Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory for Political Messages: the Role of Inhibition and Prior Attitudes

Retrieval-induced forgetting (RIF) is a phenomenon wherein repeatedly accessing a portion of information causes decreases in memory for related information that is not practiced (Anderson, Bjork, Bjork, 1994). This study applied the retrieval practice paradigm commonly used in cognitive research to persuasive political statements in order to understand the cognitive implications that selective exposure to political messages may have. This study had a mixed design, with retrieval practice agreement (proattitudinal or counterattitudinal), attitude extremity (neutral, moderate, extreme), gender, and practiced issue (affirmative action or gun control) as between subject variables and item practice status (retrieval practiced, non-practiced/shared stance, non-practiced/shared issue, and non-practiced/different issue) as a within-subjects variable. As it was hypothesized that participants' attitudes might moderate RIF effects, attitude strength and extremity for each issue were assessed as well as potential moderating variables. Participants (n=l24) were presented all sentences in the study phase, were given 3 trials of retrieval practice for 5 sentences from one stance, and then a recognition task determined participants' accuracy and response time in distinguishing all original sentences from lures (inversions of those original sentences). Analysis (controlling for attitude strength and retrieval practice accuracy) failed to reveal any signs of RIF for hit or false alarm rates or in reaction times, but attitude extremity did affect recognition: while there was no difference between unpracticed items for neutral participants, moderate participants had lower hit rates for unpracticed control items relative to unpracticed items from the same issue as the practiced items. Males showed more false alarms for unpracticed/same stance items relative to all other items while females showed fewer false alarms for these items. While there was no clear evidence of RIF, this research may contribute to future studies on this topic.
To Twist , or Not to Twist ? A Scientific Attempt to Understand What We Think We Already Know About Sail Trim

The impact of mainsail sheet tension and traveler position on performance has been investigated, particularly under conditions when it is necessary to reduce power. Photographs of the mainsail on a Beneteau First 36.7 under various trim conditions were taken and analyzed to determine sail shape. The resulting shapes were used to create a CFD model, and the aerodynamics forces on the sail plan were determined. The results strongly suggest that for this boat it is more efficient to reduce power by keeping the main sheeted hard and lowering the traveler than by keeping the traveler up and easing the sheet, although a small amount of sheet easing is beneficial. The lift distributions for all sail trim combinations investigated are underloaded near the masthead relative to an elliptic distribution, which means that any additional twist in the main increases the induced drag. The difference in performance is almost entirely attributable to differences in the induced drag.
The Interaction between House Prices and Loans for House Purchase: The Spanish Case

The aim of this paper is to analyse, using a vector error-correction model (VECM), the dynamic interaction between house prices and loans for house purchase in Spain. The results show that both variables are interdependent in the long run: loans for house purchase depend positively on house prices, while house prices adjust when this credit aggregate departs from the level implied by its long-run determinants. In contrast, disequilibria in house prices are corrected only through changes in this variable. As for short-run dynamics, the results show that the two variables have a positive contemporaneous impact on each other, indicating the existence of mutally reinforcing cycles in both variables.
Optimization of a Markerless Gait Analysis Application Aimed at Orthopedic Care for Developing Countries

In this work, a low-budget markerless gait analysis application that is aimed at orthopedic care was built and optimized for use in developing countries and small practices. The application utilizes Microsoft Kinect to detect and track body joints and then calculates nine gait parameters that are important for performing a gait assessment. The measurements of the hip flexion/extension, hip abduction/adduction and knee flexion/extension followed the graphs of standard gait pattern. Also they were consistent and homogeneous among all ten participants. Due to the low tracking accuracy for both the ankle and the foot, measurements of ankle plantar flexion and dorsiflexion didn’t follow the trajectory of the standard graph. Moreover, measurements from participants were sparsely distributed across their average value.
The Role of Cell Adhesion Genes in the Pathogenesis of Medulloblastoma

Medulloblastoma is the most common pediatric brain tumour, yet many of the underlying genetic and epigenetic factors have yet to be discovered. After a genome wide screen of a large cohort of primary medulloblastomas, we discovered that many of the genes within the cell adhesion family are affected by either copy number loss and/or decreased expression unexplained by copy number change. This led us to believe that both genetic and epigenetic factors were affecting this gene family. Through methylationspecific PCR, RT-PCR and high-throughput methylation status analysis, we have concluded that promoter CpG methylation plays a role in the expression of the PCDH10 protein in both medulloblastoma cell lines and primary tumours. Through functional validation with a stable cell line re-expressing PCDH10, I show that cell cycle and proliferation remain unchanged but migration is decreased in cells with PCDH10 reexpression. This suggests that PCDH10 has characteristics of a tumour suppressor in medulloblastoma. iii Acknowledgements I would like to thank Dr. Michael Taylor, my supervisor, for all of his support and advice throughout my graduate studies. I would also like to thank all of the members of the Taylor Lab for teaching me numerous lessons and skills in the lab, a special thank you to Stephen Mack, Paul Northcott, Dr. Adrienne Weeks, and Dr. Livia Garzia. I am very grateful for the supportive environment that has been provided for me in the Brain Tumour Research Centre. Further, I would like to thank my committee members, Dr. Meredith Irwin and Dr. Susan Done, for their helpful advice and support. Finally, I would like to thank my parents, sister and friends for their endless support and encouragement when it was most needed.
Incorporating Judgement in Fan Charts

