Miracle-dz/UniFAR-FTUs huggingface dataset:
The Principal Component Structure of Natural Sound

Redundancy reduction on the basis of the second-order statistics of natural images has been very successful in accounting for the psychophysics of low-level vision. Here we study the second-order statistics of natural sound ensembles using Principal Component Analysis (PCA). Their eigen spectra exhibit a nite-size scaling behavior as a function of the window size, with universality after the 2{5 milliseconds range. In contrast with natural scenes, auditory spectra do not universally obey a power law, but rather depend strongly on the auditory environment. We study the distribution of the PCA coeecients and nd them highly non-Gaussian, with kurtoses in the mid hundreds. The dependence of the kurto-sis on the eigenmode's average power is non-trivial|highly erratic. Moreover, the kurtosis increases with the size of the window up to, at least, 80 milliseconds, and also becomes more erratic as a function of the eigenmode's power. We compare these results with the ones based on Fourier Analysis, and also discuss their implications for eecient coding of natural auditory stimuli.
Cardiometabolic and neuroimaging correlates of cognitive function in polycystic ovary syndrome

Background: Polycystic ovary syndrome (PCOS) is a disorder characterized by insulin resistance and hyperandrogenism, which leads to an increased risk of type 2 diabetes in later life. Androgens and insulin signalling affect brain function but little is known about brain structure and function in younger adults with PCOS. Aims and Methods: To establish whether young women with PCOS display altered white matter microstructure and cognitive function. Eighteen individuals with PCOS (age, 31 ± 6 y; body mass index [BMI] 30 ± 6 kg/m2) and 18 control subjects (age, 31 ± 7 y; BMI, 29 ± 6 kg/m2), matched for age, IQ, and BMI, underwent anthropometric and metabolic evaluation, diffusion tensor MRI, a technique especially sensitive to brain white matter structure, and cognitive assessment. Cognitive scores and white matter diffusion metrics were compared between groups. White matter microstructure was evaluated across the whole white matter skeleton using tract-based spatial statistics. Associations with metabolic indices were also evaluated. Results: PCOS was associated with a widespread reduction in axial diffusivity (diffusion along the main axis of white matter fibres) and increased tissue volume fraction (the proportion of volume filled by white or grey matter rather than cerebrospinal fluid) in the corpus callosum. Cognitive performance was reduced compared with controls (first principal component, t = 2.9, P = .007), reflecting subtle decrements across a broad range of cognitive tests, despite similar education and premorbid intelligence. In PCOS, there was a reversal of the relationship seen in controls between brain microstructure and both androgens and insulin resistance.
Implementation of Co-Operative Communication Protocol

In a wireless transmission the signal quality suffers severely from bad channel quality due to effects like fading caused by multi-path propagation. To reduce such effects diversity can be used thereby increasing the network capacity and coverage. In this paper we study and simulate the transmission protocols such as Amplify and Forward, Decode and Forward and Coded Cooperation. Cooperative communication refers to processing of this overheard information at the surrounding nodes and retransmission towards the destination to create spatial diversity, thereby to obtain higher throughput and reliability
Modelling of Plasma Turbulence in Tokamaks

Understanding turbulence in fusion plasmas has become a crucial task in order to achieve sufficient confinement level in large-scale devices like ITER. The ELMFIRE full f nonlinear gyrokinetic simulation code has been developed for calculation of plasma evolution and dynamics of turbulence in tokamak geometry. Code ELMFIRE is based on a particle-in-cell algorithm with direct implicit treatment of ion polarization and consideration of either kinetic or adiabatic electrons, and also impurities. The gyrokinetic model performs averages over the gyro-orbits while keeping accuracy over the most interesting time and length-scales regarding turbulence development. Opposite to delta f algorithms, the full f method is suitable for calculating also strongly perturbed plasmas including wide orbit effects, steep gradients and rapid dynamic changes. ELMFIRE is here been tested against the neoclassical theory, and used for computation of the neoclassical radial electric field and the influence of turbulence on that magnitude.
Neural networks and brain function

