Miracle-dz/UniFAR-FTUs huggingface dataset:
On Modeling Link Flooding Attacks and Defenses

The increasing popularity of Internet of Things (IoTs) is making people universally connected and thus bringing the ease of life. Because of their sheer volume, weak security, and continual operation, IoT devices, along with many computer servers, are widely compromised to launch powerful distributed denial-of-service (DDoS) attacks. The emerging link flooding attacks (LFAs) are one type of such attacks that attract significant attention in both academia and industry against the routing infrastructure. The attack traffic flows originating from bots (e.g., compromised IoT devices) are deliberately aggregated at upstream critical links and grow intensified, gradually making a network connected to the critical links disconnected. Although LFAs are far more sophisticated than traditional DDoS attacks, whether such sophistication comes without a downside has never been investigated. In this paper, by modeling link flooding attacks and defenses, we tackle a series of questions concerning the practical issues of LFAs. Specifically, from the perspective of attacks, we advance a novel notion of strike precision, and reveal that LFAs may exhibit attack interference (i.e., unexpectedly interfere the connectivity of innocent networks) which might undermine the stealthiness and persistence of LFAs. From the perspective of defenses, we make the first step to study attack intention, i.e., inversely inferring the target network to disconnect based on the identified links under attack. Furthermore, we consider a strong defender who employs traffic engineering to mitigate LFAs, and formulate the game-theoretic interactions between attackers and defenders. Our formulation demonstrates that LFAs can be effectively mitigated based on traffic engineering from a game-theoretic perspective. We also study practical issues of non-cooperative defenses (e.g., light-weight probe deployment, multi-protocol-based measurement).
Single-substrate integration technique of planar circuits and waveguide filters

The integrated planar technique has been considered as a reliable candidate for low-cost mass production of millimeter-wave circuits and systems. This paper presents new concepts that allow for a complete integration of planar circuits and waveguide filters synthesized on a single substrate by means of metallized post (or via-hole) arrays. Analysis of the synthesized integrated waveguide and design criteria are presented for the post pitch and diameter. A filter design method derived from a synthesis technique using inductive post is presented. An experimental three-pole Chebyshev filter having 1-dB insertion loss and return loss better than 17 dB is demonstrated. Integrating such planar and nonplanar circuits on a substrate can significantly reduce size, weight, and cost, and greatly enhance manufacturing repeatability and reliability.
Prolonged Postoperative Opioid Use After Arthroscopic Femoroacetabular Impingement Syndrome Surgery: Predictors and Outcomes at Minimum 2-Year Follow-up

Background: The association between prolonged postoperative opioid use on outcomes after hip preservation surgery is not known. Purpose: To compare minimum 2-year patient-reported outcomes (PROs) between patients who required ≥1 postoperative opioid refill after undergoing hip arthroscopy for femoroacetabular impingement syndrome (FAIS) versus patients who did not require a refill and to identify preoperative predictors for patients requiring ≥1 postoperative opioid refill. Study Design: Cohort study; Level of evidence, 3. Methods: Data from consecutive patients who underwent arthroscopic surgery for FAIS between January 2012 and January 2017 were analyzed. Multivariate regression analysis was performed to classify patient and radiographic variables as predictive of requiring ≥1 opioid prescription refill after surgery. Patients completed the following PROs preoperatively and at 2-year follow-up: Hip Outcome Score— Activities of Daily Living subscale (HOS-ADL), HOS–Sports Subscale (HOS-SS), modified Harris Hip Score (mHHS), International Hip Outcome Tool (iHOT-12), and 100-point visual analog scale (VAS) for pain and satisfaction. Scores were compared between patients needing additional prescription opioids and those who did not. Results: A total of 775 patients, of whom 141 (18.2%) required ≥1 opioid prescription refill, were included in the analysis. Patients requiring opioid refills had significantly lower 2-year postoperative PRO scores compared with patients not requiring refills: HOS-ADL (79.9 ± 20.3 vs 88.7 ± 14.9), HOS-SS (64.6 ± 29.5 vs 78.2 ± 23.7), mHHS (74.2 ± 21.1 vs 83.6 ± 15.9), iHOT-12 (63.6 ± 27.9 vs 74.9 ± 24.8), and VAS satisfaction (73.4 ± 30.3 vs 82.2 ± 24.9), as well as significantly more pain (26.8 ± 23.4 vs 17.9 ± 21.8) (P ≤ .001 for all). Predictors of requiring a postoperative opioid refill included patients with active preoperative opioid use (odds ratio, 3.12 [95% confidence interval, 1.06-9.21]; P = .039) and larger preoperative alpha angles (odds ratio, 1.04 [95% confidence interval, 1.01-1.07]; P = .03). Conclusion: Patients requiring ≥1 opioid prescription refill after hip arthroscopy for FAIS had lower preoperative and 2-year PRO scores when compared with patients not requiring refills. Additionally, active opioid use at the time of surgery was found to be predictive of requiring additional opioids for pain management.
Pathophysiological Potentials of NRF3-Regulated Transcriptional Axes in Protein and Lipid Homeostasis

