Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation of Similar Color Objects using Modified GrowCut Method

One of the most complex and prominent problems in the field of image processing is the image segmentation. Image segmentations are mainly of two types, namely fully automatic and interactive segmentation. Using fully automatic technique it is not always possible to produce a prominent and visually distinguishable output. As a result interactive segmentation gained popularity in recent years. GrowCut is a well known interactive image segmentation technique, which can localize the marked objects. In this present work, we have modified the GrowCut method so that all similar colored objects are segmented with respect to the marked objects. The proposed method is also faster than the GrowCut method.
A Catholic and Enhanced Study on Visual Analysis of Topic and Geo-Competition on Social Medical

In the intelligence civilization, in addition to practical competence and information technologies, it is becoming increasingly critical for people to develop a wider rage and encouraging social connections. Micro blogging communities that support updates, sharing new information like text, images, and videos time to time provided with privacy such as twitter. A twitter is Micro blog that uses digital backchannels to represent the timely exchange of pithy comments and impressions in large events. At present, mutual updates displayed in the form of a simple catalogue (list), making it difficult to get an overview of the communication that proceeds rapidly. This will confuse the participants of the twitter from the main event occurred. In other way, our Visual Backchannel design provides an evolving,interactive, and multi-faceted visual overview of large-scale ongoing conversations on Twitter. To visualize an uninterrupted updating information stream, we include visual saliency for what is happening at this moment and what has just occurred a moment ago, set in the context of the evolving conversation. For visual system we introduce a Temporal adjustable Stacked graph represents topic streams that visualizes topic over time accompanied by two compact visualizations, people Spiral, Image Cloud that has shared images which are going to be varied according to the popularity in the events together with post listing all these are linked with the time ranges. We consider our design considerations, in particular with respect to developing visualizations of dynamically changing data. Through the Extension representation of user‟s data supposed to increase the efficiency of the visual backchannel.
Genotype‐adjusted familial correlation analysis using three generalized estimating equations

We analyze familial correlation of a memory score from Caribbean Hispanic families that have multiple family members affected with Alzheimer's disease, adjusting for having at least one APOE‐ε4 allele, as well as other confounders. To enhance the efficiency of correlation model, this paper proposes an alternative approach for three generalized estimating equations proposed by Yan and Fine (Statist. Med. 2004; 23:859–874). The efficiency of correlation model is evaluated through the asymptotic relative efficiency computation and simulations. Copyright © 2008 John Wiley & Sons, Ltd.
Nitrogen Amendment Stimulated Decomposition of Maize Straw-Derived Biochar in a Sandy Loam Soil: A Short-Term Study

This study examined the effect of nitrogen (N) on biochar stability in relation to soil microbial community as well as biochar labile components using δ13C stable isotope technology. A sandy loam soil under a long-term rotation of C3 crops was amended with biochar produced from maize (a C4 plant) straw in absence (BC0) and presence (BCN) of N and monitored for dynamics of carbon dioxide (CO2) flux, phospholipid fatty acids (PLFAs) profile and dissolved organic carbon (DOC) content. N amendment significantly increased the decomposition of biochar during the first 5 days of incubation (P < 0.05), and the proportions of decomposed biochar carbon (C) were 2.30% and 3.28% in BC0 and BCN treatments, respectively, during 30 days of incubation. The magnitude of decomposed biochar C was significantly (P < 0.05) higher than DOC in biochar (1.75%) and part of relatively recalcitrant biochar C was mineralized in both treatments. N amendment increased soil PLFAs concentration at the beginning of incubation, indicating that microorganisms were N-limited in test soil. Furthermore, N amendment significantly (P < 0.05) increased the proportion of gram-positive (G+) bacteria and decreased that of fungi, while no noticeable changes were observed for gram-negative (G−) bacteria and actinobacteria at the early stage of incubation. Our results indicated that N amendment promoted more efficiently the proliferation of G+ bacteria and accelerated the decomposition of relatively recalcitrant biochar C, which in turn reduced the stability of maize straw-derived biochar in test soil.
Implications for preserving neural stem cells in whole brain radiotherapy and prophylactic cranial irradiation: a review of 2270 metastases in 488 patients

