Miracle-dz/UniFAR-FTUs huggingface dataset:
National Trends in Surgery for Rotator Cuff Disease in Korea

The objective of this study was to investigate the national trends in rotator cuff surgery in Korea and analyze hospital type-specific trends. We analyzed a nationwide database acquired from the Korean Health Insurance Review and Assessment Service (HIRA) from 2007 to 2015. International Classification of Diseases, 10th revision (ICD-10) codes, procedure codes, and arthroscopic device code were used to identify patients who underwent surgical treatment for rotator cuff disease. A total of 383,719 cases of rotator cuff surgeries were performed from 2007 to 2015. The mean annual percentage change in the age-adjusted rate of rotator cuff surgery per population of 100,000 persons rapidly increased from 2007 to 2012 (53.3%, P < 0.001), while that between 2012 to 2015 remained steady (2.3%, P = 0.34). The proportion of arthroscopic surgery among all rotator cuff surgeries steadily rose from 89.9% in 2007 to 96.8% in 2015 (P < 0.001). In terms of hospital types, the rate of rotator cuff surgery increased to the greatest degree in hospitals with 30–100 inpatient beds, and isolated acromioplasty procedure accounted for a larger proportion of the rotator cuff surgeries in small hospitals and clinics compared to large hospitals. Overall, our findings indicate that cases of rotator cuff surgery have increased rapidly recently in Korea, of which arthroscopic surgeries account for the greatest proportion. While rotator cuff surgery is a popular procedure that is commonly performed even in small hospitals, there was a difference in the component ratio of the procedure code in accordance with hospital type.
Relaxed Analysis Operator Learning

The problem of analysis operator learning can be formulated as a constrained optimisation problem. This problem has been approximately solved using projected gradient or geometric gradient descent methods. We will propose a relaxation for the constrained analysis operator learning in this paper. The relaxation has been suggested here to, a) reduce the computational complexity of the optimisation and b) include a larger set of admissible operators. We will show here that an appropriate relaxation can be useful in presenting a projection-free optimisation algorithm, while preventing the problem to become ill-posed. The relaxed optimisation objective is not convex and it is thus not always possible to find the global optimum. However, when a rich set of training samples are given, we empirically show that the desired synthetic analysis operator is recoverable, using the introduced sub-gradient descent algorithm.
A Mutual-Information-Based Approach to Entity Reconciliation in Heterogeneous Databases

Entity reconciliation is crucial to data interoperability in heterogeneous databases. In our previous research works, we proposed an entities matching algorithm based on attribute entropy to identify the corresponding entities, which can resolve the limitations of present main approaches and improve the precision of entities matching obviously. By our further research, we find that some attributes with different importance in identifying the entities will obtain the same weights just according to attribute entropy. So in this paper we employ mutual information to quantify attribute weight due to mutual information well describes the correlation of probability distributions over two attributes. According to this idea, the final entropy computation algorithm and entity reconciliation algorithm based on mutual information are presented. The experimental results on real-world data show that our mutual-information-based approach can obtain better performance.
Evolving patches for software repair

Defects are a major concern in software systems. Unsurprisingly, there are many tools and techniques to facilitate the removal of defects through their detection and localisation. However, there are few tools that attempt to repair defects. To date, evolutionary tools for software repair have evolved changes directly in the program code being repaired. In this work we describe an implementation: pyEDB, that encodes changes as a series of code modifications or patches. These modifications are evolved as individuals. We show pyEDB to be effective in repairing some small errors, including variable naming errors in Python programs. We also demonstrate that evolving patches rather than whole programs simplifies the removal of spurious errors.
Spatial organization in 2D images

Information about the spatial organization in an image is an important clue towards identifying, or interpreting the contents of the image. In this paper the authors present a fuzzy logic method of representation, recognition and description of spatial relations between regions in an image which takes into account shape, size, orientation, or more generally a region as a whole. The method can be applied equally to crisp and fuzzy regions of the image, or combinations of these. Several examples are used to illustrate the results given by this method. <<ETX>>
Speculative bubbles and fat tail phenomena in a heterogeneous agent model

