Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning to Author Text with textual CBR

Textual reuse is an integral part of textual case-based reasoning (TCBR) which deals with solving new problems by reusing previous similar problem-solving experiences documented as text. We investigate the role of text reuse for text authoring applications that involve feedback or review generation. Generally providing feedback in the form of assigning a rating from a likert scale is far easier compared to articulating explanatory feedback as text. When previous feedback generated about the same or similar objects are maintained as cases, there is opportunity for knowledge reuse. In this paper, we show how compositional and transformational adaptation techniques can be applied once sentences in a given case are aligned to relevant structured attribute values. Three text reuse algorithms are introduced and evaluated on a dataset gathered from online Hotel reviews from TripAdvisor. Here cases consists of both structured sub-rating attributes together with textual feedback. Generally, aligned sentences linked to similar sub-rating values are clustered together and prototypical sentences are then extracted to enable reuse across similar authors. Experiments show a close similarity between our proposed texts and actual human edited review text. We also found that problems with variability in vocabulary are best addressed when prototypes are formulated from larger sets of similar sentences in contrast to smaller sets from local neighbourhoods.
Psychoacoustic Considerations in Surround Sound with Height

This paper presents recent research findings in the psychoacoustics of 3D multichannel sound recording and rendering. The addition of height channels in new reproduction formats such as Auro-3D, Dolby Atmos and 22.2, etc. enhances the perceived spatial impression in reproduction. To achieve optimal acoustic recording and signal processing for such formats, it is first important to understand the fundamental principles of how we perceive sounds reproduced from vertically oriented stereophonic loudspeakers. Recent studies by the authors in this field provide insights into how such principles can be applied for practical 3D recording and upmixing. Topics that are discussed in this paper include the interchannel level and time difference relationships in terms of vertically induced interchannel crosstalk, the effectiveness of the precedence effect in the vertical plane, the aspect of tonal coloration resulting from vertical stereophonic reproduction, the effect of vertical microphone spacing on envelopment, the effect of interchannel decorrelation, and the use of spectral cues for extending vertical image spread.
Skeletal development in the African elephant and ossification timing in placental mammals

We provide here unique data on elephant skeletal ontogeny. We focus on the sequence of cranial and post-cranial ossification events during growth in the African elephant (Loxodonta africana). Previous analyses on ossification sequences in mammals have focused on monotremes, marsupials, boreoeutherian and xenarthran placentals. Here, we add data on ossification sequences in an afrotherian. We use two different methods to quantify sequence heterochrony: the sequence method and event-paring/Parsimov. Compared with other placentals, elephants show late ossifications of the basicranium, manual and pedal phalanges, and early ossifications of the ischium and metacarpals. Moreover, ossification in elephants starts very early and progresses rapidly. Specifically, the elephant exhibits the same percentage of bones showing an ossification centre at the end of the first third of its gestation period as the mouse and hamster have close to birth. Elephants show a number of features of their ossification patterns that differ from those of other placental mammals. The pattern of the initiation of the ossification evident in the African elephant underscores a possible correlation between the timing of ossification onset and gestation time throughout mammals.
Effects of electrolytic lesions of the ventrolateral periaqueductal gray and nucleus raphe magnus on morphine - induced antinociception in the nucleus cuneiformis

Introduction: The nucleus cuneiformis (NCF) and ventrolateral periaqueductal gray (vlPAG), two adjacent areas, mediate the central pain modulation and project to the nucleus raphe magnus (NRM). Methods: This study examined whether the antinociceptive effect of morphine microinjected into the NCF is influenced by inactivation of vlPAG and NRM in rats. Animals were bilaterally microinjected with morphine (2.5 μg/0.3 μl saline) into the NCF. Electrolytic lesions were made in vlPAG (0.1 mA, 45 sec) and/or NRM (1 mA, 30 sec). Tail-flick latency (TFL) was measured at 30, 60, 90 and 120 min after microinjection. Results: The results showed that TFLs are significantly decreased in vlPAG+NRM lesions group at 30 (P < 0.001) and 60 (P < 0.01) min after intra- NCF administration of morphine whereas TFLs did not affect in solely vlPAG lesion animals. Our findings show that concurrent lesions of NRM and vlPAG completely reversed the analgesic effect of morphine in NCF. However, vlPAG do not play a critical role directly in pain modulatory system elicited from NCF, at least at the level of morphine-induced analgesia. Discussion: It can be concluded that its interactive effect in descending pain modulation from NCF to NRM should not be neglected.
Identification of a novel sequence type of Escherichia coli as the causative agent of pyelonephritis and bloodstream infection

