Miracle-dz/UniFAR-FTUs huggingface dataset:
Apical tuft input efficacy in layer 5 pyramidal cells from rat visual cortex

1 The integration of synaptic inputs to the apical dendrite of layer 5 neocortical pyramidal cells was studied using compartment model simulations. The goal was to characterize the generation of regenerative responses to synaptic inputs under two conditions: (a) where there was an absence of background synaptic input, and (b) when the entire cell surface was subjected to a uniform blanket of synaptic background conductance such that somatic input resistance was reduced 5‐fold. 2 Dendritic morphology corresponded to a layer 5 thick‐trunked pyramidal cell from rat primary visual cortex at postnatal day 28 (P28), with distribution of dendritic active currents guided by the electrophysiological characteristics of the apical trunk reported in this cell type. Response characteristics for two dendritic channel distributions were compared, one of which supported Ca2+ spikes in the apical dendrite. 3 In the absence of background, synaptic input to the apical tuft was surprisingly effective in eliciting somatic firing when compared with input to apical oblique branches. This result obtained even when the tuft membrane was the least excitable in the dendritic tree. 4 The special efficacy of tuft input arose because its electrotonic characteristics favour development of a sustained depolarization which charged the apex of the apical trunk to its firing threshold; once initiated in the distal trunk, firing propagated inward to the soma. This mechanism did not depend upon the presence of depolarizing channels in tuft membrane, but did require an excitable apical trunk. 5 Rather than disconnect the tuft, background synaptic conductance enhanced the efficacy advantage enjoyed by input arriving there. This counterintuitive result arose because background reduced the subthreshold spread of voltage, and so diminished the ability of the excitation of various individual oblique branches to combine to charge the relatively thick adjacent trunk. In contrast, drive from the depolarized tuft is exerted at a single critical point, the apex of the distal trunk, and so was relatively undiminished by the background. Further, once initiation at the apex occurred, background had little effect on inward propagation along the trunk. 6 We conclude that synaptic input to the apical tuft of layer 5 cells may be unexpectedly effective in triggering cell firing in vivo. The advantage in efficacy was not dependent upon the characteristics of tuft membrane excitability, but rather stemmed from the geometry of the tuft and its junction with the distal apical trunk. The efficacy of tuft input was, however, critically dependent upon inward propagation, suggesting that modulation of membrane currents which affect propagation in the apical trunk might sensitively control the efficacy of tuft input.
Modeling and Simulation : Applications , Methodology , Technology

This paper introduces a method to integrate Unmanned Aircraft Systems (UASs) into a highly functional manned/ unmanned team through the design and implementation of 3D distributed formation/flight control algorithms with the goal to act as wingmen for a manned aircraft. The proposed algorithms are designed to increase UAS autonomy, dynamically modify formations, utilize standard operating formations to reduce pilot resistance to integration, and support splinter groups for surveillance and/or as safeguards between potential threats and manned vehicles. The proposed work coordinates UAS members by utilizing artificial potential functions whose values are based on the state of the unmanned and manned assets including the desired formation, obstacles, task assignments, and perceived intentions. The overall unmanned team geometry is controlled using weighted potential fields. Individual UASs utilize fuzzy logic controllers for stability and navigation as well as a fuzzy reasoning engine for predicting the intent of surrounding aircrafts. Approaches are demonstrated in simulation using the commercial simulator X-Plane and controllers designed in Matlab/Simulink. Experiments include staggered trail and right echelon formations as well as splinter group surveillance.
Display motion blur: Comparison of measurement methods

Abstract— Motion blur is a significant display property for which accurate, valid, and robust measurement methods are needed. Recent motion‐blur measurements of a set of eight displays by a set of six measurement devices provided an opportunity to evaluate techniques of measurement and analysis. Both the raw data waveforms collected by each device and the metrics derived from those waveforms were examined. Significant discrepancies between instruments and variability within instruments were found. A new motion‐blur metric (GET) that exhibits increased robustness and reduced variability relative to existing metrics is proposed.
Detection of weak signals based stochastic resonance and application in FOG

In engineering signal processing, parameters of the signal are often submerged by noise. In paper, a method called stochastic resonance (SR) was used to improve the SNR of system. The zero-averaged stochastic noise with normal probability distribution function and adaptable bandwidth could be produced, in which the thermal noise from a resistor is operated as initial noise source and processed by a suitable circuit. Numerical simulation proves its effectiveness. The method could be used to detect useful weak signal of fiber-optic gyroscope (FOG) submerged by noise. And then the dead-band of FOG could be restrained according to the stochastic resonance. Finally, theoretic analysis showed that this method might be applied in other weak signal detection systems based on stochastic resonance effect.
Designing a Global Authentication Infrastructure

