Miracle-dz/UniFAR-FTUs huggingface dataset:
Silhouette rendering based on stability measurement

A better silhouette for a mesh can be rendered if we take into account the stability of edges inside and outside the current silhouette. Using the dot product between the normal and the viewing direction we can measure this stability. This gives us two types of edges: silhouette and non-silhouette and an associated stability of each. We apply this classification and stability measure to achieve several different styles of rendering as well as temporal frame coherence.
Gene expression A friendly statistics package for microarray analysis

Summary: The friendly statistics package for microarray analysis (FSPMA) is a tool that aims to fill the gap between simple to use and powerful analysis. FSPMA is a platform-independent R-package that allows efficient exploration ofmicroarray datawithout the need for computer programming. Analysis is based on amixedmodel ANOVA library (YASMA) that was extended to allow more flexible comparisons and other useful operations like k nearest neighbour imputing and spikebased normalization. Processing is controlled by a definition file that specifies all the steps necessary to derive analysis results from quantifiedmicroarray data. In addition to providinganalysiswithout programming, the definition file also serves as exact documentation of all the analysis steps. Availability: The library is available under GPL 2 license and, together with additional information, provided at http://www.ccbi. cam.ac. uk/ software/psyk/software.html#fspma Contact: peter@sykacek.net
2016 Ieee International Conference on Big Data (big Data) Wisdom: Weighted Incremental Spatio-temporal Multi-task Learning via Tensor Decomposition

—This paper presents a novel multi-task learning framework for the accurate prediction of spatio-temporal data at multiple locations. The framework encodes the data as a third-order tensor and performs supervised tensor decomposition to identify the latent factors that capture the inherent spatio-temporal variabilities of the data and their relationship to the target variable of interest. The framework is unique in that it trains both spatial and temporal prediction models from the latent factors of the decomposed tensor and aggregates their outputs to generate its final prediction. The latent factors and model parameters are simultaneously estimated by optimizing a joint objective function. We also develop an incremental learning algorithm called WISDOM to efficiently solve the optimization problem, in which the model is gradually updated with new data, either from a previously unobserved location or from its most recent time period. WISDOM can also incorporate known patterns from the application domain to guide the tensor decomposition. Finally, we showed that WISDOM outperforms several baseline algorithms in more than 75% of the locations when applied to a global-scale climate data.
Computational model of cell positioning: directed and collective migration in the intestinal crypt epithelium

The epithelium of the intestinal crypt is a dynamic tissue undergoing constant regeneration through cell growth, cell division, cell differentiation and apoptosis. How the epithelial cells maintain correct positioning and how they migrate in a directed and collective fashion are still not well understood. In this paper, we developed a computational model to elucidate these processes. We show that differential adhesion between epithelial cells, caused by the differential activation of EphB receptors and ephrinB ligands along the crypt axis, is necessary to regulate cell positioning. Differential cell adhesion has been proposed previously to guide cell movement and cause cell sorting in biological tissues. The proliferative cells and the differentiated post-mitotic cells do not intermingle as long as differential adhesion is maintained. We also show that, without differential adhesion, Paneth cells are randomly distributed throughout the intestinal crypt. In addition, our model suggests that, with differential adhesion, cells migrate more rapidly as they approach the top of the intestinal crypt. Finally, by calculating the spatial correlation function of the cell velocities, we observe that differential adhesion results in the differentiated epithelial cells moving in a coordinated manner, where correlated velocities are maintained at large distances, suggesting that differential adhesion regulates coordinated migration of cells in tissues.
Regulation of microRNA expression in the neuronal stem cell niches during aging of the short-lived annual fish Nothobranchius furzeri

In the last decade, our group has intensively studied the annual fish Nothobranchius furzeri as a new experimental model in Biology specifically applied to aging research. We previously studied adult neuronal stem cells of N. furzeri in vivo and we demonstrated an age-dependent decay in adult neurogenesis. More recently we identified and quantified the expression of miRNAs in the brain of N. furzeri and we detected 165 conserved miRNAs and found that brain aging in this fish is associated with coherent up-regulation of well-known tumor suppressor miRNAs, as well as down-regulation of well-known onco miRNAs~– In the present work we characterized the expression of miR-15a, miR-20a, and microRNA cluster 17–92 in the principal neurogenic niches of the brain of young and old subjects of N. furzeri, by using in situ hybridization techniques, together with proliferating-cell nuclear antigen immuno-staining for a simultaneous visualization of the neuronal progenitors. We found that: (1) the expression of miR-15a is higher in the brain of old subjects and concentrates mainly in the principal neurogenic niches of telencephalon and optic tectum, (2) the expression of miR-20a is higher in the brain of young subjects, but more widespread to the areas surrounding the neurogenic niches, (3) finally, the expression of the microRNA cluster 17–92 is higher in the brain of young subjects, concentrated mainly in the principal neurogenic niches of telencephalon and cerebellum, and with reduced intensity in the optic tectum. Taken together, our data show that these microRNAs, originally identified in whole-brain analysis, are specifically regulated in the stem cell niche during aging.
A flexible format for exchanging pulsar data

