Miracle-dz/UniFAR-FTUs huggingface dataset:
SINS Initial Alignment of Swaying Base Under Geographic Latitude Uncertainty

To solve the problem of initial alignment of the strapdown inertial navigation system(SINS) under swaying base with geographic latitude uncertainty,a new latitude estimation algorithm and initial alignment method are presented.The former uses the angle between the two gravities in the inertial frames of different times to extract latitude,while the latter utilizes the continuous attitude update to record the attitude changes caused by sway interrupt,and then uses the estimation of the initial attitude to determinate the attitude of the body.Theoretical analysis results show that the estimation error of latitude is mainly dependent on the accelerometer errors,while the error caused by gyro errors and swaying interrupt is tiny.The simulation results show that the proposed latitude estimation algorithm and initial alignment method can be used with good results under swaying base environments with latitude uncertainties.
A Coeﬃcient of Variation Based Image Selective Segmentation Model Using Active Contours

Most image segmentation techniques are eﬃcient to segment images with prominent edges, but are less so for some challenging images with low frequencies and with overlapping regions of homogeneous intensities. In our recent work we proposed an eﬀective model of selective segmentation which works well for many examples except these challenging images. In this paper we propose a new model using the coeﬃcient of variation as a ﬁdelity term. Test results show that the new model performs much better than previous works in successfully segmenting the challenging images.
Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed

The effects of mountain pine beetle (MPB)‐induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high‐resolution computational grid. Simulations of MPB‐affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB‐affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope‐scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field‐based studies and previous modeling work. Hillslope‐scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB‐induced tree mortality was offset by increased late‐summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB‐induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long‐term gage observations that are complicated by inter‐annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB‐affected area or a water year with above average snowpack.
ResearchHigh-End Measuring Instruments—Review Structural Deformation Monitoring of Flight Vehicles Based on Optical Fiber Sensing Technology: A Review and Future Perspectives

Structural deformation monitoring of ﬂight vehicles based on optical ﬁber sensing (OFS) technology has been a focus of research in the ﬁeld of aerospace. After nearly 30 years of research and development, Chinese and international researchers have made signiﬁcant advances in the areas of theory and meth-ods, technology and systems, and ground experiments and ﬂight tests. These advances have led to the development of OFS technology from the laboratory research stage to the engineering application stage. However, a few problems encountered in practical applications limit the wider application and further development of this technology, and thus urgently require solutions. This paper reviews the history of research on the deformation monitoring of ﬂight vehicles. It examines various aspects of OFS-based deformation monitoring including the main varieties of OFS technology, technical advantages and disadvantages, suitability in aerospace applications, deformation reconstruction algorithms, and typical applications. This paper points out the key unresolved problems and the main evolution paradigms of engineering applications. It further discusses future development directions from the perspectives of an evolution paradigm, standardization, new materials, intelligentization, and collaboration. (cid:1) 2022 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license
SMU Science and Technology Law Review SMU Science and Technology Law Review

Our Sycamore [sic] processor takes about 200 seconds to sample one instance of a quantum circuit a million times—our benchmarks currently indicate that the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. 1 We want to make our defenses so good, and our architectures so strong, that we do not care whether we are being attacked most of the time because the
An Efﬁcient Method for Solving Two-Dimensional Partial Differential Equations with the Deep Operator Network

: Partial differential equations (PDEs) usually apply for modeling complex physical phenomena in the real world, and the corresponding solution is the key to interpreting these problems. Generally, traditional solving methods suffer from inefﬁciency and time consumption. At the same time, the current rise in machine learning algorithms, represented by the Deep Operator Network (DeepONet), could compensate for these shortcomings and effectively predict the solutions of PDEs by learning the operators from the data. The current deep learning-based methods focus on solving one-dimensional PDEs, but the research on higher-dimensional problems is still in development. Therefore, this paper proposes an efﬁcient scheme to predict the solution of two-dimensional PDEs with improved DeepONet. In order to construct the data needed for training, the functions are sampled from a classical function space and produce the corresponding two-dimensional data. The difference method is used to obtain the numerical solutions of the PDEs and form a point-value data set. For training the network, the matrix representing two-dimensional functions is processed to form vectors and adapt the DeepONet model perfectly. In addition, we theoretically prove that the discrete point division of the data ensures that the model loss is guaranteed to be in a small range. This method is veriﬁed for predicting the two-dimensional Poisson equation and heat conduction equation solutions through experiments. Compared with other methods, the proposed scheme is simple and effective.
Risk management, ﬁrm reputation, and the impact of successful cyberattacks on target ﬁrms ✩

