Miracle-dz/UniFAR-FTUs huggingface dataset:
Fragment and Forge: Breaking Wi-Fi Through Frame Aggregation and Fragmentation

In this paper, we present three design flaws in the 802.11 standard that underpins Wi-Fi. One design flaw is in the frame aggregation functionality, and another two are in the frame fragmentation functionality. These design flaws enable an adversary to forge encrypted frames in various ways, which in turn enables exfiltration of sensitive data. We also discovered common implementation flaws related to aggregation and fragmentation, which further worsen the impact of our attacks. Our results affect all protected Wi-Fi networks, ranging from WEP all the way to WPA3, meaning the discovered flaws have been part of Wi-Fi since its release in 1997. In our experiments, all devices were vulnerable to one or more of our attacks, confirming that all Wi-Fi devices are likely affected. Finally, we present a tool to test whether devices are affected by any of the vulnerabilities, and we discuss countermeasures to prevent our attacks.
An Educational Guide through the FMP Notebooks for Teaching and Learning Fundamentals of Music Processing

This paper provides a guide through the FMP notebooks, a comprehensive collection of educational material for teaching and learning fundamentals of music processing (FMP) with a particular focus on the audio domain. Organized in nine parts that consist of more than 100 individual notebooks, this collection discusses well-established topics in music information retrieval (MIR) such as beat tracking, chord recognition, music synchronization, audio fingerprinting, music segmentation, and source separation, to name a few. These MIR tasks provide motivating and tangible examples that students can hold onto when studying technical aspects in signal processing, information retrieval, or pattern analysis. The FMP notebooks comprise detailed textbook-like explanations of central techniques and algorithms combined with Python code examples that illustrate how to implement the methods. All components, including the introductions of MIR scenarios, illustrations, sound examples, technical concepts, mathematical details, and code examples, are integrated into a unified framework based on Jupyter notebooks. Providing a platform with many baseline implementations, the FMP notebooks are suited for conducting experiments and generating educational material for lectures, thus addressing students, teachers, and researchers. While giving a guide through the notebooks, this paper’s objective is to yield concrete examples on how to use the FMP notebooks to create an enriching, interactive, and interdisciplinary supplement for studies in science, technology, engineering, and mathematics. The FMP notebooks (including HTML exports) are publicly accessible under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Impact of Lateral Flow on Surface Water and Energy Budgets Over the Southern Great Plains—A Modeling Study

As the horizontal grid spacing decreases, treatment of hydrologic processes in land surface models (LSMs), such as the lateral flow of surface and subsurface flow, need to be explicitly represented. Unlike previous studies that mainly focused on the mountainous regions, in this study, the offline Weather Research and Forecasting (WRF)‐Hydro model is employed to study the impact of lateral flow on soil moisture and energy fluxes over the relatively flat southern Great Plains (SGP). The vast amount of measurements over the SGP provide a unique opportunity to assess the model behavior. In addition, newly developed land surface properties and input forcing are ingested into the model, in an attempt to reduce uncertainties associated with the initial and boundary forcing and help to identify model deficiencies. Our results show that the more realistic inputs (parameters, soil types, forcing) lead to larger underestimation of latent heat flux and dry bias, indicating the existence of model structural uncertainty (embedded errors) in WRF‐Hydro that need to be characterized to inform future model development efforts. Including lateral flow processes partly mitigates the model deficiencies in representing hydrologic processes and alleviates the dry bias. In particular, both surface and subsurface lateral flow increase soil moisture mainly over the lower elevations, except that subsurface flow also affects soil moisture over steeper terrains. Additional simulations are performed to assess the effect of routing resolution on model results. When LSM resolution is high, noticeable differences in soil moisture are produced between different routing resolutions especially over steep terrain. Whereas when LSM resolution is coarse, differences between routing resolutions become negligible, especially over flat terrain.
Fluid: Resource-aware Hyperparameter Tuning Engine