NRF3 (NFE2L3) belongs to the CNC-basic leucine zipper transcription factor family. An NRF3 homolog, NRF1 (NFE2L1), induces the expression of proteasome-related genes in response to proteasome inhibition. Another homolog, NRF2 (NFE2L2), induces the expression of genes related to antioxidant responses and encodes metabolic enzymes in response to oxidative stress. Dysfunction of each homolog causes several diseases, such as neurodegenerative diseases and cancer development. However, NRF3 target genes and their biological roles remain unknown. This review summarizes our recent reports that showed NRF3-regulated transcriptional axes for protein and lipid homeostasis. NRF3 induces the gene expression of POMP for 20S proteasome assembly and CPEB3 for NRF1 translational repression, inhibiting tumor suppression responses, including cell-cycle arrest and apoptosis, with resistance to a proteasome inhibitor anticancer agent bortezomib. NRF3 also promotes mevalonate biosynthesis by inducing SREBP2 and HMGCR gene expression, and reduces the intracellular levels of neural fatty acids by inducing GGPS1 gene expression. In parallel, NRF3 induces macropinocytosis for cholesterol uptake by inducing RAB5 gene expression. Finally, this review mentions not only the pathophysiological aspects of these NRF3-regulated axes for cancer cell growth and anti-obesity potential but also their possible role in obesity-induced cancer development.
A Physics-Guided Neural Network Dynamical Model for Droplet-Based Additive Manufacturing

This article develops a physics-guided data-driven model for the height evolution of parts printed in droplet-based additive manufacturing. The proposed model is a convolutional recurrent neural network (ConvRNN) whose structure is derived based on the physical understanding of mass conservation during the height evolution. Because of this physics-guided model structure, the model parameters obtained are invariant to the geometry of the printed part and thus portable from one geometry to another, the conditions on physical stability of the evolution translate directly to training stability of the neural network, and the data required to train this model are much less compared to a pure black-box model. These aspects of the model are validated experimentally on an inkjet 3-D printing setup. The proposed model outperforms a black-box off-the-shelf multilayer perceptron (neural network) by using about two orders of magnitude less data for training, at the same time delivering $1.7\times $ smaller rms error on test data. The proposed model is also compared with a state-of-the-art reduced order linear model and shows $1.4\times $ smaller rms error on test data. Finally, experimental results also underline that the model parameters learned are geometry invariant, that is, the model parameters trained on one geometry can be used to predict the height map evolution for other geometries without relearning.
A Study on 3D Virtual Clothing by Utilizing Digital Fashion Show