We describe a data format currently in use amongst European institutions for exchanging and archiv- ing pulsar data. The format is designed to be as flexible as possible with regard to present and future compatibil- ity with dierent operating systems. One application of the common format is simultaneous multi-frequency ob- servations of single pulses. A data archive containing over 2500 pulse proles stored in this format is now available via the Internet, together with a small suite of computer programs that can read, write and display the data.
Role of Leadership Competencies and Team Social Capital in it Services

As the nature of work changes into team-based knowledge work, the social capital among team members becomes more and more critical. This study applies social capital theory to IT service team environment. The research model of this study includes emotional, cognitive, and social intelligence competencies of project managers (PM) as they lead to the project performance, while team social capital is posited as a mediator between these leadership competencies and team project performance. A PLS analysis of 285 data points collected via a validated questionnaire revealed the followings: (1) emotional intelligence competencies of PM directly influence the project performance, (2) social intelligence competencies of PM indirectly influence project performance only via team social capital, and (3) cognitive intelligence competencies of PM maintains direct influence on project performance in shorter term projects, but indirect influence only via the accumulated team social capital in longer term projects. The analysis also reveals that it takes time to grow team social capital. Implications of the findings are discussed, and further studies are suggested.
Synthesis from Knowledge-Based Speci(cid:12)cations ?

In program synthesis, we transform a speci(cid:12)cation into a program that is guaranteed to satisfy the speci(cid:12)cation. In synthesis of reactive systems, the environment in which the program operates may behave nondeterministically, e.g., by generating di(cid:11)erent sequences of inputs in di(cid:11)erent runs of the system. To satisfy the speci(cid:12)cation, the program needs to act so that the speci(cid:12)cation holds in every computation generated by its interaction with the environment. Often, the program cannot observe all attributes of its environment. In this case, we should transform a speci(cid:12)cation into a program whose behavior depends only on the observable history of the computation. This is called synthesis with incomplete information. In such a setting, it is desirable to have a knowledge-based speci(cid:12)cation, which can refer to the uncertainty the program has about the environment's behavior. In this work we solve the problem of synthesis with incomplete information with respect to speci(cid:12)cations in the logic of knowledge and time. We show that the problem has the same worst-case complexity as synthesis with complete information.
Kernel-based Behavior Analysis for Android Malware Detection

The most major threat of Android users is malware infection via Android application markets. In case of the Android Market, as security inspections are not applied for many users have uploaded applications. Therefore, malwares, e.g., Geimini and Droid Dream will attempt to leak personal information, getting root privilege, and abuse functions of the smart phone. An audit framework called log cat is implemented on the Dalvik virtual machine to monitor the application behavior. However, only the limited events are dumped, because an application developers use the log cat for debugging. The behavior monitoring framework that can audit all activities of applications is important for security inspections on the market places. In this paper, we propose a kernel-base behavior analysis for android malware inspection. The system consists of a log collector in the Linux layer and a log analysis application. The log collector records all system calls and filters events with the target application. The log analyzer matches activities with signatures described by regular expressions to detect a malicious activity. Here, signatures of information leakage are automatically generated using the smart phone IDs, e.g., phone number, SIM serial number, and Gmail accounts. We implement a prototype system and evaluate 230 applications in total. The result shows that our system can effectively detect malicious behaviors of the unknown applications.
Spatial queries in dynamic environments

Conventional spatial queries are usually meaningless in dynamic environments since their results may be invalidated as soon as the query or data objects move. In this paper we formulate two novel query types, time parameterized and continuous queries, applicable in such environments. A time-parameterized query retrieves the actual result at the time when the query is issued, the expiry time of the result given the current motion of the query and database objects, and the change that causes the expiration. A continuous query retrieves tuples of the form <result, interval>, where each result is accompanied by a future interval, during which it is valid. We study time-parameterized and continuous versions of the most common spatial queries (i.e., window queries, nearest neighbors, spatial joins), proposing efficient processing algorithms and accurate cost models.
Defending Grey Attacks by Exploiting Wavelet Analysis in Collaborative Filtering Recommender Systems