This study delineated the incidence of metastatic involvement of neural stem cell (NSC) regions and further aimed to explore the feasibility of selectively sparing the NSC compartments during whole brain radiotherapy (WBRT) and prophylactic cranial irradiation (PCI). A total of 2270 intracranial metastases in 488 patients were identified. Lesions were classified according to locations, including lesions in the NSC compartments (subventricular zone, SVZ, or hippocampus) and those in the rest of the brain/brainstem. The incidence of involvement of NSC regions was compared between oligometastatic patients (those with 1–4 lesions) and non-oligometastatic patients (those with 5 or more lesions) using a chi-square test. The volume of the NSC regions accounted for 2.23% of the whole brain, and the overall rate of metastatic lesions in NSC regions was 1.1% in 2270 metastases (25/2270), and 4.7% in 488 patients (23/488). Of the NSC region metastases, 7 (0.3%) involved the hippocampus and 18 (0.8%) occurred in the SVZ. Among the 7 hippocampal metastases identified in this study, 1/7 (14.3%) were found in oligometastatic patients, while 6/7 (85.7%) metastases were in non-oligometastatic patients. For metastases in the SVZ, all lesions occurred in non-oligometastatic patients with none in oligometastatic patients. Metastatic involvement of the NSC compartments was significantly lower in oligometastatic patients (0.15%, 1/670) than in non-oligometastatic patients (1.5%, 24/1600) (P < 0.001). Our retrospective review of 2270 metastases in 488 patients is that the volume of the compartments of NSC regions was 2.23% relative to the whole brain, but the incidence of involvement of the NSC compartments was 1.1%, and the vast majority of NSC lesions were found in non-oligometastatic patients. We believe our data supports selective reduction of doses for these aforementioned structures, when treating oligometastatic patients with WBRT and locally advanced-stage small-cell lung cancer patients with PCI.
A Boolean Expression based Template Matching Technique for Optical Circuit Generation

With the increased need of high speed computing paradigm, the optical circuits are gaining more importance. Immense investigations are under progress to build full-fledge optical circuits with minimum hardware. In this work, we are showing a template matching scheme that generates low cost optical circuits using Mach-Zehnder Interferometers (MZI) based optical devices. In this proposed design, initially we design four optimized templates using MZIs and later these templates perform exhaustive search in boolean logic expression to find its structural matches. If a match is found then it replaces the corresponding sub-circuit with its own template. Experimental results are provided and a comparative analysis is made with recently reported works. It has been found that the proposed scheme not only reduces the optical cost of a circuit but also brings down the total optical device utilization in the circuit.
Learning Time Series Detection Models from Temporally Imprecise Labels

In this paper, we consider the problem of learning time series detection models from temporally imprecise labels. In this problem, the data consist of a set of input time series, and supervision is provided by a sequence of noisy time stamps corresponding to the occurrence of positive class events. Such temporally imprecise labels occur in areas like mobile health research when human annotators are tasked with labeling the occurrence of very short duration events. We propose a general learning framework for this problem that can accommodate different base classifiers and noise models. We present results on real mobile health data showing that the proposed framework significantly outperforms a number of alternatives including assuming that the label time stamps are noise-free, transforming the problem into the multiple instance learning framework, and learning on labels that were manually aligned.
Representing Uncertainty in RTS Games by Björn Jónsson

Real-time strategy (RTS) games are partially observable environments, requiring players to reason under uncertainty. The main source of uncertainty in RTS games is that players do not initially know the game map, including what units the opponent has created. This information gradually improves, in part by exploring, as the game progresses. To compensate for this uncertainty, human players use their experience and domain knowledge to estimate the combination of units that opponents control, and make decisions based on these estimates. For RTS game AI to mimic this behavior of human players, a suitable knowledge representation is required. The order in which units can be created in RTS games is conditioned by a game specific technology tree where units represented by parent nodes in the tree need to be created before units represented by child nodes can be created. We propose the use of a Bayesian Network (BN) to represent the beliefs that RTS game AI players have about the expansion of the technology tree of their opponents. We implement a BN for the RTS game StarCraft R © and give several examples of its use. In particular, we evaluate our design by improving strategy prediction under uncertainty from previously reported work [37]. Using our BN, we are able to increase the precision of strategy prediction up to 56%. These results show that the proposed BN can be used to infer creation time values for unobserved units in RTS games and that BNs are a promising approach for RTS game AI to represent and reason with uncertainty in RTS games. Meðhöndlun óvissu í rauntíma herkænskuleikjum
Automatic face tracking system using quadrotors: Control by goal position thresholding

This paper proposes a human face tracking system for obtaining elderly people's facial images, which can be used to estimate their individual emotion. Quadrotors are used to overcome occlusion and obtain closer facial images, while Kinect sensors provide human detection and quadrotor navigation. Noise from the measured head position results in vibration of the goal position, and subsequently the quadrotor, which can cause blurred images and safety problem. In order to improve the stability of the quadrotor, we propose an algorithm using threshold to fix the quadrotor's goal position. Performance of the algorithm is evaluated by using the detected positions of the quadrotor and is compared with tracking without threshold algorithm, as well as with different threshold values. Based on these positions, face tracking results are also calculated by simulating projection of the face in real world onto the image plane and evaluating the quality of the obtained face.
Polyethylene terephthalate recycling for food-contact applications: testing, safety and technologies: a global perspective

