Miracle-dz/UniFAR-FTUs huggingface dataset:
New images of the Earth's upper mantle from measurements of surface wave phase velocity anomalies

[1] The sensitivity of a surface wave to the lateral structure of the Earth's mantle depends on the local structure and thickness of the crust; particularly at short periods, the strong lateral heterogeneity of the crust has a significant nonlinear effect on the surface wave “sensitivity functions. ” Thus far, this effect has not been quantified, and tomographic studies of the upper mantle based on surface wave observations have not taken it into account. On the basis of a Jeffreys-Wentzel-Kramers-Brillouin (JWKB) description of surface wave propagation we find and discuss the lateral variations of the sensitivity of Love and Rayleigh waves to mantle seismic anomalies, associated with a realistic model of the crust [Mooney et al., 1998]. We then use the resulting laterally varying sensitivity kernels to determine a new tomographic image of horizontally and vertically polarized shear velocity in the upper mantle from Love and Rayleigh wave phase velocity measurements (periods from 35 to 300 s). In terms of large-scale patterns of high and low velocity our model is similar to previously published ones, confirming, among other features, the anomalous anisotropy underlying the central Pacific [Ekstrom and Dziewonski, 1998]; we find, however, that the lateral dependence of the surface wave sensitivity kernels has a significant effect on the absolute amplitude of the anomalies, which should not be neglected as we attempt to obtain higher-resolution images of the upper mantle.
Convergence vs. retreat in Southern Tyrrhenian Sea: Insights from kinematics

The Tyrrhenian Sea is an extensional basin opened by trench retreat and back‐arc extension during subduction of the Calabrian slab in the last 10–12 My. Subduction is still active beneath the SEmost part of the Tyrrhenian Sea, as testified by seismicity down to 500 km depth. By analyzing seismicity and geodetic data, together with recent tomographic images, we define the present‐day situation. An evident ∼N‐S compressional regime prevails in the Tyrrhenian region west of the Aeolian archipelago, while east of them a NNW‐SSE extension is documented by focal mechanisms and GPS data, with a much smaller strain rate with respect to the past. The transition between these two domains is accommodated by a N‐S discontinuity zone which runs from Aeolian Islands to Mt. Etna with an extensional to strike‐slip deformation.
Analysis of dispersion curves of Rayleigh waves in the frequency-wavenumber domain

The method of spectrum analysis of surface waves (SASW) is discussed briefly. The analysis of the dispersion curves of Rayleigh waves in the frequencywavenumber (fk) domain is suggested due to the problems encountered in SASW. Three models of the layered media are considered according to typical situations in practice. All the modes that can be effectively excited are analyzed. The excitation and propagation characteristics of the Rayleigh waves are investigated by numerical simulation. The effects of some parameters such as number of channels and distance (s) between the source and the first receiver on the dispersion curves are investigated in detail for three models. Some important results about the number of receiver channels, relative error, mode jumping, and other aspects are obtained. It is found that reliable dispersion curves can be obtained by fk analyses when the distance between the first receiver and the source is greater than one half the wavelength (0.5λ). Key words: dispersion curves, Ra.
Combining variable precision rough set and neural network in remote sensing image classification

This paper presents a new approach of Remotely Sensed data classification based on Variable Precision Rough set(VPRS) and BP neural network, compared to traditional rough sets, VPRS is more robust to noise and can generate more concise and representative classification rules of the remote sensing image. After the rules are deduced, they are fed to the BP neural network, which results in short training time and a high classification accuracy.
Rotational Thromboelastometry Coagulation Parameters (ROTEM®) May be Discriminative for Active Inflammatory Bowel Disease: A Prospective Observational Study.

