imaging study examined the neurocognitive mechanisms that allow listeners to ‘read’ speakers’ intents from vocal prosodic patterns. Participants categorized prosodic expressions that gradually varied in their acoustics between criticism, doubt, and suggestion. Categorizing typical exemplars of the three intentions induced activations along the ventral auditory stream, complemented by amygdala and mentalizing system. These findings likely depict the stepwise conversion of external perceptual information into abstract prosodic categories and internal social semantic concepts, including the speaker’s mental state. Ambiguous tokens, in turn, involved cingulo-opercular areas known to assist decision-making in case of conflicting cues. Auditory and decision-making processes were flexibly coupled with the amygdala, depending on prosodic typicality, indicating enhanced categorization efficiency of overtly relevant, meaningful prosodic signals. Altogether, the results point to a model in which auditory prosodic categorization and socio-inferential conceptualization cooperate to translate perceived vocal tone into a coherent representation of the speaker’s intent.
The importance of a halotyrosine dehalogenase for Drosophila fertility

The ability of iodotyrosine deiodinase to salvage iodide from iodotyrosine has long been recognized as critical for iodide homeostasis and proper thyroid function in vertebrates. The significance of its additional ability to dehalogenate bromo- and chlorotyrosine is less apparent, and none of these functions could have been anticipated in invertebrates until recently. Drosophila, as most arthropods, contains a deiodinase homolog encoded by CG6279, now named condet (cdt), with a similar catalytic specificity. However, its physiological role cannot be equivalent because Drosophila lacks a thyroid and its associated hormones, and no requirement for iodide or halotyrosines has been reported for this species. We have now applied CRISPR/Cas9 technology to generate Drosophila strains in which the cdt gene has been either deleted or mutated to identify its biological function. As previously shown in larvae, expression of cdt is primarily limited to the fat body, and we now report that loss of cdt function does not enhance sensitivity of the larvae to the toxic effects of iodotyrosine. In adult flies by contrast, expression is known to occur in testes and is detected at very high levels in this tissue. The importance of cdt is most evident in the decrease in fertility observed when either males or females carry a deletion or mutation of cdt. Therefore, dehalogenation of a halotyrosine appears essential for efficient reproduction in Drosophila and likely contributes to a new pathway for controlling viability in arthropods.
Sustainable Chinese manufacturing competitiveness in the 21st century: green and lean practices, pressure and performance

Instead of focusing on economic growth, firms in the twenty-first century are paying more attention to environmental aspects in order to enhance their sustainable competitiveness. ‘Green and lean’ practices have emerged as a vital method for organisations that are seeking to become competitive and environmentally sustainable. This article aims to describe and evaluate green and lean practices, pressures and performance among various Chinese manufacturing organisations. Based on a literature review, five green and lean practice propositions are identified and summarised. This research collects data from 172 Chinese manufacturing organisations and derives groupings of green and lean practice, pressures and performance via an exploratory factor analysis. The results show that due to competition, marketing pressure and regulatory factors, Chinese manufacturing organisations have increased their environmental awareness to gain environmental competitiveness. This research establishes a foundation of green and lean practice for further investigation. It also suggests that a win-win relationship between economic growth and environment in Chinese manufacturing is possible, and can be enhanced by implementing green and lean practices.
On the Observed-Data Deviance Information Criterion for Volatility Modeling

We propose importance sampling algorithms based on fast band matrix routines for estimating the observed-data likelihoods for a variety of stochastic volatility models. This is motivated by the problem of computing the deviance information criterion (DIC)—a popular Bayesian model comparison criterion that comes in a few variants. Although the DIC based on the conditional likelihood—obtained by conditioning on the latent variables—is widely used for comparing stochastic volatility models, recent studies have argued against its use on both theoretical and practical grounds. Indeed, we show via a Monte-Carlo study that the conditional DIC tends to favor overfitted models, whereas the DIC based on the observed-data likelihood—calculated using the proposed importance sampling algorithms—seems to perform well. We demonstrate the methodology with an application involving daily returns on the Standard & Poors 500 index.
The contribution of inspiratory muscles function to exercise limitation in heart failure: pathophysiological mechanisms.

