Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Privacy-Preserving Techniques for Encrypted Traffic Inspection over Network Middleboxes

Middleboxes in a computer network system inspect and analyse network traffic to detect malicious communications, monitor system performance and provide operational services. However, encrypted traffic hinders the ability of middleboxes to perform such services. A common practice in addressing this issue is by employing a"Man-in-the-Middle"(MitM) approach, wherein an encrypted traffic flow between two endpoints is interrupted, decrypted and analysed by the middleboxes. The MitM approach is straightforward and is used by many organisations, but there are both practical and privacy concerns. Due to the cost of the MitM appliances and the latency incurred in the encrypt-decrypt processes, enterprises continue to seek solutions that are less costly. There were discussion on the many efforts required to configure MitM. Besides, MitM violates end-to-end privacy guarantee, raising privacy concerns and issues on compliance especially with the rising awareness on user privacy. Furthermore, some of the MitM implementations were found to be flawed. Consequently, new practical and privacy-preserving techniques for inspection over encrypted traffic were proposed. We examine them to compare their advantages, limitations and challenges. We categorise them into four main categories by defining a framework that consist of system architectures, use cases, trust and threat models. These are searchable encryption, access control, machine learning and trusted hardware. We first discuss the man-in-the-middle approach as a baseline, then discuss in details each of them, and provide an in-depth comparisons of their advantages and limitations. By doing so we describe practical constraints, advantages and pitfalls towards adopting the techniques. We also give insights on the gaps between research work and industrial deployment, which leads us to the discussion on the challenges and research directions.
Temporal correlations robustly reveal regulatory coherence upon environmental perturbation

Transcriptional Regulatory Networks (TRNs) orchestrate the timing, magnitude, and rate of organismal response to many environmental perturbations. Regulatory interactions in TRNs are context-dependent, affording the opportunity to detect responsive links upon environmental perturbation. To measure the transition between regulatory status directly, one powerful approach is chromatin immuno-precipitation binding, ChIP-Seq. However, genome-wide ChIP-Seq is costly and currently inaccessible for many transcription factors (TFs) across multiple conditions in most organisms. Seeking to exploit the abundance of RNASequencing data now available, many past studies have relied upon population-level statistics from cross-sectional studies, generating pairwise gene co-expression, to capture transient regulatory activity. Here, we employ a minimal stochastic model of transcriptional regulation and demonstrate that population correlations from cross-sectional studies may fail to capture transient regulatory activities. To characterize network rewiring in response to environmental perturbations, we use the dynamic correlation between time-series gene expression profiles in Oryza sativa in a network prior. Overall, stronger regulatory interactions are observed following environmental perturbation, which we term regulatory coherence. Previously known regulators with changing regulatory activities are reliably identified with our method. Exploiting dynamic correlations has the potential to prioritize stress-responsive regulators, affording greater detection power as compared to traditional differential expression approaches.
Automated Pipeline for Infants Continuous EEG (APICE): a flexible pipeline for developmental studies

Infant electroencephalography (EEG) presents several challenges compared with adult data. Recordings are typically short. Motion artifacts heavily contaminate the data. The EEG neural signal and the artifacts change throughout development. Traditional data preprocessing pipelines have been developed mainly for event-related potentials analyses, and they required manual steps, or use fixed thresholds for rejecting epochs. However, larger datasets make the use of manual steps infeasible, and new analytical approaches may have different preprocessing requirements. Here we propose an Automated Pipeline for Infants Continuous EEG (APICE). APICE is fully automated, flexible, and modular. Artifacts are detected using multiple algorithms and adaptive thresholds, making it suitable to different age groups and testing procedures without redefining parameters. Artifacts detection and correction of transient artifacts is performed on continuous data, allowing for better data recovery and providing flexibility (i.e., the same preprocessing is usable for different analyses). Here we describe APICE and validate it using two infant datasets of different ages tested in different experimental paradigms. We also tested the combination of APICE with common data cleaning methods such as Independent Component Analysis and Denoising Source Separation. APICE uses EEGLAB and compatible custom functions. It is freely available at https://github.com/neurokidslab/eeg_preprocessing, together with example scripts.
Journalism in the Context of a Sanitary Crisis: Representations of the Job and Journalists’ Expectations

