Miracle-dz/UniFAR-FTUs huggingface dataset:
Falkor: Federated Learning Secure Aggregation Powered by AESCTR GPU Implementation

We propose a novel protocol, Falkor, for secure aggregation for Federated Learning in the multi-server scenario based on masking of local models via a stream cipher based on AES in counter mode and accelerated by GPUs running on the aggregating servers. The protocol is resilient to client dropout and has reduced clients/servers communication cost by a factor equal to the number of aggregating servers (compared to the naïve baseline method). It scales simultaneously in the two major complexity aspects: 1) large number of clients; 2) highly complex machine learning models such as CNNs, RNNs, Transformers, etc. The AES-CTR-based masking function in our aggregation protocol is built on the concept of counterbased cryptographically-secure pseudorandom number generators (csPRNGs) as described in [32] and subsequently used by Facebook for their torchcsprng csPRNG. We improve upon torchcsprng by careful use of shared memory on the GPU device, a recent idea of Cihangir Tezcan [38] and obtain 100x speedup in the masking function compared to a single CPU core. Finally, we demonstrate scalability of our protocol in two realworld Federated Learning scenarios: 1) efficient training of large logistic regression models with 50 features and 50M data points distributed across 1000 clients that can dropout and securely aggregated via three servers (running secure multi-party computation (SMPC)); 2) training a recurrent neural network (RNN) model for sentiment analysis of Twitter feeds coming from a large number of Twitter users (more than 250,000 users). In case 1), our secure aggregation algorithm runs in less than a minute compared to a pure MPC computation (on 3 parties) that takes 27 hours and uses 400GB RAM machines as well as 1 gigabit-per-second network. In case 2), the total training is around 10 minutes using our GPU powered secure aggregation versus 10 hours using a single CPU core.
Determination of Critical Micelle Concentration of Sodium Dodecyl Sulfate in Distilled Water at 298.15K by Surface Tension Measurements

Surfactants are chemicals that adsorb to the interface between a solution and another phase (gases or solids) and self-assemble molecular clusters known as micelles in a solution (water or oil phase). Measurements of the surface tension of sodium dodecyl sulfate (SDS) in distilled water at 298.15K are reported. The increase of concentration of sodium dodecyl sulfate (SDS) in distilled water then decreased in surface tension at 298.15K. Critical micelle concentration (CMC) decreased with a decrease in surface tension. The graphs of surface tension versus concentration were made to determine the CMC of the solution.
Capturing the Aftermath of the Dobbs v. Jackson Women's Health Organization Decision in Google Search Results across the U.S

How do Google Search results change following an impactful real-world event, such as the U.S. Supreme Court decision on June 24, 2022 to overturn Roe v. Wade? And what do they tell us about the nature of event-driven content, generated by various participants in the online information environment? In this paper, we present a dataset of more than 1.74 million Google Search results pages collected between June 24 and July 17, 2022, intended to capture what Google Search surfaced in response to queries about this event of national importance. These search pages were collected for 65 locations in 13 U.S. states, a mix of red, blue, and purple states, with respect to their voting patterns. We describe the process of building a set of circa 1,700 phrases used for searching Google, how we gathered the search results for each location, and how these results were parsed to extract information about the most frequently encountered web domains. We believe that this dataset, which comprises raw data (search results as HTML files) and processed data (extracted links organized as CSV files) can be used to answer research questions that are of interest to computational social scientists as well as communication and media studies scholars.
Solving Uncertain Online Shopping Problem With Discounts Using Robust Counterpart Methodology

Online Shopping is a phenomenon that is growing rapidly at this time and consumers are an important element in the buying and selling competition in the market and consumers who make a difffference in determining the profifits of the sellers. This research discusses the problem of online shopping using the Robust Optimization method. Robust Optimization Method is a process to get optimal results with an uncertainty. Based on the demand model to optimize the buying price, an Integer Linear Programming model with discount functions is built which will be converted into Robust Optimization. In this study also used a tool that is the Maple application in the numerical calculation process.
Effects of Combined Training Programs in Individuals with Fibromyalgia: A Systematic Review

Fibromyalgia is a rheumatic disease characterised by chronic widespread muscular pain and its treatment is carried out by pharmacological interventions. Physical exercise and a healthy lifestyle act as an important mechanism in reducing the symptoms of the disease. The aims of this study were to analyse and systematise the characteristics of combined training programs (i.e., type and duration of interventions, weekly frequency, duration and structure of training sessions and prescribed intensities) and to analyse their effects on people diagnosed with fibromyalgia. A systematic literature search was performed using the PRISMA method and then randomised controlled trial articles that met the eligibility criteria were selected. The Physiotherapy Evidence Database scale was used to assess the quality and risk of the studies. A total of 230 articles were selected, and in the end, 13 articles met the defined criteria. The results showed different exercise interventions such as: combined training, high-intensity interval training, Tai Chi, aerobic exercise, body balance and strength training. In general, the different interventions were beneficial for decreasing physical symptoms and improving physical fitness and functional capacity. In conclusion, a minimum duration of 14 weeks is recommended for better benefits. Moreover, combined training programs were the most effective for this population, in order to reduce the symptoms of the disease with a duration between 60 and 90 min, three times a week with a light to moderate intensity.
I3D Light - A Simple Motion Information Stream for I3D

