Miracle-dz/UniFAR-FTUs huggingface dataset:
An Adaptive Learning Approach for 3-D Surface Reconstruction From Point Clouds

In this paper, we propose a multiresolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3-D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen's self-organizing map (SOM). Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multiresolution, iterative scheme. Reconstruction was experimented on with several point sets, including different shapes and sizes. Results show generated meshes very close to object final shapes. We include measures of performance and discuss robustness.
Therapeutic Aspects of Funeral Ritual: A Thematic Analysis

The experience of significant funeral rituals for 32 adult bereaved individuals was examined in an intensive interview study. Intewiewees had lost either a spouse or a parent. Structured and open-ended questions were asked regarding the funeral experience. Thematic analysis of the narrative data revealed five prevalent themes with corresponding meta-themes. A review of these themes suggests the therapeutic use of a narrative approach to grieving individuals in the process of reconciliation of the loss.
AMPK α1 Activation Is Required for Stimulation of Glucose Uptake by Twitch Contraction, but Not by H2O2, in Mouse Skeletal Muscle

Background AMPK is a promising pharmacological target in relation to metabolic disorders partly due to its non-insulin dependent glucose uptake promoting role in skeletal muscle. Of the 2 catalytic α-AMPK isoforms, α2 AMPK is clearly required for stimulation of glucose transport into muscle by certain stimuli. In contrast, no clear function has yet been determined for α1 AMPK in skeletal muscle, possibly due to α-AMPK isoform signaling redundancy. By applying low-intensity twitch-contraction and H2O2 stimulation to activate α1 AMPK, but not α2 AMPK, in wildtype and α-AMPK transgenic mouse muscles, this study aimed to define conditions where α1 AMPK is required to increase muscle glucose uptake. Methodology/Principal Findings Following stimulation with H2O2 (3 mM, 20 min) or twitch-contraction (0.1 ms pulse, 2 Hz, 2 min), signaling and 2-deoxyglucose uptake were measured in incubated soleus muscles from wildtype and muscle-specific kinase-dead AMPK (KD), α1 AMPK knockout or α2 AMPK knockout mice. H2O2 increased the activity of both α1 and α2 AMPK in addition to Akt phosphorylation, and H2O2-stimulated glucose uptake was not reduced in any of the AMPK transgenic mouse models compared with wild type. In contrast, twitch-contraction increased the activity of α1 AMPK, but not α2 AMPK activity nor Akt or AS160 phosphorylation. Glucose uptake was markedly lower in α1 AMPK knockout and KD AMPK muscles, but not in α2 AMPK knockout muscles, following twitch stimulation. Conclusions/Significance These results provide strong genetic evidence that α1 AMPK, but not α2 AMPK, Akt or AS160, is necessary for regulation of twitch-contraction stimulated glucose uptake. To our knowledge, this is the first report to show a major and essential role of α1 AMPK in regulating a physiological endpoint in skeletal muscle. In contrast, AMPK is not essential for H2O2-stimulated muscle glucose uptake, as proposed by recent studies.
DFKI: Multi-objective Optimization for the Joint Disambiguation of Entities and Nouns & Deep Verb Sense Disambiguation

We introduce an approach to word sense disambiguation and entity linking that combines a set of complementary objectives in an extensible multi-objective formalism. During disambiguation the system performs continuous optimization to find optimal probability distributions over candidate senses. Verb senses are disambiguated using a separate neural network model. Our results on noun and verb sense disambiguation as well as entity linking outperform all other submissions on the SemEval 2015 Task 13 for English.
Patterns of Early Gut Colonization Shape Future Immune Responses of the Host

