Miracle-dz/UniFAR-FTUs huggingface dataset:
Differences in Visual Perception: The Individual Eye by Jules B. Davidoff (review)

In the hands of the gestalt psychologists, experiments on visual perception have had an artistic flavor from the beginning. This is so because men like Wertheimer, Kohler and Koffka concentrated on the organizational processes that give form to the raw material of retinal stimulation. Quite naturally these men were interested in the arts and often drew examples from the various media. This is true also for Wolfgang Metzger, who has written on art education, creativity, etc. His principal work, however, has been in strict experimentation and in the theoretical discussion of the gestalt principles. His book on the laws of seeing, first published in the early 19409, has now grown into an impressive and expensive tome, richly illustrated and equipped even with red-green spectacles for stereoscopic and stroboscopic demonstrations. Metzger’s chapters deal with the usual topics of perceptual investigations. For the lint time, however, we receive a systematic survey of the many brilliant studies of the past decades, among them prominently those of Kanizsa, Metelli, Galli, Vicario and their teams at Trieste and Padua. There is no lack of curiosities, magic tricks and puzzles, but the author reminds his readers that all these ‘illusions’ are only conspicuous symptoms of the fact that constantly and universally all aspects of the visual field are subject to modifying interaction, which distinguishes the ontogrum (physical projection on the retina) from the phenogram (experienced image). Of particular interest is the extensive treatment of movement perception, in the course of which the art historian might note that Duchamp’s demonstrations on the turntable are preceded by Benussi’s equally imaginative experiments on ‘stereokinetics’, published in 1927. In depth perception, the question of exactly how disparate images combine in binocular vision is shown to be a richly revealing problem. Unfortunately, the phenomena of visual expression are given short shrift and the discussion of color is limited mostly to properties it shares with brightness. There are choice tidbits, such as the note on why weavers use checkerboard patterns only for clowns’ costumes. Metzger writes a gracefully relaxed prose and he speaks his mind sharply when he deals with his adversaries. His arguments against attempts, held over from Helmholtz, to explain perceptual organization through noncommittal references to ‘past experience’ should act as a coup de gruce. And when it comes to the politically inspired objection that statements on the general functioning of the human mind are worthless because they neglect ideological determinants, Metzger is willing to reply: ‘Since the way in which, under similar circumstances, a bird, a rat, a fish, or an octopus, and in some respects even a fly, see the world shares essential features with the vision of m a n a fact on which Soviet and American psychologists do not disagret i t is hard to understand why the world should look different to the professor who puts the garbage out on the curb than to the sanitation man who collects it. ’
The Arf activator Gea2p and the P-type ATPase Drs2p interact at the Golgi in Saccharomyces cerevisiae

Arf GTPases regulate both the morphological and protein sorting events that are essential for membrane trafficking. Guanine nucleotide exchange factors (GEFs) specific for Arf proteins determine when and where Arf GTPases will be activated in cells. The yeast Gea2p Arf GEF is a member of an evolutionarily conserved family of high molecular mass Arf GEFs that are peripherally associated with membranes. Nothing is known about how these proteins are localized to membranes, and few direct binding partners have been identified. In yeast, Gea2p has been implicated in trafficking through the Golgi apparatus and in maintaining Golgi structure. A major function of the Golgi apparatus is the packaging of cargo into secretory granules or vesicles. This process occurs through a series of membrane transformation events starting with fenestration of a saccular membrane, and subsequent remodeling of the fenestrated membrane into a mesh-like tubular network. Concentration of secretory cargo into nodes of the tubular network leads to enlargement of the nodes, which correspond to forming vesicles/granules, and thinning of the surrounding tubules. The tubules eventually break to release the secretory vesicles/granules into the cytoplasm. This process is highly conserved at the morphological level from yeast to mammalian cells. Drs2p, a multi-span transmembrane domain protein and putative aminophospholipid translocase, is required for the formation of a class of secretory granules/vesicles in yeast. Here we show that Drs2p interacts directly with Gea2p, both in vitro and in vivo. We mapped the domain of interaction of Drs2p to a 20-amino-acid region of the C-terminal cytoplasmic tail of the protein, adjacent to a region essential for Drs2p function. Mutations in Gea2p that abolish interaction with Drs2p are clustered in the C-terminal third of the Sec7 domain, and are important for Gea2p function. We characterize one such mutant that has a thermosensitive phenotype, and show that it has morphological defects along the secretory pathway in the formation of secretory granules/vesicles.
Receptive field resolution analysis in convolutional feature extraction