The aim of this paper is to propose a heterogeneous agent model of stock markets that develop complicated endogenous price fluctuations. We find occurrences of non-stationary chaos, or speculative bubble, are caused by the heterogeneity of traders' strategies. Furthermore, we show that the distributions of returns generated from the heterogeneous agent model have fat tails, a remarkable stylized fact observed in almost all financial markets.
DeepFruits: A Fruit Detection System Using Deep Neural Networks

This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it is a key element for fruit yield estimation and automated harvesting. Recent work in deep neural networks has led to the development of a state-of-the-art object detector termed Faster Region-based CNN (Faster R-CNN). We adapt this model, through transfer learning, for the task of fruit detection using imagery obtained from two modalities: colour (RGB) and Near-Infrared (NIR). Early and late fusion methods are explored for combining the multi-modal (RGB and NIR) information. This leads to a novel multi-modal Faster R-CNN model, which achieves state-of-the-art results compared to prior work with the F1 score, which takes into account both precision and recall performances improving from 0.807 to 0.838 for the detection of sweet pepper. In addition to improved accuracy, this approach is also much quicker to deploy for new fruits, as it requires bounding box annotation rather than pixel-level annotation (annotating bounding boxes is approximately an order of magnitude quicker to perform). The model is retrained to perform the detection of seven fruits, with the entire process taking four hours to annotate and train the new model per fruit.
Psychedelic therapy from an existential psychological viewpoint : a theoretical analysis

Clinical research into the therapeutic applications of classical psychedelics has slowly but steadily resumed over the last couple of decades. Continuing the research that went dormant in the late 1960‟s, modern trials are looking into the use of high-dose „psychedelic therapy‟ for various psychological issues. Although it may be too early to conclude on its efficacy, research is finding the therapy physiologically and psychologically safe. However, there is little theory to fit the practice. This thesis attempts to explain theoretically how psychedelic therapy exerts its effects by applying an existential psychological model of psychopathology. Psychedelic therapy is based on the observation that positive outcomes are related to strong spiritual experiences, called „mystical experiences‟. This eluding concept is examined in depth, with its phenomenological characteristics described. Experiential research on mystical experiences is reviewed. An existential psychological model is presented, and it is discussed how mystical experiences can be therapeutic as explained by this model. Growth in adaptiveness of defenses toward existential conflicts is highlighted as a possible changemechanism of psychedelic therapy. Implications and recommendations for future research are discussed.
Unravelling the Intrinsic Functional Organization of the Human Striatum: A Parcellation and Connectivity Study Based on Resting-State fMRI

As the main input hub of the basal ganglia, the striatum receives projections from the cerebral cortex. Many studies have provided evidence for multiple parallel corticostriatal loops based on the structural and functional connectivity profiles of the human striatum. A recent resting-state fMRI study revealed the topography of striatum by assigning each voxel in the striatum to its most strongly correlated cortical network among the cognitive, affective, and motor networks. However, it remains unclear what patterns of striatal parcellation would result from performing the clustering without subsequent assignment to cortical networks. Thus, we applied unsupervised clustering algorithms to parcellate the human striatum based on its functional connectivity patterns to other brain regions without any anatomically or functionally defined cortical targets. Functional connectivity maps of striatal subdivisions, identified through clustering analyses, were also computed. Our findings were consistent with recent accounts of the functional distinctions of the striatum as well as with recent studies about its functional and anatomical connectivity. For example, we found functional connections between dorsal and ventral striatal clusters and the areas involved in cognitive and affective processes, respectively, and between rostral and caudal putamen clusters and the areas involved in cognitive and motor processes, respectively. This study confirms prior findings, showing similar striatal parcellation patterns between the present and prior studies. Given such striking similarity, it is suggested that striatal subregions are functionally linked to cortical networks involving specific functions rather than discrete portions of cortical regions. Our findings also demonstrate that the clustering of functional connectivity patterns is a reliable feature in parcellating the striatum into anatomically and functionally meaningful subdivisions. The striatal subdivisions identified here may have important implications for understanding the relationship between corticostriatal dysfunction and various neurodegenerative and psychiatric disorders.
IT Readiness, ICT Usage, and National Sustainability Development: Testing the Source-Position-Performance Framework