We address the problem of scaling authentication for naming, routing, and end-entity certification to a global environment in which authentication policies and users' sets of trust roots vary widely. The current mechanisms for authenticating names (DNSSEC), routes (BGPSEC), and end-entity certificates (TLS) do not support a coexistence of authentication policies, affect the entire Internet when compromised, cannot update trust root information efficiently, and do not provide users with the ability to make flexible trust decisions. We propose a Scalable Authentication Infrastructure for Next-generation Trust (SAINT), which partitions the Internet into groups with common, local trust roots, and isolates the effects of a compromised trust root. SAINT requires groups with direct routing connections to cross-sign each other for authentication purposes, allowing diverse authentication policies while keeping all entities globally verifiable. SAINT makes trust root management a central part of the network architecture, enabling trust root updates within seconds and allowing users to make flexible trust decisions. SAINT operates without a significant performance penalty and can be deployed alongside existing infrastructures.
Incremental Phonological Encoding during Unscripted Sentence Production

We investigate phonological encoding during unscripted sentence production, focusing on the effect of phonological overlap on phonological encoding. Previous work on this question has almost exclusively employed isolated word production or highly scripted multi-word production. These studies have led to conflicting results: some studies found that phonological overlap between two words facilitates phonological encoding, while others found inhibitory effects. One worry with many of these paradigms is that they involve processes that are not typical to everyday language use, which calls into question to what extent their findings speak to the architectures and mechanisms underlying language production. We present a paradigm to investigate the consequences of phonological overlap between words in a sentence while leaving speakers much of the lexical and structural choices typical in everyday language use. Adult native speakers of English described events in short video clips. We annotated the presence of disfluencies and the speech rate at various points throughout the sentence, as well as the constituent order. We find that phonological overlap has an inhibitory effect on phonological encoding. Specifically, if adjacent content words share their phonological onset (e.g., hand the hammer), they are preceded by production difficulty, as reflected in fluency and speech rate. We also find that this production difficulty affects speakers’ constituent order preferences during grammatical encoding. We discuss our results and previous works to isolate the properties of other paradigms that resulted in facilitatory or inhibitory results. The data from our paradigm also speak to questions about the scope of phonological planning in unscripted speech and as to whether phonological and grammatical encoding interact.
The hypercoagulable profile of patients with stent thrombosis

Objective Coronary stent thrombosis is a devastating complication after percutaneous coronary intervention (PCI). The mechanisms underlying stent thrombosis are multifactorial. Whether the coagulation system is involved in the pathophysiology of stent thrombosis is unclear. We hypothesised that thrombin generation, reflecting the coagulation potential, is enhanced in patients with stent thrombosis. Methods A case–control study was performed, including 63 patients with PCI: 23 cases (stent thrombosis) and 40 controls (no stent thrombosis). Thrombin generation was measured using 0, 1 and 5 pM tissue factor (TF) triggers. Active site-inhibited factor VIIa (ASIS) and recombinant thrombomodulin were added to study the contact activation system and the protein C pathway, respectively. Results Thrombin generation was significantly increased for all TF triggers in cases compared with controls. Addition of ASIS to the measurement without exogenous TF revealed significantly enhanced contact activation in cases compared with controls; mean peak height: 241 vs 183 nM. Thrombin generation was also significantly increased in cases compared with controls in the presence of exogenous TF; mean peak height: 263 vs 233 nM (5 pM TF). Addition of thrombomodulin reduced thrombin generation by 23% in cases and 31% in controls (p<0.018), suggesting alterations in the protein C pathway in cases. Conclusions This is the first study that suggests the involvement of the coagulation system in stent thrombosis. Stent thrombosis patients showed a hypercoagulable state, most likely caused by enhanced contact activation and attenuation of anticoagulation by the protein C pathway.
Genotyping of the Pseudorabies Virus by Multiplex PCR Followed by Restriction Enzyme Analysis

Suid herpesvirus 1 (SuHV-1) is the causative agent of Aujeszky's disease. The infectious agent has only one serotype, but it was classified by restriction enzyme analysis of the whole genome into four genotypes, named I to IV. The aim of this study was to standardize a rapid method for genotyping SuHV-1 without virus isolation, using a multiplex-PCR followed by enzymatic restriction analysis. The complete genome of the virus was analyzed in silico to determine the restriction sites for the enzyme BamHI. Primers were designed to flank sites with emphasis on certain points of differentiation of genotypes. The standard PCRs were able to detect the SuHV-1 and also to differentiate genotypes from brain tissue of infected pigs. The BamHI-PCR is a rapid, practical, and sensitive way to genotype SuHV-1.
Learning Task-Relevant State Spaces with a Utile Distinction Test