Instead of introducing new learning algorithm for solving complex classification tasks, many research groups in machine learning have focused on creating a good feature representation. In addition, labeled data is often difficult and expensive to obtain sufficiently large amount of data. So, learning features from unlabeled data is proposed since unlabeled data is much easier to obtain than the labeled data. In this work, a highlevel feature representation is created by a sparse autoencoder with convolutional extraction. A sparse autoencoder is an unsupervised feedforward neural network that is trained to predict the input itself and has been widely used for learning good feature representation. A major advantage of this feature extraction approach not only provides good feature representation for higherlevel tasks but also can scale up to large images. However, there are several parameters that require careful selection to obtain high performance. The main objective in this work is to present a detailed analysis on the effect of receptive field resolution in handwritten classification based on MNIST database. In the experiment, the results show that receptive field resolution is one of the critical parameters to achieve state-of-the-art performance.
Strong Anticipation in Social Systems and the Emergence of a Knowledge-Based Society

Reflexive agents not only communicate in terms of information exchanges, but also provide these exchanges with meaning from a hindsight perspective. This is an anticipatory mechanism because an expectation can then be specified. At the level of the social system, meaning can additionally be communicated. When meanings are variously codified (because of functional differentiation in the communication), the potential asynchronicity ( ∆ t) in the updates provides the communication system with a second anticipatory mechanism. Interactions between these two anticipatory degrees of freedom can lead recursively to co-evolution and stabilization of expectations. However, the horizon of knowledgeable expectations can be expected to meta-stabilize the previously stabilized organization of expectations. A next-order selection may lead to globalization. Globalization can be modeled using the hyper-incursive formulation of the logistic equation, whereas stabilization is based on an interaction among two incursive subdynamics. A globalized system can be considered as a strongly anticipatory system which constructs its own future states. A strongly anticipatory system is no longer necessarily based on historical manifestations, but its operation can increasingly be knowledge-based.
The subjective quality of episodic future thought and the experience of meaning in life

Abstract Two studies assessed whether mentally simulating specific future events to occur in familiar (vs. unfamiliar) settings indirectly increases meaning life via the subjective quality of the simulations. Participants in both studies (N = 344) were randomly assigned to visualize themselves doing something in familiar (e.g. home) or unfamiliar (e.g. fantasy world) settings in the future. They then rated the subjective quality of these visualizations and completed a measure of meaning in life. We replicated previous findings by showing that mental simulations involving familiar settings were of greater subjective quality than simulations involving unfamiliar settings. However, we also found that simulating future events in familiar (vs. unfamiliar) settings indirectly increased the perceived meaningfulness of life. These findings integrate research in cognitive psychology with research on the psychology of well-being and reveal how mental time travel contributes to the perception that one’s life has meaning.
Read disturbance issue for nanoscale STT-MRAM

Spin transfer torque magnetic random access memory (STT-MRAM) has been widely considered as one of the most promising candidates for the next-generation nonvolatile memory technologies, thanks to its attractive features, including high density, high speed, low power and high endurance etc. However, our investigation demonstrates that read disturbance may become a big reliability issue of STT-MRAM, since read and write currents share the same path. As technology scales down to nanoscale nodes, this read disturbance issue becomes more serious and may turn into be a critical reliability barrier for STT-MRAM commercialization, because the difference between the read and write currents decreases. In this paper, we propose a circuit to detect the read disturbance by exploiting its typical features, i.e., (a) the resistance (read current) of the memory cell will have a sudden change if read disturbance occurs; (b) only one-direction of read disturbance can occur during normal read operations. Based on the detection results, the correct data can be restored back into the memory cells after read disturbance or system-level algorithms can be employed to correct the read disturbance fault.
Study of interhemispheric coordination for birdsong production