Pattern association memory autoassociation memory competitive networks, including self-organizing maps error-correcting networks - perceptrons, backpropagation of error in multilayer networks, and reinforcement learning algorithms hippocampus and memory pattern association in the brain - amygdala and orbitofrontal cortex cortical networks for invariant pattern recognition motor systems - cerebellum and basal ganglia cerebral neocortex. Appendix 1: introduction to linear algebra for neural networks. Appendix 2: Information theory. Appendix 3: Pattern associators. Appendix 4: Autoassociators. Appendix 5: Recurrent dynamics.
Application of Image Mosaic Algorithm in Lateral Multi-lens Video Logging

The wall sequence images acquired by lateral multi-lens video logging method had some peculiarities that the overlap region of adjacent images can be estimated. This paper proposed an image mosaic algorithm which first estimated the overlap areas of adjacent images, and then matched for the areas with SIFT feature matching algorithm. To achieve seamless image stitching, the gradated in-and-out linear fusion algorithm had been adopted to match overlap images. The experiments showed that this method can rapidly and accurately extract the corresponding adjacent image matching points, acquire the panoramic mosaic image of the lateral multi-lens video logging, and lay a foundation for the logging results analysis in the next stage.
The Role of Soft Information in a Dynamic Contract Setting : Evidence from the Home Equity Credit Market ∗

We analyze more than 108,000 home equity loans and lines of credit applications to study the role of soft and hard information during underwriting. Credit underwriting is a dynamic process involving multiple interactions between borrower and lender. During this process, lenders have the opportunity to obtain hard and soft information from the borrower. Our analysis suggests that the use of soft information during the underwriting process can be effective in reducing overall portfolio credit losses ex post. JEL Classification: D1; D8; G21
Multiple signaling pathways regulate the transcriptional activity of the orphan nuclear receptor NURR1

The orphan nuclear receptor nurr1 (NR4A2) is an essential transcription factor for the acquisition and maintenance of the phenotype of dopamine (DA)-synthesizing neurons in the mesencephalon. Although structurally related to ligand-regulated nuclear receptors, nurr1 is functionally atypical due to its inability to bind a cognate ligand and to activate transcription following canonical nuclear receptor (NR) rules. Importantly, the physiological stimuli that activate this NR and the signaling proteins that regulate its transcriptional activity in mesencephalic neurons are unknown. We used an affinity chromatography approach and CSM14.1 cells of mesencephalic origin to isolate and identify several proteins that interact directly with nurr1 and regulate its transcriptional activity. Notably, we demonstrate that the mitogen-activated protein kinases, ERK2 and ERK5, elevate, whereas LIM Kinase 1 inhibits nurr1 transcriptional activity. Furthermore, nurr1 recruits ERK5 to a NBRE-containing promoter and is a potential substrate for this kinase. We have identified amino acids in the A/B domain of nurr1 important for mediating the ERK5 activating effects on nurr1 transcriptional activity. Our results suggest that nurr1 acts as a point of convergence for multiple signaling pathways that likely play a critical role in differentiation and phenotypic expression of dopaminergic (DAergic) neurons.
Design and Implementation of a Reversible Central Processing Unit

This work addresses the reversible circuit design using novel modularization approach by presenting architecture of a logically reversible processor based on the Von Neumann architecture that can operate with very low power consumption, protection of power analysis attack and long span of life due to less heat dissipation. The organization and architecture of the proposed processor is designed from scratch. Sequential algorithms are proposed to produce the components of the reversible processor. The capabilities of the new processor is determined, the datapath layout is designed to handle the necessary capabilities, the instruction format is defined and the necessary logic is also constructed to control the data path. To estimate the execution time of the algorithm, we consider the computational complexity, memory access patterns and the complexity of the instructions. Existing component designs are compared with the proposed components and theorems and lemmas are presented to prove the superiority of the proposed architecture. The proposed design is simulated and the simulation result verifies the correctness of the proposed design.
Universal construction of robust adaptive control laws for a class of nonlinear systems preceded by generalized Prandtl-Ishlinskii representation

