Miracle-dz/UniFAR-FTUs huggingface dataset:
Stable path planning algorithm for avoidance of dynamic obstacles

Previous research of path planning has focused mainly on finding shortest paths or smallest movements. These methods, however, have poor stability characteristics when dynamic obstacles are considered on real-life or in-body map's environments. In this paper, we suggest a stable path planning algorithm for avoidance of dynamic obstacles. The proposed method makes the movement of a mobile robot more stable in a dynamic environment. Our focus is based on finding optimal movements for stability rather than finding shortest paths or smallest movements. The algorithm is based on Genetic Algorithm (GA) and uses k-means clustering to recognize the distribution of dynamics obstacles in various mobile space. Simulation results confirm this method can determine stable paths through environments involving dynamic obstacles. In order to validate our results, we compared the dynamic k values used in k-means clustering and grid-based dynamic cell sizes from several test sets.
let-7b and miR-126 Are Down-Regulated in Tumor Tissue and Correlate with Microvessel Density and Survival Outcomes in Non–Small–Cell Lung Cancer

Angiogenesis is a critical event in the development, progression, and spread of various human cancers, including lung cancer. Molecular mechanisms that underlie the complex regulation of angiogenic processes are poorly understood. However, an increasing body of evidence indicates miRNAs as important regulators of tumor angiogenesis. Forceps biopsies were collected from tumor tissue, surrounding tissue, and non-tumor tissue from 50 NSCLC patients. Lung tissue samples from individuals with no clinical evidence of a cancerous disease served as controls. Immunohistochemical staining for Factor VIII was used to evaluate microvessel density (MVD). TaqMan® primer-probe sets were used in quantitative real-time RT-PCR reactions to determine expression levels of let-7b, miR-126, miR-9, and miR-19a. We demonstrated significantly higher MVD and decreased expression levels of let-7b and miR-126 in tumor tissue and surrounding tissue in comparison to corresponding non-tumor tissue or lung tissue from the control group. In addition, no differences in MVD and expression levels of both miRNAs between tumor tissue and surrounding tissue from NSCLC patients were observed. Low expression of both miRNAs correlated with high MVD and worse progression-free survival and overall survival. These observations strongly suggest similar molecular alternations within tumor tissue and surrounding tissue that comprise a specific microenvironment. Low expression of let-7b and miR-126 seems to have a possible anti-angiogenic role in lung tumor tissue and significantly correlates with worse survival outcomes for lung cancer patients. Moreover, the regulation of let-7b and miR-126 expression could have therapeutic potential because it could reduce tumor angiogenesis and therefore suppress tumor growth in lung cancer patients.
A Novel Neural Networks-Based Texture Image Processing Algorithm for Orange Defects Classification

In this paper is proposed, implemented and evaluated a novel radial basis probabilistic neural network (RBPNN) based classification algorithm for classification fruit surface defects in color and texture of a very important fruit as orange. The proposed algorithm takes orange images as inputs then the texture and gray features of defect area are extracted by computing a gray level co-occurrence matrix and the defect areas are classified through an RBPNN-based classifier. The conducted experiments and the results reveal as the classification accuracy achieved is up to 88%.
Comparing eye and gesture pointing to drag items on large screens

Large screens are populating a variety of settings motivating research on appropriate interaction techniques. While gesture is popularized by depth cameras we contribute with a comparison study showing how eye pointing is a valuable substitute to gesture pointing in dragging tasks. We compare eye pointing combined with gesture selection to gesture pointing and selection. Results clearly show that eye pointing combined with a selection gesture allows more accurate and faster dragging.
Real-time direct tracking of color images in the presence of illumination variation

