Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing Risk in Community Care of Older People: Perspectives from the Frontline

Abstract Since the mid-1980s, Australian governments have focused on expanding community and home-based services for older people. This has led to increased levels of dependency, vulnerability, and complexity to be managed in the community. Consequently, aged care services have had to develop mechanisms for regulating and managing these increased risks, and risk management has become more central to the practices of professional workers in this field. This paper reports on some findings from a large-scale study that explores the way risk management policies have been translated into practice by community-based services in Victoria, Australia. Drawing on interviews with 18 frontline and management professionals employed in community aged care, we found that these workers were wrestling with a diverse and new range of institutional risks beyond those encountered in the actual delivery of frontline care. We found that these workers experienced “risk” in four different contexts, which often created demands for contradictory or conflicting responses. Here we examine these “contexts of risk practice”: professional workers' relationships with their clients, relationships with other service providers, the unregulated nature of the home as a work environment, and community expectations about the management of risk. Despite tensions that frequently arose, workers expressed strong professional commitments to their clients and were motivated to find positive resolutions amid competing interests. We conclude that tensions experienced by workers were embedded in the structural dimensions of institutional relationships and the systematic absence of shared understandings of “acceptable” risks in the community care of older people, rather than in the failure of professional agency.
Fashion Matters: La Sape and Vestimentary Codes in Transnational Contexts and Urban Diasporas

The focus of this essay is provided by a discussion of the symbiotic relationship between Paris as a narrative construct in the minds of its former African colonial subjects, and the complex manner in which urban spaces and narrative productions are simultaneously reconfigured according to the cultural, political, and sociological agendas of cultural practitioners. Using a theoretical context inspired by a transnational understanding of performance and identity, the manner in which dress codes (the phenomenon of "la sape") have marked the experiences of the Congolese diasporas in France are explored as they relate to the 1998 novel by Alain Mabanckou, Bleu-Blanc-Rouge.
A NonStop kernel

The Tandem NonStop System is a fault-tolerant [1], expandable, and distributed computer system designed expressly for online transaction processing. This paper describes the key primitives of the kernel of the operating system. The first section describes the basic hardware building blocks and introduces their software analogs: processes and messages. Using these primitives, a mechanism that allows fault-tolerant resource access, the process-pair, is described. The paper concludes with some observations on this type of system structure and on actual use of the system.
High-resolution studies of massive star-forming regions

We summarize the status of our program of near-infrared adaptive optics observations of ultracompact HII regions. By means of selected results we demonstrate the usefulness of this technique for disentangling the complexity of massive star-forming regions. The primary scientific aims of our study are the identification of the ionizing stars, the characterization of the stellar population, the clarification of the role of dust for the excitation of the HII region and, last but not least, the search for circumstellar disks surrounding high-mass stars. We present results obtained by adaptive optics observations and additional measurements for G45.45+0.06, G5.89-0.39, and G309.92+0.48 to illustrate our scientific objectives.
Use Data Mining to Improve Student Retention in Higher Education - A Case Study

Data mining combines machine learning, statistics and visualization techniques to discover and extract knowledge. One of the biggest challenges that higher education faces is to improve student retention (National Audition Office, 2007). Student retention has become an indication of academic performance and enrolment management. Our project uses data mining and natural language processing technologies to monitor student, analyze student academic behaviour and provide a basis for efficient intervention strategies. Our aim is to identify potential problems as early as possible and to follow up with intervention options to enhance student retention. In this paper we discuss how data mining can help spot students ‘at risk’, evaluate the course or module suitability, and tailor the interventions to increase student retention.
Toward optimal allocation of location dependent tasks in crowdsensing

Crowdsensing offers an efficient approach to meet the demand in large scale sensing applications. In crowdsensing, it is of great interest to find the optimal task allocation, which is challenging since sensing tasks with different requirements of quality of sensing are typically associated with specific locations and mobile users are constrained by time budgets. We show that the allocation problem is NP hard. We then focus on approximation algorithms, and devise an efficient local ratio based algorithm (LRBA). Our analysis shows that the approximation ratio of the aggregate rewards obtained by the optimal allocation to those by LRBA is 5. This reveals that LRBA is efficient, since a lower (but not tight) bound on the approximation ratio is 4. We also discuss about how to decide the fair prices of sensing tasks to provide incentives since mobile users tend to decline the tasks with low incentives. We design a pricing mechanism based on bargaining theory, in which the price of each task is determined by the performing cost and market demand (i.e., the number of mobile users who intend to perform the task). Extensive simulation results are provided to demonstrate the advantages of our proposed scheme.
The Nature and Use of Formal Control Systems for Management Control and Strategy Implementation