This paper presents a reinforcement learning algorithm tha t learns an agent-internal state space on-line, in response t the demands of the task—thus avoiding the need for the agent designer to delicately engineer the agent's internal state space. The algorithm scales well with (1) large perceptual state spaces by pruning away unnecessary features, and (2) “overly small” perceptual state spaces ( i.e. hidden state) by augmenting the provided features with short-term memory of past features. The algorithm, calledU-Tree, uses a tree-structured representation, and is related to work on Prediction Suffix Trees (Ron, Singer, & Tishby 1994), Parti-game (Moore 1993), Galgorithm (Chapman & Kaelbling 1991), and Variable Resolution Dynamic Programming (Moore 1991). U-Tree is a direct descendant of Utile Suffix Memory (McCallum 1995c), which used short-term memory, but not selective perception . U-Tree is demonstrated solving a highway driving task in which the agent weaves around slower and faster traffic. The agent uses active perception with simulated eye movements based on perception from the driver's point of view. The environment has hidden state, time pressure, stochasticity, over 21,000 world states and over 2,500 percepts. The algorithm successfully solves this task, using its utile distinction est to build a tree that has just 143 agent internal states.
Achieving convergence, causality preservation, and intention preservation in real-time cooperative editing systems

Real-time cooperative editing systems allow multiple users to view and edit the same text/graphic/image/multimedia document at the same time for multiple sites connected by communication networks. Consistency maintenance is one of the most significant challenges in designing and implementing real-time cooperative editing systems. In this article, a consistency model, with properties of convergence, causality preservation, and intention preservation, is proposed as a framework for consistency maintenance in real-time cooperative editing systems. Moreover, an integrated set of schemes and algorithms, which support the proposed consistency model, are devised and discussed in detail. In particular, we have contributed (1) a novel generic operation transformation control algorithm for achieving intention preservation in combination with schemes for achieving convergence and causality preservation and (2) a pair of reversible inclusion and exclusion transformation algorithms for stringwise operations for text editing. An Internet-based prototype system has been built to test the feasibility of the proposed schemes and algorithms
Formal static fault tree analysis

Fault tree analysis (FTA) is a traditional informal reliability and safety analysis technique. FTA is basically a combinational model in which standard Boolean logic constructs, such as AND and OR gates, are used to decompose the fault events. Several dynamic constructs, such as Functional Dependency (FDEP) and Priority AND (PAND) gates, are also proposed to handle dynamic behaviors of system failure mechanisms. In this article, we focus on some paradoxes and constraints of the traditional FDEP and PAND gates, and present our static solutions to these dynamic gates. The proposed static fault tree model is formalized with Maude, an executable algebraic formal specification language. Two example fault tolerant parallel processor (FTPP) configurations are used to demonstrate our static fault tree model.
A puncturing algorithm for rate-compatible LDPC convolutional codes

A family of rate-compatible (RC) punctured low-density parity-check convolutional codes (LDPC-CCs) is derived from an LDPC-CC by periodically puncturing encoded bits (variable nodes) with respect to several criteria: (1) ensuring the recoverability of punctured variable nodes, (2) minimizing the number of completely punctured cycle trapping sets (CPCTSs), and (3) minimizing the number of punctured variable nodes involved in short cycles. As an example, a family of RC punctured LDPC-CCs with rates 4/9, 4/8, 4/7, 4/6, and 4/5 are obtained from the (21,3, 5) Tanner LDPC-CC.
Smart material interfaces: a new form of physical interaction

Smart Material Interface (SMI) is the latest generation of user interface that makes use of engineered materials and leverages their special properties. SMIs are capable of changing their physical properties such as shape, size and color, and can be controlled under certain (external) conditions. We provide an example of such an SMI in the form of a prototype of a vacuum cleaner. The prototype uses schematic electrochromic polymer at the suction nozzle of the vacuum cleaner, which changes its color depending on the dust level on a floor. We emphasize on the new affordances and communication language supported by SMIs, which challenges the current metaphors of user interfaces in the field of HCI.
Brain Gray Matter Decrease in Chronic Pain Is the Consequence and Not the Cause of Pain

Recently, local morphologic alterations of the brain in areas ascribable to the transmission of pain were reported in patients suffering from chronic pain. Although some authors discussed these findings as damage or loss of brain gray matter, one of the key questions is whether these structural alterations in the cerebral pain-transmitting network precede or succeed the chronicity of pain. We investigated 32 patients with chronic pain due to primary hip osteoarthritis and found a characteristic gray matter decrease in patients compared with controls in the anterior cingulate cortex (ACC), right insular cortex and operculum, dorsolateral prefrontal cortex (DLPFC), amygdala, and brainstem. We then investigated a subgroup of these patients (n = 10) 6 weeks and 4 months after total hip replacement surgery, monitoring whole brain structure. After surgery, all 10 patients were completely pain free and we observed a gray matter increase in the DLPFC, ACC, amygdala, and brainstem. As gray matter decrease is at least partly reversible when pain is successfully treated, we suggest that the gray matter abnormalities found in chronic pain do not reflect brain damage but rather are a reversible consequence of chronic nociceptive transmission, which normalizes when the pain is adequately treated.
Efficient computation of the degree of belief in a propositional theory

