Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Social Media Matter? Investigating the Effect of Social Media Features on Consumer Attitudes

ABSTRACT The purpose of this study is to explore the impact of social media's features (i.e., entertainment, usefulness, informativeness and irritation) toward consumers’ attitude toward the brand. Subsequently, this study explores the impact of this attitude toward consumers’ brand loyalty, brand awareness and purchase intention. Data for this study was collected through a large public university in Australia. Paper surveys were distributed to students, their friends and members of their immediate families (N = 724). The findings show that entertainment feature has the strongest impact on consumers’ attitude toward the brand's social media use, followed by informativeness, usefulness and finally, irritation. Consumers’ attitude toward a brand's social media strongly influences consumer loyalty, awareness and purchase intention. The findings of this research provide some insights into the impact of different features of social media which will be useful for practitioners and academics interested in social media.
Dynamics of Disease Progression and Gastrostomy Tube Placement in Children and Adolescents with Cystic Fibrosis: Application of Joint Models for Longitudinal and Time-to-Event Data.

BACKGROUND Previous small-sample studies have examined the effect of gastrostomy (g-) tube placement on weight, height, and lung function in adolescent patients with cystic fibrosis (CF), but there are no RCTs to date reporting efficacy. The goal of this study was to implement a dynamic prediction model to 1) understand the role of rapid lung function decline in g-tube placement in real-world clinical settings; 2) provide a prognostic tool with the potential to aid clinicians in optimizing the timing of g-tube placement, in relation to rate of lung function decline and current nutrition status. METHODS A dynamic prediction model was developed, utilizing data on patients 6-21 years of age from the Cystic Fibrosis Foundation Patient Registry (1997-2013). A joint model was implemented, which coupled a semiparametric mixed model to characterize rapid lung function decline with a time-to-event model to identify risk factors for g-tube initiation. RESULTS The 4,034 individuals (21.3%) who underwent g-tube placement during adolescence or young adulthood had poorer nutrition and lung function at baseline and initially had increased rates of pancreatic enzyme use, infection and gastroesophageal reflux disease, compared to those who did not receive g-tubes; these associations changed over follow up. Rapid lung function decline was associated with increased risk of g-tube supplementation. CONCLUSIONS By jointly modeling longitudinal patterns of lung function decline with g-tube delivery, it is possible to construct prognostic aids to evaluate treatment delivery in relation to the onset of rapid lung function decline and other important clinical markers. These algorithms have the potential to enable more effective monitoring of disease progression and promote more timely treatment delivery.
Tilted or parallel implant placement in the completely edentulous mandible? A three-dimensional finite element analysis.

PURPOSE According to the so-called All-on-Four protocol, four dental implants are placed in the interforaminal region of the edentulous mandible to support full-arch fixed prostheses. In this design, the posterior implants are tilted distally to a maximum of 45 degrees. The purpose of this finite element study was to evaluate the stress concentration in peri-implant bone during two loading conditions and to compare this design with another design in which the four implants are placed parallel to each other and perpendicular to the occlusal plane. MATERIALS AND METHODS Three-dimensional finite element models consisted of mandibular bone, four dental implants inserted in two different configurations-with the distal implants tilted (model A) or four parallel implants (model S)-and hybrid superstructures. Two loading conditions (178 N/central incisors or 300 N/left first molar) were considered, and von Mises stress values were determined. RESULTS During anterior loading, higher stress concentrations were detected in the peri-implant bone of all four implants in model A. During posterior loading, lower stress concentrations were observed around the anterior implants of model A; however, the tilted posterior implants were subjected to higher stresses in every condition. CONCLUSIONS Application of either of these designs was successful in reducing peri-implant stress in one loading condition. However, neither design demonstrated better performance in both loading conditions; therefore, within the limitations of this study, neither design demonstrated clearly superior performance.
Remote Worldwide Control through SMS using Nokia Mobile

Mobile phone can serve as powerful tool for worldwide communication for even roaming user. A system has been developed to extend the capability of mobile phone for remote monitoring and control of devices. Nokia Mobile Phone model 3315 was chosen for implementation because of its popularity and low cost. As this model does not support AT commands, F-Bus protocols were used to exchange information between mobile and PC through COM1 port. The system was designed to send SMS to specified mobile user if there is a change in the status of the input port. Moreover, system also scans for any incoming SMS Message. If any SMS with valid code is received, system responds by activating the appropriate output port bits. The various applications of the system are described and further modifications and possibilities are discussed.
Chromosomal variation in neurons of the developing and adult mammalian nervous system