The economic difficulties of media companies, ethical-deontological lapses, technological progress and the globalisation of information flows have been seen as the main factors of the contemporary crisis in journalism. With repercussions on working conditions and the public image of journalists, these variables are, however, only the most visible face of threats to an activity that, according to Nelson Traquina (2002), has a symbiotic relationship with democracy. Beyond these economic, social and cultural circumstances are also the expectations of the professionals themselves. In an occupation so often described as passionate, the professional situation seems to be less and less rewarding, not only due to the decrease in job opportunities, with newsrooms increasingly empty, but also due to the lack of perspective on career progression. This is one of the results of the “Study on the Effects of the State of Emergency on Journalism in the Context of the Covid-19 Pandemic”, conducted between May and June 2020. With a particular focus on reading journalists’ expectations, in this article we analyse the symbolic representations of a job that founded its social legitimacy on an idea of public service. Based on studies about the profession and its representations, we tried to find answers to understand why the acceptance of precariousness and abandonment of the profession can still be understood as places of resistance. © 2021. All Rights Reserved.
Tangential flow filtration facilitated fractionation and PEGylation of low and high‐molecular weight polymerized hemoglobins and their biophysical properties

Various types of hemoglobin (Hb)‐based oxygen carriers (HBOCs) have been developed as red blood cell substitutes for treating blood loss when blood is not available. Among those HBOCs, glutaraldehyde polymerized Hbs have attracted significant attention due to their facile synthetic route, and ability to expand the blood volume and deliver oxygen. Hemopure®, Oxyglobin®, and PolyHeme® are the most well‐known commercially developed glutaraldehyde polymerized Hbs. Unfortunately, only Oxyglobin® was approved by the FDA for veterinary use in the United States, while Hemopure® and PolyHeme® failed phase III clinical trials due to their ability to extravasate from the blood volume into the tissue space which facilitated nitric oxide scavenging and tissue deposition of iron, which elicited vasoconstriction, hypertension and oxidative tissue injury. Fortunately, conjugation of poly (ethylene glycol) (PEG) on the surface of Hb is capable of reducing the vasoactivity of Hb by creating a hydration layer surrounding the Hb molecule, which increases its hydrodynamic diameter and reduces tissue extravasation. Several commercial PEGylated Hbs (MP4®, Sanguinate®, Euro‐PEG‐Hb) have been developed for clinical use with a longer circulatory half‐life and improved safety compared to Hb. However, all of these commercial products exhibited relatively high oxygen affinity compared to Hb, which limited their clinical use. To dually address the limitations of prior generations of polymerized and PEGylated Hbs, this current study describes the PEGylation of polymerized bovine Hb (PEG‐PolybHb) in both the tense (T) and relaxed (R) quaternary state via thiol‐maleimide chemistry to produce an HBOC with low or high oxygen affinity. The biophysical properties of PEG‐PolybHb were measured and compared with those of commercial polymerized and PEGylated HBOCs. T‐state PEG‐PolybHb possessed higher hydrodynamic volume and P50 than previous generations of commercial PEGylated Hbs. Both T‐ and R‐state PEG‐PolybHb exhibited significantly lower haptoglobin binding rates than the precursor PolybHb, indicating potentially reduced clearance by CD163 + monocytes and macrophages. Thus, T‐state PEG‐PolybHb is expected to function as a promising HBOC due to its low oxygen affinity and enhanced stealth properties afforded by the PEG hydration shell.
Dual Crisscross Attention Module for Road Extraction from Remote Sensing Images