Vision-based Human Activity Recognition (HAR) aims to recognize human activities based on the analysis of video data, and has extensive applications in modern industry and human life. Inflated 3D (I3D) is a deep learning architecture that is commonly used for action recognition by using two-stream video data: RGB stream and optical flow stream. I3D achieved great success on a variety of action recognition benchmarks. However, the use of optical flow incurs high computational cost, making the approach unsuitable for real-time applications. We propose an alternative simple motion information extractor to replace the optical flow branch and reduce the computational cost. It is a modified I3D that uses 128 frames of 112x112 images as input. The low spatial resolution and long temporal range of the proposed I3D RGB stream can reduce the spatial information and enhance the motion information. Experiments show that this simple motion stream can increase the accuracy of the original I3D spatial stream by 4.09% on the Kinetics 400 dataset.
BLDC motor torque ripple factor lowering and FOPID based motion control using DGOA algorithm

The Brushless Direct Current (BLDC) motor has many benefits due to characteristics like its small size and precise speed regulation. Uncertainty problems are presented by the system’s slow Proportional-Integral (PI) controller response time as well as some BLDC motor operating circumstances. The proposed Fractional-Order Proportional-Integral-Derivative (FOPID) controller and Difference of Orientation Offset Gaussian (DOOG) Grasshopper Optimization Algorithm (GOA) (DGOA) function are used to mitigate torque ripples in BLDC motors and overcome these drawbacks. An adaptive parameter has been introduced to enhance the performance of the conventional GOA method, and the performance of the suggested DGOA is compared to the benchmark functions. The simulation of the driver with the suggested DGOA-FOPID results in an improvement in Torque Ripple Reduction and speed control is obtained that better torque ripple reduction and speed regulation have been achieved.
Towards operational resilience for AI-based cyber in multi-domain operations

There is a growing orientation of cyber systems, technologies, and processes away from notions of cybersecurity and towards notions of cyber resilience. In multi-domain operation settings, such as joint all-domain command and control (JADC2), the scale and evolvability of networks makes resilience an especially useful concept for cyber operations, as the attack surface is simply too complex to secure. Generic design patterns for cyber resilience in cyber-physical systems have been difficult to identify. This is due in part to the generality of cyber-physical systems (CPS). Artificial intelligence and machine learning (AI/ML), however, are more specific than CPS, typically serving as a component or subsystem within a CPS, and thereby offer a more promising opportunity to define general resilience concepts for AI/ML-based cyber systems. In this paper, we introduce resilience concepts for AI/ML-based cyber systems. We consider the measurability and testability of resilience, as well as suggest possible requirements for resilience. To illustrate and contextualize the discussion of resilience, we use a notional example of AI/ML-based network defense analysis in a JADC2 setting. With the aid of the JADC2 example, we discuss the difficulties in engineering AI/ML for cyber resilience. Although AI/ML often have learning processes embedded, that does not make them resilient, as the learning processes are dependent on other systems, technologies, and processes. This paper concludes that to extend cyber resilience to an AI/ML-based cyber systems, one can use generic design patterns to identify resilience mechanisms and to associate them with testable, measurable requirements.
2023 Canadian Colposcopy Guideline: A Risk-Based Approach to Management and Surveillance of Cervical Dysplasia

This guideline provides evidence-based guidance on the risk-based management of cervical dysplasia in the colposcopy setting in the context of primary HPV-based screening and HPV testing in colposcopy. Colposcopy management of special populations is also discussed. The guideline was developed by a working group in collaboration with the Gynecologic Oncology Society of Canada (GOC), Society of Colposcopists of Canada (SCC) and the Canadian Partnership Against Cancer (CPAC). The literature informing these guidelines was obtained through a systematic review of the relevant literature via a multi-step search process led by information specialists. The literature was reviewed up to June 2021 with manual searches of relevant national guidelines and more recent publications. Quality of the evidence and strength of recommendations was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. The intended users of this guideline include gynecologists, colposcopists, screening programs and healthcare facilities. Implementation of the recommendations is intended to promote equitable and standardized care for all people undergoing colposcopy in Canada. The risk-based approach aims to improve personalized care and reduce over-/under-treatment in colposcopy.
CAMBRIDGE WORKING PAPERS IN ECONOMICS JANEWAY INSTITUTE WORKING PAPERS A Capability Approach to Merger Review