A basic assumption about the normal nervous system is that its neurons possess identical genomes. Here we present direct evidence for genomic variability, manifested as chromosomal aneuploidy, among developing and mature neurons. Analysis of mouse embryonic cerebral cortical neuroblasts in situ detected lagging chromosomes during mitosis, suggesting the normal generation of aneuploidy in these somatic cells. Spectral karyotype analysis identified ≈33% of neuroblasts as aneuploid. Most cells lacked one chromosome, whereas others showed hyperploidy, monosomy, and/or trisomy. The prevalence of aneuploidy was reduced by culturing cortical explants in medium containing fibroblast growth factor 2. Interphase fluorescence in situ hybridization on embryonic cortical cells supported the rate of aneuploidy observed by spectral karyotyping and detected aneuploidy in adult neurons. Our results demonstrate that genomes of developing and adult neurons can be different at the level of whole chromosomes.
Map of science with topic modeling: Comparison of unsupervised learning and human‐assigned subject classification

The delineation of coordinates is fundamental for the cartography of science, and accurate and credible classification of scientific knowledge presents a persistent challenge in this regard. We present a map of Finnish science based on unsupervised‐learning classification, and discuss the advantages and disadvantages of this approach vis‐à‐vis those generated by human reasoning. We conclude that from theoretical and practical perspectives there exist several challenges for human reasoning‐based classification frameworks of scientific knowledge, as they typically try to fit new‐to‐the‐world knowledge into historical models of scientific knowledge, and cannot easily be deployed for new large‐scale data sets. Automated classification schemes, in contrast, generate classification models only from the available text corpus, thereby identifying credibly novel bodies of knowledge. They also lend themselves to versatile large‐scale data analysis, and enable a range of Big Data possibilities. However, we also argue that it is neither possible nor fruitful to declare one or another method a superior approach in terms of realism to classify scientific knowledge, and we believe that the merits of each approach are dependent on the practical objectives of analysis.
Investigating connectivity in brain-like networks

Experimental research over the last two decades has shown that the anatomical connectivity among neurons is largely non-random across brain areas. This complex organisation shapes the flow of information, giving rise to specific pathways and motifs, which are ultimately responsible for processes like emotions, cognitive functions and behaviour, just to mention few. Due to the spectacular progress of technology, the study of the brain wiring diagram, known as connectomics, has received considerable attention in recent years, resulting in the proliferation of large data sets. From one side, this adds a significant contribution towards a better understanding of the complex processes that take place in the brain. On the other side, however, analysing such large connectivities is a hard task that has not yet found a satisfactory solution. Particular evidence has been found for bidirectional motifs,occurring when two neurons project onto each other via connections of equal strength, and unidirectional motifs, when one of the two connections is dominant. These specific motifs were found to correlate with short-term synaptic plasticity properties, which are related to resources availability for signal transmission. The aim of this thesis is to add a contribution to the ongoing efforts spent on answering the two main questions related to motif evidence: How can we satisfactory detect and measure motifs in large networks and why do they have the characteristics that we observe? Following existing literature, we hypothesise that bidirectional and unidirectional motifs appear as a consequence of learning processes, which move the distribution of the synaptic connections away from randomness through activity dependent synaptic plasticity. Based on this, we introduce a symmetry measure for global connectivity and a statistics-based heuristic algorithm for directed and weighted graphs that is able to detect overlapping bidirectional communities within large networks. On the other side, to address the why question we introduce an error-driven learning framework for short-term plasticity that acts jointly with Spike-Timing Dependent Plasticity, a well-known learning mechanism for long-term plasticity: By allowing synapses to change their properties,neurons are able to adapt their own activity depending on an error signal. This results in more rich dynamics and also, provided that the learning mechanism is target-specific, leads to specialised groups of synapses projecting onto functionally different targets, qualitatively replicating the experimental results of Wang and collaborators in 2006.
Analysing the content of Web 2.0 documents by using a hybrid approach