Management control research from organization theory, accounting, and business policy is reviewed; and a two-stage qualitative study of management control systems (MCSs) used in business organizations is reported. The study identified four MCS components used at the middle management level: budget, policies and procedures, performance appraisal system, and statistical reports. Each MCS component played a role during the control cycle of target setting, monitoring, and corrective feedback. The findings were used to propose two models: One model links the MCS to business level strategy implementation, and the other defines primary and secondary roles for MCS components in the management control process.
Biotechnology and Bioengineering

Funding information European Union Framework Program 7, Grant/Award Number: FP7‐ 613793; Portuguese Foundation for Science and Technology, Grant/Award Numbers: NORTE‐ 01, POCI‐01‐0145‐FEDER‐006684, UID/BIO/ 04469 Abstract In recent years microorganisms have been engineered towards synthesizing interesting plant polyphenols such as flavonoids and stilbenes from glucose. Currently, the low endogenous supply of malonyl‐CoA, indispensable for plant polyphenol synthesis, impedes high product titers. Usually, limited malonyl‐CoA availability during plant polyphenol production is avoided by supplementing fatty acid synthesis‐inhibiting antibiotics such as cerulenin, which are known to increase the intracellular malonyl‐ CoA pool as a side effect. Motivated by the goal of microbial polyphenol synthesis being independent of such expensive additives, we used rational metabolic engineering approaches to modulate regulation of fatty acid synthesis and flux into the tricarboxylic acid cycle (TCA cycle) in Corynebacterium glutamicum strains capable of flavonoid and stilbene synthesis. Initial experiments showed that sole overexpression of genes coding for the native malonyl‐CoA‐forming acetyl‐CoA carboxylase is not sufficient for increasing polyphenol production in C. glutamicum. Hence, the intracellular acetyl‐CoA availability was also increased by reducing the flux into the TCA cycle through reduction of citrate synthase activity. In defined cultivation medium, the constructed C. glutamicum strains accumulated 24mg·L (0.088mM) naringenin or 112mg·L (0.49mM) resveratrol from glucose without supplementation of phenylpropanoid precursor molecules or any inhibitors of fatty acid synthesis.
An Inductive Approach to Modeling Affective Reasoning in Interactive Synthetic Agents

MCQUIGGAN, SCOTT W. An Inductive Approach to Modeling Affective Reasoning in Interactive Synthetic Agents (Under the direction of James C. Lester). Recent years have witnessed significant progress on synthetic agents. With a broad range of applications in education, training, and entertainment, foundational work on synthetic agents has yielded expressive models of embodied cognition and behavior that support rich interaction. Complementing advances in cognition and behavior, affective reasoning has begun to play a central role in synthetic agents. A key challenge posed by affective reasoning in synthetic agents is devising empirically informed models of affect that enable synthetic agents to accurately respond in social situations. This thesis presents an inductive affective modeling paradigm for learning models of affect by observing human-human social interactions. First, in training sessions, one trainer directs a synthetic agent to perform a sequence of tasks while another trainer manipulates a synthetic agent’s affective states to produce appropriate behaviors. These include spoken language, gestural behaviors, and posture. Second, the model generator tracks observable situational attributes pertaining to locational, intentional, and temporal information to induce a model of affect. Finally, at runtime, a synthetic agent applies the model by tracking precisely the same observable attributes and using them to drive situation-appropriate behaviors. The inductive affective reasoning framework has been implemented in a model generator that induces models of empathy for synthetic agents. A 31-subject experiment indicates that a data-driven approach can generate models of empathy that are both efficient and accurate. In the experiment, naïve Bayes affective classifiers and decision tree affective classifiers were learned to model situational assessment (when to perform an affective behavior) and interpretation (which affective behavior to select). Results suggest that inductively generated models satisfy the real-time performance requirements of interactive environments and can provide the basis for empirically informed affective reasoning in synthetic agents. An Inductive Approach to Modeling Affective Reasoning in Interactive Synthetic Agents
X-Rays from the Nearby Solitary Millisecond Pulsar PSR J0030+0451: The Final ROSAT Observations