The most important trigger for immune system development is the exposure to microbial components immediately after birth. Moreover, targeted manipulation of the microbiota can be used to change host susceptibility to immune-mediated diseases. Our aim was to analyze how differences in early gut colonization patterns change the composition of the resident microbiota and future immune system reactivity. Germ-free (GF) mice were either inoculated by single oral gavage of caecal content or let colonized by co-housing with specific pathogen-free (SPF) mice at different time points in the postnatal period. The microbiota composition was analyzed by denaturing gradient gel electrophoresis for 16S rRNA gene followed by principal component analysis. Furthermore, immune functions and cytokine concentrations were analyzed using flow cytometry, ELISA or multiplex bead assay. We found that a single oral inoculation of GF mice at three weeks of age permanently changed the gut microbiota composition, which was not possible to achieve at one week of age. Interestingly, the ex-GF mice inoculated at three weeks of age were also the only mice with an increased pro-inflammatory immune response. In contrast, the composition of the gut microbiota of ex-GF mice that were co-housed with SPF mice at different time points was similar to the gut microbiota in the barrier maintained SPF mice. The existence of a short GF postnatal period permanently changed levels of systemic regulatory T cells, NK and NKT cells, and cytokine production. In conclusion, a time window exists that enables the artificial colonization of GF mice by a single oral dose of caecal content, which may modify the future immune phenotype of the host. Moreover, delayed microbial colonization of the gut causes permanent changes in the immune system.
Blink and It's Done: Interactive Queries on Very Large Data

In this demonstration, we present BlinkDB, a massively parallel, sampling-based approximate query processing framework for running interactive queries on large volumes of data. The key observation in BlinkDB is that one can make reasonable decisions in the absence of perfect answers. BlinkDB extends the Hive/HDFS stack and can handle the same set of SPJA (selection, projection, join and aggregate) queries as supported by these systems. BlinkDB provides real-time answers along with statistical error guarantees, and can scale to petabytes of data and thousands of machines in a fault-tolerant manner. Our experiments using the TPC-H benchmark and on an anonymized real-world video content distribution workload from Conviva Inc. show that BlinkDB can execute a wide range of queries up to 150x faster than Hive on MapReduce and 10--150x faster than Shark (Hive on Spark) over tens of terabytes of data stored across 100 machines, all with an error of 2--10%.
Gender and the Wage Gap in Turkish Academia

Turkey maintains one of the lowest female labour force participation rates in Europe, but also boasts an above average number of female professors. Turkey is well above the European average (15 per cent) with approximately 28 per cent of full professorships being occupied by women. Despite these seemingly positive indications, do men and women in Turkish academia earn the same wages? This study explores whether or not there exists a gendered pay gap in Turkish academia. Using data collected from a survey of more than 700 Turkish academics, we observed that there is a gendered wage gap that disadvantages women, but only at the highest pay levels found at private universities indicating the existence of intra-class inequality, where men and women despite occupying the same class position are compensated differently.
Fault diagnosis based on the structure information of partially observed Petri nets

In this paper, we present a fault diagnosis approach for a class of partially observed Petri nets using its structure information. With a novel graph named Diagnosis Marking Path Graph (DMPG), the proposed method does not need traverse all states of the discrete event system. For the considered Petri net, some of its transitions are unobservable including all the transitions representing faulty behaviors. In particular, a concept of diagnosis node is firstly defined. Then three diagnosis states of faults are presented based on the analysis of a DMPG, which is computed depending on the structure information of Petri nets. Finally, the validity of the method is illustrated using an example.
Cross-Lingual Syntactically Informed Distributed Word Representations

We develop a novel cross-lingual word representation model which injects syntactic information through dependency-based contexts into a shared cross-lingual word vector space. The model, termed CL-DepEmb, is based on the following assumptions: (1) dependency relations are largely language-independent, at least for related languages and prominent dependency links such as direct objects, as evidenced by the Universal Dependencies project; (2) word translation equivalents take similar grammatical roles in a sentence and are therefore substitutable within their syntactic contexts. Experiments with several language pairs on word similarity and bilingual lexicon induction, two fundamental semantic tasks emphasising semantic similarity, suggest the usefulness of the proposed syntactically informed cross-lingual word vector spaces. Improvements are observed in both tasks over standard cross-lingual “offline mapping” baselines trained using the same setup and an equal level of bilingual supervision.
Review of meta-analyses evaluating surrogate endpoints for overall survival in oncology