User involvement in Web 2.0 has made a significant contribution to the increase in the amount of multimedia content on the Web. Images are one of the most used media, shared across the network to mark user experience in daily life. Interactive applications have allowed users to participate in describing these images, usually in the form of free text, thus gradually enriching the images' descriptions. Nevertheless, often these images are left with crude or no description. Web search engines such as Google and Yahoo provide text based searching to find images by mapping query concepts with the text description of the image, thus limiting the information discovery to material with good text descriptions. A similar issue is faced by text based search provided by Web 2.0 applications. Images with less description might not contain adequate information while images with no description will be useless as they will become unsearchable by a text based search. Therefore, there is an urgent need to investigate ways to produce high quality information to provide insight into the document content. The aim of this research is to investigate a means to improve the capability of information retrieval by utilizing Web 2.0 content, the Semantic Web and other emerging technologies. A hybrid approach is proposed which analyses two main aspects of Web 2.0 content, namely text and images. The text analysis consists of using Natural Language Processing and ontologies. The aim of the text analysis is to translate free text descriptions into a semantic information model tailored to Semantic Web standards. Image analysis is developed using machine learning tools and is assessed using ROC analysis. The aim of the image analysis is to develop an image classifier exemplar to identify information in images based on their visual features. The hybrid approach is evaluated based on standard information retrieval performance metrics, precision and recall. The example semantic information model has structured and enriched the textual content thus providing better retrieval results compared to conventional tag based search. The image classifier is shown to be useful for providing additional information about image content. Each of the approaches has its own strengths and they complement each other in different scenarios. The thesis demonstrates that the hybrid approach has improved information retrieval performance compared to either of the contributing techniques used separately.
The Effect of GA Redundancy on the Design of Reverse Logistics Network

Genetic algorithm's approach has been one of the most important optimization techniques though the related problems of selection pressure still exist. Diversity is the key issue. For this reason, we explored the implication of redundancy in both genetic algorithm's overrepresentation and multi-explanation. Our research result supports the view of cross-competition but not diversity loss when considering uniform coding redundancy with expressive elitism and the tolerance of infeasible solutions. On the other side, we developed new decoding procedure based on the inborn searchability of the small world. In designing the network of the reverse logistics having multiple lower-dimensional constraints, with the help of multiple overlapped fitness functions, the performance of genetic algorithms can truly be improved.
Inter- and intra-observer variability for assessment of the synergy between percutaneous coronary intervention with TAXUS and cardiac surgery (SYNTAX) score and association of the SYNTAX score with clinical outcome in patients undergoing unprotected left main stenting in the real world.

BACKGROUND The Synergy Between Percutaneous Coronary Intervention With TAXUS and Cardiac Surgery (SYNTAX) score was proposed as a method to evaluate the complexity of coronary anatomy. However, the reproducibility of assessment for the SYNTAX score in unprotected left main coronary artery (ULMCA) disease has not yet been adequately evaluated. The purpose of this study is to assess inter- and intra-observer variability for the assessment of the SYNTAX score in patients undergoing ULMCA stenting in daily clinical practice. METHODS AND RESULTS The SYNTAX score of 101 consecutive patients who underwent ULMCA stenting with sirolimus-eluting stent was independently assessed by 2 experienced interventional cardiologists. One of the 2 cardiologists evaluated all the cases again 6 months after the initial assessment. The κ value for inter-observer variability in estimating the SYNTAX score was 0.62 according to the dichotomized analysis (≥ 33, < 33) and 0.58 according to the tertile analysis (< 23, 23 ≤ - < 33, ≥ 33), while the intra-observer variability was 0.78 and 0.69, respectively. Patients with a high SYNTAX score (≥ 33, n = 55) compared with those with low or intermediate score (< 33, n = 46) had a significantly higher rate of target-lesion revascularization (TLR) of the ULMCA lesion at 2 years (24% vs. 4.4%, P = 0.01). CONCLUSIONS Both inter- and intra-observer variability for estimating the SYNTAX score were within an acceptable range and a high SYNTAX score showed a higher rate of TLR in patients undergoing ULMCA stenting in daily clinical practice.
What matters most to people in retirement villages and their transition to residential aged care

INTRODUCTION: As older people age and become frail, their decline in independence and concomitant changing care needs may force them to move from retirement village to a residential aged care (RAC) facility. The purpose of this study was to identify factors that contribute to subjective wellbeing among older people living in retirement villages in Aotearoa New Zealand and to compare results with the data from the residents of the care home facilities co-located with the retirement villages. METHOD: This study is mainly quantitative in nature to examine what factors contributed to subjective wellbeing among older people living in retirement villages. Descriptive and regression analyses were used with data collected in 2016 from residents of two retirement villages ( N = 163) from one aged residential care provider in Aotearoa New Zealand and they were then compared with already-published data on RAC residents. In addition, four village residents participated in semi-structured interviews. RESULTS: Results showed that retirement village residents reported being generally satisfied with their living environment and their overall wellbeing is positively influenced by their social and psychological milieu. CONCLUSIONS: This research provides insights on what matters most to retirement village residents’ subjective wellbeing, which includes a dignified environment enhancing positive mental health, relationship building and reducing loneliness and isolation. Results were also compared with feedback from care home residents co-located in the same estate to provide an indicative picture for comparison against other studies to inform and expand choices for older people to consider when relocating in late-life.
Robust Color Image Superresolution: An Adaptive M-Estimation Framework