Introduction: Globally, extra-intestinal pathogenic Escherichia coli are one of the predominant causative agents of bacteraemia. Case presentation: This case report outlines a presentation of community-acquired pyelonephritis and secondary bloodstream infection in an 81-year-old man. Laboratory investigations revealed that the causative isolate was a multi-drug-resistant E. coli of a novel multi-locus sequence type. This sequence type (ST) was designated ST-458 and was most closely related to the globally prevalent ST-131 lineage. Conclusion: This is the first report of a novel E. coli ST, ST-458, which caused pyelonephritis and bacteraemia.
Profit Sharing and Monitoring in Partnerships

We consider partnerships among risk-averse professionals endowed with (i) a risky and personally-costly production technology and (ii) a personally-costly monitoring technology providing contractible noisy signals about partners’ productive efforts. Partners shirk both production and monitoring tasks because efforts are unobservable. We characterize optimal partnership size, profit shares and incentive payments when every partner performs the same tasks, and show that medium-sized partnerships are dominated by either smaller or larger partnerships. Prohibiting some partners from monitoring increases the incentives for others to monitor. We illustrate how task assignments and incentives interact, leading to improvements in partner welfare.
Evaluation of Finnish Diabetes Risk Score in Screening Undiagnosed Diabetes and Prediabetes among U.S. Adults by Gender and Race: NHANES 1999-2010

Objective To evaluate the performance of Finnish Diabetes Risk Score (FINDRISC) in detecting undiagnosed diabetes and prediabetes among U.S. adults by gender and race. Methods This cross-sectional analysis included participants (aged ≥20 years) from the National Health and Nutrition Examination Survey (NHANES) 1999–2010. Sensitivity, specificity, area under the receiver operating characteristic (ROC) curve and the optimal cutoff points for identifying undiagnosed diabetes and prediabetes were calculated for FINDRISC by gender and race/ethnicity. Results Among the 20,633 adults (≥20 years), 49.8% were women and 53.0% were non-Hispanic White. The prevalence of undiagnosed diabetes and prediabetes was 4.1% and 35.6%, respectively. FINDRISC was positively associated with the prevalence of diabetes (OR = 1.48 for 1 unit increase, p<0.001) and prediabetes (OR = 1.15 for 1 unit increase, p<0.001). The area under ROC for detecting undiagnosed diabetes was 0.75 for total population, 0.74 for men and 0.78 for women (p = 0.04); 0.76 for White, 0.76 for Black and 0.72 for Hispanics (p = 0.03 for White vs. Hispanics). The area under ROC for detecting prediabetes was 0.67 for total population, 0.66 for men and 0.70 for women (p<0.001); 0.68 for White, 0.67 for Black and 0.65 for Hispanics (p<0.001 for White vs. Hispanics). The optimal cutoff point was 10 (sensitivity = 0.75) for men and 12 (sensitivity = 0.72) for women for detecting undiagnosed diabetes; 9 (sensitivity = 0.61) for men and 10 (sensitivity = 0.69) for women for detecting prediabetes. Conclusions FINDRISC is a simple and non-invasive screening tool to identify individuals at high risk for diabetes in the U.S. adults.
Analysis of the mushy region in conduction- convection problems with change of phase