Complex learned motor sequence generation, such as birdsong production, relies on precise coordination of activity in both brain hemispheres; however, little is known about the neural mechanisms of this coordination. By using systematic electrical and visual stimulation to briefly perturb the activity of neurons in the motor pathway during song production, I investigated the neuronal dynamics responsible for generating different acoustic elements of birdsong. These experiments allowed me to dissect complex motor behavior and verify the hypothetical existence of behavioral units for procedural sequences of motor behavior. On one hand, I discovered mostly disjoint time intervals during which electrical stimulation of either the right or left hemisphere was effective in distorting vocalizations. Such interhemispheric switching of stimulation effectiveness was even observed during repetitive calls uttered immediately after song. This evidence supports a novel form of ping-pong–like motor dynamics for song production. Furthermore, the interhemispheric switching patterns obtained from two sibling birds, both of which learned songs that were temporally and spectrally similar, were intrinsically uncorrelated. This implies that an idiosyncratic neural representation for learned song exists across both cerebral hemispheres. On the other hand, using non-invasive visual perturbation, I found that song disruptions also occurred in the midst of syllables and that furthermore, certain parts of the song motifs were resistant to visual perturbation. By analyzing syllable transitions for several birds receiving visual or electrical stimulation in HVC (a premotor nucleus for song production) and LMAN (a basal ganglia nucleus for song learning), I found most stimulation-induced syllable transitions were also observed during catch trials, although much more rarely. Therefore, stimulation seems to selectively increase the likelihood of some rare song sequence transitions within the song repertoire. By analyzing the size distribution of an effective set of contiguous stimulation times, I found evidence for power-law behavior and for self-organized chain networks of HVC projection neurons. Taken together, these findings indicate that the motor program for song production contains discrete sub-syllabic elements that reside bilaterally in the brain and are coordinated via rapid interhemispheric switching dynamics. The formation of the neural networks representing these elements might result from the idiosyncratic song learning process specific to each bird.
First results in Octopus development of a distributed file system

The Octopus method was created by Nokia to assist development of embedded, real time software systems. Like all methodologies, its application to industrial projects presents several difficulties. One of the pilot applications of Octopus at Nokia has been the design of a real time, distributed file system (Magix) for the DX200 telephone switch product family. The first results from the analysis and high level design phases have shown a number of problems in the method, as well as highlighting several positive aspects. A perspective on the near future leads towards a tailoring of the method in order to render it adequate for all problem domains.
A Survey of 2D and 3D Shape Descriptors

3D objects play a vital role in computer games, movies, TV, engineering design, and biological sciences. Researchers have studied 3D object retrieval techniques using 2D and 3D shape descriptors in the last several decades. In this paper, some of the most popular shape descriptors are reviewed. We first discuss the important criteria for a good shape descriptor. Then, we classify 2D and 3D shape descriptors into several categories. For each category, we review the state-of-the-art techniques along with their advantages and disadvantages. We also examine the recent contributions and improvements in these techniques and provide a comparison with other successful techniques based on previous literature and surveys. Finally we discuss the possible future directions.
A Novel Approach To Vortex Core Region Detection

In this paper we present a simple and efficient vortex core region detection algorithm based on ideas derived from combinatorial topology. These ideas originated from Sperner's lemma, which by itself is of little value to detecting vortex cores. However, we take these ideas from the lemma and apply them in a point-based fashion to detecting vortex core regions. The resulting algorithms for both 2D and 3D are quite simple and very efficient compared to existing ones. We applied our algorithms to both numerically simulated and procedurally generated datasets to illustrate the efficacy of our approach.
FTY720 Attenuates Angiotensin II-Induced Podocyte Damage via Inhibiting Inflammatory Cytokines

FTY720, a new chemical substance derived from the ascomycete Isaria sinclairii, is used for treating multiple sclerosis, renal cancer, and asthma. Sphingosine 1-phosphate (S1P) is a bioactive sphingolipid metabolite and exists in red blood cells. FTY720 is a synthetic S1P analog which can block S1P evoking physiological effects. Recently studies show that S1P was participating in activated inflammation cells induced renal injury. The objective of this study was to assess the protective effect of FTY720 on kidney damage and the potential mechanism of FTY720 which alleviate podocyte injury in chronic kidney disease. In this study, we selected 40 patients with IgA nephropathy and examined their clinical characteristics. Ang II-infusion rat renal injury model was established to evaluate the glomeruli and tubulointerstitial lesion. The result showed that the concentration of S1P in serum and urine was positively correlated with IgA nephropathy patients' renal injury. FTY720 could reduce renal histological lesions induced by Ang II-infusion in rats. Moreover, FTY720 decreased S1P synthesis in Ang II-infusion rats via downregulation of inflammatory cytokines including TNF-α and IL-6. In addition, FTY720 alleviated exogenous S1P-induced podocyte damage. In conclusion, FTY720 is able to attenuate S1P-induced podocyte damage via reducing inflammatory cytokines.
Unique hr practices in the Indian IT industry: A research agenda

