Miracle-dz/UniFAR-FTUs huggingface dataset:
Membrane Mechanics of Endocytosis in Cells with Turgor

Endocytosis is an essential process by which cells internalize a piece of plasma membrane and material from the outside. In cells with turgor, pressure opposes membrane deformations, and increases the amount of force that has to be generated by the endocytic machinery. To determine this force, and calculate the shape of the membrane, we used physical theory to model an elastic surface under pressure. Accurate fits of experimental profiles are obtained assuming that the coated membrane is highly rigid and preferentially curved at the endocytic site. The forces required from the actin machinery peaks at the onset of deformation, indicating that once invagination has been initiated, endocytosis is unlikely to stall before completion. Coat proteins do not lower the initiation force but may affect the process by the curvature they induce. In the presence of isotropic curvature inducers, pulling the tip of the invagination can trigger the formation of a neck at the base of the invagination. Hence direct neck constriction by actin may not be required, while its pulling role is essential. Finally, the theory shows that anisotropic curvature effectors stabilize membrane invaginations, and the loss of crescent-shaped BAR domain proteins such as Rvs167 could therefore trigger membrane scission.
Dealing with Deviations on Software Process Enactment: Comparison Framework

Software development is a collective and complex task carried out through the cooperation of human agents and automated tools, this interaction defines the software process. PSEE (Process-centered Software Engineering Environment) are environments designed to support the creation and exploitation of software process models that define the expected behaviors of process agents. However, human agents may deviate from the process model; therefore, the PSEE should be flexible enough to cope with these unexpected actions. This paper deals with the problem of deviation during software process enactment; it gives an overview of significant research works that have been proposed to support deviations in the context of software process execution.
A collision-mitigation hashing scheme utilizing empty slots of cuckoo hash table

In SDN and NFV technologies, performance of a virtual switch is important to provide network functionalities swiftly. Since the lookup operation of the virtual switch has been considered a major bottleneck of performance, we need to devise an efficient way to reduce the lookup time. To improve the lookup speed, previous research has suggested a compact lookup table in a fast memory, but the issue of collision in a hash table has not been addressed well enough. This paper proposes a new scheme that mitigates collisions by utilizing empty slots of the hash table. We propose to insert a new element that may collide to an empty slot instead of linking it with a pointer. According to an evaluation on our experiments, about 20% of elements that could have experienced collisions in the conventional scheme are inserted into empty slots in each bucket. Moreover, the access time of collided elements has halved by avoiding unnecessary memory accesses.
Blind Image Watermarking Scheme in DWT-SVD Domain

Discrete Wavelet Transform (DWT) is widely applied to image watermarking applications because it decomposes a cover image into spatial domain as well as frequency domain simultaneously. Also, Singular Value Decomposition (SVD) is suitable for watermarking applications since some largest singular values are sufficient to embed watermarks instead of using all singular values. We propose a hybrid blind watermarking scheme based on DWT and SVD for image data. The proposed scheme embeds watermarks by modifying log-scaled singular value of selected coefficients of all sub-bands. We have found two properties to be robust against malicious attacks commonly happened to images. We performed experiments to prove that the proposed scheme has the robustness against to a wide range of attacks such as JPEG compression, Gaussian noise addition, median filtering, blurring, histogram equalization, gamma correction, reseating, shift, and rotation.
Particularism and Public Goods : The Effect of Incentives to Cultivate a Personal Vote on Education Spending and Performance