We develop a model where a ﬁrm has an optimal exposure to cyber risk. With rational, fully informed agents and with no hysteresis, a successful cyberattack should have no impact on a ﬁnancially unconstrained target’s reputation and post-attack policies. In contrast, when a successful attack involves the loss of personal ﬁnancial information, there is a signiﬁcant shareholder wealth loss, which is much larger than the attack’s out-of-pocket costs. This excess loss is higher when the attack decreases sales growth more and lower when the board pays more attention to risk management before the attack. Further, an attack decreases a ﬁrm’s risk appetite, as it beefs up its risk management and information technology and decreases the risk-taking incentives of management. Finally, successful cy-berattacks adversely affect the stock price of ﬁrms in the target’s industry. These results imply that successful attacks with personal ﬁnancial information loss provide adverse information about cyber risk to target ﬁrms, their stakeholders, and their competitors.
The Role of E-Trust as Mediating Variable on Predicting the Effect of Website Design Quality and Online Reviews on Online Booking Intention

Digital technology has increased access to information and made online travel booking more convenient, impacting the public's increased consumption of products and services. In online booking platforms, both Website Design Quality and Online Reviews, including appearance, navigational functionality, and consumer feedback, can influence consumers' trust and considerations. This research explores the influence of the quality of Website Design and Online Reviews on Online Booking Intention. E-Trust will act as a mediating variable in this study. The research was conducted among followers of one of the official Instagram accounts of an Online Booking Platform who had yet to make any transactions. A questionnaire was used to collect data, and 138 respondents participated. The data were analysed using Structural Equation Modelling Partial Least Square, and the results indicate that good Website Design Quality and Positive Online Reviews significantly influence Online Booking Intention. These findings also highlight the importance of E-Trust in influencing consumers during their decision-making process.
The application of MTA as apical plug for root canal obturation – in vitro study

Summary Introduction Prognosis of endodontically treated tooth is directly correlated to the quality of apical obturation. Modern concept of endodontics in particular way points out the quality of apical filling. The aim of this study was to assess the quality of root canal obturation with MTA apical plug using the method of gas (argon) penetration. Material and Methods Sixty-six freshly extracted single rooted (single canal) teeth were divided into the two experimental (30 teeth) and one control group (6). All canals were instrumented using hand and rotary files in step-back technique and copious irrigation of 1%NaOCl. In the first experimental group teeth were obturated using different sealers: Gutta Flow (Roeko), AH Plus (DeTrey), Acroseal (Septodont) and mono gutta-percha cone (10 canals each). In the second experimental group obturation involved 3 mm of MTA-Angelus apical plug while the remaining canal space was filled with the same three sealers as in the first group. The rate of gas permeability by Leak detector-Edwards LD 416 was measured in all teeth. Results The best seal was found in teeth obturated with Gutta Flow and MTA plug with average diffusion rate of 264.4 sec while the worst quality of obturation was found with Acroseal (178.5 sec-the highest gas permeability). All samples with MTA plug exhibited significantly lower leakage than the samples filled without MTA apical plug. Conclusion Root canals filled with MTA apical plug exhibited statistically significant lower gas permeability in comparison to the ones filled with sealer and guttapercha cones only.
Government cloud computing and the policies of data sovereignty

Government cloud services are a new development at the intersection of electronic government and cloud computing which holds the promise of rendering government service delivery more effective and efficient. Cloud services are virtual, dynamic and potentially stateless which has triggered governments' concern about data sovereignty. This paper explores data sovereignty in relation to government cloud services and how national strategies and international policy evolve. It concludes that for countries data sovereignty presents a legal risk which can not be adequately addressed with technology or through contractual arrangements alone. Governments therefore adopt strategies to retain exclusive jurisdiction over government information.
Towards Autonomous Computer Networks in Support of Critical Systems