*IT technology has been rapidly introduced to the clothing and fashion industry, and especially fashion shows have been changed very fast to keep up with the current digital era. In this research, the author designed virtual clothes, and investigated whether it is possible to make them similar to actual clothes and then performed a digital fashion show with these virtual clothes. This research discussed, based on case development and studies, whether a digital fashion show can express the designer`s idea more creatively than the existing fashion shows and what needs to be improved for the effectiveness of digital fashion shows. As a result, the virtual clothes have been recognized to be very similar to actual clothes and facilitate creative expressions that are hard to be presented in actual fashion shows. The adaptation of 3D virtual clothes to real fashion industry in the future can make new contents through the innovation of distribution and industry.
Storage capacity of pixelated paraxial diffractive elements

Diffractive optics finds attractive applications in the development of optical data storage systems. The performance of these systems is measured by their storage capacity specifying the amount of information that can be stored. In this paper information theory is applied to derive statements on the capacity of optical storage systems that make use of pixelated paraxial diffractive elements. It is motivated that the storage capacity of diffractive elements is directly correlated with the amount of information that can be correctly transmitted via a noisy communication channel consisting of the storage medium, free space, and a detector. Examinations on the storage capacity are restricted to noise effects due to the modulation characteristics of the storage medium. In this context redundant encoding schemes are shown to be useful to optimize the information capacity. Finally, in an experiment the storage capacity of a storage system with phase modulating diffractive elements is derived using the proposed methods.
COMPACT BRANCH-LINE COUPLER FOR HARMONIC SUPPRESSION

This paper presents the modifled design that can reject harmonic components in the branch-line coupler. After adding open stubs at the center of branch lines of the traditional design, their new network parameters can be found in order to maintain the conventional function at an operating frequency and suppress its harmonic terms chosen. Experimental results show the second and third harmonic suppressions to be i28.3 and i39.6dBs, while maintaining its traditional performance at the fundamental frequency.
Neck Stabilization Exercises Enhance Respiratory Function after Stroke: Respiratory Function Index Change Trajectory Analyzed Using a Hierarchical Linear Model

Background and Objectives: This study aimed to assess the effect of neck stabilization exercise on respiratory function in stroke patients through longitudinal observation and determine whether there is a difference in its effect based on the side of paralysis in the patients. It is difficult to observe the amount of change observed in individuals and groups as most intergroup comparison studies only use mean values. To address these shortcomings, this study adopted a hierarchical linear model (HLM) in our trajectory analysis. Materials and Methods: We conducted neck stabilization training three times a week for four weeks in a single group of 21 stroke patients. To evaluate respiratory function, their forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), forced expiration ratio (FEV1/FVC), and peak cough flow (PCF) were measured. Data analysis was performed using HLM 8.0. Results: A significant increase was found in the respiratory function after neck stabilization training (p < 0.05). While neck stabilization training overall was longitudinally effective, the growth rate of respiratory function in left-sided paralytic patients was less than the whole group value. Conversely, the growth rate of respiratory function in right-sided paralytic patients was greater than the whole group value. Conclusions: This study demonstrated that neck stabilization training is longitudinally effective in improving respiratory function in stroke patients. Additionally, the growth rate of respiratory function was greater in patients with right side paralysis than in patients with left side paralysis.
Neural Embeddings for Text Analysis: A Case Study in Neoliberal Discourse

This paper examines the notions of neoliberalism and the financialization and marketisation of public life by using computational tools such as sentence embeddings on a novel corpus of neoliberal articles. More specifically, we experimented with distributional semantics along with several Natural Language Processing (NLP) techniques and machine learning algorithms in order to extract conceptual dictionaries and “seed” words. Our findings show that sentence embeddings reveal repetitive patterns constructed around the given concepts and highlight the mechanical character of an ideology in its function of providing solutions, policies and constructing stereotypes. This work introduces a novel pipeline for computer-assisted research in discourse analysis and ideology.
Estimation of Leaf Area Index in vineyards by analysing projected shadows using UAV imagery