Current hyperparameter tuning solutions lack complementary execution engines to efficiently leverage distributed computation, thus ignoring the possibility of intra-and inter-GPU sharing, which exhibits poor resource usage. In this paper, we present Fluid, a generalized hyperparameter tuning execution engine, that coordinates between hyperparameter tuning jobs and cluster resources. Fluid schedules evaluation trials in such jobs using a water-filling approach to make the best use of resources both at intra-and inter-GPU granularities to speed up the tuning process. By abstracting a hyperparameter tuning job as a sequence of TrialGroup, Fluid can boost the performance of diverse hyperparameter tuning solutions. Our experiments show that Fluid can speed up synchronous BOHB by 100% , and BOHB and ASHA by 30% while having similar final accuracy.
Blockchain or not Blockchain? Costs and beneﬁts of large-scale synchronization

Blockchain can be viewed as a mechanism to implement trustworthy access to shared data in systems with mutual distrust. System participants may have conflicting interests and might even be willing to cheat, but the implementation is expected to ensure that they share data and exchange assets in a consistent, available and fair way. The TrustShare project is devoted to the algorithmic basics of blockchains, in order to discover novel efficient data-sharing and asset-transfer implementations. Any software system, be it a multiprocessor application or a large-scale distributed service, involves manipulation of shared data by a collection of users. Depending on the application requirements, the data can be accessed for simple reading and writing, or with more sophisticated conditional operations that may combine reading data units and, in case certain conditions on the read values are met, updating them. In a distributed system prone faults and security attacks, we cannot rely on a trusted “central party” that can store and process data. Instead, users of the systems maintain replicas of the shared data and involve a synchronization protocol to keep the replicas up to date. The prominent blockchain technology aims at implementing a public ”ledger”: a decentralized consistent history of transactions proposed by an open set of participating processes, with no static membership. This problem can be seen as an instance of fault-tolerant state-machine replication [26], prominent examples of which are the crash-tolerant Paxos protocol by Lamport [21] and the BFT (Byzantine fault-tolerant) system by Castro and Liskov [4]. These systems use instances of consensus protocols in order to ensure that users get consistent views of the system evolution. Principal downside of classical consensus protocols are lack of scalability and the need for a fixed or properly reconfigurable set of participants out of which only a bounded fraction (up to one third) can be faulty. This can be hard to ensure in an open (permissionless) system, where an arbitrary fraction of participants can be controlled by the adversary [9]. Prominent blockchain protocols [25,29] achieve (nondeterministic) consistency by assuming that (1) the system is synchronous, (2) participants can use asymmetric cryptography, and (3) the adversary can control
An integrative microenvironment approach for laryngeal carcinoma: the role of immune/methylation/autophagy signatures on disease clinical prognosis and single-cell genotypes

The effects of methylation/autophagy-related genes (MARGs) and immune infiltration in the tumor microenvironment on the prognosis of laryngeal cancer were comprehensively explored in this study. Survival analysis screened out 126 MARGs and 10 immune cells potentially associated with the prognosis of laryngeal carcinoma. Cox and lasso regression analyses were then used to select 8 MARGs (CAPN10, DAPK2, MBTPS2, ST13, CFLAR, FADD, PEX14 and TSC2) and 2 immune cells (Eosinophil and Mast cell) to obtain the prognostic risk scoring system (pRS). The pRS was used to establish a risk prediction model for the prognosis of laryngeal cancer. The predictive ability of the prediction model was evaluated by GEO datasets and our clinical samples. Further analysis revealed that pRS is highly associated with single nucleotide polymorphism (SNP), copy number variation (CNV), immune checkpoint blockade (ICB) therapy and tumor microenvironment. Moreover, the screened pRS-related ceRNA network and circ_0002951/miR-548k/HAS2 pathway provide potential therapeutic targets and biomarkers of laryngocarcinoma. Based on the clustering results of pRS-related genes, single cells were then genotyped and revealed by integrated scRNA-seq in laryngeal cancer samples. Fibroblasts were found enriched in high risk cell clusters at the scRNA-seq level. Fibroblast-related ligand-receptor interactions were then exposed and a neural network-based deep learning model based on these pRS-related hub gene signatures was also established with a high accuracy in cell type prediction. In conclusion, the combination of single-cell and transcriptome laryngeal carcinoma landscape analyses can investigate the link between the tumor microenvironmental and prognostic characteristics.
Geometrical Framework Application Directions in Identification Systems. Review