This paper introduces a novel color tracking model for image registration that exploits directly the color information provided by standard color cameras. Furthermore, unlike previous approaches, the color tracking model is designed to handle both global and local illumination changes within a robust framework that also rejects outliers such as occluding objects, shadows, etc. In order to demonstrate the proposed approach a planar template tracking algorithm is used, however, the approach is also valid for a general class of direct tracking algorithms. In particular, the objective function is defined to be minimized directly in the CFA (color filter array) space instead of the common RGB space. It will be shown that this not only takes advantage of the discernibility of color measurements but also drastically improves the efficiency of the vision processing pipeline and ultimately improves real-time performance. A robust global illumination model is then combined with a robust M-estimation technique that is shown to handle outliers as well as global and local illumination changes. Results from synthetic and real sequences are presented to demonstrate the proposed concept.
Patterns and Mechanisms of Growth of Fifth‐Instar Manduca sexta Caterpillars Following Exposure to Low‐ or High‐Protein Food during Early Instars

For many insect herbivores, variation in protein availability is a pervasive part of the environment. I explore how variable protein availability affects growth rates of fifth‐instar Manduca sexta caterpillars and how growth is related to behavior and physiology. Groups of larvae were reared on low‐ or high‐protein artificial diets (5.9% and 17.7% casein by dry weight, respectively) and then transferred in the fifth instar to the same or opposite diet. During or after the 24‐h period following transfer, I measured growth rate, consumption rate, growth efficiency, midgut proteolytic activity, and masses of midgut contents and tissues. Fifth‐instar caterpillars reared in earlier instars on high‐protein diet grew about 20% more rapidly over 24 h than did caterpillars reared on low‐protein diet. This growth pattern appears to be caused by differences in consumption and growth efficiency: caterpillars reared on high protein consumed more food, and used it more efficiently, than did caterpillars reared on low‐protein diet. Over the short term (24 h), in contrast, fifth instars that received low‐protein diet grew as rapidly as caterpillars that received high‐protein diet. Increased (compensatory) consumption appears to be the primary mechanism by which caterpillars consuming low‐protein food maintained growth rates.
Out‐of‐core Data Management for Path Tracing on Hybrid Resources

We present a software system that enables path‐traced rendering of complex scenes. The system consists of two primary components: an application layer that implements the basic rendering algorithm, and an out‐of‐core scheduling and data‐management layer designed to assist the application layer in exploiting hybrid computational resources (e.g., CPUs and GPUs) simultaneously. We describe the basic system architecture, discuss design decisions of the system's data‐management layer, and outline an efficient implementation of a path tracer application, where GPUs perform functions such as ray tracing, shadow tracing, importance‐driven light sampling, and surface shading. The use of GPUs speeds up the runtime of these components by factors ranging from two to twenty, resulting in a substantial overall increase in rendering speed. The path tracer scales well with respect to CPUs, GPUs and memory per node as well as scaling with the number of nodes. The result is a system that can render large complex scenes with strong performance and scalability.
Analysis of plant microbe interactions in the era of next generation sequencing technologies

Next generation sequencing (NGS) technologies have impressively accelerated research in biological science during the last years by enabling the production of large volumes of sequence data to a drastically lower price per base, compared to traditional sequencing methods. The recent and ongoing developments in the field allow addressing research questions in plant-microbe biology that were not conceivable just a few years ago. The present review provides an overview of NGS technologies and their usefulness for the analysis of microorganisms that live in association with plants. Possible limitations of the different sequencing systems, in particular sources of errors and bias, are critically discussed and methods are disclosed that help to overcome these shortcomings. A focus will be on the application of NGS methods in metagenomic studies, including the analysis of microbial communities by amplicon sequencing, which can be considered as a targeted metagenomic approach. Different applications of NGS technologies are exemplified by selected research articles that address the biology of the plant associated microbiota to demonstrate the worth of the new methods.
On the Approximation Theory of Linear Variational Subspace Design

Solving large-scale optimization on-the-fly is often a difficult task for real-time computer graphics applications. To tackle this challenge, model reduction is a well-adopted technique. Despite its usefulness, model reduction often requires a handcrafted subspace that spans a domain that hypothetically embodies desirable solutions. For many applications, obtaining such subspaces case-by-case either is impossible or requires extensive human labors, hence does not readily have a scalable solution for growing number of tasks. We propose linear variational subspace design for large-scale constrained quadratic programming, which can be computed automatically without any human interventions. We provide meaningful approximation error bound that substantiates the quality of calculated subspace, and demonstrate its empirical success in interactive deformable modeling for triangular and tetrahedral meshes.
Outcomes of Surgical Repair for Persistent Truncus Arteriosus from Neonates to Adults: A Single Center's Experience