"Shilling" attacks or "profile injection" attacks have always major challenges in collaborative filtering recommender systems (CFRSs). Many efforts have been devoted to improve collaborative filtering techniques which can eliminate the "shilling" attacks. However, most of them focused on detecting push attack or nuke attack which is rated with the highest score or lowest score on the target items. Few pay attention to grey attack when a target item is rated with a lower or higher score than the average score, which shows a more hidden rating behavior than push or nuke attack. In this paper, we present a novel detection method to make recommender systems resistant to such attacks. To characterize grey ratings, we exploit rating deviation of item to discriminate between grey attack profiles and genuine profiles. In addition, we also employ novelty and popularity of item to construct rating series. Since it is difficult to discriminate between the rating series of attacker and genuine users, we incorporate into discrete wavelet transform (DWT) to amplify these differences based on the rating series of rating deviation, novelty and popularity, respectively. Finally, we respectively extract features from rating series of rating deviation-based, novelty-based and popularity-based by using amplitude domain analysis method and combine all clustered results as our detection results. We conduct a list of experiments on both the Book-Crossing and HetRec-2011 datasets in diverse attack models. Experimental results were included to validate the effectiveness of our approach in comparison with the benchmarked methods.
K-MEANS BASED ALGORITHM FOR ISLAMIC DOCUMENT CLUSTERING

Document clustering is an unsupervised learning task. It is a form of data analysis, aims to group a set of objects into subsets or clusters. In this paper, the target domain of clustered documents is Islamic religious domain. The Islamic document clustering is considered as an important task for gaining more effective results with; the traditional information retrieval (IR) systems, organizing web text and text mining. Fast and high-quality document clustering can tremendously facilitate the user to successfully navigate, particularly on the Internet since the number of available online documents is increasing rapidly, everyday. Thus, religious domain has become an interesting and challenging area for Natural Language Processing (NLP). The aim of this paper is to evaluate the efficiency and accuracy of Arabic Islamic document clustering base on K-means algorithm with three similarity/distance measures; Cosine, Jaccard similarity and Euclidean distance. In order to implement the algorithms, we have to pre-process the data (document). The pre-processing steps are necessary in order to eliminate noise and keep only useful information so that we can boost the performance of documents clustering. Additionally, this research investigates the effect of using stemming and without stemming words on the accuracy of Arabic Islamic text clustering. Based on our experiments, we have found that the stemming process than gives better impact than without stemming process, and the K-means with Cosine similarity measure achieves the highest score of performance.
Learning collection fusion strategies

Collection fusion is a data fusion problem in which the results of retrieval runs on separate, autonomous document collections must be merged to produce a single, effective result. This paper explores two collection fusion techniques that learn the rmrnber of documents to retrieve from each collection using only the ranked lists of documents returned in response to past queries and those documents! relevance judgments. Retrieval experiments using the TREC test co]lection demonstrate that the effectiveness of the fusion techniques is within 10’? %of the effectiveness of a run in which the entire set of documents is treated as a single collection.
Human Nature Review

The philosophy of biology began to develop as a distinct field within the philosophy of science in the early 1970s, shortly before Philip Kitcher turned from mathematics and physics to biology in his thinking about general issues concerning the nature of science. Not only did the answers to traditional questions within the field seem problematic once one turned from the " hard sciences " to the softer biological sciences, but the questions themselves came to be viewed as less obviously the right ones to be asking. At the core of the philosopher's view of science thirty years ago was a series of questions about science in general. What was distinctive about science that made it our paradigm of successful intellectual inquiry? How should we think about the nature of testing and confirmation in science? What was the character of scientific explanation? Was scientific change a rational process, and if so, how should we understand that process? (And if not-as was suggested to many by influential works such as Thomas Kuhn's The Structure of Scientific Revolutions and Paul Feyerabend's Against Method-what are the implications for our broader views of science? ). The work of the logical positivists from the 1930s on, particularly that of Rudolph Carnap and Carl Gustav Hempel, had established such questions as con-stitutive of the field, and much of philosophy of science in the 1960s and 1970s was either a development of positivist ideas or a reaction to, and departure from, them. The feature of positivism and the work that followed in its stead most relevant here is the presupposition that the right questions to be asking about science were perfectly general questions, questions about science per se. The various areas of physics and chemistry were taken as paradigms of scientific inquiry, and were drawn on extensively, even if not always in depth, both to illustrate and to test the answers given to the general questions asked.
Perception-Induced Effects of Corporate Social Irresponsibility (CSiR) for Stereotypical and Admired Firms

How do stakeholders react to Corporate Social Irresponsibility (CSiR)? What are the emotional mechanisms and behavioral outcomes following CSiR perception? The psychology of CSR literature has yet to address these important questions and has largely considered CSR and CSiR as the opposite poles of the same continuum. In contrast, we view CSR and CSiR as distinct constructs and theorize about the cognitive (perceptual), emotional, and behavioral effects of CSiR activity on observers (i.e., primary and secondary stakeholders) building on theories of intergroup perception. Specifically, building on the Stereotype Content Model (SCM; Fiske et al., 2002) and the BIAS map (i.e., Behaviors from Intergroup Affect and Stereotypes; Cuddy et al., 2007)—which extends the SCM by predicting behavioral responses—we make predictions on potential stakeholder reactions to CSiR focusing on two practice-relevant cases: (a) a typical for-profit firm that engages in a CSiR activity, (b) an atypical admired firm that engages in CSiR activity.
Supplemental Material of Spontaneous symmetry breaking in 2 D : Kibble-Zurek mechanism in temperature quenched colloidal monolayers