Utilizing the Source-Position-Performance (SPP) framework of competitive advantage and the literature on information technology (IT) and sustainability as the guiding theoretical lenses, we posit that the government and business IT readiness (i.e., sources of advantage) leads to differentiation in government and business ICT usage (i.e., positional advantage), which in turn affects the national sustainability (i.e., performance) in terms of economic, environmental, and social developments. Based on secondary data from 108 countries, our results generally supported the hypothesized model. Specifically, government and business IT readiness in a country appeared to be a significant enabler of government and business ICT usage respectively, which in turn led to enhancement of national sustainability development. Post hoc mediation analysis indicates that government ICT usage (1) fully mediated the effect of government IT readiness on environmental and social developments; and (2) partially mediated the effect of government IT readiness on economic development. On the other hand, business ICT usage (1) fully mediated the effect of business IT readiness on economic development; (2) did not mediate the effect of business IT readiness on environmental development; and (3) partially mediated the effect of business IT readiness on social development. Our findings contribute to the theoretical discourse on “IT and sustainability” by identifying the role of IT readiness among government and businesses in a country and provide indications to practice on enhancing its sustainability by increasing the levels of ICT usage among them.
Serum Cystatin C Concentrations in Cats with Hyperthyroidism and Chronic Kidney Disease

Background Currently, no test can accurately predict the development of azotemia after treatment of hyperthyroidism. Serum cystatin C concentrations (sCysC) might be less influenced by changes in body muscle mass and so better indicate the presence of concurrent chronic kidney disease (CKD) in hyperthyroidism. Hypotheses sCysC will be higher in hyperthyroid cats that develop azotemia compared with hyperthyroid cats that remain nonazotemic after treatment; sCysC will be higher in nonhyperthyroid cats with azotemic CKD than healthy older cats and, sCysC will decrease after treatment of hyperthyroidism. Animals Ninety‐one cats treated in first opinion practice. Methods Case–control study. sCysC were compared between hyperthyroid cats which developed azotemia within 4 months of successful treatment of hyperthyroidism (pre‐azotemic group) and hyperthyroid cats which remained nonazotemic after treatment (nonazotemic group), and between nonhyperthyroid cats with azotemic CKD and healthy older cats. sCysC were also compared between hyperthyroid cats before treatment and at time of establishment of euthyroidism. Data are presented as median [25th, 75th percentile]. Results Baseline sCysC were not different between the pre‐azotemic and nonazotemic groups (1.9 [1.4, 2.3] mg/L versus 1.5 [1.1, 2.2] mg/L, respectively; P = .22). sCysC in nonhyperthyroid cats with azotemic CKD and healthy older cats were not significantly different (1.5 [1.0, 1.9] mg/L versus 1.2 [0.8, 1.4] mg/L, respectively; P = .16). sCysC did not change significantly after treatment of hyperthyroidism (pretreatment 1.8 [1.2, 2.3] mg/L, after treatment 1.6 [1.1, 2.4] mg/L; P = .82). Conclusions and Clinical Importance sCysC do not appear to be a reliable marker of renal function in hyperthyroid cats.
Contrasting genetic structure between mitochondrial and nuclear markers in the dengue fever mosquito from Rio de Janeiro: implications for vector control

