Miracle-dz/UniFAR-FTUs huggingface dataset:
Theoretical Neuroscience

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.
ON ACOUSTICS MADRID , 2-7 SEPTEMBER 2007 AUDIO-VISUAL INTERACTIONS IN DYNAMIC SCENES : IMPLICATIONS FOR MULTISENSORY COMPRESSION PACS

New media technologies enrich human capabilities for generation, transmission and representation of audio-visual content. Knowledge about human sensory and cognitive processing is critical to advance in these technologies. Traditionally, media technologies have adopted a unimodal view on human perception using, for example, separate compression modules for audio and visual data streams. Drawing on the neuroscience advances that have revealed the strongly multisensory nature of human perception, we suggest that audio-visual content processing might benefit from adopting a multimodal approach that is tailored to the rules of human multisensory processing. While visual dominance in spatial domain is largely known for static scenes, such as in the famous “ventriloquism effect”, more complex interactions emerge for dynamic audio-visual stimuli. In this paper we first review some studies on “dynamic ventriloquism” effect where visual motion captures the perceived direction of auditory motion. Second, we show how rhythmic sound patterns fill-in temporally degraded visual motion based on recently discovered “auditory-induced visual flash illusion”. Finally, we discuss the implications of these findings for multisensory processing and compression techniques.
Editorial Comments–Acute Stress Symptoms, Dissociation, and Depression Among Rescue Personnel 24 Hours after the Bet-Yehoshua Train Disaster: The Effect of Exposure to Dead Bodies

Web publication: 30 October 2008 Abstract Introduction: The immediate impact of exposure to severe wounds, dead bodies, and immediate threat to life has been understudied. Most studies focus on the acute stress disorder and/or post-traumatic stress disorder phases in order to assess rescue personnel's symptomatology, and tend to neglect the immediate exposure to elements of the disaster. Hypothesis: Rescue personnel who had a history of previous exposure to dead bodies would exhibit higher levels of acute stress symptoms, dissociation, and depressive symptoms within the 24 hours following a traumatic event. Methods: Twenty-three rescue personnel participated in the search and excavation of dead and mutilated bodies following the Bet-Yehoshua train crash in Israel. The rescue personnel group was divided based on previous exposure to dead bodies. Each participant completed a demographic questionnaire, which included a question on perceived threat to life, the impact of event scale revised, the dissociative experience scale, and the center of epidemiologic studies depression questionnaire. Student's ^-tests, along with multivariate analysis of covariance (MANCOVA) were conducted in order to learn which factors are related to psychiatric symptomatology following the immediate exposure to such stressors. Results: Among rescue personnel, those with previous exposure to dead bodies did not differ in their levels of acute stress symptoms, dissociation, and depressive symptoms from those who were not previously exposed to dead bodies. Conclusions: These results may suggest the possibility that the impact of exposure to dead bodies does not emerge in the acute stress reactions (ASR) phase (up to 24 hours after the event), but later when people have time to process the trauma. Another possibility is that the rescue coping mechanisms of detachment may serve as a buffer for the horrific sights encountered during the ASR period.
Paper No. 18-03141 An integration of population synthesis methods for agent-based microsimulation

ACKNOWLEDGMENTS This research was funded in part through the United States Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) under the project Traveler Response Architecture using Novel Signaling for Network Efficiency in Transportation (TRANSNET). The authors would like to thank the Boston Metropolitan Planning Organization and the Boston Metropolitan Planning Organization’s Central Transportation Planning Staff for providing access to their GIS files
ERROR ESTIMATES FOR AN OPTIMAL CONTROL PROBLEM GOVERNED BY THE HEAT EQUATION WITH STATE AND CONTROL CONSTRAINTS