Objective This study aimed to report our experiences with surgical repair in patients of all ages with persistent truncus arteriosus. Methods From July 2004 to July 2014, 50 consecutive patients with persistent truncus arteriosus who underwent anatomical repair were included in the retrospective review. Median follow-up time was 3.4 years (range, 3 months to 10 years). Results Fifty patients underwent anatomical repair at a median age of 19.6 months (range, 20 days to 19.1 years). Thirty patients (60%) were older than one year. The preoperative pulmonary vascular resistance and mean pulmonary artery pressure were 4.1±2.1 (range, 0.1 to 8.9) units.m2 and 64.3±17.9 (range, 38 to 101) mmHg, respectively. Significant truncal valve regurgitation was presented in 14 (28%) patients. Hospital death occurred in 3 patients, two due to pulmonary hypertensive crisis and the other due to pneumonia. Three late deaths occurred at 3, 4 and 11 months after surgery. The actuarial survival rates were 87.7% and 87.7% at 1 year and 5 years, respectively. Multivariate analysis identified significant preoperative truncal valve regurgitation was a risk factor for overall mortality (odds ratio, 7.584; 95%CI: 1.335–43.092; p = 0.022). Two patients required reoperation of truncal valve replacement. One patient underwent reintervention for conduit replacement. Freedom from reoperation at 5 years was 92.9%. At latest examination, there was one patient with moderate-to-severe truncal valve regurgitation and four with moderate. Three patients had residual pulmonary artery hypertension. All survivors were in New York Heart Association class I-II. Conclusions Complete repair of persistent truncus arteriosus can be achieved with a relatively low mortality and acceptable early- and mid-term results, even in cases with late presentation. Significant preoperative truncal valve regurgitation remains a risk factor for overall mortality. The long-term outcomes warrant further follow-up.
A Simple Push-Pull Algorithm for Blue-Noise Sampling

We describe a simple push-pull optimization (PPO) algorithm for blue-noise sampling by enforcing spatial constraints on given point sets. Constraints can be a minimum distance between samples, a maximum distance between an arbitrary point and the nearest sample, and a maximum deviation of a sample's capacity (area of Voronoi cell) from the mean capacity. All of these constraints are based on the topology emerging from Delaunay triangulation, and they can be combined for improved sampling quality and efficiency. In addition, our algorithm offers flexibility for trading-off between different targets, such as noise and aliasing. We present several applications of the proposed algorithm, including anti-aliasing, stippling, and non-obtuse remeshing. Our experimental results illustrate the efficiency and the robustness of the proposed approach. Moreover, we demonstrate that our remeshing quality is superior to the current state-of-the-art approaches.
Counting and Arithmetic of the Inca

The Inca Empire - the greatest pre-Columbian empire on the American continent - extended from Ecuador to central Chile for more than five thousand miles. Its capital was Cuzco established in the high Peruvian Andes. This highly advanced civilization developed a counting system used to run the empire - in particular, to build the 14,000 mile road structure and monumental architecture. Some of the algorithms believed to be used by the Inca to do computations using a yupana, an ancient calculating device, will be presented, as well as classroom activities for the course “Mathematics in Non-European Cultures” for non Mathematics and Science majors offered at Millersville University of Pennsylvania. Key Words: Ethnomathematics, Inca, Yupana, Arithmetic Resumen El Imperio Inca – el imperio pre-Colombino mas grande del continente Americano – se extendio desde Ecuador hasta Chile central por mas de cinco mil millas. La capital fue Cuzco, la que fue establecida en las Alturas de los Andes Peruanos. Esta civilizacion altamente avanzada desarrollo un sistema contable para organizar el imperio – en particular, para construir una red de caminos de 14.000 millas y una arquitectura monumental. Algunos de los algoritmos que se creen haber sido usados por los Inca para hacer calculos fue la "yupana". Este antiguo artefacto de calculo sera presentado, entre otras actividades del curso “Matematicas en Culturas No-Europeas” para estudiantes de todas las areas de concentracion, excepto Matematicas y Ciencia, ofrecido en la Universidad de Millersville en Pennsylvania. Palabras Clave: Etnomatematicas, Inca, Yupana, Aritmetica
Minor intron splicing is regulated by FUS and affected by ALS‐associated FUS mutants