For the nonlinear systems preceded by smart actuators which exhibit hysteresis nonlinearities, the increasing attention is to design the controller to mitigate the effect of hysteresis. Among the developed approaches, some attempts have been made to fuse the available hysteresis models with available control approaches without the inverse hysteresis construction. Focusing on the Prandtl-Ishlinskii model, a generalized Prandtl-Ishlinskii model, which can accommodate more general class of hysteresis shapes than the conventional Prandtl-Ishlinskii model, will be fused with robust control techniques. The global stability of the system and tracking a desired trajectory to a certain precision are achieved, and simulation results attained for a nonlinear system are presented to illustrate and further validate the effectiveness of the proposed approach.
Mining source code to automatically split identifiers for software analysis

Automated software engineering tools (e.g., program search, concern location, code reuse, quality assessment, etc.) increasingly rely on natural language information from comments and identifiers in code. The first step in analyzing words from identifiers requires splitting identifiers into their constituent words. Unlike natural languages, where space and punctuation are used to delineate words, identifiers cannot contain spaces. One common way to split identifiers is to follow programming language naming conventions. For example, Java programmers often use camel case, where words are delineated by uppercase letters or non-alphabetic characters. However, programmers also create identifiers by concatenating sequences of words together with no discernible delineation, which poses challenges to automatic identifier splitting. In this paper, we present an algorithm to automatically split identifiers into sequences of words by mining word frequencies in source code. With these word frequencies, our identifier splitter uses a scoring technique to automatically select the most appropriate partitioning for an identifier. In an evaluation of over 8000 identifiers from open source Java programs, our Samurai approach outperforms the existing state of the art techniques.
The Problematics of Political Polls: Mathematics Curriculum for Social Understanding

The use of statistical techniques in determining a variety of campaign characteristics andoutcomes is only one of the many ways in which mathematics and mathematics curriculum have a political effect. The denial of the political nature of mathematics is widespread. Thegeneral conception -or misconception -is thatmathematics is value-free andculture-free since the laws of number are the same universally. As Alan Bishop puts it, "The ideas are decontextualized and abstracted in such a way that obviously they can apply everywhere" (1988, p. 180). How have we created a mathematics curriculum thatgives such an impression?
SEMANTIC RETRIEVAL TECHNIQUE BASED ON DOMAIN ONTOLOGY

The Semantic Web is a latest technique for organizing information and it characterize a huge interest area for the worldwide research group of people, however it is still far from a significant implementation. In this research we have proposed a scheme for information retrieval stand on ontologies, dynamic semantic network, and lexical chains, significant an approach for achieve and indexing consequences by means of a narrative metric to compute semantic relatedness between words. Our technique has numerous novelties, in meticulous concerning the utilize of a collective knowledge base from which we mine precise domain ontologies; furthermore, the anticipated semantic relatedness metric achieve optimally evaluate with further metrics in the using a general test set. In meticulous we are taking into consideration the opportunity of introduce several form of normalization for the semantic constituent with respect to the length of lexical chains and the size of the documents, applying our research news paper domain and we are improving the analysis accuracy of our system compared with other metrics.
Aggregation of Pi-based forecast to enhance prediction accuracy