In this work, we study priori error estimates for the numerical approximation of an optimal control problem governed by the heat equation with certain control constraint and ending point state constraint. By making use of the classical space-time discretization scheme, namely, finite element method with the space variable and backward Euler discretization for the time variable, we first project the original optimal control problem into a semi-discrete control and state constrained optimal control problem governed by an ordinary differential equation, and then project the aforementioned semi-discrete problem into a fully discrete optimization problem with constraints. With the help of Pontryagin’s maximum principle, we obtain, under a certain reasonable condition of Slater style, not only an error estimate between the optimal controls for the original problem and the semi-discrete problem, but also an error estimate between the solutions of the semi-discrete problem and the fully discrete problem, which leads to an error estimate between the solutions of the original problem and the fully discrete problem. By making use of the aforementioned result, we also establish an numerical approximation for the exactly null controllability of the internally controlled heat equation.
Coarse-Grained Complexity for Dynamic Algorithms

To date, the only way to argue polynomial lower bounds for dynamic algorithms is via fine-grained complexity arguments. These arguments rely on strong assumptions about specific problems such as the Strong Exponential Time Hypothesis (SETH) and the Online Matrix-Vector Multiplication Conjecture (OMv). While they have led to many exciting discoveries, dynamic algorithms still miss out some benefits and lessons from the traditional "coarse-grained" approach that relates together classes of problems such as P and NP. In this paper we initiate the study of coarse-grained complexity theory for dynamic algorithms. Below are among questions that this theory can answer. What if dynamic Orthogonal Vector (OV) is easy in the cell-probe model? A research program for proving polynomial unconditional lower bounds for dynamic OV in the cell-probe model is motivated by the fact that many conditional lower bounds can be shown via reductions from the dynamic OV problem (e.g. [Abboud, V.-Williams, FOCS 2014]). Since the cell-probe model is more powerful than word RAM and has historically allowed smaller upper bounds (e.g. [Larsen, Williams, SODA 2017; Chakraborty, Kamma, Larsen, STOC 2018]), it might turn out that dynamic OV is easy in the cell-probe model, making this research direction infeasible. Our theory implies that if this is the case, there will be very interesting algorithmic consequences: If dynamic OV can be maintained in polylogarithmic worst-case update time in the cell-probe model, then so are several important dynamic problems such as k-edge connectivity, (1 + ϵ)-approximate mincut, (1 + ϵ)-approximate matching, planar nearest neighbors, Chan's subset union and 3-vs-4 diameter. The same conclusion can be made when we replace dynamic OV by, e.g., subgraph connectivity, single source reachability, Chan's subset union, and 3-vs-4 diameter. Lower bounds for k-edge connectivity via dynamic OV? The ubiquity of reductions from dynamic OV raises a question whether we can prove conditional lower bounds for, e.g., k-edge connectivity, approximate mincut, and approximate matching, via the same approach. Our theory provides a method to refute such possibility (the so-called non-reducibility). In particular, we show that there are no "efficient" reductions (in both cell-probe and word RAM models) from dynamic OV to k-edge connectivity under an assumption about the classes of dynamic algorithms whose analogue in the static setting is widely believed. We are not aware of any existing assumptions that can play the same role. (The NSETH of Carmosino et al. [ITCS 2016] is the closest one, but is not enough.) To show similar results for other problems, one only need to develop efficient randomized verification protocols for such problems.
Numerical Method for Determining Potential Coefficients Matrix for Multiconductor Transmission Line

Consider the propagation of electromagnetic energy through multiconductor three-phase high-voltage transmission line with arbitrary number of conductors. The mathematical formulation of the problem represents the system of partial differential equations known as transmission line equations. When constructing the capacitance matrix of an electric line, it is necessary to solve the boundary problems for the Laplace equation with nonlocal boundary conditions. The aim of this research is to develop a new method for constructing a potential coefficients matrix, which allows us to express the voltage vector in the wires through the charge vector. The application of this method leads to the necessity of solving a boundary value problem for Laplace equations with nonlocal boundary conditions. A new type of non-local boundary conditions has been identified, which has not been previously investigated. The boundary conditions of this type are represented by the contour integral over the boundary of the region from an unknown potential. In the general case, the obtained problem does not have a unique solution. The theorem of existence and uniqueness of the solution for the boundary value problem for the Laplace equation with nonlocal boundary conditions is proved. However, the requirement that the potential on the wire surface is constant allows us to prove the existence and uniqueness of the solution for considered problem. In order to illustrate the application of the developed approach we have solved numerically the problem for the sector-shaped cable with three cores. The values of potential and capacitive coefficients obtained by calculation are given. The error of the values of the diagonal elements of the matrices of potential and capacitive coefficients is estimated as less than 0.1%.
The effect of the excess sludge pretreatment on biogas productivity