A few decades ago, farmers could precisely monitor their croplands just by walking over the fields, but this task becomes more difficult as farm size increases. Precision viticulture can help better understand the vineyard and measure some key structural parameters, such as the Leaf Area Index (LAI). Remote Sensing is a typical approach to monitoring vegetation which measures the spectral information directly emitted and reflected from vegetation. This study explores a new method for estimating LAI which measures the projected shadows of plants using UAV (unmanned aerial vehicle) imagery. A flight mission over a vineyard was scheduled in the afternoon (15:30 to 16:00 solar time), which is the optimal time for the projection of vine shadows on the ground. Real LAI was measured destructively by removing all the vegetation from the area. Then, the projected shadows in the image were detected using machine learning methods (k-means and random forest) and analysed at pixel level using a customised R code. A strong linear relationship (R² = 0.76, RMSE = 0.160 m² m-2 and MAE = 0.139 m² m-2) was found between the shaded area and the LAI per vine. This is a quick and simple method, which is non-destructive and gives accurate results; moreover, flights can be scheduled during other periods of the day than solar noon, such as in the morning or afternoon, thus enabling pilots to extend their working day. Therefore, it may be a viable option for determining LAI in vineyards trained on Vertical Shoot Positioned (VSP) systems.
Stabilising and optimising a primary closed-loop milling circuit feeding a flotation circuit using StarCS RNMPC

Abstract Most milling circuits can be well approximated using linear process models, but the mill itself tends to exhibit strong non-linear behavior. To overcome this, each section of the milling circuit is typically controlled using a linear controller and the non-linearities are handled by non-linear capable supervisory layer, such as fuzzy logic or expert rules. Mintek developed the StarCS RNMPC that can use both linear and non-linear models to enable the entire milling circuit to be handled by one controller. MPC is inherently optimising and can therefore provide stabilisation as well as optimisation of the milling circuit, while adhering to all process constraints. This paper shows a simulation of a milling circuit that is stabilised and optimised using a single StarCS RNMPC controller with linear and non-linear prediction models as well as other unique features, such as cascaded CV-to-CV prediction models.
First external validation of the FLIPI‐L score in a single‐center series of patients with follicular lymphoma

The FLIPI‐L has recently been proposed as a novel prognostic index in follicular lymphoma (FL), combining FLIPI and the presence of lymphopenia. In our single‐center validation in 381 FL patients, lymphopenia was less frequent than in the original publication and thus the distribution of risk categories was different. Although it was not able to properly predict time to first treatment, FLIPI‐L performed slightly better than FLIPI alone in the prediction of response, early relapse, progression‐free and overall survival, and histological transformation. This new tool or others encompassing parameters from the microenvironment might improve upon the prognostic ability of classical scores.
Grain boundary strengthening of carbon-doped TiZrN coatings by laser carburization

ABSTRACT The improved mechanical properties of carbon-doped TiZrN coatings were investigated in terms of the microstructure and bonding state. The carbon incorporation and structural change were confirmed as a shift to lower degree of the diffraction pattern and the decreased grain size from 24.64 to 22.19 nm. The clear grain boundaries (GBs) were observed in the carbon-doped coating, and its fast Fourier transform (FFT) exhibited a diffused ring pattern. Edge dislocations were also observed in the inverse FFT image, indicating the formation of an amorphous phase due to laser carburization. From the X-ray photoelectron spectroscopy depth profile analysis, the carbon concentration decreased to 37.26 at. % after carburization, which is non-stoichiometric behavior that suggests the formation of the amorphous carbon (a-C) rather than carbides. Both sp2- and sp3-hybridized bonds were detected in the C 1s spectrum of the carbon-doped coating, indicating that the diffused carbon atoms were trapped in the GBs as a-C. The change in the GB structure increased the compressive residual stress from 3.97 to 4.63 GPa. In addition, the hardness, elastic strain to failure (H/E), and plastic deformation resistance (H3/E2) of the carbon-doped TiZrN increased by 19.22%, 12.64%, and 49.59%, respectively, demonstrating the effect of GB strengthening.
Previsão top-down ou bottom-up? Impacto nos níveis de erro e de estoques de segurança