Methodology – The research aims to gather evidence from software professionals in Indian IT companies situated in various parts of India, about their expectations and experiences in relation to the HR practices followed in their respective companies. A multiple case study approach will be adopted in this study and the primary data will be collected by conducting semi-structured interviews with software professionals from five selected Indian IT companies and by obtaining written responses from controlled online discussion boards specifically set up for this study by the researcher.
Wavelet Blind Equalization Algorithm Based on Support Vector Machine

In order to improve steady-state mean square error performance and increase the convergence rate, this paper presents a blind wavelet equalization algorithm based on Support Vector Machine initialized. This algorithm uses Support Vector Machine to utilize a short initial data segment, transforms blind equalization problem into support vector regression problem and sets the initial weight. Orthogonal wavelet transform is introduced before signal equalized. The results of computer simulation based on a water channel demonstrate that the algorithm converges fast and the error performance is stable.
Temporal Network Change Detection Using Network Centralities

In this paper, we propose a novel change detection method for temporal networks. In usual change detection algorithms, change scores are generated from an observed time series. When this change score reaches a threshold, an alert is raised to declare the change. Our method aggregates these change scores and alerts based on network centralities. Many types of changes in a network can be discovered from changes to the network structure. Thus, nodes and links should be monitored in order to recognize changes. However, it is difficult to focus on the appropriate nodes and links when there is little information regarding the dataset. Network centrality such as PageRank measures the importance of nodes in a network based on certain criteria. Therefore, it is natural to apply network centralities in order to improve the accuracy of change detection methods. Our analysis reveals how and when network centrality works well in terms of change detection. Based on this understanding, we propose an aggregating algorithm that emphasizes the appropriate network centralities. Our evaluation of the proposed aggregation algorithm showed highly accurate predictions for an artificial dataset and two real datasets. Our method contributes to extending the field of change detection in temporal networks by utilizing network centralities.
English-Chinese Knowledge Base Translation with Neural Network

Knowledge base (KB) such as Freebase plays an important role for many natural language processing tasks. English knowledge base is obviously larger and of higher quality than low resource language like Chinese. To expand Chinese KB by leveraging English KB resources, an effective way is to translate English KB (source) into Chinese (target). In this direction, two major challenges are to model triple semantics and to build a robust KB translator. We address these challenges by presenting a neural network approach, which learns continuous triple representation with a gated neural network. Accordingly, source triples and target triples are mapped in the same semantic vector space. We build a new dataset for English-Chinese KB translation from Freebase, and compare with several baselines on it. Experimental results show that the proposed method improves translation accuracy compared with baseline methods. We show that adaptive composition model improves standard solution such as neural tensor network in terms of translation accuracy.
Evaluating Agreement and Disagreement among Movie Reviewers

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Hybrid Biogeography-Based Optimization for Integer Programming

Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark integer programming problems. Thus we modify the mutation operator and/or the neighborhood structure of the algorithm, resulting in three new BBO-based methods, named BlendBBO, BBO_DE, and LBBO_LDE, respectively. Computational experiments show that these methods are competitive approaches to solve integer programming problems, and the LBBO_LDE shows the best performance on the benchmark problems.
Neural Network Based Inverse Control of Systems with Hysteresis

A model of piezoelectric actuator with hysteresis has been built in this paper with Prandtle-Ishlinskii model. After that, a radial basis function (RBF) neural network based adaptive inverse control scheme for nonlinear systems with unknown hysteresis nonlinearity is developed. A nonlinear filter based on RBF neural networks is used in hysteresis inverse plant modeling. We use the inverse model as the controller to control the piezoelectric actuator model directly. The simulation results show that the method interposed in this paper can restrain the hysteresis effect to lower than 1.25%.
Cursor measures for motion-impaired computer users

"Point and click" interactions remain one of the key features of graphical user interfaces (GUIs). People with motion-impairments, however, can often have difficulty with accurate control of standard pointing devices. This paper discusses work that aims to reveal the nature of these difficulties through analyses that consider the cursor's path of movement. A range of potential cursor measures was applied, and a number of them were found to be significant in capturing the differences between able-bodied users and motion-impaired users, as well as the differences between a haptic force feedback condition and a control condition. cursor measures found in the literature, however, do not make up a comprehensive list, but provide a starting point for analysing cursor movements more completely. Six new cursor characteristics for motion-impaired users are introduced to capture aspects of cursor movement different from those already proposed.