A recent trend dictating evolution of management and orchestration of computer networks is constituted by the softwarization and virtualization of them, which have drastically simplified the deployment and real-time reconfiguration of network functions, allowing them to continuously adapt and to deal with dynamic demands in an automated way. Alongside, recent management and orchestration approaches for softwarized networks employ Artificial Intelligence (AI) and Machine Learning (ML) to further reduce reaction time and improve the accuracy of decisions, where the network operations can be automated to the point of realizing autonomous driving networks. However, while automating operations can improve the overall system (it is acknowledged that 70% of network faults are caused by manual errors), AI/ML methods are not the panaceas, and we are still far from having a fully operating and efficient automated architecture. In this dissertation, we present a novel class of software network solutions that share the goal of enabling intelligent and autonomous computer networks, exploring how to exploit the power of AI/ML to handle the growing complexity of critical systems. We start with a new network management scheme for adaptive routing and autonomous scaling of virtual network resources. Then, acting on the hosts, we propose to adjust the TCP congestion control with a ML-based solution, whose goal is to select the proper congestion window learning from end-to-end features and (when available) network signals. We believe that the proposed solutions, and their combination, can lay the foundation for automated systems that better suit modern edge environments and cellular networks by providing unprecedented flexibility and adaptation to even unseen and unknown network conditions.
Colloidal particles at liquid interfaces.

[BOOK] Colloidal Particles At Liquid Interfaces.PDF. You can download and read online PDF file Book Colloidal Particles At Liquid Interfaces only if you are registered here.Download and read online Colloidal Particles At Liquid Interfaces PDF Book file easily for everyone or every device. And also You can download or readonline all file PDF Book that related with Colloidal Particles At Liquid Interfaces book. Happy reading Colloidal Particles At Liquid Interfaces Book everyone. It's free to register here toget Colloidal Particles At Liquid Interfaces Book file PDF. file Colloidal Particles At Liquid Interfaces Book Free Download PDF at Our eBook Library. This Book have some digitalformats such us : kindle, epub, ebook, paperbook, and another formats. Here is The Complete PDF Library
Mapping error in Southern Ocean transport computed from satellite altimetry and argo

In an effort to better estimate transport dynamics in response to wind forcing (primarily the Southern Annual Mode), this study quantifies the uncertainty in mapping zonal geostrophic transport of the Antarctic Circumpolar Current from sparse temperature, salinity and sea surface height observations. To do this, we sampled an ocean state estimate at the locations of both Argo floats and the Jason-1 altimeter groundtrack. These sampled values were then optimally interpolated to create SSH and temperature/salinity grids with 1° resolution. The temperature, salinity and SSH grids were then combined to compute the zonal geostrophic transport and compared to that estimated from the full state estimate. There are significant correlations between the baroclinic and barotropic error contributions to the total transport error. The increase in Argo floats in the Southern Ocean is effective in reducing mapping error. However, that error improvement is not uniform. By analyzing systematic errors in transport time series, we find the transects that are most appropriate for analyzing the dynamics of ACC transport using Argo and altimetric gridded fields. Based on our analysis, we conclude region south of Tasmania is most appropriate, with lowest uncertainty. Using real-world data, we calculated zonal transport variability at a transect south of Tasmania. There is an insignificant trend (0.3 ± 0.4 Sv yr−1, 90% confidence) but significant low-frequency variability correlated with the Southern Annular Mode (0.53, p < 0.05). The barotropic component is most responsible for the low-frequency variability, and this would be unobservable from ship casts without velocity measurements at depth. This article is protected by copyright. All rights reserved.
Investigation of air pollution in large-scale buildings and of employees' personal exposure level

School of Health Sciences, University of Occupational and Environmental Health (UOEH), 1-1 Iseigaoka, Yahatanishi, Kitakyushu, 807-8555, Japan e-mail: kunugita@med.uoeh-u.ac. jp School of Medicine, University of Miyazaki, Miyazaki, Japan Graduate School of Engineering, Kyoto University, Sakyo-ku, Kyoto, Japan Present address: Department of Public Health, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
Variations in the Anatomy of Sphenoid Sinus: A Computed Tomography Investigation

Aims: The sphenoid sinus is surrounded by many neurovascular structures which are very vulnerable to intrasphenoid sinus surgeries. The purpose of this study is to investigate the variation of sphenoid sinus structure by CT scan imaging. Methodology: This is a retrospective study of 3D images of a paranasal sinus in 129 cases. In this study, three-way metering of the sphenoid sinus, additional septum, pneumatization of the period process (PP), anterior clinoid process (ACP) and greater wing of sphenoid and protrusion and dehiscence of adjacent structures will be assessed. Results: Protrusion of internal carotid artery (ICA), a vidian nerve, maxillary nerve (V2) and optical canal were seen respectively 50.4%, 57.36%, 62.5% and 54.3% but dehiscence of this structure was seen 8.5%, 7%, 3.9% and 6.2%. penumtazition of PP, ACP and greater wing of sphenoid were seen 96.87%, 43.9% and 41.1%. Additional septum also is seen in 76% of the population. Conclusion: This study demonstrates numerous variations in sphenoid sinus structure. Some of the variations cause many problems during intrasphenoidal surgery. Therefore, physicians should evaluate patients completely before surgery.
Towards Dynamic Request Updating With Elastic Scheduling for Multi-Tenant Cloud-Based Data Center Network