We design a novel model-based approach for reasoning, considering the reasoning process as the computation of the degree of belief of an intelligent agent. We assume a Knowledge Base (KB) expressed by a two Conjunctive Form (2-CF) Σ. We represent Σ using an appropriate logical structure. Our representation of a 2-CF is highly expressive since it supports efficient reasoning, even in the cases where the formula-based representation does not allow to do it. Indeed, we can compute the degree of belief with new information (a literal or a binary clause) efficiently, providing an efficient scheme of inductive reasoning. Exploiting this logical structure of a 2-CF, we propose a way to determine the relative value for every element in the KB which is an essential problem when new knowledge is aggregated and is necessary to maintain the consistency of the KB.
Frequency Estimation for Sychrophasor Measurement Units in Power System Luoyang Fang and

Frequency estimation is a crucial signal processing technique in Phasor Measurement Units (PMU). In this report, we propose a new algorithm for frequency estimation by interpolation of zero-padded discrete Fourier transform (DFT) samples. The bias performance of the proposed estimator is analyzed and an iterative algorithm is further proposed to reduce the bias to an arbitrarily small level. Simulations show that our proposed algorithm have the best performance among existing ones in the literature. In addition, the performance of our algorithm can satisfy the requirements of standard C37.118. 1, with short observation windows.
The Complex Gradient Operator and the CR-Calculus ECE275A - Lecture Supplement - Fall 2005

A thorough discussion and development of the calculus of real-valued functions of complex-valued vectors is given using the framework of the Wirtinger Calculus. The presented material is suitable for exposition in an introductory Electrical Engineering graduate level course on the use of complex gradients and complex Hessian matrices, and has been successfully used in teaching at UC San Diego. Going beyond the commonly encountered treatments of the first-order complex vector calculus, second-order considerations are examined in some detail filling a gap in the pedagogic literature.
Gondola: a Parametric Robot Infrastructure for Repeatable Mobile Experiments: Demo Abstract

When deploying a testbed infrastructure for Wireless Sensor Networks (WSNs), one of the most challenging features is to provide repeatable mobility. Wheeled robots, usually employed for such tasks, strive to adapt to the wide range of environments where WSNs are deployed, from chaotic office spaces to neatly raked potato fields. For this reason, wheeled robots often require an expensive customization step in order to adapt, for example, their localization and navigation systems to the specific environment. To avoid this issue, we present Gondola, a parametric robot infrastructure based on pulling wires, rather than wheels. Gondola avoids the most common problems of wheeled robots and easily adapts to many WSNs' scenarios. Different from existing solutions, Gondola can easily move in 3-dimensional space, with no need of a complex localization system and with an accuracy that is comparable to off-the-shelf traditional robots.
Recurrence and Treatment after Renal Transplantation in Children with FSGS

Focal segmental glomerulosclerosis (FSGS) is a common cause of end-stage renal disease and a common pathologic diagnosis of idiopathic nephrotic syndrome (NS), especially in steroid-resistant cases. FSGS is known to recur after kidney transplantation, frequently followed by graft loss. However, not all patients with FSGS suffer from recurrence after kidney transplantation, and genetic and secondary FSGS have a negligible risk of recurrence. Furthermore, many cases of recurrence achieve remission with the current management of recurrence (intensive plasmapheresis/immunosuppression, including rituximab), and other promising agents are being evaluated. Therefore, a pathologic diagnosis of FSGS itself should not cause postponement of allograft kidney transplantation. For patients with a high risk of recurrence who presented with classical symptoms of NS, that is, severe edema, proteinuria, and hypoalbuminemia, close monitoring of proteinuria is necessary, followed by immediate, intensive treatment for recurrence.
George Lakoff. Women, Fire, and Dangerous Things: What Categories Reveal about the Mind . Chicago: University of Chicago Press. 1987. Pp. xvii + 614. US$29.95.

This is an ambitious and important book. Lakoff has taken as his task a comprehensive analysis of the nature of category formation. After an extensive critique of the traditional view that a category is determined solely by the properties (elements, features) shared by its members, Lakoff argues that there are several additional types of mental categories, each characterized by its own criteria. The book is rich in detail, exciting and insightful, and at times frustrating and opaque. Some sections are almost written in a point form reminiscent of an elaborate outline, although one might suspect that if such sections had been fleshed out in all their relevant detail, the book would have been three times as long. In other places details are tediously and unnecessarily elaborated to the extent that one sometimes loses the major trains of argument. The overall organization and structure are clear, but local instances of disorganization abound. I was left with the overall impression that the work would have benefitted greatly from of a ruthless editor.