Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation using Meta-texture Saliency

We address segmentation of an image into patches that have an underlying salient surface-roughness. Three intrinsic images are derived: reflectance, shading and meta- texture images. A constructive approach is proposed for computing a meta-texture image by preserving, equalizing and enhancing the underlying surface-roughness across color, brightness and illumination variations. We evaluate the performance on sample images and illustrate quantitatively that different patches of the same material, in an image, are normalized in their statistics despite variations in color, brightness and illumination. Finally, segmentation by line-based boundary-detection is proposed and results are provided and compared to known algorithms.
AdOpt: An Adaptive Optimization Framework for Large-scale Power Distribution Systems

Optimizing self-evolving and dynamically changing systems is a grand challenge. In order to apply optimizations almost all conventional optimization techniques require a runtime system model. However, system models and their solution techniques vary in their strengths and limitations. For a rigid system, a single system model is acceptable. But if the system is constantly changing its structure then a rigid model is not able to represent the system properly, resulting in an inefficient use of technique in some cases. Therefore, in this paper we propose a framework for an optimization engine that adapts the optimization technique based on the system state. The adaptation involves selection of techniques based on historical statistics and current data, and dynamic generation of a model at runtime. This runtime model is then used to apply a relevant optimization technique to find a desired optimization plan for the system. We have evaluated the proposed framework on an electricity distribution system. Our results show that the proposed framework is adaptable, fast and able to manage numerous situations.
The Journal of Systems and Software

We study the problem of scheduling tasks onto a heterogeneous multi-core processor platform for makespan minimization, where each cluster on the platform has a probability of failure governed by an exponential law and the processor platform has a thermal constraint speciﬁed by a peak temperature threshold. The goal of our work is to design algorithms that optimize makespan under the constraints of reliability and temperature. We ﬁrst provide a mixed-integer linear programming (MILP) formulation for assigning and scheduling independent tasks with reliability and temperature constraints on the heterogeneous platform to minimize the makespan. However, MILP takes exponential time to ﬁnish. We then propose a two-stage heuristic that determines the assignment, replication, operating frequency, and execution order of tasks to minimize the makespan while satisfying the real-time, reliability, and tem- perature constraints based on the analysis of the effects of task assignment on makespan, reliability, and temperature. We ﬁnally carry out extensive simulation experiments to validate our proposed MILP for- mulation and two-stage heuristic. Simulation results demonstrate that the proposed MILP formulation can achieve the best performance in reducing makespan among all the methods used in the comparison. The results also show that the proposed two-stage heuristic has a close performance as the representative existing approach ESTS and a better performance when compared to the representative existing approach RBSA, in terms of reducing makespan. In addition, the proposed two-stage heuristic has the highest feasibility as compared to RBSA and ESTS.
An Airborne Remote Sensing Image Mosaic Algorithm Based on Feature Points

This paper focuses on a image mosaic method based on feature points. Image registration and stitching are the key technology of image mosaic. Based on analysis of research, this paper selected a mosaic algorithm based on SIFT feature points which have a good scale and rotation invariant feature for further research. For the wrong matches because of the algorithm restriction, occlusion, sensor moves, or the symmetric structure of the scene itself, this paper introduces the RANSAC algorithm for precise matching. During the process of image stitching, this paper reaches the goal of image mosaic by using the Homography Matrix solved by RANSAC.
Automatic Detection of Answers to Research Questions from Medline Abstracts

Given a set of abstracts retrieved from a search engine such as Pubmed, we aim to automatically identify the claim zone in each abstract and then select the best sentence(s) from that zone that can serve as an answer to a given query. The system can provide a fast access mechanism to the most informative sentence(s) in abstracts with respect to the given query.
Creative Ways to Teach Arterial Blood Gas Interpretation

There are many creative ways to teach arterial blood gas interpretation. This article illustrates the use of the stepwise approach, tables, figures, case studies, illustrations, computer-based learning modules, and the tic-tac-toe approach. The authors recommend making several approaches available so students and new critical care nurses can choose the ones that work best for them.
Intracellular delivery of nanocarriers and targeting to subcellular organelles