This paper explores how features of the electoral and party system affects the composition and efficiency of government spending--specifically government spending on education. In doing so we contribute to the literature the connection between institutions spending on two fronts. First, we move beyond the simple institutional dichotomies that characterize many existing studies (e.g. presidential v. parliamentary or majoritarian versus PR) and focus instead on the incentives to cultivate a personal vote generated by the electoral and party system. Second, we not only consider how institutions shape the level and composition of government spending, we also demonstrate how those spending decisions affect public goods outcomes. We argue that where the party system emphasizes political particularism resources are allocated less efficiently and the effect of increased spending on literacy is diminished. We test our hypotheses using data on education spending and performance in over 60 developing democracies since 1978. We find that though personal vote systems spend just as much on education as party vote systems, incentives to cultivate a personal vote are associated with higher levels of illiteracy. This is because the particularism in personal vote systems dampens the marginal effect of increased education spending on illiteracy and at its highest levels particularism completely undermines the positive effects of increased education spending on literacy. Finally, we find that the modifying effect of particularism on education spending is strongest when electoral competition is most meaningful—namely, at higher levels of democracy.
N-to-SRGB Mapping for Single-Sensor Multispectral Imaging

Visualization of a multispectral image in a standard color space, typically the sRGB space, is an important task for human color perception. When we reproduce the sRGB image from the multispectral image with N spectral bands, an N-to-sRGB mapping is required. The challenge of the N-to-sRGB mapping in single-sensor multispectral imaging with a multispectral filter array (MSFA) is to reduce demosaicking error amplification and propagation across different spectral bands, which are not trivial because of very sparse sampling of multiple spectral bands in a single image sensor. In this paper, we propose a novel N-to-sRGB mapping pipeline for effectively suppressing the demosaicking error amplification and propagation. Our idea is to apply guided filtering in the mapped sRGB space using one of input N band images before the amplification and propagation as a guide image. Experimental results demonstrate that our proposed pipeline improves the mapping accuracy for various MSFA types.
DESIGN AND DEVELOPMENT OF CONTROL MODULE FOR BATTERY CHARGING AND MONITORING

This paper presents the preliminary development of efficient control module for battery charging and monitoring. While designing a charging system for battery some parameters must be considered such as the state of charge, lifecycle of battery and charging time. These parameters are monitored and controlled with the help of Atmega microcontroller. This embedded module is interfaced with charging module for the battery. The battery used in this work is a lead acid battery. A two stage charging technique, includes combination of constant current and constant voltage source which is used to charge lead acid battery. Index Terms Batteries, Constant Current Mode, Constant Voltage Mode, Lead Acid Battery, Microcontroller, Thermal Management
Health behaviors during and after a cancer diagnosis

With improvements in cancer survival rates, more patients with cancer are living longer, and hence, cancer is becoming viewed as a chronic illness requiring long‐term management. An important aspect of patient care during and after cancer treatment is patient health behaviors. For example, sequelae from various cancer treatments, such as chemotherapy and radiotherapy (RT), can compromise health in a variety ways, including decreased immune functioning, cardiotoxic effects of chemotherapy and/or RT, and weight gain. In addition, the stress caused by a cancer diagnosis and its treatment can disrupt existing health behaviors or exacerbate unhealthy behaviors. Continued smoking or alcohol use can complicate treatment and increase risk for further malignancy. Furthermore, decreased physical activity and poor nutrition can cause weight gain, which may contribute to secondary health problems such as cardiovascular disease and diabetes. The authors reviewed the extant literature on four key health behaviors among patients with cancer and survivors: healthy diet, reduced tobacco use, reduced alcohol use, and increased physical activity. They described the prevalence of these behaviors, reviewed the effects of interventions designed to alter unhealthy behaviors, and discussed the implications and future directions for this emerging area of research. Cancer 2005. © 2005 American Cancer Society.
How good is the Chord algorithm?

The Chord algorithm is a popular, simple method for the succinct approximation of curves, which is widely used, under different names, in a variety of areas, such as, multiobjective and parametric optimization, computational geometry, and graphics. We analyze the performance of the chord algorithm, as compared to the optimal approximation that achieves a desired accuracy with the minimum number of points. We prove sharp upper and lower bounds, both in the worst case and average case setting.
Manipulating Kv4.2 identifies a specific component of hippocampal pyramidal neuron A‐current that depends upon Kv4.2 expression