BACKGROUND AND AIMS Inflammatory bowel disease (IBD) is associated with increased risk of thromboembolic events. The rotational thromboelastometry (ROTEM®) is a validated integrative assessment of coagulation, but it has never been studied in IBD patients. METHODS We performed a monocentric prospective observational study in a national tertiary center. Adult IBD patients underwent ROTEM® analysis on admission to our IBD Department. Parameters evaluated with ROTEM® tests (INTEM, EXTEM and FIBTEM) were clotting time (CT), the time of clot formation (CFT), clot firmness amplitude after 5 and 10 minutes (A5 and A10) and maximum clot firmness (MCF). ROC curves were performed in order to evaluate the ability of ROTEM® to predict active IBD. RESULTS Several ROTEM® parameters were significantly associated with active IBD compared to patients in remission, towards a hypercoagulable status for patients with active disease: CT, CFT, A5, A10, MCF. ROC analysis demonstrated that parameters related to clot robustness showed a very good prediction ability of active IBD (AUC >0.8): A5, A10, MCF in INTEM (p<0.001), in EXTEM (p<0.001) and MCF in FIBTEM (p<0.001). ROTEM® parameters showed high correlations with inflammation markers as C-reactive protein (CRP) and faecal calprotectin (FC). CONCLUSIONS Our study showed that ROTEM® parameters are modified in patients with active IBD, being correlating with inflammation markers and demonstrating a high prediction ability of active IBD. Future research is needed to validate ROTEM® as a method to discriminate patterns of active IBD and to guide anticoagulant therapy in patients with active IBD.
Comment on “High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM (ZS) and high‐performance computing” by Eric Laloy and Jasper A. Vrugt

Laloy and Vrugt [2012] (doi:10.1029/2011WR010608, hereafter referred to as LV) recently introduced a new Markov Chain Monte Carlo (MCMC) algorithm, entitled MT-DREAM(ZS). To illustrate the improved performance of this new algorithm, LV compared it against another adaptive MCMC approach, DREAM(ZS) [Vrugt et al., 2009], and a direct search method, SP-UCI [Chu et al., 2010]. The modeling cases used as benchmarks were the Sacramento Soil Moisture Accounting (SAC-SMA) model and a 241-parameter groundwater model developed by Keating et al. [2010]. Based on their experimental results, LV concludes that ‘‘SP-UCI performs poorly’’ on both models, therefore LV raises the question about the ability of SP-UCI to deal with complex and multimodal searching spaces. Also, the experiments show that MT-DREAM algorithm demonstrates substantial improvement over DREAM(ZS) and SP-UCI for searching the global optima of high-dimensional models. We congratulate LV on their new algorithm and the consistent performances for the test examples provided in the MT-DREAM(ZS) and DREAM(ZS) packages. However, after repeating other two conclusive experiments in LV’s paper, we would like to communicate our concerns regarding the unfair judgments about the performance and ability of SP-UCI for these two models. Also, we are puzzled about the reproducibility of the experimental results and the effectiveness of the MT-DREAM(ZS) algorithm in assessing complex posterior distributions reported by LV about both the MT-DREAM and SP-UCI algorithms on the SACSMA model and the 241-parameter ground water model.
UPPERMOST PERMIAN TO LOWER TRIASSIC CONODONTS AT BIANYANG SECTION, GUIHZOU PROVINCE, SOUTH CHINA

ABSTRACT A new conodont biostratigraphic study is presented from a key section on the flanks of the Permian-Triassic Great Bank of Guizhou, an isolated carbonate platform from South China, that has recently provided much key data for understanding the nature of this mass extinction interval. Detailed investigation at Bianyang (Guizhou Province) has revealed ten conodont zones, in ascending order: Clarkina yini Zone; Hindeodus changxingensis Zone; Hindeodus parvus Zone; Sweetospathodus kummeli Zone; Neospathodus dieneri Zone; Neospathodus cristagalli Zone; Discretella discreta Zone; Pachycladina-Parachirognathus assemblage zone; Icriospathodus collinsoni Zone; Triassospathodus homeri Zone. This allowed the Permian-Triassic boundary (PTB) to be defined in the section based on the first occurrence of Hindeodus parvus. Furthermore, it is proposed that the first occurrence of Discretella discreta can be used as an auxiliary reference for defining the Induan-Olenekian boundary when Novispathodus waageni is absent both at Bianyang and elsewhere.
Temperature Anomalies in the Northeastern North Atlantic: Subpolar and Subtropical Precursors on Multiannual Time Scales