A conduction-convection problem with change of phase is studied, where convective motion of the liquid aects the change of phase. The mushy region is the portion of the system to which temperature and enthalpy do not assign a phase, solid or liquid. In this paper we show that the enthalpy density remains constant in time almost everywhere in the mushy region.
Role of the CNS Melanocortin System in the Response to Overfeeding

The voluntary suppression of food intake that accompanies involuntary overfeeding is an effective regulatory response to positive energy balance. Because the pro-opiomelanocortin (POMC)-derived melanocortin system in the hypothalamus promotes anorexia and weight loss and is an important mediator of energy regulation, we hypothesized that it may contribute to the hypophagic response to overfeeding. Two groups of rats were overfed to 105 and 116% of control body weight via a gastric catheter. In the first group, in situhybridization was used to measure POMC gene expression in the rostral arcuate (ARC). Overfeeding increased POMC mRNA in the ARC by 180% relative to levels in control rats. For rats in the second group, the overfeeding was stopped, and they were infused intracerebroventricularly with SHU9119 (SHU), a melanocortin (MC) antagonist at the MC3 and MC4 receptor, or vehicle. Although SHU (0.1 nmol) had no effect on food intake of control rats, intake of overfed rats increased by 265% relative to CSF-treated controls. This complete reversal of regulatory hypophagia not only maintained but actually increased the already elevated weight of overfed rats, whereas CSF-treated overfed rats lost weight. These results indicate that CNS MCs mediate hypophagic signaling in response to involuntary overfeeding and support the hypothesis that MCs are important in the central control of energy homeostasis.
Using Panel Data to Easily Estimate Hedonic Demand Functions

The hedonics literature has often asserted that if one were able to observe the same individual make multiple purchase decisions, one could recover rich estimates of preference heterogeneity for a given amenity. In particular, in the face of a changing price schedule, observing each individual twice is sufficient to recover a linear demand function separately for each individual, with no additional restrictions. Constructing a rich panel data set of buyers, we recover the full distribution of demand functions for clean air in the Bay Area of California. First, we find that estimating the full demand function, rather than simply recovering a local estimate of marginal willingness to pay, is important. Second, we find evidence of considerable heterogeneity, which is important from a policy perspective; our data-driven estimates of the welfare effects associated with a nonmarginal change in air quality differ substantially from those recovered using the existing approaches to welfare estimation.
Seeing the Big Picture: Size Perception Is More Context Sensitive in the Presence of Others

This paper tests the hypothesis that social presence influences size perception by increasing context sensitivity. Consistent with Allport’s prediction, we expected to find greater context sensitivity in participants who perform a visual task in the presence of other people (i.e., in co-action) than in participants who perform the task in isolation. Supporting this hypothesis, participants performing an Ebbinghaus illusion-based task in co-action showed greater size illusions than those performing the task in isolation. Specifically, participants in a social context had greater difficulty perceiving the correct size of a target circle and ignoring its surroundings. Analyses of delta plot functions suggest a mechanism of interference monitoring, since that when individuals take longer to respond, they are better able to ignore the surrounding circles. However, this type of monitoring interference was not moderated by social presence. We discuss how this lack of moderation might be the reason why the impact of social presence on context sensitivity is able to be detected in tasks such as the Ebbinghaus illusion.
The construction of general terms for shape patterns: strategies adopted by children attending Fourth class in two Irish primary schools