To intensify biogas production during anaerobic stabilization of organic matter in sludge, pretreatment is applied. The effect of pretreatment of excess activated sludge (AS) and excess aerobic granular sludge (GS) on biogas productivity (BP) and composition was investigated. The sludge was pretreated with homogenization (6,500 rpm for 0.5 min (H0.5) and 1 min (H1.0)) or ultrasound disintegration at 20 kHz (50% amplitude for 2 min (D50%_2.0) and 4 min (D50%_4.0), and 100% amplitude for 4 min (D100%_4.0)). BP of AS of GS without pretreatment was 603.3±5 dm3/kg TS (793.4±7 dm3/kg VS); that was 200.6±4 dm3/kg TS (480.8±6 dm3/kg VS). With disintegration, the BP of AS increased by 7.8% (650.4±10 dm3/kg TS) (D50%_2.0) and 16.1% (700.6±11 dm3/kg TS) (D100%_4.0), and that of GS increased by 7.0% (214.0±5 dm3/kg TS) (D50%_2.0) and 16.0% (232.8±5 dm3/kg TS) (D100%_4.0). With homogenization, BP increased by 2.0-3.0% (AS) and 1.6-3.2% (GS).
Problematising Intercultural Communicative Competence in Language Teaching and Learning

In light of students’ international mobility, learning modern languages has become the key to unlocking new opportunities. Within this global mobility, intercultural communicative competence (ICC) has become a new buzzword in language teaching and learning. Generally, it is defined in terms of knowledge, attitudes and skills which supply language learners with “the ability to interact effectively with people from cultures that we recognise as being different from our own” [1]. Despite several attempts in contemporary literature to establish an encompassing model of teaching ICC, a coherent understanding of how this concept relates to classroom pedagogical practices is still lacking [2]. This paper, therefore, addresses two interrelated facets of teaching ICC. First, the theoretical framework underpinning ICC models in foreign language learning is critically discussed. Secondly, the practical facet of teaching ICC will be further examined through discussion of findings from teachers’ interviews. In this respect, teachers’ perspectives about ICC are explored to highlight the challenging nature of teaching ICC and the pedagogic issues it raises given the inconclusiveness of existing teaching models. Finally, practical considerations are suggested for teachers to implement the intercultural dimension into their language classroom.
The Interdisciplinary Center, Herzliya

One of the best practices for Distributed Denial of Service (DDoS) resiliency in the cloud is the auto-scaling mechanism, where machines can be added and removed in an online manner to respond to ﬂuctuating load. It is commonly believed that the auto-scaling mechanism translates the DDoS attacks into Economic Denial of Sustainability attack (EDoS). Rather than suﬀering from performance degradation up to a total denial of service the victim suﬀers only from economic damage incurred by paying the extra resources required to process the bogus traﬃc of the attack. In this paper we analyze the ’Yo-Yo attack’, an eﬃcient attack on the auto-scaling mechanism. In the Yo-Yo attack, the attacker sends periodic bursts of overload, thus causing the auto-scaling mechanism to oscillate be-tween scale-up and scale-down phases. The Yo-Yo attack causes signiﬁcant performance degradation in addition to economic damage, while the attack is harder to detect and requires less resources from the attacker compared to traditional DDoS. We demonstrate the attack on Amazon EC2 [2], and analyze protection measures the victim can take by reconﬁguring the auto-scaling mechanism. Our work shows that DDoS mitigation is a crucial component in cloud environment, and that auto-scaling is not a bullet-proof remedy.
A Novel Approach to Unsupervised Automated Extraction of Standard Cell Library for Reverse Engineering and Hardware Assurance