In contrast to point forecast, prediction interval-based neural network offers itself as an effective tool to quantify the uncertainty and disturbances that associated with process data. However, single best neural network (NN) does not always guarantee to predict better quality of forecast for different data sets or a whole range of data set. Literature reported that ensemble of NNs using forecast combination produces stable and consistence forecast than single best NN. In this work, a NNs ensemble procedure is introduced to construct better quality of Pis. Weighted averaging forecasts combination mechanism is employed to combine the Pi-based forecast. As the key contribution of this paper, a new Pi-based cost function is proposed to optimize the individual weights for NN in combination process. An optimization algorithm, named simulated annealing (SA) is used to minimize the PI-based cost function. Finally, the proposed method is examined in two different case studies and compared the results with the individual best NNs and available simple averaging Pis aggregating method. Simulation results demonstrated that the proposed method improved the quality of Pis than individual best NNs and simple averaging ensemble method.
User Authentication System using Cryptography Involving Arithmetic Operations

The concept of having to identify an entity before being allowed to perform any action is quite acceptable, and expected, and required in today’s wired world. Password managers, graphical systems, pattern recognition, biometrics have always been found to be incapable of providing robust security in some or the other aspect, in critical authentication systems [24]. In our approach, the user at the time of profile creation is required to enter the password, minimum of 6 characters and a secret numeric PIN of minimum 4 digits. Now during subsequent login attempts, the user will be asked to enter the password as an answer to a random mathematical question displayed in front of him in the form of an image (readable only by human and not by a software entity) [15]. Example; Consider the password: KOREAN and secret pin: 1234, the question would be; your 2nd character of password varies by 1+3rd character of your secret pin. Now instead of the original password, the user will enter the new password as KSREAN. The password can contain any combination of the available 96 characters on the keyboard. Every time only the same character of the password will be changed. The secret pin must contain only digits (to increase security, length can be increased to 10 or more digits). If the user enters the correct password he is authenticated otherwise denied access. This concept has some assumptions that the site locks the account if number of attempts for a particular user name exceeds a predetermined threshold.
Responding to Injustice: Perception, Anger, and Identification as Drivers of Collective Action

This study examines how perceptions of injustice, anger, and group identification motivate follower intentions to engage in collective action against leaders. The study revolved around the Malaysian prime minister’s actions and responses toward allegations of misuse of public funds. Responses from 112 Malaysians via a cross-sectional survey revealed that follower perceptions of leader injustice are significantly related to anger toward the leader, which in turn is related to intentions to engage in collective action. The relationship between perceptions of distributive injustice and anger is moderated by group identification, while group efficacy moderates the relationship between anger and collective action intentions.
Impact of p21 Knockout on Topotecan-Induced Stress Responses in Human Colon Carcinoma Cells: A Proteomic Analysis

There are few reports describing the role of p21-dependent protein repression in cell death. To identify such cell death-associated proteins and to shed the light into the molecular mechanisms by which p21 is responding to pharmacological stress, we used a subcellular proteomic approach for the analysis of protein expression profiles of fractionated nuclei, mitochondria, and cytosols of isogenic p21 null (p21-/-) and wild-type human HCT-116 cells following treatment with sublethal doses (1μM) of the topoisomerase I inhibitor, topotecan (TPT). In total, 174 unique deregulated proteins were identified in HCT-116 cells following treatment with TPT, whereas only 146 proteins were identified in p21-/cells. They contributed to multiple functional activities of stress signaling pathways, and that p21-/cells are accelerated to be more responsive to topotecan-induced cell death due to the following: 1) down regulation of proteins involved in the transcriptional and replication machinery of cells like DNA (cytosine-5)-methyltransferase 1, Matrin 3, DNA replication licensing factor MCM4, heterogeneous nuclear ribonucleoprotein Q, poly(Rc)-binding protein 1 and splicing factor arginine serine rich 7; 2) the activation of a caspase-independent apoptosis by the upregulation of the Bcl2 inhibitor of transcription (Bit1) protein; and 3) the activation of TNF signaling by the upregulation of macrophage immigration inhibitory factor (MIF), and 26S proteosome non-ATPase regulatory subunit 2 (TRAP2) proteins. We suggest that the upregulation of these proteins are contributing factors to the molecular mechanisms of topotecan-induced cell death in p21-/cells; and that the data present an opportunity for developing new therapeutic approaches for selective targeting of p21-
DESIGN OF FUZZY DECISION SUPPORT SYSTEM (FDSS) IN TECHNICAL EMPLOYEE RECRUITMENT