Serving the ever-growing demand for computation, storage, and networking resources for multi-tenant in cloud computing is an important mission of Data Center Networks (DCNs). In this paper, we study the dynamic request updating problem, and our objective is to maximize the elasticity of cloud-based DCNs while achieving rapid response to multi-tenants. We use virtual clusters under the hose communication model to denote requests. Instead of using heuristic algorithms as the existing work does, this paper introduces a novel two-stage dynamic request updating framework with elastic resource scheduling strategy. In the first stage, we propose a multi-tenant fast initial provisioning scheme to realize the real-time response and analyze its optimality and complexity. Additionally, we provide a deep reinforcement learning-based dynamic updating strategy to enhance the elasticity of virtual clusters that are being used or scaling during the second stage. We train a fully connected neural network by creating a new feasible action set to realize the reduction, and it approximates the policy based on a proposed aggressive objective selection method to improve training speed while avoiding high dimensions caused by large scales of tenants and DCNs. Extensive evaluations demonstrate that our scheme outperforms baselines in terms of both elasticity and efficiency.
Evolution of ENSO‐related seasonal precipitation anomalies in East Asia: A robustness revisit

The El Niño–Southern Oscillation (ENSO) is a major source of seasonal climate predictability and a key predictor for East Asian precipitation. However, the impacts of ENSO on East Asian precipitation are extremely complex and still controversial. Thus, it is necessary and significant to use various (observational and model) data sources to further examine the robustness of the impacts. This study revisits the evolution of the ENSO‐related seasonal precipitation anomalies in East Asia, including symmetric and asymmetric impacts of El Niños and La Niñas, the differences in the influences of eastern Pacific (EP) and central Pacific (CP) El Niños, and the interdecadal change of ENSO influences. The ENSO impact on East Asian precipitation has weakened (strengthened) in the ENSO's developing (decay) phase in the recent two decades. The ENSO impacts are robust in (i) southern China‐lower reaches of the Yangtze River‐southern Japan around the ENSO's mature phase, (ii) western North China in the developing phase and (iii) southwestern China in the decay phase. The distribution of East Asian precipitation anomalies is asymmetric in El Niño and La Niña years. The model simulations forced with observed sea surface temperature generally reproduce the observed evolution of seasonal precipitation anomalies associated with ENSO and confirm the robust impact of ENSO in East Asia. These results indicate the necessity to consider the asymmetric impact of El Niños and La Niñas, to distinguish the El Niño flavours for their impact on the East Asian climate, and to include the interdecadal variation of ENSO influence in addressing East Asian climate anomalies.
The Biogeochemistry of Carbon Isotopes in Local Lakes

The Crystal Lakes are a chain of small interconnected kettle glacial lakes in southwestern Clark County surrounded by residential areas and agricultural land. Main Lake, the deepest of the four, has unique biogeochemical patterns as revealed by its summer thermal stratification. In order to understand these patterns, data and samples were collected monthly over the period of a year at the deepest point in the lake. Water samples were analyzed for nutrients, major solutes and carbon isotope composition. The results reveal that the chemical and biological systems are based on three processes; the thermal stratification of the water column, photosynthesis by phytoplankton and purple sulfur bacteria (PSB), and the decomposition of organic matter in the sediment. Thermal stratification and photosynthesis create oxygen rich, nutrient poor and isotopically heavier water in the epilimnion and metalimnion during the summer months. Decomposition in the hypolimnion results in anoxic, nutrient rich and isotopically lighter water at the same time. Turnover of the lake in the fall mixes oxygen, nutrients and carbon isotopes throughout the water column, which allows these processes to follow the same pattern again the next summer.
Genetics in Ischemic Stroke: Current Perspectives and Future Directions

Ischemic stroke is a heterogeneous condition influenced by a combination of genetic and environmental factors. Recent advancements have explored genetics in relation to various aspects of ischemic stroke, including the alteration of individual stroke occurrence risk, modulation of treatment response, and effectiveness of post-stroke functional recovery. This article aims to review the recent findings from genetic studies related to various clinical and molecular aspects of ischemic stroke. The potential clinical applications of these genetic insights in stratifying stroke risk, guiding personalized therapy, and identifying new therapeutic targets are discussed herein.