Introduction: Recent trends in drug delivery indicate a steady increase in the use of targeted therapeutics to enhance the specific delivery of biologically active payloads to diseased tissues while avoiding their off-target effects. However, in most cases, the distribution of therapeutics inside cells and their targeting to intracellular targets still presents a formidable challenge. The main barrier to intracellular delivery is the translocation of therapeutic molecules across the cell membrane, and ultimately through the membrane of their intracellular target organelles. Another prerequisite for an efficient intracellular localization of active molecules is their escape from the endocytic pathway. Areas covered: Pharmaceutical nanocarriers have demonstrated substantial advantages for the delivery of therapeutics and offer elegant platforms for intracellular delivery. They can be engineered with both intracellular and organelle-specific targeting moieties to deliver encapsulated or conjugated cargoes to specific sub-cellular targets. In this review, we discuss important aspects of intracellular drug targeting and delivery with a focus on nanocarriers modified with various ligands to specifically target intracellular organelles. Expert opinion: Intracellular delivery affords selective localization of molecules to their target site, thus maximizing their efficacy and safety. The advent of novel nanocarriers and targeting ligands as well as exploration of alternate routes for the intracellular delivery and targeting has prompted extensive research, and promises an exciting future for this field.
Scan Matching in the Hough Domain

Scan matching is used as a building block in many robotic applications, for localization and simultaneous localization and mapping (SLAM). Although many techniques have been proposed for scan matching in the past years, more efficient and effective scan matching procedures allow for improvements of such associated problems. In this paper we present a new scan matching method that, exploiting the properties of the Hough domain, allows for combining advantages of dense scan matching algorithms with feature-based ones.
Perspectivism in Social Psychology: The Yin and Yang of Scientific Progress

Following William J. McGuire's model as a theorist and researcher, this resource brings together psychologists from Europe, Israel and North America offering new and emerging agendas for social cognition, under the common theme of perspectivist methodology and the study of thought systems. Additionally, the book offers a historical approach to the study of stereotyping and intergroup relations and uses language as an indicator of social psychological processes.
Linguistic Parsing of Lists in Structured Documents

This paper shows how taking document structure into account helps to improve the performance of linguistic parsing. We restrict our study to one specific structure in a single markup language: lists in HTML documents. First we establish a typology of lists based on a corpus study. Then, after describing a transformation process that creates documents with uniform list markup, we show how the list tags can be incorporated into a parsing system, and how they enhance performance at every level of parsing.
Offline Arabic Handwritten recognition system with dropout applied in Deep networks based-SVMs

As a machine learning algorithms, deep learning algorithms developed in recent years, have been successfully practiced in many fields of computer vision, like face recognition, object detection and image classification. These Deep algorithms look for drawing out a very performing representation of the data, among which image and speech, through multi-layers in a deep hierarchical structure. In this study, a deep learning model based on Support Vector Machine (SVM) named Deep SVM (DSVM) is represented. We applied the dropout technique on the Deep SVM (DSVM). It is worth noting that this model has an inherent capacity to choose data points crucial to classify good generalization capacities. The deep SVM is built by a stack of SVMs permitting to extracting/learning automatically features from the raw images and to realize classification, too. We chose and tested the Multi-class Support Vector Machine with an RBF kernel, as non-linear discriminative features for classification, on Handwritten Arabic Characters Database (HACDB). Further to these advantages, our model is safeguarded against over-fitting because of strong performance of dropout. Simulation outcomes prove the efficiency of the suggested model.
Understanding Information Adoption in Online Review Communities: The Role of Herd Factors

Online consumer reviews have shown as an important source of information that affects individuals' purchase decision making. To understand the influence of massive online reviews in online communities, this study extends prior research on information adoption by incorporating the perspective of herd behavior. We develop and empirically test a research model using data collected in an existing book review site. Our results illustrate two major aspects of findings. First, informational factors, including argument quality and source credibility, predict the adoption of online reviews. Second, we find strong empirical support for the impacts of herd factors, that is, discounting own information and imitating others posit significant influences on the adoption of online reviews. Our findings suggest that herd behavior plays an important role in consumers' information adoption in online review communities. Discussions on both theoretical and practical implications are provided.
Unsupervised abnormality detection using saliency and Retinex based color enhancement