Overall survival (OS) is the gold standard in measuring the treatment effect of new drug therapies for cancer. However, practical factors may preclude the collection of unconfounded OS data, and surrogate endpoints are often used instead. Meta-analyses have been widely used for the validation of surrogate endpoints, specifically in oncology. This research reviewed published meta-analyses on the types of surrogate measures used in oncology studies and examined the extent of correlation between surrogate endpoints and OS for different cancer types. A search was conducted in October 2010 to compile available published evidence in the English language for the validation of disease progression-related endpoints as surrogates of OS, based on meta-analyses. We summarize published meta-analyses that quantified the correlation between progression-based endpoints and OS for multiple advanced solid-tumor types. We also discuss issues that affect the interpretation of these findings. Progression-free survival is the most commonly used surrogate measure in studies of advanced solid tumors, and correlation with OS is reported for a limited number of cancer types. Given the increased use of crossover in trials and the availability of second-/third-line treatment options available to patients after progression, it will become increasingly more difficult to establish correlation between effects on progression-free survival and OS in additional tumor types.
Staphylococcus aureus synthesizes adenosine to escape host immune responses

Staphylococcus aureus infects hospitalized or healthy individuals and represents the most frequent cause of bacteremia, treatment of which is complicated by the emergence of methicillin-resistant S. aureus. We examined the ability of S. aureus to escape phagocytic clearance in blood and identified adenosine synthase A (AdsA), a cell wall–anchored enzyme that converts adenosine monophosphate to adenosine, as a critical virulence factor. Staphylococcal synthesis of adenosine in blood, escape from phagocytic clearance, and subsequent formation of organ abscesses were all dependent on adsA and could be rescued by an exogenous supply of adenosine. An AdsA homologue was identified in the anthrax pathogen, and adenosine synthesis also enabled escape of Bacillus anthracis from phagocytic clearance. Collectively, these results suggest that staphylococci and other bacterial pathogens exploit the immunomodulatory attributes of adenosine to escape host immune responses.
That was fast! Speeding up NN search of high dimensional distributions

We present a data structure for fast nearest neighbor retrieval of generative models of documents based on Kullback-Leibler (KL) divergence. Our data structure, which shares some similarity with Bregman Ball Trees, consists of a hierarchical partition of a database, and uses a novel branch and bound methodology for search. The main technical contribution of the paper is a novel and efficient algorithm for deciding whether to explore nodes during backtracking, based on a variational approximation. This reduces the number of computations per node, and overcomes the limitations of Bregman Ball Trees on high dimensional data. In addition, our strategy is applicable also to probability distributions with hidden state variables, and is not limited to regular exponential family distributions. Experiments demonstrate substantial speedups over both Bregman Ball Trees and over brute force search, on both moderate and high dimensional histogram data. In addition, experiments on linear dynamical systems demonstrate the flexibility of our approach to latent variable models.
Security in Offloading Computations inMobile Systems Using Cloud Computing

The progression in the technology has made very essential devices of such as aerial phones of late 80’s and Pentium 4 processor into today’s stock. None of them is comparable to the power of smart phones of this generation whose recent market has been reached its unbelievable height. We browse the Internet, send emails, organize our lives, watch videos, upload data on social networks, use online banking, find our way by using GPS and online maps, and communicate in revolutionary ways through smart phones. Many new apps are emerging at an incredible manner. We felt enthusiastic while using smart phones by installing and handling new apps, but less happy with the battery lifetime. Energy efficiency is the fundamental consideration for the mobile system. Cloud computing has the potential to save mobile client energy. But the savings from offloading the computations need to exceed the energy cost of the additional communication. If the apps are more computational intensive they can be offloaded or else they can be run in the mobile system itself. Offloading can be done from mobile system to grid-powered servers where computations are performed. Offloading depends on various parameters such as energy consumption and bandwidth. Offloading, however, causes privacy concerns because sensitive data may be sent to servers. The privacy can be protected by using two techniques such as Encryption of data and Steganography in computation offloading
Invitation to Psychology