Abstract An adjoint ocean general circulation model of the North Atlantic is employed to calculate sensitivities of temperature in the northeastern North Atlantic with respect to atmospheric nonlocal fluxes and ocean state variables at prior times, up to 7 yr. Maximum sensitivities cross the Atlantic from east to west within 3 to 4 yr. On this interannual time scale, advection of temperature perturbations by the climatological flow is suggested as the prime mechanism responsible for SST perturbations in the northeastern North Atlantic. The pathway of sensitivities lies preferentially beneath the surface and can be understood in terms of the reemergence mechanism. This provides the link between local forcing, mainly by heat flux in winter, and resurfacing of perturbations at remote locations. On the multiannual to decadal time scale, the western subpolar gyre plays a key role: negative temperature sensitivities that evolve in parallel with positive salinity sensitivities in the Labrador and Irminger Seas g.
Weak synchronization can alter circadian period length: implications for aging and disease conditions

The synchronization of multiple oscillators serves as the central mechanism for maintaining stable circadian rhythms in physiology and behavior. Aging and disease can disrupt synchronization, leading to changes in the periodicity of circadian activities. While our understanding of the circadian clock under synchronization has advanced significantly, less is known about its behavior outside synchronization, which can also fall within a predictable domain. These states not only impact the stability of the rhythms but also modulate the period length. In C57BL/6 mice, aging, diseases, and removal of peripheral circadian oscillators often result in lengthened behavioral circadian periods. Here, we show that these changes can be explained by a surprisingly simple mathematical relationship: the frequency is the reciprocal of the period, and its distribution becomes skewed when the period distribution is symmetric. The synchronized frequency of a population in the skewed distribution and the macroscopic frequency of combined oscillators differ, accounting for some of the atypical circadian period outputs observed in networks without synchronization. Building on this finding, we investigate the dynamics of circadian outputs in the context of aging and disease, where synchronization is weakened.
Role of Malnutrition in Atrial Fibrillation: A Prospective Study including Individuals ≥ 75 Years of Age

Background: Atrial fibrillation (AF) is the most common rhythm disorder in the elderly. The AF can cause life-threatening thromboembolic complications. Therefore, there is a need to determine the risk factors of AF. In this study, we aimed to examine the association of markers of malnutrition with AF in individuals aged 75 years and older and to find the factors that may affect mortality. Methods: In this prospective study, 358 consecutive individuals aged 75 years and older presenting to the cardiology outpatient clinic were included. All participants were divided into AF and sinus rhythm (SR) groups. In addition, a questionnaire and scoring system were used to assess malnutrition status. Information was obtained from all patients through outpatient clinic visits or telephone interviews for one year. Death from any cause was considered as the endpoint. Results: AF was observed in 71 (19.8%) patients. Death was higher in patients with AF (p < 0.001), high CONUT score (p = 0.018), and GLIM malnutrition (p = 0.018). GLIM malnutrition caused a 2.8-fold increase in the development of AF. Conclusions: Screening for malnutrition in the elderly is essential. According to GLIM criteria, malnutrition may play a role in the development of AF and increase one-year mortality in the elderly.
A correlation analysis of monthly mean CO2 retrieved from the Atmospheric Infrared Sounder with surface station measurements

As one of the major greenhouse gases, atmospheric carbon dioxide (CO2) concentrations have been monitored by both top-down satellite observations and air sampling systems on surface stations. The Atmospheric Infrared Sounder (AIRS) on board NASA’s Aqua low Earth orbit (LEO) satellite is a high-resolution infrared sounder that has been in operation for more than 10 years. The World Data Centre for Greenhouse Gases (WDCGG) archives and provides data on CO2 and other greenhouse gases measured mainly from surface stations. In this article, we focus on the correlation between the two different sources of CO2 data and the influencing factors. In general, we find that a linear positive correlation occurs at most stations. However, the variation in the correlation coefficient is large, especially for stations in the Northern Hemisphere. The station’s location, including its latitude, longitude, and altitude, is an important influencing factor because it determines how much its CO2 measurements are influenced by human activities. We also use root mean square difference (RMSD) and bias as evaluation indicators and find that they have similar trends like correlation coefficients.
AE-BP Based Prediction Algorithm for Vibration Anomaly Detection and Intelligent Control of Civil Structures