Traditional pixel-based semantic segmentation methods for road extraction take each pixel as the recognition unit. Therefore, they are constrained by the restricted receptive field, in which pixels do not receive global road information. These phenomena greatly affect the accuracy of road extraction. To improve the limited receptive field, a non-local neural network is generated to let each pixel receive global information. However, its spatial complexity is enormous, and this method will lead to considerable information redundancy in road extraction. To optimize the spatial complexity, the Crisscross Network (CCNet), with a crisscross shaped attention area, is applied. The key aspect of CCNet is the Crisscross Attention (CCA) module. Compared with non-local neural networks, CCNet can let each pixel only perceive the correlation information from horizontal and vertical directions. However, when using CCNet in road extraction of remote sensing (RS) images, the directionality of its attention area is insufficient, which is restricted to the horizontal and vertical direction. Due to the recurrent mechanism, the similarity of some pixel pairs in oblique directions cannot be calculated correctly and will be intensely dilated. To address the above problems, we propose a special attention module called the Dual Crisscross Attention (DCCA) module for road extraction, which consists of the CCA module, Rotated Crisscross Attention (RCCA) module and Self-adaptive Attention Fusion (SAF) module. The DCCA module is embedded into the Dual Crisscross Network (DCNet). In the CCA module and RCCA module, the similarities of pixel pairs are represented by an energy map. In order to remove the influence from the heterogeneous part, a heterogeneous filter function (HFF) is used to filter the energy map. Then the SAF module can distribute the weights of the CCA module and RCCA module according to the actual road shape. The DCCA module output is the fusion of the CCA module and RCCA module with the help of the SAF module, which can let pixels perceive local information and eight-direction non-local information. The geometric information of roads improves the accuracy of road extraction. The experimental results show that DCNet with the DCCA module improves the road IOU by 4.66% compared to CCNet with a single CCA module and 3.47% compared to CCNet with a single RCCA module.
Experimental Investigation Into Gravity Drained Journal Bearings

Turbomachines with large & heavy rotors have journal bearings that utilize thin hydrodynamic oil film to maintain a gap between the shaft & bearings. They are fed with a continuous supply of lube oil at a high rate to maintain the oil film and remove the heat generated. The shaft imparts high rotational velocities to the oil as it passes through the bearing. Due to high kinetic energy of oil leaving the bearing, gravity drained bearing housings generally have a big sump near the bottom dead center to collect and reduce the kinetic energy of the oil. This facilitates smooth drain of oil back to the oil tank. The use of gravity to facilitate the draining results in a simple and cost-effective bearing system. The size of sump is determined by the oil flow rate in the bearing housing which itself is a function of rotor load, speed & temperature. In absence of this oil sump (in applications where there is little or no room for a large bearing housing) the swirling oil in the bearing housing doesn’t get enough time to slow down. The rapidly swirling oil therefore fails to drain into the drainpipe(s), and eventually floods the housing and leaks out through the shaft seals. The failure to drain can be attributed to multiple reasons like air pressure fluctuation, oil vortex formation, oil frothing, etc. This paper focusses on the design of a journal bearing for gas turbines without an oil sump due to design space restrictions. The flow fields in the bearing are chaotic and difficult to analytically predict without experimental validation. Therefore, a bearing rig was constructed, and multiple tests were conducted to understand the flow characteristics inside the bearing housing. Based on the understanding of the flow characteristics, design modifications were made and validated to enable the design of a sumpless gravity drained bearing housing. This paper discusses the methodology and findings from these rig tests which led to the design solutions that solved the issue of draining the high energy oil back to the oil tank without the need of having a traditional oil sump.
Adaptive Morphology for Multi-Modal Locomotion