1. What Is Psychology? The Science of Psychology. What Psychologists Do. Critical and Scientific Thinking in Psychology. Descriptive Studies: Establishing the Facts. Correlational Studies: Looking for Relationships. The Experiment: Hunting for Causes. Evaluating the Findings. I. YOUR SELF. 2. Theories of Personality. Psychodynamic Theories of Personality. The Modern Study of Personality. The Genetic Contribution. Environmental Influences on Personality. Cultural Influences on Personality. The Inner Experience. 3. Development over the Life Span. From Conception Through the First Year. Cognitive Development. Moral Development. Gender Development. Adolescence. Adulthood. Are Adults Prisoners of Childhood? II. YOUR BODY. 4. Neurons, Hormones, and the Brain. The Nervous System: A Basic Blueprint. Communication in the Nervous System. Mapping the Brain. A Tour Through the Brain. The Two Hemispheres of the Brain. Two Stubborn Issues in Brain Research. 5. Consciousness: Body Rhythms and Mental States. Biological Rhythms: The Tides of Experience. The Rhythms of Sleep. Exploring the Dream World. The Riddle of Hypnosis. Consciousness-Altering Drugs. 6. Sensation and Perception. Our Sensational Senses. Vision. Hearing. Other Senses. The Mystery of Pain. Perceptual Powers: Origins and Influences. Puzzles of Perception. III. YOUR MIND. 7. Thinking and Intelligence. Thought: Using What We Know. Reasoning Rationally. Barriers to Reasoning Rationally. Intelligence. The Origins of Intelligence. Animal Minds. 8. Memory. Reconstructing the Past. Memory and the Power of Suggestion. In Pursuit of Memory. The Three-Box Model of Memory. How We Remember. Why We Forget. Autobiographical Memories. IV. YOUR ENVIRONMENT. 9. Learning. Classical Conditioning. Classical Conditioning in Real Life. Operant Conditioning. Operant Conditioning in Real Life. Learning and the Mind. 10. Behavior in Social and Cultural Context. Roles and Rules. Social Influences on Beliefs. Individuals in Groups. Us Versus Them: Group Identity. Group Conflict and Prejudice. V. YOUR MENTAL HEALTH. 11. Psychological Disorders. Defining and Diagnosing Disorder. Anxiety Disorders. Mood Disorders. Personality Disorders. Drug Abuse and Addiction. Dissociative Identity Disorder. Schizophrenia. 12. Approaches to Treatment and Therapy. Biological Treatments for Mental Disorders. Kinds of Psychotherapy. Evaluating Psychotherapy. VI. YOUR LIFE. 13. Emotion, Stress, and Health. The Nature of Emotion. Emotion and Culture. The Nature of Stress. Stress and Emotion. Emotions, Stress, and Health: How to Cope. 14. The Major Motives of Life: Love, Sex, Food, and Work. The Social Animal: Motives for Love. The Erotic Animal: Motives for Sex. The Hungry Animal: Motives to Eat. The Competent Animal: Motives to Achieve. Motives, Values and Well-Being. Appendix: Statistical Methods.
Understanding children's epistemic beliefs in elementary education

Research shows that the beliefs individuals hold about knowledge and knowing (epistemic beliefs) influence learning approaches and outcomes. However, little is known about the nature of children's epistemic beliefs and how best to measure these. In this pilot study, 11 Australian children (in Grade 4 or Grade 6) were asked to ‘draw, write and tell’ about their epistemic beliefs using drawings, written responses and interviews, respectively. Drawings were analysed, with the majority of children depicting external, one-way sources of knowledge. The written statements and interviews were analysed using inductive thematic analysis, showing that children predominantly described knowledge acquisition as processes of task-based learning. Interviews also enabled children to describe a wider range of views. These results indicate that the methodological combination of ‘draw, write and tell’ allowed for a deeper understanding of the children's epistemic beliefs which holds implications for future research.
Health effect of human wastes use in agriculture in El Azzouzia (the wastewater spreading area of Marrakesh city, Morocco)