This paper introduces a new color image superresolution algorithm in an adaptive, robust M-estimation framework. Using a robust error norm in the objective function, and adapting the estimation process to each of the low-resolution frames, the proposed method effectively suppresses the outliers due to violations of the assumed observation model, and results in color superresolution estimates with crisp details and no color artifacts, without the use of regularization. Experiments on both synthetic and real sequences demonstrate the superior performance over using the and error norms in the objective function.
Stock Market Integration: Evidence from Pacific- Basin Country Funds

This study analyzes the extent of stock market integration between the U.S. and the four emerging Pacific-Basin countries of Korea, Malaysia, Thailand, and Taiwan by examining the relationships between returns on closed-end country funds trading on U.S. exchanges, returns on these funds’ net asset values, and returns on U.S. equities. Based on cointegration tests and variance decomposition analysis applied to vector autoregression models, we conclude that despite the changes in capital controls these Pacific-basin countries implemented from the mid-1980s to the end of 1996, they are still largely segmented from the U.S. stock market. Because there still exists substantial potential for these four Pacific-basin countries to become more integrated with the U.S. market, the reforms implemented during the post-crisis period of 1997-1998 in Asia may have an important impact on how these markets function. I. INTRODUCTION Over the years, European stocks have generally been the primary taget of U.S. investors’ foreign portfolio acquisitions. The 1980s, though, witnessed the rising appeal of the stock markets of many emerging economies, particularly those of the Pacific-Basin. 1 Among the methods allowing foreign investors access to these markets has been the use of a country fund. 2 During the years 1980-1990, for example, more than 30 closed-end country funds representing various countries were formed in the U.S. For closed-end country funds which invest in a portfolio of financial instruments from a foreign country, two separate market prices can emerge: the U.S.-based (quoted on U.S. exchanges) share price (SP) and the fund’s net asset value (NAV) reflecting the prices of its component shares traded on the foreign market. A number of prior studies show that significant divergence (premium or discount) exists, across time, between the SP and the per share NAV. 3 Explanations partly focus on the existence of various forms of friction that cause market segmentation, including regulatory restrictions imposed on foreign investors, non-overlapping trading hours, and high information-transfer costs.
Quantitative Acetylome Analysis Reveals the Roles of SIRT1 in Regulating Diverse Substrates and Cellular Pathways*

Despite of the progress in identifying many Lys acetylation (Kac) proteins, Kac substrates for Kac-regulatory enzymes remain largely unknown, presenting a major knowledge gap in Kac biology. Here we identified and quantified 4623 Kac sites in 1800 Kac proteins in SIRT1+/+ and SIRT1−/− MEF cells, representing the first study to reveal an enzyme-regulated Kac subproteome and the largest Lys acetylome reported to date from a single study. Four hundred eighty-five Kac sites were enhanced by more than 100% after SIRT1 knockout. Our results indicate that SIRT1 regulates the Kac states of diverse cellular pathways. Interestingly, we found that a number of acetyltransferases and major acetyltransferase complexes are targeted by SIRT1. Moreover, we showed that the activities of the acetyltransferases are regulated by SIRT1-mediated deacetylation. Taken together, our results reveal the Lys acetylome in response to SIRT1, provide new insights into mechanisms of SIRT1 function, and offer biomarker candidates for the clinical evaluation of SIRT1-activator compounds.
Least-squares Estimation of Nanopore Channel Conductance in Voltage-varying Experiments

Step-changing and sinusoidal voltage patterns have expanded the capabilities of the nanopore instrument for single molecule manipulation and measurement. A challenge with voltage-varying experiments is that capacitance in the system is excited and masks the contribution of the nanopore channel conductance in the measured current. The conductance is the parameter that can be used to infer the dynamics of the complex (e.g., DNA, or DNA-protein) in the pore. We present a least-squares parameter estimation (LSPE) algorithm for estimating the channel conductance under voltage-varying conditions, including step and sinusoidal voltages, with the objective of inferring the channel conductance parameter as continuously as possible. The algorithm is shown to recover the conductance faster than by waiting for capacitive transients to settle in step-voltage experiments, and provides accurate continuous conductance estimates in sinusoidal voltage experiments, with realistic noise levels superimposed on the measurements.
Reinsurance Demand and Liquidity Creation

This paper analyzes the relation between insurers’ liquidity creation and reinsurance demand. The empirical measure of liquidity creation was developed for banks by Berger and Bouwman (2009), who distinguished two important bank activities: liquidity creation and risk transformation. Insurers also actively transform risk, but the extent of their engagement in liquidity creation is less clear. Because liquidity creation is a risky activity, it may affect the demand for reinsurance. The goal of this study is to analyze how liquidity creation affects demand for reinsurance.