Within a decision-making group, such as the monetary-policy committee of a central bank,group members often hold differing views about the future of key economic variables. Such differences of opinion can be thought of as reflecting differing sets of judgement. This paper suggests modelling each agent’s judgement as one scenario in a macroeconomic model. Each judgement set has a specific dynamic impact on the system, and accordingly, a particular predictive density – or fan chart – associated with it. A weighted linear combination of the predictive densities yields a final predictive density that correctly reflects the uncertainty perceived by the agents generating the forecast. In a model-based environment, this framework allows judgement to be incorporated into fan charts in a formalised manner.
Extremely high arsenic removal capacity for mesoporous aluminium magnesium oxide composites

Mesoporous aluminium magnesium oxide composites with varying composition (Mg content: 0–100%) and high surface area (118–425 m2 g−1) are synthesized by a facile, low-cost and scalable sol–gel method. The mesostructure and crystallinity are controlled by varying the composition and calcination temperature. The mesopores evolve from hexagonally ordered to wormhole-like in structure with increasing Mg/Al ratio. The mesoporous aluminium magnesium oxide composites are highly efficient adsorbents for removing As(V) and As(III) from water. The mesoporous magnesium oxide shows unprecedentedly high adsorption capacities of 912 mg g−1 for As(V) at pH 3 and 813 mg g−1 for As(III) at pH 7 with a dose of 0.5 g L−1; significantly higher than those of reported adsorbents. Exceptional adsorption capacities for arsenic are retained over a wide pH range, and high selectivity for As(V) is realized even in the presence of co-existing anions. The arsenic adsorption performance correlates to the properties of the composites including the Mg/Al ratio, point of zero charge, crystallinity and mesostructure. The arsenic adsorption mechanism is elucidated. Due to their high surface areas, large pore volumes, tunable mesopore structures and high quantities of accessible hydroxyl groups with strong chemisorption binding affinity to arsenic, as well as extremely high adsorption capacities and selectivity, these mesoporous aluminium magnesium oxides are promising adsorbent candidates for the remediation of arsenic in water.
FAST NMPC OF A DC-DC CONVERTER: AN EXACT NEWTON REAL-TIME ITERATION APPROACH

Abstract This paper presents a Newton optimization technique applied to the Nonlinear Model Predictive Controller (NMPC) for a DC-DC converter. The nonlinear predictor, used in this NMPC algorithm, is approximated by means of a dynamic model which is cubic in the input. This approximation allows the formulation of an explicit MPC law in terms of the states of the model. The proposed controller is tailored for this specific application, taking into account simplicity in the calculation of the control law. The approach followed makes the control law easy to implement and able to deal with the fast response dynamics presented by electronic drivers. The performance of the proposed controller is evaluated under simulation and compared with the response presented by a linear MPC. Although robustness and tracking test are performed over the whole operating range, stability results for the nonlinear MPC are not addresed.
Frame Synchronization Algorithm for LDPC Coded Burst Systems

We present a frame synchronization algorithm for low‐density parity‐check (LDPC) coded burst transmissions, which combines a conventional pilots‐assisted frame synchronization algorithm and a code‐aided algorithm based on the mean magnitude of the soft outputs from the LDPC decoder. With moderate computational complexity, the proposed algorithm is more efficient in bandwidth than conventional pilots‐assisted algorithms. When compared with other code‐aided algorithms, the proposed algorithm offers a better trade‐off between complexity and performance. Simulation results in the case of an 8‐PSK system with (1944, 972) LDPC code show that the proposed algorithm can achieve a performance equivalent to that of the perfect frame synchronization, with a bandwidth efficiency loss of 0.06 dB due to the use of pilot symbols.
Missing pieces to modeling the Arctic-Boreal puzzle

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.
HAVE Experience: An Investigation into VR Empathy for Panic Disorder