The operations literature remains inconclusive about the most adequate forecasting approach - top-down or bottom-up. This paper presents analytical results for mean values and variances of forecasting errors with exponential smoothing under these approaches. The share of the series in the total aggregate data is considered stochastic. Based on the generation of random numbers, two major impacts are confirmed on the variance of forecasting error, which were presented in previous papers, namely, portfolio and anchorage effects. The impacts are also evaluated in terms of forecasting bias and safety inventory levels.
Theoretical Approach to the Collaborative Environmental Activities: Household Waste Disposal towards Environmentally Friendly Daily Life

What brings us the proenvironmental behavior? What lies behind people's behavior in daily life? This paper is intended to analyze and discuss how the environment-oriented norm is developed and transmitted in daily life focusing on household waste disposal. Waste management companies in Finland have unique environmental policies which are intended to instill the environmentally friendly awareness into local residents by collaborative environmental activities based on environmental communication. For the purpose of obtaining the qualitative data, the participant observation was conducted in Finland. Following the results, this paper suggests the significance of the collaborative environmental activities based on environmental communication in order to transmit the environment-oriented norm.
XXIII. An essay towards the calculus of functions

The term function has long been introduced into analysis with great advantage, for the purpose of designating the result of every operation that can be performed on quantity. This extent of signification has rendered it of essential use, but the various applications of which it admits, and the questions to which it gives rise, do not appear to have met with sufficient attention. I propose in the following paper to present an outline of a new calculus, which naturally results from it. It comprehends questions of the greatest generality and difficulty, and will probably require the invention of new methods for its improvement.
Control of the Broken River

Abstract In this paper, a control system design is proposed for the Broken River in Victoria, Australia. The control scheme is decentralised, and consists of a number of local PI and P controllers. The controllers are designed using frequency response techniques based on simple models obtained using system identification methods. In a simulation example, the control system compared very favorably with current manual operation demonstrating a significant potential for substantial water savings.
Automatic Parking Based on a Bird's Eye View Vision System

This paper aims at realizing an automatic parking method through a bird's eye view vision system. With this method, vehicles can make robust and real-time detection and recognition of parking spaces. During parking process, the omnidirectional information of the environment can be obtained by using four on-board fisheye cameras around the vehicle, which are the main part of the bird's eye view vision system. In order to achieve this purpose, a polynomial fisheye distortion model is firstly used for camera calibration. An image mosaicking method based on the Levenberg-Marquardt algorithm is used to combine four individual images from fisheye cameras into one omnidirectional bird's eye view image. Secondly, features of the parking spaces are extracted with a Radon transform based method. Finally, double circular trajectory planning and a preview control strategy are utilized to realize autonomous parking. Through experimental analysis, we can see that the proposed method can get effective and robust real-time results in both parking space recognition and automatic parking.
Parameter Optimization of PID Controller Based on Quantum-behaved Particle Swarm Optimization Algorithm

The conventional parameter optimisation of PID controller is easy to produce surge and big overshoot, and therefore heuristics such as genetic algorithm (GA), particle swarm optimisation (PSO) are employed to enhance the capability of traditional techniques. But the major problem of these algorithms is that they may be trapped in the local optima of the objective and lead to poor performance. In this paper, a quantum-behaved particle swarm optimisation (QPSO) for the parameter optimisation of PID controller is proposed from sub-optimal perspective. This method is very advantageous for practical control systems. Three examples are given to illustrate the design procedure and exhibit the effectiveness of the proposed method via a comparison study with an existing Z-N, GA and PSO approaches Index Terms—QPSO, PID controller, parameter optimisation
An analytical grain-barrier height model and its characterization for intrinsic poly-Si thin-film transistor

An analytical model for the grain-barrier height of the intrinsic poly-Si thin-film transistors (TFTs) is developed, in which the grain-barrier height for the applied gate voltage smaller than the threshold voltage is obtained by solving the charge neutrality equation and the grain-barrier height for the applied gate voltage larger than the threshold voltage is obtained by using the quasi-two-dimensional (2-D) method. Good agreements between experimental and simulation results are obtained for a wide gate voltage range.