An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm. In the first stage, an adaptive color enhancement method based on Retinex theory is applied on the endoscopic images. In the second stage, an efficient salient region detection algorithm is applied to detect the clinically significant regions. The proposed algorithm is applied on a dataset containing images with diverse pathologies. The algorithm can successfully detect a significant percentage of the abnormal regions. From our experiment, it was evident that color enhancement method improves the performance of abnormality detection. The proposed algorithm can achieve a sensitivity of 97.33% and specificity of 79%, higher than state-of-the-art performance.
The Impulsive Personality: Understanding People with Destructive Character Disorders

1 The Author's Premises. - Character Traits Can Change. - Treatment Is a Means of Changing Character. - Treatment and the Needs of the Individual. - Society's Unreasonable Expectations. - Social Pressures and Impulsive Behavior. - Staff Attitude and Impulsive Behavior. - Drug Addiction as a Manifestation of Impulsive Behavior. - Specific Premises about Drug-Addicted Impulsive Individuals. - 2 The Settings and the People. - Lexington. - The Composite Patient at Lexington. - A Psychiatric Hospital Setting. - An Outpatient Clinic for Drug Abusers. - 3 Character Disorders. - Personality Disorders. - Paranoid. - Schizoid. - Explosive. - Antisocial. - Passive-Aggressive. - Borderline Personalities. - Depression. - Low Self-Esteem. - Inability to Form Close Personal Relationships. - Manipulation. - Nonpsychotic Techniques of Avoidance. - Inability to Examine One's Own Behavior. - Action to Avoid Feeling. - Other People Are Unreal. - No Continuity in Patterns of Events. - Inability to Tolerate Criticism. - Inability to Plan. - Inability to Delay Gratification. - Entitlement. - No Experience Bearing Anxiety or Discomfort. - Self-Destruction. - Examples of Depression. - 4 Developmental Defect. - Normal Development. - Loss. - Reactions to the Loss. - Guilt and Conscience. - Inadequate Personal Relationships. - Summary. - 5 Games. - Kinds of Games. - Killing with Kindness. - Contracts. - Peace at Any Price. - Secret Deals. - Distractions. - "I'm No Racist". - Poor Communication. - Goal Disharmony. - "Uh, Huh,I Knew It AU Along". - Sliding by, or "I'm No Trouble". - Good Guy-Bad Guy, or Splitting. - Jailhouse Lawyer. - The Lame Game. - Forget the Past. - Sulk. - Stir Him Up. - Confrontation Avoidance. - Focus on the Specific to Avoid the General Issue. - A Rose by Any Other Name. - No Loss Allowed. - Do as I Say, Not as I Do. - Going Through the Motions. - False Optimism. - Summary. - 6 Violence. - Destructiveness Outside of Treatment. - The Inherent Nature of Violence. - 7 A Graphic Approach to Understanding Intrapersonal Processes. - 8 Treatment. - Preconceived Distortions. - Gaining the Patient's Attention. - Structure, Limits, Goals. - Transference-Countertransference. - "Different Strokes for Different Folks". - Alcohol. - Sedative-Hypnotic Addiction. - Opiates. - Treatment Modalities. - Conclusion.
Anthropometric and physiological characteristics of junior elite volleyball players

Objectives: To investigate the anthropometric and physiological characteristics of junior elite volleyball players. Method: Twenty five national level volleyball players (mean (SD) age 17.5 (0.5) years) were assessed on a number of physiological and anthropometric variables. Somatotype was assessed using the Heath-Carter method, body composition (% body fat, % muscle mass) was assessed using surface anthropometry, leg strength was assessed using a leg and back dynamometer, low back and hamstring flexibility was assessed using the sit and reach test, and the vertical jump was used as a measure of lower body power. Maximal oxygen uptake was predicted using the 20 m multistage fitness test. Results: Setters were more ectomorphic (p<0.05) and less mesomorphic (p<0.01) than centres. Mean (SD) of somatotype (endomorphy, mesomorphy, ectomorphy) for setters and centres was 2.6 (0.9), 1.9 (1.1), 5.3 (1.2) and 2.2 (0.8), 3.9 (1.1), 3.6 (0.7) respectively. Hitters had significantly greater low back and hamstring flexibility than opposites. Mean (SD) for sit and reach was 19.3 (8.3) cm for opposites and 37 (10.7) cm for hitters. There were no other significant differences in physiological and anthropometric variables across playing positions (all p>0.05). Conclusion: Setters tend to be endomorphic ectomorphs, hitters and opposites tend to be balanced ectomorphs, whereas centres tend to be ectomorphic mesomorphs. These results indicate the need for sports scientists and conditioning professionals to take the body type of volleyball players into account when designing individualised position specific training programmes.
The Lateral Asymmetry of the Human Brain Studied by Volumetric Magnetic Resonance Imaging