Generalisation is considered by many to be a highly significant component of algebraic thinking (Carpenter & Levi, 2000; Kaput et al., 2008). In particular, constructing general terms for shape patterns supports children in reasoning algebraically about covariance and rates of change (Rivera & Becker, 2011). Generalisation is not mentioned within the current Irish Primary School Mathematics Curriculum, and shape patterns are not presented as learning activities, beyond simple repeating patterns explored with very young children (Government of Ireland, 1999). This thesis reports on a research study that explored the strategies Irish children adopted in seeking to construct general terms for shape patterns. Within the context of task-based group interviews, patterning tasks were presented to groups of three or four children (aged nine or ten years old), where the children were asked to describe and extend the patterns, and to consider near and far generalisations. Following the interviews I analysed the strategies that children used to generalise from the patterns, drawing from the work of Lannin (2005) and Rivera and Becker (2011). Taking a hermeneutic phenomenological approach, I included identification and analysis of factors that contributed to children’s strategy choices, which included explicit, recursive, numerical and figural approaches. Findings evidence the potential of children to respond in complex and sophisticated ways to novel tasks, when rich engagement with the mathematics was facilitated through the context of a task-based group interview. The research study demonstrates the necessity for conceptualising children’s thinking as multi-faceted whereby observations of relationships within patterns interact with attention to numerical and figural aspects. In addition, evidence is presented to support the contention that observations of structure exist along a continuum from numerical to figural. The study highlights the potential of task-based group interviewing coupled with hermeneutic phenomenological analysis in facilitating in-depth research into children’s emerging mathematical thinking.
Rigid-Object Water-Entry Impact Dynamics: Finite-Element/Smoothed Particle Hydrodynamics Modeling and Experimental Validation

A numerical study on the dynamic response of a generic rigid water-landing object (WLO) during water impact is presented in this paper. The effect of this impact is often prominent in the design phase of the re-entry project to determine the maximum force for material strength determination to ensure structural and equipment integrity, human safety and comfort. The predictive capability of the explicit finite-element (FE) arbitrary Lagrangian-Eulerian (ALE) and smoothed particle hydrodynamics (SPH) methods of a state-of-the-art nonlinear dynamic finite-element code for simulation of coupled dynamic fluid structure interaction (FSI) responses of the splashdown event of a WLO were evaluated. The numerical predictions are first validated with experimental data for maximum impact accelerations and then used to supplement experimental drop tests to establish trends over a wide range of conditions including variations in vertical velocity, entry angle, and object weight. The numerical results show that the fully coupled FSI models can capture the water-impact response accurately for all range of drop tests considered, and the impact acceleration varies practically linearly with increase in drop height. In view of the good comparison between the experimental and numerical simulations, both models can readily be employed for parametric studies and for studying the prototype splashdown under more realistic field conditions in the oceans.
Data dependent energy modelling: A worst case perspective

Energy consumption of the software running on a device has become increasingly important as a growing number of devices rely on batteries or other limited sources of power. Of particular interest is constructing a bounded measure of the energy consumption — the maximum energy a program could consume for any input given to it. We explore the effect of different data on the energy consumption of individual instructions, instruction sequences and full programs. The whole program energy consumption of two benchmarks is analysed over random and hand-crafted data, and maximized with genetic algorithms for two embedded processors. We find that the worst case can be predicted from the distribution created by the random data, however, hand-crafted data can often achieve lower energy consumption. A model is constructed that allows the worst case energy for a sequence of instructions to be predicted. This is based on the observation that the transition between instructions is important and thus is not a single energy cost — it is a distribution dependent on the input and output values of the two consecutive instructions. We characterise the transition distributions for several instructions in the AVR instruction set, and show that this gives a useful upper bound on the energy consumption. We explore the effect that the transfer function of the instruction has on the data, and give an example which leads to a bimodal energy distribution. Finally, we conclude that a probabilistic approach is appropriate for estimating the energy consumption of programs.
The Relationship between Post-Traumatic Stress Disorder and Self-Esteem along with the Importance of Support for Children

Post-Traumatic Stress Disorder (PTSD) is widely known in our society. The symptoms of PTSD are particularly believed to occur predominantly in children. We believe that Yogo teachers, who play a role in maintaining and promoting the health of children, are expected to provide appropriate support for children with a tendency for PTSD. In this study, we investigated the tendency for PTSD in students at University, as well as self-esteem related to depression and anxiety. Furthermore, we clarified the relationship between PTSD and self-esteem and examined the support provided by Yogo teachers. As a result, it was found that the higher the tendency for PTSD, the lower the self-esteem. We believe that the onset of PTSD causes a decline in memory ability and attentional function, which interferes with one’s life and leads to self-denial, resulting in a decline in self-esteem among those with a high tendency for PTSD. These results suggest that Yogo teachers should provide support to prevent the onset of PTSD in child students due to accidents, incidents, natural disasters, etc., as well as support to prevent the decline in self-esteem associated with the onset of PTSD.
Psychological Stress-Induced, IDO1-Dependent Tryptophan Catabolism: Implications on Immunosuppression in Mice and Humans