We report on X-ray observations of the solitary 4.8 ms pulsar PSR J0030+0451. The pulsar was one of the last targets observed in 1998 December by the ROSAT PSPC. X-ray pulses are detected on a 4.5 σ level and make the source the 11th millisecond pulsar detected in the X-ray domain. The pulsed fraction is found to be 69% ± 18%. The X-ray pulse profile is characterized by two narrow peaks that match the gross pulse profile observed at 1.4 GHz. Assuming a Crab-like spectrum the X-ray flux is in the range fX = (2-3) × 10-13 ergs s-1 cm-2 (0.1-2.4 keV), implying an X-ray efficiency of LX/ ~ (0.5-5) × 10-3(d/0.23 kpc)2.
A Person by Situation Account of Motivated System Defense

Three studies demonstrate how individual differences in confidence in the sociopolitical system interact with threats that engage the system justification motive to produce system defense. Following threat, participants low, but not high, in system confidence increasingly defended the system, by rejecting system change (Study 1) and preferring domestic over international products (Studies 2 and 3). These findings contribute to the literature on system justification theory in two ways: First, they expand scholars' understanding of when and for whom system-level threats instigate motivational processes of system defense, and, second, they demonstrate that the system justification motive is not merely another example of worldview verification phenomena but instead involves a specific goal to defend the status quo.
Clostridium difficile toxin-induced inflammation and intestinal injury are mediated by the inflammasome.

BACKGROUND & AIMS Clostridium difficile-associated disease (CDAD) is the leading cause of nosocomial diarrhea in the United States. C difficile toxins TcdA and TcdB breach the intestinal barrier and trigger mucosal inflammation and intestinal damage. The inflammasome is an intracellular danger sensor of the innate immune system. In the present study, we hypothesize that TcdA and TcdB trigger inflammasome-dependent interleukin (IL)-1beta production, which contributes to the pathogenesis of CDAD. METHODS Macrophages exposed to TcdA and TcdB were assessed for IL-1beta production, an indication of inflammasome activation. Macrophages deficient in components of the inflammasome were also assessed. Truncated/mutated forms of TcdB were assessed for their ability to activate the inflammasome. The role of inflammasome signaling in vivo was assessed in ASC-deficient and IL-1 receptor antagonist-treated mice. RESULTS TcdA and TcdB triggered inflammasome activation and IL-1beta secretion in macrophages and human mucosal biopsy specimens. Deletion of Nlrp3 decreased, whereas deletion of ASC completely abolished, toxin-induced IL-1beta release. TcdB-induced IL-1beta release required recognition of the full-length toxin but not its enzymatic function. In vivo, deletion of ASC significantly reduced toxin-induced inflammation and damage, an effect that was mimicked by pretreatment with the IL-1 receptor antagonist anakinra. CONCLUSIONS TcdA and TcdB trigger IL-1beta release by activating an ASC-containing inflammasome, a response that contributes to toxin-induced inflammation and damage in vivo. Pretreating mice with the IL-1 receptor antagonist anakinra afforded the same level of protection that was observed in ASC-/- mice. These data suggest that targeting inflammasome or IL-1beta signaling may represent new therapeutic targets in the treatment of CDAD.
Perceptions of Organizational Stress Among U.S. Military Officers in Germany

This article reports the results of an exploratory study of perceptions of organizational stress among U.S. military officers stationed in Germany. The sample data were analyzed by item comparisons, factor analysis, and cluster analysis. Work load, work design, job qualifications, performance evaluation, and organization structure were identified as stress precipitators. The cluster analysis yielded three groups of individuals with different stress-frequency patterns. These groups were labeled achievement-centered, organization-centered, and self-actualization-centered. Directions for future research are discussed within the context of an increasing rate of change in military organizations.
An Fmri Study of Emotional Face Processing in Adolescent Major Depression in Partial Fulfillment of the Requirements for the Degree of Master of Arts Emotion Face Processing in Adolescent Depression Emotion Face Processing in Adolescent Depression