Studies were undertaken to determine the composition of five different types of post-consumer polyethylene terephthalate (PET) feedstreams to ascertain the relative amounts of food containers and non-food containers. Deposit post-consumer PET feedstreams contained ~100% food containers, whereas curbside feedstreams contained from 0.04 to 6% non-food containers. Analysis of the PET containers from the different type feedstreams after the containers were subjected to a commercial PET wash system and after processing with a proprietary decontamination technology was accomplished to determine the levels of compounds in the post-consumer PET after the various stages of processing. Comprehensive thermal desorption/GC/MS, purge and trap GC/MS purge and trap GC quantitation, PET dissolution and extraction GC analysis and PET dissolution HPLC analysis established the types and concentrations of compounds that absorb in the PET from the various types of postconsumer feedstreams. A total of 121 compounds were identified in the five different feedstreams. The concentration of absorbed compounds remaining in the deposit material and the non-food applications material after the commercial wash was 28 and 39mgkg -1 respectively. Analysis of the feedstreams after subjecting the material to a proprietary decontamination process demonstrated the ability of removing all the absorbed compounds to a level below the level of the threshold of regulation. The safety of sourcing of post-consumer PET from food use applications verses non-food use applications of PET has been established.
A Power-Efficient Clustering Protocol for Coal Mine Face Monitoring with Wireless Sensor Networks Under Channel Fading Conditions

This study proposes a novel power-efficient and anti-fading clustering based on a cross-layer that is specific to the time-varying fading characteristics of channels in the monitoring of coal mine faces with wireless sensor networks. The number of active sensor nodes and a sliding window are set up such that the optimal number of cluster heads (CHs) is selected in each round. Based on a stable expected number of CHs, we explore the channel efficiency between nodes and the base station by using a probe frame and the joint surplus energy in assessing the CH selection. Moreover, the sending power of a node in different periods is regulated by the signal fade margin method. The simulation results demonstrate that compared with several common algorithms, the power-efficient and fading-aware clustering with a cross-layer (PEAFC-CL) protocol features a stable network topology and adaptability under signal time-varying fading, which effectively prolongs the lifetime of the network and reduces network packet loss, thus making it more applicable to the complex and variable environment characteristic of a coal mine face.
Computer-based assessment of the effects of amiodarone on short QT syndrome variant 1 in human ventricles

Short QT syndrome (SQTS) is a channelopathy associated with a short QT interval and an increased risk of arrhythmias. The SQT1 variant results from a gain-of-function mutation (N588K) in the KCNH2-encoded channels. Inherited arrhythmogenic effects of SQTS have been clearly characterized, while little is known about the pharmacological therapy for SQTS. Therefore, this paper assessed the effects of amiodarone, class III antiarrhythmic agent, on SQT1. The wild-type (WT) and N588K IKr Markov chain formulations were incorporated into human ventricular action potentials (APs). The modified cells were then integrated into one-dimensional (1D) and 2D tissues. The inhibitory effect of amiodarone on channels was modelled using half-maximal inhibitory concentration (IC50) and Hill coefficient (nH) values. Amiodarone prolonged the SQT1 ventricular cell AP duration (APD). Amiodarone caused a QT prolongation and a decrease in T-wave amplitude. Amiodarone decreased vulnerable window, and increased the critical size of ventricular substrates. Amiodarone terminated and prevented re-entrant waves. The actions of amiodarone exhibited in silico, that anti-arrhythmic effects on SQT1. Our data substantiate a causal link between amiodarone and QT interval prolongation, and offer an explanation for decreased vulnerability to re-entry and termination of re-entrant arrhythmias in SQT1.
From speech to letters - using a novel neural network architecture for grapheme based ASR

Main-stream automatic speech recognition systems are based on modelling acoustic sub-word units such as phonemes. Phonemisation dictionaries and language model based decoding techniques are applied to transform the phoneme hypothesis into orthographic transcriptions. Direct modelling of graphemes as sub-word units using HMM has not been successful. We investigate a novel ASR approach using Bidirectional Long Short-Term Memory Recurrent Neural Networks and Connectionist Temporal Classification, which is capable of transcribing graphemes directly and yields results highly competitive with phoneme transcription. In design of such a grapheme based speech recognition system phonemisation dictionaries are no longer required. All that is needed is text transcribed on the sentence level, which greatly simplifies the training procedure. The novel approach is evaluated extensively on the Wall Street Journal 1 corpus.
Morbidities and Hospital Resource Use During the First 3 Years of Life Among Very Preterm Infants