There is a growing interest in using robots in dangerous environments, such as for exploration, search-and-rescue or monitoring applications, in order to reduce the risks for workers or rescuers and to improve their efficiency. Typically, flying robots offer the possibility to quickly explore large areas while ground robots can thoroughly search specific regions of interest. While existing robotic solutions are very promising, they are often limited to specific use cases or environments. This makes them impractical for most missions involving complex or unpredictable scenarios, such as search-and-rescue applications. This limitation comes from the fact that existing robots usually exploit only a single locomotion strategy, which limits their flexibility and adaptability to different environments. In this thesis, a multi-modal locomotion strategy is investigated as a way to increase the versatility of mobile robots. We explore integrated design approaches, where the same actuators and structure are used for different modes of locomotion, which allows a minimization of the weight and complexity of the robot. This strategy is challenging because a single locomotor system must accommodate the potentially conflicting dynamics of multiple modes of locomotion. Herein, we suggest taking inspiration from nature, in particular the common vampire bat Desmodus rotundus. The goal being to make multiple modes of locomotion dynamically compatible (i.e. have compatible speeds and torques requirements), by optimizing the morphology of the locomotor system and even by adapting the morphology of the robot to a specific mode of locomotion. It is demonstrated in this thesis that the integrated design approach can be effectively implemented on a multi-modal aerial and terrestrial robot, and that two modes of locomotion can be made dynamically compatible by optimizing the morphology. Furthermore, an adaptive morphology is used to increase the efficiency of the different modes of locomotion. A locomotor system used both for walking on the ground and controlling flight, has been successfully implemented on a multi-modal robot, which further has deployable wings to increase its performances on the ground and in the air. By successfully exploiting the concepts of integrated design and adaptive morphology, this robot is capable of hovering, forward flight and ground locomotion. This robot demonstrates a very high versatility compared to state of the art of mobile robots, while having a low complexity.
Building Indoor Temperature Control Using Control Horizon Method in Cooling Systems

Abstract In this paper, the TOU tariff's based building indoor temperature control algorithm in cooling systems is proposed using control horizon method. A control horizon switching method and linear programming algorithm is used for optimal control, and both TOU and peak tariffs are included to calculate the energy costs. Simulation results show that the reductions of energy cost and peak power can be obtained using proposed algorithms. Key Words : Energy Saving, Optimal Control, Linear Programming, Control Horizon, Building Indoor Temperature *Corresponding Author : Ho-Chan Kim Tel: +82-64-754-3676 email: hckim@jejunu.ac. kr 접수일 12년 09월 13일 수정일 12년 10월 05일 게재확정일 12년 10월 11일 1. 서론 지구 대기의 기후변화로 인한 기온상승으로 냉방기의 보급 확대가 매년 증가함에 따라 에너지소비가 많은 여름철 국가 전체의 전력수급 안정을 확보하고, 예상하지 못한 전력공급의 차질을 미연에 방지하기 위해 대형 건물 등의 실내 냉방온도 제한조치 등이 도입되고 있다 . 건물에서의 에너지사용량은 전 세계적으로 총에너지사용량의 약 40%를 차지하고 있으며, 우리나라의 경우에도 총에너지사용량의 약 25%를 차지하고 있다[1]. 건물에서 사용되는 에너지를 절감하기 위해서는 건물 신축 시 고효율 자재 사용을 통한 단열과 냉난방을 고려한 사전적 에너지 절감 방안이 우선되어야 한다. 그러나 기존 건물의 경우 벽두께, 창문구조 등의 사전적용이 어렵기 때문에 에너지를 소비하는 조명장치, 시스템에어컨 등의 사용 효율을 높여 전력소비를 절감하는 방법을 사용하게 된다. 우리가 일상에서 생활하는 건물에서 에너지는 조명, 전열, 동력, 냉방분야로 분류할 수 있다. 그 중 냉난방 분야는 건물내부의 환경 및 재실자의 건강과 업무능률 향상을 위한 실내 환경의 쾌적성을 고려한 에너지 소비를 하게 된다. 건물의 냉난방으로 발생되는 에너지비용과 전력피크를 절감하기 위해서는 실제 에너지 사용의 흐름을 파악하는 것이 무엇보다 중요하며 실제 에너지 사용의 흐름을 파악하는 기법으로 컴퓨터를 이용한 시뮬레이션 모델링이 주로 이용되고 있다[2]. 건물내부의 실제 에너지흐름은 외부의 기후변화에 따라 전도 , 대류복사 등의 모든 열전달 현상을 포함한 복합적이며 상호영향을 미치는 동적시스템으로 구성되어 있기 때문에 시뮬레이션을 실제상황과 동일하게 모델링하는 데는 많은 어려움과 한계가 따른다. 따라서 건물의 시뮬레이션 모델링에는 수많은 가정요소와 단순한 기법이 도입되고 있으며 도입정도에 따라 해석능력과 범위가 결정하게 되며,
Study of the Mechanism of Groove Wear of the Diamond Tool in Nanoscale Ductile Mode Cutting of Monocrystalline Silicon