i Acknowledgments I would like to acknowledge several people who helped make this project possible. A special thank you to Drs. Bonnie Klimes-Dougan and Katie Cullen for allowing me to explore their adolescent neuroimaging data set and for providing support throughout this endeavor. I would also like to thank Ruskin Hunt for his invaluable guidance in the area of neuroimaging statistical analysis and Emily Noack for her assistance preparing the literature review. Finally, thank you to Drs. Scott Crow, Bonnie Klimes-Dougan, and Monica Luciana for taking the time to serve as members of my final exam committee. Abstract OBJECTIVE: Major Depressive Disorder (MDD) is a serious, often chronic illness associated with significant impairment and suicide. MDD often begins during adolescence when brain areas that regulate emotion processing are still maturing. To expand upon our limited understanding of the neurobiological underpinnings of MDD early on in development, this study examined function within fronto-limbic neural circuits in response to an emotional faces task among depressed adolescents and healthy controls (HC) using functional magnetic resonance imaging (fMRI). METHOD: 34 adolescents with MDD (12 medicated, 22 unmedicated) and 16 healthy age and gender matched controls completed an emotional faces task where BOLD response was examined when viewing happy and fearful faces (presented in a block design) during fMRI. Scanning was completed using a 3.0 Tesla scanner. Data preprocessing and analysis was carried out using FEAT in FSL. Whole brain group level analyses were conducted using a mixed-effects model (FLAME) with cluster-wise significant testing (min Z=2.32; cluster significance = p<0.05, corrected). RESULTS: In response to viewing fearful versus happy faces, MDD showed reduced activation in areas of the right thalamus, right insula, and right hippocampus compared to HC. CONCLUSION: Results suggest that emotion processing in adolescent MDD is associated with abnormalities in subcortical and paralimbic brain regions within the broader fronto-limbic neural network. It is possible that these findings reflect deficits in depressed adolescents' ability to elicit cognitive control from higher cortical regions and to accurately respond to and process the emotional significance of fearful stimuli.
Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo-presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real-presence data with forest layer are better predictors than those from pseudo-presence data. Using real-presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.
Molecular Determinants of T Cell Epitope Recognition to the Common Timothy Grass Allergen

We investigated the molecular determinants of allergen-derived T cell epitopes in humans utilizing the Phleum pratense (Timothy grass) allergens (Phl p). PBMCs from allergic individuals were tested in ELISPOT assays with overlapping peptides spanning known Phl p allergens. A total of 43 distinct antigenic regions were recognized, illustrating the large breadth of grass-specific T cell epitopes. Th2 cytokines (as represented by IL-5) were predominant, whereas IFN-γ, IL-10, and IL-17 were detected less frequently. Responses from specific immunotherapy treatment individuals were weaker and less consistent, yet similar in epitope specificity and cytokine pattern to allergic donors, whereas nonallergic individuals were essentially nonreactive. Despite the large breadth of recognition, nine dominant antigenic regions were defined, each recognized by multiple donors, accounting for 51% of the total response. Multiple HLA molecules and loci restricted the dominant regions, and the immunodominant epitopes could be predicted using bioinformatic algorithms specific for 23 common HLA-DR, DP, and DQ molecules. Immunodominance was also apparent at the Phl p Ag level. It was found that 52, 19, and 14% of the total response was directed to Phl p 5, 1, and 3, respectively. Interestingly, little or no correlation between Phl p-specific IgE levels and T cell responses was found. Thus, certain intrinsic features of the allergen protein might influence immunogenicity at the level of T cell reactivity. Consistent with this notion, different Phl p Ags were associated with distinct patterns of IL-5, IFN-γ, IL-10, and IL-17 production.
The Narrative Explorer

The Narrative Explorer is an interactive web application for text visualization and analysis. The texts are visualized in the Narrative Explorer in two ways. The affective content of the text, quantified as the sentiment polarity of the sentences, is represented by a bar graph timeline. The co-occurrence of characters or concepts in the text is represented by a chord diagram. These visual representations are linked and can be examined interactively. The Narrative Explorer allows the user to upload and visualize a new text or select an existing text from the database for visualization. The Narrative Explorer is intended for a variety of audiences, from humanities scholars and students engaged in exploratory text analysis to non-specialist readers interested in an analytical perspective
Defining Energy Consumption Plans for Data Querying Processes

During the last few years, we have been witnessing a significant increase in research about the development and production of hardware and software components with low levels of energy consumption. Today, energy consumption is one of the most critical issues in the area of information technologies and communication. One of the fractions in which this concern is most evident is in the management of database systems, with particular emphasis on those commonly designated as data centers. On these systems daily run a large amount of data querying processes, monitored and controlled by high sophisticated database management systems, which are responsible to establish efficient processing plans to support them. Using the information provided by a querying execution plan, especially the one related to the operators they used to perform database operations, we designed and developed an alternative method to define energy consumption plans for database queries. In this paper we present how such method works on the estimation of the energy consumption of each database operator integrated in the execution plan of a query at compile time. With it, we build up its corresponding energy consumption plan for executing the query, taking into consideration as well the characteristics of the computational platforms used for that.