Improvements in in vivo imaging methods have boosted research on brain asymmetry aimed at further establishing putative anatomical substrates for brain functional lateralization and particularly to explain left-hemisphere specialization for language. We analyzed volume asymmetries for major anatomical divisions of the lateral (perisylvian) brain region and their relative white matter content. A total of 100 healthy right-handed subjects were examined with 3D magnetic resonance imaging (MRI). The insular plane was used to limit the lateral brain, and the sylvian fissure and central sulcus to define frontal, parietal, temporal, and temporo-parieto-occipital regions. Results revealed a frontal region showing similar volumes in both hemispheres, a parietal region and a temporal region both larger in the left hemisphere, and a temporo-parieto-occipital region with predominantly right-sided asymmetry. Volume measurements of the parietal, temporal, and temporo-parieto-occipital regions complemented each other and accounted for 58% of planum temporale area variations. All study regions showed significant asymmetry for relative white matter content (percentage of white matter relative to region volume). White matter asymmetry, however, was particularly relevant for the frontal and temporal regions showing a highly frequent left-sided pattern (frontal region, 90%; temporal region, 91% of subjects). Leftward asymmetry in these two regions occurred in both genders, although hemisphere differences were significantly larger in men. Results from this MRI volume analysis of structural asymmetries in the lateral brain region complement data obtained by other methods and suggest a high occurrence of leftward asymmetry for relative white matter content in language-related regions.
Effects of Advancing Age on Drivers` Cognitive Workload

ABSTRACT Driving is a complex psychomotor task often interrupted by secondary activities that increase cognitive workload and divert attention away from the roadway. The risk of inattentive driving is known to vary with age. To assess the characteristics of advancing age on driver's cognitive workload under dual task condition, we evaluate the performance of 96 drivers divided into three age groups: 20's, 40's, and 60's. This study considers driver's cognitive workload in the context of urban and highway driving. Error rate & Dual task cost are used to measure driver's cognitive workload. Results indicate that age impacts cognitive workload during dual task driving conditions. Keyword: Elderly Driver, Cognitive Resource, Dual Task, Distraction, Driving Workload 1. 서 론 우리나라는 2000년도에 65세 이상 인구가 전체 인구의 7%를 넘으면서 고령화 사회로 진입하였고, 2019년과 2026년에는 각각 고령 사회와 초고령 사회로 진입할 것으로 예상되고 있다. 특히, 고령화 사회에서 고령 사회로 진입하는 시기가 19년밖에 걸리지 않을 것으로 예상되며 주요 선진국과 비교하여 고령화가 훨씬 빠르게 진행되고 있다. 고령화가 진행되면서 1999년에서 2002년 사이에 61~ 70세 운전면허소지자는 16.8%, 71세 이상은 22.5%의 증가를 가져왔으며 전체 운전면허소지자의 증가율 6.8%를 크게 상회하고 있다. 따라서 고령 사회로 진입하는 과정에서 고령 운전자의 급격한 증가는 필연적일 것으로 예상되며 고령 운전자는 새로운 자동차 소비 주체로 성장할 것이다. 그러나 고령 운전자는 교통사고 발생률이 높은 문제점을 가지고 있다(Coughlin and Reimer, 2006). 한국도로교통안전관리공단의 조사에 따르면, 2006년 기준으로 61세 이상 고령 운전자의 교통사고율이 지속적으로 증가하는 것을 제시하고 있으며, 교통사고를 유발하는 요인 중에서 전방주시 태만, 판단 오류, 발견 지연과 같이 운전자 부주의에 의한 것이 약 69.1%에 해당하는 것을 나타내고 있다. 이러한 운전 부주의를 유발하는 대표적인 요인으로 휴대전화 통화와 내비게이션과 같은 차량편의 및 정보 기기의 조작을 들 수 있다(Stutts et al., 2003; Wang et al., 1996). 고령 운전자는 시력, 청력, 운동 기능 등 육체적 능력뿐만 아니라, 단기 기억력, 공간 지각력 등과 같은 인지적 능력도 동시에 떨어지게 된다(Malfetti, 1985). 이에 따라 고령
Inferences About the Distribution of Dominance Drawn From Yeast Gene Knockout Data