In nanoscale ductile mode cutting of the monocrystalline silicon wafer, micro-, or nano-grooves on the diamond cutting tool flank face are often observed, which is beyond the understanding based on conventional cutting processes because the silicon workpiece material is monocrystalline and the hardness is lower than that of the diamond cutting tool at room temperature. In this study, the mechanism of the groove wear in nanoscale ductile mode cutting of monocrystalline silicon by diamond is investigated by molecular dynamics simulation of the cutting process. The results show that the temperature rise in the chip formation zone could soften the material at the flank face of the diamond cutting tool. Also, the high hydrostatic pressure in the chip formation region could result in the workpiece material phase transformation from monocrystalline to amorphous, in which the material interatomic bond length varies, yielding atom groups of much shorter bond lengths. Such atom groups could be many times harder than that of the original monocrystalline silicon and could act as "dynamic hard particles " in the material. Having the dynamic hard particles ploughing on the softened flank face of the diamond tool, the micro-/nanogrooves could be formed, yielding the micro-/nanogroove wear as observed.
Milestones in neuropathology: Bridging morphology with molecules

Neuropathology is a highly specialized branch of pathology dealing with diseases of the nervous system, enabling the study of structural abnormalities on biopsied and autopsied material through macroscopic, microscopic and occasionally, ultrastructural examination. When compared to other branches of pathology, neuropathology has had complex origins because of its pivotal links with basic and clinical neuroscience. The beginning of neuropathology can be traced back to the year 1906, with the legendary studies on the nervous system by two great Nobel Laureates, Cajal[1,2] and Camillo Golgi. Other great contributions to neuropathology came from Rudolf Virchow and Pio del Rio‐Hortega, who threw light on understanding the terms “Neuroglia” and “myelin. ”[3,4] Subsequently, Paul Ehrlich, another Nobel laureate established the concept of the blood–brain barrier. [5] These have been some of the discoveries that built the foundation for neuropathology.
Storing COVID-19 Vaccination Records on a Blockchain

As the world grows more globalised the threat of pandemics increases. Widespread international travel allows diseases to rapidly spread worldwide. The COVID-19 pandemic has highlighted how unprepared we are to combat this threat. One approach which shows promise at preventing the spread of diseases is the employment of vaccinations to produce immunity. However, one problem with immunisation is that it can be difficult to verify whether someone has been vaccinated. This is exacerbated when travelling across different jurisdictions. An internationally recognised vaccination passport could solve this issue by allowing users to present their vaccination records when required. Using a blockchain to implement this passport would have several key advantages over the alternatives in terms of transparency, decentralisation and immutability. This dissertation implements and assesses the viability of a previously proposed blockchain based vaccination passport. The system is permissioned so that only authorised entities can write to it. However, it is publicly readable so that users can present their vaccination records to whomever they wish. The blockchain makes use of an iris-based identification system. The iris scans are hashed before being stored on the blockchain so that they cannot be linked back to the user. A locality sensitive hashing algorithm is employed to ensure that different scans of the same iris produce similar hashes. A unique identifier is created for each user by combining their stored hashed iris scan with some of their personal information. This identifier is stored alongside their records. When a user wants to retrieve their records, they must first locate their stored hashed iris scan and then use it to recreate their identifier. A prototype of the system is built using an Ethereum blockchain. An open-source iris recognition system is employed and adapted to the application. Improvements have been made to its speed and accuracy. The prototype has been tested using three different iris image datasets. It is found to achieve very promising results in terms of its speed and memory usage. Additionally, high matching accuracy is reported on all the datasets.