Dengue is the most prevalent global arboviral disease that affects over 300 million people every year. Brazil has the highest number of dengue cases in the world, with the most severe epidemics in the city of Rio de Janeiro (Rio). The effective control of dengue is critically dependent on the knowledge of population genetic structuring in the primary dengue vector, the mosquito Aedes aegypti. We analyzed mitochondrial and nuclear genomewide single nucleotide polymorphism markers generated via Restriction‐site Associated DNA sequencing, as well as traditional microsatellite markers in Ae. aegypti from Rio. We found four divergent mitochondrial lineages and a strong spatial structuring of mitochondrial variation, in contrast to the overall nuclear homogeneity across Rio. Despite a low overall differentiation in the nuclear genome, we detected strong spatial structure for variation in over 20 genes that have a significantly altered expression in response to insecticides, xenobiotics, and pathogens, including the novel biocontrol agent Wolbachia. Our results indicate that high genetic diversity, spatially unconstrained admixing likely mediated by male dispersal, along with locally heterogeneous genetic variation that could affect insecticide resistance and mosquito vectorial capacity, set limits to the effectiveness of measures to control dengue fever in Rio.
ANALYZING TIME SERIES OF SATELLITE IMAGERY USING TEMPORAL MAP ALGEBRA

This paper presents the application of a set of spatio-temporal satellite image analysis functions based on temporal map algebra. The temporal map algebra functions treat time series of imagery as three-dimensional data sets where two dimensions encode planimetric position on the earth’s surface and the third dimension encodes time. Whereas the conventional local, focal, and zonal map algebra functions take as input one or more grids and output a grid (or, in the case of zonal functions, a table), temporal map algebra functions take one or more three-dimensional data ‘cubes’ as input and output a data ‘cube’ (or, in the case of temporal zonal functions, a table). As a demonstration of the utility of temporal map algebra for time series satellite image analysis, we investigate the impact of El Nino/Southern Oscillation (ENSO) on the 1982-1993 monthly time series Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) signal in southern Africa. Results suggest that vegetation intensity is suppressed, and its spatial and temporal variability enhanced, during ENSO warm and cold phase months, particularly over forest, woodland, and wooded grassland. These effects are generally diminished by the following growing season, particularly following an ENSO cold phase. For shrubland, vegetation intensity tends to increase during the growing season following an ENSO cold phase.
LIFE‐COURSE DESISTERS? TRAJECTORIES OF CRIME AMONG DELINQUENT BOYS FOLLOWED TO AGE 70*

Linking recently collected data to form what is arguably the longest longitudinal study of crime to date, this paper examines trajectories of offending over the life course of delinquent boys followed from ages 7 to 70. We assess whether there is a distinct offender group whose rates of crime remain stable with increasing age, and whether individual differences, childhood characteristics, and family background can foretell long-term trajectories of offending. On both counts, our results come back negative. Crime declines with age sooner or later for all offender groups, whether identified prospectively according to a multitude of childhood and adolescent risk factors, or retrospectively based on latent-class models of trajectories. We conclude that desistance processes are at work even among active offenders and predicted life-course persisters, and that childhood prognoses account poorly for long-term trajectories of offending.
Impact of secondary metabolites and related enzymes in flax resistance and/or susceptibility to powdery mildew

Changes in various physiological defenses including secondary metabolites, proline, total soluble protein and antioxidant enzymes were investigated in leaves and stems of 18 flax lines either resistant or susceptible to powdery mildew. The results showed that the total alkaloids content in flax stems was significantly increased in resistant lines when compared with resistant parent, but significantly decreased in susceptible lines and susceptible parent when compared with resistant parent. Stems of the resistant flax lines had a higher content of total phenols than susceptible ones upon pathogen challenge. Infection with powdery mildew significantly increased peroxidase, polyphenol oxidase and catalase activities in leaves of flax lines when compared with either resistant or susceptible parents as well as proline content. This increase was much pronounced in tolerant lines than resistant lines. Total soluble protein content in flax leaves increased significantly in resistant lines when compared with resistant parent but decreased significantly in susceptible lines when compared with resistant parent.
Geoscientific Model Development ECHMERIT V 1 . 0 – a new global fully coupled mercury-chemistry and transport model