: Intelligent structures utilize neural networks for intelligent controller prediction, allowing vibrating structures to adaptively adjust their state under dynamic loading. Intelligent structure technology plays a crucial role in preventing the loss of life and the destruction of structures, especially for large structures with hundreds or thousands of members, and their contents. Therefore, to address the problems of unknown time-varying characteristics of the structural system and uncertainty of the environmental loading of the structural system in the vibration control of large nonlinear structures, this paper designs a smart structure technique based on a self-encoder and BP neural network. The technique aims to detect vibration anomalies in civil structures and predict them for intelligent control. This paper firstly introduces the concept of structural vibration control, selects intelligent control for prediction, and proposes an anomaly detection algorithm based on AE to detect structural vibration anomalies. Through comparison experiments of BP neural networks and LSTM, the BP neural network is finally selected for the intelligent control prediction of civil structure vibration.
A lock-in amplifier biosensor for dairy applications

Antibiotic exposure can cause the development of antibiotic resistant bacteria and can induce allergic reactions in humans. A source of high antibiotic exposure is contaminated dairy milk. To prevent contaminated dairy milk, development of antibiotic biosensors for on-site detection is required. This is particularly important for dairy farmers as fines and suspension of license are consequences of shipping contaminated milk to processing plants, where antibiotic tests are currently performed. There are also environmental and economic consequences when whole dairy tanks are contaminated and go to waste. Our work addresses this problem by developing an antibiotic biosensor for farmers to test their milk on-site for ciprofloxacin prior to sending to processing plants. Ciprofloxacin is frequently used to treat common bacterial infections in cattle. Our work provides the following contributions. We introduce an antibiotic biosensor that integrates fluorescence spectroscopy, microfluidic processing, and lock-in amplification to improve the limit-of-detection of ciprofloxacin below the regulatory limit for milk. We also perform traditional fluorescence detection for comparison. Our antibiotic biosensor has a signal-flow starting with an ultraviolet light emitting diode for illumination of ciprofloxacin, and moving through a microfluidic platform, a photodiode for detection of the fluorescent wavelength, and a lock-in amplifier. Our antibiotic biosensor is well-suited for fast on-site analyses and is designed for ease-of-use. Overall, our work shows promise for the integration of real-time on-site antibiotic detection of antibiotics in dairy.
Size-Reduced Highly Selective Bandpass Filters Based on Dual-Mode Slow-Wave Patch Resonators

A novel dual mode slow-wave patch resonators (SWPRs) are proposed based on capacitive-load patches arrays (CLPAs) with short circuit posts in this brief. Owing to CLPAs and cross slots, size of patch can be reduced significantly. Using SWPR’ s TM100 and TM010, two types of bandpass filters (BPFs) with size-reduced and highly-selective are realized. Moreover, different cascading methods of dual-mode SWPRs for high-pole filters’ design by stepped impedance folded coupling line (SIFCL) are analyzed and compared to maintain high selectivity. For the demonstration, two four-pole quasi-elliptic BPFs are designed, fabricated, and measured to verify the performance and design method of the proposed dual-mode SWPR filters. Compared with traditional patch filters, size of the proposed filters can be reduced by 55% and 42%.
Simulated annealing two‐point ray tracing