It is increasingly recognized that psychological stress influences inflammatory responses and mood. Here, we investigated whether psychological stress (combined acoustic and restraint stress) activates the tryptophan (Trp) catabolizing enzyme indoleamine 2,3-dioxygenase 1(IDO1) and thereby alters the immune homeostasis and behavior in mice. We measured IDO1 mRNA expression and plasma levels of Trp catabolites after a single 2-h stress session and in repeatedly stressed (4.5-days stress, 2-h twice a day) naïve BALB/c mice. A role of cytokines in acute stress-induced IDO1 activation was studied after IFNγ and TNFα blockade and in IDO1−/− mice. RU486 and 1-Methyl-L-tryptophan (1-MT) were used to study role of glucocorticoids and IDO1 on Trp depletion in altering the immune and behavioral response in repeatedly stressed animals. Clinical relevance was addressed by analyzing IDO1 activity in patients expecting abdominal surgery. Acute stress increased the IDO1 mRNA expression in brain, lung, spleen and Peyer's patches (max. 14.1±4.9-fold in brain 6-h after stress) and resulted in a transient depletion of Trp (−25.2±6.6%) and serotonin (−27.3±4.6%) from the plasma measured 6-h after stress while kynurenine levels increased 6-h later (11.2±9.3%). IDO1 mRNA up-regulation was blocked by anti-TNFα and anti-IFNγ treatment. Continuous IDO1 blockade by 1-MT but not RU486 treatment normalized the anti-bacterial defense and attenuated increased IL-10 inducibility in splenocytes after repeated stress as it reduced the loss of body weight and behavioral alterations. Moreover, kynurenic acid which remained increased in 1-MT treated repeatedly stressed mice was identified to reduce the TNFα inducibility of splenocytes in vitro and in vivo. Thus, psychological stress stimulates cytokine-driven IDO1 activation and Trp depletion which seems to have a central role for developing stress-induced immunosuppression and behavioral alteration. Since patients showed Trp catabolism already prior to surgery, IDO is also a possible target enzyme for humans modulating immune homeostasis and mood.
Distributed and stream data mining algorithms for frequent pattern discovery

The use of distributed systems is continuously spreading in several applications domains. Extracting valuable knowledge from raw data produced by distributed parties, in order to produce a unified global model, may presents various challenges related to either the huge amount of managed data or their physical location and ownership. In case data are continuously produced (stream) and their analysis is required to be performed in real time, communication costs and resource usage are issues that require careful attention in order to run computation in the optimal location. In this thesis, we examine in details the problems related to the Frequent Pattern Mining (FPM) in distributed and stream data and present a general framework for adapting an exact FPM algorithm to a distributed or streaming context. The FPM problems we consider are Frequent Itemset Mining (FIM), and Frequent Sequences Mining (FSM). In the first case, the input data are sets of items and the frequent patterns are those included in a user-specified number of input set. The second one consists in finding frequent sequential patterns in a database of time-stamped events. Since the proposed framework uses (exact) frequent pattern mining algorithms as the building block of the approximate distributed/stream algorithms, we will also describe two efficient algorithms for FIM and FSM: DCI, introduced by Orlando et al., and CCSM, which is one of the original contributions of this thesis. The resulting algorithms for distributed and stream FIM have been tested with real world and synthetic datasets, and are able to find efficiently a good approximation of the exact results and scale gracefully. The framework for FSM is almost identical, but has not been tested yet. The few differences are highlighted in the conclusion chapter.