This paper presents a Virtual Reality (VR) system that was developed to increase empathy and understanding for panic disorder. The system is designed to give users a heightened awareness of the experience of those symptoms and a deeper, experiential understanding and empathy towards sufferers of panic attacks. VR provides an immersive and controllable experimental environment and serves as a safe dynamic test bed suitable for the study of this topic. The research uses the immersive auditory and visual modalities of VR as contributing factors for a positive empathetic experience, which may be used by medical professionals or those seeking a greater understanding of panic attack symptoms through first hand experience. The main goal is to assess whether the system is capable of imparting users with an enhanced level of understanding of panic attack symptoms leading to a greater sense of empathy. The paper describes the design and implementation of the ‘HAVE Experience’, and an initial experiment conducted with 26 subjects in a controlled environment. Participants were situated in a virtual elevator, where they were exposed to increasing levels of panic disorder symptoms in a controlled manner. The findings indicate that VR is a good medium for conveying empathetic experiences. Moreover the study revealed that an overwhelming majority of participants felt an increased level of empathy and understanding for panic attack sufferers.
Effects of bracing in adolescents with idiopathic scoliosis.

BACKGROUND The role of bracing in patients with adolescent idiopathic scoliosis who are at risk for curve progression and eventual surgery is controversial. METHODS We conducted a multicenter study that included patients with typical indications for bracing due to their age, skeletal immaturity, and degree of scoliosis. Both a randomized cohort and a preference cohort were enrolled. Of 242 patients included in the analysis, 116 were randomly assigned to bracing or observation, and 126 chose between bracing and observation. Patients in the bracing group were instructed to wear the brace at least 18 hours per day. The primary outcomes were curve progression to 50 degrees or more (treatment failure) and skeletal maturity without this degree of curve progression (treatment success). RESULTS The trial was stopped early owing to the efficacy of bracing. In an analysis that included both the randomized and preference cohorts, the rate of treatment success was 72% after bracing, as compared with 48% after observation (propensity-score-adjusted odds ratio for treatment success, 1.93; 95% confidence interval [CI], 1.08 to 3.46). In the intention-to-treat analysis, the rate of treatment success was 75% among patients randomly assigned to bracing, as compared with 42% among those randomly assigned to observation (odds ratio, 4.11; 95% CI, 1.85 to 9.16). There was a significant positive association between hours of brace wear and rate of treatment success (P<0.001). CONCLUSIONS Bracing significantly decreased the progression of high-risk curves to the threshold for surgery in patients with adolescent idiopathic scoliosis. The benefit increased with longer hours of brace wear. (Funded by the National Institute of Arthritis and Musculoskeletal and Skin Diseases and others; BRAIST ClinicalTrials.gov number, NCT00448448.).
Physical and Colorimetric Changes in Eucalyptus grandis Wood after Heat Treatment

Planted forests can meet the world’s demand for wood. In Brazil, eucalypt species are cultivated on a large scale, but their dimensional instability and color limit their use, which makes heat treatment necessary. The aim of this study was to evaluate physical and colorimetric properties of Eucalyptus grandis after heat treatment at 140, 170, 200, and 230 °C for 3 h. Mass loss, shrinkage, equilibrium moisture content, volumetric swelling, fiber saturation point (FSP), and colorimetric parameters were determined; photos were also taken with a scanning electron microscope for all treatments. Heat treatment reduced the wood mass by 0.33 to 10.64% and caused shrinkage by 0.23 to 5.16%. Treatment at 230 C reduced oven dry density. Equilibrium moisture content was 9.40, 9.34, 8.55, 6.55, and 5.05% for control and test samples treated at 140, 170, 200, and 230 °C, respectively. Heat treatment reduced thickness swelling and FSP by 59.65% and 56.31%, respectively. Heat treatment also reduced the L* (lightness), a* (green–red coordinate), and b* (blue–yellow coordinate) values of the wood samples. Heat treatment improved physical properties and darkened the wood; however, the damage observed in scanning electron microscope images could reduce the mechanical properties of wood.
The effect of particle interactions on dynamic light scattering from a dilute suspension

The calculation of dynamic laser-light scattering by dilute suspensions of Brownian particles is reviewed. It is shown that present theories of diffusion can provide approximations for the autocorrelation of the intensity of the scattered light that are only uniformly accurate for correlation times up to order (D0 k2)−l where D0 is the diffusivity of a single particle and k is the scattering wave vector. The meanings of, and connections between, down-gradient, self- and tracer diffusion for both short and long times are established and it is shown how these may be inferred from light-scattering experiments for optically monodisperse and polydisperse systems. For dilute systems, equations giving the time evolution of the intermediate and self-intermediate scattering functions, F(k, t) and Fs(k, t), accurate to first order in the volume concentration of particles are constructed, and are solved for suspensions of hard spheres with and without hydrodynamic interaction. For short and long times (semi-) analytic solutions are given; for intermediate times numerical results are presented. The formal correspondence of the limiting values of the time-dependent solutions with the results of Batchelor (1976, 1983) and others for steady sedimentation in polydisperse systems is established.
On the Inductive Bias of Word-Character-Level Multi-Task Learning for Speech Recognition