The approaches review of the framework application in identification problems is fulfilled. It is showed that this concept can have different interpretations of identification problems. In particular, the framework is understood as a frame, structure, system, platform, concept, and basis. Two directions of this concept application are allocated: 1) the framework integrating the number of methods, approaches or procedures; b) the mapping describing in the generalized view processes and properties in a system. We give the review of approaches that are the basis of the second direction. They are based on the analysis of virtual geometric structures. These mappings (frameworks) differ in the theory of chaos, accidents, and the qualitative theory of dynamic systems. Introduced mappings (frameworks) are not set a priori, and they are determined based of the experimental data processing. The main directions analysis of geometrical frameworks application is fulfilled in structural identification problems of systems. The review includes following directions: i) structural identification of nonlinear systems; ii) an estimation of Lyapunov exponents; iii) structural identifiability of nonlinear systems; iv) the system structure choice with lag variables; v) system attractor reconstruction.
University of Birmingham Does a screening trial for spinal cord stimulation in patients with chronic pain of neuropathic origin have clinical utility and cost-effectiveness (TRIAL- STIM)? a randomised controlled trial

Spinal cord stimulation (SCS) is an established treatment of chronic neuropathic pain. Although a temporary SCS screening trial is widely used to determine whether a patient should receive permanent SCS implant, its evidence base is limited. We aimed to establish the clinical utility, diagnostic accuracy, and cost-effectiveness of an SCS screening trial. A multicentre single-blind, parallel two-group randomised controlled superiority trial was undertaken at 3 centres in the United Kingdom. Patients were randomised 1:1 to either SCS screening trial strategy (TG) or no trial screening strategy (NTG). Treatment was open label, but outcome assessors were masked. The primary outcomemeasure was numerical rating scale (NRS) pain at 6-month follow-up. Between June 2017 and September 2018, 105 participants were enrolled and randomised (TG 5 54, NTG 5 51). Mean numerical rating scale pain decreased from 7.47 at baseline (before SCS implantation) to 4.28 at 6 months in TG and from 7.54 to 4.49 in NTG (mean group difference: 0.2, 95% confidence interval [CI]:21.2 to 0.9, P5 0.89). We found no difference between TG and NTG in the proportion of pain responders or other secondary outcomes. Spinal cord stimulation screening trial had a sensitivity of 100% (95% CI: 78-100) and specificity of 8% (95% CI: 1-25). The mean incremental cost-effectiveness ratio of TG vs NTG was £78,895 per additional quality-adjusted life-year gained. In conclusion, although the SCS screening trial may have some diagnostic utility, there was no evidence that an SCS screening TG provides superior patient outcomes or is cost-effective compared to a no trial screening approach.
Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder

Citation for published version: McIntosh, AM, Hall, LS, Zeng, Y, Adams, MJ, Gibson, J, Wigmore, E, Hagenaars, S, Davies, G, FernandezPujals, AM, Campbell, AI, Clarke, T-K, Hayward, C, Haley, CS, Porteous, DJ, Deary, IJ, Smith, DJ, Nicholl, BI, Hinds, DA, Jones, AV, Scollen, S, Meng, W, Smith, BH & Hocking, LJ 2016, 'Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder: a family-based mixed-model analysis', PLoS Medicine, vol. 13, no. 8, e1002090. https://doi.org/10.1371/journal.pmed. 1002090
A Survey Based Study on Fog Computing Awareness