ECHMERIT V1.0 – a new global fully coupled mercury-chemistry and transport model G. Jung, I. M. Hedgecock, and N. Pirrone CNR – Institute for Atmospheric Pollution, Division of Rende, 87036 Rende, Italy Received: 29 April 2009 – Accepted: 29 April 2009 – Published: 7 May 2009 Correspondence to: G. Jung (g.jung@cs.iia.cnr.it) Published by Copernicus Publications on behalf of the European Geosciences Union.
Adaptive filter-based reconstruction engine design for compressive sensing

The reconstruction in compressive sensing is an underdetermined question. Almost all existing reconstruction algorithms utilize pseudo inverse to solve this problem. However, the matrix inverse in pseudo inverse has high complexity. In this paper, we apply least mean square filter (LMS) to signal reconstruction and propose a new reconstruction algorithm for compressive sensing. The results show that proposed method has good recovery performance and low computational complexity compared with existing works. Moreover, we implemented the proposed reconstruction algorithm in 90nm CMOS which operated at 200 MHz and occupied an area of 1.36mm2. Throughput of the proposed method is 70% higher than state-of-the-art under the same cost.
Internet-based motivational interviewing: Factors influencing the impact of a brief motivational intervention on college students’ awareness of weight-related risk

entitled Internet-based motivational interviewing: Factors influencing the impact of a brief motivational intervention on college students’ awareness of weight-related risk by Melissa A. Jensen Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Psychology ____________________________________ Mojisola Tiamiyu, Ph.D., Committee Co-Chair
CORPORATE GOVERNANCE AND CORPORATE SOCIAL RESPONSIBILITY: A CRITICAL REVIEW

This paper aims to critically review the existing literature on the relationship between Corporate Governance, in particular board diversity, and its influence on both Corporate Social Responsibility (CSR) and Corporate Social Responsibility Reporting (CSRR) and suggest some important avenues for future research in this field. Assuming that both CSR and CSRR are outcomes of boards’ decisions, this paper proposes that examining boards’ decision making process with regard to CSR would provide more insight into the link between board diversity and CSR. Particularly, the paper stresses the importance of studies linking gender diversity and CSR decision making processes which is quite rare in the existing literature. It also identifies some of the important methodological drawbacks in the previous literature and highlights the importance of rigorous qualitative methods and longitudinal studies for the development of understanding of the diversity-CSR relationship.
Improving Axial Resolution in Confocal Microscopy with New High Refractive Index Mounting Media

Resolution, high signal intensity and elevated signal to noise ratio (SNR) are key issues for biologists who aim at studying the localisation of biological structures at the cellular and subcellular levels using confocal microscopy. The resolution required to separate sub-cellular biological structures is often near to the resolving power of the microscope. When optimally used, confocal microscopes may reach resolutions of 180 nm laterally and 500 nm axially, however, axial resolution in depth is often impaired by spherical aberration that may occur due to refractive index mismatches. Spherical aberration results in broadening of the point-spread function (PSF), a decrease in peak signal intensity when imaging in depth and a focal shift that leads to the distortion of the image along the z-axis and thus in a scaling error. In this study, we use the novel mounting medium CFM3 (Citifluor Ltd., UK) with a refractive index of 1.518 to minimize the effects of spherical aberration. This mounting medium is compatible with most common fluorochromes and fluorescent proteins. We compare its performance with established mounting media, harbouring refractive indices below 1.500, by estimating lateral and axial resolution with sub-resolution fluorescent beads. We show furthermore that the use of the high refractive index media renders the tissue transparent and improves considerably the axial resolution and imaging depth in immuno-labelled or fluorescent protein labelled fixed mouse brain tissue. We thus propose to use those novel high refractive index mounting media, whenever optimal axial resolution is required.