Fused in sarcoma (FUS) is a ubiquitously expressed RNA‐binding protein proposed to function in various RNA metabolic pathways, including transcription regulation, pre‐mRNA splicing, RNA transport and microRNA processing. Mutations in the FUS gene were identified in patients with amyotrophic lateral sclerosis (ALS), but the pathomechanisms by which these mutations cause ALS are not known. Here, we show that FUS interacts with the minor spliceosome constituent U11 snRNP, binds preferentially to minor introns and directly regulates their removal. Furthermore, a FUS knockout in neuroblastoma cells strongly disturbs the splicing of minor intron‐containing mRNAs, among them mRNAs required for action potential transmission and for functional spinal motor units. Moreover, an ALS‐associated FUS mutant that forms cytoplasmic aggregates inhibits splicing of minor introns by trapping U11 and U12 snRNAs in these aggregates. Collectively, our findings suggest a possible pathomechanism for ALS in which mutated FUS inhibits correct splicing of minor introns in mRNAs encoding proteins required for motor neuron survival.
Diagnostic performance of lung ultrasound in the diagnosis of pneumonia: a bivariate meta-analysis.

BACKGROUND AND OBJECTIVE Pneumonia is a common disease with both high morbidity and mortality, the diagnosis of pneumonia remains a clinical challenge. Many studies have been conducted to identify the usefulness of lung ultrasound for the diagnosis of pneumonia, but with inconsistent and inconclusive results. The present study aimed to establish the overall diagnostic accuracy of lung ultrasound in diagnosing pneumonia. METHODS Based on a comprehensive search of the Pubmed, Embase, and the Cochrane database, we identified out-come data from all articles estimating diagnostic accuracy with lung ultrasound for pneumonia. Quality was assessed with the Quality Assessment for Diagnostic Accuracy Studies. Results from different studies were pooled using a bivariate meta-analysis. Summary receiver operating characteristic curve was used to assess the overall performance of lung ultrasound-based assays. RESULTS Nine studies containing 1080 subjects were included in this meta-analysis. The summary estimates for lung ultrasound in the diagnosis of pneumonia in the studies included were as follows: sensitivity, 0.97 (95% CI: 0.93-0.99); specificity, 0.94 (95% CI: 0.85-0.98); DOR, 507.99 (95% CI: 128.11-2014.34); positive likelihood ratio, 15.62 (95% CI: 6.31-38.68); negative likelihood ratio, 0.03 (95% CI: 0.01-0.08); The area under the summary receiver operating characteristic curve was 0.99 (95% CI: 0.98-1.00). CONCLUSION Lung ultrasound is a capable of diagnosing pneumonia with high accuracy and is a promising attractive alternative to chest radiography and thoracic CT scan.
Information-processing deficits and thought disorder in schizophrenia.