Now-a-days employee recruitment is one of the most important assets of any companies. The aim of study is developing a fuzzy decision support system (FDSS) to select appropriate employee in technical field by taking some qualitative judgments of decision makers into consideration. Proposed approach is based on Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. FAHP method is used in determining the weights of the criteria by decision makers and then rankings of the technical employee are determined by TOPSIS method.
Psychosis prevalence and physical, metabolic and cognitive co-morbidity: data from the second Australian national survey of psychosis

Background There are insufficient data from nationwide surveys on the prevalence of specific psychotic disorders and associated co-morbidities. Method The 2010 Australian national psychosis survey used a two-phase design to draw a representative sample of adults aged 18–64 years with psychotic disorders in contact with public treatment services from an estimated resident population of 1 464 923 adults. This paper is based on data from 1642 participants with an International Classification of Diseases (ICD)-10 psychotic disorder. Its aim is to present estimates of treated prevalence and lifetime morbid risk of psychosis, and to describe the cognitive, physical health and substance use profiles of participants. Results The 1-month treated prevalence of psychotic disorders was 3.10 cases per 1000 population aged 18–64 years, not accounting for people solely accessing primary care services; lifetime morbid risk was 3.45 per 1000. Mean premorbid intelligence quotient was approximately 0.5 s.d. s below the population mean; current cognitive ability (measured with a digit symbol coding task) was 1.6 s.d. s below the population mean. For both cognitive tests, higher scores were significantly associated with better independent functioning. The prevalence of the metabolic syndrome was high, affecting 60.8% of participants, and pervasive across diagnostic groups. Of the participants, two-thirds (65.9%) were current smokers, 47.4% were obese and 32.4% were sedentary. Of the participants, half (49.8%) had a lifetime history of alcohol abuse/dependence and 50.8% lifetime cannabis abuse/dependence. Conclusions Our findings highlight the need for comprehensive, integrative models of recovery to maximize the potential for good health and quality of life for people with psychotic illness.
Kindlin-2 cooperates with talin to activate integrins and induces cell spreading by directly binding paxillin

Integrins require an activation step prior to ligand binding and signaling. How talin and kindlin contribute to these events in non-hematopoietic cells is poorly understood. Here we report that fibroblasts lacking either talin or kindlin failed to activate β1 integrins, adhere to fibronectin (FN) or maintain their integrins in a high affinity conformation induced by Mn2+. Despite compromised integrin activation and adhesion, Mn2+ enabled talin- but not kindlin-deficient cells to initiate spreading on FN. This isotropic spreading was induced by the ability of kindlin to directly bind paxillin, which in turn bound focal adhesion kinase (FAK) resulting in FAK activation and the formation of lamellipodia. Our findings show that talin and kindlin cooperatively activate integrins leading to FN binding and adhesion, and that kindlin subsequently assembles an essential signaling node at newly formed adhesion sites in a talin-independent manner. DOI: http://dx.doi. org/10.7554/eLife.10130. 001
Burst Detection in Social Media Streams for Tracking Interest Profiles in Real Time

This work presents RTTBurst, an end-to-end system for ingesting descriptions of user interest profiles and discovering new and relevant tweets based on those interest profiles using a simple model for identifying bursts in token usage. Our approach differs from standard retrieval-based techniques in that it primarily focuses on identifying noteworthy moments in the tweet stream, and ? summarizes? those moments using selected tweets. We lay out the architecture of RTTBurst, our participation in and performance at the TREC 2015 Microblog track, and a method for combining and potentially improving existing TREC systems. Official results and post hoc experiments show that our simple targeted burst detection technique is competitive with existing systems. Furthermore, we demonstrate that our burst detection mechanism can be used to improve the performance of other systems for the same task.