The use of wastewater and excreta in agriculture constitutes an important source of spread Salmonella strains and protozoan infections into the environment. This practice has been used in El Azzouzia (the wastewater-spreading area of Marrakesh city, Morocco) for several years. The available circumstantial evidence gained from epidemiological and microbiological investigations suggests that the use of untreated wastewater causes an excess of protozoan infections among children living in El Azzouzia (72%) compared with those from a control area (45%). The pathogenic protozoan infections observed were giardiasis (39%) and amoebiasis (28%). For Salmonella infection, 21.34% of the exposed children were infected, while this rate did not exceed 1.14% in the control group. The serogroups B and C were the most commonly isolated. The sewage farming children are therefore more exposed to detectable risk from pathogenic micro-organisms than the control children.
Mining roles with noisy data

There has been increasing interest in automatic techniques for generating roles for role based access control, a process known as role mining. Most role mining approaches assume the input data is clean, and attempt to optimize the RBAC state. We examine role mining with noisy input data and suggest dividing the problem into two steps: noise removal and candidate role generation. We introduce an approach to use (non-binary) rank reduced matrix factorization to identify noise and experimentally show that it is effective at identifying noise in access control data. User- and permission-attributes can further be used to improve accuracy. Next, we show that our two-step approach is able to find candidate roles that are close to the roles mined from noise-less data. This method performs better than the approach of mining noisy data directly and offering the administrator increased control in the noise removal and candidate role generation phases. We note that our approach is applicable outside role engineering and may be used to identify errors or predict missing values in any access control matrix.
Estimating the Laplace‐Beltrami Operator by Restricting 3D Functions

We present a novel approach for computing and solving the Poisson equation over the surface of a mesh. As in previous approaches, we define the Laplace‐Beltrami operator by considering the derivatives of functions defined on the mesh. However, in this work, we explore a choice of functions that is decoupled from the tessellation. Specifically, we use basis functions (second‐order tensor‐product B‐splines) defined over 3D space, and then restrict them to the surface. We show that in addition to being invariant to mesh topology, this definition of the Laplace‐Beltrami operator allows a natural multiresolution structure on the function space that is independent of the mesh structure, enabling the use of a simple multigrid implementation for solving the Poisson equation.
Particle Swarm Optimization Based Clustering of Web Usage Data

Web session clustering is one of the important Web usage mining techniques which aims to group usage sessions on the basis of some similarity measures. In this paper we describe a new Web session clustering algorithm that uses particle swarm optimization. We review the existing Web usage clustering techniques and propose a swarm intelligence based PSO-clustering algorithm for the clustering of Web user sessions. The proposed algorithm works independently without hybridization with any other clustering algorithm. The results show that our approach performs better than the benchmark k-means clustering algorithm for clustering Web usage sessions.
Gaps in service in the recognition and treatment of depression and suicidal ideation within a four-county area.

PURPOSE To examine gaps in service in the treatment of depression and suicidal ideation. METHODS A phenomenological investigation of clients' (n = 10) and service providers' (n = 40) perspectives. FINDINGS Compartmentalized systems of care and lack of continuity between inpatient and outpatient treatment contributed to a sense of frustration in both groups. Receiving mental health care was likened to being given a broken-apart puzzle with individual pieces shuffling around in a box. Little bits of help are available, but none of them mesh. CONCLUSIONS Comprehensive solutions are needed if the human and social implications of depression are to be addressed.
The Psychopathology of Everyday Life

It is filled with anecdotes, many of them quite amusing, and virtually bereft of technical terminology. And Freud put himself on the line: numerous acts of willful forgetting or "inexplicable" mistakes are recounted from his personal experience. none of such actions can be called truly accidental, or uncaused: that is the real lesson of the Psychopathology.