OBJECTIVE: The goal of this investigation was to study the relationship between information-processing deficits and thought disorder in schizophrenic patients. METHOD: Fifty-two subjects diagnosed with schizophrenia were administered tests of information processing and thought disorder. The information-processing tests included visual backward masking and prepulse inhibition of the startle reflex. Thought disorder was measured with the Magical Ideation Scale, the Scale for the Assessment of Positive Symptoms, the alogia subscale of the Scale for the Assessment of Negative Symptoms, and the Ego Impairment Index-human experience variable and its subcomponents derived from the Rorschach. RESULTS: Elevated poor responses on the Ego Impairment Index-human experience variable were significantly correlated with information-processing deficits. In a simultaneous multiple regression, the auditory prepulse inhibition measure was the best predictor of poor responses on the Ego Impairment Index-human experience variable. CONCLUSIONS: The results suggest a correlative relationship between information-processing deficits and thought disorder. The relationship is most apparent when highly sensitive measures of both information processing and thought disorder are used. Furthermore, the prediction of poor responses on the Ego Impairment Index-human experience variable by auditory prepulse inhibition is important, since the neural circuitry of prepulse inhibition is known and involves the modulatory influences of the cortical-striatal-pallidal-thalamic circuit. These findings lend support to the hypothesis that information-processing failures are associated with cognitive fragmentation and thought disorder. More speculatively, these results allow us to hypothesize that impairments in part of the cortical-striatal-pallidal-thalamic circuit may lead to thought disorder, as well as prepulse inhibition deficits.
Parametric multichannel noise reduction algorithm utilizing temporal correlations in reverberant environment

In this paper, we propose a parametric multichannel noise reduction algorithm utilizing temporal correlations in a noisy and reverberant environment. Under the reverberant condition, the received acoustic signal becomes highly correlated in the time domain and it makes successful noise reduction quite difficult. The proposed parametric noise reduction method takes account of interdependencies between components observed from different frames. Extended speech and noise power spectral density (PSD) matrices are estimated containing additional temporal information, and the parametric multichannel noise reduction filter based on these PSD matrices is applied to the input microphone array signal. According to the experimental results, the proposed algorithm has been found to show better performances compared with the conventional multiplicative filtering technique which considers the current input signals only.
Intergenerational support and life satisfaction of young-, old- and oldest-old adults in China

ABSTRACT Objectives: This study investigated variation across different old-age groups in the association between intergenerational support and elderly life satisfaction in China, taking into account both exchange patterns and different types of support. Method: Using the first two waves (2010 and 2012) of China Family Panel Studies, we applied the fixed-effect approach to examine the moderating effect of age separately for exchange patterns and different types of intergenerational support. The sample included 3989 elderly people. Results: There were age differences in the association between intergenerational support and elderly life satisfaction, for both exchange patterns and different types of support. Particularly, there was significant difference between the young-old (61–70) and the oldest-old (85+) in terms of the association. Conclusion: Theoretically, this study helps to elaborate on social exchange and equity theories by introducing explanations from socio-emotional selectivity theory. It further highlights how policies for elderly care should be developed considering the diverse needs, characteristics and goals of elderly people rather than treating them as a singular homogenous group, in particular in relation to different old-age groups.
Wetting hysteresis induced by nanodefects

Significance Drops may fail to slide even on extremely smooth surfaces. This fact is due to the ubiquitous imperfections of surfaces: defects of molecular size—here too small to be noticed and experimentally characterizable—can hinder a macroscopic drop. To understand these far-reaching nanoscale phenomena, we combine a molecular description of the liquid with advanced techniques for the study of rare events. This approach allows us to bridge the diverse scales involved, demonstrating that even weak nanometer-sized surface defects can give rise to measurable differences between advancing and receding liquid fronts, i.e., contact angle hysteresis. The present results also shed new light on the unexpectedly long life of surface nanobubbles. Wetting of actual surfaces involves diverse hysteretic phenomena stemming from ever-present imperfections. Here, we clarify the origin of wetting hysteresis for a liquid front advancing or receding across an isolated defect of nanometric size. Various kinds of chemical and topographical nanodefects, which represent salient features of actual heterogeneous surfaces, are investigated. The most probable wetting path across surface heterogeneities is identified by combining, within an innovative approach, microscopic classical density functional theory and the string method devised for the study of rare events. The computed rugged free-energy landscape demonstrates that hysteresis emerges as a consequence of metastable pinning of the liquid front at the defects; the barriers for thermally activated defect crossing, the pinning force, and hysteresis are quantified and related to the geometry and chemistry of the defects allowing for the occurrence of nanoscopic effects. The main result of our calculations is that even weak nanoscale defects, which are difficult to characterize in generic microfluidic experiments, can be the source of a plethora of hysteretical phenomena, including the pinning of nanobubbles.