OBJECTIVE: The objective of this study was to determine how the use of hospital resources during the first 3 years of life was associated with prematurity-related morbidity in very preterm infants (gestational age of <32 weeks or birth weight of <1501 g). METHODS: The study was a retrospective, national register study including all very preterm infants born alive in Finland between 2000 and 2003 (N = 2148). Infants who died before the age of 3 years (n = 264) or who had missing register data (n = 88) were excluded from the study. The relationship between 6 morbidity groups and the need for hospital care during the first 3 years of life was studied by using a negative binomial model. RESULTS: A total of 66.2% of the infants did not have any of the morbidities studied. Infants who were subsequently diagnosed as having cerebral palsy (6.1% of the study group), later obstructive airway disease (20.0%), hearing loss (2.5%), visual disturbances or blindness (3.8%), or other ophthalmologic problems (13.4%) had initial hospital stays that were a mean of 7, 8, 12, 17, and 3 days longer, respectively, than those for infants without these conditions. All morbidity groups were associated with increased numbers of hospital visits during either the second or third year of life, compared with infants without these morbidities. The need for hospitalizations and outpatient hospital care decreased with postnatal age for infants with later morbidities and for infants without later morbidities. CONCLUSIONS: Most very preterm infants born in Finland survived without severe morbidities and required relatively little hospital care after the initial discharge. However, those with later morbidities had a long initial length of stay and more readmissions and outpatient visits during the 3-year follow-up period.
A multivariable robust controller for a pilot plant

In this paper, a pilot plant located at our laboratory is initially presented. The system consists of industrial components (a water tank, a resistor, pneumatic valves and a heat exchanger) and the main goal is to control some of its temperatures. Due to the high nonlinearity introduced by the heat exchanger, a model of the plant is obtained at an operating point and an analysis is made to obtain some properties of its controllability. Results of this analysis are used to synthesize a multivariable H∞ controller to keep robust the plant against disturbances and small changes of the operating point. The performance of the controller is finally presented with experimental results.
Blending Concept Extraction, Semantic Wikis and Ontologies for Text Analysis: The Luminary System

Automated text analysis encompasses a number of different techniques. However, applications frequently implement these techniques as single solutions, rather than creating an integrated environment that includes interaction and representation for the analyst. The Luminary system blends semantic reasoning, entity and concept extraction, entity co-referencing, and visualizations, all controlled by a governing domain ontology. It stores the results of its analysis in a semantic wiki, providing a familiar yet powerful user interface to analysts. At the same time, the wiki API enables the Luminary wiki to interact with automated processes. This innovative design enables analysts to modify the automated analysis process, review and correct inaccuracies in the results, collaborate with other analysts, perform sophisticated semantic queries, and publish analytical results.
Stress, the Stress System and the Role of Glucocorticoids

All living organisms have developed a highly conserved and regulatory system, the stress system, to cope with a broad spectrum of stressful stimuli that threaten, or are perceived as threatening, their dynamic equilibrium or homeostasis. This neuroendocrine system consists of the hypothalamic-pituitary-adrenal (HPA) axis and the locus caeruleus/norepinephrine-autonomic nervous system. In parallel with the evolution of the homeostasis and stress concepts from ancient Greek to modern medicine, significant advances in the field of neuroendocrinology have identified the physiologic biochemical effector molecules of the stress response. Glucocorticoids, the end-products of the HPA axis, play a fundamental role in the maintenance of both resting and stress-related homeostasis and, undoubtedly, influence the physiologic adaptive reaction of the organism against stressors. If the stress response is dysregulated in terms of magnitude and/or duration, homeostasis is turned into cacostasis with adverse effects on many vital physiologic functions, such as growth, development, metabolism, circulation, reproduction, immune response, cognition and behavior. A strong and/or long-lasting stressor may precipitate and/or cause many acute and chronic diseases. Moreover, stressors during pre-natal, post-natal or pubertal life may have a critical impact on our expressed genome. This review describes the central and peripheral components of the stress system, provides a comprehensive overview of the stress response, and discusses the role of glucocorticoids in a broad spectrum of stress-related diseases.
Observation of Magnetic Fields in Medium Carbon Low Alloy Steel JIS S45C under Point Contact Loading

In order to understand the phenomena caused by the contact stresses occurring within surface, non-destructive methods that can be related to contact conditions are necessary. The main purpose of this work is to study the relationship between magnetization location and direction, spherical Hertzian contact and changes in the magnetic field asymmetry. In the present work, we used a newly developed GaAs film sensor-equipped scanning Hall probe microscope (SHPM) and observed magnetic fields in tool steel plates before and after contact tests under 196N load, at room temperature in air. Medium carbon low alloy steels specimens (JIS S45C) were used in the experiments. Around the contact test area, changes in ‘S’ and ‘N’ poles generated by magnetization using a square magnet block were investigated.