We present a new method for solving the two-point seismic ray tracing problem based on Fermat's principle. The algorithm overcomes some well known difficulties that arise in standard ray shooting and bending methods. Problems related to: (1) the selection of new take-off angles, and (2) local minima in multipathing cases, are overcome by using an efficient simulated annealing (SA) algorithm. At each iteration, the ray is propagated from the source by solving a standard initial value problem. The last portion of the raypath is then forced to pass through the receiver. Using SA, the total traveltime is then globally minimized by obtaining the initial conditions that produce the absolute minimum path. The procedure is suitable for tracing rays through 2D complex structures, although it can be extended to deal with 3D velocity media. Not only direct waves, but also reflected and head-waves can be incorporated in the scheme. One important advantage is its simplicity, in as much as any available or user-preferred initial value solver system can be used. A number of clarifying examples of multipathing in 2D media are examined.
Resilient Synchronization of Neural Networks Under DoS Attacks and Communication Delays via Event-Triggered Impulsive Control

This article focuses on solving the synchronization problem of neural networks (NNs) in the presence of denial-of-service (DoS) attacks and communication delays. Specifically, an attack detection algorithm constructed based upon the acknowledgment (ACK) signal is provided to detect the sleeping and active intervals of DoS attacks. To reduce information transmission during the synchronization-seeking process, a new kind of Lyapunov function-based resilient event-triggered mechanism (ETM) is designed to modulate the information transmission between the master and slave systems. Then, an event-based impulsive controller is designed to achieve synchronization in the master–slave systems with event-triggered communication and communication delay between the event generator and the controller, where the impulsive control instants are produced by the resilient ETM rather than prescribed. Furthermore, a resilient sampled-data-based ETM and an event-based controller consisting of hybrid state feedback and impulsive controllers are developed. Under the proposed ETMs and controllers, some sufficient yet efficient criteria are derived to guarantee the master–slave synchronization of NNs. The influence of the attack parameters and triggering parameters on the synchronization performance is also discussed. Finally, two numerical examples and an application in image encryption and decryption based on the master–slave chaotic systems are given to demonstrate the effectiveness of the theoretical results.
Improvement of the spatial resolution of MODIS coastal waters thermal mapping

Thermal mapping is an highly relevant tool for the assessment of the quality of coastal waters. Remote sensing is an useful technique for monitoring large surfaces in near real time, nevertheless, spatial resolution represents an important limiting factor. In this work it the spatial improvement, from 1km to 250m, of MODIS thermal imagery on coastal water obtained with the SWTI (SharpeningWater Thermal Imagery) is shown. This algorithm is applied, for the first time, to MODIS images acquired on the lagoon of Venice and on the delta of the Po River. The performances of SWTI are evaluated taking as a reference a couple of ASTER images acquired simultaneously to the MODIS images and on the same areas. Moreover, the water temperatures obtained with a simple bilinear interpolation of the MODIS images is also considered. Several statistical parameters, as bias and root mean square difference, are used to quantify the the difference between ASTER and MODIS/SWTI water temperatures along coastlines. In all the the cases these differences are lower than 1K.
CSyn-fp: Standard Cell Synthesis of Advanced Nodes With Simultaneous Transistor Folding and Placement

The three major tasks in standard cell layout synthesis are transistor folding, transistor placement, and in-cell routing, which are tightly interrelated, but generally performed one at a time to reduce the extremely high complexity of design space. In this article, we propose an integrated approach to the two problems of transistor folding and placement. Precisely, we propose an optimal algorithm of search tree-based design space exploration, devising a set of effective speeding up techniques as well as dynamic programming-based fast cost computation. Our algorithm also incorporates the minimum oxide diffusion (OD) jog constraint, which closely relies on both of transistor folding and placement. To our knowledge, this is the first work that tries to simultaneously solve the two problems. In addition, to make an effective cell layout synthesis flow down to in-cell routing, we provided a fast in-cell routability estimation metric to be used in transistor placement and a method to explore cell layouts by varying the cell size constraint. Through experiments with the transistor netlists and design rules in the ASAP 7-nm library, it is shown that our proposed method is able to synthesize fully routable cell layouts of minimal size within very fast time for each netlist, outperforming the cell layout quality in the ASAP 7-nm library, which otherwise, may take several hours or days to manually complete layouts of the quality level comparable to ours.