Data from several thousand knockout mutations in yeast (Saccharomyces cerevisiae) were used to estimate the distribution of dominance coefficients. We propose a new unbiased likelihood approach to measuring dominance coefficients. On average, deleterious mutations are partially recessive, with a mean dominance coefficient ∼0.2. Alleles with large homozygous effects are more likely to be more recessive than are alleles of weaker effect. Our approach allows us to quantify, for the first time, the substantial variance and skew in the distribution of dominance coefficients. This heterogeneity is so great that many population genetic processes analyses based on the mean dominance coefficient alone will be in substantial error. These results are applied to the debate about various mechanisms for the evolution of dominance, and we conclude that they are most consistent with models that depend on indirect selection on homeostatic gene expression or on the ability to perform well under periods of high demand for a protein.
Maize Mutants Lacking Chloroplast FtsY Exhibit Pleiotropic Defects in the Biogenesis of Thylakoid Membranes Online version contains Web-only data. Article, publication date, and citation information can be found at www.plantcell.org/cgi/doi/10.1105/tpc.014787.

A chloroplast signal recognition particle (SRP) that is related to the SRP involved in secretion in bacteria and eukaryotic cells is used for the insertion of light-harvesting chlorophyll proteins (LHCPs) into the thylakoid membranes. A conserved component of the SRP mechanism is a membrane-bound SRP receptor, denoted FtsY in bacteria. Plant genomes encode FtsY homologs that are targeted to the chloroplast (cpFtsY). To investigate the in vivo roles of cpFtsY, we characterized maize cpFtsY and maize mutants having a Mu transposon insertion in the corresponding gene (chloroplast SRP receptor1, or csr1). Maize cpFtsY accumulates to much higher levels in leaf tissue than in roots and stems. Interestingly, it is present at similar levels in etiolated and green leaf tissue and was found to bind the prolamellar bodies of etioplasts. A null cpFtsY mutant, csr1-1, showed a substantial loss of leaf chlorophyll, whereas a “leaky” allele, csr1-3, conditioned a more moderate chlorophyll deficiency. Both alleles caused the loss of various LHCPs and the thylakoid-bound photosynthetic enzyme complexes and were seedling lethal. By contrast, levels of the membrane-bound components of the thylakoid protein transport machineries were not altered. The thylakoid membranes in csr1-1 chloroplasts were unstacked and reduced in abundance, but the prolamellar bodies in mutant etioplasts appeared normal. These results demonstrate the essentiality of cpFtsY for the biogenesis not only of the LHCPs but also for the assembly of the other membrane-bound components of the photosynthetic apparatus.
Plant biomechanics and mechanobiology are convergent paths to flourishing interdisciplinary research.

Over recent decades, there has been a real renaissance of interest in how inner and outer mechanical forces influence biological systems at all scales from macromolecules up to functional ecology. Many areas of animal and medical science are being reshaped by considering biomechanical and mechanobiological aspects, like stiffness-driven differentiation of stem cells, embryo development, tumour invasion, bone and cartilage adaptation, cardiac and arterial remodelling, brain neurobiology, touch and haptics, motion control, and proprioception (e.g. Discher et al., 2005; Stoltz et al., 2005, Boccafoschi et al., 2013; Bukoreshtliev et al., 2013). The same is true and no less impressive in plant sciences where researchers continue to be fascinated by the features that plants have evolved in order to grow and sense, withstand, acclimate, and adapt to the mechanical challenges they face. But what are the major frontiers in plant biomechanics and mechanobiology, the hotspots where physical and biological disciplines cross over? Is this really a new field or can we trace it back in time, and if so, how far? And what exactly do the seemingly mirror-image names biomechanics and mechanobiology mean?