BACKGROUND Heart failure induces histological, metabolic and functional adaptations in the inspiratory muscles. This inspiratory muscle weakness, which occurs in 30% to 50% of the heart failure patients, is associated with reduction in the functional capacity, reduction in the quality of life and with a poor prognosis in these individuals. OBJECTIVES The objective of this review was to discuss the pathophysiological mechanisms that may explain the role of the inspiratory muscles in the exercise limitation with focus in the reflexes that control the ventilation and the circulation during the exercise. METHOD We performed searches in the PUBMED database using the terms "inspiratory muscles", "inspiratory muscle training", "metaboreflex" and chemoreflex" and including studies published since 1980. RESULTS Inspiratory muscle weakness is associated with exercise intolerance and with an exaggerated inspiratory chemoreflex and metaboreflex in heart failure. The inspiratory metaboreflex may be attenuated by the inspiratory muscle training or by the aerobic exercise training improving the exercise performance. CONCLUSIONS Patients with heart failure may present changes in the inspiratory muscle function associated with inspiratory chemoreflex and metaboreflex hyperactivity, which exacerbate the exercise intolerance.
Simulated Provocations: A Hypermedia Radio Theatre for Reflection on Classroom Management

Background. Learning to manage a classroom is a difficult but important part of teacher education. Earlier research on simulations for learning classroom management has highlighted the difficulty of supporting reflection. Purpose. This case study explores and evaluates the design of a simulation for student teachers’ reflection on classroom management. Design. The design process resulted in the scenario-based SIMPROV simulation, which was made in the form of a hypermedia radio theatre that students go through in pairs or triads. Authoritarian, authoritative, democratic, and compliant leadership styles were built into the choices student teachers made. Evaluation. The simulation was evaluated in two courses where the participants’ level of reflection and perceived knowledge improvement was measured using a questionnaire. Forty-three first-year student teachers, 48 third-year student teachers, and 38 of the student teachers’ mentors participated in the evaluation. Results. The results indicate that participants engaged in reflection and understanding to a high degree, and only to a low degree in critical reflection or habitual action. Conclusions. The conclusions are that the scenario-based simulation designed as a hypermedia radio theatre supported knowledge improvement, understanding, and reflection and that social interaction during and after simulation sessions was an important feature.
Record of Volcanism Since 7000 B.C. from the GISP2 Greenland Ice Core and Implications for the Volcano-Climate System

Sulfate concentrations from continuous biyearly sampling of the GISP2 Greenland ice core provide a record of potential climate-forcing volcanism since 7000 B.C. Although 85 percent of the events recorded over the last 2000 years were matched to documented volcanic eruptions, only about 30 percent of the events from 1 to 7000 B.C. were matched to such events. Several historic eruptions may have been greater sulfur producers than previously thought. There are three times as many events from 5000 to 7000 B.C. as over the last two millennia with sulfate deposition equal to or up to five times that of the largest known historical eruptions. This increased volcanism in the early Holocene may have contributed to climatic cooling.
Effects of Illumination , Texture , and Motion on Task Performance in Streamtube Visualization of Diffusion Tensor MRI

We present results from a user study comparing user task performance on streamtube visualizations generated from diffusion tensor magnetic resonance imaging (DTI) datasets. The independent variables include illumination model (global illumination and OpenGL style local illumination), texture (with and without), motion (with and without), and task. The three spatial analysis tasks are: (1) a depth-judgment task: determining which of two marked tubes is closer to the user’s viewpoint, (2) a visual-tracing task: marking the endpoint of a tube, (3) a contact-judgment task: analyzing tube-sphere penetration. Our results indicate that global illumination did not improve task completion time for the tasks we measured. Global illumination reduce the error rates of participants’ answers over local OpenGL-style rendering when motion was present for the visual-tracing task. Motion contributes to spatial understanding for all tasks, but at the cost of longer task completion time. A high-frequency texture pattern led to longer task completion times and higher error rates. These results suggest that generic visualization techniques are unlikely to be better than task-specific techniques tailored to the data being presented. Lighting design noticeably alters performance, indicating that designers need to pay it specific attention.
Unifying theories of logics with undefinedness

A relational approach to the question of how different logics relate formally is described. We consider three three-valued logics, as well as classical and semi-classical logic. A fundamental representation of three-valued predicates is developed in the Unifying Theories of Programming (UTP) framework of Hoare and He. On this foundation, the five logics are encoded semantically as UTP theories. Several fundamental relationships are revealed using theory linking mechanisms, which corroborate results found in the literature, and which have direct applicability to the sound mixing of logics in order to prove facts. The initial development of the fundamental three-valued predicate model, on which the theories are based, is then applied to the novel systems-of-systems specification language CML, in order to reveal proof obligations which bridge a gap that exists between the semantics of CML and the existing semantics of one of its sub-languages, VDM. Finally, a detailed account is given of an envisioned model theory for our proposed structuring, which aims to lift the sentences of the five logics encoded to the second order, allowing them to range over elements of existing UTP theories of computation, such as designs and CSP processes. We explain how this would form a complete treatment of logic interplay that is expressed entirely inside UTP.
Image Antiblurring and Statistic Filter of Feature Space Displacement: Application to Visual Odometry for Outdoor Ground Vehicle