The somatodendritic A‐current, ISA, in hippocampal CA1 pyramidal neurons regulates the processing of synaptic inputs and the amplitude of back propagating action potentials into the dendritic tree, as well as the action potential firing properties at the soma. In this study, we have used RNA interference and over‐expression to show that expression of the Kv4.2 gene specifically regulates the ISA component of A‐current in these neurons. In dissociated hippocampal pyramidal neuron cultures, or organotypic cultured CA1 pyramidal neurons, the expression level of Kv4.2 is such that the ISA channels are maintained in the population at a peak conductance of approximately 950 pS/pF. Suppression of Kv4.2 transcripts in hippocampal pyramidal neurons using an RNA interference vector suppresses ISA current by 60% in 2 days, similar to the effect of expressing dominant‐negative Kv4 channel constructs. Increasing the expression of Kv4.2 in these neurons increases the level of ISA to 170% of the normal set point without altering the biophysical properties. Our results establish a specific role for native Kv4.2 transcripts in forming and maintaining ISA current at characteristic levels in hippocampal pyramidal neurons.
Ultra wideband propagation for future in-body sensor networks

Body area network (BAN) technology can enable the real-time collection and monitoring of physiological signals for personalized healthcare. Implantable biomedical sensors transmitting continuously clinical information to an external unit can facilitate the involvement of the patients in the management of chronic diseases. In addition, ingestible sensors like the wireless capsule endoscope (WCE) have been proven extremely useful as clinical diagnostic tools. It is envisaged that such devices will evolve to also perform in-body therapeutic procedures. Future medical applications may require the interconnection of two or more of these in-body devices to interchange information for better diagnostics or to relay data from deeply implanted sensors. In this context, ultra wideband (UWB) radio links can be used for the communication interfaces of in-body sensors due to their large bandwidth and low power consumption. Nevertheless, little is known about the behavior of the in-body to in-body (IB2IB) radio channel in the UWB spectrum. This paper aims to fill this gap by providing insight into the behavior of the IB2IB channel based on propagation measurements in 3.1-8.5 GHz. Because of the impossibility to conduct in-body measurements with human subjects, we used a phantom that emulated the dielectric characteristics of the human muscle tissue. The path loss as a function of the distance between antennas and the frequency are thoroughly discussed.
Fast First-order Methods for the Massive Robust Multicast Beamforming Problem with Interference Temperature Constraints

In this paper, we consider the large-scale case of the robust beamforming problem with interference temperature constraints. Previous semidefinite relaxation (SDR) method becomes impracticable because of its expensive computational cost. Even successive convex approximation (SCA) method, the state-of-the-art method, cannot tackle this problem efficiently. Thus, we are motivated to design two efficient first-order methods, multi-block alternating direction method of multipliers (ADMM) and linear programming-assisted subgradient descent (LPA-SD), to solve it. Numerical results demonstrate the potential of our proposed methods in terms of both computational efficiency and solution quality.
Identification of autonomous landing sign for unmanned aerial vehicle based on faster regions with convolutional neural network

In order to realize autonomous landing of the unmanned aerial vehicle (UAV) in power patrolling, a visual method vision based on Faster Regions with Convolutional Neural Network (Faster R-CNN) for UAVs is studied. In this paper, we design the landing sign of the combination of concentric circles and pentagon, and propose the Faster R-CNN recognition algorithm which can be used to identify the target sign. Faster R-CNN successfully identifying the landing mark is the most important step for the UAV autonomous landing. Then, the estimation algorithm of position and direction based on vision is proposed. Position and direction for the UAV landing can be obtained based on least squares ellipse fitting and Shi-Tomasi corner detection method after the landing sign is effectively identified by Faster R-CNN. The experimental results show that it can achieve recognition speed of nearly 81 millisecond each frame and 97.8% accuracy by using Faster R-CNN for detection and identification. The proposed method has better identification accuracy compared with three target identification methods, the Support Vector Machine (SVM) classification, the Back Propagation (BP) neural network and You Only Look Once (YOLO) based on deep learning. The position and direction estimation error of the vision algorithm is within the allowable range, and it can meet the UAV real-time landing requirements.
Video search in video sharing site based on public video lists