End-to-end automatic speech recognition (ASR) commonly transcribes audio signals into sequences of characters while its performance is evaluated by measuring the word-error rate (WER). This suggests that predicting sequences of words directly may be helpful instead. However, training with word-level supervision can be more difficult due to the sparsity of examples per label class. In this paper we analyze an end-to-end ASR model that combines a word-and-character representation in a multi-task learning (MTL) framework. We show that it improves on the WER and study how the word-level model can benefit from character-level supervision by analyzing the learned inductive preference bias of each model component empirically. We find that by adding character-level supervision, the MTL model interpolates between recognizing more frequent words (preferred by the word-level model) and shorter words (preferred by the character-level model).
Clinicopathological Study on the Effects of Momordica charantia on Streptozotocin-Induced Diabetic Wistar Rats

Momordica charantia (MC) a traditional medicine used for the treatment of many disorders was fed to streptozotocin (STZ)-induced diabetic male Wistar rats at 2, 5 and 10% of the standard diet. Rats were then observed for 12 weeks before sacrificed. Immediately, tissues from liver, kidney and pancreas were taken for histopathological examination. Serum samples were analyzed to evaluate liver, kidney and pancreatic functions. In addition, blood samples were collected to analyze hematology parameters. The results of the present study indicate that oral doses of MC at 5% and 10% of the daily diet resulted in alleviation of the pancreatic, hepatic and renal dysfunction induced by diabetes. The improved pancreatic, hepatic and renal functions were judged by histopathological, hematological and serobiochemical parameters. In conclusion, the MC fruits may be used as an antidiabetic herbal medicine.
A Novel “Petaloid” Mutant of Torenia (Torenia fournieri Lind. ex Fourn.) Bears Double Flowers through Insertion of the DNA Transposon Ttf1 into a C-class Floral Homeotic Gene

A double-flowered torenia (Torenia fournieri Lind. ex Fourn.) mutant, “Petaloid”, was obtained from selfed progeny of the “Flecked” mutant, in which the transposition of the DNA transposon Ttf1 is active. A normal torenia flower has a synsepalous calyx consisting of 5 sepals, a synpetalous corolla consisting of 5 petals, 4 distinct stamens, and a syncarpous pistil consisting of 2 carpels. In contrast, a flower of the “Petaloid” mutant has 4 distinct petals converted from stamens, whereas the calyx, corolla, and pistil remain unchanged. The double-flower trait of the “Petaloid” mutant was unstable; some or all of the 4 petals converted from stamens frequently reverted to stamens. Furthermore, most S1 plants obtained from self-pollination of the somatic revertant flower bore only normal single flowers. In petals converted from stamens, expression of the C-class floral homeotic gene T. fournieri FARINELLI (TfFAR) was almost completely inhibited. This inhibition was caused by insertion of Ttf1 into the 2nd intron of TfFAR, whereas reversion of converted petals to stamens was caused by excision of Ttf1 from TfFAR. The clear correspondence of the TfFAR genotype to the floral phenotype suggested that homozygous TfFAR alleles with the Ttf1 insertion caused the mutant phenotype. In contrast, TfFAR was moderately expressed in the pistil of the “Petaloid” mutant, leaving the pistil unchanged. We succeeded in inactivating Ttf1 transposition by cross-pollination between mutant and normal-type plants to genetically separate the transposon Ttf1 from the unidentified factor activating its transposition, which made the “Petaloid” mutation more stable.
Sequential Graphical Lasso for Fault Detection and Isolation

This article proposes a sequential graphical Lasso based approach for monitoring of complex industrial systems. The graphical Lasso is a widely used algorithm to estimate the precision matrix (inverse covariance matrix), which encodes the conditional relationship between pairs of variables given other entities. Based on the estimated precision matrix, a graphical model can be constructed to represent the structured correlation information between process variables. The proposed approach utilizes the graphical model to localize anomalous variables. Different from the conventional graphical Lasso approach, the proposed method considers an additional fusseed lasso term and a similarity term in the objective function and the optimization problem can be solved by the alternative direction method of multiplier (ADMM). Using a moving window approach, the proposed method generates a sequence of sparse Gaussian graphs and a new monitoring statistic based on penalized likelihood ratio and matrix norm is constructed. Once a fault is detected, the problem of fault isolation becomes a graph matching problem and a fault score index is calculated for each variable. The validity of proposed method in fault detection and isolation is illustrated by a typical fault observed in the Tennessee Eastman (TE) process.