Merger analysis typically focuses on possible strategic price effects in markets where there is existing competition between the merging firms. We refer to this as the product based approach. This paper proposes a complementary approach based on an assessment of the merging firms’ capabilities that can provide insights on potential merger effects, including in circumstances where the product based approach offers little practical guidance to antitrust authorities. Our approach is rooted in the resource-based view of business strategy that starts from the premise that it is a firm’s capabilities (sometimes called core competencies), which drive its competitive advantage across markets. We argue that mergers in which firms’ capabilities are less overlapping are more pro-competitive on several dimensions: immediate competition in overlapping markets, immediate competition in other markets, long-run competition and innovation.
City, University of London Institutional Repository

The creation and validation of product line software architectures are inherently more complex than those of software architectures for single systems. This paper compares a process for creating and evaluating a traditional, one-of-a-kind software architecture with one for a reference software architecture. The comparison is done in the context of PuLSE-DSSA, a customizable process that integrates both product line architecture creation and evaluation
The Internet of Things: a security point of view

Purpose – The purpose of this paper is to provide an in-depth overview of the security requirements and challenges for Internet of Things (IoT) and discuss security solutions for various enabling technologies and implications to various applications. Design/methodology/approach – Security requirements and solutions are analysed based on a four-layer framework of IoT on sensing layer, network layer, service layer, and application layer. The cross-layer threats are analysed followed by the security discussion for the enabling technologies including identification and tracking technologies, WSN and RFID, communication, networks, and service management. Findings – IoT calls for new security infrastructure based on the new technical standards. As a consequence, new security design for IoT shall pay attention to these new standards. Security at both the physical devices and service-applications is critical to the operation of IoT, which is indispensable for the success of IoT. Open problems remain in a number o.
Development of Natural Active Agent-Containing Porous Hydrogel Sheets with High Water Content for Wound Dressings

This work was concerned with the fabrication of a porous hydrogel system suitable for medium to heavy-exudating wounds where traditional hydrogels cannot be used. The hydrogels were based on 2-acrylamido-2-methyl-1-propane sulfonic acid (AMPs). In order to produce the porous structure, additional components were added (acid, blowing agent, foam stabilizer). Manuka honey (MH) was also incorporated at concentrations of 1 and 10% w/w. The hydrogel samples were characterized for morphology via scanning electron microscopy, mechanical rheology, swelling using a gravimetric method, surface absorption, and cell cytotoxicity. The results confirmed the formation of porous hydrogels (PH) with pore sizes ranging from ~50–110 µm. The swelling performance showed that the non-porous hydrogel (NPH) swelled to ~2000%, while PH weight increased ~5000%. Additionally, the use of a surface absorption technique showed that the PH absorbed 10 μL in <3000 ms, and NPH absorbed <1 μL over the same time. Incorporating MH the enhanced gel appearance and mechanical properties, including smaller pores and linear swelling. In summary, the PH produced in this study had excellent swelling performance with rapid absorption of surface liquid. Therefore, these materials have the potential to expand the applicability of hydrogels to a range of wound types, as they can both donate and absorb fluid.
Northumbria Research Link

 Abstract — Although visual surveillance has emerged as an effective technolody for public security, privacy has become an issue of great concern in the transmission and distribution of surveillance videos. For example, personal facial images should not be browsed without permission. To cope with this issue, face image scrambling has emerged as a simple solution for privacy-related applications. Consequently, online facial biometric verification needs to be carried out in the scrambled domain thus bringing a new challenge to face classification. In this paper, we investigate face verification issues in the scrambled domain and propose a novel scheme to handle this challenge. In our proposed method, to make feature extraction from scrambled face images robust, a biased random subspace sampling scheme is applied to construct fuzzy decision trees from randomly selected features, and fuzzy forest decision using fuzzy memberships is then obtained from combining all fuzzy tree decisions. In our experiment, we first estimated the optimal parameters for the construction of the random forest, and then applied the optimized model to the benchmark tests using three publically available face datasets. The experimental results validated that our proposed scheme can robustly cope with the challenging tests in the scrambled domain, and achieved an improved accuracy over all tests, making our method a promising candidate for the emerging privacy-related facial biometric applications.
Northumbria Research Link