Precise, reliable, and low-cost vehicular localization across a continuous spatiotemporal domain is an important problem in the field of outdoor ground vehicles. This paper proposes a visual odometry algorithm, where an ultrarobust and fast feature-matching scheme is combined with an effective antiblurring frame selection strategy. Our method follows the procedure of finding feature correspondences from consecutive frames and minimizing their reprojection error. The blurred image is a great challenge for localization with a sharp turn or fast movement. So we attempt to mitigate the impact of blur with an image singular value decomposition antiblurring algorithm. Moreover, a statistic filter of feature space displacement and circle matching are proposed to screen or prune potential matching features, so as to remove the outliers caused by mismatching. An evaluation of benchmark dataset KITTI and real outdoor data, with blur, low texture, and illumination change, demonstrates that the proposed ego-motion scheme significantly achieved performance with respect to the other state-of-the-art visual odometry approaches to a certain extent.
Partial page buffering for consumer devices with flash storage

As the capacity of the NAND flash memory increases rapidly, flash storage device needs to maintain larger amount of storage metadata (e.g., mapping information), which necessitates larger amount of hardware resources such as DRAM. Therefore, for storage manufacturers, it is needed to develop a novel scheme that minimizes the amount of storage metadata while preserving the storage performance. One of the effective approaches to cope with the increased storage capacity is enlarging the mapping unit to decrease the amount of mapping information. However, larger mapping unit can greatly increase the number of internal Read-Modify-Write operations which is very costly. In this paper, we propose the `Partial Page Buffering' scheme, in which only partial page write requests are buffered, to reduce the Read-Modify-Write operations in storage devices. The proposed scheme enables us to increase the mapping unit size while preserving the storage performance.
Ansprüche des Auerhuhns an die Landschaft und das Waldbestandsmosaik

GRAF, R. F. & K. BOLLMANN (2008): Western Capercaillie habitat at different spatial scales. Ornithol. Beob. 105: 33–43. Past actions to stop the decline of Western Capercaillie Tetrao urogallus may have failed because they concentrated on improving forest structure in single stands. Important population processes, however, act at much larger scales. We investigated Capercaillie habitat at different spatial and temporal scales, with the main aim to identify the factors that affect Capercaillie populations at the larger scales of forest stand mosaics and entire landscapes. At the landscape scale, we developed a habitat model that identified presently and historically occupied habitats successfully. This model has then been used for spatial priority setting in the Swiss Capercaillie action plan and as a spatial basis for analyzing large-scale (meta-)population dynamics. At the scale of forest stand mosaics, we found a clear positive relationship between Capercaillie population trend and the amount of open forest: the more open forest, the higher the chance for finding a stable population. Therefore, actions for habitat improvement have to be coordinated also at the scale of stand mosaics. Information on forest structure derived from new remote sensing data may help to assess and monitor habitat suitability on large enough areas in the future. Our results emphasize the importance of the large spatial scales for the development of Capercaillie populations. Also, we provide methods and tools that allow to incorporate multi-scale habitat requirements of Capercaillie in conservation concepts.
Event-triggered resilient filtering with stochastic uncertainties and successive packet dropouts via variance-constrained approach

Abstract In this paper, we discuss the event-triggered resilient filtering problem for a class of time-varying systems subject to stochastic uncertainties and successive packet dropouts. The event-triggered mechanism is employed with hope to reduce the communication burden and save network resources. The stochastic uncertainties are considered to describe the modelling errors and the phenomenon of successive packet dropouts is characterized by a random variable obeying the Bernoulli distribution. The aim of the paper is to provide a resilient event-based filtering approach for addressed time-varying systems such that, for all stochastic uncertainties, successive packet dropouts and filter gain perturbation, an optimized upper bound of the filtering error covariance is obtained by designing the filter gain. Finally, simulations are provided to demonstrate the effectiveness of the proposed robust optimal filtering strategy.