Reverse engineering today is supported by several tools, such as ICWorks, that assist in the processing and extraction of logic elements from high definition layer by layer images of integrated circuits. To the best of our knowledge, they all work under the assumption that the standard cell library used in the design process of the integrated circuit is available. However, in situations where reverse engineering is done on commercial off-the-shelf components, this information is not available thereby, rendering the assumption invalid. Until now, this problem has not been addressed. In this paper, we introduce a novel approach for the extraction of standard cell library using the contact layer from these images. The approach is completely automated and does not require any prior knowledge on the construction or layout of the target semiconductor integrated circuit. The performance of the approach is evaluated on two AES designs with 10,000 cells compiled from standard libraries with 32nm and 90nm node technologies having 350 and 340 standard cells respectively. We were able to successfully extract 94% and 60% of the standard cells from the 32nm and 90nm AES designs using the proposed approach. We also perform a case study using a realworld sample extracted from a smartcard. Finally, we also investigate the various challenges involved in the extraction of standard cells from images and the steps involved in resolving them.
An Actuarial Pricing Method for Air Quality Index Options

Poor air quality has a negative impact on social life and economic production activities. Using financial derivatives to hedge risks is one of the important methods. Air quality index (AQI) options are designed to help enterprises cope with the operational risk caused by air pollution. First, the expanded Ornstein–Uhlenbeck model is established using an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH) method to predict AQI for a city. Next, the average AQI is constructed to be as the underlying index for the AQI options. We then priced AQI options using an actuarial method with an Esscher transform. Meanwhile payoff functions for the options are established to let enterprises hedge against the operational risk caused by air pollution. Finally, we determined the price of AQI options using data from Xi’an, China, and the example of a tourism enterprise as a case study of how AQI options can be applied to hedge against operational risk for enterprises. With AQI options trading, enterprises can hedge against operational risks caused by air pollution. The applicability of AQI options is wide, it can also be applied in other cities or regions.
C-S & S-C Monitoring of Time and Cost Variances of Schedule Using Complex Earned Value Method Indicators

Planning and implementation of construction projects are difficult processes and are burdened with many risk elements. The budget spread over time, which is developed on the basis of the schedule, presents the expected distribution of costs throughout the duration of the works, which during the implementation of the project is subject to constant changes resulting from time, cost and organizational factors. Managing construction contracts requires managers to be able to analyze on an ongoing basis the variances of production costs from the values calculated in the offer cost estimate and assumed in the Budgeted Cost of Work Scheduled. The article attempts to analyze the emerging time and cost variances using proprietary C-S and S-C monitoring, based on simple indicators of the EVM method. An example of construction of a multi-family housing development was used to study the variances of planned and incurred costs.
Qualifying Paper 1: A Corpus Study of Left Dislocation and Topicalization

2 The Data 3 2.1 The structure of the corpus . 3 2.1. 1 Information status annotation . 4 2.1. 2 Animacy annotation . 6 2.1. 3 Annotation of corpus sample . 8 2.2 Data extraction . 8 2.2.1 Animacy and Information status . 11 2.2.2 Grammatical function . 11 2.2. 3 Grammatical weight . 12 2.2. 4 Speaker . 13 2.2. 5 Referential Distance . 13
Fluid Viscosity and Corresponding Effects on Fluid flow, Velocity Magnitude and Electric Field Distribution in Electrohydrodynamic Jetting.