In this day and age, the rise in technological advancements has the potential to improve and transform our lives every day. The rapid technology innovation can have a great impact on our business operations. Currently, Cloud computing services are popular and offer a wide range of opportunities for their customers. This paper presents a survey on a more recent computing architecture paradigm known as Fog Computing. Fog networking is a beneficial solution that offers the greater facility of data storage, enhanced computing, and networking resources. This new concept of fog complements cloud solution by facilitating its customers with better security, real-time analysis improved efficiency. To get a clear picture and understanding of how fog computing functions, we have performed an extensive literature review. We also presented a comparative study of fog computing with cloud and grid computing architectures. In this study, we have conducted a survey that led us to the conclusion that fog computing solution is still not applicable and implemented in most of the IoT industries due to the lack of awareness and the high architecture’s cost. Results of the study also indicate that optimized data storage and security are a few of the factors that can motivate organizations to implement the Fog computing architecture. Furthermore, the challenges related to fog computing solution are reviewed for progressive developments in the future.
Teaching a Robot with Unlabeled Instructions: The TICS Architecture

In this work, we propose a framework that enables a human to teach a robot a new task by interactively providing it with unlabeled instructions. We ground the meaning of instruction signals in the task-learning process, and use them simultaneously for guiding the latter. We implement our framework as a modular architecture, named TICS (Task-Instruction-Contingency-Shaping) that combines different information sources: a predefined reward function, human evaluative feedback and unlabeled instructions. This approach provides a novel perspective for robotic task learning that lies between Reinforcement Learning and Supervised Learning paradigms. We evaluate our framework both in simulation and with a real robot. The experimental results demonstrate the effectiveness of our framework in accelerating the task-learning process and in reducing the number of required teaching signals.
An integrated platform to evaluate graph embedding

Graphs, such as social networks, word co-occurrence networks, and communication networks, occur naturally in various real-world applications. Analyzing these networks yields insight into the structure of society, language, and different patterns of communications. Many approaches have been proposed to perform the analysis. Recently, many researchers are interested on methods which use the representation of graph nodes in vector. In this research, we provide a comprehensive and structured analysis of an integrated platform to evaluate graph embedding techniques. We will first explain our platform and then evaluate many techniques of graph embedding on a few common datasets and compare their performance against one another. We have implemented graph embedding techniques on an integrated platform and further evaluated the performance of each technique.
Status, scientific results and technical improvements of the NBH on TCV tokamak

The TCV tokamak contributes to physics understanding in fusion reactor research by a wide set of experimental tools, like flexible shaping and high power ECRH. A 1MW, 25 keV deuterium heating neutral beam (NB) has been installed in 2015 and it was operated from 2016 in SPC-TCV domestic and EUROfusion MST1 experimental campaigns ( ̃50/50%). The rate of failures of the beam is less than 5%. Ion temperatures up to 3.5 keV have been achieved in ELMy H-mode, with a good agreement with ASTRA predictive simulations. The NB enables TCV to access ITER-like βN values (1.8) and Te/Ti ̃1, allowing investigations of innovative plasma features in ITER relevant ELMy H-mode. The advanced Tokamak route was also pursued, with stationary, fully non-inductive discharges sustained by ECCD and NBCD reaching βN ̃1.4–1.7. Real-time control of the NB power has been implemented in 2018 and presented together with the statistics of NB operation on the TCV. During commissioning, the NB showed unacceptable heating of the TCV beam duct, indicating a higher power deposition than expected on duct walls. A high beam divergence has been found by dedicated measurement of 3-D beam power density distribution with an expressly designed device (IR measurement on tungsten target).
NAYAN-Narrator for the Visually Impaired