A large number of video files are shared in video sharing sites in the internet. In this paper, we propose video community extracting methods based on web community extracting method, which consist of Fan pages and Center pages, tf-idf, and Zipf's low. With our proposed methods, a video and a video list are considered as a Center page and a Fan page in web community extraction, respectively. For evaluation, we executed video search using the proposed methods and compared the search results with those of other methods. Our experiments demonstrated that the proposed methods could provide better search results than other methods, such as web search engines.
Sigma: A New Open Economy Model for Policy Analysis

In this paper, we describe a new multicountry open economy SDGE model named "SIGMA" that we have developed as a quantitative tool for policy analysis. We compare SIGMA's implications to those of an estimated large-scale econometric policy model (the FRB/Global model) for an array of shocks that are often examined in policy simulations. We show that SIGMA's implications for the near-term responses of key variables are generally similar to those of FRB/Global. Nevertheless, some quantitative disparities between the two models remain due to certain restrictive aspects of SIGMA's optimization-based framework. We conclude by using long-term simulations to illustrate some areas of comparative advantage of our SDGE modeling framework.
Requirements for Cell-Free Cyanide Oxidation by Pseudomonas Fluorescens NCIMB 11764

The involvement of cyanide oxygenase in the metabolism of pyruvate and a-ketoglutarate-cyanohydrin was investigated and shown to occur indirectly by the consumption of free cyanide arising from the cyanohydrins via chemical dissociation. Thus, free cyanide remains the substrate, for which the enzyme displays a remarkably high affinity (Kmapp,4 mM). A model for cyanide utilization is therefore envisioned in which the substrate is initially detoxified by complexation to an appropriate ligand followed by enzymatic oxidation of cyanide arising at sublethal levels via chemical dissociation. Putative cyanide oxygenase in cell extracts consumed both oxygen and NADH in equimolar proportions during cyanide conversion to CO2 and NH3 and existed separately from an unknown heat-stable species responsible for the nonenzymatic cyanide-catalyzed consumption of oxygen. Evidence of cyanide inhibition and nonlinear kinetics between enzyme activity and protein concentration point to a complex mechanism of enzymatic substrate conversion.
Generating Real-Time Crowd Advice to Improve Reinforcement Learning Agents

Reinforcement learning is a powerful machine learning paradigm that allows agents to autonomously learn to maximize a scalar reward. However, it often suffers from poor initial performance and long learning times. This paper discusses how collecting on-line human feedback, both in real time and post hoc, can potentially improve the performance of such learning systems. We use the game Pac-Man to simulate a navigation setting and show that workers are able to accurately identify both when a sub-optimal action is executed, and what action should have been performed instead. Our results demonstrate that the crowd is capable of generating helpful input. We conclude with a discussion the types of errors that occur most commonly when engaging human workers for this task, and a discussion of how such data could be used to improve learning. Our work serves as a critical first step in designing systems that use real-time human feedback to improve the learning performance of automated systems on-the-fly.
Adaptive One-Bit Compressive Sensing with Application to Low-Precision Receivers at mmWave

Multiple input multiple output (MIMO) systems employing large antenna arrays are the basic architecture for millimeter wave (mmWave) systems. Due to the higher bandwidths to be used at mmWave, the corresponding sampling rates of high-resolution analog-to-digital converters (ADCs) are also very high, so that ADCs become the most power hungry devices in the reception chain. One solution is to employ low resolution, i.e. one-bit, ADCs. We develop an adaptive one-bit compressed sensing scheme that can be used at low-resolution mmWave receivers for channel estimation. The simulation results show that the adaptive one-bit compressed sensing scheme outperforms the fixed one in the context of mmWave channel estimation.
LARGE SCALE EXPERIMENTS WITH FUNCTION TAGGING