The phenomenon of electrohydrodynamic (EHD) jetting is affected by both the flow and electric properties of the dielectric fluid. A computational fluid dynamics (CFD) approach has been used to analyse the resultant effect of fluid viscosity on EHD flows. This study looks at the unique effect of fluid viscosity on the flow profile, velocity magnitude and the electric field distribution. It is very difficult to experimentally study these relationships, but CFD provides insights that can open the world of Electrohydrodynamics to new levels of applications; as this will give an idea of how to manipulate the jet formation. Viscosity has been highlighted as one of the key parameters that aid jet elongation and stability. Therefore, the necessity to study its role. Most studies have been carried out experimentally, but this paper provides computation insights. To solve the multiphase problem, a finite volume method using the Volume of Fluid approach for capturing the shape of the interface was used for the investigation. The leaky dielectric model which describes the process solves the combination of the Charge Transport Model and Navier-Stokes equations simultaneously. The transient liquid-gas interface tracking was achieved using the VOF technique. Among many other features observed, the results showed that it takes more time for the electric field to overcome the opposing surface tension of the solution at higher viscosity than at lower viscosity. Higher electric field magnitudes/strength were observed for the fluid of lower viscosity than that of the higher viscosity. Also, an increase in the viscosity reduces the droplet size/jet diameter.
Analysis, Modeling and Simulation of Multiscale Problems Mesoscopic modeling for continua with pores: dynamic void growth in viscoplastic metals

SSSS SSSS SSSS SSSS SSSSS SSSSS SSSSSS SSSSSS SSS SSS SSS SSS AMS MSP SSS SSS SSS SSSSS SSS SSS SSS SSS SSS SSS SSS SSS SSSSS SSSSS AMSMSPAMSM PPPPP PPPPP PPPP PP PPPPP PPPPP PPPPP PPPPP PPPPP PP PPPP PPPPP PPPPP PPPPPPPPPPP MMM MMMMM MMMMM MMM MMM MMM MMM MMM MMM MMM MMM MMM MMM AMSMSPAMSMSPA MMM MMM MMMMMM MMMMMM PAMSMSPAMSMSP AAA AAAA AAA AAA AAA AAA AAA AAA AAA AAAA AAAAAAAAAAAA AAA AAA AAA AAAAA
Feed Forward Backpropagation Neural Network Model to Predict Remaining Useful Life Estimation of Ion Implant Tool

--This paper proposes a feed forward backpropagation neural network (NN) based remaining useful life (RUL) prediction approach. Estimation of remaining useful life (RUL) is an important tool to reduce maintenance cost of equipment. The accurate RUL prediction based on the current and previous health condition of the equipment is essential to make a timely maintenance decision for failure avoidance. In this paper, an artificial neural network (ANN) based method is developed for achieving more accurate remaining useful life prediction of semiconductor manufacturing equipment. The ANN model takes the multiple measurement values at the current and history inspection points as the inputs, and the output is the remaining life hours of the equipment. The ANN RUL prediction uses FeedForward Backpropagation Neural Network (FFBPNN) with Levenberg Marquardt of training algorithm. The effects of changing the number of neurons in the input layer, the number of neurons in the hidden layer, the rate of learning, and the momentum constant are investigated. We employed variable importance analysis in identify critical feature variables to be given as input for an artificial neural network (ANN) to predict the lifetime of tungsten filament. The objective of this research paper is to propose a predictive model to be able to evaluate the health state of tungsten filament and to estimate the RUL of the component.
Investigating keyword extraction for identifying units of stance in legislative texts

This paper examines the language and legal terms used in EU and UK legislative texts, in a case study on immigration law. The theoretical and methodological frameworks combine discourse analysis and corpus linguistic techniques, applied to a small corpora of 400.000 words (1988-2009), subsequently divided into two sub-corpora. The analysis investigates the semantic relations around keywords and keyword clusters (ngrams) by carrying out concordance analyses of collocations and observing the frequencies of specific terms, such as deportation, leave to enter. Arguably, the lexico-semantic/grammatical patterns produced reveal the underlying discourse of a government’s stance towards immigration. The analysis also makes use of the related notions of semantic prosody (Louw, 1993), semantic preference and discourse prosody (Stubbs, 2002), for example through an analysis of cultural keywords and the collocates of alien, asylum and illegal, and other node words around the nexus immigrant/crime/terrorism.