Worldwide there are millions of blind people and even more number of visually impaired people. Disability of optical text and image reading features a huge impact on the standard of life for visually disabled people. Although there are several devices designed for providing a helping hand to the visually disabled to work out objects using an alternating sense like sound and touch, the event of text reading and image narrating devices are still at a nascent stage. In the current scenario, systems involving image captioning or text recognition are generally limited either by explicitly hoping on color and shape identification or by requiring manual assistance or even thanks to the high cost. Therefore, a low-cost and effective system is presented that can be automatically mapped and helps to skim the text clearly yet explain images to visually impaired people. Our important objective is to acknowledge the text character and pictures present in books, novels, letters, etc. and explain the content in sequence through speech signals just like the human narration.
The effect of long-term fertilization on soil water storage and water deficit in the Black Soil Zone in northeast China

Zou, W. , Si, B. , Han, X. and Jiang, H. 2012. The effect of long-term fertilization on soil water storage and water deficit in the Black Soil Zone in northeast China. Can. J. Soil Sci. 92: 439-448. The Black Soil Zone in northeast China is one of the most important areas of agricultural production in China and plays a crucial role in food supply. However, further improvement in crop yield hinges on effective management of soil water. There is a poor understanding of how different fertilization methods affect crop water use efficiency. The objective of this study was to examine the effect of different fertilization methods on soil water storage and deficit in Black soils. A long-term experiment was conducted at the National Field Research Station of Agro-ecosystems, at Hailun County, Heilongjiang province in northeastern China from 1999 to 2008. Three fertilizer treatments including no fertilizer (CK), inorganic fertilizer (NP) and inorganic fertilizer plus organic material (NPM) were tested. The results showed that soil water storage decreased in the order CK, NP, and NPM during the growing season and the differences in soil water storage in the active root zone (0-70 cm) and below the active root zone (70-130 cm) and soil water deficit were statistically significant among the three treatments. Due to the uneven temporal distribution of rainfall and crop water uptake, soil water content was very dynamic in all three treatments: The low soil water storage and resulting soil water deficit (defined as the monthly difference between potential evapotranspiration and soil available water storage) within the 0- to 70-cm soil profile were found in both June and July. Further, soil receiving NPM was more likely to have a soil water deficit, but less likely to have excessive water. A lower risk of excess water may result in deeper root penetration and increased water use at greater depth, and thus the water deficit under the NPM treatment may not be the limiting factor for crop production. Therefore, NPM seems a viable management practice for improving crop yields in the Black Soil Zone in northeast China, possibly due to higher soil organic carbon and nutrient supply and lower probability of excess water.
Multi-Camera Panoramic Imaging System Based on Adaptive Brightness Uniformization For The Truck

With the development of science technology and logistics industry, the transportation of large trucks is also indispensable. It is also accompanied by many traffic accidents. The paper mainly focuses on the problem of blind spots in the parking of large trucks. A panoramic imaging system with six cameras is implemented to improve its safety performance. It mainly includes the realization of modules included simultaneous acquisition of images by multiple cameras, image calibration and correction, top view image generation, image stitching and image fusion. In view of the brightness difference of images acquired by different cameras, we proposed an adaptive brightness uniformization method based on γ-transformation. Meanwhile, we compared the proposed method with various image enhancement methods included histogram equalization, Laplace operator and logarithm transformation. The experimental results in the system demonstrate the superiority of our proposed method compared to others.
Do Fossil Fuel Divestment Commitments and Green Finance Policies Impact Fossil Fuel Investment Brokerage within and between Financial Centres?

Using a global dataset of over 840,000 equity, bond and syndicated loan investment banking deals, we build the fossil fuel investment brokerage profile of financial centres worldwide between 2000 and 2018. We also study whether financial centre fossil fuel divestment commitments and country level green banking policies impact this profile over our study time period. We find that several financial centres shift their fossil fuel investment brokerage profiles substantially, including the asset classes which they are active in, and that divestment commitments and green banking policies fail to restrain fossil fuel investment, in particular the inter-financial centre brokerage of fossil fuel finance.