The Kibble-Zurek mechanism describes the formation of topological defects during spontaneous symmetry breaking for quite different systems. Shortly after the big bang, the isotropy of the Higgsfield is broken during the expansion and cooling of the universe. Kibble proposed the formation of monopoles, strings, and membranes in the Higgs field since the phase of the symmetry broken field can not switch globally to gain the same value everywhere in space. Zurek pointed out that the same mechanism is relevant for second order phase transitions in condensed matter systems. Every finite cooling rate induces the system to fall out of equilibrium which is due to the critical slowing down of order parameter fluctuations: the correlation time diverges and the symmetry of the system can not change globally but incorporates defects between different domains. Depending on the cooling rate the heterogeneous order parameter pattern are a fingerprint of critical fluctuations. In the present manuscript we show that a monolayer of superparamagnetic colloidal particles is ideally suited to investigate such phenomena. In thermal equilibrium the system undergos continuous phase transitions according KTHNY-theory. If cooled rapidly across the melting temperature the final state is a polycrystal. We show, that the observations can not be explained with nucleation of a supercooled fluid but is compatible with the Kibble-Zurek mechanism.
Leaky Scanning and Reinitiation Regulate BACE1 Gene Expression

ABSTRACT β-Site β-amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) is the β-secretase in vivo for processing APP to generate amyloid β protein (Aβ). Aβ deposition in the brain is the hallmark of Alzheimer's disease (AD) neuropathology. Inhibition of BACE1 activity has major pharmaceutical potential for AD treatment. The expression of the BACE1 gene is relatively low in vivo. The control of BACE1 expression has not been well defined. There are six upstream AUGs (uAUGs) in the 5′ leader sequence of the human BACE1 mRNA. We investigated the role of the promoter and the uATGs in the 5′ untranslated region (UTR) of the human BACE1 gene in BACE1 gene transcription and translation initiation. Our results show that the first and second uATGs are the integral part of the core minimal promoter of the human BACE1 gene, while the third uAUG is skipped over by ribosomal scanning. The fourth uAUG can function as a translation initiation codon, and deletion or mutation of this uAUG increases downstream gene expression. The fourth uAUG of the BACE1 5′UTR is responsible for inhibiting the expression of BACE1. Translation initiation by the BACE1 uAUGs and physiological AUG requires intact eIF4G. Our results demonstrate that during human BACE1 gene expression, ribosomes skipped some uAUGs by leaky scanning and translated an upstream open reading frame, initiated efficiently at the fourth uAUG, and subsequently reinitiated BACE1 translation at the physiological AUG site. Such leaky scanning and reinitiation resulted in weak expression of BACE1 under normal conditions. Alterations of the leaky scanning and reinitiation in BACE1 gene expression could play an important role in AD pathogenesis.
Extension of base mispairs by Taq DNA polymerase: implications for single nucleotide discrimination in PCR.

Thermus aquaticus (Taq) DNA polymerase was used to measure the extension efficiency for all configurations of matched and mismatched base pairs at template-primer 3'-termini. The transition mispairs, A(primer). C, C.A, G.T, and T.G were extended 10(-3) to 10(-4)-fold less efficiently than their correctly paired counterparts. Relative efficiencies for extending transversion mispairs were 10(-4) to 10(-5) for T.C and T.T, about 10(-6) for A.A, and less than 10(-6) for G.A, A.G, G.G and C.C. The transversion mispair C(primer). T was extended with high efficiency, about 10(-2) compared to a correct A.T basepair. The unexpected ease of extending the C.T mismatch was not likely to have been caused by primer-template misalignment. Taq polymerase was observed to bind with similar affinities to each of the correctly paired and mispaired primer-template 3'-ends. Thus, the failure of Taq polymerase to extend mismatches efficiently appears to be an intrinsic property of the enzyme and not due to an inability to bind to 3'-terminal mispairs. For almost all of the mispairs, C.T being the exception, Taq polymerase exhibits about 100 to 1000-fold greater discrimination against mismatch extension compared to avian myeloblastosis reverse transcriptase and HIV-1 reverse transcriptase which extend most mismatched basepairs permissively. Relative mismatch extension efficiencies for Taq polymerase were measured at 45 degrees C, 55 degrees C and 70 degrees C and found to be independent of temperature. The mispair extension data should be important in designing experiments using PCR to distinguish between sequences that vary by a single nucleotide.