We present in this paper large scale experiments with two De- cision Trees based approaches to the task of function tagging. The task of function tagging involves labeling certain nodes in an input parse tree with a set of functional marks such as logical subject, predicate, etc. In the flrst ap- proach, we consider only nodes that are labeled with a functional tag. In the second approach, all nodes are considered whether they are labeled with func- tion tags or not. The non-labeled nodes are simply considered being labeled with the generic tag NON-F. The results obtained on a standard data set are signiflcantly outperforming baseline approaches when the most frequent tag is assigned.
Activation of p38 MAP kinase and JNK but not ERK is required for erythropoietin-induced erythroid differentiation.

p38 MAP kinase (p38) and JNK have been described as playing a critical role in the response to a variety of environmental stresses and proinflammatory cytokines. It was recently reported that hematopoietic cytokines activate not only classical MAP kinases (ERK), but also p38 and JNK. However, the physiological function of these kinases in hematopoiesis remains obscure. We found that all MAP kinases examined, ERK1, ERK2, p38, JNK1, and JNK2, were rapidly and transiently activated by erythropoietin (Epo) stimulation in SKT6 cells, which can be induced to differentiate into hemoglobinized cells in response to Epo. Furthermore, p38-specific inhibitor SB203580 but not MEK-specific inhibitor PD98059 significantly suppressed Epo-induced differentiation and antisense oligonucleotides of p38, JNK1, and JNK2, but neither ERK1 nor ERK2 clearly inhibited Epo-induced hemoglobinization. However, in Epo-dependent FD-EPO cells, inhibition of either ERKs, p38, or JNKs suppressed cell growth. Furthermore, forced expression of a gain-of-function MKK6 mutant, which specifically activated p38, induced hemoglobinization of SKT6 cells without Epo. These results indicate that activation of p38 and JNKs but not of ERKs is required for Epo-induced erythroid differentiation of SKT6 cells, whereas all of these kinases are involved in Epo-induced mitogenesis of FD-EPO cells.
Flow Control Mechanism for Wireless Network-on-Chip

Network on chip (NoC) provides a network-based interconnect infrastructure that facilitates the communications among a slew of function cores in a modern System-on-chip (SoC) design. Apart from topology, switching technique and routing strategy adopted in an NoC, flow control scheme that regulates the packet injection rates is another determining factor that impacts the NoC efficiency. In this paper, we propose a Feedback-Based end-to-end congestion control scheme that supports Wireless NoC to make adjustment automatically' upon receiving a feedback message, the source node will adjust its packet size and transmission rate accordingly. Besides, an arbitration optimization strategy, fast-forward scheme is imported to assign higher priority to the downstream flits at the same input port and to the same next output port, thus lighten the resource waste caused by the rest communication tasks. Finally, simulation results indicate the superiority.
Dual-Frequency Miniaturized Substrate Integrated Waveguide Quarter-Mode Cavity-Backed Antenna Based on Minkowski Fractal Gap with Orthogonal Polarization Radiation Characteristics

A novel quarter-mode substrate integrated waveguide miniaturized cavity-backed antenna loading Minkowski fractal gap is presented in this paper. Firstly, the resonant frequency of the rectangular substrate integrated waveguide resonator is reduced by etching the fractal gap in the resonator to achieve miniaturization. In addition, because of the symmetry of electric field distribution in second and third order resonant modes, the cavity can be segmented into a quarter-mode and the other order resonance modes with asymmetric electric field distribution can be suppressed according to the cavity model theory. Hence, the cavity size is further reduced. The dimension of designed antenna is 0. 26λ0×0. 26λ0 (λ0 is the wavelength in free space; in this paper, the corresponding wavelength is 3.6 GHz). Moreover, the orthogonal polarization of the proposed antenna in two frequency bands is achieved because the electric field is orthogonal in second and third order resonant modes. This dual-frequency orthogonal polarization characteristic enables antenna to communicate in two working bands and has good channel isolation. The simulated and measured results are consistent. The antenna gain is 4.67dBi and 3.4dBi, respectively, at 3.7GHz and 4.6GHz.