Due to the recent advancement of computer graphics hardware and software algorithms, deformable characters have become more and more popular in real-time applications such as computer games. While there are mature techniques to generate primary deformation from skeletal movement, simulating realistic and stable secondary deformation such as jiggling of fats remains challenging. On one hand, traditional volumetric approaches such as the ﬁnite element method require higher computational cost and are infeasible for limited hardware such as game consoles. On the other hand, while shape matching based simulations can produce plausible deformation in real-time, they suffer from a stiffness problem in which particles either show unrealistic deformation due to high gains, or cannot catch up with the body movement. In this paper, we propose a uniﬁed multi-layer lattice model to simulate the primary and secondary deformation of skeleton-driven characters. The core idea is to voxelize the input character mesh into multiple anatomical layers including the bone, muscle, fat and skin. Primary deformation is applied on the bone voxels with lattice-based skinning. The movement of these voxels is propagated to other voxel layers using lattice shape matching simulation, creating a natural secondary deformation. Our multi-layer lattice framework can produce simulation quality comparable to those from other volumetric approaches with a signiﬁcantly smaller computational cost. It is best to be applied in real-time applications such as console games or interactive animation creation.
ESAT-6 a Major Virulence Factor of Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb), the causative agent of human tuberculosis (TB), is one of the most successfully adapted human pathogens. Human-to-human transmission occurs at high rates through aerosols containing bacteria, but the pathogen evolved prior to the establishment of crowded populations. Mtb has developed a particular strategy to ensure persistence in the host until an opportunity for transmission arises. It has refined its lifestyle to obviate the need for virulence factors such as capsules, flagella, pili, or toxins to circumvent mucosal barriers. Instead, the pathogen uses host macrophages, where it establishes intracellular niches for its migration into the lung parenchyma and other tissues and for the induction of long-lived latency in granulomas. Finally, at the end of the infection cycle, Mtb induces necrotic cell death in macrophages to escape to the extracellular milieu and instructs a strong inflammatory response that is required for the progression from latency to disease and transmission. Common to all these events is ESAT-6, one of the major virulence factors secreted by the pathogen. This narrative review highlights the recent advances in understanding the role of ESAT-6 in hijacking macrophage function to establish successful infection and transmission and its use as a target for the development of diagnostic tools and vaccines.
The head theory and the Bloomfieldian Puzzle

As a response to Zhou Guoguang's (2005) arguments against Si Fuzhen (2004), this paper mainly discusses some issues related to the head theory and the Bloomfieldian Puzzle, attempting to clarify some confusions found in the literature. As a way to crack the Bloomfieldian Puzzle, this paper presents a novel analysis of the traditional concepts of endocentric vs. exocentric structure and argues that almost all phrases are endocentric in view of the head theory. On the other hand, there should be an endocentric force in all phrases so that the structures can be converged. It is claimed that several grammatical categories probably share some grammatical properties, and the phenomena can be accounted for by means of binary distinctive features. Thus the binary distinctive feature approach is applied beyond the traditional domain of research. It is pointed out, in addition, that functional words always serve as grammatical heads.
2-µm CO overtone absorption in young stellar objects

12 CO overtone absorption bands have been detected in five of 10 low-luminosity YSOs studied in the Ophiuchus cloud core. The majority of those showing absorption have class II spectral energy distributions. The majority of the class I objects show no spectral features at all. If the bands are assumed to be photospheric in origin, then the results can be understood as a decrease in veiling by an IR continuum excess as the sources evolve from class I to class II
The Design of Guaranteed Cost Reliable Controller for T-S Fuzzy Time-Delay Systems with Dynamic Output Feedback

Guaranteed cost reliable controller for T-S uncertain time-delay systems with actuator failure is studied in this paper. For a class of time-delay systems with norm bounded uncertainties, the sufficient existence condition of guaranteed cost reliable controller is deduced with the theory of Lyapunov and linear matrix inequality. Meanwhile, singular value decomposition is used to construct the design method of the controller. Finally, a numerical example is given to show the steps and method of the theories proposed in the paper, also show the correctness of the theories.
Coherence management in lithography printing systems

In proximity lithography, interference and diffraction effects arise when printing small features because of the proximity gap. Different techniques are used in order to control and take advantage of these effects. In this paper, the focus is set on the MO Exposure Optics developed to shape the angular spectrum of the exposure light. The MO Exposure Optics contains several elements including microlens arrays that have certain symmetry and sampling. The MO Exposure Optics allows to set the angle of illumination and can be used to define spatial coherence. We study here in detail the influence of different illumination settings on optical proximity correction (OPC) structures. We apply this concept for the first time to a LED illumination. The propagation of light after an optical proximity correction structure is measured by recording aerial images over a distance of up to 60 μm behind the mask with a high resolution microscope setup.1 As an example structure, we investigate here an optical proximity correction structure that is intended to make the edge of a line sharper. Using illumination filter plates that limit the angle of illumination and increase the coherence lead to pronounced interference effects in aerial images as expected. But special settings of the illumination allow to achieve comparable results with much larger illumination angles and higher throughput. We will show examples and analyze the results